{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Programming for Data Analysis Project 2019."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Table of Contents\n",
    "1. [Introduction](#overview)  \n",
    "    - [Objectives of the project](#objectives)\n",
    "    - [About this notebook and technologies used](#notebook)  \n",
    "    - [Goal of the project](#goal)  \n",
    "    - [About data simulation](#data-simulation)  \n",
    "    \n",
    "2. [Investigate the types of variables involved, their likely distributions, and their relationships with each other](#investigate)\n",
    "    - [Import Python libraries and options](#load-libraries)\n",
    "    - [Load real-world dataset into python](#real-world-dataset)\n",
    "    - [Prepare the dataset for analysis](#prepare)\n",
    "    - [The distributions of the data](#distributions)\n",
    "    - [Relationships between the variables](#relationships)\n",
    "        \n",
    "3. [Synthesise/simulate a data set as closely matching their properties as possible.](#synthesis)\n",
    "\n",
    "4. [Conclusion](#conclusion)\n",
    "\n",
    "5. [References](#references)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"overview\"></a>\n",
    "# 1. Introduction and Project Overview:\n",
    "\n",
    "This notebook contains the body of the work for my submission for the Programming in Data Analysis Project 2019 as part of the Higher Diploma in Data Analytics at GMIT. \n",
    "\n",
    "<a id=\"objectives\"></a>\n",
    "##  Objectives of the Project:\n",
    "The problem statement from the Programming for Data Analysis Project 2019 instructions [1] is as follows:\n",
    "\n",
    "For this project you must create a data set by simulating a real-world phenomenon of your choosing. You may pick any phenomenon you wish – you might pick one that is of interest to you in your personal or professional life. Then, rather than collect data related to the phenomenon, you should model and synthesise such data using Python. We suggest you use the numpy.random package for this purpose.\n",
    "Specifically, in this project you should:\n",
    "- Choose a real-world phenomenon that can be measured and for which you could collect at least one-hundred data points across at least four different variables.\n",
    "- Investigate the types of variables involved, their likely distributions, and their relationships with each other.\n",
    "- Synthesise/simulate a data set as closely matching their properties as possible.\n",
    "- Detail your research and implement the simulation in a Jupyter notebook – the data set itself can simply be displayed in an output cell within the notebook.\n",
    "Note that this project is about simulation – you must synthesise a data set. Some students may already have some real-world data sets in their own files. It is okay to base your synthesised data set on these should you wish (please reference it if you do), but the main task in this project is to create a synthesised data set. \n",
    "\n",
    "The pdf document is included in this repository for reference.\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"notebook\"></a>\n",
    "## About this notebook and python libraries used.\n",
    "\n",
    "This project was mainly developed using the python [2] and the following packages:\n",
    "- Seaborn [3] is a Python data visualization library for making attractive and informative statistical graphics in Python.\n",
    "- Pandas [4] provides data analysis tools and is designed for working with tabular data that contains an ordered collection of columns where each column can have a different value type. \n",
    "- Numpy.random [5] is a subpackage of the `NumPy` package for working with random numbers. NumPy is one of the most important packages for numerical and scientific computing in Python.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"goal\"></a>\n",
    "## The goal of the project\n",
    "The end goal of this project is to simulate a real-world phenomenon across at least one hundred data points across at least 4 different variables. A dataset must be simulated or synthesised. The instructions note that it is ok to base the synthesised dataset on an actual real-world dataset but the main task is to  create a synthesised data set.\n",
    "\n",
    "\n",
    "### 1. Choose a real-world phenomenon that can be measured and for which you could collect at least one-hundred data points across at least four different variables.\n",
    "The real-world phenomenon I have chosen is the World Happiness Score, in particular the main determinants of happiness at country levels across the world as reported in the World Happiness Report [6].\n",
    "\n",
    "The variables on which the national and international happiness scores are calculated are very real and quantifiable. These include socio-economic indicators such as Gross Domestic Product (GDP), life expectancy as well as some life evaluation questions regarding freedom, perception of corruption, family or social support.\n",
    "Differences in social support, incomes and healthy life expectancy are the three most important factors in determining the overall happiness score according to the World Happiness Reports.\n",
    "\n",
    "The aim of the World Happiness report is to see what countries or regions rank the highest in overall happiness and each of the six factors contributing to happiness. Over the years the reports looked at how country ranks and scores changed and whether any country experienced a significant increase or decrease in happiness.\n",
    "\n",
    "The researchers studied how 6 different factors contribute to the happiness scores and the extent of each effect. \n",
    "These are economic production, social support, life expectancy, freedom, absence of corruption, and generosity. They looked at how these factors contribute to making life evaluations higher in each country than they are in Dystopia, a hypothetical country that has values equal to the world’s lowest national averages for each of the six factors. \n",
    "While these factors have no impact on the total score reported for each country, they were analysed to explain why some countries rank higher than others.\n",
    "These factors describe the extent to which these factors contribute in evaluating the happiness in each country.\n",
    "\n",
    "### 2. Investigate the types of variables involved, their likely distributions, and their relationships with each other.\n",
    "\n",
    "First I will investigate the variables in the datasets used by the World Happiness Reports. I will study their distributions by looking at descriptive statistics and plots such as histograms and boxplots. I will explore relationships that may exist between the variables using visualisations such as scatterplot, pairplots etc and statistics such as correlation and covariance statistics.\n",
    "\n",
    "With this information in mind, I will try to create a simulated dataset that is as close to the real world phenomenon as possible. \n",
    "\n",
    "### 3. Synthesise/simulate a data set as closely matching their properties as possible.\n",
    "\n",
    "Having studied the distributions of the real dataset by looking at statistics and plot I will use Python to simulate the data, focusing on using the `numpy.random` package as much as possible but using other Python libraries as may be required. I will look at how simulation is performed and what must be considered when simulating a dataset such as this one. I will look at how each of the variables are distributed and how they could be simulated. I will also consider the relationships between the variables. While it might be relatively straightforward to simulate a single variable, modelling the real-world correlations between the variables will be challenging.\n",
    "As there is much inequality in the world, this will be reflected in the distribution of the variables that model factors such as income and life expectancy. Therefore I will need to look at regional variations and how this would affect the simulation of data. The distributions are likely to vary between regions, particularly between the lesser developed countries and the countries of the more developed world.\n",
    "\n",
    "### 4. Detail your research and implement the simulation in a Jupyter notebook – the data set itself can simply be displayed in an output cell within the notebook.\n",
    "\n",
    "All the analysis will be documented in this notebook which means that the document is quite lengthy and might take some time to load. The first section of code involves reading in the real world dataset and getting it into a state where it is ready to be analysed. The data is available in excel and csv files which is left unchanged. As the files containing the 2018 did not include the geographic regions of the countries studied, I had to add these to the data by merging with an earlier dataset. Some other manipulation such as renaming columns, dropping unnecessary columns, adding region codes etc is documented below. The end result of this is written to a csv files to the data folder in this repository."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "<a id=\"data-simulation\"></a>\n",
    "## About data simulation.\n",
    "The goad of this project is to simulate a dataset. Simulating data is used for a number of reasons.  Monte carlo simulation are used to simulate real world problems using repeated random sampling while simulated data is \n",
    "very useful for learning and demonstration purposes. Data can be simulated before the real world data is collected to help identify the type of tests and programs that need to be run.\n",
    "Collecting data requires resources of time and money whereas data can be simulated easily using computer programs.\n",
    "\n",
    "Statistical analysis can be performed on the simulated data in advance of collecting the real data this process can be repeated as many times as needed. By studying simulated data you can become more familiar with the different kinds of data distributions and be in a better position to make decisions about the data and what to do with it such as how to measure it and how much is required. Simulations produce multiple sample outcomes. Experiments can be run by modifying inputs and seeing how this changes the output. The process of generating a random sample can be repeated many many times which will allow you to see how often you would expect to get the outcomes you get. Repeating the process gives multiple outcomes which can then be averaged across all simulations.\n",
    "\n",
    "When data is collected, it is often only a small sample of data from the overall population of interest. The researchers of the World Happiness Reports did not collect all the data about the variables of interest.  The typical sample size used per country was 1000 people while some countries had more than one survey per year and others had less.\n",
    "A sample is a subset of numbers from a distribution and the bigger the sample size the more it resembles the distribution from which it is drawn. Depending on the distribution the data is drawn from, some numbers will occur more often than others. Sample statistics are descriptions of the data that can be calculated from the sample dataset and then be used to make inferrences about the population. The population parameters are of most interest. These are the characteristics of the actual population from which a sample dataset is taken.  Samples are used to estimate the parameters of the population. The sample mean is the mean of the numbers in the sample while the population mean is the mean of the entire population but it is not always possible to study the entire population directly. The law of large numbers refers to how as a sample size increases, the sample mean gets closer to the true population mean. Under the law of large numbers the more data that is collected, the closer the sample statistics will get to the actual true population parameters.\n",
    "\n",
    "The sampling distribution of the sample means is when you collect many samples from the population and calculate the sample means on each sample. If you know the type of distribution you could sample some data from this distribution, calculate the means or any other sample statistic of the samples and plot them using a histogram to show the distribution of the sample statistic. The sampling distributions can tell you what to expect from your data. \n",
    "\n",
    "Simulation can be used to find out what the sample looks like if it comes from that particular distribution. This information can be used to make inferences about whether the sample came from particular distribution or not.\n",
    "The sampling distribution of a statistic varies as a function of sample size. Small sample taken from the distribution will probably have sample statistics such as sample means that vary quite a bit from sample to sample and therefore the sampling distribution will be quite wide. Larger samples are more likely to have similar statistics and a narrower sampling distribution.  \n",
    "\n",
    "As the size of the samples increases, the mean of the sampling distribution approaches the mean of the population. The sampling distribution is itself a distribution and has some variance.\n",
    "The standard deviation of the sampling distribution is known as the standard error. As the sample size increases, the standard error of the sample mean decreases. According to the central limit theorem, as the sample size increases the sampling distribution of the mean begins to look more like a normal distribution, no matter what the the shape of the population distribution is.\n",
    "\n",
    "Large experiments are considered more reliable than smaller ones.  If you take a big enough sample, the sample mean gives a very good estimate of the population mean. \n",
    "\n",
    "When simulating a random variable, you first need to define the possible outcomes of the random variable. To do this you can use the sample statistics from the sample dataset. Using simulated data therefore allows you to identify coding errors as you know what the outcomes should be.\n",
    "\n",
    "Resampling methods are another way of simulating data and involve resampling with replacements. Bootstrap resampling is the most common method.\n",
    "\n",
    "For this section I referred to an online book called Answering Questions with Data (Textbook): Introductory Statistics for Psychology Students by Matthew J C Crump [6].\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "<a id=\"investigate\"></a>\n",
    "# 2. Investigate the types of variables involved, their likely distributions, and their relationships with each other\n",
    "Having identified a real-world phenomenon to simulate, the next step is to investigate the types of variables involved, their likely distributions, and their relationships with each other. To do so I need data. \n",
    "\n",
    "#### Available Data and research\n",
    "\n",
    "The World Happines Report is produced by the United Nations Sustainable Development Solutions Network in partnership with the Ernesto Illy Foundation.\n",
    "The first World Happiness Report was published in 2012, the latest in 2019. The World Happiness Report is a landmark survey of the state of global happiness that ranks 156 countries by how happy their citizens perceive themselves to be.\n",
    "Each year the report has focused in on a different aspect of the report such as how the new science of happiness explains personal and national variations in happiness and how well-being is a critical component of how the world measures its economic and social development. Over the years it looked at changes in happiness levels in the countries studies and the underlying reasons, the measurement and consequences of inequality in the distribution of well-being among countries and regions.\n",
    "The 2017 report emphasized the importance of the social foundations of happiness while the 2018 report focused on migration. The latest World Happiness Report (2019) focused on happiness and the community and happiness has evolved over the past dozen years. It focused on the technologies, social norms, conflicts and government policies that have driven those changes.\n",
    "\n",
    "Increasingly, happiness is considered to be the proper measure of social progress and the goal of public policy.\n",
    "Happiness indicators are being used by governments, organisations and civil society to help with decision making. Experts believe that measurements of well-being can be used to assess the progress of nations. The World Happiness reports review the state of happiness in the world and show how the new science of happiness explains personal and national variations in happiness.\n",
    "\n",
    "The underlying source of the happiness scores in the World Happiness Report is the Gallup World Poll - a set of nationally representative undertaken in many countries across the world. The main life evaluation question asked in the poll is based on the Cantril ladder. Respondents are asked to think of a ladder, with the best possible life for them being a 10, and the worst possible life being a 0. They are then asked to rate their own current lives on that 0 to 10 scale. The rankings are from nationally representative samples, for the years 2016-2018. The overall happiness scores and ranks were calculated after a study of the underlying variables.\n",
    "\n",
    "Happiness and life satisfaction are considered as central research areas in social sciences.\n",
    "\n",
    "The variables on which the national and international happiness scores are calculated are very real and quantifiable. These include socio-economic indicators such as gdp, life expectancy as well as other life evaluation questions regarding freedom, perception of corruption, family or social support.\n",
    "Differences in social support, incomes and healthy life expectancy are the three most important factors in determining the overall happiness score according to the World Happiness Reports.\n",
    "\n",
    ">The variables used reflect what has been broadly found in the research literature to be important in explaining national-level differences in life evaluations. Some important variables, such as unemployment or inequality, do not appear because comparable international data are not yet available for the full sample of countries. The variables are intended to illustrate important lines of correlation rather than to reflect clean causal estimates, since some of the data are drawn from the same survey sources, some are correlated with each other (or with other important factors for which we do not have measures), and in several instances there are likely to be two-way relations between life evaluations and the chosen variables (for example, healthy people are overall happier, but as Chapter 4 in the World Happiness Report 2013 demonstrated, happier people are overall healthier). [](https://worldhappiness.report/faq/)\n",
    "\n",
    "\n",
    "\n",
    "The World Happiness Reports and data are available from the [Worldhappiness](https://worldhappiness.report) website.\n",
    "The latest report is [The World Happiness Report 2019](https://worldhappiness.report/ed/2019/)[7].\n",
    "The World Happiness Report is available for each year from 2012 to 2019 containing data for the prior year. For each year there is an excel file with several sheets including one sheet with annual data for different variables over a number of years and other sheets containing the data for the calculation of the World Happiness score for that year. \n",
    "Some of the data such as Log GDP per capita are forecast from the previous years where the data was not yet available at the time of the report.\n",
    "[Kaggle](https://www.kaggle.com) also hosts part of the [World Happiness datasets](https://www.kaggle.com/unsdsn/world-happiness#2016.csv) for the reports from 2015 to 2019.\n",
    "\n",
    "The full datasets are available online in excel format by following a link under the Downloads section on the [World Happiness Report](https://worldhappiness.report)[8] website to  <https://s3.amazonaws.com/happiness-report/2019/Chapter2OnlineData.xls>.\n",
    "\n",
    "[Kaggle Datasets](https://www.kaggle.com/unsdsn/world-happiness#2016.csv)[9] also has some datasets in csv format.\n",
    "\n",
    "I have downloaded both the latest csv and excel files to the `/data` folder in this repository. The data from the excel file is the most comprehensive as it includes data for several years from 2008 to 2019. There are two main excel sheets in the 2019 data. The sheet named `Figure2.6` contains the main variables used as predictors of the happiness score in the 2019 World Happiness Report. The data is contained in columns A to K while the remaining columns contain actual tables and figures used in the World Happiness annual report. A second sheet called `Table2.1` contains all the available data from 2008 up to 2019 and provides more detail.\n",
    "\n",
    "The happiness scores and the world happiness ranks are recorded in Figure 2.6 of the 2019 report with a breakdown of how much each individual factor impacts or explains the happiness of each country studied rather than actual measurements of the variables. The actual variables themselves are in Table 2.1 of the World Happiness Report. There are some other variables included in the report which have a smaller effect on the happiness scores.\n",
    "\n",
    "In this project I will focus on the main determinants of the Happiness scores as reported in the World Happiness reports. These are income, life expectancy, social support, freedom, generosity and corruption. The happiness scores and the world happiness ranks are recorded in Figure 2.6 of the 2019 report with a breakdown of how much each individual factor impacts or explains the happiness of each country studied rather than actual measurements of the variables. The columns in `df6` dataframe correspond to the columns in Figure 2.6 data from the World Happiness Report of 2019. The values in the columns describe the extent to which the 6 factors contribute in evaluating the happiness in each country. \n",
    "\n",
    "The actual values of these variables are in Table 2.1 data of the World Happiness Report. There are some other variables included in the report which have a smaller effect on the happiness scores.\n",
    "\n",
    "- Life Ladder\n",
    "- Log GDP per capita / Income\n",
    "- Social Support / Family\n",
    "- Healthy Life Expectancy at birth\n",
    "- Freedom to make life choices\n",
    "- Generosity\n",
    "- Perceptions of Corruption"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Life Ladder\n",
    "The variable named Life Ladder is a Happiness score or subjective well-being from the Gallup World Poll\n",
    "It is the national average response to the question of life evaluations. The English wording of the question is “Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time?” This measure is also referred to as Cantril life ladder. [10](Statistical Appendix 1 for Chapter 2 of World Happiness Report 2019, by John F. Helliwell, Haifang Huang and Shun Wang)\n",
    "The values in the dataset are real numbers representing national averages. They could vary between 0 and 10 but in reality the range is much smaller in between these numbers.\n",
    "\n",
    "- Log GDP per capita:\n",
    "\n",
    ">GDP per capita is a measure of a country's economic output that accounts for its number of people. It divides the country's gross domestic product by its total population. That makes it a good measurement of a country's standard of living. It tells you how prosperous a country feels to each of its citizens.[11](https://www.thebalance.com/gdp-per-capita-formula-u-s-compared-to-highest-and-lowest-3305848)\n",
    "\n",
    "\n",
    "Gross Domestic Product per capita is an approximation of the value of goods produced per person in the country, equal to the country's GDP divided by the total number of people in the country. It is usually expressed in local currency or a standard unit of currency in international markets such as the US dollar. GDP per capita is an important indicator of economic performance and can be used for cross-country comparisons of average living standards. To compare GDP per capita between countries, purchasing power parity (PPP) is used to create parity between different economies by comparing the cost of a basket of similar goods.\n",
    "\n",
    "GDP per capita can be used to compare the prosperity of countries with different population sizes.\n",
    "\n",
    "There are very large differences in income per capita across the world.\n",
    "As average income increases over time the distribution of gdp per capita gets wider. Therefore the log of income per capita is taken when the growth is approximately proportional. When $x (t)$ grows at a proportional rate, $log x (t)$ grows linearly. [12][Introduction to Economic Growth Lecture MIT](https://economics.mit.edu/files/1489).\n",
    "\n",
    "Per capita GDP is a unimodal but skewed distribution. The log of GDP per capita = log (Total GDP per capita/ population) is a more symmetrical distribution. [13][Sustainable Development Econometrics Lecture](http://www.columbia.edu/~so33/SusDev/Lecture_1.pdf)\n",
    "\n",
    "The natural log is often used in economics as it can make it easier to see the trends in the data and the log of the values can fit a normal distribution.\n",
    "\n",
    "- Healthy Life Expectancy at Birth.\n",
    "\n",
    "Healthy life expectancies at birth are based on the data extracted from the World Health Organization’s (WHO) Global Health Observatory data repository.\n",
    "\n",
    "Healthy life expectancy (HALE) is a form of health expectancy that applies disability weights to health states to compute the equivalent number of years of good health that a newborn can expect.\n",
    "The indicator Healthy Life Years (HLY) at birth measures the number of years that a person at birth is still expected to live in a healthy condition. HLY is a health expectancy indicator which combines information on mortality and morbidity. [14][Eurostat](https://ec.europa.eu/eurostat/web/products-datasets/-/tps00150).\n",
    "\n",
    ">Overall, global HALE at birth in 2015 for males and females combined was 63.1 years, 8.3 years lower than total life expectancy at birth. In other words, poor health resulted in a loss of nearly 8 years of healthy life, on average globally. Global HALE at birth for females was only 3 years greater than that for males. In comparison, female life expectancy at birth was almost 5 years higher than that for males.\n",
    "HALE at birth ranged from a low of 51.1 years for African males to 70.5 years for females in the WHO European Region. The equivalent “lost” healthy years (LHE = total life expectancy minus HALE) ranged from 13% of total life expectancy at birth in the WHO African Region to 10% the WHO Western Pacific Region. [15][www.who.int](https://www.who.int/gho/mortality_burden_disease/life_tables/hale_text/en/).\n",
    "\n",
    "\n",
    "- Social Support\n",
    "is the national average of the binary responses (either 0 or 1) to the GWP question “If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?”. [10](Statistical Appendix 1 for Chapter 2 of World Happiness Report 2019, by John F. Helliwell, Haifang Huang and Shun Wang)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"load-libraries\"></a>\n",
    "### Load Python Libraries:\n",
    "Here I load the python libraries and set up some formatting for the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NumPy version 1.16.2 pandas version  0.24.2 seaborn version 0.9.0\n"
     ]
    }
   ],
   "source": [
    "# import python libraries using common alias names\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "# display matplotlib plots inline\n",
    "%matplotlib inline\n",
    "\n",
    "# check what version of packages are installed.\n",
    "print(\"NumPy version\",np.__version__, \"pandas version \",pd.__version__, \"seaborn version\",sns.__version__  )  # '1.16.2'\n",
    "\n",
    "# set print options with floating point precision if 4, summarise long arrays using threshold of 5, suppress small results\n",
    "np.set_printoptions(precision=4, threshold=5, suppress=True)  # set floating point precision to 4\n",
    " # set options to display max number of rows\n",
    "pd.options.display.max_rows=8 \n",
    "# I did change the max number of rows to display when developing the project to see more rows as necessary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!ls data # see what files are in the data folder of this repository"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"prepare\"></a>\n",
    "### Prepare the dataset for analysis\n",
    "Here I load some real-world dataset for the World Happiness Report into python. The data is available in the `data` folder of this repository which is what I use for this project. The dataset can also be read in directly from the URL. \n",
    "Data for other years is also available by following the links from the [World Happiness Report](https://worldhappiness.report) website."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "# read the data directly from the url or alternatively from the data folder in this repository\n",
    "url=\"https://s3.amazonaws.com/happiness-report/2019/Chapter2OnlineData.xls\"\n",
    "# The entire data from Table2.1 sheet\n",
    "WH = pd.read_excel(url, sheet_name='Table2.1')\n",
    "# The data from the sheet Figure2.6, columns A to K\n",
    "whr18 = pd.read_excel(url,sheet_name='Figure2.6', usecols=\"A:K\")\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of the data from Table2.1 is: \n",
      " (1704, 9)\n",
      "The shape of the data from Figure 2.6 is: \n",
      " (156, 8)\n"
     ]
    }
   ],
   "source": [
    "# import the data from the data folder in this repository\n",
    "Table2_1 = pd.read_excel('data/Chapter2OnlineData2019.xls', sheet_name='Table2.1', usecols=\"A:I\")\n",
    "# The data from the sheet Figure2.6, selected columns between A and K\n",
    "Fig2_6 = pd.read_excel('data/Chapter2OnlineData2019.xls',sheet_name='Figure2.6', usecols=\"A:B, F:K\")\n",
    "# read in only selected columns from Figure2.6\n",
    "Fig2_6_x = pd.read_excel('data/Chapter2OnlineData2019.xls',sheet_name='Figure2.6', usecols=\"A:B\")\n",
    "# the 2019 data, same values as Kaggle data except not including the rank but including the whiskers or intervals\n",
    "print(\"The shape of the data from Table2.1 is: \\n\",Table2_1.shape)\n",
    "print(\"The shape of the data from Figure 2.6 is: \\n\",Fig2_6.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I have read in the data from the excel sheet by selecting certain columns. There are 1704 rows in the excel sheet `Table 2.1` and 156 rows in sheet `Figure2.6`.\n",
    "Table 2.1 contains the data on which the happiness scores in Figure 2.6 of the World Happiness Report for 2019 are calculated. When the Table2.1 data is filtered for 2018 data there are only 136 rows. The report does note that where values were not yet available at the time, values were interpolated based on previous years. \n",
    "\n",
    "Here I am going to merge the two spreadsheets and just filter for the columns I need. I then need to cleanup the dataframe names throoughout this project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Table2_1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# look at columnes for Figure 2.6 data\n",
    "#Fig2_6.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make the dataframe easier to work and also to merge the two dataframes I will rename the columns. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Country', 'Happiness score'], dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# only contains the country and happiness score for 2018\n",
    "Fig2_6_x.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename the columns\n",
    "Table2_1.rename(columns={'Country name':'Country', 'Life Ladder':'Life_Satisfaction','Log GDP per capita':'Log_GDP_per_cap',\n",
    "                         'Social support':'Social_Support', 'Healthy life expectancy at birth':'Life_Expectancy','Freedom to make life choices':'Freedom',\n",
    "                        'Perceptions of corruption':'Corruption_perceptions'}, inplace=True)\n",
    "# look at the columns\n",
    "#Table2_1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge the two dataframes that came from the two spreadsheets on the Country variable.\n",
    "merged= pd.merge(Fig2_6_x,Table2_1, on=\"Country\",how=\"right\")\n",
    "# as the figure 2.6 data is for 2018 only and I am only interested in the Happiness Score I will chnage the column name and drop all the other columsn from Figure 2.6\n",
    "merged =merged.rename(columns={'Happiness score':'Happiness_Score_2018'})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding Region information:\n",
    "\n",
    "The World Happiness Report report does note somewhere that for the world as a whole, the distribution of happiness is normally distributed but when the global population is split into ten geographic regions, the resulting distributions vary greatly in both shape and average values. \n",
    "\n",
    "Therefore I think it is important to look at the geographic regions when studying the properties of this dataset. The region data is not available in the data available from the World Happiness Report but it was included in the csv file for 2015 and 2016 on Kaggle in addition to the country. (For some reason the datasets for later years on Kaggle had a single `Country or region` variable that only contained the country). \n",
    "The following segment of code is used to add the geographic regions to the data files I am using for this project. First I had to rename the columns containing the country and then using pandas `merge` to join the dataframes based on the country names being equal to get the geographic regions into my dataset. This dataframe was then written to csv file. \n",
    "\n",
    "For merging dataframes I referred to the pandas documentation and a blogpost by Chris Albon,[pandas merge with a right join](https://chrisalbon.com/python/data_wrangling/pandas_join_merge_dataframe/)[16].\n",
    "A `Region` variable has been added to the data in order to look at the distributions across regions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t DataFrame merged\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Happiness_Score_2018</th>\n",
       "      <th>Year</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Corruption_perceptions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.4802</td>\n",
       "      <td>2006</td>\n",
       "      <td>7.473253</td>\n",
       "      <td>10.906543</td>\n",
       "      <td>0.951352</td>\n",
       "      <td>71.540001</td>\n",
       "      <td>0.918958</td>\n",
       "      <td>0.285015</td>\n",
       "      <td>0.407931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.4802</td>\n",
       "      <td>2009</td>\n",
       "      <td>7.524521</td>\n",
       "      <td>10.911548</td>\n",
       "      <td>0.938339</td>\n",
       "      <td>72.260002</td>\n",
       "      <td>0.891277</td>\n",
       "      <td>0.119585</td>\n",
       "      <td>0.342427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.4802</td>\n",
       "      <td>2012</td>\n",
       "      <td>7.776209</td>\n",
       "      <td>10.935776</td>\n",
       "      <td>0.946864</td>\n",
       "      <td>72.779999</td>\n",
       "      <td>0.945428</td>\n",
       "      <td>0.133088</td>\n",
       "      <td>0.323241</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country          Region  Happiness_Score_2018  Year  Life_Satisfaction  \\\n",
       "0  Switzerland  Western Europe                7.4802  2006           7.473253   \n",
       "1  Switzerland  Western Europe                7.4802  2009           7.524521   \n",
       "2  Switzerland  Western Europe                7.4802  2012           7.776209   \n",
       "\n",
       "   Log_GDP_per_cap  Social_Support  Life_Expectancy   Freedom  Generosity  \\\n",
       "0        10.906543        0.951352        71.540001  0.918958    0.285015   \n",
       "1        10.911548        0.938339        72.260002  0.891277    0.119585   \n",
       "2        10.935776        0.946864        72.779999  0.945428    0.133088   \n",
       "\n",
       "   Corruption_perceptions  \n",
       "0                0.407931  \n",
       "1                0.342427  \n",
       "2                0.323241  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read in the kaggle dataset for 2015 as this contains the Regions as well as the country names.\n",
    "k15 = pd.read_csv(\"data/2015.csv\")\n",
    "# extract the country and regions from the 2015 file:\n",
    "Regions = k15.loc[:,['Country','Region']]\n",
    "#Regions.shape # 158 rows\n",
    "# see how many unique regions and countries\n",
    "Regions.describe(include=\"object\")\n",
    "#merge the dataframes on country variable\n",
    "merged=pd.merge(Regions, merged,on='Country',how='right')\n",
    "#merged.describe()\n",
    "# There should now be two non-numeric variables in the dataset. Country name and Region\n",
    "#merged.describe(include=\"object\")\n",
    "# a peak at the dataset\n",
    "print(\"\\t DataFrame merged\")\n",
    "merged.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I now have a dataframe `merged` containing the data from `Table 2.1` in the World Happiness Report of 2019 with the geographic regions added as well as the 2018 Happiness Score from the `Figure 2.6` data. \n",
    "However some countries were missing a region value as these countries were not included in the 2015 dataset. In this case I looked up the geographic region and added them to the dataframe to replace the NaN values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write to csv\n",
    "merged.to_csv(\"data/merged.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a dataframe called df from the merged dataframe\n",
    "df=merged"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add the missing region values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find how many rows have missing values for Region\n",
    "df['Region'].isna().sum()\n",
    "# print the rows with missing Region valuesBelize\n",
    "df.loc[df.loc[:,'Region'].isna()]\n",
    "# update the value of Region for the following countries\n",
    "df.loc[df['Country']==\"Taiwan Province of China\",['Region']]=\"Southeastern Asia\"\n",
    "df.loc[df['Country']==\"Namibia\",['Region']]=\"Sub-Saharan Africa\"\n",
    "df.loc[df['Country']==\"Somalia\",['Region']]=\"Sub-Saharan Africa\"\n",
    "df.loc[df['Country']==\"Hong Kong S.A.R. of China\",['Region']]=\"Southeastern Asia\"\n",
    "df.loc[df['Country']==\"South Sudan\",['Region']]=\"Sub-Saharan Africa\"\n",
    "df.loc[df['Country']==\"Gambia\",['Region']]=\"Sub-Saharan Africa\"\n",
    "df.loc[df['Country']==\"Belize\",['Region']]=\"Latin America and Caribbean\"\n",
    "df.loc[df['Country']==\"Cuba\",['Region']]=\"Latin America and Caribbean\"\n",
    "df.loc[df['Country']==\"Guyana\",['Region']]=\"Latin America and Caribbean\"\n",
    "# checking to make sure all regions have values now\n",
    "df['Region'].isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I added in a region code but this is no longer of use. I will leave it in for now but will remove it later.\n",
    "To create the region code I looked at the proportion of the overall number of countries that are in each region and then created a new column with the region number. The numbers assigned are not ordered as such - I just started with 1 for the region with the greatest number of countries.\n",
    "To do this I will add a new column for the RegionCode that has the Region name to start and then [replace the string](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.replace.html?highlight=replace#pandas-series-str-replace) with the Region name in this new column with an integer from 1 to 10. (There is probably a better way of doing this - `where` did not work for me when there was 10 options to choose from).\n",
    "First I look at how the countries are split between geographic regions and then assign a number from 1 to 10 for the region with the highest number of countries although there is no order as such."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sub-Saharan Africa             0.221244\n",
       "Central and Eastern Europe     0.200117\n",
       "Latin America and Caribbean    0.151995\n",
       "Western Europe                 0.135563\n",
       "                                 ...   \n",
       "Southern Asia                  0.045775\n",
       "Eastern Asia                   0.029343\n",
       "North America                  0.015258\n",
       "Australia and New Zealand      0.014085\n",
       "Name: Region, Length: 10, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# just looking again at the proportion of countries over the 10 regions\n",
    "df.Region.value_counts()/len(df.Region)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add a new column called RegionCode with the Region \n",
    "df['RegionCode']=df['Region']\n",
    "df.head()\n",
    "# replace the new regionCode with a number for each region as follows:\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Sub-Saharan Africa\",1)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Central and Eastern Europe\",2)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Western Europe\",3)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Latin America and Caribbean\",4)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Middle East and Northern Africa\",5)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Southeastern Asia\",6)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Southern Asia\",7)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Eastern Asia\",8)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"Australia and New Zealand\",9)\n",
    "df['RegionCode']=df[\"RegionCode\"].replace(\"North America\",10)\n",
    "\n",
    "# convert to integer - might use this later for correlations.\n",
    "#df[\"RegionCode\"] = pd.to_numeric(dfh[\"RegionCode\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Write the datasets with the Regions added to csv files:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write the dataframes to a csv files:\n",
    "df.to_csv(\"data/Table2_1.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read in the prepared datasets for analysis:\n",
    "\n",
    "Note that `Table 2.1` data includes some rows where there are some missing values as there were some countries added to the World Happiness Report in recent years for which the data was not available.\n",
    "Also some of the data in `Table 2.1` was not available for 2018 at the time of the 2019 report being published. Some imputation was used or some interpolation from previous years values.\n",
    "[Statistical Appendix 1 for Chapter 2](https://s3.amazonaws.com/happiness-report/2019/WHR19_Ch2A_Appendix1.pdf)[10] of the World Happiness Report for 2019 outlines how imputation is used for missing values when trying to decompose a country's average ladder score into components explained by the 6  hypothesized underlying determinants (GDP per person, healthy life expectancy, social support, perceived freedom to make life choice, generosity and perception of corruption).\n",
    "\n",
    "All the data I am using to figure out the distribution of variables have now been prepared\n",
    "- df6: This contains the data from Figure 2.6 of the World Happiness Report with region values added\n",
    "- df:  This contains the data from Table 2.1 of the World Happiness Report with region values added\n",
    "- df18: This contains the data from Table 2.1 filtered for 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " \t The dataframe df18 containing the Table 2.1 data from the 2019 World Happiness Report.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Happiness_Score_2018</th>\n",
       "      <th>Year</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Corruption_perceptions</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.4802</td>\n",
       "      <td>2018</td>\n",
       "      <td>7.508587</td>\n",
       "      <td>10.975945</td>\n",
       "      <td>0.930291</td>\n",
       "      <td>74.099998</td>\n",
       "      <td>0.926415</td>\n",
       "      <td>0.096369</td>\n",
       "      <td>0.301260</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.6001</td>\n",
       "      <td>2018</td>\n",
       "      <td>7.648786</td>\n",
       "      <td>10.755594</td>\n",
       "      <td>0.958219</td>\n",
       "      <td>72.400002</td>\n",
       "      <td>0.935438</td>\n",
       "      <td>0.015593</td>\n",
       "      <td>0.150607</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Country          Region  Happiness_Score_2018  Year  \\\n",
       "7   Switzerland  Western Europe                7.4802  2018   \n",
       "26      Denmark  Western Europe                7.6001  2018   \n",
       "\n",
       "    Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy  \\\n",
       "7            7.508587        10.975945        0.930291        74.099998   \n",
       "26           7.648786        10.755594        0.958219        72.400002   \n",
       "\n",
       "     Freedom  Generosity  Corruption_perceptions  RegionCode  \n",
       "7   0.926415    0.096369                0.301260           3  \n",
       "26  0.935438    0.015593                0.150607           3  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read in the Table 2.1 data back in, set the index_col to be the first column\n",
    "df = pd.read_csv(\"data/Table2_1.csv\", index_col=0)\n",
    "# look at top and bottom rows to see it all looks ok\n",
    "df.tail(2)\n",
    "df.head(2)\n",
    "# Create a dataframe with 2018 data from the Table 2.1 of the World Happiness Report 2019:\n",
    "df18=df.loc[df.loc[:,'Year']==2018]\n",
    "print(\"\\n \\t The dataframe df18 containing the Table 2.1 data from the 2019 World Happiness Report.\\n\")\n",
    "df18.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1704, 12) (136, 12)\n"
     ]
    }
   ],
   "source": [
    "# see the dimensions of the dataframes\n",
    "print(df.shape,df18.shape) #  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Subset the datasets to work with variables of interest.\n",
    "Here I first create a smaller dataframe from df18 called dfh containing the variables of interest. This is just to make the dataframes easier to work with and print. The initial work on this project was done looking only at 2018 data. However there are few missing values that were not available at the time. Therefore I create another dataframe containing only the relevent variables for each year from 2012 to 2018.\n",
    "\n",
    "Below I subset the larger file (from Table 2.1 data in World Happiness Report 2019 which contains data for several years prior to 2018) to include only the main variables of interest for this project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.508587</td>\n",
       "      <td>10.975945</td>\n",
       "      <td>0.930291</td>\n",
       "      <td>74.099998</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.648786</td>\n",
       "      <td>10.755594</td>\n",
       "      <td>0.958219</td>\n",
       "      <td>72.400002</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Norway</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.444262</td>\n",
       "      <td>11.085626</td>\n",
       "      <td>0.965962</td>\n",
       "      <td>73.199997</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Canada</td>\n",
       "      <td>North America</td>\n",
       "      <td>7.175497</td>\n",
       "      <td>10.701248</td>\n",
       "      <td>0.922719</td>\n",
       "      <td>73.599998</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Finland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.858107</td>\n",
       "      <td>10.636060</td>\n",
       "      <td>0.962155</td>\n",
       "      <td>71.900002</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Country          Region  Life_Satisfaction  Log_GDP_per_cap  \\\n",
       "7   Switzerland  Western Europe           7.508587        10.975945   \n",
       "26      Denmark  Western Europe           7.648786        10.755594   \n",
       "34       Norway  Western Europe           7.444262        11.085626   \n",
       "47       Canada   North America           7.175497        10.701248   \n",
       "58      Finland  Western Europe           7.858107        10.636060   \n",
       "\n",
       "    Social_Support  Life_Expectancy  RegionCode  \n",
       "7         0.930291        74.099998           3  \n",
       "26        0.958219        72.400002           3  \n",
       "34        0.965962        73.199997           3  \n",
       "47        0.922719        73.599998          10  \n",
       "58        0.962155        71.900002           3  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop year column as this only contains 2018 anyway.\n",
    "## create a data frame dfh that contains only a subset of the columns from df\n",
    "df18 = df18.loc[:,['Country','Region','Life_Satisfaction','Log_GDP_per_cap','Social_Support','Life_Expectancy', 'RegionCode']]\n",
    "df18.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t DataFrame called df_years \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.776209</td>\n",
       "      <td>10.935776</td>\n",
       "      <td>0.946864</td>\n",
       "      <td>72.779999</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.492804</td>\n",
       "      <td>10.954624</td>\n",
       "      <td>0.958796</td>\n",
       "      <td>73.059998</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.572137</td>\n",
       "      <td>10.955430</td>\n",
       "      <td>0.938334</td>\n",
       "      <td>73.199997</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.458520</td>\n",
       "      <td>10.958175</td>\n",
       "      <td>0.927628</td>\n",
       "      <td>73.500000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.473593</td>\n",
       "      <td>10.957976</td>\n",
       "      <td>0.949661</td>\n",
       "      <td>73.800003</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year      Country          Region  Life_Satisfaction  Log_GDP_per_cap  \\\n",
       "2  2012  Switzerland  Western Europe           7.776209        10.935776   \n",
       "3  2014  Switzerland  Western Europe           7.492804        10.954624   \n",
       "4  2015  Switzerland  Western Europe           7.572137        10.955430   \n",
       "5  2016  Switzerland  Western Europe           7.458520        10.958175   \n",
       "6  2017  Switzerland  Western Europe           7.473593        10.957976   \n",
       "\n",
       "   Social_Support  Life_Expectancy  RegionCode  \n",
       "2        0.946864        72.779999           3  \n",
       "3        0.958796        73.059998           3  \n",
       "4        0.938334        73.199997           3  \n",
       "5        0.927628        73.500000           3  \n",
       "6        0.949661        73.800003           3  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using .loc to create a dataframe containing only the required columns for this project\n",
    "dfx= df.loc[:,['Year','Country','Region','Life_Satisfaction','Log_GDP_per_cap','Social_Support','Life_Expectancy', 'RegionCode']]\n",
    "# using .loc to subset only the rows contains years from 2011 to 2018.\n",
    "df_years = dfx.loc[dfx.loc[:,'Year'].isin([2018,2017,2016,2015,2014,2013,2012,2011])]\n",
    "# look at the columns\n",
    "df_years.columns\n",
    "print(\"\\t DataFrame called df_years \\n\")\n",
    "df_years.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Missing values\n",
    "The dataframe called`df_years` contains all the data from Table 2.1 of the 2019 World Happiness Report data for the years between 2011 and 2018. There are some missing values for some columns. I will write this to csv. To see only the rows containing missing data I use `isnull().any(axis=1)` as per [stackoverflow](https://stackoverflow.com/a/30447205)[17]. There are not many missing values overall. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# to see how many observations for each year\n",
    "#df_years.groupby('Year').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.776209</td>\n",
       "      <td>10.935776</td>\n",
       "      <td>0.946864</td>\n",
       "      <td>72.779999</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.492804</td>\n",
       "      <td>10.954624</td>\n",
       "      <td>0.958796</td>\n",
       "      <td>73.059998</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.572137</td>\n",
       "      <td>10.955430</td>\n",
       "      <td>0.938334</td>\n",
       "      <td>73.199997</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.458520</td>\n",
       "      <td>10.958175</td>\n",
       "      <td>0.927628</td>\n",
       "      <td>73.500000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.473593</td>\n",
       "      <td>10.957976</td>\n",
       "      <td>0.949661</td>\n",
       "      <td>73.800003</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year      Country          Region  Life_Satisfaction  Log_GDP_per_cap  \\\n",
       "2  2012  Switzerland  Western Europe           7.776209        10.935776   \n",
       "3  2014  Switzerland  Western Europe           7.492804        10.954624   \n",
       "4  2015  Switzerland  Western Europe           7.572137        10.955430   \n",
       "5  2016  Switzerland  Western Europe           7.458520        10.958175   \n",
       "6  2017  Switzerland  Western Europe           7.473593        10.957976   \n",
       "\n",
       "   Social_Support  Life_Expectancy  RegionCode  \n",
       "2        0.946864        72.779999           3  \n",
       "3        0.958796        73.059998           3  \n",
       "4        0.938334        73.199997           3  \n",
       "5        0.927628        73.500000           3  \n",
       "6        0.949661        73.800003           3  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# write the csv file to csv \n",
    "df_years.to_csv(\"data/WHR_2012_2018.csv\")\n",
    "# read back in the csv file.\n",
    "df_years= pd.read_csv(\"data/WHR_2012_2018.csv\", index_col=0)\n",
    "df_years.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 44 rows with missing values out of a total of 1138 rows for data from 2011 to 2018.\n"
     ]
    }
   ],
   "source": [
    "# look at only rows with missing values: https://stackoverflow.com/a/30447205\n",
    "# any(axis=1) to check for any missing values per row, then filter with boolean mask\n",
    "nulldata=df_years[df_years.isnull().any(axis=1)]\n",
    "# see how rows with missing values\n",
    "print(f\"There are {nulldata.shape[0]} rows with missing values out of a total of {df_years.shape[0]} rows for data from 2011 to 2018.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"distributions\"></id>\n",
    "## The distribution of the data: What does the real data look like?\n",
    "In order to be able to simulate data I need to know more about the data and what it looks like. I will go through each of the variables in a sub-section of their own but I will first look at the summary statistics and some visualisations of the distribution of the most important variables in the datasets. I will look a the similarities in the data and the differences in the data. \n",
    "\n",
    "The distributions can be plotted to summarise the data visually using histograms and kernel density estimates plots.\n",
    "The histogram plots the distribution of the frequency counts across the bins. Distributions can have very different shapes and describe the data. Histograms can show how some of the numbers group together, the location and shape of the data. The height of the bars on a histogram indicate how much data there is, the minimum and maximum values show the range of the data. The width of the bars can be controlled by changing the bin sizes.\n",
    "[Kernel Density Estimation](https://en.wikipedia.org/wiki/Kernel_density_estimation)[18] is a non-parametric way to estimate the probability density function of a random variable. Inferences about the population are made, based on a finite data sample.\n",
    "\n",
    "The central tendency measures shows how common certain numbers are, how similar data points are to each other and where the most data tends to be located while the variance shows the spread of the data and how different the data points are.\n",
    "\n",
    "#### Central Tendency measures:\n",
    "- The most frequently occurring number in the dataset is the mode.\n",
    "- The median is the middle number (s) in the data when they are ordered from smallest to largest.\n",
    "- The mean is the average of the data. \n",
    "- The mean can be influenced by very large or small numbers while the mode and median are not sensitive to larger numbers that do not occur very often.\n",
    "The mean is the balancing point of the data - the location in the data where the numbers on one side sum to the same amount as the numbers on the other side.\n",
    "\n",
    "#### Variance measures:\n",
    "\n",
    "- The range is the width of the variation in the data, between the minimum and maximum or boundaries of the data. \n",
    "- The variance is the mean of the sum of the squared deviations of the data where the deviations is how far each values is from the mean.\n",
    "- The standard deviation is the square root of the variance and is in the same size as the data itself.\n",
    "\n",
    "### Correlation of the data variables.\n",
    "\n",
    "- Measures such as the covariance and correlation can show how the data variables might be related to each. \n",
    "- Scatterplots can be used to see how two variables might be related to each other and the strength and directions of any such relationships that exist. \n",
    "\n",
    "Correlation is not the same as causation while lack of an obvious correlation does not mean there is no causation.\n",
    "Correlation between two variables could be due to a confounding or third variable that is not directly measured.\n",
    "Correlations can also be caused by random chance - these are called spurious correlations.\n",
    "These are all things to consider when looking at data and when attempting to simulate data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualising the Distribution of the dataset to see the distributions and relationships between variables.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Pair Plots of the main variables in the dataset:\n",
    "A seaborn `pairplot` can show if there are any obvious relationships between variables. The univariate distribution of each variable are shown on the diagonal. The pairplot below is for the data for 2018. The scatterplots in the pairplot shows a positive linear relationship between each of the variables Income (Log GDP per capita), Healthy Life Expectancy, Social support and satisfactions with life (Life Ladder). While the life ladder distribution looks more normally distributed than the other variables it has 2 distinct peaks. The other distributions are left skewed. The [2016 World Happiness Report](https://s3.amazonaws.com/happiness-report/2016/HR-V1Ch2_web.pdf)[10] notes how for the world as a whole, the distribution of world happiness is very normally distributed about the median answer of 5, with the population-weighted mean being 5.4 but when the global population is split into ten geographic regions, the resulting distributions vary greatly in both shape and average values. Only two regions—the Middle East and North Africa, and Latin America and the Caribbean— have more unequally distributed happiness than does the world as a whole.\n",
    "\n",
    "Therefore taking this into account it is important to look at the data on a regional basis. The second pairplot uses the `hue` semantic to colour the points by region and shows the distributions for each variables for each region on the diagonal. The distribution plots show very different shapes for each variable when broken down by regions. Sub-Saharan Africa stands out as a region that has far different levels of life satisfaction, income and life expectancy than most other regions.\n",
    "Regions such as Western Europe, North America and Australia and New Zealand have distributions that are centred around much higher values than regions such as Sub-Saharan Africa and South Asia. The distributions for North America, Australia and New Zealand are very narrow as these regions contain a very small number of countries compared to the other regions.\n",
    "\n",
    "On a regional level the distributions look more normally distributed for all the four variables but with different locations and spreads. This means that any simulation of the variables must take the separate distributions into account."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Distribution of Life satisfaction, Income, Social Support and Healthy Life Expectancy globally  and then by region\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 915.75x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pairplot of the variables, drop missing values\n",
    "print(\"\\nDistribution of Life satisfaction, Income, Social Support and Healthy Life Expectancy globally  and then by region\\n\")\n",
    "sns.pairplot(df18.iloc[:,:6].dropna());\n",
    "\n",
    "# could also plot the pairplot for all years from 2011 to 2018.\n",
    "#sns.pairplot(df_years.iloc[:,1:7].dropna());\n",
    "\n",
    "# pairplots showing the Region as the colour of the dots.\n",
    "sns.pairplot(df18.iloc[:,:6].dropna(), hue=\"Region\", palette=\"bright\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The pairplots show a distinction between the different geographic regions for most variables. Sub-Saharan Africa stands out as a region that has far different levels of life satisfaction, income and life expectancy than most other regions.\n",
    "The histograms for each variable are plotted again individually to see the distributions more clearly for each variable."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of each variable.\n",
    "A closer look at each of the variables in the histograms below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x648 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the subplots, style and palette\n",
    "sns.set(style=\"ticks\", palette=\"colorblind\")\n",
    "f,axes=plt.subplots(2,2, figsize=(9,9))\n",
    "# plot the distributions of each of the main variables. At global level first. Look at Regional after\n",
    "sns.distplot(df18['Life_Satisfaction'].dropna(), ax=axes[0,0], bins=10, color=\"r\");\n",
    "# set axes title\n",
    "axes[0,0].set_title(\"Distribution of Life Ladder globally 2018\");\n",
    "sns.distplot(df18['Log_GDP_per_cap'].dropna(), ax=axes[0,1], bins=10, color=\"g\");\n",
    "axes[0,1].set_title(\"Distribution of Income globally 2018\");\n",
    "sns.distplot(df18['Social_Support'].dropna(), ax=axes[1,0], bins=10, color=\"b\");\n",
    "axes[1,0].set_title(\"Distribution of Social support globally 2018\");\n",
    "sns.distplot(df18['Life_Expectancy'].dropna(), ax=axes[1,1], bins=10, color=\"y\");\n",
    "axes[1,1].set_title(\"Distribution of Life expectancy globally 2018\");  \n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The distribution of Life Ladder variable looks to be normally distributed whiile there is some left skew in the other variables.\n",
    "Normally distributed data is considered the easiest to work with as normal distributions can be compared by looking at their means and standard deviations. Many statistical methods assume variables are normally distributed and others work better with normality.\n",
    "-[Sustainable Development lectures](http://www.columbia.edu/~so33/SusDev/Lecture_1.pdf)[13]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "<a id=\"statistics\"></a>\n",
    "## Central Tendency and variance statistics of the variables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the summary statistics for the variables for 2018 and also over the period from 2012 to 2018 inclusive. The 2018 statistics are similar enough to the amalgamated 2012 to 2018 statistics. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The data available for 2018 only: \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>136.000000</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>136.000000</td>\n",
       "      <td>132.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.502134</td>\n",
       "      <td>9.250394</td>\n",
       "      <td>0.810544</td>\n",
       "      <td>64.670832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.103461</td>\n",
       "      <td>1.186589</td>\n",
       "      <td>0.116332</td>\n",
       "      <td>6.728247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.694303</td>\n",
       "      <td>6.541033</td>\n",
       "      <td>0.484715</td>\n",
       "      <td>48.200001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.721326</td>\n",
       "      <td>8.346278</td>\n",
       "      <td>0.739719</td>\n",
       "      <td>59.074999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.468088</td>\n",
       "      <td>9.415703</td>\n",
       "      <td>0.836641</td>\n",
       "      <td>66.350002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.277691</td>\n",
       "      <td>10.166517</td>\n",
       "      <td>0.905608</td>\n",
       "      <td>69.075001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.858107</td>\n",
       "      <td>11.453928</td>\n",
       "      <td>0.984489</td>\n",
       "      <td>76.800003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy\n",
       "count         136.000000       127.000000      136.000000       132.000000\n",
       "mean            5.502134         9.250394        0.810544        64.670832\n",
       "std             1.103461         1.186589        0.116332         6.728247\n",
       "min             2.694303         6.541033        0.484715        48.200001\n",
       "25%             4.721326         8.346278        0.739719        59.074999\n",
       "50%             5.468088         9.415703        0.836641        66.350002\n",
       "75%             6.277691        10.166517        0.905608        69.075001\n",
       "max             7.858107        11.453928        0.984489        76.800003"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# summary statistics of the dataset (2018)- just showing the main variables of interest\n",
    "print(\"The data available for 2018 only: \\n\")\n",
    "df18.iloc[:,0:6].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Summary statistics for all years from 2012 to 2018 based on Table 2.1 data. \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1138.000000</td>\n",
       "      <td>1112.000000</td>\n",
       "      <td>1132.000000</td>\n",
       "      <td>1112.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.426942</td>\n",
       "      <td>9.259777</td>\n",
       "      <td>0.806205</td>\n",
       "      <td>63.625778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.127066</td>\n",
       "      <td>1.180980</td>\n",
       "      <td>0.119364</td>\n",
       "      <td>7.228575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.661718</td>\n",
       "      <td>6.465948</td>\n",
       "      <td>0.290184</td>\n",
       "      <td>36.860001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.596455</td>\n",
       "      <td>8.370898</td>\n",
       "      <td>0.741112</td>\n",
       "      <td>58.375001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.358060</td>\n",
       "      <td>9.448528</td>\n",
       "      <td>0.828651</td>\n",
       "      <td>65.480000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.267663</td>\n",
       "      <td>10.197885</td>\n",
       "      <td>0.903454</td>\n",
       "      <td>68.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.858107</td>\n",
       "      <td>11.770276</td>\n",
       "      <td>0.987343</td>\n",
       "      <td>76.800003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy\n",
       "count        1138.000000      1112.000000     1132.000000      1112.000000\n",
       "mean            5.426942         9.259777        0.806205        63.625778\n",
       "std             1.127066         1.180980        0.119364         7.228575\n",
       "min             2.661718         6.465948        0.290184        36.860001\n",
       "25%             4.596455         8.370898        0.741112        58.375001\n",
       "50%             5.358060         9.448528        0.828651        65.480000\n",
       "75%             6.267663        10.197885        0.903454        68.500000\n",
       "max             7.858107        11.770276        0.987343        76.800003"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# summary statistics of data from 2012 to 2018\n",
    "print(\"Summary statistics for all years from 2012 to 2018 based on Table 2.1 data. \\n\")\n",
    "df_years.iloc[:,3:7].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Boxplots to show the central tendancy, symmetry, skew and outliers.\n",
    "\n",
    "Boxplots can show the central tendency, symmetry and skew of the data as well as any outliers. The rectangular boxes are bounded by the hinges representing the lower (1st) quartile and upper (3rd quartile). The median of 50th percentile is shown by the line through the box. The whiskers show the minimum and maximum values of the data excluding any outliers. A distribution is symmetric if the median is in the centre of the box and the whiskers are the same length.  \n",
    "While none of the variables look symmetric, the distribution of Life ladder is less asymmetric than the other variables. A skewed distribution has the median closer to the shorter whisker as is the case for Healthy Life Expectancy, Social support and Log GDP per capita. A positive/right skewed distribution has a longer top whisker than bottom while a negatively skewed / left skewed distribution has a longer lower whisker as is the case for Log GDP per capita, Social support and Healthy life expectancy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# set up the subplots, style and palette\n",
    "sns.set(style=\"ticks\", palette=\"colorblind\")\n",
    "f,axes=plt.subplots(1,4, figsize=(12,3))\n",
    "# plot the distributions of each of the main variables. At global level first. Look at Regional after\n",
    "sns.boxplot(df18['Life_Satisfaction'], ax=axes[0], color=\"r\");\n",
    "sns.boxplot(df18['Log_GDP_per_cap'], ax=axes[1], color=\"g\");\n",
    "sns.boxplot(df18['Social_Support'], ax=axes[2],color=\"b\");\n",
    "sns.boxplot(df18['Life_Expectancy'], ax=axes[3],color=\"y\");\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "<a id=\"regional\"></a>\n",
    "## Distribution of the data by geographic region.\n",
    "As the pairplot showed earlier, there are wide variations between regions and for this region I will look at the distributions of each variable on a geographic regional basis. Below are the mean and standard deviation statistics showing how the central tendency and spread of the distributions vary across regions. The mean and standard deviations at a global level are then shown. There is quite a difference in the statistics on a regional basis which is lost in the overall statistics."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Mean and Standard Deviation by Region:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean and standard deviation for the variables on a regional basis. \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">Life_Satisfaction</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Log_GDP_per_cap</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Social_Support</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Life_Expectancy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Region</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Australia and New Zealand</th>\n",
       "      <td>7.2736</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>10.6112</td>\n",
       "      <td>0.1552</td>\n",
       "      <td>0.9470</td>\n",
       "      <td>0.0097</td>\n",
       "      <td>73.4000</td>\n",
       "      <td>0.2828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Central and Eastern Europe</th>\n",
       "      <td>5.6472</td>\n",
       "      <td>0.6164</td>\n",
       "      <td>9.6812</td>\n",
       "      <td>0.6087</td>\n",
       "      <td>0.8722</td>\n",
       "      <td>0.0817</td>\n",
       "      <td>66.7673</td>\n",
       "      <td>2.2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eastern Asia</th>\n",
       "      <td>5.5575</td>\n",
       "      <td>0.3296</td>\n",
       "      <td>10.0508</td>\n",
       "      <td>0.5844</td>\n",
       "      <td>0.8533</td>\n",
       "      <td>0.0737</td>\n",
       "      <td>70.0500</td>\n",
       "      <td>5.7076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latin America and Caribbean</th>\n",
       "      <td>5.9530</td>\n",
       "      <td>0.7548</td>\n",
       "      <td>9.2870</td>\n",
       "      <td>0.6722</td>\n",
       "      <td>0.8475</td>\n",
       "      <td>0.0820</td>\n",
       "      <td>66.9333</td>\n",
       "      <td>3.3755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southeastern Asia</th>\n",
       "      <td>5.5089</td>\n",
       "      <td>0.6609</td>\n",
       "      <td>9.1068</td>\n",
       "      <td>0.6375</td>\n",
       "      <td>0.8222</td>\n",
       "      <td>0.0609</td>\n",
       "      <td>64.6889</td>\n",
       "      <td>5.7106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southern Asia</th>\n",
       "      <td>4.2989</td>\n",
       "      <td>0.9597</td>\n",
       "      <td>8.3931</td>\n",
       "      <td>0.6878</td>\n",
       "      <td>0.6888</td>\n",
       "      <td>0.1109</td>\n",
       "      <td>61.0333</td>\n",
       "      <td>5.1613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sub-Saharan Africa</th>\n",
       "      <td>4.5200</td>\n",
       "      <td>0.6775</td>\n",
       "      <td>7.9125</td>\n",
       "      <td>0.8863</td>\n",
       "      <td>0.6918</td>\n",
       "      <td>0.0986</td>\n",
       "      <td>55.8273</td>\n",
       "      <td>3.7124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Europe</th>\n",
       "      <td>6.8981</td>\n",
       "      <td>0.6808</td>\n",
       "      <td>10.7237</td>\n",
       "      <td>0.3230</td>\n",
       "      <td>0.9118</td>\n",
       "      <td>0.0451</td>\n",
       "      <td>72.8105</td>\n",
       "      <td>0.7593</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Life_Satisfaction         Log_GDP_per_cap          \\\n",
       "                                         mean     std            mean     std   \n",
       "Region                                                                          \n",
       "Australia and New Zealand              7.2736  0.1367         10.6112  0.1552   \n",
       "Central and Eastern Europe             5.6472  0.6164          9.6812  0.6087   \n",
       "Eastern Asia                           5.5575  0.3296         10.0508  0.5844   \n",
       "Latin America and Caribbean            5.9530  0.7548          9.2870  0.6722   \n",
       "...                                       ...     ...             ...     ...   \n",
       "Southeastern Asia                      5.5089  0.6609          9.1068  0.6375   \n",
       "Southern Asia                          4.2989  0.9597          8.3931  0.6878   \n",
       "Sub-Saharan Africa                     4.5200  0.6775          7.9125  0.8863   \n",
       "Western Europe                         6.8981  0.6808         10.7237  0.3230   \n",
       "\n",
       "                            Social_Support         Life_Expectancy          \n",
       "                                      mean     std            mean     std  \n",
       "Region                                                                      \n",
       "Australia and New Zealand           0.9470  0.0097         73.4000  0.2828  \n",
       "Central and Eastern Europe          0.8722  0.0817         66.7673  2.2000  \n",
       "Eastern Asia                        0.8533  0.0737         70.0500  5.7076  \n",
       "Latin America and Caribbean         0.8475  0.0820         66.9333  3.3755  \n",
       "...                                    ...     ...             ...     ...  \n",
       "Southeastern Asia                   0.8222  0.0609         64.6889  5.7106  \n",
       "Southern Asia                       0.6888  0.1109         61.0333  5.1613  \n",
       "Sub-Saharan Africa                  0.6918  0.0986         55.8273  3.7124  \n",
       "Western Europe                      0.9118  0.0451         72.8105  0.7593  \n",
       "\n",
       "[10 rows x 8 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at 2018 statistics by Region, round for printing\n",
    "# just look at specific columns\n",
    "print(\"The mean and standard deviation for the variables on a regional basis. \\n\")\n",
    "df18.iloc[:,:6].groupby(['Region']).agg([np.mean, np.std]).round(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean and standard deviation at a global level for 2018: \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.502134</td>\n",
       "      <td>9.250394</td>\n",
       "      <td>0.810544</td>\n",
       "      <td>64.670832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.103461</td>\n",
       "      <td>1.186589</td>\n",
       "      <td>0.116332</td>\n",
       "      <td>6.728247</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy\n",
       "mean           5.502134         9.250394        0.810544        64.670832\n",
       "std            1.103461         1.186589        0.116332         6.728247"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean and standard deviation at the global level in the dataset for 2018\n",
    "print(\"The mean and standard deviation at a global level for 2018: \\n\")\n",
    "df18.iloc[:,1:6].agg([np.mean, np.std])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean and standard deviation at a global level for years from 2012 to 2018 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.426942</td>\n",
       "      <td>9.259777</td>\n",
       "      <td>0.806205</td>\n",
       "      <td>63.625778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.127066</td>\n",
       "      <td>1.180980</td>\n",
       "      <td>0.119364</td>\n",
       "      <td>7.228575</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy\n",
       "mean           5.426942         9.259777        0.806205        63.625778\n",
       "std            1.127066         1.180980        0.119364         7.228575"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean and standard deviation at the global level in the dataset for 2012 to 2018\n",
    "print(\"The mean and standard deviation at a global level for years from 2012 to 2018 \\n\")\n",
    "df_years.iloc[:,1:7].agg([np.mean,np.std])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The statistics for 2018 and for all years from 2012 to 2018 are very similar. I am focusing on 2018 but if I need extra data I can use the dataset with all years from 2012 to 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">Life_Satisfaction</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Log_GDP_per_cap</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Life_Expectancy</th>\n",
       "      <th colspan=\"8\" halign=\"left\">RegionCode</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Region</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Australia and New Zealand</th>\n",
       "      <td>2.0</td>\n",
       "      <td>7.2736</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>7.1770</td>\n",
       "      <td>7.2253</td>\n",
       "      <td>7.2736</td>\n",
       "      <td>7.3220</td>\n",
       "      <td>7.3703</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.6112</td>\n",
       "      <td>...</td>\n",
       "      <td>73.500</td>\n",
       "      <td>73.6</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Central and Eastern Europe</th>\n",
       "      <td>26.0</td>\n",
       "      <td>5.6472</td>\n",
       "      <td>0.6164</td>\n",
       "      <td>4.6206</td>\n",
       "      <td>5.1844</td>\n",
       "      <td>5.6662</td>\n",
       "      <td>6.1360</td>\n",
       "      <td>7.0342</td>\n",
       "      <td>25.0</td>\n",
       "      <td>9.6812</td>\n",
       "      <td>...</td>\n",
       "      <td>68.425</td>\n",
       "      <td>71.1</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eastern Asia</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.5575</td>\n",
       "      <td>0.3296</td>\n",
       "      <td>5.1314</td>\n",
       "      <td>5.3813</td>\n",
       "      <td>5.6291</td>\n",
       "      <td>5.8052</td>\n",
       "      <td>5.8402</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0508</td>\n",
       "      <td>...</td>\n",
       "      <td>73.950</td>\n",
       "      <td>75.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latin America and Caribbean</th>\n",
       "      <td>18.0</td>\n",
       "      <td>5.9530</td>\n",
       "      <td>0.7548</td>\n",
       "      <td>3.6149</td>\n",
       "      <td>5.7993</td>\n",
       "      <td>6.0558</td>\n",
       "      <td>6.3491</td>\n",
       "      <td>7.1411</td>\n",
       "      <td>18.0</td>\n",
       "      <td>9.2870</td>\n",
       "      <td>...</td>\n",
       "      <td>68.725</td>\n",
       "      <td>71.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southeastern Asia</th>\n",
       "      <td>10.0</td>\n",
       "      <td>5.5089</td>\n",
       "      <td>0.6609</td>\n",
       "      <td>4.4106</td>\n",
       "      <td>5.1653</td>\n",
       "      <td>5.3396</td>\n",
       "      <td>5.9760</td>\n",
       "      <td>6.4670</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.1068</td>\n",
       "      <td>...</td>\n",
       "      <td>67.200</td>\n",
       "      <td>76.8</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southern Asia</th>\n",
       "      <td>6.0</td>\n",
       "      <td>4.2989</td>\n",
       "      <td>0.9597</td>\n",
       "      <td>2.6943</td>\n",
       "      <td>3.9636</td>\n",
       "      <td>4.4497</td>\n",
       "      <td>4.8074</td>\n",
       "      <td>5.4716</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.3931</td>\n",
       "      <td>...</td>\n",
       "      <td>64.100</td>\n",
       "      <td>67.2</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sub-Saharan Africa</th>\n",
       "      <td>34.0</td>\n",
       "      <td>4.5200</td>\n",
       "      <td>0.6775</td>\n",
       "      <td>3.3346</td>\n",
       "      <td>4.0488</td>\n",
       "      <td>4.4510</td>\n",
       "      <td>4.9260</td>\n",
       "      <td>5.8817</td>\n",
       "      <td>34.0</td>\n",
       "      <td>7.9125</td>\n",
       "      <td>...</td>\n",
       "      <td>57.900</td>\n",
       "      <td>66.4</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Europe</th>\n",
       "      <td>20.0</td>\n",
       "      <td>6.8981</td>\n",
       "      <td>0.6808</td>\n",
       "      <td>5.4093</td>\n",
       "      <td>6.5157</td>\n",
       "      <td>7.0403</td>\n",
       "      <td>7.4081</td>\n",
       "      <td>7.8581</td>\n",
       "      <td>17.0</td>\n",
       "      <td>10.7237</td>\n",
       "      <td>...</td>\n",
       "      <td>73.400</td>\n",
       "      <td>74.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Life_Satisfaction                                  \\\n",
       "                                        count    mean     std     min     25%   \n",
       "Region                                                                          \n",
       "Australia and New Zealand                 2.0  7.2736  0.1367  7.1770  7.2253   \n",
       "Central and Eastern Europe               26.0  5.6472  0.6164  4.6206  5.1844   \n",
       "Eastern Asia                              4.0  5.5575  0.3296  5.1314  5.3813   \n",
       "Latin America and Caribbean              18.0  5.9530  0.7548  3.6149  5.7993   \n",
       "...                                       ...     ...     ...     ...     ...   \n",
       "Southeastern Asia                        10.0  5.5089  0.6609  4.4106  5.1653   \n",
       "Southern Asia                             6.0  4.2989  0.9597  2.6943  3.9636   \n",
       "Sub-Saharan Africa                       34.0  4.5200  0.6775  3.3346  4.0488   \n",
       "Western Europe                           20.0  6.8981  0.6808  5.4093  6.5157   \n",
       "\n",
       "                                                    Log_GDP_per_cap           \\\n",
       "                                50%     75%     max           count     mean   \n",
       "Region                                                                         \n",
       "Australia and New Zealand    7.2736  7.3220  7.3703             2.0  10.6112   \n",
       "Central and Eastern Europe   5.6662  6.1360  7.0342            25.0   9.6812   \n",
       "Eastern Asia                 5.6291  5.8052  5.8402             4.0  10.0508   \n",
       "Latin America and Caribbean  6.0558  6.3491  7.1411            18.0   9.2870   \n",
       "...                             ...     ...     ...             ...      ...   \n",
       "Southeastern Asia            5.3396  5.9760  6.4670             8.0   9.1068   \n",
       "Southern Asia                4.4497  4.8074  5.4716             6.0   8.3931   \n",
       "Sub-Saharan Africa           4.4510  4.9260  5.8817            34.0   7.9125   \n",
       "Western Europe               7.0403  7.4081  7.8581            17.0  10.7237   \n",
       "\n",
       "                             ... Life_Expectancy       RegionCode            \\\n",
       "                             ...             75%   max      count mean  std   \n",
       "Region                       ...                                              \n",
       "Australia and New Zealand    ...          73.500  73.6        2.0  9.0  0.0   \n",
       "Central and Eastern Europe   ...          68.425  71.1       26.0  2.0  0.0   \n",
       "Eastern Asia                 ...          73.950  75.0        4.0  8.0  0.0   \n",
       "Latin America and Caribbean  ...          68.725  71.3       18.0  4.0  0.0   \n",
       "...                          ...             ...   ...        ...  ...  ...   \n",
       "Southeastern Asia            ...          67.200  76.8       10.0  6.0  0.0   \n",
       "Southern Asia                ...          64.100  67.2        6.0  7.0  0.0   \n",
       "Sub-Saharan Africa           ...          57.900  66.4       34.0  1.0  0.0   \n",
       "Western Europe               ...          73.400  74.4       20.0  3.0  0.0   \n",
       "\n",
       "                                                      \n",
       "                             min  25%  50%  75%  max  \n",
       "Region                                                \n",
       "Australia and New Zealand    9.0  9.0  9.0  9.0  9.0  \n",
       "Central and Eastern Europe   2.0  2.0  2.0  2.0  2.0  \n",
       "Eastern Asia                 8.0  8.0  8.0  8.0  8.0  \n",
       "Latin America and Caribbean  4.0  4.0  4.0  4.0  4.0  \n",
       "...                          ...  ...  ...  ...  ...  \n",
       "Southeastern Asia            6.0  6.0  6.0  6.0  6.0  \n",
       "Southern Asia                7.0  7.0  7.0  7.0  7.0  \n",
       "Sub-Saharan Africa           1.0  1.0  1.0  1.0  1.0  \n",
       "Western Europe               3.0  3.0  3.0  3.0  3.0  \n",
       "\n",
       "[10 rows x 40 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df18.groupby(['Region']).describe().round(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Central Tendency, Skew and outliers of  Life Satisfaction, Income, Social Support and Life Expectancy by region \n",
      " \n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Central Tendency, Skew and outliers of  Life Satisfaction, Income, Social Support and Life Expectancy by region \\n \")\n",
    "sns.set(style=\"ticks\", palette=\"colorblind\")\n",
    "f,axes=plt.subplots(2,2, figsize=(12,8))\n",
    "sns.boxplot(y=\"Region\", x=\"Life_Satisfaction\", data=df18, ax=axes[0,0]);\n",
    "sns.boxplot(y=\"Region\", x=\"Log_GDP_per_cap\", data=df18, ax=axes[0,1]);\n",
    "sns.boxplot(y=\"Region\", x=\"Social_Support\", data=df18, ax=axes[1,0]);\n",
    "sns.boxplot(y=\"Region\", x=\"Life_Expectancy\", data=df18, ax=axes[1,1]);\n",
    "plt.tight_layout();\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When the distributions of each of the variables representing life satisfaction, gdp per capita, social support and life expectancy at birth are broken down by regional level, they tell a very different story to the distributions of the variables at a global level. There are some regions that overlap with each other and there are regions at complete opposite ends of the spectrum. I think this further clarifies the need to look at the variables on a regional level when simulating the data. \n",
    "\n",
    "For example the boxplots show that the median values of Log GPD per capita fall into roughly 3 groups (similar to the boxplots for social support) by regions with Western Europe, North America and Australia and New Zealand having the highest scores, while Southern Asia and Sub Saharan Africa have the lowest median scores and are the most variable along with the Middle East and Nortern Africa region. There is no overlap at all between the measurements for the richer regions (such as Western Europe, Australia and North America) and the poorer regions (Sub_saharan Africa and Southern Asia). The above boxplots by geographic regions show that there is great variations between regions in the distribution of GDP per capita.\n",
    "The boxplots also show some outliers where there are a few countries from each geographic regions which are more similar to countries in another geographic region than in their own region."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "## Clustering to see groups in the countries. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Colouring the points by regions in the plots above showed that some regions had very similar distributions to other regions and very disimilar to other regions. For instance Southern Asia and Sub_Saharan Africa are always close to each other and their distribution barely overlap if at all with regions such as Western Europe, North America and Austrlia and New Zealand. Therefore I am having a quick look at using Kmeans clustering to see how it would cluster the points rather than simulating data for the 10 regions as it is a small enough dataset. \n",
    "\n",
    "Here I refer to a [pythonprogramming blogpost on flat clustering](https://pythonprogramming.net/flat-clustering-machine-learning-python-scikit-learn/)[19].\n",
    "(I just looked briefly at clustering to see if the countries could be separated into clear groups of regions and did not do a thorough clustering analysis. I chose 3 as the number of clusters to use based on the plots above but a full clustering analysis would indicate the best number of clusters)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Adapted from code at: https://pythonprogramming.net/flat-clustering-machine-learning-python-scikit-learn/).\n",
    "from sklearn.cluster import KMeans\n",
    "# select the data to use. drop any missing values\n",
    "x=df_years.loc[:,['Year','Life_Satisfaction','Log_GDP_per_cap','Social_Support','Life_Expectancy','RegionCode']]\n",
    "x=x.dropna()\n",
    "# initialise kmeans to be the KMeans algorithm (flat clustering) with the number of clusters.\n",
    "kmeans=KMeans(n_clusters=3)\n",
    "# fit the data\n",
    "kmeans.fit(x)\n",
    "# create a copy of the data\n",
    "clusters=x.copy()\n",
    "# add column with the predictions from the kmeans model\n",
    "clusters['cluster_pred']=kmeans.fit_predict(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Look at the clusters to see how the regions are clustered:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionCode</th>\n",
       "      <th>cluster_pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1696</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1697</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1698</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1701</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1094 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      RegionCode  cluster_pred\n",
       "2              3             2\n",
       "3              3             2\n",
       "4              3             2\n",
       "5              3             2\n",
       "...          ...           ...\n",
       "1696           1             0\n",
       "1697           1             0\n",
       "1698           1             0\n",
       "1701           4             1\n",
       "\n",
       "[1094 rows x 2 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clusters[['RegionCode','cluster_pred']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot the clusters and then plot the actual observations to visually compare with the geographic regions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set the figure size\n",
    "plt.rcParams[\"figure.figsize\"] = (12,3)\n",
    "# use seaborn scatterplot, hue by cluster group\n",
    "g= sns.scatterplot(clusters['Life_Satisfaction'],clusters['Social_Support'],hue=clusters['cluster_pred'],palette='rainbow')\n",
    "# place legends outside the box - # https://stackoverflow.com/q/53733755 to move legends outside of box\n",
    "g.legend(loc='center left', bbox_to_anchor=(1.10, 0.5), ncol=1);\n",
    "# add title\n",
    "plt.title(\"Clusters: Social support and Life Ladder\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# scatterplot of life ladder and social support\n",
    "g =sns.scatterplot(y = df_years['Social_Support'],x= df_years['Life_Satisfaction'],hue=df_years['Region'],palette=\"bright\")\n",
    "# https://stackoverflow.com/q/53733755 to move legends outside of box\n",
    "g.legend(loc='center left', bbox_to_anchor=(1.10, 0.5), ncol=1);\n",
    "# add title\n",
    "plt.title(\"Scatterplot of Social support vs Life Ladder\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Year', 'Life_Satisfaction', 'Log_GDP_per_cap', 'Social_Support',\n",
       "       'Life_Expectancy', 'RegionCode', 'cluster_pred'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clusters.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the clusters gdp versus life ladder\n",
    "g= sns.scatterplot(clusters['Life_Satisfaction'],clusters['Log_GDP_per_cap'],hue=clusters['cluster_pred'],palette='rainbow')\n",
    "# legends outside of box\n",
    "g.legend(loc='center left', bbox_to_anchor=(1.10, 0.5), ncol=1);\n",
    "# add title\n",
    "plt.title(\"Clustering of Life Ladder vs Log GDP\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# scatterplot of actual log gdp vs life ladder\n",
    "g =sns.scatterplot(y = df_years['Log_GDP_per_cap'],x= df_years['Life_Satisfaction'],hue=df_years['Region'], palette='bright')\n",
    "# https://stackoverflow.com/q/53733755 to move legends outside of box\n",
    "g.legend(loc='center left', bbox_to_anchor=(1.10, 0.5), ncol=1);\n",
    "# add title\n",
    "plt.title(\"Scatterplot of Life Ladder vs Log GDP per capita\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the clusters Life ladder vs Life Expectancy\n",
    "g=sns.scatterplot(clusters['Life_Satisfaction'],clusters['Life_Expectancy'],hue=clusters['cluster_pred'],palette='rainbow')\n",
    "plt.title(\"Clustering of Life Ladder vs Life Expectancy\");\n",
    "# place legends outside box\n",
    "g.legend(loc='center left', bbox_to_anchor=(1.10, 0.5), ncol=1);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9wAAADYCAYAAAAZKeuWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzsnXd4VEXbh++zfTebkE0jQALSOxgBJYQiRaSIFBXk5UVBwQKW1wKCooCAgGBHUCyIiKIUBRQrRXoVRECKCKQA6XU328/3xyTZhARpAuI393VxsXt2zuzMKZvze9ooqqqqSCQSiUQikUgkEolEIvlb0VztAUgkEolEIpFIJBKJRPJvRApuiUQikUgkEolEIpFILgNScEskEolEIpFIJBKJRHIZkIJbIpFIJBKJRCKRSCSSy4AU3BKJRCKRSCQSiUQikVwGpOCWSCQSiUQikUgkEonkMqC72gOQSCQSiUQikUgk1xYej4fk5GScTufVHopEclUxmUzExMSg1+sr/FyR63BLJBKJRCKRSCSSC+HYsWMEBwcTHh6OoihXezgSyVVBVVUyMzPJz8+nZs2aFbaRIeUSiUQikUgkEonkgnA6nVJsS/7foygK4eHhfxnpIQW3RCKRSCQSiUQiuWCk2JZIzn0fXDM53E6nk3379hEZGYlWq73aw5FIJBKJRCKR/Evx+Xykp6fTpEkTTCbT1R6ORCK5hrlmBPe+ffsYNGjQ1R6GRCKRSCQSieT/CQsXLqRly5ZXexiS8yA5OZlu3bpRu3ZtAPx+P3a7nT59+vDYY49dcH+9e/dm+fLlf/cwJf8PuWYEd2RkJCB++KKjo6/yaCQSiUQikUgk/1ZOnz7NoEGDSp4/JdcGUVFRZURyamoqt956Kz179iwR4ueLFNuSv4trRnAXh5FHR0cTExNzlUcjkUgkEolEIvm3I9MYr23S09NRVZWgoCDmzp3Lt99+i8/no23btowaNQpFUfj444/55JNPCA4OplatWlSvXp1HH32U+vXrc+jQIQoLCxk3bhyHDh1CURTuv/9++vTpw7Jly9iwYQO5ubkkJSWRkJDAhAkTrvaUJf9ArhnBLZFIJBKJRCKRSCRnIy0tjd69e+NyucjOzqZp06bMmjWLw4cPs2/fPpYsWYKiKIwaNYoVK1ZQv359Fi5cyLJly9Dr9QwePJjq1auX6fOtt97CZrPx9ddfk5WVxV133UWDBg0A2L17N19//TVarZZu3boxcOBA6tevfzWmLvkHIwW3RCKRSCT/clz5Wfg8LrR6E8Zg29UejkQikVwWikPK/X4/06ZN4+jRoyQkJDBjxgz27t1Lv379AFGMuWrVqmRlZdGxY0esVisAPXv2JC8vr0yfW7du5aWXXgIgLCyMzp07s337dqxWK3FxcSX7xsbGkpubewVnK7lWkIJbIpFIJJJ/Mfmn/mTja0PJOLSdqCbtSHj8faxR1c+9o0QikVyjaDQaRo8eTZ8+ffjggw/w+Xzce++9DB06FIC8vDy0Wi1LlizB7/f/ZV+qqpZ77/P5ADAajSXbFUUp11YiAbkOt0QikUgkl4zf58NVkIPf573aQylDYXYqP73Qg9Tf1uNzOzn1y4+sm3InjqxTV3toEolEclnR6XSMHj2a2bNn06hRI5YvX47dbsfr9TJy5Ei+//574uPj+fnnnykoKMDtdvPDDz+UW1O5devWLFmyBICsrCxWr17NjTfeeDWmJLlGkR5uiUQikZTg9/sABY3mwu2xqqriystE0eowWkP//sH9QynMSePoT/NJ2fUd0c07Ua/bMMyhla/2sADwuQvJTT5UZlvG4R343IVX5PtVVS338CqRSCRXivbt2xMXF8fOnTvp2rUr/fv3x+fz0a5dO/r27YuiKNxzzz0MGDAAi8WCzWYr47UGGDlyJBMmTKBXr174fD4eeughGjduzKFDh87yrRJJWaTglkgkEglelwN7WiL7v3oNnTGIRr0fwxIRg0Zb8Z8Jv8+LKzcDFRWDpRI+j5PkHas4sPwNjFYbLe57mdDYhmgNxgr3/7fgsuewbc6jHF//BQCn9qwh7cAm2o/6BGNw2FUeHShaPQarDXdBdsk2S3hV3AU5l/V7HZknOfLDPBxZKTToOQJrVA30luDL+p2XG1dBNqjqP+K8SiSS8sTExLBmzZpy2z/88MOS1yNGjCjz2bFjx/B4PHzzzTcAPPzwwyXLhxULaqvVysyZM8v1269fv5KccIAFCxZc+iQk/0qk4JZIJBIJBaknWD6iGWpRSPSR79+nz7sHCIoovwyj255L8vZv2PHek7gdebQYMhVLRAwbZgwuaZP6W2v6fnAYa+S/O1fYW2jnxMYlZbal7PgWr9P+jxBmxpBw2jw+lw0z78HnKkRnCuKmh9/C7cg7984V4Pd6cOZlogB6ayg6g6lcG0fWKb5+vBWOzJMAHPrmHXq8upmoBq0vZSpXDU9hAVl//sruBc+j+rw0HzSeiLqtMASFXO2hSSSSS6RatWr89ttv3HbbbSiKQtu2benYsePVHpbkX4YU3BKJRPL/HJ/Xw76lM0vENoDHkc+JTcto1Puxcu0Ls06x/uVBJe9d+Vkkbf+6bJ8eF6f3/kydzoPP3P1fhaIoaA1mvE57yTaN3oCi+Wes3aszmIhq2IZu09bicxeiaHUkbvmKJneOuuC+XPlZHFv/ObsXvIDf46Jxv6dpcNsITJUiyrTLOLyjRGwDoKr8unAiHcZ8fk2KVHtGMt+Nbo9aVFjph7Fd6PXWLsLr3HCVRyaRSC4Vg8HAK6+8crWHIfmXI4umSSQSyf9zFJQKPZVafcXh4Kf3rivz3pWfiSWsWrl2FXnHrwQejweHw0FWVhYOh6Okmuz54HQ6KSwsPGfV2mIMVhtx90wqs63ZgGfRW/45wtISXhVr5Rpo9EZ0RgtN7hx9UTnm+aeOsnXWCFy5GXgc+ez5ZDyp+zaQcXgH9swUfB4XAEoF+f+KRgvXaC730dUfl4jtYg5+M6fcNolEIpFIKkJ6uCUSieT/ORqdjsb9nuKPHz/C63IAYAqNIvamXhW2D6t9fZn3x35exK3T1pK842tceZkARDVuS2iNxpd34BXg9XpJTExk69atqKqKVqulU6dOREVFlSve5ff7cblceL1etFoteXl57Ny5E7fbTf369alduzaqqpKenk5OTg7Vq1fHYrFgMBhK+tAZzdTpMoSqcbeQdmATkfVvIiiyOnqz9UpP/S8x26Ix26IvqY+krSvKbTu+4XMMVht//DSf7jPWE1G3JeF1WhIUVR17WiIgxPb1/52A4RrN4bZG1Si3LbhyzQoNCxKJRCKRnIkU3BKJRCLBEhFDn7m/c+znReiMFmok9MMcVqXCtsFV6lCvx4Mc/nYuqCrWyteBqtJ5/AryU49hqhSJ7bqmmEOjruwkALfbzfbt20vWQvX5fGzevJlu3bphNptL2vn9frKysli7di1er5cuXbqwevXqkv12796N0WgkKyuLw4cPA7B37146duxItWplvfnGYBvGYBu265pcoVleebLyIKzTGFrW603Kqkmc2iHEd+h1TUnbtwGfq5Cts0bQ5cVVWMKi6fnaVo5vXEJhxknqdB2C5SpFO/wdxMb3Zv+yV8hLOQJAUGQsdW4ZcnUHJZFIJJJrBim4JRKJRIJWb8AaVZ2md40+Z1tTpQhaDJ1Gk35Pofr9ZB79hdUTbsOenoS18nW0HDYTy1nE+uXG5/OVCyG32+0lQroYl8vF+vXrcblcREREkJ6eXq7N8ePHiYoqazTYvXs3NpsNi8VyeSZQAbkF4HCBUQ9hVyFS/VQm3DcVftgRROWwlsx6eB7VwybgTN5N5cbt2LPgBQDs6Un4fR4ALGFVaHT7o1d+sJcBiy2a7jM2kJt8ENXnI7RGo0uOFvgnkJ4NXj+EWCDIfO72EolEIrk4pOCWSCQSyQVjtIai+rwk71yFwVIJsy0ajd5Iw16PEN3s5qs2Lp1Oh9VqpaCgoGRblSpV0GrLFjHz+/04HCJ8vrCwEKu1fAh4SEhISZtifD4fXq8Xl8tVbq3Wy0FKOjz6BqzZBW2awMJxTtzOPLKyMqlWrRpmsxm9Xl/SPj0HtFoI+5uit+2F8ML78MMO8T41CwZOC+PIp6/iPbSYdVPuLMllrt1pMEar7S/7c3mEASHIdG2JPLOtMmbbP2Nt9YslpwDcHiGw9x+Hh2bCnyfhzpth0jCI+utTJ5FIJJKLRApuiUQikVwUpkoR1GjTD5/LQcfnloBGi9lW+axrd1+RMZlMdO7cmW3btpGVlUWVKlVo0aIFRqMRt9uN1ysqsWs0GkJCQsjLyyvxgMfExJCcnAxAUFAQDRs2ZMOGDWX6r1evHrm5uVit1r8U3PZC0GnBaDhrk3OSlQuDJ8PPe8T73gkufv31F+z5OdRr0p6vt+gwGRXim6pYTAqrd8LLn4LFBFMegGa1hbAtxuUBr/fChG5+IazdDSP6Qr8OYk7r90Byupam9VsT2TCevORDXNd+AA1vfwTtGcX38h2Q5wCNAgrwxhL4ZgvcUE+IvNgrn3VwxfB73WR4M/GofgyKjkjT1RHsThccSYEx78DpLPj0Bej4uLhGAd7/Wlyn0x8C8+W3IUkkl4WhQ4cyaNAgunTpAsD06dNZtGgR27ZtK6m70bZtWxYtWkRMzPmnuCQlJTFnzhxeeumlv3W8ycnJdOvWrWTN72L69+/PoEGDzrKX5FpFCm6JRCKRXDR6s/UfVSBMURSCg4OJa9kRl1dBr1WxWLQ4nU527tzJiRMn0Gg0NG3alM6dO1NQUEBhYSGpqam0bNmSZs2a4XK5UFWV7du307p1a3JycnC73QQFBeFwOEryv2228i7B3ALYdwxeWQQRoTBmEFSvLIRqReQWgNsL4SFQXIPrdBacOC1CyEf0Ff1l5kKnOC87Nh2nVds+dHjcQmqWaB8TCevegoETwVsUTd/hUTiwAOpUA78fktKEGE9Jh8fuhLh6YDvDC56RA7l28HjBZIS0LIitDK8+CtsOQK9nhGi/swMM6a4QHFmTdk8vwOcuxBBsQ6sra13IyIUp82HOchj7XzicBItWi8/2H4OdB2H161D5CixXrvr9+NPTwa+ihASjCQq6rN/ndds5UHiU4cfGk+w+TW1TDebVmUptS81ybQt9TvJ9BYBChN6GRrnIYmyOLCjMhLyTEF4XLBHkOg3k2qHtSChwQKgVDiUGxHYxX20Q50gKbsmV4NMf4bn3xO9SbBRMGQ7/ueXS+mzdujW7du0qEdybN2/m+uuvZ9euXcTHx3PixAksFssFiW2AkydPkpSUdGmDOwtRUVEsX778svQt+WchBbdEIpFIzpu0bCgoFGHLwea/N6e40ClE56V4hQESU2H4y1rW/wot6sG8Z1W07lMkJiZSt15DDJZoHC4htLds2YKqqrRq1Qqj0YhOpyMzM5Pk5GSqV6+OSw3luz0hHDihYXBXP1XDHJh0rjJh3CCOiVEPv/0pxG4xX6yB/R9DtciyY3R5hAB9Zo4IAx/RF25PgEI3JDwMyemiXUJTmP8s3PYMoPqpVq0an/6kLxHbINouXgsd4+DHnWKbzwfLN4gwdKsFOj0uCp8BrNwMy6fCbW0CfaRlw70vwQ/bxfvmdWDWE0LEv/wQTPuk1JzWQtvm8HBvxLraZ1lbe9sBeHOpeN3+enhpQdnPfz8BdudZTuLfiN9ux7NxC/kjnsCfmoZpyCCCxo9FGxl57p0vkhy/nTdSF5LnE6kNR50nGH50HF/Ue50IY9H3FqSRiZM3MpawKOMbwnSVmFzjKeJD4gjSBmoEqE4n3sxM1PwCtCEhEBZKmiafxemryPMVMLTynejtNkhNIWLHGDRHVoHegmfoemavbYHZBD/MhNW/QNUIaFIL5o2FGtGQZ4fVu+D4aTAV3Xe5BXAyQxiCVBXCK4FBJyIngq9c6QLJv5RPf4QHZ4i6FCB+rx+cIV5fiuiOj48v8UKnpqZiMBi49dZb2bhxI/Hx8ezcuZOEhARAFMCcOnUqTqcTm83GxIkTiY2NZd68eXz55ZdoNBqaNWvGiy++yOTJk0lOTmbixImMHz+euXPn8u233+Lz+Wjbti2jRo0iJSWFYcOGYbPZMJlM9OrViw0bNpCbm0tSUhIJCQlMmDDhguZTv359Dh06BMCyZcvYvn0706ZNo1OnTjRr1ozff/+dTz/9lHXr1jFv3jwURaFx48Y8//zzBAUFER8fzy233MLu3bsJCgpi5syZxMTEnHXuksuLXNNCIpFIJOfF6SzoNQbqDoRa/WHkq0IsXir5Dth1CIZMhYdfEULU5bm4vjJyhEj8aafIV92yH3qMUlD1UbTrPIAfD8YxcGpVnltQj+SsUKrF1MBut7Nu3TpcLhcmk4k6derQtm1bQsLr0P1pDY++oWPOVxrajNCxeb8Jh6MQH0H8+gds+g0+XwP/mQjfboUZn5Wf25pfyo8zPQfiH4Lvt8Mvh2HYdOHV3rof4psEjA6bfhPe7YY14MhJPZUqhZKaU95dnpkLIWc4bSNDYeYi4UkuFtvFzPys7LbtvwfENsCvf8B326BDcyHIzuT7bVDo+osTgRD2xeTkQ/QZnmydVhgpLjdqRiY5Pfrh+/MYqt1O4dtzcb4/H7UoveBC8dvt+EvVCCj3eXoGQdsOMunbSFYbJ/FU8N0AHCr8E4/qxeEr5LTzNBlaHysKtvFtznrsfgdJ7lMMPTKaHE8ejgIn+TkFFDgyKdywkez6N5DdsAWZ9a7Hs3krk/58g+kp75JT6GH3ATN9xxm55eWmfBzyGVm3rwSNDv2qEdQKy+Cpt2HoNOjSEqZ8DJPmCwPI4rXw5Cxh9HjzcRHxoKrw21FhDGn/CLQZAePe85Ga4eLzNSLnO89+UYetDJm5kJIhflPkcub/v3juvYDYLsbhEtsvhcaNG5OYmIjL5WLjxo0kJCSQkJDAxo0bAUoEt9vtZty4cbzyyit8+eWXDB06lOeffx6fz8e7777L0qVLWbZsGR6Ph9TUVMaNG0eTJk0YP34869evZ9++fSxZsoSvvvqK1NRUVqwQKzYcO3aMGTNmMG/ePEAU2HzzzTdZsWIFa9euLRHPpUlLS6N3795l/lXU7kzat2/P999/T0ZGBu+88w4LFixg5cqVmM1mZs2aBUBWVhZxcXGsXLmSnj17Mnny5LPOXXL5kR5uiUQikZwTrxdWbRHirZgv1sJ9t8EtLS+t76Mn4aYHxcM+CAF7YIHwwF0Ibrcbe6GGrfvL/mn78yT4FQsffKMwab7YdjgJOjymY9fcenBwPwDp6elYrVYURUGr1ZOZJzzWpZm60MDCsSZ27tHw2U9wYyMY+674rFbVij2AoRVE3G/dX1awvvqIEB9L14kQ9LVvwH3T4OAJyM6HldPBbDARYq7HA0E+3lupKREqWi3c2x0GjA/0F1dXhGr+chgGdin//ZWsZcPc9xwp3+ZwEtSLFeLsTBKagvYcJvvuN8J7RUt3z10BUx8URhWfTxTqeu4e8aB9KFHkd4dVgohKf93nheB0ITref7CcqvMcTyLHrnAqCwo9EBv510XDTmXCkSQ/Zq2PmMJTWGbPwDLyQTTVY8DjAa0WTUQ4al4+eSOfxLV4GVoARWHQF++yq/GNJHtSURQtH6UuZWXmauZUfZvqmV0Z5epE9dhCJmdNxKa1kZVq45mPDWTnm3jyLhON9iWjsQuVq9rt5A+8n0k7v+Oeqndhza3PDQ+bKS7Mf/9rISx/qTttR+zFlJVJAj5CguBIshC5+Q74+Ds4mgKDboE5X4n7IzkNFr4gUhI8PnjkdeEN/37CScIPv0fQ7v00aP4AP/zegurX2WhYA/Q6cVgvdDny5DQYNAk27oXrosX33lAPDFfA+CK5+iSlXdj280Wr1dK8eXN+++03Nm7cyKBBg4iNjcXpdJKbm8vu3bt57rnnOH78OElJSTz88MMl+xYUFKDVaomLi+POO++kc+fODB06lMqVK3P8+PGSdlu2bGHv3r3069cPAKfTSdWqVWnRogXh4eFlwtXj4uJKinHGxsaSm5tbbswXG1LevHlzAHbs2EHHjh1L0psGDBjA2LFjATAajfTp0weAvn378uqrr5517pLLjxTcEolEcg3g9UJGnhA5kaFX7nvTsmHVVli3G7q2Eg/H904J5Arv/P3SBLfbA699HhDbAE43LFsPT/Qv397jFcJBpysvzjIzM8nL01K9chSJqYHtIUFCGCxbX7Z9QSEcTtZgsVhwOBzYbDZOZcD874QRYNhtIq916idl99Mbg3nhQy2jB5b9bPFa+HwiLN8IjqJQ6Xqx0KJ++XlUiwi87tpKiI1eYwLblv0M7zwNPUZDjzZQs2SVNTO1q/nZPFtl8scKWo0IR1/0kwgB9/lECHnVcGj7CCSlitD/5nWE1xqE93zysLIe8d5t4ZXPoW6MCC/OzIUereGDb4Qw+19/eHuZOP63JwjBnV0AVUrl/Lo9wmuu04oc8Lh64np57A34aZcQ2fvng90FJ06J0Ps8uzBUzBsrws8nDBW575eCwwl/pMD0hWI+93Ttgm7tNizvvIJv8RKUofdx+tnXmD1PwWSE4b3gk+9gUDeofIbozswVYf4ffA11qmnIyNWwZX8dXn14FK7O7bBtWUPupt04msejQ0WjsaLUqAN6vRDiqor2mak8/v3raGMrs6PgN1pam9FVewcZ6SYMPguaQnh4HMydOA2dTqXNEGPJ9fPdNh0/jutF86Zz8P4mDEP+tDRcrgJeSfmA1vtf5YxV8Hj/ay1tg90U3DGU4C43k/LOWE6o0WgUePsJeOgVETkx5YHAPj/tAp9fiGirRYSXL3o6leor20PWUQAM+xbT9tb5nNT8l9RsDSdOi+ujWS0Y1FX8JqgqWM3loy2Kyc6HB2YIsQ3iWus+ShjYqoRf2nmXXBvERlHm97n09kuldevW/PLLL+zdu5cZM0Scenx8PKtXr8Zms2G1WvH7/cTExJQIXZ/PR0ZGBgCzZ89mz549rF+/nmHDhjFz5swy/ft8Pu69916GDh0KQF5eHlqtluzsbEymsgUjSxfVVBSl3LKT54OqqiiKUlLs88y+/WcYElVVLVMYVFGUknZarfYv5y65vMiQcolEIvmHk5krqju3HSFyeTf/FhB0F0pWnvAkpKSLXM1zfe/90+H+abDge1Ex+5fD8NNr8PNbolBX3/YXN45iNArYQoTHtWGNQCi1rQKvcEauKEaWMEIU8Np2oMiLifBu//7775w8vocPn3GVeJrNRpg31s+fKQrVK3igiw5T8Hg81KtXj0JfCAkjRWjjh99Am4fh+rpwY8NA+zGDXCh+O16vEGLWUhW/T2eJwmR7PhQVn+c8BR88U3HBtNrVoFML8bpPO+EBLs2xU0Lcrn+rfCh2sEVDk1oK93aD+tVFGP6UBTDkJWhSW4w3JAhubSXaD58BH46B3+aLf398BnXPSNmrHAbr3oT/doXPxovXZqMIKdfrhKHnh1fFeW/bDKZ/WjbXPiNXhK8njIDbx8K2/cIY8d1W2DFXCKpCFySmgU4D/3kxEJr850lRQbvRdXAys/yxOhtp2cKgkF5UV6CYxFRYsk4UrLs5Du5+UUPndxszv+tbqD/9TNazr3D9fQpvfymup1bDoXd7OHQ80EdOUR7zr3+Iufl8Yj4OFzw7GAqr1cLxexJ/WhvwTNZA2s6oyYOvGzieYWBB09H4lgROqD8vnzrG6rxw4jUeOjoOxRHG/14xcdODCjc/KvLj334S3v+iElmpIeXu7ddXh+O9/Y6S97qmjTmsniTdk0W9Cpa7rxNZiNGkxffHUZzvfIDzwYfZuTWbRoPh3RWw+EVo3RhMenFum9WGTW/Dt1tEtIHFCDNGgC3KhjO6TZm+Q3dPp7IpgwKHCDmf/y2k54rj3WwIXNcfHnkN0s6SauJyw7o9gffVKwvDWe5ZwtTtheI36yK0iuQfypTh4horjcUotl8q8fHxLF++nHr16qHTCZ9iQkIC8+bNK8nfrlWrFrm5uezcKQpeLF26lKeffpqsrCx69OhBvXr1ePzxx0lISODQoUNotdoSEdu6dWuWL1+O3W7H6/UycuRIvv/++0sfeAXYbDaOHDmCqqqsWbOmwjY33ngja9asISdH3HBffPEFN910EyCWuyzeb9myZbRv3/6sc5dcfqSHWyKR/KspcIiljbQaETKamSsezjUa4fkL/ZvWK75UTmeKatThIRAdLvIpTQbhmV25CUbPEe2OnRJL+hz+DGqY/rrPM0nLhuEvw9ebRRjyw73h+SFnD+O1O0UYeWnmfCW8oe0fCXhKo8Mu/jjqdPBkf+jTVjzsN6sDX2+CbjeVbefziQJkxXl+x0/DzY/B4U+FZ0Sj0WA0Gjl58iSVtVvZNjsOp0dPaIiOguxE9iTGMnqQgc37A4aGu7uoVI3UUv+229DpdGw5ILx2pXlzCcwc6eezH+HuTi703hOkpmQyZlA473+jMOa/Ime82NHgcMKO32HFJnGdtWsO0x4sP+8oGyyaANl54lx89G35NpXDRKhtRZiNou99x0Qxq7s7C49lVJF3OCQIJg8XXmoVkQow7n1xTh/uA6MHBopkuT1iqa5h0wP9j/0vdG8tvPNhIeJe6fS4ED4RlYSxpXitb59PeNiffz9wbm4bI8LiOzwqDBFPDhCGh++2iWJtTnfZ+ew8BBPuE9coCKGV5xCiNzxEzKe4QJ/bI0Kkx38gvOz33ArXVYGmtSG0KJqhXqwwiNz6VCAaY/T8IKq9cD017B6WTnSz/ZCO2V/pycoT1dP7tBMe2C374NhpkVOfnAZ1YkTUw+cTYcEPwsDR/SYN/dpreHZuIFc9JR0OJcGMh01sTm9Ix1Yt8O7YhWbEvbxc+Dl77AdoaK7NkSMhfLtNKZn77iMilz86VIfNcoa7Goio5EdvDsWj06Fv0xrT+28woXA8R50naFrbRdvGOjbuF1admEh4rGs+2sz0kv093/1Iz9cLaV7HRqFLhIo/NQC2HoD1syDICN1HwyP9RM2DuSvFfga9gbVTX6V17u+QUlSNT2emoFBh2SZx3T56B9zXQ5zzuzsLw9HCH6FRTXj67vLGJr0ObqgrromGXX7cAAAgAElEQVR3nhZi2usD6xm/ZT4fnEiFFz4QBsIHeonr8e8s0ii5OhQXRvu7q5SDWLYxJyeH//znPyXbWrduzf/+9z/atBHGI4PBwBtvvMGUKVNwuVxYrVamT59OWFgYAwYM4M4778RsNlOzZk3uuOMOXC4X+fn5jBo1ihkzZnDw4EH69++Pz+ejXbt29O3bl5SUlIsab3EOd2latWrFuHHjeOqpp3jooYeIiIigRYsWZGdnl9u/QYMGPPjggwwePBiPx0Pjxo2ZOHFiyeffffcdr732GlFRUUyfPv2sc5dcfhT1YmIcrgLJycl07tyZ1atXX3BJf4lE8v+T1Gx4di4sWQu1q8KXLwlv3+qdoCgi73Xag1c2RLsiTmZA64fghSHC47t4rchtfGaQeDB9dm5gLeZi5j8nvJHni6rC7C9FeG9p1r4J7ZsH2pzOgh92CE9U11ZQ++6y7YMtwkPWrZRR/GBR6O7FkFsA0xYKzzAIQ8iXU4RQLJ0bmpkrQq63HSi7/+IXxfrQIML7Vq1aVeKNCA0NpUWLFqxevZoWN93C8cwoomwKJzOhZrQQtKXP/ca9ZSuMA3S4Ht4acZJIm7BPO51OQkNtpKTaScwMJTnDRMsGKuv3QP0aCnVjYNg02PMH3NURJt5fPky5mJR0uOsFcdxHDYT+4wOevFYNYMW0v84rBiE+cwqEh8h6lgrS+/6E5kPLbvtoLAzuJl6fyoQm94h+itFp4chnUCUMch0i5zwyVBgRKttESLytSPxk5EDPZ8rm94MQVK8vFnno62eJate9x8B7z0DvsWWLb3VpCT3jRdh5dJgQu28tEwW8OreAW28SYfWhVvGQ3vC/ZXPg5z8n2mXlie9sUF2Is9JGhNrV4MeZdo4f2UVmZgZhEZWJjo2j6ygLD/WG+28Tc7h9jLgveoyCT8cLI0HbpiLKpPQcd7wnag+cWfRr7ZtCeM6u9C6aUCsH2lfjrvRxeFUfnSu1odqmSbw8v+zJuqsjPDnAT2hUDnc8GcaB42J7sAV2TMug2raVaGvWAEVhVu2DvJr+MQBPRAzmbvNw/kzVkV2gEBkK4Uoesad/Jb9LdwA0/QfgfH0uK7dquaUl9BtHSf8WE2x8W9xbX0wUEQqlaV4Hvh++kshvbgdFwTPoe3Iq30L3UfDYHaK42qxlou1DveH6OnDPFFEdf/nUigXykSTIyoehU4WRDUQV/63vCGMAiGuy6b3CAFLMe6NhSPcLzxm/WORz57n5/fffadiw4bkbSq44paucS64Mf3U/SA+3RCL5V1LoEmsAf7RKvK8aAQt/EGIbhLD5aBUM6hII7b0cpGULr6JBJ8KmS4cgg3hYn7sCmtYS3tEn3gp89tVGsU5xzSrlBXdMpBAsZ8uVPBOnG9ZWUC17096A4D6VCTc+IP4HUbl4QCdRxKyYJ/oLg0BpDp64eMGd7xChyMX4/SIkddu7ZddnNhnEmtJnCu7rSoXUBgUFcfvtt3P69Gm0Wi0Gg4EtW7agKAq2YJUGdRSy8qBBLARVIE7rxgjP6OGiJVcVBZ6/x83xP3azOzsbvV6PVqulXbt2/LZ7PSaTiYaRlck96aJr08rUry+StRcVrYddKUgImrPNe/ScwHzW7RHnetNvIky8bbPyYltVVdR8L+gUNBbx59ugP7coL14qrDSL10HfDuJ6VFURBVIar094xvV64fHt86w4HnqdEPnr3hQedhDe9jrVygvu2ChRjb1qhKhGvv2AyNee+RksGCeMPydOQ3xjeP1RcY9E2YQBasAEUbkeRJX3xFR4/l4huNftLl8hfdUWIQ5bDBPe0dgo0WdpZj7sZN/udSWeIkfiMTwuB9MfaE98MyP2QjE3i0l49Fe/LtI3qoRDywbl53fslPie0lERBr2IpunQXMXUcQh7Ocyugr14VeG53us4yENt/bw8v2xfd3VU0UUk4jI5+eRlH4ePmnEVmLm5iY+g6TOxL1mKbkB/Ch54nNpWP6ZMI06/C5NSmdFzdXy3XcGgE8fbFhzCnheqoQc0sTFkTJrNTUO1xESK810stkH85kxfKLzTFS3RlpIOhdVvxdlhCp56/VhzpBrtq4il4lKzA4YygFc/h4+fE8uOxTcp/1tXTJ0YmLcqILaLv+e9lcLoqCjw+/GyYhvg7S+hV8LVN5BKJBLJhSIFt0Qi+VeSUyCKVxVTJ0aEbp7J5n2XT3Anp8Nto0Wla70OJg0TBZpKV632+0U4Zs94UYCoNGnZcDhRhAD/uFM8lIJom54jHvib1xHb0nPgj2Th/YtvIh5KTaVybM1G6NUWvtxQ9ju6lCp4tnJTQGwDjJ0La14XD+Mb9sLtbYWY6fJEoI2iiAfsi8XlKe8hTM0G/xmxV0FmePF+sUTV6aI1qPt3okxetlarxWKxUKtWLVwuF3a7nRtuuIGIiAiMRiOKIrysZ6NymPBOfrNZFE0bfCuEBflYe0Q8+Xs8HsLCo1A0OtxuN263m7w8sbZWdHSgpPr5CIKCQiGuQVwPXpefddtV/tNDW6Hxwp/vwbs9C8+qkyg2PcZ7aqKpakbRndvdV1HRtvgmYC66PqxmYVj59MfA5wlNRaix3w9LfxbbVFUIUhD3VrHgDjKL8PW1uylZH/yODuL6zbPDVy+J/PyaVYTnvt0jYvvMEUKAa7Wiv0FdRYSH0x0Q28XM/w7G/Fe8jq6guFbnlvDGYkoKiCWlgdcv7pVvitIi6sd62bGxbFhmamoqPXv5uG2s8OL37yjy7s1G4bUvnk+XlsLr7y0V8f3J98KL3+dZERGiKKLo257DKh1jPZz+XaVGXFX2OQ4zr+7LbMjbQVdLB65zmPjoaT8TPtHgdMP/+vux1T2E3qLhl4IDeFQP7Zq3IkJvw+51wejHyRz8GHPWhvHR/0wc/DyBdY0Wk+9xYnFV4bktSpkc9ux8yA2vTqVl36A0j2PCfAP2QggyVZwrnWuHBhZxfqtGCINHMXd1hHyXgafWP8va1+G1R4XhsHXjQJpLadbtFuf+gV5nrzquKIF15ktzIlWcP50uED1RmshKoK+gHoJEIimP9G7/s5CCWyKR/CsxG6FxzcCD3S+HhXA8s1J199aX5/vthSKntXhZKY9XFIbq266s4NbpYGRfIVYqWj7KZBQPtvPGikrl0eHCcDBsuqgc3byOENv3ThF5oCByqze9LapEl6ZHa3jgduFdMujhucEizLaYPEf5Oby7AuY8KcQ2CAHSK0GIc1uw8IKHX0JepdUixNjvJwLb7rm14uW1akTDzveF4SEkSHzv2QS00WjEaDQSFhZWcYOzEB0mQouLybcbuLHt7eTkZGMymTmWakGrUwkJCSkR25UqVSI2NvYsPVZMsFlEFiSnqXzysIug1cnostzo82PwOywlHmwoqjy7Kwvn64EHKO+vOVjfaYUSbqyo+zI0rAFDegSiPVo3Fnm32iLxEhIEr4yEpjXhm61CbD92Z6BaeKcbRNG80tx8xlJh10XDrqJzE2wR3up9x4QnfO4KcT+2by6u8d/mC0EcYhHX7Jh3hZB/9QtRcM6gF6KsdMJbJavYBqLI1w31xD1dPP6urWDP4bJjGjYdfnwVxg4W64CHh2jQ6XRlKv4ajUYOnlDYKgqA88VaeLivqMxfLLZBXO9P9C+7znrf9sJDvH2uyMWvGqmiRyXx50JWP55NWC09fWaFc0toW77OWk2cpTGNXU35qPcpaiSYWDQ0GI1eoWqMgiGiKjqNhkaWOmQ7neAx4S7U4rDD8DfFuvKVw0TovNZnAq8JTzbsSxPF5rb/HhiXVgsmk46Fjg5084uibwC/HhUF9YItIsKimOG9oGZV+GYTrJgKL30iolZ6xgtDw7HTEB4sigAmNBUh3RYTdIwTNR1K07EFdL9J/Db8FXd3FuuBlza2jegjfg9BRPB0bhmISDIZ4OUR/5yaGxKJRHIhyBxuiUTyr+WPZFFY61SmeEjcMRc++UE8JBoNwhv1366XpxBPWjZ0/l/Z8E2Ar6eXF/m5BbD/uAiT7TlaiHMQD7f/u0vk+YLIYfxuKywtMhoU5y/vPQpx95Xt8+Y4WDwpUNiqmAJHQFjbgoUQKubEaWh8TyBcV6MRAqhxzbJ95OSL8FONRhTQ0l+i6TY5HSbPF17N3u2EUSDqKoeN+rPdeLZmoKY60XaMZmeGkQXrtAzqCk1qgkFbiN1uR1EULBYLZvNZ4mf/gpR00OS6CBq3C+wBEWiZ1hxd44AlwZ/vofDF/fgO5pXZ3/xsI/TxEZwP2flCZPn8wqNdkRfe6xOeZ6u5rHcyPQcemglfbRCid2AXsW742Tz5SWlQd6DoJ6dACOd6sUJ8F6cJFDhEVfUzIy4+fQF6xAvj1Dullqf9+DkY0DlQhCs1W4QdZ+YKsWjUi/G3e0QYikCEp2+ZI/Ks3V64o72XR3omsn/vlpLldlrc2IHn5lfhqw0B1+nSyZB4GnYc8NMnzsuJLA2zv9fx+qPCsLD3qAih/3kPpGRAXoEIex/RD+5o5WPl3afwulSiGuq5451IgsIDff+yMJ81U8uW8K7T2cyN91kJjdFjCS/rws3IhbQsEd5vMUG+Xcxx7H9FJfA+bYsMDk8VLZenhakPiGP1yiJxn3ZtJeoDgMhzf/F+eP9rcV7vuVUYu95cCr9+CAcTRdG/EKsIp/9uO/z0Ksz7Vnivv5gYqHCfniPSAr4oSjm5o4Ootn4+ER5p2eK3ceonwtjyxAC4sUHZ6IW0HDiaLI5x60YQaRPn+UohnzvPjczhlkgCyBxuiUTy/5JaVWHneyJkMsgEwUGiiNVTRYXAwkIu3wNcpSDh6SktuDWa8uIVhPeuTRNRfOrgJ+Lh/boqUD9WFLwaPxR6tRH5vsViu0OcyPOFssWuisnIFR7xM7Fazl5cKzocdn8ovHiFLlHJunSOdDGhwefnafLnuvEnOfCfLETXLBQlVI9iKv9nJyZSCDi7U3hAzxTwfqcPRQHFWFaM+HPc+E/Y8ae7ivo3oBguvaKSP9uN45k9+E8VJbUuS6bVtOa0fLxSqbGZL0pkl6ZaJLgO5OKylz1R7sWJaGo2DHi5dQpKuKHc/oqt/LazYQs+t9dRp63Y+BQZKow9rz0qBLfV/Nd9Od3CaFQ6BzcprazHWlEC3szSmAzCAzvxflHUcM9haB8nireVrnhd2Sb+OfN9fLFGYW+yhuvrwu4PRMVxrUZ4SE9lCiPXy59CYpoOrSWWXr0qk5LmwGKx8EeKoYzYVhQhqm9t6GaQ6zTG79MgysTA52rhtJmpWU2hfnV4eSG88GHZsTepWbSsVriGvJM+brwvmORdTqq3MmG2ie8Iji4fE22N0LJ3sYPcFC/dXwpDo1OwhGnQaBUiKgVWETh+CuLuF68//l5El3QfJbzWX04Rv3GhViGE31oqjHG/HIaYKFgyGd5eKvoKrwQj+wmv/Cufw9EUcf+t2ipWB9h9RBRYjI0SRr1Rc4SHHcoWLIsMhdlPinxuFXFdnK/x8miKEOv9O4r7fcrHwojQp12gTVTo1Te8SSQSyd/BZRPcixcv5pNPPil5n5ycTO/evenSpQtTp07F5XLRvXt3nnjiib/oRSKRSC4ejUaIyDNzPoMucDmti8FoEMI+MU3kwEaFinzPv3ogjQgV/+7rGdhWLVJUaC5+3SFOiAlbcMCTVDdGPEgXh46CCM+80FBvo170Net/QhwZz1/PlcOf68H5xmG8O4ricjVgmdIMXZOKn6AtpvIFxvwOL/7kQtxLEsGoxdi/OprKRhSDFn+Om8KpB/AdKPL66hSCZsahrV1BXP6Fjj3ZERDbACq4Fp7A/HQD/KigKGhCL+HglEJjriAp1aJF0Sil2ugw3nMd3t3Z4BBJxNqmldBElz1gPq+KM0fE6BqDFXTGcxsffB6VwmwfWce9WKO0mEM1mEPLjyks5PzFVLBFiNbjpYqJDexS1tATZBZF0JZvDOSF14iGmxqJ18VCs3gNdNXrx58tDBNKkK7EsOJzQV13IeaaJgpVLQ6Xyn+6gNkEXq+CTicMWa8/LoqeDXtZj9WkZ/IDQdz8FLz7NDw9UKRZVCoKra9f1Y/y9Sn0n5/AD5DowHooj6i3WgBG9DqRdvDddlEDQqOBB28Xa4h3aKigtDRSp7OZsOt0zOudSqexoVx/txWNVqHq9UaiGuhJOygmbQnX0Li3hcXD03HbVfJP+1j5VAY9Xw6nSjMDulIGpL1HA8fvUCK8uxw2vC2K/GkUUBBF40wGEd1yxzixOsOPO0QawSfPi3NjMogw8fW7RaXx6HDRx9CpcOwLkU4w6BaRU/2fiaJWBEDXG4VxsDTnY8ipiJWbYf8xGH8ssG3JOrFkXEXr1kskEsm1zGUT3HfddRd33XUXAEeOHGHkyJEMHz6cgQMHsmDBAqpUqcKDDz7Izz//TIcOHS7XMCQSieSqUTkM3h0lPIMgRLf2Eh4mo2wVV6SubIOt78KL88TD8bCiNWvP57tUn4qa50a1+1DMWrBoMZgv/U+Dmu8JiG0APzjf/xPLxKZoKp1fWIF62onj6d3CfQZ4N6VjndMKpbIWNcMVENsAXhXnvD+xjGmIYr3EsAV/RdtUvL/l4Hz1EJpqZsxP1EdzXVCFRcv8uW7UQh+KooBZiybk7OPR1g1GU9WM/2RRHLRBg3FgDRRT2ZOnqWzCOqclvj8L0IQYUKKMOLxa3Mc8GIIUNHqFYxucrH81B0+hStwgKy0HB5d4Vs9GxhEPn92ThtcpDnLcf6y0GRmCuVLF+zmyfXjsoq0hSMFs01KQ5iVxm4uknS7qdzVTubGB1W9oGfOOEIm924r85zOrVteuCgcWiCr4kaHQs3XFBdHUAg+erZm45h9Ddfsx3F4NQ69qaEL06M0K+kIftT0ONFaFk4s85P7ppue0CIKixByiw0SucMv6QtCl54j76Jf3RXpFfGMhPHXaIiNWrhf7T6llx5DvRU13QVHOfHQ4fDZB5Hm7PCK83Kz4yf6lEFOoBq1eYdPb4vrcu9ROg24WLOFaTCEabpsRTn6aD0e6j5BqOla/lIO76JiqKtgz/Xz5SAb3rayCNTIwhsZnFCdcth5iK8PUB4WxLC1brHawYS88/TZ887IwZthCIOKMege1q0KnliIcfNVW2HNERNKEWMRxqBwmDG5LJ8OX60XOfOvGAW/7pdKumaiOXpqOcVJsSy6e4hSADz/8kISEhJLtnTp14uOPPz7vtICkpCTmzJnDSy+9xLZt25g1axYLFiw4537Z2dm0b9+eJ554gvvuu++c7S+GN954gyZNmtC5c+fL0r/k8nFFQsonTJjAE088QVJSEjVq1CgpLtOrVy++++67coI7Ly+vpBhNMadPn0YikUiuNSoFiX8Xi8vlwuv1oigKer0evb68eNNoRAXot58U4by24ECBqXPhP+nA8exe1BwPaBWM99dC37lymaJdFzdwX7lNqt1bvvz4WVC9ftzLk0vENgAeFc+mdIz9YlEdFfRf4EX1qZzn1M+KproFJdIoBFYRhj7VcC1KBJ+KP9GB/bm9WOe0RAkzorr9qDluPDuz0MXZcL5+qMQYoG1hw/y/+mhCDTiyfGQd85B6wMN1bUwERWkw2QxYpjXHuy8HNdeD/qZwlAoMEopWgxJmRBNmRFVVTu11s+TBU7gLVKxRGvq8FcG3zwYMHNvm5hNRW0/Dnme/+Aqzffw4KbtEbAPs/rSAlvcEY65AWNmzfHwzKpPEbeK4VL/JyK2Tw1gzNZuja0REwG9L7cQ/HEzcQCtvj9Tg0SjYQpQKUzdMRnHdjhkU2ObNcoPbD4qCV6/BFKbHn+7C+UagIpp7USLaGkFo2kbicar4vXB8o5NqNxhofrsFU6gVS3hZQ4hGIyJEnr9XiNri+6Ma5fHrFDThRnyny66TpQSXvSdiIkVURqEThnRXsWpUPLkG8mK07P40n6Nrxf7B0Vq0BqXomPv5bHAa9W4xE9VQz2eD00r6i25qoCDVh+oDd4GK2+6HyIACjQgRHvmn3hZV7jvdAKP/E0iLibLBkkliiTet5q9DvBVFiO4He4tidjWrCEFeepnBUCuE1gmshPB30rKBqEq/8AfxvntrUYxR8v+EXxfCj89BbiJUqg63TIHmg8693znQ6/U8//zzrFixAqv14qKdTp48SVJS0gXvt3LlSjp16sTnn3/O0KFDhcH1b+bxxx//2/uUXBkuu+DevHkzTqeT7t278/XXXxMZGTDXRkVFkZqaWm6f+fPnM2vWrMs9NIlEIvnH4ff7cbkCQm/r1q2kpKSg0Who0qQJ9evXx2isuDJ1RWHZf/ldeR6cs44IsQ3gU3G9f1QU4jqjSraa4wFVRTFozsuDrIQZy4vW26qihJznnx0FCK5AeBZ5izUxZpRKetRcT6D/3tVKPr8UNDYDQTOvx7MmFf9pJ4ZuVfBsy8D/R6lkeYdPrIkdZsSf4sD+5G60TUPB4S3jefftysa3PxdP8zB+npnD/hWB8tA9poVRv5sFrc2AoV1U6SGgqiqolISWl37vyPTzzTOZuAuEUA6rpefouoA4NNs01GpnIj/Ni6fQj0av4Mzxo6rCK22wFIVj+1TyT5dP9Hfm+6nIkXlsg7NEbAMkbnPhcaglYruYnR8VUKeTBdXvR6OD9BN+rJE6TKEKpuCzuzB9GS5c0w7gO5QPJg2aQbVwtY+EnVnl2nrWp6E2tfHDhOwSYXt8s5OMox5ued72lw+753oO1gTrMT1YG/uoPeAS4Q66TpVRKrgew4KBYBAXrBYHsOGNnJIxGawKNz8dijFYHHNVVSnM8fPrEjudnw2l1yvhHNvgJLy2jirNjKx8SqzJVfo8FVPJKoo89ogXxe8sxvJV+ovTUs6H4t+LmMhzt/27iQyFNx6DKcNF9IHV/NdL9kn+Rfy6EJY/AJ6i38LcE+I9XLLojoqKok2bNkyfPp1JkyaV+/ydd95hxYoVaLVaEhISGDVqFKdOnWLYsGHYbDZMJhMZGRkkJyczceJEunXrRlZWFsOHDycxMZGaNWvy5ptvYjCUTylatmwZY8eOZfLkyWzdupX4+HgABg8eTKNGjdi1axcul4unn36ajz/+mKNHjzJkyBCGDBmC3W7nxRdf5MiRI/h8PoYPH85tt93GsmXL+PLLL8nJyaFjx46kpaVx44030q9fPz766CM+++wztFotHTt2ZNSoURw+fJhJkybhcDjIysrigQceYODAgZd0TCV/D5ddcC9atIihQ4cC4kGy9B/B4iqhZ3LvvffSt2/fMttOnz7NoEGXbv2SSCSSK43qV0uEoVJJXyY/tzRut5vjx4+zZ88eqlSpQkhICCkpKYD4/dy7dy8xMTFnFdwXihcf/v7RaP6shPp1KmqWG/wihJcI8R2q24fvSAGFrx9CTXWiaxWGaWQ9NGF/ncOssRkIevl6XEuT8Cc70HeJRhdnQ9GeX1EzRavBeHs1PD+lllTwVqKM6G4QMfVKqIGgV+NwLU7Cn+rE0KMK2saVUBQFV4Efd4EfZ54fs02L2aZBq7swb4MmzIjxzurC2FDgxbcn94wGIpfY7/DiWnAcvCqaSCP+REe5vvzpLlQVjv5cVpj+/EoO1VubsIRqcGT7ceb4MIUqmBU/nh9OoWa4MPSsBqE6PKtOoeZ4RCh1kJ7c5ICHPy/FR7M7hBhs0N3C9QOtHFhppyDVT2G2n9SDbg596+Dkry5qtjOT8EglLDYR3tyoVxA7PgxUN7OEaQiKKBKHbh94VJQgHe5CPyf3uDgT1adSKVZL/ikffi9E1NXTfYwVm8GDV6PBq9ei0WrYNCuXajcYaNw7CL2p/DWgOn24Pz0hxDaA04//gz/wX29DV0FevrZBCF4fJcK2mMPfF3LTsBDsGX5CqmjRmy+uiJ4m1oL13Rb4EwtRwo0oNgOaCgS3GGsueN1gCcNi03LrxDA6PqNSkOojpKoOsy0wBp1RoUYbIyc2u1g9JYfYVgbaPGQmop6RpY9kY8/wYwkXYeem0PLXrMkIVf+e2/+qc7H535JrnB+fC4jtYjwOsf1v8HKPGTOGXr16sWnTpjKh5T///DNr1qxh6dKl6PV6Hn30URYtWkSHDh04duwY77//PjExMSVh5OPHj2fbtm2cPHmSd955h2rVqtG/f382b97MzTffXOY7Dx48SEZGBi1btqR79+58/vnnJYIbhN5ZsmQJs2bNYvLkyaxYsYKsrCz69OnDkCFDmDNnDo0bN2b69OkUFBRw991307x5cwBSU1NZtWoVOp2OMWPGALB3714+/fRTli5ditlsZtiwYezbt4/ly5czYsQI4uPjSUpK4vbbb5eC+x/CZRXcbrebHTt2MG3aNACio6NJT08v+Tw9PZ2oqKhy+4WEhBASchnW6ZFIJP8q/E4fuP0oVt1ZRezVRi3w4N2VjWuRWGjaOLAGuhtsFXqJCwoK2L5dLKYdEhJS5veymIyMjHJrS6teP6rDi2LWoejPLTDcbjcej4fdv+4mNS2V8PBwWkxqhualo/iz3WW8xGqBF8f430o8fd7tWTitf2J6qA6ac+R6ayKMmO6rher2oQk6z7ztYm+6ywd6DdbZLfDuyUExatA2qoSmqDK3olFQokyYhtdC9aolIfCuAj97lxSw/tVcVD+YQjQMmB9JZN0LL3Kmun2oTh9KkA7TY3UDofc6BdNDdSBIi+JVUQuF+PUdysN4Z3U8a0WYsBKiw/xkA1SXD9+qFO5928afv/mxxhowBCmoKmj0Kt4MN/40D6pLQUWDY/KvwvgBeH5MxTK5Cdo4BX8KOKbsx/x0Axr2sPD7KvHQmpPkRWeC5ndZaNjLyhf3peH3QlCEhvj/mqlMIdGNClDvtHH8kMrBbx1cP8CKzqDhxvuDua6NEVeBH71ZQ3gtPZYwDf50J67PE/GfcmK4NRoahnJdvIm9i+3i3Oqgw9OhoEDbRypRKUbH/uV2brrDiPLqPlyNQ8lpUY11b6hujnIAACAASURBVOdSmOOnUa8ggsK1uPJU9EVRGP5Cr4gUcPpQ9Bp8v59h1AA8R+3omwejaxeBd4Pw/mobBKO/ORy3R0WrB18gyAGdUcGZ62fx8HTuXVqZiDrned5VFQqzQGcCrxvl+DqUbbPRRDeD6x6BoOrl9/F5IPMIfD8K8k/CTY9A3e6YTmzAdGwtIY3ugKAbQBdITDeHauk+JZzNs3OJrOmlbicDvkIn3hwHd72hx6uGoqK/KCORRHJNkJt4YdsvEKvVyqRJk0pCy4vZunUrPXv2LFld4o477uCrr76iQ4cOhIeHnzXHu0GDBiWpsLVr1yY7O7tcmyVLltCtWze0Wi09evRg9uzZZGRkEBEhlm1s3749AFWrVqV58+b8H3vnHV5Flf//15Q7t6ZXCJ1QQigiSBMBERQRQcCComtBdEXBVSwsuiso9oLYsYvYBURQRKSDVGkiHRJCTb1pt039/TEhIQSU3dUt3999P08euOfOmTkzc2bueX/K++N2u8nIyKhOnz0RDTxr1iwAgsEge/fuBaBNmzbIp5R02LBhAxdeeCExMbbF6v333wcgKyuLlStXMn36dPbs2UMwWNcAHMV/Bn8o4d69ezdNmjTB47GlSTt06EBOTg4HDx6kQYMGzJ8/n+HDh/+RQ4giiij+y2GZFhjWWRHFk/tYhRHCM3OxjoVw9E9H7p78q+JU/ymYR0KEnttV/Tn07C68z5+D1LLuWI8ePVr9f7/fT2pqah39ipPTcnRdRw1H0AMqYoWFvDOI0jO1mpSeCl3XKS8vp6Kigj179lSn9BwOHaYyWEmfO7rg9XmwJAF9WymWbiJ45WqyfQLGJj+EDDgLcTXBIf7qvbUqdcwyFSMngNTCB7pF8JHtWPlhcEu4722F3D0JSxYRT7MfQZEQTjpdtdKsJtsA4XKT7x/xM+y1ZERJQAtZIIC7StjK0k2scs0O13ZJ9vlilwYzC8N2DnnIQGzixftSJ9uwoYiYJSpmYQQxUUG5pRn6D8chZGAZFs7rGqPOP4rrzkwiXx7C2F5FJIVcWj+UzcLPNfYsDJHRUWH4JC+Rx3+BwgjuFjEoVzYgXEW2TyDy5WHwLCP85efEvvsh6teHuej+TMIVJnnrwqS1UUhs5qDheU5WvliGWRUl3m98DObnubC0wE6Fn51H0xuasaPUhxo0MXXYOT9AvQ5OcldH2PtDiKRmMr3vj8e57CjGQnvuhbaVotyeiSM2gZ53x7FpZgVdR8dQcUzng6F2TWlRhmGvJaP8UojqVzEvacgXI4urx7J2ejm974ujfkf7ZpkBHW3xcSLv5oBh4biqIVK7eMzDoZNuLjiaeLC8Dlx3tIAbG0OgBPxbEd+/Eufln9Ll1haseb3GQ9/5phh2LwxiGbD+nXIunuhAjvmNWOVgMez62q4hGN8Y+jwMq5+HvNVw4AfY/B6M3Q4x9Wv3CxTC9C6gBk5MPph/F+ycY3/eMB36Toae94OjRjHOlyJx4YPxhP0R5txdRv4ODUmBC+4waTtUxpX8byijEEUU/ynENbLDyE/X/juhZ8+e1aHlJ2CaddUw9aramS7XmZ+5k8muIAh2es9JUFWV+fPnI8syS5YsqW6fPXs2t91mh8qfrL1yKnk+MbZnn32W7OxswDasx8XFMW/evNOOTZblWhHC+fn5uN1uHnroIWJjY7nwwgsZOHAg8+fPP+N5RfHvxb9esPRXcOjQIdLT06s/O51OnnrqKcaOHcvAgQNp1qwZAwYM+COHEEUUUfwXwyyOEJmZS2jqbvQdZXYo81nAKlUJjN+MvqwAY3cF4Vf2oi3NxzJOJy/9n4W6uK5Ohbqk4DRbUm0NBzhy5AhpaWl07NiR1NRUZFnm3HPPrTZg6rrO0SNHmTvva75e9A0Lty4l1N5JeK+f4qIi1q9fz969ewmFaghMKBRiwYIFuFyuOvoZpaWl0NSNkOIkNGErwYe2EZq83U5NPeWXQmzm+13qXVthA3VJPoE/byT89E6MjX7CL+6xyTZAyCD07C4iBRoLJ/kp3KOihmrfY8uwbPJbFMYs09DCZjXZPoGyoxq6avH95BKm9zvKB0OPs2dREK1UQ19VSOiZnYTf3Ed4Zi5mqYpREkH/sYjQpO0EH9iC+v1xLL8KbglMCDy4BTQTY00x+rpiBNW0BeF8DqRMH1afNIyHOiA28NSQbQALtA9zaN3TXnx1ucaN+uLumjz3Sq2OcQNAkAQsTUPftIXgi88itXWjxEhc9nQSoxfWZ+grySQ2diA7QJRqFmFpzWWMpbXnmjU7j6zeCpZhsHZ6OeVHDbbPCbDhvQpKD+nsXx7ms5sL0Ps2RMyoIYn6gqPoJSpFezUufTyRzAs9bJxRk9Nu6rDkyVLUBjGIjbwc3apWk+0T2L80jKlBwW4Vo1wn8s4BMOzFqzb/KMol9ZDOqUpA9snId7ZCjJNxuEVERwhxyZ8Q32uE+NXl4D+AMrMH514tM/LjVHrfF8fwN5JxxYps/dwmwJIiIKx5ASqOnWb2nRi4Ads/hzm3wKE18POn8HYvuPipmm1Cfji2rW7f41tqyDZAxnk1ZPsEVj0D4dK6fQ2DNa9XkL/DfucZKiybZhCq6+SPIor/W+j/ODg8tdscHrv9d8SECRNYtWoVBQX2O7Bbt2588803hMNhdF1n1qxZdOvWrU4/SZKqifjZYOnSpSQkJLBq1SqWLFnCkiVLePTRR/nss8/qkPMzoVu3bnzyyScAFBQUMHjwYI4dO/N7q3PnzixfvpxAIICu64wfP57t27ezevVqxo0bR79+/VixYgUAhlFXYDSKfz/+UMI9cOBApk6dWqute/fufP311yxcuJCJEyf+ISp+UUQRxX8/TL9NmtUvDqGvLCT44Fb0X8682jTLVLQNxYQ/O4h5JFRLLAtA++6YLWL1XwaxWV2VaLGph8LCQgoLCwmHbXJpRQxiYmJo06YNcXFxZDVtRWzASfPNXnoL7biy3xW0aJyJ0+kkUlFCJBRk9Y+rq39MQ6EQP25fT6SpzA+LF1NUVMSWLVtYsmQJoWAIozRC3sE8LMtC07Q6VnNZlhFlCX1LCZZmgSKCCfrKQpy3NgeH/a4W0ly47sj8h0pvWREDsziCvr0UMz+MWWVYsQI6kRk1hXjF+m6MfRW1O6smsmmyY26QGVfm48/R2fBeOTvmBYj4NYztpQTu2UTlzesJTv6ZOLdJcmbtsfW6J579S0McWBHGMiFUanu9haAOLglH/3TEFBdyh3iMI0EIGITf2GfPp6proK0sxAwZqBtLcF7TmMineWirChHcEsEJW9GXF6LNO0Jw4jbCJSbfv1CJpdddbFmqiVylWB2fIWHm1hA281gYMdmJcHJ9bREcl/gIf2zXUNLWb0Bq7UJ02TnYvhSpum62UK5x7hUuHO6q31XjNIs93cQTYxIpM9j+VYBGXV3sXlg77DBQaFJZbGL2q/HoCj6Z1DZO8taFKTtiECgyaivIA5UFBkKKC8uvEtegrjhaQhOJfUtDfHZTgf38nmxbCBmEpu7CdXcrPO90wfNSJ+QeyTiTq8IX9Agc31p7h6aOs2IL3mSBZhe4WPZ8KUufLgXLDi0/7wYFadMb8MusutfhBILFsP612m2hEig/ArEnaZi7T6NE5kuv23aWUENw9Oe6xpWSnOjiOIr/4+gwEoa8CXGNAcH+d8ibv0v+9sk4EVquafbvzYUXXkifPn0YPnw4l112GfXr1+f666+v06958+ZUVFRw//33n9VxZs+ezXXXXVerbdCgQUQiEVauXHlW+7jrrrsIh8MMGjSIG2+8kfvvv59Gjc7s8c/Ozub6669nxIgRDBkyhM6dO9OjRw/Gjh3Lddddx8CBA/npp5/IyMjg8OHDZzWGKP5Y/FvKgkURRRRRnArzcBCruHborPrFIaSsuDqh4WalRvjN/egrCsElIj9cV+NBiHWA9M8b8MygjlUUQd9QgtjEi5TpQ4z7x/N+T4WjazLad8cx99veQLG5j3CWk4ULFwC2V7tX955wLAIxElnhDNomN0Rq6iP0xA7MnKqc2UYe3H9tQ8QM8OO00WRd/ziyLGNZVnWonN/vxykoXNF1AMbuCqy2Lgo0P+FACL724+5pE7m9e/fSqVMn1qxZUy1m2bVrVxyCjNjEh3NkY8R0F/r6EtQvD+G8MxPf9PNAt8AlnTFk/XSwTAtjdznBR7bb/cEuPXZJul0i7CSPrpFTidQ2DmPLSR5Bj1Rdk9oyYeMHFbhiRTZ+UEGrLkkE39xvj7e+GytgoC44ytWvZjDngVLKDulc+mQi7niJo5sjDH89hf3LQmx4r4Jed/kgoKMtL0BfZecGM/cIzlubQWZdI4mxvQyjRxqbczx0H+Ei/MpenNc2Rv2udsi/Va4h5FbQY0wcYpKImOHGPFITZSBemsHPi2yPdsE+nUbZsZiHawxI4Q9y8EzOwthajlmsIrURCL4xDWO3XRbLeXFfxJTTy1BbAriPlXPTjER2Lo6gW+BsF4fxc40hyzEgnfBbr8ENd+JJlAiXm8TWkyksP8mAJYDkFCDZZZvlRQHnLc1wNXPypy/T0UMmJbk6cRkSZUdqCGLWZR5UQ8DZM5VYNFpc5GLv4prSWF1HxTJzRAEOj4jpc9gRA6Ga/kITH7oo4kyuef4jFQahUgt/rpfEIWtxbZ+Kc8MT9peSg0q9Ifk7dSqORxgwOZHcNWG0kEW7oW5itk6AQMGv54ZKDvDW1ZLBnWiHiAM06g4JzepuE9cQWl0Gu7+xPx/bAm2Gw46TCH7PB8BV9345YySa9FAo2lv7uie3/hdqCEYRxf8KOoz83Ql2gwYNaoV0gx1avnv37urPY8aMYcyYMb/aLyEhoVYodteuXav/f0KT6mRMnz69TpuiKKxatQqoyd8GGDZsGMOGDav+fGJsPp+P5557rs5+Tt3+5OOPHDmyjpj0zTffXC1UHcV/F6KEO4ooovhdUKxDkQHFBjR1QKr8G/z3dHm9iggRA3VRMUKsA6lljE3uQoZNtsFWLy5SkTsnop8oF+QQcI1ufmYV4d+AZVoYW/yEntxZ3SZ1TsR9T0vE2H+NdIsJCp5JbasJVYUQYvGGZdXfFxUVUZ5fSkpiEsEHt2EURdAAIVHBM7ENgQlbQbdrP5v5YTQq6HDxWGLFWAadcyGGLHKk9Dgbd2ymX8++yJsDhF+qqVmcOqw+wgAZ80Al6UOaVSufx8bGMmjQIEzDxKU4cYQFyFeJfJqHvtomoM5bm+Hol4aY4MQyQarn5h+FVaYRemlvNdkGiHyQg9g1GWQRqUM8xlabYKvzjuL5WzbhN/Zh7Cy3vem3NSdYXkPKJaeArlq0GeDGqtBwj21J+M39mHsrEBIVW8zNA8NeScYwLNa/XcGmmTWhzxdPSiDrMjctOtn52ifIttjEi3lzC4qDIoqsoNzTBt7aA5V21ITUOoZfVmmsfTdAtxEuEGyxOsEnI3dPAt1C3+IHUcCb7cMnmZjHVDxT2qFt8mNs8mN0SUVoEUPFF6VIDnDFibjubIF5NIQQ40D97iiOHm7KRt9C3AdvIHsTiSxaQuSrr0AQUAYPRLzjLwSDDk4uMWtWaph7K1G/PYqQ4sTXwE0HpQhzgYbzlmYYP5di7KpAai2CcpjQt1soOjdIz7FxbJxRwUUPxfPl6CL0iJ3fPmRaEg63QJnbQ9y0brjcFlK8jCAL+FIkSg+brHm9nMueSeKnDyso3q/TtKeLDtf4+PCq42QNiKNHP4WLxoS4YEw8mu7Al+bAn6sRLjeRwhDRTTxPNoGyEFaJiZ4jYfatj+Cs8YxrYZOd3wT5YUqVAUaAQVPupkVWDtLhZYT6vsW6mTLb5hZz06wEZMWgVT8Ft7MEZclNSHvngiBCx19ZgLoTYMDz8GZ30KtSGVpcCimt4bJXbC93ajb4TkPKvSkw9D3bGx4ogLR2kH0ltL0Kcpba5Lv+ubXyt09Adoqcd3MspYcM9i0N40kQueihOFwJv58OhWlYqEETxS0iRgXYoogiiij+Yzgrwj127FiuvfZaevTo8UePJ4ooovgvhGXBUR0+KbcJ9S3x0ECGExV3inW4pwA+rCo/nCDC2ibQ8le4qpjusknOiZBaEZzXNyH41A7MPVXe4EYePI+3rxO6Gp6+D/e4ligjGmEVhpBaxSH8hjfaLC3FqqjEUlUEnw8pLRUroGOJgGYSfj+n1vbGxhKsoAH/RMEEy7CwylSskIHglsAnI8UrBMr9bFi3uTqvOjY2lq5ZnUh0xUHExNEvDX2zH8cFKQiSgHE0hPeN8yBsoM47ghCjIixajvG3KZREVDx33onSfSiN8l00vngwDlMi+N4WhHQXzqsaVnl9dUSHg8DPZXjK4KKs87HcIkq5gPFpAY6+aRjbiwjOOgyigHJFBlLrWCLvHCAyMxfvi+eiry9Balm7fo9ZXlWXO9YBAR2zRMXIDSC3isUsDGOWqMhZsahCAP4Ui7TWg7G6xA4j1i1CBTpfP1nJta+0Rp17COOXMuSsWIRYB+JNzbHcDhyqBrpB3lbbWOFwC7Qb5uWru4o49yoPgkci/IZNtgGsEpXQC7vwvtYZTbPJ47Yv7fnl8AiIEqx+tYxr3k1FWncMzq9Sj3ZLGHdk8em4UiqO2x7XRl0UBozLgid+Rmodi3lhfVZeVQyAHgwh90pEL9fRr27Oz7MqccQIZE1phjsSQf0ir9pAJMTIeJ45B6ldAgX7dVY8XEb7YV6adY5D/PYQgZer8vQ8Ep4pbaicOA6lUwcEjxvR7cbq0Q/X4lXoYZPDO0T0n3zEpKs08ok19bS3lBJ6usZYpK8qwjOlHUZuADFeQbgwFsvahrZ7N2a3vsgvvMW2p4LE1Q/T98F4TMvk5q/TKdilktjEwf5lIeaOs89VcsDwN1Jo2KXGQOaMEcm+wsNXY4vIHuKlQScnsRkya6eXEamw2PJFkFZdA7hGXYRZVEzMG9Nw3zgSy5BxuAWadReRd6zHf9PNWIWFSG2y8H3+KWacA8Vbc5xIucWy52rnwP/wjEbGF+9QebCQte8rBIoEkjMtFj8VZMi0JJxCBRTsB6MCmveDvo/anuhfQ0oW/GUvHF4PcQ0goSl4UzAzr8AqK8c6Vo4QYyKmpiKIpxgKvSn238lod4399xvwJssMmJKEHjZBEE6rTG5oFqFSA8sE2SXgjjtzHfOTESwx2Dk/yP7lIRp0ctLhGh/epLPrG0UUUUQRxe+LsyLc/fv357XXXmPy5MlcffXVDB8+nPj404e0RRFFFP8ZmKWlWJVBEAWE2BhEX93atWeDcgMU3UAJ2PmrglviuFOmcy5UcRGeK4HNTaFtVT3Y40YN2Qbwm3BfPnxYH860PhTjFTyPtcP4uRSzIILcLQl9q7+abAO2V/dAJWJmDNJ5CQSz4wl3sYXFDH+EWI+J5VaxKiuwZAVJOb0asVlcTOWkJwi9+iZYFnLbbOLnzSY8w48ggnNkE6QO8ejHasKDxS6JhAQJ86iO5BRqLVbNMtXOjxUFxPi6RN88FCT48Dbk85NxnJ9i5/omOBC7O2nVtAH5+fkoikLfcy6AJ/cROrwfRHA9mIWrTSyRjw5i6RbK0AYY+ytRP8zBNbkt1qHdVN5SEw4XmDwZaWZLjM0NcfdJs0tpeSTc41vX8vq6722F3DWJ8NTduB7IwtxVQXjaHsRGHuRWsUTeyUFIUrDCBpF3c3A/nI2Q6sQqiIBpIXdNQoi3PW9mSMfcW0lkRg6WbuG8siFCvIPgX7fhfjCL0Iu7a4TCHALypMasmnc7DTteTpO7h2BOPYZQz0V5qcXx7RrrvgjS7cZGWIUq2jY/FX6LFe9EKNhdSfNeLjpf6aZelknPcbG07O9h00cVNOrupOCAgYWAseOUvP+wiVmpsfy1EryJbq54KQk1YKH4REzNwuERsLCQeySDaSF1TMBKcrLuy1A12QbIW6/ivzWWjLe7kLdJpWJ1hJtnJOLwCCAbyCMyqAx7mTG8wPYMAxs/CXLjF6lYPxZV78eq0G2PfiMvsRuLGXB/Fh/eVkKzt+LRF5wkihM0iLx/CO8jk7D8x9H0EHphMeEKhS/uFqgsANtaUcqoWSmIBSHU3WVI2fFEZp+Uo+cSQRaw/Cpyp4SqcmxOtL79KUjqw4+vVwKVdLklhpJcjR9fL6P/3xLwJIuktVGwTFj1cs01NTRYOKmE62amVT8D7jiJ1gNcNOnuoviATkITuyTY9jl2LnhqawexwiHCR+3zC73+Nq7LL8WdmMS1M1NxhgsJ9ByBVWk/68aOnQRvu524rz8DakpoGbqFHq5tbQuXmZimgxVvOLhknIb54wpwe3D17obiFkGMhya9YMQsECAYjsG/U0etDJHSSsGbJNYtISg7baIdV1MWyKysJPzJl1TceQ9oGmJ6GglLFyC3bsnvCVesCLGnl9OJVJocWBFi8ZRSwuUmTXq6uHRKIt7kXyfOkUqT5c+X8stc+37krYuQtyHC4BeS8CRESXcUUUQRxb8bZ0W4Bw8ezODBg9m/fz+zZs3iyiuvpGPHjtxwww20b9/+jx5jFFFE8RswCgupuPsBIp9+CQ4HnvvuxnvvWMSkxDP2KTMgZNkpmqkylBiwOABvl0GmJPCABElPbkfunMSyQY05btQsUnVgShE8lgxlpu31PhUHNIj8hkCnGK8gXpCKWViEpZUjOCMIKc4a1WbArNSRYx0EH8jm4WKBdyoEBOD2FBcP55fhmZRjewcfbY0VZ9b1QAFG3mFCr9TkWenbfyHw3IvILW5C/6EY/Se/7cldWgARE+UvLREzYwltL0dIc7N/q07mpT48iRLG8RChZ3Zh7q2w86rvz0Js5KlexJtlKqGpuxB8Mo4uSQT/tq1aHEr41kHaUy3pck42kuhDnF2AXlUGSYhXkOq7CYzbVO3RDz+3C/ej7RAaeaD0GOHPq3JDJQnnoIE4evbBqixFatMaK2Rg5odw3dKMyMzcWl7f4OM78D7dgeDjO6A4gvq5ndMqtYzBOB7C83QHrKIIgk/GqtDRd5QhtYjBSnIieGXERGf1tbOKVYIPb6seY+jpnbgntkFs5QOXVFuVW7OwviilcadhrP/gL/juaUza0E5oXdJY9LcKOgwWaX9BOdqqTUjNGqN3zuCLUX5K8+ww7o25lQSKTfpOjIO1GmrIpEkPF7k/hmnYxYXpEJFaxNQ+piIiuKHvGJHFLxuU5Or48zQ2z7Q93T3HxdKmt0LkpR2YJSqev7ZB1cE/va5CfuFeDU+Ki/qdXLCxCFm1UOcew7QspJuasfHjymqyDXYJsj0/hGidHVcdJg9g5oeR28djHgjg/Cmfm+dk4CwMETrleGZ+GGN/EVacyMIH+1Cau520dr0Y+vJHrHjRiT9Xp2EnBdfRcoJeJ+H4WBwhCXlYY3hlJ8J1iehNdIJFhxDTKnE63FgFfjAtjJCD7/4eIlhsT8av7y3mhs/T6DDChyjA3u9DLH26lCHTkuuoi1ccM6rnsFlejrFnP5GXX8fR63wa9+uDmltAu4ua4nWKpHSIIa6eiFpQH9farRjvT0csOoZlgeQQUAMWPiFAuLKy1jG0tetBq31gh0sgva3C8e01Wg9NerqQXTBkokp5t/OxSu3rbDRpjHPNEqT0NHtDdzyBYoPZYwrJ/0WrahK5/rM04jJqL33CZYVEKkqwLAtnTCLu+FSssnIq7rgbqkQJzeP5lI8aQ/zXnyEm1RgFzIoKzMIitDXrkdu0RmrYADE5iTPByC9AW7sBIycX5+WXItZLR/R4TrttuNzkmwdLqp+13FVh1r1dTq974pCdZ9a81YIWO+bXFsI7vCGCHrIg4Yzdoogiiiii+INw1jncpmly8OBBcnNzMQyDpKQkJk2aRJ8+fRg3btwfOcYoovj/BmbIgLABThHRYz+e4TIDNWihRyycPrGOd8OyLCKz5xH55Au7QVUJPvEszkEDULp3pUiHFUGYF4DLvNDHAxowqRByNAia8G49WBqEP1dVivoeka9kJxvubk3sy7sxBzQEah/XAF4vhRf9sK4xeAQInkSwH0ywSCrXMIK6LXrlkarPqXrspomxey9l149C37wVR59exLzwEuGXi2zvqkdCzra91qs0kTdPErB+tUxgQIqHPlVh6ZEZR3Df40RItj37pmERKDIo3K2Ruu+XOtda37oV5URFkKr8W/fENphHQxA0CN+1EQFAhNbjW2OuriRiWchZcVilKvJ5iShDMrCCOlZxBBIVBMlW9jYPBlGGNkD99mgtJWarVEPdlk/hrtfodM0L6Dk1udbK0AZoKwvrhM9ri/Nx3ZCOtn41jp494KXXSfjmG8wjsRg/RxDcLpTLGmBFDMRUF0KsUuP1lQWUa5KRWitYoSO4x8dDkpMTlUqskIHSNYngxG3VCu9SxwRcNzdFW1uM48b6GMdyqPz7m4ipqbjvHI2+qrLuGFcXIrVPgEBdlXirQsfpsQ0/B9Z+BH36smBsKUlNZbp02kmg45VQVYLFseNwNdk+gd0Lg/S+L552w7ysnV7O5o8DpLdzkN1HwagE19gWhB77xa7f7JVxjclE++gI1pEQA+7KZNkMFW9yzbyTFAEppxwjzyYkwYe34bisPu2GpJO7Oly9nSBB894unPNzEVvFImXHERj3U8399MkInBJKXDVfOKVkmqNHMnqVUcDcW4H7sjBCfRd4JAjWWKscvZNRetUjHCgkVGJ7h/N/XsH+xVPoOvpqjJBMetNzUQMin91dSvlRu2+rS9z0mdyMHYueZufr0+zzdDi55PEfUB6dTmT2XJSBA7j2hRf4+C8iIb99EtvnBrjorwn4D2p8+1dbDyFSYRLXQKLscM24WvR3I1cpn+tbtuHvPQAEgYQ/j6LknPNxjbwGIRikmW6g957KzBtLCRabSA6FfvfeQ2YPC3XZSlzDBhPfQCaU60aIicGqqHmgHd27Ijhq5y97EiWueCmJ1a+WOthwXQAAIABJREFUc3RzhEbdXHS7LRZPvEXFY69Wk20AM/cg6qLFuG+oUQsu2KlWk22w1enXvV1O37/GI1fdo1BpPkseG0bhjh8BSGzekf6PLcBRWlZNtk9A//kXLLVmf5Zpoi1bRemQqznxULnvvA3fY39HTKgbBWgUFFJ62XD0nzYDUHnfRBJWLULp1qXOtgDF+7U6z1re2giRSgvZedouNgQLxSMQqajpLEj2XxRRRBFFFP9+nFVZsKlTp9K7d2/efvttBg4cyPfff8+ECROYOXMmH3300R89xiii+J+DWaZiFoQxiyNYkbMr82KWRAhP30tg/GbCL+/BLIwQLjNY8WIZb/Y/xruDjvPJnwqoyK9NSKxwGHXB93X2py5dQbkBfyuE4Ufh/TK46iisDEJhicrf80uZueEwn+mVaJUa0/y1+x/V4aDTgVUYoY9gkHLSYk0Cbo+H2VXca3IRLGoIvdzQ3AGvpMK1wRDBv2wicMdGKketQ513xL4eas31MAsK8V88GH3TFrAstKXLqbjrzzj/lIqjfxq+aecixCvoEZNvKuu6yxcgIzayvUNmuQbIaKsLCX2YQ/lhjU9uyOfQ6jKk7j1QLukHJ5UhdF5xOVK3BJRhySCC4JXQlhUgZ8cROTmf24TI9P1I9dxE3jpAaNpu3Pe2wtE/neCTOwk+uJXAPZsxcgJ2zU2ngDA+Gz07AeF0ImOigGXpHNsbgQ41EQhCrIyYVHcVLdZzEZr5AYEnnkVwKsTPm4WxIwb180KMneVo3xUQemYnBA3Uzw8BFlKLGMQWMbgnNEVd8yElHTtQnN2J0suvhMI85GsaISQqiM19RD7Pq1VOzdjsx4qYCF2SUHNzKGnfhdCrbxJ4ZAqBj79CSK97TmKqC+tICCHFiRBzih23j4cDG+z6oglNzyGtpZf0bIWe16uo48dVk20AKVhWhxTEpEkIAlgGbP08QFJzmSETvPhm7sT6YD+ROYdxTcjC/VoHPH/PRl9ViLasAHNvBZEnd9LtOjdlR2qOkb9DRayoiaDAsmtAZ6Qa9JsQR2JTmfR2Cle/kYSyuRB94XH0zX60hcdqGU+MdSV0usqDdBJHdMYItOzvQbmuAVJ2HEI9F8rVjRCb+tDX2mHmUlsHlhrEKC/E/WBDpPbxCOkulKtTUS4qQNyZidt/H4NfWFgz5u3LCRXuYflTvTHFCOs+DlaTbYDd34cwfRF2fjOtZnxahLXTxyI+OhGpdSvU+d/CExM576qaZyCxqX2vjv1c40Fe+VIZg55NIvNCF7H1Jc4Z4aPvgwk4fSJmWRmBKc8AoEx6lHBKK6QFa+C6W/GMG4PVawDfTa6s9qIbGix6XkeLyFQ+8DBmcQkObwBXQye+Lz9DrPJGy22ziZ3x1mkjcnypMn0nxHP1e6n0ujfONjiaJlZRUZ1tzeLaL7HKgrrv3orjBuZJwQxHf/q+mmwDlOzfTO6qLxHS0xBiawQc5HbZOOd+R8BKJFAV0mMWFFI+dnw12QYIvfYWVkVt7331+A7mVZNt+wIZVE54BLPEf9rtE5vUFVCr31FB8f66AJorTqTXPbUJ/3k3x6D4/tBKsFFEEUUUUZwBZ+XhLikp4a233qJ169a12j0eD88///wfMrAoovhfhVkcIfj4Djuk1yniGtUMuXdqHe9urT4VGqHnd2Nssz02emGE4OEQ8oRstn1RU6e3NE9n7Zvl9Lk/HofLXjwJLhfKwEuIzJ1fa5/Khb0pNOGtU1JczzU04j/OQVhsu7NdQNy4llzVLpVH1doLMp9oYUVMkrb7+altAu+HJQoFgRvjBV4rEzhYtXD9JgAtFJiVYYebJ4c0IlP3YfmrFvImqDMPIndIgGNBpDbxCKKAFQhiHj5S65ja6jVImU4c3RshKDb7KsvTuUgSeecUL/ul6FgBHfniFJTLGxB+5wD6qiKkfuns/DbINU/qmK89Tej23TivGY5n3B2UjrgJ93VXIbfNoqRNNp5x43Defj1iIy/6tL0ol9QDtXZ9XKtCqy5NZR4MIjglQlN3VXt0rTKN0FM7kZ/syMGfVDa8qyK7BHqNyyAh2w0b/Ogr/Qg+B862abSqfzs/fyvgvSgVT5mGuTIfY38lSv96iE291aXAhDQXjotSKG//MlZhIaWXDiVpxyYiMwprz59DQXCKGEeCWEYA19gU1BU/Elm4ENewgWCqhF55A2P/AQLPTcP7+GSkW0yEJBNjfe3SbADa0TB5AYnUmS/WzKdHn2CfMpBGcT5czbyYB2rGqFxaD/WHfNSl+Xie6kBk1iGsggiO/ilojcLkf7CCuIataXnejRgv7GLgxCysiE6gYQbyc68i1quHuWkD1vfzOX/MSFa9bHs+RRkunpSIJ1GkstAmOT1u9CBvKsDxl1boG0sQvBKETYREmeCYn2rft+NhPF6dimM1DOvA8jCXjE1G++hgrTrVTkOnZXkJTcfEIYjgqWcSfPqA/WXYAG9tQ4NVruEqrOS6j9LY/lUAh1uwhalSJDSvRemg46Q0OQ/yVcKv7gOHiKNvIkJSKVbYS+jbxXBeD5yjM3A4/AgVTyHkfgiWilC+FHf8Zrre8jzr3h1PSlZ3/Hl2lEagtICSvNohy5IMamVdkhcoPIS/1EvM+3Owrr4EbdEiGoyZAggkNpNp2c82VqW0rCF2SQ1MfJE8+t+gYSaloygasiMAxIIogtOJY+xfONz0Wn64qgJDA29KLNdMj0O+JJOiN4prz00dIqUqUtssAloZG194gPLDu2l35YM0Wr8M0QJcLqTU00QLVMHhFmsJfQuKgufesYQ/+QIsC6l1K7wP3INyUW/MwiLEFFvnoXE3F5LDJv4n0PE6Xy1htuL9W+ocr3jfJoQBt5Gw5BvKbrwdwalgvfMVsx/RKN6fT0ITmcFTk0iIl7GKap8vloWl1n2mAKzQqUkEYFVWYhmnN8q64gUueiie5c+XoYct6rVX6HFHbPW7/0yQFZFWAzxkdHJydHOEtDYKsfUlnN4o4Y4iiiii+E/grN6+d955J59++ikABw4cYMyYMRQW2gu+nj17/nGjiyKK/zGYYaNW/iwRk/Br+6CibqhtLahmNdmu3lduAEE362xauFurJSQkCAKuoZfjGnMbyqBLkTt2wPPwg8gtMxGAU30hCapRTbZPwPogh/EOvZYF7iKXRfLxEHK3JOQ4hbjb1jP+/V08NWsfcUGN908h8kN8kCxDugyiZtkk8BRYpSqhNw9g5ldgWRaC24VwiriblNkcZBmrvBR19RoCP/zI6ldKyTquM9pjImFbCu+MtejiMpEvCKBtnEr4vWkol3oQm3qx3BKtuwZQhw1AffddtJWrqbzrXrSftpD08zrkjudQ9qfRoGkEn38eqYmBsd/2MpkFYcTmtcckn5uAseckVTjJrgl9MgSXSME+nfn3lZC/Q+PIJpVPRxUSdkrohz/F82RTPM90wFxWhm9pAq37ufnkDj9brGTCE86lsFkapk/GdXsm7r9n436oDZ6H2xCZ/zVW1fsW0yTyzQLktqeIwwkgJip4Hm6IsX8XpYOvpnzkzQQemYK/70CUPhcgdz4XAP2XnagLvsPf52Iqx9+N1PWU/FFFxGzkI6NZCO+dt5H442K8Tz2Geckwlrys8+X4UsqubAUPtUf6e3t4oB2/rNZxXtUQ901NMctyMfI/h/hVVE6+BW3iI1z5/Db6j5qH+XIxysVe2LoWiguJPPMps95tzVu3e1m05RKES6+g/RAY9U0qV70Vz+jvUqnfQUIQBRSvSNthXpIzHTjOSyI4cSvqZ3lE3s0h9PRORCSElFMiBLwylf5DXPKoSWprB0nNZC56KAG9VMPzZHukjglIbWJx3dcaIdWJo3Mi3iZOXG0dhF/aW03I9c1+HOclIpxUf1yId+DKjsGbItJ9TCxdR8cQV19GlAScMQkkte9ERCrHLNuFcqWKa6wHbe9HWKEgoicFR5/h6K4GbFvuQAg+i1D8Dlg1RE0IbaB57+voN2EOnQdPIDa2Pu6ENIpzlpM1sDb5N01wxSXhTqxXq735haMI5Hs4tMuF8shjyB3aEpcZyy1fpjDi/ZTq9BRfmkTX0THIbuh1o4qz4hj6S88TbN2M8s7dUL9ZgFlejhgTg3fyw0g33cai57VqIhsoNPnusQDlBQKNu9e+B85YAcWswPniYyx4oBd5P86hNG8HK1+4kc0LpmKlJf8q2T4TpJaZJPy4BPfYO4j78C2Cr7xBUeMs/JcMQd+zDwB3ksjIT9NoeoGL+ucoDJ6aRP32NffQNCyaXHBtnX1n9r8J0eHA0akjCUu+wTl/EV//XaN4v/0e9+fqzLmziLAZi/vWG2uPK6s1puIlWFKXREstWyDWr32PPA/cc8acb1eMRNsrvNz6bT1Gf1+Poa8k40s9u0xAV6xIcnMH7a/0kdZGwR0fjSeP4v8f7Nmzh1atWrFw4cLf3vg0OHToEBMnTvyH+syePZsJEyYAMHr0aPLz83+jx++Dk497Mm644Qbuu+++Wm0vv/wyL7/88u927PHjxzNkyJDqvwsuuID+/fv/U/u64YYbWLdu3b88pjNdj/80zopwT5gwgWbNmgGQkZFBly5d/uGJGEUU/18gZGDsKq/TbBytSz5rQaBaBboaThHJJSGc8pS2usSDM6Z2o+COx3fvZNzXPkPsG3Px3nM/YlIiMSKMOUUkxzLrhmZbYQO3ZbGnocFb8QaL65t8lGyQGivhHNkEyzJBEtDXFiNgkSbCsgyTHm7o6ITP61t0cJ00Hq+E3PWURaRLREhUsHIDmEeOYeYXICYmEPvRO1AlGiQkJhL3yXvgdlP5t8fw9+yP+vU8JMli6Z8LuOb7SrY6NbY6NSZoOnGb11Larx/hGR8TePQp/Jf2x/XnFGSfgMcqwcw7VGsIoTffxSoqxsw7RPzsj3HdfAMA+r79OHqk47i0HpHP83CNaYHcNxWxgRvHwHoo1zRCrVKCFpv7MI7n4L6r9sJZ6J3Gls8CtdosA/at0jA2b6F81Cj09Xmonx5CW5RPzAE//R6OY9eiCHMfKaO8BCI/lWIWRRAbuhGbeVHXL6Zi9Oha+5RbtcBxUUotS4pjQDqmHiD40qsQCKBv3lrzpWkSfG4arpF2mSLnsMGoCxYBoC5aAhzAeVMDxMYepA7xeJ5qi0wJwT498fe+hJJuF2KpKv4im+RVFhh8coefGeMDzHtVZd9GHS1gIcgiVqSCirvGE3z6GSonPIhVUYFr5DXIqoFTFnGOSCL0/jOUDryMiObmy3tC1TnbeesiLH7TgWgdJCEwgsZyG2Jy6yGb2zHLVByaRo8RLjyJIuq3x0CrmcdWYQR9VxnOCc3BK1fPN9e9mWyePYlIZSWXP5/E1e+lknWZG/FwwFarbx+H3CUJbd4RguM2EZ62B80ZZN1Hf0HofhKp1S0iPxzH81wHnONb4LqvJd5pnYjIEps/rmTGsHy+uLWI49tV9IhtiXHFJhNTrwlKp3ORmqeh79qM5647INKCwG0b0P66BcfrO2jX14EeW5N3XI2kkVhrVFK1DoiHyqm3YC+XPjAX/4HNNOzmpNvtMfhSJZJbOrj8uST0MjcDHphDox5DiWvYmi63T+ecfndQb9GzNJ53L66WGcTN/gphbTnOj/ciLT9uq+1jq46fd3MMN81KRynYR2TREsIffQa6jllQQPnIUZj5BViRCEaDTFRPSh1htcLdGrpq0fXWWJr1ciGIkJzpYMQbPtxJDlRBq85LP4EDS2aiBmobGs8WYkwMSrfz8E64l7IbRttpKYC+eSull1+FkV+AwymS2kph0LNJDH0lmZb9PbhOKpsQ8psc2VSPrmNmElM/E196UzqPfouY9DbV20ipKZg4KDlQ+4TLjxoYuoD3oQfwTX0aR49uOMf8GfnDOcz4s8mXtxVWR2VU7ys9jcR1y/Dc9xecQwcTv2gezv4XIghnDhF3uEV8qRJx9WU8iVHSHMX/DcwuWkiXLUNpsL4HXbYMZXbRP0eMz4RZs2YxYMAAPvvss3+q/9GjRzl06NBvb3gGvPXWW6Slpf3T/X8vfPfdd/zwww9/2P6ff/555s6dy9y5c3n//fdxOp3cfffdf9jx/pdxVqZSv9/Pn/70JwCcTic33XQTX3311R86sCii+F+E4JGQ2sfbAk7VjSA1OL0KbfUmcQ5cY1sSemJHVbkpcP05E8sjMez1ZJY8UUrQb9BumJesQR5EqWaBZhkW2vpiwlN3V7fJ3ZJwjW1JTKyDvyXBpV74NmBxqRucIQGjVQzG7hrBIuWy+pgrCkhZVsDNE9sQfnk/xtoSAti1sN0PZOH5ezZCooLxSxnaHRvoWM/N7OuaIGTHkeKRTk6PRnBKOK9tDBET7ccixDQXrjEtbOXuGxqhrV6McskFCOlpKP37krx3K1ZlACHGh5ichHk8n9D0dwDQv/yCrnPGsucH2PxiGbxYhi9N4uYPXQSmPA2A2LQJzquvxCopQd//C9qWH3GfM7LOdRaTEtF+2kLgiWcJPDOV+K8/R1u3AUeH9ohxTpy3NMMZMkAA1+2ZEDFBFjAPlyP3iEdIBqmRSenwK/BNmYR8YSf0pQWImT6UbokkHKqrdB2XamIWFqFv/RnxhRpDiTVzP83e6kZSUweVxRYlOSpaVgy8txvXrc0QE504sjogNm6ElJ6GcunFCInx4HIR+ugl3JNvwdwXRKzvQqjvQ1v2A+q6DTh6dK0zBisSQfB48NwzFudlAwj87bGqLyzKrrka7xOPolx1Aab/OGZRiOATz+EYeQPC5cOxKirQ3n2V5Bs8IARrFNTLTJKayyBYdBgSgEg5VsTCrCqtJmU2J+alZyn/020YObkIPh8xb70KTtuwpOFGPSUv/+DaCLrQEAI/gWobOIR9t6LHzQE1HvmXMqTmPjStbuQHmkW5moNzchqiLuGIj2Xf2g85snkB51z/Anu+C5B1hY+Q36IyOY64wgCUaqhza1IahDQXxQc3sX/Zh9RrfSH1H+mL8JOK1NoHrZwc2vMNqR3OR/ElYAkOcr4L2CkXmTIH10T49MYCRn2bTkxazX0W42IR42KRW7XELAyjfrgeLPsZVa5ogPrZQaT+jbCavIJwZAoIAlb6w2ibU4m8nWtfy/axuC4dQnD0/Zz31cdooka9VhZpE+NRQxaSFoB5c7HUIF1uf5e89aU0auagtFsPrGI75Fk5vzfGEi/6Olsczdjsx9hVjjKiEZRqKE28aE4B4pPQliyvc3nVZSuRs1ohZXfENCUUn1Dr/jXp4eLoZpUtn9klxy55NAHTgKK9GgGxAUnNIK5RFmV5NfXCPckZSIobMxRCcDpPW2HgN6HrGLt212oy9uyFcI0AnvMMucuGarH4SZOmF/SjzbCeCCLsWuCiUTc7giRUaqBWWlhAXIZE2ZEaAu1NFpEUATElGc/YP8Pl17DmA40dYwzUqlSTjR+U0/PuOGRHzfGlBhn4npyEpWmI7tNoPEQRxf9xzC5ayAO5TxEy7Wf0iHqcB3KfAmBY8iX/8v41TWPevHl89NFHjBgxgry8PBo1akTfvn2ZMWMGDRo0YN26dbzyyit8+OGHvPfee8yZMwdRFGnfvj2PPvooU6ZM4fDhw0yePJkBAwbw7LPPYpomLVq04N5772XixIlUVFRQUFDA0KFD65DME8eKj49n4sSJ5OfnU1BQQPfu3Xn88cdrGdl0XWfSpEns3buXoqIiWrVqxQsvvEBRURF33XUXLVq0YOfOnSQlJTFt2jTi4+P56quveP311/H5fGRkZOA5Q6WDO+64g8mTJ9O5c+c65Zy3bdvGk08+STgcJiEhgcmTJ7Njxw4WLFjAiy++SE5ODgMGDGD16tUkJyczatQo7r777tNWp7Isi/vvv59evXoxaNAgAFasWMFLL72Erus0aNCAxx57jISEBBYsWMB7771HOBxGVVWeeOIJzj333H/L9fhP4qwIt2EY5OfnV1trioqKbHGgKKKIohYEp4RzRGPM42GMTX6EGBnXHZng+/VHTZBE5PZx+N7uYoc0JzvBJyN6ZJr0kBgxIxVMUGIFHKeUg7HKNSIzcmq16WuL4VYDYh0kyzDABxejE5qyA+1YCPeDWeg/lWDmBJDPT0bwyYSe2onUIgZ9fQnG2pLqfZl5QfQ1RXaO8bAGdqgtYO6vxP3YdhyX1YNbmoFS2/sixiso1zREGZKBkVNJ+O19iKluXKOaUtz9JZxXXmpv53bDqQtPw6gWIjKPHUd+diI3vfMEpX4vCYkB3GkeHG4BQXEQ+9FHKH36YR6PICYq4ITwx5+jrvwR51VDiXwxx96nJOH9+18JPluVl6zrBF98lbiP3kVItsWaRJcErpPOo+qdHfjkdYzdezGPHUdb9SNYFuqq1XgnXI5ycTrmkRDGumI6XlefHd8Eqcy3F+Zp2Q7S0wsIb/3ZPsdEN8aUTkhlEeQ9pfz8dYgVL9ZERGxMFLn+pUwEn4j6cxn6nCISvl+Ivn0zodfeRExLRenZA2PbZkp6dkVumQlOJ94J96Kt24icnWXXYG/cCPNgXs1pPHgvUstMnIOGYB47RWzKNJGzW6Hn7kLKqI9ZUIR038NsXJ7GzxN0XHGpXHjHVDIIMXBKAkueLiNcYdK0p4vzbvIRF7MBYce1oB5CrPcw7tE3UvnA3/CM/TOVf52EkZNrz9PKSspvHE3CsgWE352BQ9aQHHKt/NrULAXJKgT1JM9CeA8VXoGyIyINW8cSfucAzusao68rrlFw9slILWLxvOtCOs+JdY7CslevJf+XlVzwlw9xrg2TrUdQDBdHD8CWT4LEpkr0uDEDpbEPc00hYqsYHBelUn6wmMyL/kTEFPFLCtvyvBQv1+n/Nw9Nel5Z84wVqzQMl9FEK0XvH09wVCKfjfVTvE8jJu30z7sV0O0xO0WU4Q0JPrQNVBN9Bci9euMadTmoYSJzLbR5NeGIxrZylCs7oG/agmhYiJuWk/j5XISRtyJlNkIJFyAkn0OJty1iiUhiUzfijoXVZBvAcf4FhCYfrzUefU0RyuAMgn//GaGeC89THTCbNkDudA7aug21tpWaN6Vs5CgS1yzBk5LCkBeTWfKEn5Jc3Z4LN8cw564iW+W8oYxlCnw8Mr+6tnlsfYnhry9n/rh6WKaBwxPLxQ/MwZz9LeVz5uHocwHua69C/EfDyxUHYv16mEdrvOdieho4lV/pVHVOToGExjI5K1VyVtrv1YQmJpJTIFhisPTpUnZ+E6ReB4WLH03k2wnFBApNPEkiQ6Yl40ms0tGQJHL+H3vnHR5VtfX/z2nTJ5NKCiEQWiDU0JuigAoKojT1KiIXr92rKCgKKlfBQlHgIiA2VFRQEEEBUREB6VIFkQBJaCmE9EyfOef3x4GEIUHxitf3977zeZ48Onv22WefzZmZs/Za67v2m9nzWWiOdv5PfgIukC/MAJFlBPmSi8SECfO/ipdPzqsyts/hVj28fHLeZTG4169fT1JSEqmpqfTp04fFixczduzYWvsGg0HeeOMNNm7ciCRJjB8/noKCAiZMmMDs2bN57rnn2LZtGzk5Oaxbtw673c7bb79N//79ufnmm6moqKBnz54MHz681vG///57mjdvzqxZs/D5fNxwww0cOHCAli1bVvXZvXs3iqKwePFiVFVlxIgRrF+/nhYtWvDLL7/w4osvkp6ezsMPP8wXX3zBtddey7Rp0/j888+JjIzk3nvvvaiB2aFDB0pLS5k0aRLTpk2ravf5fEyYMIF58+aRlJTExo0beeaZZ5g9ezaTJk1C0zS2bt1KTEwM27dvp1evXmRnZ9OqVatazzN37lzKysqqQrmLi4uZPn0677//Pg6Hg0WLFjFt2jReeOEFFi1axLx584iOjmbJkiXMnz+fefPm/VfW46/kkr7x77rrLm666SauuOIKBEFg8+bNPPHEE3/23MKE+f8SMcqAeUwz3TsqghChIMi/7bkRTDKCSdaN7fPbBQFrzK+EEmoa1OLxuzB0PLCrhOABPfHaNX4fcqcY5N7xCBYJ97P79XNFGdAKPDXGUvM9CMlm1FM1RX+CP5WhuYJVAmdVx7gDaGUBXGOrRYnUzEp89S1YV3zK0ZgEFhZCXRkG2vXc76prttlQruyBf8MP+txXryL62THI38zD++nnuJo2xj53BrY5M6A4AueDuyCgRwYYRzXCNvkVitq2wbHwbSyjHyaYlY3SoR3OKa/p9X7PrZHHq9fBtVovvr6AsfdVlLzwcmjbjdejVeQixtdDjjcjmCUMqsbtr9oprRSRDX4spw/iu+0OACyT/sWmj0R+/LiY6IYyg2Yls+/+UMElV7FKhVPAmiIT8GoIVhn/rp2Unx0DwPvlV0Rv+Y6yO0YhpzfD/NC9lI+8HzExgYj35lM5fiKRi9/Ds3Q56olTyHeNRGyejn/pp6hJfVFPeYhc/RWulyehudxYHh+N3KY1FQ88SmDXHiJ3/MDh1SK7PtHvA787yIqJMGpFNClHshk+IxGMEmKJB5ujEOHnG9AcN6GZbwW1FNPwpmCcgty6Jf6nngtdSJ9P30wRRYLz/03fJ8fw9XQVv1vDniDR9/kIzKcHhd5fETeT+a3EjvdLuf/zWAQBgjuLsfyrFf51BRChYLg6Hs/sTII/lxP4sQSlXwJXPPAeqs+LuqyUwDrdGPP9XIpySzPa3mpnyT2F7P3MxT1f1MEQbyCwqxjnP34kamBDGvaey/pXyzm1y4deRA82zy3n+ucikX0BBKOI750stA2FBAC2FmHrEccV9yQQUffiP6tChKJvDjSyEdxTUi3Op0FgfTEeJIx/r09g076aB6saQkwMKApS/RR8Cz+EhXqVELfNhnntenxO+Pzh01iiJQaPuHATKwCKEBKKj0GEs98TWp6H4I5iDNclIj41Bv/WHXqYtiRhefRBggd+QT1+As3pwt5ERjEKDJ4XB6Jeak0Lagx+Iw5rjIgNOIiGAAAgAElEQVQ5UmTXwsoqYxv0EOyjG6z0n3mU4qyDJDRuhXfKq3hef0O/rz//At/qr4n48G2kmIvXsb4QMS4Ox6cfUDpgGFpxMUJUFI4lCxHjfttwt8ZI3Dw7li/GFFF4yE9cmsKA6TFYYyRy93k5uFJPBcrb62PLnHJumhWLOVJENomYo8SQSKO6bWsa+E36mDHYfl1RPEyY/2vk+mrPbb5Y++9l6dKlVV7W66+/njFjxlw0zFmSJDIyMhgyZAi9e/dm5MiRxMfHk5OTE9IvNTUVu90OwKhRo9i6dStvv/02hw8fxu/3465FEBGgf//+7Nu3jwULFpCVlUVpaSkuV2iKYceOHYmMjOTDDz8kKyuLnJycqj4xMTGkp+spLk2aNKGsrIzdu3eTkZFBbKwuDjlgwAC2bt160fV47LHHGDhwYEhoeU5ODidOnOD++++vaqusrMRms5GamsqhQ4fYunUrI0aMYMeOHVitVrp06VJr+svWrVtZuHAhS5YswWDQvwf37t1LXl5eVXS0qqo4HA5EUeT111/nu+++Izs7m+3btyNeENn0Z6/HX8UlGdxDhgyhZcuWbN26FUmSGDVqFE2bNv2z5xYmzP+3iHYF7H9sDM0bRCvzE/ipFDHRjFjXjOio+VAn2BUMNyXjfT+n+vxN7AiWUANYOC+skYBGYPMZBIeMclV1nlHwl3IMj6bhWxGqHK70rAMRMoKxpuEvtXAgmGu2C7JI8GhN5eTgnlLcfdNJzxE59zg+pRg21a82usXYGByfvI9nwUJ8GzdjfWI07rfew/3vufoYR7Mo6XQV0T/tx/XCPt3YBr2E1/vZWKe3QWnRHOfzLxG5Zjm+xu3w5Z/Gtyo0T8xy3yjcb76L+Z6RSHXq1Jhr1TW2TMc2ZRLOyVNB07A8fB+CzY5gi9A3SuwygkFCK/ahHM4llizU0tMYWrfA8NoryG3bsO87Mz++o4eaFmcFOJ3pxxIrUnpBmpipjoJ/XQFK5zpovjJcM98IeV8rL8f/4y4iFr+P9/MvKO0/FDm9GY535qLWSUQbM4kKjwfprofJy5Sw28043srCNGIw6nEN38ITqEctmEdOARkEUTfM7FMmIUQ48FliOLyhOHRSGpza46dhUEN9Qc8P1wTQ3oxCq/sJ/s318H1djmCvg2lkFKaht6DmlmO4uie+laur7wm7HSE5Beu/JuDfup2UiEOM/KQ9/vxSpMp8jHt3ofZZgpj/NJSsQI0YSLnyPDs+UPFWaHwxuYIBjzTBNX4v/q1FyO2jMQxIwvnwLnBXG3f+bwqw3lQP55Nn2wWQWkciNbETVU+iqBjqNJcZOi0ScXMBgVI/ht7xKN3r4F2QRUVcnbPGdjWyIuBbcQrvZ8exTG1LYOMFSvGbC2k1NxWhwo3v2yL9cxGpIJqrf2YFhwHr1Laop9xoZTWVrAW7gmAzYhiUjPetrKp2MdWKmneciDdnI8ZEIxgUTCOH43n3g7PH2dDqNmDj2FJ8Tg2fM4C/XjpSs7SqcGv30k8wDB2B76PqG84wMBn/puqIB/WMF79XxWtIwPDFWiyeUqTTx/CuWEXF6CcRYmMRbPrmlClCwlRdNQsA23k2bkV+TaHIinyVbe/YOLmjNTf/K4j65rsh7/vWfAtOF/wOg1uQJJSO7YnZvx3N6USwWhFjYxCkS8t3jk5VGPpmHMGAhiQLVXnSxdmh6SEnd3rZ8GoZA2fGYoqouYFqiZEYMD2G714qwVOu0mqQjeY3hKb/hAkTBpIM8Zzy5dfa/kcpKipi48aNHDhwgPfffx9N0ygvL+ebb3TdknPRuYHzylHOmTOHPXv2sGHDBu6+++4QT/A5TKZqkZqXX36ZEydO0L9/f/r06cPmzZsvGvX7wQcfsGbNGoYNG0a3bt3IzMys0Xft2rXMmjWLO++8k0GDBlFSUlLVx2isdsAIgqCLzZ797znk34iWMZvNvPjii4wePZrrrrsOh8OBqqokJyezfPlyQPf0nzlbavGqq65i06ZNZGVlMXHiRO68805EUeTqq6+uMXZhYSFjxozh5ZdfJikpqao9GAzSrl27Ks+11+vF6XTidDoZMmQIN954Ix07diQtLa1Geek/ez3+Ki45Ycput9OpUyfatWuH3+/nwIEDf+a8woT5P4Fa7id4wkXg5zLUYi/aeWWKgkcrqbxnB54Zmbie3ItnZiZqWc0cYUERUa5LxDwhHbl7LMa/p2J5pkUN41xqFhGq4iwLGG6oi1jXjNRBD6nWin0EjlZgfjodsb4FMdmM6b7GBHOcuB7djf+7Aj1E/qyBLbVwYLw1pVZDXFBE5GYRNdql9Ag+8EmcLyeU5Ye9FzjWpfg6WMY8gmPRAqQmjfAsWhK6dqdP6yV4ii8wXLwqqHresm3yc0gx0Zzc6aXUGYXxq++xPPk4ptuGErl8MYFDh3E+8wKuabPQvF4uhhQTjeWf9xPz03ait67DeMutUJGKb2U5nney8C07iVru1w1vRwHlQ4dS+Y8HKb76elwz51Lkrcu6OaE/srsXVXL1E5FI5/0zNeltRD6yC7VsM7LVi9g1odbaxILJhGvyVEw39Sfmp21ELvsIqUEKilHEkhqLHB2Ps8hKUmMzERtPoO4uIbDDhVTfiphiQT3uwrfoDP4vy5DbOfB/9z2aV0FQIlEsIvHpNev/WuIk1IH1q381NMAcR+CnFLwLC9FOe1GPVuJ67iQEjHjmnMY26RWUK/VKFmKD+thXfEawyIhgGYB96msEFr6Pu2ESPDIca51oyG+CZ2YR/oppqGnZHDryMguHg7dcX7uj33koR8E2pwOWp9MxDq2n77hfWOveJIGmIdhkkAXME1ogt49Gza5E3HKahGSBobOiUd87ivf9HPwrTuEcrRvnhnsak5RhxJ5QfU+LMnT+mxk2nvXABDS40JCSBERPANeYPXhmZuK8dwfBfaWhkSYCIAr4vspFbGBFqHPe59EqYbw5GdEgofSKx/xsC+QesRjvrI/56abIHZphuOZqBIMBMSYG+7TJxBz5iejdm4neuQlBlig7Wf0Qufx5Ad5dge2DBRheeAlt6J0U1Y3GPLU1htsTsExvi+BQ8K/KPXuRIPesw873Knizby7z+51m/bsynqAV10vTkBqmErXmc8S4WAJ+FU+5WqsA4zlaD7OFCPsJIrQYYCV3jw9NA2ushGC8QFVeFPW/34mgKEiJCciNGyElJiAoNe/fX8MSLWGvEypKVq+9qYZgZbMbLBjttRvQRptIkz5m7lySwD1rkuj5uCMschYmTC2MS74Ps2gKaTOLJsYl3/eHx16+fDldunRhw4YNfPfdd6xbt4777ruPRYsWERUVxZEjegWDtWvXAnro8/XXX0/Tpk155JFH6N69O4cOHUKSpBCj/Hw2bdrEqFGj6NevH9nZ2RQUFKCqteiKnO17yy23cOONN+L1evnll19q9N2yZQv9+vVj8ODBREREsG3bNoIXKRUI0L59e/bs2VN13lWrVv3munTo0IG+fftWVZxq2LAhZWVl/Pjjj4AeFXBO0bxnz54sWrSIxo0bExUVhaIorFu3jm7duoWMGQwGeeyxxxg2bBhXXnllyHtt2rRhz549ZGfr6Y5z5sxhypQp5OTkIAgC9913H507d+abb76pca3/jfX4K7ikbYCZM2fyzjvvEHPerrMgCFU3bJgwYX4/apkPz9wjBM56mAS7jGV6BlKiGbXch+etrJA6wYEdxWgVfnDUfJgUIxTEzrHIGdEgCwhizYdCMcqAdVoG/u1noNSPfFUdxCgDglHC/GhTtDI/miuIGG8Ch4y5kQ31aCX+NXkEduols3yfnsA8qx22uR30UFSjhBhx8YdbIc6gK3wvPQEBDamlA3lAXdZW1nyoPn8rwalChQoRooTFZiPo9iClJBMoLLzgqABSm0iCe6uVjsUUCxgFIubNQ0ytB0BUfQVfpcqSCTLDnhqC8OG7VDz+NMEjRwHwfv4llscfRrpAVVSt9KOedOP/vgCpkQ25YxxSvbq4TjjJ66bwdgcJE3CXEiA+14WSasL95lvVA7hcBLZtx2Lx1qgHbKsjEVVf5u6VCeTt9mCPcGI+sRtDfjlSg/b4PspHahuF7YVn8X71DZwNqZLbZyB3ao/SvStS3VCldACDVUTbnIfty1xwB6vSnMUYA95FxzHd3QjNGUDzqojJZlQ8BE+XwTYX0k16Dd8Od9k5tsXLmSP6hFvebMVZGCT7pErDdAfB/WVIbSIhYMe//gJPRVAjsLcMwa7gmVWI9ZEZyB/YQZTQLFG4Rm4DFTyHK7E8+RxCUl0sf78H90un0Er18wW2F2ManUaTHlGsM5yuGjq5gwFTlIwYLUG0EbXCB14VpW8i/lXVObym4Q0gQsZ0byOCe0sJ7CrBv/KsYbmzBGlXMcYRqagZURgH1MX1ykFwBvB9eQppWH2+fqWEgTNjydvrxV0UJL2/BenTLLRC79n5FWG4ISlEcM1wUzL+784LidTA82YW1qYRVeXEtDI/rif3oJX68eR7MD/eDDVXD0WUM6LQIhQqCgLs/9yF0Wag2cgmSA4RyShxYciMGB2NGF29GWPyqDS91sKeRXpUSdmpIIvHiAyZP4D135eR94APv7ucv38eg72ZB//e9ciNuyK1jkSQBQy3N6DCI/HDrOo0h/3LXNRrn0Kz0zmgqoh14nCeUdn5fhn5+/00vdZM2nWWWg3LiCSZ296vw+a5ZQgIdHswgsgUidveq6OLElr8aP8aT+Vj1eVbzPf8HcFuqzHWX4E5RmTIG3F893IJ7lKVtrfYaNLb/KuK4qIkVJVaCxMmTO2cy9N++eQ8cn0FJBniGZd832XJ3162bBmjR48Oabv99tt56623eOKJJ5g8eTKzZ8+uKmkcHR3NLbfcwpAhQzCbzaSmpjJ48GC8Xi8VFRWMHTuWIUOGhIx377338sQTT2AymUhISKBly5acPHmy1vmMGDGCiRMnMn/+fGw2GxkZGTX6Dh06lDFjxrBy5UoURaFdu3YXHQ8gNjaWCRMmcNddd2E2m2ncuPElrc1jjz3G+vW6IKbBYGDmzJlMnjwZr9eLzWbjlVd0EdpGjRqhaRqdOnUCoFOnThw+fBjrBal3u3btYvv27ZSVldWwB5cvX86LL77Io48+iqqqxMfHM3XqVCIiImjevDn9+vVDEAR69OjBzp07/5L1+G8jaJegftarVy8+/vjjv1Ti/uTJk/Tu3Zu1a9eSnJz8l80jTJjLRfBoJc5Hd4W0yd1jMf2zKXhVnE/uQcsLdftaX81AavIHY9UvAbXcj++7fKRoI+6pv1S1C3FGDNMyMEb/tiBR1ViugB7WG9TAKCI6DPzggiuPV2teJcqwq4EeUp7rh/FnYKMLelrghVhIUsD/4y6Ke/atMjwtY0djfXoMBE14FmQT3FeK1MSG6e+N8G0oILinDOO9jRCtMqogkH9MZc9iJ1cMLsHTNSNkjsZBA4lYMA/RXr22WlDD/30BnhmZVW1SMzvmiS3JQqLVSZFz5dAjRdgX56euTcD53CRcL01DiIhAq6wEVcX2zVoKhRZ89WI5lQVB6ncz0m9yDLY4Cc2vEjyRS3GXKzD2vRZj38fwfVxtuCmDEzFcZca38QcEswkxJhoprSlSUsLF1/yMF+dju9FKdO+/mGzG8nwrKkfpCtlCnBFBFsAmY34kFf/aXII5QcyPN0N0GAj6VHJ/8iEIAqIEJ3Z42fx6GT0fj6TtAKMeRWCSEIwinjeP4F8TmntnntACz5zDaMU+pJYOlD7xBPaWYugdj2vCT+ctvIhhcBJSWiTu5/aHjCGl2TEMqkewcQRZ2/3Y4yViGilVxp1a6kM94cL70TGUPgkIVgk1x4ncKQZijUgRin7vVQaofOBHfc7nYZnSBtcTe5HaRaF0jcXz+mHkrjEIA+qxaIKT4uwAKV2M3DA+AkOlB9cLP4MzAJKA4aa6KNcmgCCg5rlBBTHJhPP+H+H801gkbHM7IEbrntzgMSfOh0IfLqRWDszj0hHPGtvvDSrAU6YPIikwYlkC0Q0uzWPrKgqy9a1yMr92E1Vf5opHHGx4rYyTP+obBcYIgZHLE7EY9LJoYqQDrTKAJoBoldn8ehmb54aWNWx6rZnrX45GNog4i4IsuaeQwkPVO0fth9vo8YgDxVS7Z9pboV/LhaUMAdTiEoLZOXjXfIuhe1ekFs2RLlKT+q/CWRQEFYwOAdnwH6ioh/n/lvBz529z8OBBmjdv/ldPI0yY/xH82ufhkjzciYmJ/yPqyYUJ878JtahmCLNa4AG/ihAhY7ghKSSPU4gxIMReuqH7R9CKvPjezsYwLAXLxJb4NxYixBlxXZNIhd1A0m8PUYVokcES+lXT2gi7Gmi8XgL1ZBgVKRAvwZkADM2FzWf1R46WwWEffFYXYlq3JPbwXoJHshCTEvBHRXPa5kAGoh9ojJrrRj1cgfPpvQhGCdMjTfFMOYh60o3gUIgf24xeTzg4sy9IxLin8E55RffaNaiPffqLIcY2nFV///h4SBuSSNCtMsMnVRnbAKUqLPVLPKqIWB55GPNtd6GW+BEcMr41KzFExhO7PJvbnk/G0MiKImmIchDNJyAYRAQZtKIiTHfche+90Pxp/9I8lC5tUX9pjunRJqBWIsXXnm+ulvjQSn1oVgnraxkEsyoRDCJiihUUAeW6BPxf5aMVetEUAcujafh/KEasG41hUExVGoJkEDHZRd4fUoB21oBUzAKN+5gRHaH/lsZb6hPYWYp2Rr+f5W6xiElm5DaRiClWpGZ23C8fRKsMYByWoocZn1s7r4paEkSuRQMAs4R60oXTYia1uwlzVGifwIEyXSdgfxnBX8qRO0SDRSKw5DhFXVOIbiZii5NRPSqCSUI73+AW4Fwdu+CuEr2EnQiG65NwGRWKsnQ18fz9PvwuFYNRwjq1Ld4lx5BbRqHmOHE+uBOCGnL3OIzDG4A3iHliS3zLThHcVwpBDUPfRD2s/dxpLTWvU3MF0YIa7tIgR75zVxnboEdE7Hi3gj4TopCU384FtsRIXPGIg05/j0AygOrXkI0CCBDdQOb6l2N0sS+5OtVDsMlVkd/1OhthbuiYqT1MVYam36WFGNsA+5Y46TQqAiU0QrSK2gztc4jRUYjRUSjtMy7a56/mVwUrw4QJEyZMmEvgkgzurl27MmXKFHr37h0iHNCiRYs/bWJhwvxvR2pk01WCfdUP2EqfBASbgiAJKFfHI0Qo+L8tQKxrxji0HmKU8VdG/GOonqDuwRMFgid0L7Lvk+P46xiR20SBT2VfUKD1ZXDy2Cp9NP+xmH87g4gJJuQ0O4LDgFurNrbPsdENbg0EgwEpKREpKZFjPhieBxsLoZ0RPkySaQR4Xtfzs4z3N8b7TlZVPXStzI9nVibW1zJIvCIOtcVD2O4fAV4Pgt2OlHBpG4rG2+vj/ewE3NCwxnuapCs1a3kirudP6GrQIpgeHozUKBrTrVGIdYz4N5/G9fFxUDWMNyej3JCE4IjA+uJEpPr1Md4nE9xRjH9jYbUYHBDcV4Z/zWlMdzSodW7qGS/OcXvRCjx6uLRVwvfDGfAHMfRJQO4ai3F4KoYBdVELvUj1rQgRsp7bX0sKgqOezJ1L4tnxXgUGsx5mXlu4rBhnwvpqhu5NN4pnhb9kxBYOAj8U6iXrzl5GMLsS0wON8byTDe4gYhM7xhuSECIUxMY21CNnRfZkAePNyXg/P0llZCSqNVjD4FZznIiJZqSOERgGRuBbtw4xNg6lVVvcR4MsebWQoW/FYXHIGEc2xDOjulazclUdgvvLql4LRhHLtAyCJomKY0H+8VE0SKBYRPgkG9emMwhxJkyPpgHgm1Ud9RD4oRCpqQ25fTTBXyqQ20VhuiuVQK4LpVVUiHq/YJExDK2H79OzwmVGEdMDTThxMMjuj8tIavPHP9+KSQwxfvtPiSbg03Oof8t4jGmk0GGEjV0fVqIGIe06M42u0kX1NE2rkdMMYKxFQCxMmDBhwoQJU80lGdyfffYZAF999VVVWziHO0yYP4YQIWOd2hbPm0fRSnwo1yWiXBGHcFaMSTxb7khKA83lRPOcQS2LQHTUFCL7o6gVfvyrcvEuPg6CgPWVNro4lgraaS/+b/KR70olI0bG8QcdPpozgOfNowTWV+djy11iMD3SFMmoYBf1/O1zOEQ4/5SFARiWC9vPRtvv8kLfk7Al2UrU0Hr4Pj+JWM9CMLOi6hjPyIYUdKvDaq9MhiTSNtZB3IXFcS9AiFAwDE7GO0c34jHqJZTU9ad55KYU3hIMeLXqOQ616V5x94xD1aWXVPDMO4rtjWjkFg4CB8tCoha8Hx1DbGJDbhOJadDdeOdnoZb4UK6Iw/xUOu7JB5BaRqKe3QDRKvxoqlbDQNb8Kt5lJ9EKPAhxRsT6FtzPVwtbeg5WYKlrQW7hgAgFKeXXy6ABGMwisfUlrhkTgVbiRRJ9CJUCQWcJ+P1gtRKIsOvCMgZQEiWkklLUIh+C24xUz4K/3I/pn00R400Ej1QiJphQT7mxjG8BsoBW6oMoGc1ThuXp5gQPVaLmupFaR+JblYs8MJl9H3np+XjNmppym0g9JP1ameIuncCj3xByqxbEvbuMM4eD+Jwq1hgF2kQhvJCBeLgMQyMrlPtxz9INcKldFEQYkGwSVARwrMhEPViO0i8RBAj8VIZwUwpqvAVfViWSr6Z4S/DncrQSH75lek63L1LBOrMd4gV6C4JV1jdZrk1AK/YhJpjwBESWDM5HlKDLPyIwRYh4yqtDyjveZa/Vu+0qCqKqGiaH+Kuhzqbf8YG1REl0e8BB+xF20EAxi5giRIJ+jYIDPgp+8dHyZiv7lzmrjun1ZCTmqLDRHSZMmDBhwlyMSzK4v/vuuz97HmHC/J9DUCSkhjbMT6dDQEOIkBGk0AfX4MlTlPQZQPBQJogiljGPYn3y0RCxpMuBdtqLd+Gxc6/wfZOP+YnmeN7NRiv1ofSJx9gnHstlyGHUPMEaJZUCW4vg3iDRFoU58XBnnu4UFYA58XDOMad5gng1ge2e0Hkc84NTEDHeUp/IG5PQ/BpSswiCB8sRukTzbdd4bi89a/wUwRA7zEuoHrc2BElA6RiNOCGdwI5ixCQzQpwJrTxA7LtHOTCyEfP9EiZBD4lPEDRQNbSiWlTTA2r1dV5AYEMhUtMIXOP2VUU7+JacwDi8Aaan0xFNEu5XDuohzzck1eqNVgMqUpod4dYUtMoAgR+La/Txr81HSo8IEX3y+/143G6Ki85gt1kxGhSMJhOy0YKmagQOluOeuL9KvM8wtC7+Y8tx/etf2H7axrZ9e8nNy0MQBJo1aUKTE7m4h9yBlNaUyG++xPRAEzyzD6MecyK1iUTpEYuUZNbDqAMaYoqF4PHDlPa9GWSZyOWfITdMIHioAKWXgufTOfT+x12ItYUl17UQPFWCe9pLVcY2QOCnA9gLDuGol1ZlqOYdVvlybDmxTQx0uEUmzqQi905A7BqDx2Fg5wcuOo20IazNRz2o5zBLTez4N55GHdeGDW87Ob0kQMNuJjqNjIAlJ/VokLNIrSIJ7Kj+t9VK/fi3FWHsVzP5QrArSHYFEnTP8ektHtBADcD3U0sZ/EYsR9a6CQagzTAr9vjQm9TnUsnb62PdK6V4ylXa3mqlzTAb5sjLE/pssIoYrKHr7S5VWXJvIUGfxjXPRtOkj5nS4wFSrzBhjZXCpa/ChAkTJkyYX+GSDO7i4mJWrFiB0+lE0zRUVeXYsWNMnz79z55fmDD/6xHtoV4wLRhELTwDgkDlc5N1YxtAVXFNeRXziL9ddoM78EtZyGv/qjwwiVheaYMgCggWqdbSX/8RAqCIoSJWsgCCgEmEgTbIbgRHfdDYAFGi7lwGUIt9aKJIqmLk/DK5kbrzmfsLRZ6PM9LYAabH0nBP/pnS/vUY5wxd4yUVMC3u1w1uACHGiCQLCDYFzR1EMIgYhtXD98kJ4nYX81znWIzD6iGoCqJBQTWoSG0jCe45TzU92Yx2tga61LyW6ITmNnwnKkJSCwD8PxRi7pmOf9MZlOsSkbvHoEaGevtBj04Ibi/CtzIPMVLBeHdDgj+X4ycvpJ/YxB5ibKuqSl5uLhs2bqyeStNGNKwbR1TdxnoY/uzD1Ur5AgTzXIgjbsbasx05zkpy8/RzaJrGwcxMkttmINZLJngoE62wEs9rx9BK/QixRgSDiGfxMUx3NUSMM+EpO4O35AwBbxGWH1ahnBTRioyoFOF6ewrejxeDqmLKPYl99nQg1Cvv8YuUnAZbSei9CyCUl3L1k5GYHPr1ChKkdjXQ6RYLsqzhUs2YB1rI+n4u5Sf3k9z57wQ8GYgHqwXD1HwP6qBUlo4rozhbN653HgtQWaLR69FmBKcc0HO4r4hDTo/A+9bR0EkEflOPFIColOqf4VO7fSweWciVox20Hmqt1XPtKtKN33O59T/MKsdWR6LFQOuvKmj/EbyVKj6nfj1fPVOMNU4kKkUhrZ8Foy3s3Q4TJkyYMGF+jUv6pXz00UfZvHkzS5cuJT8/n88//xzxP6iVGSZMGFBLy1CLanogAdSSEjwLF1HSvQ/eL1YR2L23Rp9A5pHLPie5ec3wajHSoP+dLR12uRCssi6edR6GQclwVlDKLkF9BXpZIUXRX58jsP405uOVvJEA0We/gmwivB4POQE9vLzHcTgdACnBjOWFVohN7ThrKZFZe4VNHa/Xi9fr1VW6I43ILRwoHaIRY40Yb07G9lYnLP9qpZefsklopX7UEh+iXcE8Og35yjiESAWpQxTCuMbszvoJl8uF1DwCuVts1XnEtg68LYwExNAJCvEmhCHRlJYf5Bf3O5xIWk9x4Ge2L3gMZ1F1KSpN0wjsLMYzIxP1cAWBHcU4/7kLqVVkiHEvNrGhdI0NOYfH5WL7jh0hbb8cziKogrtUL8WlnSfsJz4Yz/GG37P6mavJLo9uXpcAACAASURBVNrL6YoKLuRMRQVS40ZnJ6eglfoRR8Xhvj/AL4mLKGr2C15PMe7S02yYcjvL7m3OF+Ov5OsXB+CPEfDMOor7hVysj01ArKt7h/2bt6FVOmucC0Hg+EEj5n8+HNrscKC0bU89u4fg20cJHConsZHAlddoGKbuQXxmFzYpn7UTe7H3wwlkr1/ExinXkrd3JcrtKfrmD+D/Jp+Aw1hlbJ8j8xs3aqwZ6yttsb3REaV3PJpfhfMjD8xSjfW+GCaHyLUTo1DM+vGxjRWaXmO+aJj4iR2eKmP7HD9/4cJXeWkG/n+C0Sognbdn5SxUUVUN6ZK27MOECRMmTJj/21yS1Zybm8v8+fO58sorueOOO/j444/Jysr67QPDhPlvoXpB9f12v78Q1eXC/+NuyoYNp3TgLXi/XI1aWhrSJ/BLJuV33UswKxv/ug0YrukVOogkoWS0uexzE+KMGEc00F3Jgq40rfSKr8onv6znMkoo/RKxvpaBcVRDLNPbYhiYjGiufnrXNA3V5UJTVfzuSlxFubiKctFaGjF9eQpcAT6tC9+nwMpk+NoJdhGO+uFMEArPptkW2wwsd4vcExk6hwyj3v9CfD4feXl5rF+/ng0bNlBYWIjfH6rKLNgUxHgTYpIZ34ESPMtO4J72C87Hd6MWeBCjjcj3puJ5rgFnbrVx0FuET5TZsWMHfpOG6cHGWN7IwDQvg6JbbXy9dR3Fajliz1iEaAPOaRkceimDMxHZfPFIB/YsnMimV0eydfYD1Ot0AxunDsdbrocva5WBkPrTAHhVggfKMAxOxjKtLdY5HbA81xIxUlcgD3jdnDn8I67iXLzeUKV8TdNQNQ0tEEAt8qL0iANAbGClVDnMtnf+SeXpY+Tv/Io4R8088PjISIIH9TJygllG6h3Ncd83rHquB/uWTmbt9JvYv2wqZw5tJ3fX11XHlR0/SOa2BUido8Cj4ltdjunOEQAYrumFEFGzFJ4pQiCmsQINWhP55XIM/fthGnUX0ds3orotBFacwr/pDK4xexC9QdS5h8AVBIuEx19I+anMkPH2L3kZn68E6/QMsEkQUJEkEC8wKm1xElqum8CPxXjePkpgnb45YX61HdI1CSg31cU2uz1C1KWV8jLaRJr3tzBqZSL3fJ3IoDmx2Opc3JKNTq05bmwTBenP01PEaBe5/pUYFIv+fRCRJNH3hejLFsYeJkyYMH+UkydPkpaWxrPPPhvSfvDgQdLS0qr0qAYOHFjr8b169aq13vPw4cPZtm0b27ZtY/jw4Zc8n3//+990796dgQMHhvzl5eX99sEXMGvWLH788cfffdxvUds1b9u2jZYtW3L48OGQ9rS0tN819r59+5g6dSqga4GNGzfuj032EsnMzCQtLY01a9aEtK9fv54rrriCxx9/vMYxF7snLieXtD8dG6vv1Ddo0IDMzExuvPFGXSgnTJi/mqATPEfh5BSQzFD3CTCk8Kc+ff6HqPkFFHe9Gs5+dkoHDCVq/RoMV3av6uN5/6Pq/1/yOVGrl6GeKcLz4WLExAQi5ryGEHt5w8lBD2s3DKiL0iter9NsFBFsl2Yw/Kfnw64gNa5pSAXPFOH7YjXeZStQXhrP/o3vcmjVXARBpMXNj9P02rto/XMJG5pEMiegkCjBQ1Ew7nR1talzOlGnAvDwafgwCebGw1dOvSTZg5FQm01TUVERIgb59ddf079/fxyOmhEAHnwcMuVSnlpBw071icqX8SzIxvTPJnjxclL08XNkEm+5jCRaVMY39uL3+wn4StkwczhN7pzO1t0/A7Bp3za6XNcR0wMdub5A4iHPGeIXPAVatdey+OhuREmmJGsvQf/ZnGVZQKilJrpgkfCcFXuzvpaB6DDgc5bjKjqFFgywcnRXWt/xPCnJ3Th24kTVcVFRUeD3IGpReFecwHhdEoJdRrMLHN0+tarfqV1raHHbszRMbUB2zjEkSaJ1ixYoO/fgyS9A6d4VIdoCgwX2PDYxZG4lOT9hdNT0/pYc34fQcQRsKobyIGJ8DIZ+12Kd8ASi2Vyjv2wUadDVjOSTIZCBefDzaJUantnFmMclIP6tPlq5H8EooVX4q0O8NRBqcc1KihH1uAtfdh62OR0AAb8s0f1hBxtf08PWRRmuHWtHyTmD1C4K76JjoELQKLOjMgqfM4bWV1lJrHORGlkX4UJl8V8jqoFM02vNZH6tK/A76kl0HGn/U2tEK2aRRj1NjPoykYBXQzELWGLCUW5hwoT5z3B/uJjK8RNRj59ETEnGNnki5ttv+cPjRkZGsnHjRoLBIJKkPwisWrWK6PPS8JYvX/6Hz3Op3HrrrTz88MO/3fE32LFjB507d74MM7p0xo0bxyeffFK1jr+XI0eOUFRUU7fmz2bp0qX07duXxYsXc91111W1f/XVVzz00EPcckvN++y/cU9cksEdExPDW2+9Rdu2bfn3v/+NzWbDc55ITZgwfxmeHNiTAZyNsSxcCBm/gFT/r5xVrXiXfVFlbJ/D9e95yJ3aI54ttydntK1+0+ej9MZhRK7+HNvk50AQEONiEf6kdA7BeBnztC/AXXqagv0bOP3zZhr0GIKjXjOM9pobB2plJc7nJuOeMx+5QztKju7g4PKZVe/vWzyZhBd7UcfQjptLXfRuYKNYErn2hMC5yN+nonXVcIDjAQgCt+ZCVzN0MUFffymRe7KoWLwEuV1bDH2uQqpTB1VVycwM9XpqmkZ2djZt27ZFVVV8TieBM0UYFAOHck/y85HDaJrGiRMn6NyqA8kOmaDPi+r3sC8igbvOnNv4EVnlMvNTsofcpa/SuPdwHDYLNpuNyspKgsEg+3MOojRoyB4vGGQVNVAzYkMN+LHEJQMCruI8JMWE8c4GBHaX6N5bQGrp0NXli30o/RIRrDKaplFwYAM/L5tBfIseaMEAP3/6Mr1fWofF1JCColKioyJp3qQReMv4YfYIYut3oonx78jJFqQkE1G0IZvF5xaG7yZcQ9/XttM2ox0ABkVBiI3DdiITzEakmBiEorwa11F0+Ec6/mM6u959KqQ9pctAqKvff0r/RKRmgzCPHIoYFVXrPaUFVAwBPwQ1Kl85CG79+i2TW+NdkE1gi/5DL0QZsLzcGiHOgFboA3cQozOCuGZdKPxlqz6YIJAx5AXEr3z4jxZjvDUFMdqAEWgz1EbatRbKTvqJri9jkFWE/WZck38GFYRIBfXqRH4aWYLPqdF6qK3W+V4uLFES1zwbxZWjIwl4NcyRYq3l2i43slHEVnv59zBhwoS5ZNwfLqb8nofApW8aqsdO6K/hDxvdVquVZs2asWPHDrp06QLApk2b6NatW1WftLQ0Dh06RGlpKWPHjiU/P59GjRpVRXz5fD7Gjx/P/v37qVu3LiUlJTXOc+zYMSZOnEhpaSkmk4lnnnmG9PT0S55nZWUlTz/9NAUFBZw+fZquXbsyefJkCgoKGDNmDC6XC1EUmTBhAjk5Oezfv58JEyYwe/bsEE/z9u3bee211/B4PJSXl/PUU0/Rp08fxo0bh81m48CBAxQUFPDggw8yePDgi17zhWRkZKAoCm+++Sb33XdfyHuqqvLiiy+yZcsWBEHgxhtv5J577mHbtm1MnToVVVWJj4/n4MGDuFwu5s6dS3x8PMeOHWP48OHk5ubStWtXJk2aBMD8+fNZvXo1wWCQHj16MHbsWE6dOsXdd99NVFQUJpOJAQMGsHHjRsrKyjhx4gTdu3dn4sSJNebt9/v54osv+PDDD7n11ls5fvw4KSkpfPrpp6xdu5YtW7YgiiIrVqzA4XBw+PBhZsyYwU033VR1T4wfP56srCwMBgPjxo2ja9euLFy4kOXLl+N2u1EUhenTp9OwYc3ysL/GJRnczz//PCtXrqRDhw60bNmSWbNmMXbs2N91ojD/A9CC4CuA8vUgWsHeCQwJAKiFZ/D9sAXvytUYb+iL4YpuiLGXloP4l6EG0HJnIHBeQqPqgTOLIfmJv25eF0FKqVezrUEKglz9MTQOvAH32+8R2K6HDkkt05GaNkKK//1PusGAH2/5GdSAH8lgwhypj6E6neD2IERH/WnG+/l4yovYNGMUJ7d9CcDPy16j8/2zaHr9vUhyqHdWK6/A/dYCAOTWLTiZuaHGeCd3rCTpHj3UPhqwq/BDfTgWgHgJoiU4F+nazghGAbwabHFDvBAkfd0qSu+6p2o8pWcPHJ8uRIqLxW63Y7FY8Hg8qKp+X1mteuh04MwZvAsX431xGq5gkNSxjxB9w7Vs/OknAA4eyyTpmh4EgpXkF51knjG0tneZCrucfrr2GYlXsVPuLKdP716cPJaFx+OjcbN0PgvoIbvvqXFMHfI0xa8MqzrelpCKbLbR8e7pHNv0GfsWTcae1IgrHnsf25wOBLOdCDYZPEHc846g9EvE+Lf6CEYJd0kBO999ClFSMEfpn3m/q5xvxnSj/pW30ea6u4lOTef4hk/ZOucBtGCAk9tXkX9oPVfc/i7GgInGvUaQteEjSnP2AxCb1hlrZCwmowlEQRfsSkwIuWajPYr0m0ez7+NJVW1RDdugWB30ePw9fvr0ZYIeF0373YOmqahyEPNT6UitHYi/EWGhHnPhfHovlmdaVBnbUrtIkIQqYxtAK/HhXXwcy7MtcT23H63Yh7DOS6/xn1Pw80ZKjvxEg/Y3o+yUCf5cjJBggvPEx0wRemmsyHrVn1O1XTSWZy2orgBOg4mVz5fjc2qkXmHCUffPT2w2R0qYI3+7X5gwYcL8T6Ny/MQqY7sKl5vK8ZfHy92vXz/WrFlDly5d2LdvH2lpaWhaTY2LWbNmkZ6ezptvvsmOHTtYvXo1AB988AEAq1evJicnhxtvvLHGsU8++STPPvss6enpHDlyhAcffLBGCDPAokWL+Pbbb6teJycn8/rrr/P999/TvHlzZs2ahc/n44YbbuDAgQN8//33XHXVVdx9991s2LCBnTt3MmrUKJYuXcpDDz1UI6x74cKFTJo0iUaNGrFlyxZefPFF+vTpA0B+fj4fffQRmZmZ3HnnnQwePPii11wbkyZNYtCgQfTu3ZsmTZpUtX/88cfk5eWxYsUKfD4fw4cPp2nTppjNZnJycli3bh12u53PPvuM7du3c//99/PZZ5+Rl5fH559/jsVioU+fPhw+fJi8vDz279/PkiVLEASBsWPHsmLFCtq3b092djZvvfUWycnJfPbZZ+zevZsvv/wSSZLo27cvt912W431WL9+PUlJSaSmptKnTx8WL17M2LFjGTp0KDt37qRTp04MGjSIFStWkJaWxuzZs0OOnzlzJikpKbz++uscOnSIZ599llatWvHtt9/ywQcfYDKZmDlzJh9++CHPPPPMRdeuNi7pyWDNmjXceeedAIwdO5axY8cyf/7833WiMP8D8J6CvW0hcHa3ztQQWm1C9VioePYFPPPeBsDz9vuY7h2FfcoLiBGXv+bzZUMQQKwZkqyJdv4bRWoCmp4vDKFK2iF9vB5EWUGUJJQruyO3akHgJ70+shhfB8sjD4QY3FJ8HaK+/BS1qAQEEKKikOrE/f65+TwU7N/Ixql34Ck9TXSjDK4evwSzV6LyqecIHs3GPPIOTEMHIcbG/EfXf8lzcVdWGdvn2PPhv6jfYyiW6FADDUFAMBrRfD6Ch46Q2G8gR/kgpEtSRu+Q14oQJEkrJEnSQHKAVF2zOVaCTSnwyGnIC8B04Qz+iZNDjvev/wGtrIyK6FhsTdMxJjaiuaxRlHWY4hPHSE5O1q/jYCaex6u9st7x/yKydUscDgdlZWXIsoxYx4RiMKEeLaJDPZUmBpFMH2w7GxAUZzKxZ3cep0/rYnjy3p/p27snBlnEabLRQwWzAGvdApsbX8OVL2+gZM08Iuqm0bjPCESDiZPbvmDbXD1EzV2Szxf/bMdN8w9i6ZAI6Krl1hfbIFhDIxZUv5fSnP046jUjqkErSnJ+Iuj3krdrNe1HvIDmdVcZ2+fI37cOdYQP1/j9mJ5sznUvfou3oghBUjCYHRiKzHgWHEasY0S5LhExJjSVQzKYSL/pUWIatydnwyLqpPegwZXDQBAoOLCRVkOeQFSMHN+8jOChbaR0vBGl6W/fj2qZD/dMPSdbcwcRYo1oZ7wY+iSgnqgpsKblehCiDVhfy9CDYQwiYoRC/Y43kejtjm9KDmq5H0Qw3d8YwfHrxv45QUE1qKEUq/R8PBKTQ8QaJ2GJCuc1hwkTJszFUI/XzJP+tfbfS69evZgxYwaqqrJ69Wr69evHqlWravTbvn17VbWljh07Uq9evar2c2HHDRo0ICMjI+Q4p9PJ/v37eeqp6ucBl8tFSUmJnpZ1HhcLKe/fvz/79u1jwYIFZGVlUVpaisvlomvXrjz88MMcPHiQnj17cscdd/zqtU6dOpV169bx1VdfsXfvXpzO6t+/7t27IwgCTZs2pfSsXtDFrrk2kpKSGD16dFVo+Tm2bdvGzTffjCRJmM1mBgwYwJYtW+jVqxepqanY7TWfywE6dOhAZKS+U5ySkkJJSQlbtmxh3759DBo0CACPx0NSUhLt27cnJiam6vkLdK+7zaZHkNWrV4+yspoVSpYuXUr//v0BuP766xkzZgyPPPIIBkPN1LvWrVvXaNuxYwfTpk0D9EiIxYv1qL7p06ezcuVKcnJy2LhxI82bN7/oul2MXzW4P/74YzweDwsWLAgJO/D7/SxatIh77rnnV47W63fPnj0bt9tN9+7dmTBhAps3b+all17C6/XSr18/Ro8e/bsnHeY/QA1A7oxqYxvAkwWl36D5e+N5c0FId89bC7A98yT8pwZ3oAyC5brHWbJXedIvJ8EzxQjGOxCkt/VzARgSIbL/ZT/XhZQE4ZNyeOYM+DUYEw33RULM2U+Ut6KY0z9v5vDX7xDdsA1N+92DJT6RyG++IHj4KJrbjdwyHTEhvsbYYlwcYtzvN7LPx1dRzHfPDyTo1XeRi4/uZvO/76Nzys14Fy0BoGLHTjSnC8ujD4YY/ZefmjvLmhqstacYHYX1hWeofPQJ/Ju2EP/8WFJ7DCN706cIgkCja/5ORJNOBDWQBCBQAWVrIeufECiG+H9AvadB0dfPKEJ7MyyvC34gthBKzg/rFwTk9hlgMLKqEm7LE9EwIwDvNGjF4PTmmI1nxcaWrag54c9WEHP3cMrKymiTkUGh0YJRhOhWPbnWB8udMMIBz8bCjCKVZM3LhtOnqw4PBAIcyMyiRcfODDyp3z+r68HMYliiRpLe+Ao6Nu+CVZYQRBFXcR673w/dVfU5y3AX5WKJ1g3uC8vMARgjYmk19Ek2zbibDVOH0+2f81GDfkTZQHTDNpijEnCX5CMbLfhd1aWxBFFCEEQ0wPvmUawz2mFO0e/ZwJ4SnM/srp7HmnysM9ohRoX+sJkiYqjf7SaSO16PKCtVpava3j6RXQuepvCXrSS1u4Y2t03AGHWJmz9BUHP1e9u3+Djmx9PwvJUFGogN7brS+HlluZRedRBsSo0a5oJZRukSi5wWgZrrRmpkQ7DLtdY6rw1RErDFSdjiwkZ2mDBhwlwKYkoy6rETtbZfDs6Fle/cuZOtW7fy+OOP12pwC4IQ4vk+l6t8Ybt8wfORqqoYDIaQvN/8/PwqY/JS+OCDD1izZg3Dhg2jW7duZGZmomka7du3Z+XKlXz//fesWrWKZcuW8e677150nL/97W907tyZzp0707VrV8aMGVP1ntForLqe/8feeYdHUW5//DM727LpPaGFXiNSBaQooFc6KiCKIHovVhSuCoodFSyAYkMQG4oFUWl26SIqCIJIR0ICCaT3umX298fZ7GaTAAFB/Xnn8zw8sO9OeWd2E+b7nnO+53TXfDJGjx7NN998w+uvv+53/VVxu924XPJMZ7We3Iyk6n2snIfL5WL8+PHcdNNNABQWFqKqKnl5eTWOVXk9tV0HQE5ODps2bWLPnj28++67uN1uCgsLWb16NYMHD64xn9rmajQa/e7X4cOHsVqtjB8/nrFjx9KnTx+ioqLYt2/fSa/zZJwyn9RoNHLw4EHKy8s5ePCg98/Ro0dP6zZ37NgxHnvsMV599VVWrVrF3r172bhxIw8++CCvvvoqX375Jbt372bjxo1nPGmds0EDZ2bNYYdnrHr/1j/Sz9WRC2mzYFsC/NISdnWXWutzjctFwZ3P4IpZjRb+NFrE87hCl+NKr13MVaWiOI/ijBTyUvZQmptea7rRqThsh+nZYFYgX4OHs+FHTxRTczlJWv8Ba6cP5egPy9n53nS+mdaPsrwM1NgYzL16YLm8H2p8XJ365pZqkGSHeXnwZbG0vDod9pJ8r9iuJGvvZgwtmviNlS18m5KsHI47/dtin0uM1iDiO/i7rV8w6n4swTVrcxWLhYAbriPil80EPfskFmsI3W99kZHvpDB0UQrHRs+hd14U8/Igxwk4MmD/1WA/BloJnHhBSgrc/t+BSCPEGUGNjiTwofsw9e9NxI6viCncRcSqCajmb+hlTKNfgOznBiZlGSgy+MSj6eKahiXGi7sRX68e/YcM4yV3FAlJ8jm9UGhh2HEDbxbAHRmwuMDNwtBCKlKP1DiG3W7nhMPNj+XweTGMOw4tzTAlHHoHQJDZ5E39NxjNBNdrXuMYlpBTl38YVJVGF1/Nv55aTWy7nuQe3kF0q+406DIAW0Q8iqJgCYqg801P++3Xdsh/4WfPF9upeddO3EUOKj466retO9eOllxL+y4PqslMiaaQ5oBjDigPq0/3ia8ycPZ3dPnPbG+qe50IMGDsLuLcdaCI8vm/Yx5WH7V9KFpmGQEPtkVtFYwSZ8V8XSOMXSI4WdqLIdiE2igQU/coDNFWFKve60pHR0fnfBE0czrYqhlh2gJk/BwxcOBAnnvuORITE2sI5kp69OjhFc27du3i6NGj3vHPPvsMTdNIS0vjl19+8dsvODiYxo0be/fdvHkz119//RnNb/PmzYwePZphw4ZRUVHB/v370TSNWbNmsWrVKq666ioeffRR9u4VY1VVVb2itpL8/HySk5OZPHkyffr0Ye3atTW2qes1n4oZM2awaNEi7+vu3buzYsUKXC4XZWVlfPbZZ7UauqmqelqD7e7du7Ny5UpKSkpwOp0nTc2vCytXrqR79+589913rFu3jvXr13PbbbexZMmSOh+jS5cufPHFF4CI7Ztvvpndu3eTkJDAjTfe6E0vP919ro1TPlmMGjWKUaNGsWbNGnr06EFgYCAVFRUUFxcTGXnqSMTq1asZNGgQcXHyEDV37lxSUlJISEjwpjAMHTqUr7/+mksuucRv38LCQgoLC/3G0tPTz/jidKpgMEO9/0LW+74xxQKRI1AcwQTcNoGyVxZ43wq49T+1tuKpE85sSH3K97oiBVLuh2ZvgPEMj+ksAq0YUCRqqfhW45SQENSEBLJbX4GpRzdwOHClv0nED2tPfjygojCXnR884TXjskXWY+Cc7wmOa3LK/apiVODVOIluR6twZwa8XwBX2MBRkM2eT+f4bV9wbD/lBVkEhNeMaJ+OXRXQO8XXN7qHFVY0qN1luxJzYBiq2YrL7jM3jG7TA233fr/tDLExLC03cU8SvB0PVwSC7RyXdVtCIuk9+W2O/biSzKRtNO09hMj6NgylP0NgezD6Z1EYwsMxhIf7tT/LcECLJLB7BN/kTGhigiFlP6D4RdANUH4EXKXe75pWVIS7oAh3aSlKSBCW664m4Jo2KCYj7LtExDpQXw1l8QW/0jotgUINijQxXKvEfGkfzIMHYP/iawBM/S/FOnQQARExtD4iNdoAfW0wqFpm3EdFCs+EBxDfsDHGXXv8/hNq06YNa52+qPQxJzybC/uCoG+g/y9pa0gkPe6az1dTemMvlhSxC697GFNgTRf1Gp9DcDj1Ol5GbGIfDKqxRv2+arbQ5NLriE3sQ8Zv3xFZryMBWRFoC2RRzjy8AUqwZzaK4u1X7UdtYx5yXfBKHszMkc9xYCAsig8kJqBme7HTYQgwYv1PMyqMCs6fc1GCjKgtglCCzahNg3DtLcQ0tD5KqAkl0kz54mSsE5qhhJw/530dHR0dndNTWad9PlzKK+nbty8PPfQQkydPPuk2kyZNYtq0aQwePJimTZt6tcmYMWM4dOgQAwcOpH79+rRs2bLGvrNnz2b69Om88cYbmEwm5s6dW2sApXoNN0j99/jx45k+fToLFy4kKCiIjh07kpqayrhx47j33ntZtmwZqqry7LPPAtC7d28ee+wxnn32WTp1EqPSsLAwRo4cyeDBgzEajXTv3p3y8nJKS0vP+JpPRb169bjnnnu8NcujR48mOTmZ4cOH43A4GDp0KJdffjlbtmzx2699+/a88sorzJkz56QGY/369WP//v1cc801uFwuevfuzVVXXUVaWtpp51Wd5cuX18iavv7663njjTc4fPhwnY4xadIkHn74YYYNG4bRaGTWrFm0adOGJUuWMGjQINxuN127dq3RMq0uKO46hPa+/PJLXnjhBb799luOHDnCmDFjmDlzJv369TvpPo899hgmk4nU1FROnDjBpZdeSosWLdiwYYM3P/6HH37gjTfe4K233vLb9+WXX65RyF7J2rVr/XL6dc4AZyGU7obUp8Fgg0aPgaUpqFa07GwcW7ZR8dW3WAb+C1O3Lmdvmpb3Ley9wn8soA0krgfzGQhORyYkPwBZi8EYCU1fgbB/+Yl2LSub0tfeouKT5aiJ7Qie+ShqQqNTHjb/2D5W3OLvJpnQayQ9734Ls+30CwIZTuh7FPZ5zJcTTPBRPdheBreHQ3lBJl/ffykFR/1TTga/uJXAyPrYIuvV8QZIFPfKNPjeE6webHMwNyKbxkoOJmM4qCG1LmI4K8pI37WBTXOkZ3NY40T63/cR2sx5lL/5jmxkseDauIYrYjqyuwJMwJFmUP8PapKKwhxcpcUYLTbM4dG40jPIvWwoEWsWYSiankH8WAAAIABJREFUi1L8k3wPAS78GYK6nPaYSwrgumqtK4cFwvLw7Rh+9exvioVWH+Mu3opSshOix+G2Xkjpwk8pfWEehqhItKwsonZ9hZJ2N4T2hSP+/xk74idzq3UObxca6W6FzxpAVBXF68rOgeIS3LgxBAVhiIrkxzK4OMW3zdqGMDgVyqv8ZlWAlGZQz+CipKSEXbt2Ybfbadu2LRERERzFTOskf4H/ZQMYWIvhteZyUl6QRVnuCSzBEZgCw7AEnXsHLS3fjmNDJq4DhZguiUFtG4qhimB1Hiik9L6d3gYBhvoB2J6+sEZKeSU7y6Fjsv/YjCi4P/KUOv3UcyxzQZkTTAZvKr3rYBEVHySjJobizpVrMLQMxja1DUqgHr3W0dGpG6mpqfTv319/7jwF+/btO6t6Vh2dfyKn+nmo09PHggULePfddwFo0qQJy5Yt44477jil4Ha5XGzbto3Fixdjs9m4/fbbsVqtfitAbre71hWh8ePHc9VVV/mNpaenn3HKxrlGy8vHXV4OqgE15v9hfxRjCIRcDC0/kEhxFXMpQ1QUlsEDsAwe8MfPY2sLigncDt9Y5FVgrL29Tw3smZ768m8g07MY40iHA6Og8+9+AtMQHUXgtHsIuOUmlEAbBo+jNC5PZFetWaNRnJFSY6zg2D5c9jKog+D+qtgntgFSHJIKfE+4BP6sodF0+fezrJ3uc7aMu7Avhcf28/PCe+j3yHKstfQhrg0XEmkF6GyFt0N3Eb27n6dmXZVFiJixoPorM6MlgMgWXRj8/I9oDjuqwYz24UrM906GWydgSksj58KO3E8Uuz32DA4gy3VqwZ3thN8qxPH7ikBoaoZwFXAVgyOb4rxStix8gOyDPxN/waV0vukZrC4VY/14lLyPUHLf8D/g8Reh+ZuSgXEK+lrySGlQDMBX5cHckxNGpBE0cwJKzC0omQuhyfOQch9KkafVU9Z7kDAHU49eBDd8GlfKUUzdu+IuK0BBEX+BahidebQyacyKcnNHcC6BihUIxF4i5hzmqEioZjKXYBSjszKPwF5ZDHeFw+xc3zZjQiDIIClWISEhdO/e3VsHBhCvwYZGcF8WFGuSTt6tZutpAAyqEVtEvLdm+3xhCDNjHl4fnPVQTDXTHtQEG4GvdsG5MRMl2oqxS8RJxTbAlrKaY+tKpYd66FmWQBsCVAjw31mJteAuc1HxTrIMmA1Yb2yii20dHR0dHR2dv4Q6PYFomuZNDQeIj4+vUTRfnaioKHr06OFtNn/ZZZfx9ddf+xXoZ2VlEVOLcA0JCSHkb+aO7Uo7TuF/7sD+7VrUli0Ife8NjBdegGL6f5iieKZp3Wd8/EhotxoO3yLO6NFjIH7yaUUVAI4s2H8VRF4JedVNLtxQ9LO4q1dBMRp9Tt6uMig/LFF8gAYPgLUZqD71Et44EXNQGM6KUjSHKOfGva/BElS3BYHDjppjqU4I8Xy1FUUh9oJLGD7/N45sXEJIveZYQqPZNHsc9uI8EfZ1JEoVQ7ZxJ2B6SCbRSTf5DOJwwZFJED6ohuAuyU5j0+yxpO/aAIDBZOZfszdzT3Bz1psN/NShI5MzYHmxbx+LAjGnED75LpiWBW96jCEfy4bXY2FscBHGku2U5Wew5qknyD8qNUdJGz+krCCDi+77CLVDe6Dm/XWbYlE8ZQJacTFa6nHKPliKsWljzAMuR42LBUcWMSmTULKXAAr/jrqeEY3mYDKEoRSrlP/QCXPvnzAEhPrEtgfl+CwM1i7kjRgjA0Yj0ce3gKUBhA+EY49VEd4KxN3K3QF2THlLUA68htvcCK3Bo/z64RvkHtlFh+unE960PeYA389QpArrGsGEE5DkgEIXzIiGywNhRRH0t0Fvm2dhgspp+P/qDTRALxt8Vl8WWaJUqKNv13lFURQw1T4RxWpErW+kcHRjyjQxBImuNLOrhYttNccGBMpCxLnEEGom4IG2aKmlaNkVGNuFoYTpYltHR0dHR0fnr6FOTyEREREsWbKEkSNHoigKy5cvJ+o06cZ9+/bl/vvvp7CwkMDAQDZt2sSAAQNYuHAhKSnSaufzzz9nxIgR5+RCzidaQQGFd/wX+zdSh+E6cJC8y4YSuW87avy5d9/+f48aACF9IPE7QJO0Z7WOdZr2dCj6AQIvgMAOULzV/31bG3AWg7GWXFsAeyr82hHcnhrZnKXQcS8E+HoI2oJVRr+xBkd5BTkpR0nfu4vWg2/HYKzb4sn1IVKHWrUW4/Ywf6FhtoXgDIkk/+hejv64gvwUaQVmDgpDMdQ9nGdQYHAQfNEA2ikuKPOvwcbtAHua3HOPM3dZQTYFqfu9YhtAc9jZ+dZUOt75KQeNERgVeCUWWpjhyxIxYnsn3l8UVqdIg7cKxChuQVQeAy35RLlzUR3BkPIgzrBnvWK7khM713GivILgx6cTmLZDFj/KPbU0xkjctvE4d+5GbdYU56+/kXfpAPAs5qlt2xC+6RtU1zqP2AZwY8p+j6iwy3A6XWjBl+AIi8H50ocEPXEHNFsIGa9D8c+yuWJEy6kSanY6KX74FYJfuBulYL0sDKW/JqI7dgKKPQuz60c4NF525wfU/K9pfcUXfHrr85zYuZbh837F3OQC7yEtBugeIKLbBQQpEKxKpsDlZ1ieHPn/TBeecMJNJ+CbEqhnhEXx0CsAAmoR0Q2M8Hy0OPuXuWFEsDi4n0yg/xEq23bp6Ojo6Ojo6PzV1Onx7oknnuCee+7hiSeeQFEU2rVr5+3jdjIuvPBCJkyYwJgxY3A4HPTs2ZPrrruOpk2bctddd1FRUcEll1zCgAHnIIX5POMuLcO+er3/WEEB7oJC0AV37SjKmdVrV+K2Q0hviP43mMKheAuU/AoYIH4SFP0EaXOg8azaW42lv+4T2yD/Tp8v6cYA9uMouy9BLf8dFagXegX1rluEYql7G676Rkn/fThLTNMeiYJWtTzbm4PCSeg1gk2zxwGgGAx0n/jqaR2lqxOuwqAgcDhsuMOHoeR+6nvTFCumcq4Sr+B22cuoKMypcZyKwhxGBxRzZUgwtrIinKkHuGbLZ0xs15uwFl2wBUafspZWQxYZFkXlclXuI1gzX5U3mr8BBhvW0EiGv/gt+ccOsfOjlyk4tp+AiHiy3SrvFBp4MrYNhrgNUPoL7sIs3FoiBVdPxvHDVsK/X03Z64u8YhvAtXcf7pxcYE3NyRT9gNFVhDtnEYH938XQZiPK/l5grgeNnpR08uyluOtPp7CgDYVJB7E67ZjmL8T++ZdopY+jhvWHPZdB2AAwRUHyfdBmFRy4zv9crnyMriSCYhIozkzhwJcL6D5xXo0pncrE7p9IsQvuzxSxDdDcBOll2bhMRjDXrCkPV+G2cBgdIt+jQAOE/UndtIo1SHPAkiIpARgYBLH/Y5+Xjo6Ojo6Ozl9DnR45GjduzLJlyygoKEBVVW/j8dMxcuRIRo4c6TfWo0cPVq2qpZ/t3xmTCVP7RBxbfvaNmc1n7+L9v4LbJZFDg63ubcbMDUUc7/kXqKGQ8DRYm4iYzHgbDt8BuMBdAc1er+FwXWuduNFTc6s54fgrUP679y2l4Bso+w0sdV84CVahj02cwt3uk0cljWYrDbsPY+SiZIpOHCY4vhmWoAhU09lF3kymUGj6AhhUyPsGbImQMBNSHoFWH/quSTFgi4jHGhpNeUGWd7zNsDuIyrofl+Ux9n/zGdvevM/zztM0638DF932AsZTpNUHKjAkEC41Z/rENkD+amj2KsYj9xJesIbwqAuJm76A9XMfouGoh5nmiCYMhUJrIFHGQCq+20vxA2/g3LVbbiBQ8tQcLIOuoHzxB37ndBcUQdOrILNa7XdoHzg2EyWwA4acd1GyxHFeShJGQocdUG8KRaZmdC+L4HCFpMy/MHkao0ZdhSEsFJQQ3O3WQdYHuFGg9SowhGAw1nT8dhsjcZQVyX2ISRD3fFcBaGXSZ94U+8da6f0/pNgNaz1mqG9G5XGlto6ItNmQHgyNn4GAtt5SjhwXlGkSzY42njRL/bzxWwX0SvH6u9HaLItmuujW0dHR0dHROd/UqXqupKSExx9/nEmTJuF0Onn00UcpKTl5v9V/GmpUJCFvL8BQz2NSZLUS8tZ8lNC/V5353wp7JpTukxTo4m3gqBlxrYEzX1KkT7wKzjyoSIaD10kf76KfIHsJXh/nnJWgVWt94CqByGHeSC8g/44Z5zl+HpT+VvO8JbtBO/OeehHq6VOAzQHBBMU0Iv6CngSFqpjK10HxdhGGZ4MpFurdAy3egahRcPhWCOsvafuV57SFkJ96gP7TV9HsshuIu7Avve59hwadL0FxpmEvPMGvHz7pd9jD6xbjKCv2P5cjB8oOQuGPYD9BlOri7XgIcVRr1xDUGZImoeR9LgssxVsISBtD/+kf8ELsJXxZpnJtiGQDAOB04vz1N6/YBlACbZh69vA7rKFRQwwN6kHwRVB/GhisYAiQ63drULYPQnqi5H7iPx+3HSpSKLJ1ZUxWuLfmvsINE8tCKO3UGUVVcTldpO3azbpFW1i7cANL/9ON/GMpuBvPkvN40EL6UZBRREVRLmEJibQZ8h8oWC895n9pCb928VvE+V8hQIGuVrjQAkPZRsShkZKRUrAGdvWQHunAcQeMSIOGh6H9EeklX3Keer7XRp4LHsryiW2A/XY4aD/pLjo6Ojo6Ojo654w6re/PmDGDmJgYcnJysFgsFBcX8+ijj542rfyfhNqqBRHbN+EuLkGxBaCEhWGw1eICpAMV6ZC7XHpvu4oguKcn7dhSw9zLi7MQjr8sYsleS/89R4Z/9DqgJSjV1otcRfD7bZIWXPQT4IbgiyV/1Z4Jac9AxDDI+7zKTgoEd4XSvRB0AadFs4MzR4SlGuyJ3pvBcJofpbIDsKubREQBwodAi7dkQcCZLy7fWoUc03wKB3yDSVqsGaPkWK0/BVO8nxGeyRZM455XU56fSatBt2INjSHrwFbWPH4dncbdR3hUGJqzmvOb2y0ithJHDiRPhcy35XVwT2j5PlHWBNyBrUWQVl5LUFdIvt//ePbjFLkryFID2NgIcp1g9nxcxq6dUZs2wZV0RAbMZgIffQC1UQPCf9pA2fzXUZs3JeDfN4hpGkDDhyH+LtzOfJSM1+DQTfJxYEMJaI1SfSHFkkCJBtvL/UOpGnBCM9AQqCjOYeOz1+EoLfS+v27G1fzrhR/ROhzCUrwFs6UeGBviPniA4fO2EBYXhpIxRwwAE9dLxkXJL/J3q6VSBvEPx+7pUR5sgBdj4bOCEqKzqrVxdDsg70vKYu5gWhZs9KyNZbtEfCc3k5TyPwO329e/vSqOWsZ0dHR0dHR0dM41dXrk2bdvH3fffTdGo5GAgADmzJnDvn37Tr/jPwjFYECNi8PYvBlqvXq62D4VWgkkTRQBDFC0GdJmSxpudZzFUHFcos/HpkP+t+JqXhWDFcKugJJd8loNEQFvqi5MFWkftqsnZC2BrI/k34oiAvz4XBH9jZ8HS2NJyW75PmR/DL/fAPaTRJ01JzgLxAG9YCMcvksi1EU/wsHrIeUBqEg9+f1w5sORe3wCFUT029PBkQtHH4dtjeCX5rCnnzi7nwpjCAQ0g+hrRXyj1bi3luAIQhu2BtysmtiBTbOuJzfpV9Y8MRYNC22GT/Lbvn7XQRitVRZDHBkitq0tIHEjxIyHvC+g4hiKMQIu2ARB3aRmWjHJAkhVDFaCVCsLtP1Ylz9Bu23vYyuUiKcaF0v45jWELHqNoFkziTywA2PzphhCQjB360LIG/MIfOg+1GgLFO+EE/MlgqwGgCkOLXo8rvoPYW/6KeVBl1HS8GmZRyVxE8EUS5ABBlRb37EoYt4F4LKX+4ltgOL0IySXOolKqU/Xoqvpm9edbHN96nXoR3hcIMrORFm4OfYE7BsOzeYBBsmccNdsM3auKHLBCQdkOU+/7fkkwwkzcmBoGjyRLWUG48JMaJaEmhtbGlHshg3VE1GQVnp/FhFGeMS/kxsNjNDW8ufNQUdHR0fn/LJlyxbGjRt3RvtU3X748OFnfM5169bRqlUrdu/efcb71pWbb76ZjIyM83b8utCvXz9SU2s+52ZmZjJlyhQGDx7MsGHDuPXWWzl27NgZHfvDDz/kww+lLLJVq1a1bjNu3Di2bNly5hP/G1GnCLfB4K/LXS5XjTGdvxeujAxcR1JQVBVDo4aosX9i3/DyQ/h7eANF30PBOgi7zGem5sgWA7Tjc8UtGk1cyZ1jxW06cxEYI6D+PSKYL9go4lUNBFXazWHPlNRyg1nGms2HvQMltRWg3hSJGpf8Iq8P3QQdfpU5aKViqFa4CRQLUIuasWdCxptQsFZEf/hgEZ8lOyWdu5LsD6H9FrDUr3kMze5Nr/XDkS390E+84Bsr3QOpz0Dj2bX2EPffPwdylkHGQjA3goQZEik3x4MpCpdLYe+Kl3CWVyn/cLs58t1yEkdMJbpVN5I3fUzchX1p1ONKrCFVVIk9HVAkCn/oRp+zeMqD0GGnpJG3/VwimcZIaPGeGJC5CiTi3+wNKrLzWH17R9weI7TwJu3518xvCQiPRY2LJWD89TWvye1G0bLBZZeFmMM3Q6nnP7LGs1HiJlJs68RHzo5sL1dYlg4NjG4Wtd5OW0M2qhogmQL2dILMbp6OjiLHCZ+XQIIJ3o6XUgAAo9nmNUKrJLp1d3a5LFgVaGORWuNkO8Qq5biPPY1Stbe8IwOKtkBQF7C180vrP5ekOWBKJnxWLHN6M07E4qkM7s4HuU74zwn4wvN1+rEMtlfA8thSDPGTIPsjcGTKm4GdIOgirIo4uB+rsh5kABr+yd0UuwfAlgSYlye9428OhTi9fltHR0fnL2Hv5yV8/2IBhekuQuJUek0Ope2QM2zrcQ7YutXXCWflypVnvP+yZcsYMGAAH330EYmJiedyal5ef/3183LcP0ppaSnjxo3j3//+N7Nnz0ZRFFatWsVNN93EV199hamObZOvu+6602/0D6BOjxxdu3Zl9uzZlJeXs2nTJt5//326det2vuf2v4erGCpSpIbZXB9ibhTxdIZmTK4T6eT1uQLX7yKS1HZtCV/7+Z8nugNaAQp+oju4h4hpQwBEXS1jpXsh7Vn5t1YmUUr7cektHdIb6t8n++V+Bkm3iQmbwSLCpsMuqDgG+4aJ+DUESrQxfCh0PizO5tZmYIoDYxhEXAnHHgc0EUpH/utfRx0xVI5RFUeuCPR8Tz/wihQRVvYUyHjLf1t7mtSqVxyVlmZVU+dNkRB3KyTd6RtTw8DWGgo2yGtjuAhVRwaUbJMsgVMJbrdLBE7SRM/ANlkUaPslbG8GiWtRAnsQ1qhdjV1DG7TBGhpFQs+radhtaO3t0Gyt5TMo3uET2yCCOm0ONJkrzt6VBHaAzklyT9UgHE4Tm2fJ5xzduhuKaiRr/xaKM5IIsBSCapOFEFcJuPI8qflWcGaI6Vn575KB0PRVSLpDRPfRxyBqDMGWAK4IUpiXD5kuKHUrHHLH0c5QBDsvApe0AXNHXE10wku8FR2JI96KgvQZr+xvbQ2P5fKZ37Bpzg3kHNpGXPu+tJr0Fo9qYRxqcJSwrNcwaOUo3IHTHoJKbYXHGoRdDvF31r313RmQ7oB7M+Ejj2DdVg59j8LuJhBfh//LXG65R0cdEG6QnuFn23qs1O0T25VkOMFU8jMcfVDKGypSwBAkCzLmGIKB52LgdzvsqJCe26/Gylz+TEJVuCgAOllB5X/O305HR0fnb8Pez0v4dnoeznJ5Riw84eLb6XkA50V0O51Opk+fzqFDh8jOzqZVq1Y8//zzzJkzB4BRo0bx8ccf06pVKw4cOMDLL79MRkYGKSkppKWlMWrUKG6//fYax83NzeWnn35ixYoVXHnlldx///1eU+mePXvSv39/du3aRVRUFCNGjGDx4sWkp6fzzDPPcNFFF5GSksL06dPJz8/HarXyyCOP0LZtW6ZNm0Z+fj4pKSlMnTqVGTNm8O677xIdHc3jjz/O9u3bMZlM3HHHHQwaNIivvvqKt99+m/Lycux2O0899RSdOnXym+vWrVuZO3cu5eXlFBYW8sADD3DZZZcxbdo0goKC2LNnDxkZGUycOJERI0aQn5/P1KlTSU9Pp1mzZlRUVNS4/i+++IKIiAhGjx7tHRs2bBhmsxm73U5FRQUPPvggGRkZZGZm0qNHD2bOnMnWrVuZPXs2mqbRokULGjRoAMBdd90FwCOPPMKuXbsIDw/nqaeeol49yWBcunQpTz/9NAAPPPAA3bp1o6SkhCeeeIJDhw7hcrm4+eabGTJkCMXFxSc992uvvYbVauXw4cO0atWKOXPmYDaf/zaidXrsmTJlCjabjeDgYObOnUurVq247777Tr+jzplRuhd2tIf0V+HoQ7Cri6RInyHliz/0im0A15692L/45lzO9NQYI6HFIl/EL6QPxN0Gme9I/XMl+VXaPR19WGpgwweCJcETIesqUXFcEpWOHAUhl0g6s8EKR+4VsQ0iUA/9W1pkWRqJgLa1BZMnEm5tLFFYSxMxAWv7jaREq0EQOVKc0as7nmslPrENEHqJ9PXWymsXV4pR0oyr16ArKkRdK1H7oK4QMQLa/yQp8cEXQ+vlMrdmr0K7tRBziywSVOLIkWh4VRw50j+6Kq4CqDgi7dJ+vxWD8wQtB95MSH1fD/LothcT066X9/VJe48bo6H5WyKIq+PIEsEP0natIhWOz4ET82RBRDHislcQGNOIqxd8T/+J19L/tmGMfO17VEM57LkEtiXI9yF9PuxoJ4sEjjTYO9hnQFa6G5Jul4UX8KTki+htaIJvGkot8IEmMDSgEEPyfSK2Y8ZD4jqUev8FVyH750/EnLKTaLfdK7YBFEUhtEErLnv8C65ZnMalDy7laEgjnglLJ/63CwhIewrLiecx72yH4szyzKNKHytjJESOkPHaWtT9QVxuSHfVFLm5GuTV0XTsiAMuOALdU6DVEbgnE3LOMi3dANiqCdXxgQWox+fIYtNvvcUx//BtUPi9d5uGJvi6ymc1Mlic/v8KjIoutnV0dHT+Sr5/scArtitxlrv5/sWC83K+HTt2YDKZ+Oijj1i9ejVFRUVs3LiRhx9+GICPP/64xj4HDhzgzTff5OOPP2bhwoUUFhbW2GbVqlX07NmTBg0akJiY6NeBKTs7mz59+rBixQoqKipYs2YNH3zwAXfddRfvvPMOAPfffz9Tp05l+fLlPPnkk9x9993e/cPCwvjqq6/o16+fd2zx4sWUlpZ6Bfa8efOw2+0sWbKEBQsWsGrVKiZMmMDChQtrzPW9995jxowZLF++nBkzZvDiiy9630tPT+eDDz5g/vz5zJo1C4CXXnqJtm3b8tlnn3H99deTnZ1d45j79u2jXbuaQZ0BAwYQGBjIhg0baNOmDR999BHffPMNP//8M3v27AEgOTmZd955h2effbbG/l27dmXlypVcfvnlzJw50ztus9lYsWIFzzzzDFOnTsVutzN//nzatWvHsmXLeP/991mwYAHHjh075bl37NjBo48+yldffcXx48f5/vvva8zhfFCnWIfJZGLixImMHTv2jNqC6ZwBziJfBLYS+wko2gqRda8rcWsazoOHah6+lrGzxZWegWvPPrBaUZs3rRk5N4ZA1Ggx2rIfl/rW/SMk/Ti8St/1sMsg1eOWXbxN+h+3+kjagKHAbxdDeZK8r4ZBh18kEmwMk5Tnop+qzUyTCLOlkXfE7Xbj1sBgDJOa59C+kPUBpD0PjR6XKHjJjprRbTmpRJ3dHjtje7oI5qz3oNETItwrXdODusr1ObMg+xNo+JD/oQwWqYeOHif3JOlOaPGmpMKnPi3Rf5C2aBdslG3UUEmNP/qoGJolzIbAdhINNpgl+6F0V7V7HyW18848KE/CFtSWgbM3UZp7HIPRTEBoDNawOvQcN5h8deKpT0jKfcQQWVSIn+SLvtvTYccF4MqX12nPQOI6rFkL6Hn7kxj395bvMWBRwwhovxVyi+S+HbkbOmz3fAc0yfCovlhRusf3eUaO8Msc8Ot7ba+Q6Gq9u6U+f+9Q0EpQAzvR6brX+Py+YQx+/kcCo6ql/GsOrKG+SH1nF1jTl4Kryn+u7gqUjFdwR1yJkrhO3PLVYJlPyW6IGHT6+3kWlGpwxA5tzPBzlfJwFQitw1JpoQumZkpLrkreLYSpkWcX5Q5X4ZlomJTpG+tiM+E2RuDVsBUeI7xq7fn+13qU6+jo6OjUTmF67V1hTjb+R+natSthYWG8//77JCUlkZycTGlp6Sn36datG2azmcjISMLCwigqKiIkxD8os3z5cu68UzIXBw0axHvvvceYMT4Poj59+gBQv359OnfuDEC9evUoLCykpKSE3bt388ADD3i3Ly0tJS9PIv3t27evMaeff/6Za665BoPBQHR0NF988QUA8+bNY926dRw5coStW7fWWvI7e/Zs1q9fz9dff82vv/7q12mqZ8+eKIpCy5Ytyc+XZ7mtW7d6jbG7du1Kw4YNaxzTYDCcMjI8ZMgQdu3axaJFi0hKSiI/P99735s0aUJwcM3WylarlWHDhgFSU//CC76Sy8o2061btyYyMpKkpCR++OEHysvL+fTTT7338NChQ6c8d4sWLYiLkyBJs2bNKCg4Pws91alThPvw4cOMGDGCiy++mG7dujF27FiOHz9+vuf2P0gtH0d1J+7ToBgMBNzy72qDCtZx1/6BeflwpR0nt3Mv8i4bQl6vy8i/bCiujMyaGxosvpTjvK8gtJ/0RjZViQTa2kL9+0XUYoDQSyGguUQLcz7xiW0QQZf+mi9qrgbLMf2u0yhiy0NxloMtrxfw1UO5pP5SiqO0BFJnQspUyH4P9g6AAyMlbb0yEl4VYwg0eND3Ov8biVRrdshdJcK40ZPQ6hNoNMNX021pDOVHobyKcYQzX2qcj0wSUVqwBtLmSg15wGGJAAAgAElEQVRwsa+GCPsxOP4inFgg17/nX7KwENILtCL4fQIcvkUEdeM5Ir4rCbtCMgiceZINkLscTrxMQGgEkc06Ep7QDmtoJDjyJEpfHWeBpya+SgjUFA8d9oojtxriac1l8+2f9YFPbIPUxWe9DwHNUQtWesV25WdoSPek/cuALFLU99xjrcy/pRuAtbnUZDeeJSUDVSP/VTFFQOzNEHWNlAtonv9MSn7BmjuLVldcT15ylcUJRxZkvg+HboDMd73lBYEqqLX8HCqKKi3S9o8QMV52CHZfIlkF54lAA5S5ReRGeKakAs/HQEgdfi2Uu/G2RKtK2lkalgUYYFwo7G0C78XL3+0CbCgNp/t/D23tpMRAR0dHR0enGiFxtac4nWz8j7J27VqmTJmC1Wrl6quvpmvXrrjdp25TYbH4XDUVRamx/Z49ezh48CAzZ86kX79+zJs3j0OHDrFz507vNlXFqKr6X5umaZjNZlauXOn98/HHHxMWJs84VmvNkkKj0YhSJUUrJSWF4uJiRo4cSWpqKl27dj2padyYMWPYtWsXiYmJ3HbbbbVea9VjV7/m6vMHSExMrNUs7qGHHuLQoUMsXryYWbNmERERwdixY2nWrJn3mLVdH/h7hrndboxG32p91TlomobRaETTNGbPnu29h0uXLqV3796nPPfpPtvzRZ3U3IMPPsioUaPYuXMnO3bs4IorruChhx46/Y46dccYDI2m45eyam4okdMzPVTLFoSuWoqxSydM3boS9s1K1FpWp84Ut8tF6auvox33iSjn7j041m88yURCcQX2wt7gfUojF1BS2gyXViXUZYqSdk+dk6DLUWj6sldwae4maOEv4G76roi9NqvEGKyyLlwNhMZPS8QaZL9Wn3gjayXZDpbckM33LxWx7/NSltyQg1ZeJAZoVSn51RfBro4aBPF3wYW/QNP5cOF2WTBIXA9xd6IpoWjRt0DOp7D3CjGMCrwQAtvD7t6wfyjkr5O0bPtxvNFwAHOCRIrLask8sB+D2BtFjAb3kDT4sMtg31DIXSER9h1t5Vo7HZR7036LpDanPSeLGPXvEzFfuF7S7EHS0jNeh/3D4cgUn7O62yVi8uANsKe/mNhVprCrFln0+a2nlDqkL4CdF0gmAUhKeXU8tfaKq2YKEq4iX49rY7jcm/DLxBzvxDz5DCtFt7k+tPlc0u7r3VOLK30VFFWyKpx5VDfsM5RuJappa2yRnui2sxCSp8GhsRKtPjReyhOcHvEcNVIyKrwHCID4yTjMXURgZ70vixlqmCwS1YYjRxYbnDXT0OqKQYHLA+HHUvikPmxoJLXb19YxJTtChXHVqiQCFEj8A+7cYaoYt10fKn+HqYC1KXQ6AM0XyefVbq3PGFFHR0dHR6cKvSaHYrT61/YYrQq9Joeel/P9+OOPDBw4kBEjRhASEsKWLVtwueR5TFVVnM4zr7NatmwZ11xzDRs2bGDdunVs3LiR4cOHs2TJkjrtHxwcTOPGjb1GbZs3b+b662sxkq1C165d+fLLL3G73eTk5DB27Fj27t2LoijcdtttdOvWjdWrV3uvrZL8/HySk5OZPHkyffr0Ye3atTW2qU6PHj28c9u1axdHjx6tsc2AAQNIS0vzS8n/9NNP2bp1KwkJCWzevJnRo0czbNgwKioq2L9/P5p26nq40tJS1q5d6z3WxRdf7H3vs88+A+C3336jpKSEhIQEunfv7nU4z8zMZNiwYZw4ceKszn2+qVOiX1lZGdde64uQjhs3jqVLl563Sf3PEtAaOu2BjLclXTjqmrOqDTWEhWIdOghTj4tQUDBERZ5+p7rgcqElJdccTq75gwigudxk7LWzfGIRZXkatggDV74SRVw7MwbV88tWDarRm9t19BjF01fh3L0P66jBBIyMwZA9ERKeFoFWWWttjodWH4NWjstlIDs5hLIDKtGtXBSdcJJ/zP+XaMEJjRhThH/UFUXaWp0MU4T8CepYZTAUJ9HsXlFM4zalBDeYiSH2Nm+at3L4dhGkFUclQt35EJgbQOQ1kpatlctCwdEHIX4isu5V5RdB5CgxDnPmQMvFIpwz38VPSGrlIvTrTRJndLcG5SnQ4AER+ceegBbvSjTWECxR4hMvyziIM3v+11JLrlXAru4esQqk3CeLEPXvk9TyrPclcl2J2wHHX4KmL0H0WEh7WtLBQVLPo8fCgWug9ceSuu+uNNswQOwEODhWTLUSnoFjT0r0PnIkRI0CUyy03y7nU1S59vwnxAcg4qpT9yh32yVtH5WqixtaYC/smQqRkZ7WYa4iqR+vRA2TFm+uIjCGyveq42+QuVhafcXchGKuh6oE4b5wO0rm2xLtjxgGbqOk1btdEv03hsvixe//kRr08AHQ5AU55lkQbYS7IqTvtYKIaGsdk16MCtwUKlHyRQVQzwgvx0L0uQ4iGExgaQCx48/xgXV0dHR0/mlUGqOdD5fybdu20bGj73lt6NChXH/99UyZMoUvvvgCk8lEp06dvC2u+vfvz/Dhw1m2bFmdz2G32/n888959913/cZvvPFGRo8e7Zcmfipmz57N9OnTeeONNzCZTMydO9cvylydMWPGMGPGDG/K9SOPPELnzp1p06YNAwcORFEUevXqxfbt2/32CwsLY+TIkQwePBij0Uj37t0pLy8/ZVr9pEmTmDZtGoMHD6Zp06a1ppRbrVYWLVrEU089xaJFi1AUhQYNGvDWW29hNpsZP34806dPZ+HChQQFBdGxY0dSU1Np1KhRLWcUQkJCWLNmDS+++CKxsbFekzQQMX7llVdiMBh47rnnMJlM3HnnnUyfPp0hQ4bgcrmYOnUqjRo1Oqtzn28Udx1i6f/973+54YYbvK53Bw8eZO7cucyfP/+8T7CS1NRU+vfvz9q1a72Odjp/PvbvfySv9+W+AVUlcv8vGJs3q7FtcZaL90ZnUJzpEz9BsSrjlsQSeJKnfld6Brnd+6Kl+ES8bertBN5UhCH3NYnoBrTw26c408V71/rOE9PGyL+mR/DeaP9U9y7jbVxy4zqUg6Pxitf4SVKPbTyzldXyQheO1HRcMx4kZOZIDPkPiZBXQ6SV1pHJEj0HMR8LHyKtw068CCH9IGYs7L4UYm8Ro7i02ZIGHXurCMcj/xXjt5gJ0uO6YKMYiFUV3S0Wy3EA7NlQsFpEX95XIijDr4DoG0Xcu8thZwdf2yYM0PxNT9RYgX3V6pCtzeCC72XBJ20uJN/j/369eyXN21kErhxJgccBUdeJ83zOcnEYD+khUXe3QxYXFLMsJFQck4h26W+e8zSQf1tbgkGVtHpFlWh7JWEDZQHCVMsCkj0DdveBkEslKyB5KjizIbQvWtNF2J1BWEM8ZQMVx2F7Ezl+01fk3PbjENYPjLES1a+NiqOwo4Nsp5WKq3rczWISVnFUPAtavgf7rxZfgEoihkOLd2r/jtnTxRiwIlUi66Z46Td+DrFrYrRm4uwdynV0dHT+19CfO0/Pvn37aNOmzV89DR2dvwWn+nmo0+PX8ePHGTduHK1atcJoNLJ3716io6MZOlRqMSvD/Dr/fIyJbQn77GNKnpqDEhBA0FOPYYivPQqvOdx+YhugOMOFy3HyNR53bp6f2AYoe/tjbBNeBF6TeuZqgvu3ZcV+58nc50Q1KcS0MZG5z1OwqkDj7i4US0O44DuJQgZ2FEOu2oSQqxhcZVIzbKgSAbdnQuEGLEW/YA4fhPu5KRiO9pXU6ibP+1qitXgP9g32tAnrJBHUI5PlGGED5PwgPbSLt0H09SK8j0yG/NXQaKbM68hkT53zfdD8DYmcgi/NHCTqX/KLRIud2RJhbv0J7BsB8f+V2m/FImnblYI76lpZIEi6Q1qJVcdc31Nbj2RapM70OcyrQdIGy5Epwjj/W1kciL1FRGjDR2W+Zb9LLbsxGnBC0r3QeqnUoZf+BgFtJV2/bJ/8CbscjHGQ/rJcw+5L/eeU/5V8LrUJ7rIDck/LDsq8Wr4rBnKWBhjM8fhVCxlDxFzN2gTyvoYcTzqUIQAu2CzZDJpT7qVbk3FTuIhiV55kFgAkficLFZXR/aLNcPgOuV9VBXfu5x6H9WrfM3sG7O4LZfvl9dGHpDQgyL+dxx/CkYsZN3G13bO/C44scJVKpokpQhaNdHR0dHR0dHT+IdRJcE+ZMuV8z0PnDHBlZuLasx9X2nHMl/TCEBONYvkDhZlngCEsFMuQgZh6XAQGFUP4SUysANWiENbISP5RX2p3eIIR1eTkZF89JdBWY8wQEw2aJ93Z5u/cqGnuWp0tj3xfxoj54Rz9IZfcZGh9hZGg6DIxSXMViFFXbMca+wFQcRTt+Fq0inbYN+/EdEFH1KZNMYRqcGA0FG5AARSexd3+VxGibT6X6HX+at88W34IaS9If/Fj033Hz1kG9SaLyZvbKWK55BfcYVeglPwqYjeoE+wdWOWCJuNu+zW0+BS3vQwlrDfuchsGMyJY9g7Cm0Z9fK6IzdgJUg9ubSKp2E1fgj0DcAddhjv+MQwHLhMhWHZARGK2p0zEYJNtK43kDAFw4TYRmm6X1Eq7PY7wpkhxe3dkSluo9pvFVG5Xd9k3YrhcqzESGkwT8d1ujRitGQLgt16+enA1VJzobR2lT7dSy3ektnQrZ5F/HX7uCvkT0htar6i5vRoE9adIdPlwFfMQrUxM7VouESO7w7fLdYUNkKwFS2MRhW4HkuDt9IntSgo3SJp/VQJaUatdRulen9gG+S6kPCRO/dVb1J0pziIo2Q4pDwOaLIIE9zjjTI7zTkWqtNIr+UWyQ5q9JmUX6jnshOHIE/f74q0QdJH8fJnCT7+fjo6Ojo6Ojs45oE7VgCdOnOCiiy7y/uncuTPfffed97XOn4crM4uCq8aQ128QheMmkN2yA84D567lV10xREaeUmwD2EIruPolM1EtJEIc1dLEVXM1AoMzTrqPEhJMwM03+QaMRkJeeAjV/ibUmyq1olXnYVDoMNr/4VxRoXk/G4FRFtoMCqTnLXYiA9/C8nsXefB2FXtEUC3Y03EnP4xjp5mctv0pmnAPud36UvTgY7jteSKoqp7LlSNpzI4sn9gGEdmKCZo+LwLWdqHvPUc6FP2Iu923ENQFLE1wN5yJVmJGS/gUIq6EvG9r3pus9yh9O4m8ofPIDG5L+Yef4LbbJXpOtUWHvC8g7lZJRVeDRKgG94DOR3BZnsO5ZZcvdfnI3RJdbrcG2nzhSdtv65lrlrRr+6WluLQX/yzRyOKtIqqTp4qZW+FmiJsg99baTBzU1WBJb89eLvfDHA8Go4j/gJbSh72iSjaDq0Bqvm1tJI29XrU09qgxYKgmxOxZkDRJ7rW5Wo1Rw0drd58HMeyrLpZBos5amdSgOzLEtDDqGhGGBjO0/VquBUANl8yBqgR18Rj3eUom1BBJJ6+t9txdi1O8Vubrcf5HqDgKu/tJ1L3oR1m8KT/8x497LnEWwZF7RGyD+A0cHOvzEjgXuEoh8y0x+vv9P/J35puSvaKjo6Ojo6Oj8ydQJ8H92muv8dhjj2G320lNTeXaa6/l0KE/X+T9LXAWysN32SGPWdKfYydfietIMo4fqvSfLi+neNqjaAVn74Z8vlC0YiIcE7hmznZu/aKEa2ZvI6JkgPRWPgmG8HCCnppOxM4fCf30faJ+/xXjRZ2g1YfiaK6YoCJNUpU9TtrhjYxc+04MjbpbaNzTypj3YgiO8QgeY4hES0t+9WyvQNRYCO3tO6kjB/LXw+GJ4MhEYzCF9zzl/WwtIwYRePdY6T3d5jN/5/gT83E3flWixJXUu0dE2oFRsKOd9LGOv0XqkyvJfAfFGI27+btoLb6i9NMAsut3peC2ebgbPCLCrRqa1hr7hs04d0p7q+L7H0HLyxfxWh1bogjKhKd9rt9qEJoWRfGTz1O2dD3uBh4DNa0Mfr9ZjNAUo7R0q0yjL0+Cgm8lqpu/Wtq1OTMh+V786skz35Y2bYYAEbnxd4pzdZdkcZOvbBFXldqElStfosqZb8m8Wy+H+MkiWhvP8hfQbjfkroSsRZA0UUzaGjwIMf+RiPzpHP6tjSXyXpW4iRJ5djtl4aPho1Jfv7uPiEObJw2+S6rUfrf6QBYWQBYams6TVmZdUqDjbui0X5zrayOwg5jEVaXBQ+cm+pr5DtXd2klf8Kf/vjolWjEU/VBt0OVzzz8XuPLh6CP+Y0cfldIAHR0dHR0dHZ0/gTqllH/yySfMnDmTESNGUFhYyJ133smoUaPO99z+fjgLIH0hpDwAuOSBO3EDBNQ0DDtfuPPya4xpObngOMvmuucTYygEtMKWNqTKoAqBiafczRAViSEqEtOFF/i/4ciBtDlwfI4IotC+0PJDzIGxNOhsYdjcKBQFLEHV1pFM0SKEGj8rrxUTaA5ZMFHDpFVWisdVMuYGUIO999k6YSwhc+9GKd8NedslEtziQzg0RqK8YX1xqw0g+jqUtGdEfEVcKT2aKwVP2iyPCdmPUJEk5mgVx2B3HxRnHlrMMsrmvY1itRL89BSU8n2SUh7aFwrWyzGCOqO5LsX+7bPey3IXFYHLBZYEiLkRMhfJG5Ym0PAhTx12NXM6hxN3dg4V320m+Jk7UdqtlZ7g1pZyn4p3+FqtgaedWTUUIzhzqw26wRDo65NtsJzemTtyhNQte3uCK9KGDZecI2mipHEHdpDriLjSf3+tXFLbEzfI+4U/ilN71GhxQT8dphhxaU++Tz6X6BsgaoR8NhikDn1Pf0/9NZC1WD7fhGekjR+AqQG0WQmoUlpwaJzU2gd1Aeqf5vxxsjBw4mWJSMdPEkF/KlxF8r3NXw0BbaTndW3R89p+J1mb156S/1dhCBL3+ewPfWOKESx/vIWhF7fm+/wq0cpkXEdHR0dHR0fnT6BOgltRFMxmM2VlZWiadkrb+n80zjxpmVSJPRWS7pIol/HU6dV+uF0iFtQzb4FgvPAClPBw3Hm+CI3tv3egRJ4kdfavxGCRaG9FqvQ7NsdBs4U1o4p1pSIZ0p7xvS5YL6Zj9R8AgxFr8EkSNuyZgCaCUCuXlltFm6V/cNtvIfUp37Z5X6NYWxIw4TpKn1tAyOwpKIfHQvEWeV8xQbtvodVSKP8dAjtiMAWDM0HGspeKsVv16GL2RxL1znxHBL63VRYYtNU4X59PXouWmCNdhB68EqX8EDSZC42eBGMobgIoGv8oaBrGxHZYxw9HbdkCJTgYTEHQ+Dlo+JiICWP4SdvJGUJDsN19J/bNP1HxxRYsA1pjcORD3ouS9t5klnzP7aki7oI6SUq8Vo63dZmrVKLI6a/4DmxrL/XcZ/KdNsVBh1/h2FOyCNFgmqSFlx2UlmZJd8lnbo6XFPWqqdZuTZzC7cel7tpdIU7w9afWXGQ4GYoBAppL9Fwrk/k786SdV9MXJaW8uljLXSWfo7WZzD/9Rcj6wH+b7GW1ZijUPL8iJRIJT8kCkqEOPgyFP8LeAXi/X+FDpb68egZBxHCp5a/MvLA0gZhxpz/+n4kxGBrPlsWGos3ye6H5G56U/HOEGijfi7zPfWPhQ8/qd6+Ojo6Ojo6OztlQJ8E9bNgwOnTowMqVK8nOzubee+9lzZo1LFiw4HzP7y+nVIMCDWwKhDpyatngN89DeR0Ftz1dBFfRVnGKDr+i9nTbk2CIiSZi2yZKnngaLTWNgIm3YL6k1xkvgjjdkOWCEg1sBog0gKWO/X3PCGOYRJYbPyXCzRhed0FUnaJtNccKNkpk0FCLGZTbKenBB8eKiArtL2nJFcnyfnkSlB8B3NJTOe4OMARgMNiwTbsUtV0iKJk+sQ2SWn1sBiTMhLD+Va4zVCK2IZeIEK9OYGcR/EGd/YUqUBA7kecCW/BumZlfy7cSVnm+Q+MBA4T2R2nwACFz7sQ5YQSmtlYMhS8Am4DG4Grr6xd+OlylmC5tjzPnGLMLVE64FCbW70qCWkKwQfEsSIyAok2yff0HJDXaniGCUCsDcyOIbyiiPv9bsF0A9e6SbIEzQbVIOnyzBYAmqf8gEduKDEhcIw7spbsl0tzoSQi7AgrWivCMvg5SH/cdL+9zMcWKv/PM5mEMBioj1lEiVkv3Sn/z6tjaQeH3cOgmuHC71MVXF9zBZ+hroah1+5mwZ3ras1VZzMn7TBYJqv8OMcdB4kap23a7xNn/JIswfymW+tBmhXyvFKOY/VXtCvBHMYaLiM9YKFkBYZeLm/65FPU6Ojo6On8Lvv76axYuXIjT6cTtdjN8+HAmTJhwVsdav349ycnJ3HTTTbz88ssA3HXXXedyul6WLl2KzWZjyJAhp9/4LHjmmWdYsWIF3333HWaz+ZTb3nzzzcyYMYPY2NhTbqfzf+ydd3hU1daH3ymZ9JCEkNB7b1IuTRSlKIJ0uIBIU7CCBQSxIHZBERH0Xr9rF0EpEooCcq8g0otIpIVOIAGSkEJIn3a+P1aSmUkmjSQgst/nmSfMnlP2nJmE89trrd8qHSUS3JMmTWLQIEnn9PX15fvvv2f+/PnF7HXzE2eF1xJgXRq09oRPwtpgvO0kWZoH3tZYQs8/i96vjbgrlwTzZYjsB2k5TemTf5KazZozpT64BOgMBoz16+L/yYdgNqOvdG2uw4ezoXc0xNsgQA8rasBd3uUsui2JcqN74QNp9VNnDgTfX7psAEuSRC/1/pJ+mp8gcTS25ywgaICvDvwNiOHXkV7yEyR1Omq6RN2jnpOxxGXSJ1uzwIkHJS3YpzWGZqvxHjcWrv5a8Jy2FGmpZbeKCVguOr2IRZ0eQh+SumaQeuoaz4qQCOoLAd0dx610D6k+TZkXa6CWEYkqu2CXOlTzeQyX30Df+Wt0zunqV/4H7Y4UbgLncqgsSF5HnNc/aH8pjLicgPGnKbC7jh8dTHq4sg/Sdkk9tkcVqDxIWldln5ONq06Cqo/LdfXrIIsOWVHwZxcR5tfSQ9rgJc7mlkQxGdN7gOUS/JnPRd6WLgZvCd9BwB2Q4iaVOnVbQZfw0pL7GV7dCjVfkZZo2CVFv9ZMWcDJPidZAJX/CZe/d9QiB90P/reX7fyFYhcPiQLD2QXHbNnyeWdEOmr4/2rYzeIzYKhUqkXHUmMKk4WjapPl74i+RP/tKRQKhaKCOL15CX988zLpl8/jW6U27ca9TYMeD5bpmHFxcbz77ruEh4cTFBREeno6Y8aMoV69evTs2bP4A+Tj8OHDZZpPafjjjz8qzITaarWyYcMG2rZty8aNG/NaOhfGZ599ViHzuNUp8s7j4sWLVK9ePU9s5+Lh4UHnzp0rdGI3mqs2eDYOlubon9aesD/bwMTYhiTaoLaxDusbbaSFh8URmSsOe6pDbOdy6SO5ETSULvqk9/YG72sQN8hCwoiLIrYBrtph+AWIrAfVcgW3ZhOTMZ3+2m/Yr26Fcy85np8cLSnEJRHcml2ic6cfhfTD0qO67hxo8AVETRHxVeVBCH2QDM3ArkyYGAsXLDDCH+aFQagtzSG2c0nZLKIpl8vfizHW/kaONO+Mg3DqMXRNlklNrUeoo381QOjDoA8o/MbdI0RSoGu/JqLCEOCoszWFSi/qXGFt8CfdbkADzlshzau5XG/neVd9EuIXQaU70V3+Ftd0dRvELYK6bxd9Pc1xkoJ9cT47aqzOE9sgieJvJupZUiURf50JWm2HK5vkFb2nRHVzBXfsv6D6s3I9kn9yTdXNbc1lSZZ07MwcwzBjiKPmubC5XVooJQKV7oFqk9z3YvZrJ33DQdLOa75ccJvA3uXTUsoYDH6dQOctru2WOHHRPjvFcS303iLmmq6W3230cu7yFo/mOPm7ofeSGnfnshavBu7Pl3US/vyH4zvt3Vj6hpv+IivW5li4+KH8jQi8TxZx3NWilxd6I+hVVFuhUChuNKc3L2HnwkexZWcAkB5/jp0LHwUok+hOTk7GYrGQlSW+ML6+vsyZMwfPnLa5ERERvP3222RnZxMUFMQbb7xBnTp1GDNmDJMnT6ZTp07ExMQwduxYPv30U5YuXQpA9erSmeTgwYOMHDmSuLg4hgwZwlNPPYXNZuO9995j79692Gw2hgwZwvjx47Farbz22mucPHmShIQEmjRpwgcffIDVamXq1KkkJIjp76RJk/D29mbz5s3s3r2bKlWq0KxZM2bNmkVsbCw6nY7nnnuO22+/nY8++oiIiAguXbrE6NGj2bBhA61atWL//v0kJSUxc+ZM7rrrrgLXZcuWLdSuXZtBgwaxaNGiPMEdGxvLtGnTyMjIQK/XM3PmTNq0aUOPHj1YtGgRgYGBvPTSS8TFxREfH0+XLl14++23b92y4jJSpOCeNGkSq1atAiSNIjelAmD+/Pl06+Ym4vg3IUODlU7BxinB8M8LkJxTxnreCsNjA/i1NpT4NtFdX+Hy7DdbQqwanDC7jqXY5T0DElVOXAEXPxBjo7rvg3+H0s3VlgWXFxccT/oRfFsXHM+PJR4O3+0w7br8rYjshp9BcB9xWzb4gTGAJAvcFw253b4Xp0JVo533/O3o9N6udbg+LUXAVHlQUoe9m4iBmpYvSpi2S9o2eVSF1nvQYuagM0dDyAhsxlAyfFphyEnHd48OdF7gVUMitxnHZPHCGCSC2kkkBVqhlhGirTDqclVWt/idKpfexcMcBVWfEH2ddQaCB4Mtv1kZBVqlFcAcK1HqBv8BWypGN38rjdjRxX0OoQ9Iuy/LJXkhMRyaLJX6anM8XJwH1gSJ1CevcxzAt62UDFhT4dLHED3LcR2arJBr7W6BwpIIJ8ZASk5LtdRd0iaq4acSKc5zsdblpAHrAE2+H5nHoNYrYqRnz5KU/tAx116y4IxOL+nOuWnl2VFw9H7y6tiDhzjSkk1VgAqKIpvj4Mg9UrqCXnq7N1osv1s+LWXxI3+quPmy9H13/k5nnpDraurDDceSAMdHwtXf5HnqLuki0OiL0mW/KBQKheKm449vXs4T27nYsjP44xQUGRcAACAASURBVJuXyyS4mzZtSs+ePenVqxfNmjWjU6dO9O/fnzp16mA2m5k6dSoffvghrVu3ZsOGDUydOpWVK1e6PVbDhg0ZOXIkAEOHDuWjjz4iMTGRpUuXkpaWRo8ePXjooYf48ccfAVi1ahVms5kJEybQsmVLNE3Dw8ODZcuWYbfbGTduHL/99hsZGRnUqFGDTz/9lMjISNauXcuMGTPo0aMHHTt25M4772TKlCkMHTqUnj17Eh8fz6hRo1i9ejUAZrOZ9evXA7BhwwYsFgvLli1j8+bNLFiwwK3gDg8P57777uOuu+7ixRdf5NSpUzRs2JAffviBu+++m4kTJ7J161b2799PmzZt8vbbsmULzZo1Y+HChZjNZu6//36OHDlCy5ZFGx8r3FOk4NacWshER0cX+trfER1Qz+QQpkadQ2znctQMltJcBr2f9BJOcKr5rDvXNYJsSZRImmbPiYyW/428pw46ecEepzbA1Y3gmyser26D0487XjzSS1o8eTcs+Un0JokQJoa7jpfEPRpy3JjzOWQnrQHtXwXcryPNDrGdy4/pel7xTCKg/kLp02zPlOvc+FvwqCYC6uxUqb2u+760nrq0wHEA/64imHU68KpLcq33wJ5GumZkaZoXb0QFcKAeVDbAn1nw7VXo7A3DfbOplH1UUtYtCRKdNlWFY4NzjnsHNF3pEs2raoStteH5y3AkW8fXmbWZXOcDPHRmiQxbU6H1LnHItqZA7H8c18aznqR9F0X8IhGn1kSwZ9DZ4yo1jaHE5Fw0IzCrUgJ+Jz4Fz6oSBbVcAq9GUP9j6Umd/qecq8G/JQW45osi9FO2gn9nqa82hYpBXswbTifXJCod0NV9DbE9wyG2c0leJxkWTcOlXjrzqIhpQyCETZQyBZDPr8lyiUBDzgJMBQk2/07Q/qRE4b2bgFcTMVkrL8yx0rPcHAtVRsh31OAt9esZh3I2ssOJEVKC0nixfB/0bmqxLPHue4y7G7sR2DIcYjuXpNVgW6gEt0KhUPzNSb98vlTjpeH111/nySefZPv27Wzfvp3hw4fz/vvvU7duXQICAmjdWgI+ffr0YdasWaSm5i/jK5w777wTk8lEcHAwQUFBpKSksGvXLiIjI9m9W9r1ZmRkcPz4cR588EECAwNZsmQJZ86cISoqioyMDNq2bcsHH3xAXFwcd999N5MmTSpwnp07d3LmzBkWLlwISEp4rgbLnb/znAAaNWrElSsFuxglJiayY8cO3nrrLby8vOjevTtLly5l5syZdOnShaeeeorIyEjuuusuRo8e7bJvv379OHjwIF9//TVnzpzhypUrZGRkFDiHomQUKbid0wbypxD83VMKQg3wZVXoFQ1ZGmTZZSzeKRW3vReYSnMZPIKh3odQ9VFJEQ3q7dq6yRIPJx92RA7DnoBaL0pqtUcVibaWw01+iBGWVodRl2BXJrQwwffVoYoBuSmP+zzfHnYRA96lMIvQ6SF0HCQud6TRBw8queDW+4gjuObU7sy7satTdQ713HgstTNZ0aVsguwT0HyjCGuPKvJIWAHnXpANzTESuWx7UAR9dpREaxv8J68fstkOkxMC+D41wOUcP1yF5p4w8II8/zYFBtWOh4NdHNHFM09A/Y+g0t2QsgVSt0tae5WRIqTRwBhAXRN8UVWyDIL0YNJ7Ajmu1c6mXgZfMetK2y/fG982RZth2a1Sb17vA/muNV1N1QtvsbfGm6zMDCbW7sU43yRqXHxVougeISLqQRy/zz4rYhsg+yycHCutrCzJUH061HjJ1Z3cni1mdc5YEing2p6HQVKznbMQ9D459fBh0qaLoY7X6rwl0fKUX6Re2ve2iq3/zZumnzy86rt/PddrwFCp8BITc7w4cmtW6QGe+7mZY+FQV7n+ANGvyjX2be2+V3nqLtBNcy+2Qb5nYRPhykbHmDGoAmvLS4nOADqTowQB5NrqKsK1UaFQKBR/JXyr1CY9/pzb8bKwZcsWMjIy6Nu3L0OHDmXo0KEsX76cH374galTpxbYXtM0bDZb3r9BxG1hGI0OyaTT6fL2nz59Ovfeey8ASUlJ+Pr6smnTJhYuXMjYsWMZMmQIycnJaJpG3bp12bBhA9u2bePXX3/lyy+/zItY52K32/nmm28IDJQF6Pj4eCpXrswvv/yCl5druV1uunxhmmzt2rVomsawYcMAyMrKwmKxMG3aNNq3b8+6devYsmUL69evZ9WqVXz11Vd5+3777bds3LiR4cOHc/vtt3PixIm/fbC1IinyDudWvrA6nQjqU/VhR21o6Qnra0L9HHF3mycsqw5VSuu/Y6oCle6CGlOlNtY5onN1t0Nse9YVUXagpaQDH2gJp5+UqGk5UNcEa2vAhQawuTa08gKDDtB5gk+zgjuUxJQrF0syZBwXodYkXCKQ7c+KW3CJ68ENUPtt8r6ihpzUdl1BdV3ZAG+GQG4icUMPmBMUj3/cR5KKfribRF5N1cCWKa25XLBLpPa2fdD+HDT/GbzqOGaicy/qa3nA/znpoRaewNUdBdPTE1ZApV6O55pd+l2feFCix1d3gDUVfwOEGcFUnO4wVRXzuaD7inee1huh2pPSzupgFzg/C2rMoJrBxuSAVN5KfZpGhxrjE/9/YoLmextYc+rHvRtD2j7X41kuS116pdul17NXbdcWSzq9LAI4E/JPcWjPjyVJtq/9put43TmAwbVuPhePKhDcVxYQAnuWXmxb4mUBwlbEKq3dLNuYL0kZQ1FoNjEmOzYYItpIjbc5ruB25jg4ei8c7ACHusDB2x1ZCmn7HWIbZJHp/Ouy+OXfRTJdnKkxTRaQCsO3FaRHQLO1UHkYVH0MWu3867iUGwPF38CZuu9L3bxCoVAo/ta0G/c2Bk/XhWmDpw/txhXjRVMMXl5ezJs3j5iYGEA0TGRkJM2aNaN+/fpcuXKFgwcPArB+/XqqV69OYGAgQUFBnDol3WV++eUXx5wMhiIFOEDnzp1Zvnw5FouF9PR0Ro0aRUREBLt27aJPnz4MHTqUgIAA9uzZg81mY/HixXz00Uf06dOHV199laSkJNLS0jAYDHniv3Pnznz3nWTCnjp1iv79+5OZmVnUNAolPDycOXPmsHnzZjZv3sz27dupVKkS69ev57333mPt2rUMHjyYWbNmcfToUZd9d+zYwYgRIxgwYADZ2dkcO3YMu91eyJkUxVGkXLTb7aSkpOSt4uT+G8j7Yvyd8dJDDT3UyBFb1Y2wo47UQJt0EFoasW2OA3uaCFpDJfcmUmlOba/CHpKe0zYnV+LE5VKzWk4RvRB389d7SHp1wnKHOVRAD/Br42ZjN1hTxQAr+rXcA0pqcHA/97W1dqukjxt8XSN2OiQy2nonWJNEdFx4F0yvSxTaq1FeBDrIAE8HwfhKko3gp6VT9Whfh2Dzqi+GWyDGUz4tXaN/IOZoBn8RO5pV3KCNInQMOngyCL66Cpdy/vY2N8HdPpIGnkuCDWymWgXfo2cthwmaoRL4tYWI1nIej6riet10VcmvcWmwJEiNdG6rsaTVIsZabRczs1ovQ6XuImS9m0kktM1BuLhQxKRPK6eUZiStu7AexrZsSPwBGnwCsZ9C+gFxO68yRqLWzmTHwMkx0tat/r+gTQSkH5LPKfME/NEEPGtLpoFv2xK7+AMimK2JOWUZviLw7FmQ9oeUSmRHQ5VRUPtVMcRz3s8cB0mr5Ptry5AWUrVfKXyhyBIPh7pJXTtIurtmkawG5+t05RdHpgBItkDcV1DzpZwe5/nQMmX+pqrQ5oC0orPEicN+cVkiPi0geT1EvQCB98rn6hFSPrXt5YHBF8Iek0yF9APSs9wjrGR9yBUKhUJxU5Nbp13eLuWdO3dm8uTJPP7441gskh155513MmnSJEwmE/Pnz+fNN98kMzOTSpUq5XVbmjhxIi+88AIrV650cTPv0KEDM2bMICSk8HvukSNHcu7cOQYPHozVamXIkCF06tSJwMBApk2bxrp16/Dw8KBdu3bExMTwyCOPMHXqVPr374/BYGD69OkEBARw++2388EHH+Dv78/MmTOZNWtWnrnZe++9h59f6f2eDh06RHJyMvfcc0/emF6vZ9y4cSxdupQFCxbw3HPPER4ejsFg4N1333XZf9y4cbz22mt8+umn+Pn50bZt27zFDEXp0WlFhLGbNm2alzZRYEedjsjIyAqdnDMxMTH07NmTTZs2UbNmMSZRfzWyz8PhXuIcjAFqvy5OzPnrFTNPyw170k/iXB77b6nhdKbF/yCwFxWOORbMF0SgeoSWPDKdHQO/1wWcFmRM1eC2P9yYO8VD3BdwZT0E3Cn9tHO3saXBmWch/suclOMM8G4q/a+PDYWGX0jKujsRYcuUGuTLS+XcQX1cz519QQzZcvtlVx4C9f4lhmTZMTlmb5pEUZ3ed6xV2ql56qCxSSLrX12BR50Cmn/WiKfVudHocuuSjSEibrNjwJ4Cng0hKVx6sTfIEWf2DBFJ3i0cxmL2bFlo0KwiVq+1lCD7Avzu5vel/Rnwqlf4fppNjOkyj0Pk/bL4YqwsBmgBXd2nM9uyIf4zODdTTOm8G4nI9awPtWc5UoYtyXDiAddFD8860HovXPqXaw24zhPan3bfE9uSIOLZEgs+t8lnZc+UaP7Zp8F6RcoYGnwi13l/Q9fsgxovybxyhV7WORH7R+91PU/DLyF0vKS95CfjKBxo4TpmqATtIh1eA5YrcHEuxLzjul2VMXJs62U40Noh2kG+MwFdna5tlryHotzenbGl5ZQGaLKQVFREXKFQKBQFuKnvO68TuRFkhUJR9O9DkTHaY8eOFXvwqKgo6tate00TuyWwpkqkKetkzoANzs+EkJEOwW23iqCJeUduuuu8I1GvKqMdtcYgadU+za/PvE1Vry0FVTPjIrYhJ7qbb9HGmgJnn4EEabvA1e2SWt10pUTjDH5yHTxrS8TRp5WkRp8cJ9uff1Wcst3N0eANhvpQ6yXXcc0uEUnNAi03O/oXG3whZg7E/UfEfY2cax6/WHo654j6qkZ5YE4AazrYPRjqH0orLyPf55imVfMORddkCZgvYjcng1dDSNqA/sLLEj2u96EsLgR0E2O19Ag5l0dVSWn3rCnR9aS1cGay9PyudDc0/q6AWVyJ0BmkPCE7yun6VCo+mqgzSEQ15h2ot0C+q5pFjNMKqx02eErU8tK/ZLEIpG689duu9blaNqRsct03+5xEpfObaWnZkHWioOC2JOT4HfyYc24/aL1Hfp4c49guaZWkZfu1LZjqn7RSPl9TmHw3ktaDNbbg+0r8QdLi3bn0G/yRsgenNCvvho6OBJYEOPUYVH8KYmaT93tgCJS2ZnqjRHfb/CHXzXwJqj8j3xuX83gBpYjy59acKxQKhUKhUChuKGV2qZkyZUp5zOPviz0D0vcXHM8+6/i3JQ7+bCvR3KS1cGyQiICwiVLb6N1MUkNb7wFjBbUfKi/0vpKy7UzIyII1vLZ0SVt35upW19paU6i4YTdZKfWdR/tKBFIOUPq5ZRyVllf768GfHWQhwLMeXPmfOJTbs8Sk6twMqWVO3VHQ2Tk7WiKg++vCH00JTv6BzqZ0FoTBAwE5Nf0eVci0tmT/mraYY9ajj3pUzpV5Ao72k3T4rLMOsQ0Spb24QBZfrEliTmbLMS/zqCrp9Vd3Q/ZFiVpnnpCfxTlPe4RCk+9F4IFEyxsvAUMJIuYZh8VR/9ggyQg4co9cm6Lqmo2h0OK/0GwdNF0DrXdLSr0zuWZvzui95PrXeUcyDnIJHiAR8ozjUvNsy6ljMl9wiG2Q6xD9przumc94JWk1mNxEJ7xz3D4zjoopYOBd0gc8PwHdZCHGHYYAybogJ/pt8IcGnzkyI2ypktGQuFoc1f06QfXnofV2ye44/4a8L1N1ee8NP5e0emOA+/NVJJpdsk7KySdCoVAoFAqFQlFMhLskFGWsNmbMGJKSkvKc/d544w3Onz/PJ598gtVqZdy4cTz4YNlqNv7yGCtBUH/InOcY0xldTchSNsuNuTMX3peeu9WekUi33vPmaJljCoPmG6QGNu13COonqeL5BYROJ+IkV1SCGKLlTxHXe0gabdpeV8fmmi9KunZJMcfB8X866tItcXBsoNQrJ7rpw3h1m6QjOy8UWK9Kmnv6AXluS5XoZbu7pNZe5ylO9ED2VQ09V/HK/j7fge3S5sq5Nj+X7DOyQJN5jLxIaKXuYnz15z8kclr/Izg+QgS8zkPadlUZVXg0U6cH3/bQ7oiIUr2fzDE3wp0b9bdn5ZQPVHF8BlY3Pb+tia7O8fkxeIKhVkGR7YxHFWi0SAS8+YJc4/ofyqLH5aXiwl7t6ZzrWVnauiWvFdHbZAUE3lPQUK32mxBwh9Qu1/tQ3uupiZJx4dtevis1nocLc+XammpAvbkSdc5tB6fzgObrofZbcP4V2S6gW046eSH1z8ZK0iu9yigRqqZq+b6XOUL80gJxFw+bAH4dIaKdw6X70ofQ5pBE8W+UU7clSVz6L7wvv5d135Na8cLq9RUKhUKhUCgUJaLMgrswK3pN04iKiuLXX3/NE9xxcXFMmTKF8PBwTCYTI0eOpFOnTjRsWIr+zjcbei9pr2SOhcRlcqPf8DOph83FGFRwP2OQ3OTrjSJibyY8a0K9hSJ6jIHuU5CNwRK9P/2IY6zmy5LunB+PKmIqlrgK0nZL7atvW0e9c0nQLDlC1gnLZRGcAXdIZoEzfv+QntnO57Cny/lz0ftC87WSdp0ULpHrBp+Ad2PsVo2k8x5YO9+GkS2uxzYEQ+WBcO551xZaIaPg4gfy/nKpNlmcr7VsqDoJomY4DNg0C5yZJKn1RaUP6z0kglrgmmhiiHa0P5ijZZumayT6rNPL+zcEuC4O1HiufBZ+vJtIzbb5gtRdx30Kl5dAcH/J/jgxShY0jMHSc9qaKBkHJ0bL4oFPC8fcQkaKMDzc3XH80Ieg1qsSBa/1IphCZJGm2uSc72WQmKQ5917XLNIGrfH3khqv9xbx6dQz3S3GSvLIjazb0sByVeZu8IPA++DKz7Jo5HsbpO5xbYllTZbvX7Unyn5dnTHHSUtB9HK9jYHu69BBFgNOPex4frg7tDsuizxlnQN26Wnv4ebvnEKhUCgUCsXfnAoLp5w5I21uHn74YQYMGMDixYvZuXMnnTt3JjAwEB8fH3r37s3PP/9cYN+rV68SExPj8oiNdVNbebNgChMh9o/zkhZeqadrr16/Dq4Rb70P1JpVeD/fmwGDjwiVwup99Z4QMgzaRkKjr6HNn1DtKTAWIhxNYVDtcTGZCuyZF0kuMTpTwVR3UzUxV6v8T4lkyoYQmhOFNOWLoOv9IOAux/OwCWKwFvuxpAVf/Q0O3QGWeDwD9MQegQyfqSLEc9BCRoN3PUkTb7VDXLz9OokJXPYZiH5djtPwMxFrxsqSxg7SuznDtW0DmrVgdkRJscTDsSEitkHew7GB4qZ9+kmwJcvnUmUsBPaWdml+Xa7tXPnR6WUhJf4bOHyXiG2Q78DJsY73ZE2C05Ogek7piu2KCGVjqPwuBQ2QtlfR+dqJxH8tUedmax2178ZAibz7NJPaf7ub1HjzRYlQ+7SQtmfFiW1nNBtknpLIeuQAaUmHDhp9I2n8VSdBtSnuRW95R7bNsVIGEPeZiPtzM+Dci44+4HnbXRZRHPdpvgPYJVvgWrFbIHWffLb7aohJXvbFaz+eQqFQKBQKxU1KmSPchXH16lW6dOnCK6+8gsViYezYsfTp04cqVRw1yKGhoXk98Zz55ptv+PjjjytqajcGoz9QiMOwKQxa/iZRJmuiiBuPmyyqfS0YA+Xh07Tk+1yrMDGFQpMfpF9yZqQYiTX4D5ydKs+brhZhpjPmuDq7ieIa/aHuXBGoV7fLwsnpia7bWJPAchnfytUY/HEVjv2cQf3OvxLQIBWDpxc6Y4BjscC/owjtxHARiFe3yfipR6HDBYlca3YIuh+Sf4LU3RDUW7bPm1MQoBeBVVqTOy3btf8ziOC0p4mBXNznIrjrzpUxdEDRPSlLhd5DekonfOcoF9D7uJYOgES8c1vheTeWyLPeKN+bxt9KlLtALbsmj6Lc9Y1BYKrlWHAAqDKu6EhwUVjixBvAdkWep+6EBp9Li78qo+QBUH06xH8rzuz2TCkjCOpX+vMVRdJPsmgROhYO9yDP8yD2P9D2sETf0/8UN3f/rlInnx+nhaJSY02AI70c2RFXNko2RqOvlWO6QqFQKBSKW4oKE9xt27albdu2ec+HDRvG7NmzeeIJR9qkpmluU9LHjRvH4MGDXcZiY2P/3vXepjCoPOhGz+LvjU8TaPlrjpHdAakzT90lrx25B9qfKt4J3LOGiHN7JqCJUMlN8QZAlyfW/aoYaPeAH1azL0YfN22tQOqGz73gWhed264rNw284acQ9ZLUmjdaLFoyeZ1EauvOhTNPShS81bbSlR/oPHMM3E46xjxrO9XV2yQKfPJ5ad0GEpFv/H3JI7+aTR6FZTp41oI2hyVd3OAn58/vqu7XXkzm/LuKYHN+j8YAKb2o+pj0f8/Fv2vxLt2mqtBqK5x7WQziQv4pxzEUYpBWHBlHHGI7l9h/ifGbyUn4e9aBdielN7rBTxz4r6UjQH7M8ZIlgUFSyYMHijGbs8Gg7Yos3gQPgsPd5HuXcVRc+xNXOhYf/O8svt93UVivFPQpuPI/+d1DCW6FQqFQKBS3DmUW3IW1BPv999+xWCx06SIpqJqmUaNGDS5fdoiTy5cvExpa8MY9ICCAgIAb4NKr+PtjChNxemyo67hmo0DrssJw7ond8D9w6E5HCnTNV6S2OAe9UYfJWES01FhJ+n2feVrOr/eCRl+Ju3jenKtBg49FwOh9RYBnnoLMQxA1TSKVID2vg/uU7D1AjoP5Ujg+UkS3V33pDX7+FXndryOkH3KIbRCDv6QfoeqEoo+taVKffekj6UFe/Wnpo54/uqkzgGd18PynY7/mG6SGO/2AtPRqvFjS+YP7u+9HbvAVQzSv+hJJ9W0vRmYl6R3vVVc+Q1uGRH1L4wvgjDXNvReDR1jBxQZLPPzZ3tF326e1OLuXxavBHC9mele3yPtuslxa7uncvB+dSUR27iKPPV3qt5ssBfQ55SDVSnb9CsMQIItJzgtJvq3l3AqFQqFQVABpaWnMmzePffv2YTAYCAgI4IUXXqBFixbXdLwXX3yRyZMnU6NGIUETNzRp0oTjx49f0/kK44UXXqBjx44MGTLEZbxJkyY0beqaJXr33XeXuoNUdHQ0n3zyCe+8806Z5+pMTEwM9913Hw0aNHAZHz58+N87iOqGEt1dpqen8/7773PmzBkWLFjABx98wIwZM/D19WX+/Plu90lNTWXhwoUsXboUi8XCqlWrmDt3LtOnTycpKQlvb2/++9//8uabb5brG1IoikXvKxG+pNWOsWqT3Bu2FYd3czGXyo4RgZKbJl9SDH5SIx08QNLCPWtKy678mR8GX4djtPWqROev5PM/cFeTXBQ6HST/F+q8JcLQVB1OP+2I+ns1ElO1/KTugLCHi067tsSKqMx1E0/4DlpsgsAe8tyWJi28jEGuIteaKIsOTcNFnOlNjnTywjDHS8s4j1CJymYeg1PjJRLvTqDnp6w9q82xEDUdKg8WV/mUX2Vc7w11Zkurt1zsFrj4vkNsA2QclGtelgyX7LMitkEyLhJXQ/Bg+S5eXuroQe4RJmUJ5kuu+2ccgdj/gwb/Vz7eEcZA8Vs4/Yg44JtqyPOSfB4KhUKh+Ftj3hJH9qIotIRsdCGeeI6ti+nuspVS2u12HnnkETp16sTq1asxGo3s3r2bRx55hHXr1hEUVHrjzj179jBp0qQyzauiWbNmTZmPcfHiRaKjo4vf8BoIDQ0tlzne7JRIcL/11luEhoaSmJiIp6cnaWlpzJo1i3nz5hW6T/fu3fnzzz8ZNGgQdrudUaNG0b59e6ZMmcLYsWOxWCwMGzaM1q1bl9ubUShKhEewRHKDB0DKLxA8FCp1u7YWSHoPiQYWl4peFMYAeeTvH13U9jVfdBXcxmAIuL305/ZvB0d6y79924jgunqvCOKw8dJGzdnJG6QWubga57TfC7buinkHfP8BtiQ495LUzoc8IDXOHlVyWreNENM4dBD2qCwGFIc9Q0QryOeZN55V/L5FYbksqeap+yDwXkkFz++0bb0KpydD0kqpm274ubijZ52VGvPoWZAVBS02yndEszhM8JzJjinjXPNd60sLJH289hxxdY//TrILQoaBRzVZzKg8QjongMyt9pvlZ9Ro8JV+6pV6yOdj8HPN2lAoFArFLYl5SxxZH5+EbDsA2uVseQ5lEt179uzh0qVLPP300+j14vfTuXNnZs+ejd0u5/r000/ZsGEDNpuNO+64g+nTp3PhwgUmT55Mo0aNiIyMpHLlyixYsIDly5cTHx/Po48+ypIlSxg6dCitW7cmMjKS7777jkWLFrFr1y5SUlIIDQ1l/vz5hIS4DxDExcXx0ksvkZqaSnx8PIMHD+aZZ54hPDycbdu2kZKSQnR0NF27duW1115D0zTmzJnDli1bCA0NxWaz0bFjx1Jdjw0bNvDVV1+RlZWF2WzmnXfeoV27dnz11VesWrUKvV5P69ateeONN3jrrbeIiYnh9ddf59VXXy30Ok2cOJGgoCC8vLzo37+/27mXBudsgPDwcPbu3cucOXPo0aOHy7XesmULX331FTqdjhYtWvDKK6/g6+tLly5duOeeezhw4AC+vr68//771KxZk4MHDzJ79myysrIICgri9ddfp1atItrVXg+0EjBw4ECXnzabTevTp09Jdi03oqOjtcaNG2vR0dHX9byKvzk2y42ewbVhSdG0q3s07dhITTs9RdMyz2ma3Vb645gTNO3sS5q200seZ1/QNMsVp9cTNe3iR5q2p4qm7Q7WtJi5sk9xJP9P07ajn7FjnwAAIABJREFUafvqalrMPE1LWq9p8d9rWtYlTdtbXV7LfZx9SdOsWZoWPcd1fDuaduU3TbPbiz5X9gVN2+nrut+eME3Lvlj665H3vpM07cR412Ne+lTTbOZ8576kaTs8HNvsb6xpCas07Y8Wmrbd4Bg/95rju5a8yfW4O0yalnn22ueqaZqWdUHTdvm5HjduUdHXzpygaRknNC11v7yP4q6zQqFQ3EKo+87iOXr0aKn3ufrQbi2l328FHlcf2l2muXz++efaY489Vujrv/32m/bUU09pVqtVs9ls2tSpU7XVq1dr0dHRWpMmTbQjR45omqZpkydP1hYtWqRpmqZ179497/Pv3r27tnLlSk3TNC0qKkqbPHmyZrPJfdf06dO1L774QtM0TWvcuLHbuYWHh8v7v3pVa9u2rZaYmKitXLlSu+uuu7TU1FQtIyND69atm3bs2DFtw4YN2ujRozWz2awlJiZqXbt2zTu3M40bN9YGDBjg8ti6datms9m0sWPHaomJiZqmadqKFSu0xx57TLNarVqnTp00s9ms2Ww27YUXXtBiY2O13bt3a6NHjy72Ojn/PhQ2d2eio6O1Fi1aFJhj7nbO12rlypXajBkzClzrY8eOab169dKSkpI0TdO01157TZszZ07e/rnXddGiRdpjjz2mZWdna/3799cuXLigaZqmbd26VRs3blyh34vypKjfhxJFuHNXinKx2WwFxhSKG44lEbCXrvb0Wmt2bzTGAHE5b/Q1YLj29+FRGWq9DNUnA5qk1TtH+j2CIewxqDws57zBhRugOePTCoL6QM2ZcP5lOD9T+nr7dZBUa2fiv4TqTzlc2p1J2SzO5T5NC0/7NgRBg3/DyYeQns8ekr5sdPoemC9JH/essxK596zj/njmWEj5TeqN4792fe3ci1JH7mJwppfU+8ycdm2mmlJ7nnHEdd/0/Tlp3UbwawfNfoQL74kjfu23y26a5hEKrX+XzAHLJalhD7q/6EwEj8oqxVuhUCgU1xUtIbtU4yVFr9fj6elZ6Ou7du3i4MGDeXXQWVlZVK9enfbt21O5cmWaN28OQKNGjUhJSXF7jNtuuw2AOnXqMGPGDFasWMHZs2eJiIigdu3CsxQnTJjA7t27+eKLLzh58iQWi4XMzExATKb9/OR+pFatWqSkpLB3717uvfdePDw8CA4Oplu3boUeu7B07X/9619s3ryZs2fPsnfvXvR6PQaDgbZt2zJs2DB69uzJQw89RFhYGFFRUSW+TjVr1szb1t3c83OtKeW513rfvn107949ryRgxIgRvPjiiwB4enoyaJCU4w0ePJgPPviAqKgooqOjXUy609Lyd7K5/pToLr1Dhw7MnTuXrKwstm3bxpIlS+jUqVNFz02hKBnWVEjbJ2IDqxiXVbqrdLXUhR1X5wEGL8eYJQGyTkHan1DpbhFKFdnmyJIoKbk6gwjL/A7a+sL/cykxBp+iU4n1HqUXhKYwabt25D6HGE35HxwfDjVfFpOuvG2riWN65SHivu6M/+0Q2R9a7ypCcHtLvfI/uotRm6mmqwGaOU6M7bJOy/OL86DlVqh0h+txzHHSNzrzhPRIz489gwLGeqZQ6bN9pLuk4acfhLrvQfQbrtuFjHYsZBgDIbifvDedURZPyoreKC78jb6WvtvG4GtrbVZWrKmysGAMLv/e4gqFQqG46dGFeKJdLiiudSFlu59p2bIl3333XYEOSB988AG33347NpuNcePG8dBDDwHSvthgMJCcnOwi1HU6HZrm3kQ3d7vDhw/z3HPPMX78eHr37o1ery90H4A5c+YQHR1Nv3796NWrFzt37szb3t2588/BaCxdUCU9PZ1hw4YxYMAAOnToQJMmTViyZAkA//73v4mIiGDr1q1MnDiR999/32Xfoq6Tl5eXy7YlvW5Fkft+rVbXtrO5x84tB3DePndbvV6f91nb7XYMBgN2u52aNWvmiXybzUZCQgI3mhLdEU2bNg0fHx/8/f2ZP38+TZo04fnnn6/ouSkUJcMcLT1/0/ZA2n44Nggyjl378axXpIXRiZHSOzjrjLiYW5JF1B/sAmcehwNNxRVbsxV/zGvBHCs1zb/Xhj+awOXFYHW/6vqXRLM5xHYu6X9IrXguOhPU/1hqo4MHQLWnRXwbAkW4ph8QA7bUPUWfy+gvLcb8O+cYzzktIGRGOsS2TAyiXynY7zttv4htENd2/66ur1d7SuaVH9/boN0JaHMA2vwhvb2b/ACe9STbovbbENiz4H4eweUjtp0x+kvU+nqLbbsVMo/DybFiYBf/VU7GiUKhUCgUDjzH1gXPfPLDUy/jZeAf//gHlStX5uOPP8Zmk/uybdu2ER4eTsOGDencuTNr1qwhPT0dq9XKpEmT2LhxY5HHNBgMecdyZt++fXTs2JEHHniAunXrsmXLFrfb5bJjxw4mTJhAnz59OHv2LHFxcQWEpDNdunRhw4YNmM1mUlJS2LbNTQZgEURFRaHT6Xj88cfp1KkT//vf/7DZbCQlJdG3b18aN27MM888Q9euXTl+/DgGgyFPxF7LdbpWgoKCOHnyJJqmsXnzZrfbdOzYkc2bN3PlirRdXb58eV7QNzMzM2+/8PBwunXrRv369UlJSeH3338HYOXKlUybNq1C5l8ailwymThxIp9//jnfffcdkyZN+ss79SluUS5/R4HIY+z/gX8HiQyXlqs7IfJ+x/PEldD2KGCFuM9ctz07BQK6lU8fZWfsWZJynLJJntvS4PSjYkJVkRH1wrAkyRw0s6RBl6SFld4kkU5rkmPMo6q4jrc5KIZsvrc5SgA8QqDW6xA6DixxcHmJPAC8m1z73DU3/6lp9oJd4GxOKUdRM6DpSrjyiywSVB4u7t7uenS7M86rPBgC7gC0kqfh38xYL8OfHR29t0/tgwZajpu9inQrFAqFQsg1Ritvl3KdTse///1vZs+eTb9+/TAajQQFBfHpp58SEhJCjx49OHbsGMOHD8dms3HnnXcyePBgLly4UOgx7777bh599FE+//xzl/G+ffsyefJk+vfvD0h0PSamcPPTxx57jOeffx4vLy+qVq1a7Pa9evXi0KFD9OvXj5CQkAJttZwZOHCgy/M6deowf/58mjVrRp8+fdDpdNxxxx3s37+f4OBgRowYwbBhw/D29qZevXoMHTqU7OxsUlNTmT59OnPnzi31dSqK+Pj4AnPs0KEDM2fO5LnnnuPxxx8nJCSE9u3bk5ycXGD/pk2b8thjjzFmzBgsFgstWrTg9ddfz3v9559/Zv78+YSGhvLuu+9iMplYsGABb7/9NtnZ2fj5+fHuu+9e09zLE51WRPy/e/fuTJ06lQULFjBjxowCqQL33ntvhU8wl5iYGHr27MmmTZtc6gcUf0Ps2SLSNE3SiIuLAsZ9I22gnKkzG2q+UPpzW6/AsSGO1k65NFkp9cf789Xo6H2hTYSIrWtxOS8M82U4eo+jx3YuTVeVrX3UtWBJEAEa/6U8924KLTdJG7GisJtFsB4fKgsIeh9otlZS8YtaCMmOhsM9JHUfpIa8zlvFtwcrDHMsHOwsAj8X5xZleee9CAdaiLs3SLr3bfvBq2H5uXf/XUneCEfvcx3zbQctfi5bP2+FQqG4Qaj7zuKJjIykWbNmN3oailuUiuh5XhaK+n0oMsL91FNP8cMPP5CYmMiiRYtcXtPpdNdVcCtuEazJcPl7MaiypUOVB6DeB3LTbs+W1/VervXZQfeBT0tp4QTgVV+ipNeEEQzBboaDxOzLtw2kRzjGQ8fDpY8k3di74TWe0900/KWnc37B7dOy/M5RUrLOOMQ2SJ/rC3Ohzpyia8j1JnkP7U6DLUUM2YzBxWcdeNaCVtskWqr3Ar1/wXZcpcFUFVrvhPjF0q867DH5jhTYLkzSwi/Mkwh79SngWbdosW23yvu5EfXSfyXcierc2nyFQqFQKBSKW5giBfeQIUMYMmQIs2fPznOEUygqFPNFqZvO5fJiiZSFjheRl7hMXKHrL5DIo84gQqnFL5B9HjQreNW79hRvox/UeROurAe7OEji0xp8moMpBJqtg4sfiOgOvBd8WsCxoTIX76fK/Pbz0HtBjRmQfkjSyg1+UGfujYkWZhwtOJZ2QEzEijNtM3jnpGEXEw3Pj6kq4P4zTE+wcXpLJikXrDTv74t/VQMmn2LSlk3VoebzkjVRmDjWGcCrrizwaFb36eO5WK9ARqSULng1hKoTio/4/53xrAWBvcXTACTzo+575V+jrlAoFAqFQgF/qeh2cRQpuNesWcPAgQMJCwvjq6++KvB6roOdQlFupGwvOJb8k0QkL8yW51ln4GBXaHvIUTdrCitZXXFJ8GoA7Y7BlU3gEQZ+7R3H9qgCvm0l2p2yGc69AGjg3bh8zu2MqSo0+kqi+vZs0HlRsPD4OhBwJ6BzPXfICIlYlwVritRN63RiRlaCtO30BBtLx8WTfE7MPfZ+kcrIb0Kp0baEkdSSRKL1HoBHEfNOhiu/Sqp8LvGfQ+s95V/Lf7PgUQUafStp+5ZLskjmEXqjZ6VQKBQKhUJxwylScJ87JzWPJ0+eLPBaenq6EtyK8se/Q8GxgG6QvMF1zJoovZWdjarKC70JPGtDmJvvt95DapDPvyQRdYCAu0WElze5tcfmi46xpuFiyHU98QiV2uuzz4h5WtXHIOSfrmZYue3SUvdIGrmpVtFp4JbLcHaqGN7pTVDjBag2udi+0ElRljyxDeJ9tv2jFAZ+GIJXwHUw57IkS33/hfdcx7PPi8P5rSq4AUxV5KFQKBQKhUKhyKNIwf30008DMHv27AKvtWvXrmJmpLi18awjfZovvCtpvZW6Q+hYOOmmJtvoptb6euBZQ6KZ2dES6TaFVUyqd0akq9gGiJkjCxDFCNNyxegPQX3FNA57Tj9wp16M1qsQM1tS7XOpvxDCHnWfcq5pkBgu5QIghmrRr+WYmDUv8r3ZrQXHNFvOMa8H9jTIPu3edVxXRFRcoVAoFAqFQnFLcs0hoWtpbn7TY46TiFzUy5B+8ObqiXyz4FFZapfbnYBW2yFkOJwcD7VmSV1oLtWnlD2luSyYqko03rdlxdVVu6shNvhQhl/ba0enz0nbr+YqtkHMzS4ucB07N9O1HZgz9kxIXl9wPPlnMWezFGwLkUtIQw/8q7qarnV5IgCvStfQ/u2a0EPCCqg+FZfPwbu5eyM2hUKhUCgUCsUtTZER7qLQ3WquvOZ4iBwAaXvl+YV3oOkaCO6vHIrLG4OvuJTH/ssxdnE+3LYPrAngUU2i22Vxrr4Z8KwvfarznMoNUHv2X+99azbA5jpmz6TQenO9txhsJa11Hff7B5x9FkJGAu7fo2+IgQe/C+PwmjRSom20GelHYO1r/jNWegwBEHCXtDtruVn8BTwbQOWB5echoFAoFAqFolTExMRw3333FehZPXz4cB588MFSHevgwYNs3LiR6dOnl+cU89i8eTNPPPEEK1eupGXLorvPLFiwgJYtW9KzZ88KmYvi+nAd71RvcizxDrGdy/mXwb8zmJQ5UPmiA4O/61DyeqjUC2pMuTFTuhGYQqH5Rri6DbKjIHhwxdSslxWDr3w2Kb84xkLHSTsvd+h0EDJMaqETV0q/66pPSkQ8+3yOgC8cv1ADnR+phN2uoddf58Uuoz/UnAGZxyF1L4Q9IsZ6xhuYbaFQKBQKxU3E2bNniYiIID09HV9fX9q0aUO9evXKfNzQ0FDWrFlT5uOcOnWKxMTEMh+nMMLDw7nvvvtYtmxZsYL7mWeeqbB5KK4fRQrutm3buo1ka5pGVlZWhU3qr4kbEaBZuCGu0X93dDqo9gTEfiL9m0HStkOG39h53QhMYSJO/8p4hEDjxRD/NaRsgeBBEDJExGlhaEDVSVDrFSnNSP4RTj0mBnQGvxKd9rqL7Vw8QuQR0PXGnF+hUCgUipuUs2fPsnv3bmw2ua9OT09n9+7dAOUiugtj8eLFrFmzhszMTDw8PJg3bx7169fn3XffZceOHej1enr16sXYsWNZuHAhGRkZfPLJJzz66KO899577N27F5vNxpAhQxg/fjx79uxh7ty52O12GjVqRM2aNYmLi+PcuXNcuHCBf/7znzzxxBMF5pGUlMTu3btZvXo1gwYNYsaMGfj5+WGxWHjppZfyjKpHjRrF8OHDeeGFF+jYsSNDhgxh/vz57Nq1i5SUFEJDQ5k/fz4hISEVds0U5UeRgvunn366XvP46+NRVeo0M516Etd8+cb0Rb4VMNWAtkcgaY1EQIP7yWeg+GtiCoMa0yRSbfB1dTB3R9oe6V/eZKm4sWedhjpvSb91D/Wfh0KhUCgUf0ciIiLyxHYuNpuNiIiIMgvu+Ph4Bg4c6DL23nvvUaNGDX755Re+/fZbvLy8WLBgAUuWLOHhhx9m69atrFu3jszMTF588UU8PT15+umn2bt3L0888QTff/89AKtWrcJsNjNhwoS8qHRUVBS//vor/v7+fPTRRxw/fpwlS5aQmppKr169ePDBBwkICHCZz9q1a+natSs1a9akZcuWrF27llGjRnHgwAFSUlJYvXo1cXFxzJs3j+HDHYGmc+fOcebMGZYuXYper+f5559n7dq1PPzww2W6ZorrQ5GCu0aNGtdrHn99TGHQchNcXiI1tWETwbdV8cJCcW3oDOIGXu3JGz0TRUnRGYqOajuTfUEyRI4NBf/bpX7bbi5xdFuhUCgUCsXNR3p6eqnGS0NRKeXz5s1j3bp1REVFsW3bNpo1a0ZYWBienp6MHDmS7t27M23aNDw9Xbur7Nq1i8jIyLwofEZGBsePH6dhw4bUq1cPf3/HfU+nTp0wmUxUrlyZwMBAUlNTCwjuVatWMXnyZAD69u3L4sWLGTVqFI0aNeLs2bNMmDCBbt268fzzz7vsV6dOHWbMmMGKFSvyUvJr165d5mumuD6oGu7SYKoKNZ6T3kR6delueuwWsF4R52+Db/HbK8qPoD6gM4FmhtSd8mjxixLcCoVCoVD8jfH19XUrrn19K+4+7NKlS4wZM4bRo0fTrVs3QkJCiIyMxGg0smLFCvbu3cvWrVsZOXIk3377rcu+NpuN6dOnc++99wKSEu7r60tERAReXq5dW5zFuk6nK9DR6ciRI5w4cYK3336b2bNnY7PZiI+PJyIigjZt2rBu3Tp27NjBb7/9xuDBg1m3bl3evocPH+a5555j/Pjx9O7dG71ef2t2jLpJUeHZa0GJ7ZsfS7z0jj56L5yeLD21FdcPUxjctheC7oeAO6DZGvBtf6NnpVAoFAqFogJp06YNBoNrK0+DwUCbNm0q7JyHDh2iTp06jB8/nlatWvHLL79gs9k4evQoo0ePpkOHDsyYMYMGDRpw9uxZDAYDVqsVgM6dO7N8+XIsFgvp6emMGjWKiIiIa5pHeHg4w4cPZ8uWLWzevJnffvuNgQMHsnTpUjZt2sT06dO5++67mTlzJj4+Ply6dClv33379tGxY0ceeOAB6taty5YtWwqk5iv+uijlqLj1sKXDuVcg7lN5nh4BqTug1VbJYlBUPHovaXnW+DvQrOARfKNnpFAoFAqFooLJrdOuCJdydzXcHTp0YMqUKXz//ff07dsXTdPo0KEDJ0+epHnz5rRp04Z+/frh7e1Nu3bt6NatG9HR0Xz88ce8//77PPPMM5w7d47BgwdjtVoZMmQInTp1Ys+ePaWam9ls5qeffmLRokUu4+PHj2fEiBE8//zz/Pe//+X+++/H09OTAQMG0KRJk7zt+vbty+TJk+nfvz8ALVu2JCYm5hqvlOJ6o9NuknyEmJgYevbsyaZNm6hZs+aNno7iZsYcC/vr5/SKdqLdSfBueGPmpFAoFAqF4i+Duu8snsjISJo1a3ajp6FQ/CUo6vdBpZQrbkF0bhzPdaD3dLu1QqFQKBQKhUKhUFwLSnArbj08qkCD/wOcaoiqTwNDQKG7KBQKhUKhUCgUCkVpUTXcilsPnR4CusI/zkBahKSRe1QFY6UbPbO/DXarhs4gLp0KhUKhUCgUCsWtihLcilsTg688PFUPw/IkO9VO4lkLEUvTCKxlpPVQP/xCDcXvqFAoFAqFQqFQ/A1RgluhUJQbFyOyWflEQt7zQyvTGb00DN8QJboVCoVCoVAoFLceqoZboVCUC5lXbOz6z1WXsdRYG0lnLTdoRgqFQqFQKBQKxY1FCW6FQlEu6PRg8ChYs603qjpuhUKhUCgUCsWtiRLcCoWiXPAKMHDH05XQOf1VqVzfSGBtVbmiUCgUCoWiYvn5558ZMmQIAwYMoH///nz++efF7jNmzBj27NlT7HZXr17lueeeo3///vTv358JEyYQFRVV5D579uxhzJgxJZ1+hWC1Wrnjjjt48803XcYvXrxI7969GThwIGlpaS6vvfzyyxw6dOh6TvNvT4UL7nfffZcXXngBkIbgQ4YMoXfv3rz88stYrdaKPr1CobiOVGniwUNrqtLliQDuezuI4V+G4ltZ1W8rFAqFQqHIIX4J/F4XdujlZ/ySMh8yLi6Od999ly+++IK1a9eydOlS1q9fz6ZNm8p8bIB58+bRuHFjfvzxR3788UcGDx7MlClTyuXYFclvv/1Gq1at2LBhA5mZmXnje/fupWXLlqxZswY/Pz+Xfd5++21atWp1vaf6t6ZCBfeuXbtYtWpV3vPp06cza9YsNm7ciKZpLF++vCJPr1AorjMmHz3B9TzoOqkSLQf6KbM0hUKhUCgUDuKXwOlHIfscoMnP04+WWXQnJydjsVjIysoCwNfXlzlz5tCwYUMAevToQUxMDFAw8rx8+XIGDRrEoEGDCo12JyQkkJ2djd1uB6Bv37489dRTAKSlpfH0008zYsQIunfvzksvvYSmaQAkJSXxyCOP0Lt3bx5//HHMZjMA8+fPZ/jw4fTu3ZsxY8aQkCCGs507d2bixIkMHDgQi8XCzJkzGTFiBD179uTJJ58kKyuLmJgYBg0axPTp0+nXrx/jxo3jypUrbucdHh7OPffcQ+vWrVm3bh0gAdAPP/yQbdu2MWvWLD766CMmTJhA3759+e677/Ki/pqmMXfuXHr37k3fvn355ptvABHrDzzwAIMHD6Znz5788ssv1/ip3TpUmOC+cuUK8+fP5/HHHwfgwoULZGVl0aZNGwCGDBnCzz//7Hbfq1evEhMT4/KIjY2tqKkqFAqFQqFQKBSKiub8y2DPcB2zZ8h4GWjatCk9e/akV69eDBs2jLlz52K326lTp06x+/r4+LB69WrmzJnD9OnT80SxM0888QQrV67k9ttv59lnn2XlypV07doVgC1bttCsWTOWLVvGxo0b2bdvH0eOHAEkdXvWrFls2LCBhIQEdu7cyblz5zhz5gxLly5l48aNVKtWjbVr1wKycPDII4+wZs0aIiIi8PDwYNmyZfzvf/8jNTWV3377DYBjx47x0EMP8dNPPxEQEMCPP/5YYM5JSUns3LmTnj170qdPH5YtWwZAs2bNePrpp+nRowdvvPEGAGazmfXr1zNq1Ki8/X/++Wf++OMPfvzxR1asWEF4eDiXL19m8eLFvPXWW6xatYq33nqLBQsWlOajuiWpsOLKWbNmMWXKFC5dugRAfHw8VapUyXu9SpUqxMXFud33m2++4eOPP66oqSkUCoVCoVAoFIrrTfb50o2Xgtdff50nn3yS7du3s337doYPH87777/PvffeW+R+w4YNA0S0V65cmTNnztC0aVOXbVq2bMmmTZv4448/2LlzJ19++SVLly5l2bJl9OvXj4MHD/L1119z5swZrly5QkZGRt4xa9WqBUCDBg1ITk7m7rvvZsaMGaxYsYKzZ88SERFB7dq188512223AdChQwcCAwNZsmQJZ86cISoqKu+4lStXpnnz5gA0atSIlJSUAu9r7dq1dO7cmUqVKtGzZ09eeeUVjh49mrefM61bty4wtm/fPvr06YPJZMJkMrFmzRoA5s6dy6+//srPP//Mn3/+SXp6epHXV1FBEe4VK1ZQrVo1unTpkjdmt9vR6RxuxZqmuTx3Zty4cWzatMnlsWRJ2es7FAqFQqFQKBQKxQ3Cs3bpxkvIli1bWL9+PWFhYQwdOpT58+czc+ZMfvjhh7xtctO883tIGQyO8je73Y7RaOSRRx5h4MCBDBw4kLi4OF599VVsNhsdO3bk2WefZe3atSQnJ3P06FG+/fZb3nvvPYKDgxk9ejQNGjTIO5fR6Iht6nQ6NE3j8OHDTJgwAbvdTu/evenVq1fe9gBeXl4AbNq0iWnTpuHl5cWQIUPo0KFD3naenp4Fjpuf8PBwDhw4QI8ePRgwYAB6vZ6lS5e6vX6553TGaDS6aLWYmBgyMjIYNWoUBw8epGXLlnmZzIqiqRDBvX79enbs2MHAgQNZuHAhmzdv5ocffuDy5ct52yQkJBAaGup2/4CAAGrWrOnyqFq1akVMVaFQKBQKhUKhUFwPar8Neh/XMb2PjJcBLy8v5s2bl1enrWkakZGRNGvWDICgoCBOnToFUMBILTcd+9ChQ6Snp1OnTh0+++wz1qxZw5o1awgLC+P06dN88cUXeTXcMTExWK1WateuzY4dOxgxYgQDBgwgOzubY8eO5W3njn379tGxY0ceeOAB6taty5YtW7DZbAW227VrF3369GHo0KEEBASwZ88et9u54/Dhw8TGxrJlyxY2b97M5s2b+c9//sOPP/5YwJW8MDp06MB///tfLBYLmZmZTJw4kVOnThEVFcUzzzxDt27d2LRpU4nndCtTISnlX331Vd6/w8PD2bt3L7Nnz6Zfv37s37+f9u3bs2bNGrp161YRp1coFAqFQqH4//buPqzq+v7j+BMPdyGKoDU1muk1V0usrKbgzdAwN1HujuIQf5QupmyeYbq8yZErb9FlTKxr1zArnTYEBSX1shaIS0DFCslNmS3vzqboT00R0APnnN8f/GCSipObTsAY3eU2AAASqklEQVTrcV1ecr5+P5/vi/PxcPE+n8/5fEXk2+a+STV/n/pNzTJyt+/WFNu1xxvJ398fk8lEXFwcVVVVAAwbNozp06cDEB8fz6JFi3jjjTcYOnRovbYVFRWEh4fToUMHVq5ciYuLy039v/766yxbtoygoCDuueceOnXqxMqVK+nSpQvPPfccr7zyCikpKXh6ejJgwADMZnO9ZeI3Cg4OxmQyERISAtQsV699o+BGkZGRvPjii+zYsQMXFxeeeOKJW553KxkZGRiNxnoz14MGDaJ37968//779WbIb+eZZ57h8OHDGI1GbDYbzz77LI8++ijjx49nzJgxODs74+/vz7Vr16ioqMDDw+OOfbZXTvZbrUFoRrUFd2JiIkePHiUhIYGrV6/Sr18/li1bhqur63/Vj9lsJigoiOzsbHx9fVsysoiIiIi0Y/q9885unEEWae8aej202KZptYxGI0ajEajZOODGz1KIiIiIiIiItFUteh9uERERERERkfZKBbeIiIiIiIhIC1DBLSJyG9VVNq6X336nURERERGRhrT4Z7hFRFqjsrPVFK4r49LxavobO/LAIDfu8TLcuaGIiIiIyP9TwS0i8jXl/2vlvf85R9nZmntLHt97jZEJXXg00pMOBicHpxMRERGR1kJLykVEvqas1FpXbNf6ZMNVKr/S8nIREZFvo127dmE0GgkNDSUkJIS33nqr0X3t3r2bd955B4DVq1ezevXq5orZoJycHB566CEOHz58x3NXrVpFdnb2N5BKmkoz3CIiX+PsfvMstptnB5z0FqWIiEiTbLwMvzkPp6rhu86w5F6Y5NW0PktLS1m+fDkZGRl4e3tTXl5OTEwMvXv3Jigo6K77+28K3paQkZHBT37yEzZt2oSfn1+D586YMeMbSiVNpYJbRORrPHw68N0AN04VXAfAyQCBL3rh4a3PcIuIiDTWxssw9SxU2Gsen6yueQxNK7ovXbpEVVUV165dA6Bjx44kJibi5uYGQFFREUuWLOH69et4e3uzcOFCevXqRUxMDCaTiUGDBmE2m3n22WdJSUkhNTUVgJ49ewJQXFxMVFQUpaWlGI1GfvWrX2G1WlmxYgUHDhzAarViNBqZPHky+/fv53e/+x02m42+ffvi6+tLaWkpJ0+e5F//+heRkZH84he/uOl7uHjxIvv27WPr1q2Eh4czd+5cPD09qaqqYv78+Rw7dgyA6OhoJkyYwLx58xg4cCBGo5GkpCQKCgq4fPky9913H0lJSXTr1q3xT6g0K83XiIh8jYe3gbHLuxK59l5GLvDm+e096P6Iq6NjiYiItGq/Of+fYrtWhb3meFM8/PDDBAUFMXLkSMaPH19X8Pbq1QuLxcKsWbN4+eWXycrKIioqilmzZt22r+9973tERUURFRXFuHHjALhw4QLr169ny5YtrF27lqtXr5KWlgZAZmYmmzdvJjs7m4MHDwJw4sQJ1q1bx/LlywEoKSlh7dq1pKenk5KSwpUrV266blZWFkOGDMHX1xc/Pz+ysrIA+Oyzz7h8+TJbt27lj3/8Y901ap08eZIvv/yS1NRUPvjgA3r06FHXVr4dVHCLiNyCh4+BXoPceXyCJ10ecMbFQz8uRUREmuJU9d0dvxuvvvoqOTk5TJw4kX//+99MmDCBDz/8kBMnTtC5c2ceffRRAEaPHs2pU6coKyv7r/seNmwYrq6u+Pj44O3tzeXLlykoKCAnJ4ewsDAiIyM5e/YsJSUlAPTu3ZtOnTrVtR80aBCurq507dqVLl263PLamZmZjB07FoDg4OC6Wfa+ffty/Phxnn/+eXbt2sWcOXPqtevVqxdz584lPT2dxMREioqKqKiouLsnT1qUlpSLiIiIiEiL+65zzTLyWx1vitzcXCoqKggODmbcuHGMGzeOtLQ0Nm/efMvZbLvdjtVqrfsaoLr69lW/s/N/Ajo5OdW1nz17NqNGjQJqloR37NiRoqIi3N3d67WvXdp+Y/sb/e1vf+Mf//gHS5YsYdmyZVitVs6dO0dRURGPP/44O3bsIC8vjz179hAREcGOHTvq2h4+fJhf//rXTJ48mR//+Md06NDhpv7FsTRlIyIiIiIiLW7JveDxtX1JPZxqjjeFu7s7K1euxGw2AzVF9JEjR/jBD35Anz59+OqrryguLgZg586d9OzZky5duuDt7c0XX3wBwEcffVTXn8FgaLAAB/D39yctLY2qqirKy8uJjo6mqKioUfkzMjKYMGECubm55OTksGfPHsLCwkhNTSU7O5vZs2czfPhwEhIS8PDw4MyZM3VtCwsLGThwIBMnTuTBBx8kNze37s0E+XZoNTPctf9xzp496+AkIiIiItKW1f6+qcKledVujNbcu5T7+/tjMpmIi4ujqqoKqFkGPn36dFxdXUlKSmLRokVUVlbi5eVFUlISALGxscybN48tW7bU2838hz/8IXPnzm1w47GoqChOnjxJREQE1dXVGI1GBg0axP79++8qu8ViYfv27axfv77e8cmTJ/PTn/6UOXPm8OGHHzJmzBjc3NwIDQ3loYceqjsvODgYk8lESEgIAH5+fnVvPMi3g5O9law5OHjwIJMmTXJ0DBERERFpJzZu3MhTTz3l6BjfSrUzyCLS8Ouh1cxw+/n5sXHjRu69914MBt2ap9bZs2eZNGkSGzdupHv37o6OI81AY9r2aEzbJo1r26MxbXsaO6ZWq5Xz58/f8V7IIiJ30moKbnd3d73D2IDu3bvj6+vr6BjSjDSmbY/GtG3SuLY9GtO2pzFj2qtXrxZKIyLtiTZNExEREREREWkBKrhFREREROSutZKtoERa1J1eByq4RURERETkrri7u3PhwgUV3dKu2e12Lly4cNO912/Uaj7DLbfWuXNnTCYTnTt3dnQUaSYa07ZHY9o2aVzbHo1p26MxbTm+vr6YzWbOnz/v6CgiDuXu7t7gHhGt5rZgIiIiIiIiIq2JlpSLiIiIiIiItAAV3CIiIiIiIiItQAW3iIiIiIiISAvQpmmt3KpVq/jggw9wcnJi/PjxTJkyxdGRpBksX76cS5cukZiY6Ogo0gxiYmK4ePEizs41P3IXLlzIY4895uBU0hQ5OTm88cYbVFZWMmTIEBISEhwdSZogPT2dDRs21D02m82EhYWxYMECB6aSptq2bRspKSkA/OhHP2Lu3LkOTiQi7ZEK7lbswIED7Nu3j6ysLKqrqwkODiYwMJA+ffo4Opo0QUFBAZmZmQwfPtzRUaQZ2O12Tpw4we7du+sKbmndTp8+zW9/+1vS09Pp2rUrzz33HHv27CEwMNDR0aSRIiMjiYyMBODYsWNMnz4dk8nk4FTSFJWVlSxZsoRdu3bRuXNnJk6cSH5+PoMHD3Z0NBFpZ7SkvBUbOHAg69evx9nZmQsXLmC1WvHw8HB0LGmCr776iqSkJOLi4hwdRZrJl19+CcDPfvYzQkND682iSev0l7/8heDgYLp3746LiwtJSUlasdCGvPLKK8ycORMfHx9HR5EmsFqt2Gw2Kisrqa6uprq6Gjc3N0fHEpF2SAV3K+fi4kJycjJjxowhICCA73znO46OJE2wYMECZs6cqfuFtiFXrlwhICCAN998k3fffZfU1FTy8vIcHUua4OTJk1itVuLi4ggLC+O9997Dy8vL0bGkGeTn53Pt2jVGjx7t6CjSRJ6ensyYMYPRo0cTGBjI/fffzxNPPOHoWCLSDqngbgPi4+MpKCjgzJkzpKWlOTqONFJ6ejo9evQgICDA0VGkGQ0YMIAVK1bQqVMnfHx8GD9+PHv27HF0LGkCq9VKQUEBS5cuZdOmTRQXF5OZmenoWNIMUlNTtRdKG3H06FG2bNnC7t27+fjjj+nQoQNr1651dCwRaYdUcLdi//znPzly5AgA99xzD6NGjaKkpMTBqaSxdu7cSV5eHmFhYSQnJ5OTk8PSpUsdHUua6ODBgxQUFNQ9ttvt+ix3K9etWzcCAgLw8fHB3d2dkSNHUlxc7OhY0kQWi4XCwkKefvppR0eRZrB3714CAgLo2rUrrq6uGI1GDhw44OhYItIOqeBuxcxmMwkJCVgsFiwWC9nZ2Tz55JOOjiWN9M4777B9+3a2bdtGfHw8Tz/9NPPnz3d0LGmisrIyVqxYwfXr17l69SqZmZk888wzjo4lTTBixAj27t3LlStXsFqtfPzxx/Tr18/RsaSJSkpKePDBB7UXShvx8MMPk5+fT0VFBXa7nZycHPr37+/oWCLSDmmapRULDAykuLiY8PBwDAYDo0aNYsyYMY6OJSI3GDFiBIcOHSI8PBybzUZ0dDQDBgxwdCxpgscee4zY2Fiio6OpqqpiyJAhjBs3ztGxpIlOnz5N9+7dHR1DmsnQoUP5+9//jtFoxMXFhf79+zN16lRHxxKRdsjJbrfbHR1CREREREREpK3RknIRERERERGRFqCCW0RERERERKQFqOAWERERERERaQEquEVERERERERagApuERERERERkRaggltERERERESkBajgFhFpBLPZfMv7aa9atYqtW7cCkJGRwfDhw3n++ecbfZ2ioiJiYmIICQlh7NixxMbGcuzYsTu2Ky4uZsGCBQB8/vnnxMfHN3j+mTNnGDt2LGFhYXz22Wd3nfNuryciIiLSHjg7OoCISFsyY8aMuq+3bt3KzJkzCQsLa1RfFouFadOm8fbbb9OvXz8Atm3bxs9//nOys7MxGAy3bfvFF19QWloKQP/+/UlOTm7wWvv376dbt268++67jcp6t9cTERERaQ9UcIuINKN58+bRt29fSktL+fzzzzGbzVy6dIno6Ghee+01CgsLsVqtPPLIIyQkJODp6XnbviorKykrK6OioqLuWGhoKJ6enlitVpycnFi6dCmHDh2ivLwcu93O4sWL6dmzJ8nJyZSVlfHSSy8RHh7OokWL2L59OwcPHiQxMRGbzQbAtGnT8PLy4ve//z1lZWXExMSwbt26W/b75JNPUl5ezuLFi/n0008xGAyMHDmSiRMn3vZ6ZWVlvPrqqxw9ehQnJyeGDRvGrFmzcHZ2pn///kydOpW8vDzOnTtHbGws0dHRLT5GIiIiIt8ULSkXEWkB8+fPx8/Pjzlz5jB58mRSUlIwGAxkZGSQlZXFfffdx2uvvdZgH15eXsyePZvY2FiCgoKYPXs2W7ZsYfDgwbi6unLo0CHOnTvHpk2b2LlzJxEREaxZs4YePXoQHx/PU089xbJly+r1uXr1aqZMmUJGRgZLly5l3759+Pv7153/pz/96bb9AiQnJ3P9+nV27tzJ1q1b+fTTTzl16tRtr7d48WK6dOnC+++/z5YtWygpKeHtt98Gambwvb29SU1NJTk5mWXLlnH9+vVmHAURERERx9IMt4jINyA3N5eysjLy8/MBqKqqomvXrndsN2XKFCIjIyksLKSwsJA1a9awZs0aNm/ezIABA/Dy8iI1NZXTp0+zf/9+Onbs2GB/o0ePZuHCheTk5DB48GBmzZp10zkN9Zufn89LL72EwWDAYDCwYcMGoObz6rfy17/+lT//+c84OTnh6upKVFQU69atY+rUqQAEBQUB0K9fPywWCxUVFbi5ud3xeRERERFpDTTDLSLyDbDZbMyfP59t27axbds20tPTWbVqVYNtPvnkE9566y08PT0ZMWIEc+bMYceOHTg5OZGXl0dubi7Tpk0DagrXiRMn3jFHVFQUWVlZDBkyhL179xIaGnrTrHJD/To7O+Pk5FT3+MyZM1y6dKnB7/vG8202G9XV1XWPa4vr2nPsdvsdvwcRERGR1kIFt4jIN2Do0KFs3LgRi8WCzWbj5Zdf5vXXX2+wjY+PD3/4wx84ePBg3bHz589z9epVvv/975OXl8eIESOIjo7Gz8+Pjz76CKvVCoDBYKhX2NaKioriyJEjGI1GFi1axJUrVzh//ny9cxrqNyAggMzMTGw2GxaLhfj4eAoLC297vaFDh7JhwwbsdjsWi4W0tDQGDx5818+fiIiISGukgltEpJEqKioYMGBAvT/l5eW3PPeXv/wl999/PxEREQQHB2O325k3b16D/ffu3Zs333yTpKQkgoKCCA4O5oUXXmDp0qX06dOHqKgoDhw4QEhICBERETzwwAOYzWZsNhuPP/44p0+fxmQy1evzxRdfJDk5mfDwcGJiYjCZTPj6+tY7p6F+TSYTLi4uhIWFER4eTmBgIKNGjbrt9RISErh48SIhISGEhITQu3dv4uLiGvFsi4iIiLQ+Tnat3xMRERERERFpdto0TUTEgV544QWOHz9+y39LSkqiT58+33AiEREREWkumuEWERERERERaQH6DLeIiIiIiIhIC1DBLSIiIiIiItICVHCLiIiIiIiItAAV3CIiIiIiIiIt4P8AFl2xC/dqOQQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# scatterplot of life expectancy vs life ladder\n",
    "g =sns.scatterplot(y = df_years['Life_Expectancy'],x= df_years['Life_Satisfaction'],hue=df_years['Region'], palette=\"bright\")\n",
    "# https://stackoverflow.com/q/53733755 to move legends outside of box\n",
    "g.legend(loc='center left', bbox_to_anchor=(1.10, 0.5), ncol=1);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"relationships\"></a>\n",
    "## Relationships between the variables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Correlation in the data:\n",
    "The covariance and correlation statistics can be used to determine if there is a linear relationship between variables and if one variable tends to occur with large or small values of another variable.\n",
    "Covariance is a measure of the joint variability of two random variables while the Pearson correlation coefficient is the normalised version of the covariance and it shows by it's magnitude the strength of the linear relationship between two random variables. The covariance is a measure of how much two variables vary with each other and in what direction a variable changes when another variable changes. Pandas `cov` function can be used to get the covariances between pairs of variables.\n",
    "The covariances below are all positive which means that when one of the variables is above it's mean, the other variable is also likely to be above it's mean. \n",
    "\n",
    "The correlation coefficients are easier to interpret than the covariances. If there is a strong positive relationship between two variables then the value of the correlation coefficient will be close to 1 while a strong negative relationship between two variables will have a value close to -1. If the correlation coefficient is zero this indicates that there is no linear relationship between the variables.\n",
    "Pandas `corr` function is used to get the correlations between pairs of variables. There seems to be a strong positive correlation between each of the pairings between the four variables with the strongest relationship between Healthy Life Expectancy and Log GDP per capita.\n",
    "\n",
    "As noted the World Happiness Report researchers found that differences in social support, incomes and healthy life expectancy are the three most important factors in determining the overall happiness score.\n",
    "Income in the form of GDP per capita for a country has a strong and positive correlation with the averages country scores of the response to the Cantril Ladder question."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The covariance of the variables in the dataset: \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <td>1.217627</td>\n",
       "      <td>0.992087</td>\n",
       "      <td>0.092331</td>\n",
       "      <td>5.549072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <td>0.992087</td>\n",
       "      <td>1.407993</td>\n",
       "      <td>0.112260</td>\n",
       "      <td>6.782165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social_Support</th>\n",
       "      <td>0.092331</td>\n",
       "      <td>0.112260</td>\n",
       "      <td>0.013533</td>\n",
       "      <td>0.595622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <td>5.549072</td>\n",
       "      <td>6.782165</td>\n",
       "      <td>0.595622</td>\n",
       "      <td>45.269314</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "Life_Satisfaction           1.217627         0.992087        0.092331   \n",
       "Log_GDP_per_cap             0.992087         1.407993        0.112260   \n",
       "Social_Support              0.092331         0.112260        0.013533   \n",
       "Life_Expectancy             5.549072         6.782165        0.595622   \n",
       "\n",
       "                   Life_Expectancy  \n",
       "Life_Satisfaction         5.549072  \n",
       "Log_GDP_per_cap           6.782165  \n",
       "Social_Support            0.595622  \n",
       "Life_Expectancy          45.269314  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The covariance of the variables in the dataset: \\n\")\n",
    "# pandas cov function on the 4 variables in the dataset\n",
    "df18.iloc[:,:6].cov()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The correlation between variables in the dataset: \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.760206</td>\n",
       "      <td>0.719267</td>\n",
       "      <td>0.744264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <td>0.760206</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.792945</td>\n",
       "      <td>0.852848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social_Support</th>\n",
       "      <td>0.719267</td>\n",
       "      <td>0.792945</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.751514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <td>0.744264</td>\n",
       "      <td>0.852848</td>\n",
       "      <td>0.751514</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "Life_Satisfaction           1.000000         0.760206        0.719267   \n",
       "Log_GDP_per_cap             0.760206         1.000000        0.792945   \n",
       "Social_Support              0.719267         0.792945        1.000000   \n",
       "Life_Expectancy             0.744264         0.852848        0.751514   \n",
       "\n",
       "                   Life_Expectancy  \n",
       "Life_Satisfaction         0.744264  \n",
       "Log_GDP_per_cap           0.852848  \n",
       "Social_Support            0.751514  \n",
       "Life_Expectancy           1.000000  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The correlation between variables in the dataset: \\n\")\n",
    "# pandas corr function on the 4 variables \n",
    "df18.iloc[:,:6].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The correlation between variables in the dataset across all years from 2011 to 2018: \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.778394</td>\n",
       "      <td>0.715501</td>\n",
       "      <td>0.751513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <td>0.778394</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.680559</td>\n",
       "      <td>0.840854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social_Support</th>\n",
       "      <td>0.715501</td>\n",
       "      <td>0.680559</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.632336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <td>0.751513</td>\n",
       "      <td>0.840854</td>\n",
       "      <td>0.632336</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "Life_Satisfaction           1.000000         0.778394        0.715501   \n",
       "Log_GDP_per_cap             0.778394         1.000000        0.680559   \n",
       "Social_Support              0.715501         0.680559        1.000000   \n",
       "Life_Expectancy             0.751513         0.840854        0.632336   \n",
       "\n",
       "                   Life_Expectancy  \n",
       "Life_Satisfaction         0.751513  \n",
       "Log_GDP_per_cap           0.840854  \n",
       "Social_Support            0.632336  \n",
       "Life_Expectancy           1.000000  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The correlation between variables in the dataset across all years from 2011 to 2018: \\n\")\n",
    "df_years.iloc[:,3:7].corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn `regplot` or `lmplot` functions can be used to visualize a linear relationship between variables as determined through regression. Statistical models are used to estimate a simple relationship between sets of observations that can be quickly visualised. These can be more informative than looking at the numbers alone. The regression plots below show a positive linear relationship between the pairs of variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Country', 'Region', 'Life_Satisfaction', 'Log_GDP_per_cap',\n",
       "       'Social_Support', 'Life_Expectancy', 'RegionCode'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df18.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib figure\n",
    "f,axes=plt.subplots(1,3, figsize=(12,3))\n",
    "# regression plot with x as a predictor of y variable. set the axes.\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Log_GDP_per_cap\", data=df18, ax=axes[0])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Social_Support\", data=df18, ax=axes[1])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Life_Expectancy\", data=df18, ax=axes[2])\n",
    "# set the axis limits for this subplot.\n",
    "axes[2].set_ylim(0,10); axes[2].set_xlim(40,90)\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib figure\n",
    "f,axes=plt.subplots(1,3, figsize=(12,3))\n",
    "# regression plot with x as a predictor of y variable. set the axes.\n",
    "sns.regplot(x =\"Life_Expectancy\",y=\"Log_GDP_per_cap\", data=df18, ax=axes[0])\n",
    "sns.regplot(x =\"Life_Expectancy\",y=\"Social_Support\", data=df18, ax=axes[1])\n",
    "sns.regplot(x =\"Life_Expectancy\",y=\"Life_Satisfaction\", data=df18, ax=axes[2])\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib figure\n",
    "f,axes=plt.subplots(1,3, figsize=(12,3))\n",
    "# regression plot with x as a predictor of y variable. set the axes.\n",
    "sns.regplot(x =\"Log_GDP_per_cap\",y=\"Life_Expectancy\", data=df18, ax=axes[0])\n",
    "sns.regplot(x =\"Log_GDP_per_cap\",y=\"Social_Support\", data=df18, ax=axes[1])\n",
    "sns.regplot(x =\"Log_GDP_per_cap\",y=\"Life_Satisfaction\", data=df18, ax=axes[2])\n",
    "axes[2].set_ylim(0,12)\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib figure\n",
    "f,axes=plt.subplots(1,3, figsize=(12,3))\n",
    "# regression plot with x as a predictor of y variable. set the axes.\n",
    "sns.regplot(x =\"Social_Support\",y=\"Life_Expectancy\", data=df18, ax=axes[0])\n",
    "sns.regplot(x =\"Social_Support\",y=\"Log_GDP_per_cap\", data=df18, ax=axes[1])\n",
    "sns.regplot(x =\"Social_Support\",y=\"Life_Satisfaction\", data=df18, ax=axes[2])\n",
    "axes[2].set_ylim(0,12)\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The covariance and correlation statistics suggest a strong linear relationship between the pairs of variables and the regression plots confirm this. \n",
    "Life satisfactions are positively correlated with income levels (Log GDP per capita), social support and healthy life expectancy. Income and life expectancy are very highly correlated.\n",
    "\n",
    "\n",
    "(I might be interpreting the correlations incorrectly using the region codes. What I wanted to see was if the region the country is correlated with the variables as it would seem to be the case. Life expectancy and income are generally related to the region.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "<a id=\"synthesise\"></a>\n",
    "# 3. Synthesise/simulate a data set as closely matching their properties as possible.\n",
    "\n",
    "Having collected some data for the real-world phenomenon of the World Happiness Scores, I looked at the type of variables involved, their distributions and the relationships between the variables. In this section I will look more closely at the distributions of each of the variables and then simulate some data that hopefully will have properties that match the actual variables in the real sample dataset.\n",
    "\n",
    "The aim of the World Happiness Scores is to see what countries or regions rank the highest in overall happiness and how each of the six factors (economic production, social support, life expectancy, freedom, absence of corruption, and generosity) contribute to happiness levels. The World Happiness Report researchers studied how the different factors contribute to the happiness scores and the extent of each effect. While these factors have no impact on the total score reported for each country, they were analysed to explain why some countries rank higher than others and they  describe the extent to which these factors contribute in evaluating the happiness in each country.\n",
    "\n",
    "As the differences in social support, incomes and healthy life expectancy are the three most important factors in determining the overall happiness score, this is what I focus on in this project. \n",
    "\n",
    "Therefore I will simulate the following variables:\n",
    "\n",
    "- Regions and Countries\n",
    "\n",
    "- Life Ladder / Life Satisfaction \n",
    "\n",
    "- Log GDP per capita \n",
    "\n",
    "- Social Support\n",
    "\n",
    "- Healthy Life Expectancy at birth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "## Simulate Regions and countries.\n",
    "\n",
    "There are countries from 10 geographic regions in the sample dataset for 2018. While the region was not in the actual dataset for 2018, I added it in from a dataset for a previous year (2015). This allowed me to see the how the values for each variable in the dataset differ by region. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Look at the clustered groups for 2018:\n",
    "The rough clustering earlier divided the countries into 3 clustered regions.\n",
    "Of the clustered countries, 10 values were lost due to missing values. If I had more time then the missing values could be imputed based on previous years but for now there is at least 100 which is sufficient for this project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1094"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#clusters for 2018 data\n",
    "c18=clusters.loc[clusters.loc[:,'Year']==2018]\n",
    "len(c18) # only 126 countries due to missing values in some rows\n",
    "Cy=clusters # all the data for all years \n",
    "# the number of clusters for all years\n",
    "len(Cy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Look at the distribution of countries across the geographic regions.\n",
    "Below I look at the actual proportions of countries in each of the 10 geographic regions which are then plotted.\n",
    "The countplot shows the distribution of countries in the real dataset over the 10 regions. \n",
    "To avoid the axes labels overlapping, I have followed advice on a blogpost [drawing from data](https://www.drawingfromdata.com/how-to-rotate-axis-labels-in-seaborn-and-matplotlib)[20] to rotate the axes labels.\n",
    "Also to show the plot by descending order of the region with the most countries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 136 countries in the dataset. \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# see how many countries in each Region\n",
    "df18.Region.value_counts()\n",
    "# find how many values in total\n",
    "print(f\"There are {len(df18.Region)} countries in the dataset. \")\n",
    "# calculate the proportion of countries in each region\n",
    "prob=(df18.Region.value_counts()/len(df18.Region)).round(3)\n",
    "#print(f\"These countries are split over 10 geographic regions as follows: \\n{df18.Region.value_counts()/len(df18.Region)}.3f %\", sep=\"\\n\")\n",
    "# make sure they sum to 1. \n",
    "prob.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnIAAAF4CAYAAADQXRRuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzs3XdUFOf+BvBnl46AioolYgWFSOwNEVGioJQglmiCimKNsXtFscSIUYnXKBqMMcZ4ufbYvRYS1BtjxBJNFDHR2BBR6SAgZdnd9/eHP/aCBcG4uww+n3M8xx2mfGd2Z/bZd96ZkQkhBIiIiIhIcuT6LoCIiIiIXg2DHBEREZFEMcgRERERSRSDHBEREZFEMcgRERERSRSDHBEREZFEMchRmRITE+Ho6Ag/Pz/4+fnB19cXQ4cOxZEjRzTjrF69Gvv37y9zPhERETh27Nhz/1Zy+pYtWyIjI6NCNcbGxuKTTz4BAFy5cgVTpkyp0PSvQqVS4aOPPoKnpye2bNnyzN+Tk5MxZ84c+Pr64r333sPgwYNfuP6vQ3m37981duxY3Lx5s8LT7d69G4MHD4aXlxd69+6NUaNG4fLly6+lJm2ZM2cONm7c+Ny/+fn5ITs7u9zzGj58ONzd3UvtR56enn/7fXnV96MiXuXzU9Htk5OTgxEjRmhev8pxoCxRUVEYPnz4S8craz/6u4KCgp67Tmq1GsuXL4e3tzd8fX0xadIkzXj5+fmYOXMm+vXrB09Pz+fWtnr1aoSGhpYa9uWXX6Jfv37w8fHB7NmzUVhYqJV1okpCEJXh3r17om3btqWGJSYmit69e4uoqKhyz2fYsGHi6NGjLx2vRYsWIj09vUI17tmzR4wbN65C0/xd9+/fF05OTkKpVD7zt/T0dNGzZ0+xb98+oVarhRBC/Pnnn6Jr167il19+0Uo95d2++vDFF1+IoUOHisTERM2wmJgY0aVLF3H//n09Vla22bNni2+//fa1zOt5709sbKxo1aqVyMnJeS3LkLKnjzOvchwoy9GjR8WwYcNeOp4296MXrdP3338vRowYIQoLC4UQQnz++edi1qxZmv/Pnz9fCPHkmNO9e3fx8OFDIYQQDx8+FJMnTxZt2rQRixYt0szv7NmzwtPTU+Tn5wu1Wi0mTpwoNmzYoJV1osrBUN9BkqTnrbfewpQpU7Bx40Z4enpizpw5sLe3x+jRo7FmzRpER0fDyMgINWvWxLJlyxAdHY24uDgsX74cBgYGOH78OLKysnDv3j307NkT6enpmukBIDw8HFeuXIFarca0adPQq1cv7N27Fz/88APWr18PAJrXn376KdasWYOcnByEhISgf//+WLx4MQ4dOoScnBwsWrQI165dg0wmg6urK2bMmAFDQ0O88847GDduHE6fPo2UlBSMGTMGH3744TPreuHCBSxfvhz5+fkwMjLCtGnT0L59e4wZMwZKpRIDBgzAl19+iUaNGmmm2bZtG9q3b4/+/ftrhjk4OGDNmjWwsrJ64Xx79OjxwvVcv3495syZAwsLC1y/fh1JSUlo2bIlPv/8c+zfv7/c2/fWrVtYsmQJsrKyoFKpMHz4cAwaNAiPHz9GSEgI7t69C7lcjlatWiE0NBRyeelGe3d3d6xevRp5eXlYtWoVbG1tcePGDSiVSixatAgdOnQoNX5aWhoiIyMRHR0NGxsbzXBnZ2fMmTMH+fn5AJ60YIaGhuLhw4coKiqCt7c3JkyYAAA4duwYIiIioFarUa1aNYSEhKB169bIz8/HwoULcfnyZVhaWsLOzg4AEBYWBnd3d7Ru3RrXr1/XvOfr16+HQqFARkYG+vfvj2nTpuHcuXNYsWIFGjRogNu3b8PU1BRhYWFo3rw5AOD333/H0KFDkZaWBnt7e3zxxRcwNzdHy5YtcebMGVhbW2P9+vXYt28fDA0N0bhxY4SFhcHS0vKl+9G9e/dgbm4OY2NjAMCJEyewbt06FBUVwdTUFLNnz0a7du1eup6rV6/GO++8g507d2Lz5s2Qy+WoXbs2FixYgKZNm77wc1OtWrXn7q8l3ycApfbv8u43xdvnp59+QnR0NORyOe7evQtTU1N8/vnnmu1bLCQkBAUFBfDz88PevXsBPGlVunz5MrKysjB69GgEBAQAAHbt2oXt27dDrVajRo0aWLBgwTPzA560VP3nP/9BjRo10LhxY83wO3fuIDQ0FI8fP0ZqaiocHBwQHh6O3bt3l9qP7OzsnjueiYnJC7fbi/avkJAQAEBgYCC++eYb1K9fX1OPnZ0dgoODNZ8DJycnbNu2TfPZX7FiBQCgQYMGcHFxwdGjRzFq1Cjs3r0bnTt3RvPmzfHo0SPN/NRqNRQKBQoKCiCXy1FYWAgTE5OXfh5JwvSdJKlye16LnBBC/PXXX6JNmzZCiP+1XDx48EC0b99e88ty48aNIjo6WghR+pfu7NmzRWBgoGZeJVs+WrRoIdavXy+EEOL69euic+fOIj09/ZlWt5KvS/7/7NmzwtvbWwghRHBwsFi8eLFQq9WisLBQBAUFaebdokULsXnzZiGEEFeuXBFOTk6ioKCg1DpmZGQIZ2dncenSJc06d+7cWSQkJLxwuwghxPjx48WWLVteuE3Lmm9Z6zl79mwxZMgQUVhYKBQKhejfv7/YvXt3ubdvUVGR8PLyEnFxcUIIIbKzs0W/fv3E77//Lvbt2yeCgoKEEEIolUoxb948ER8f/0ztvXr1ErGxseLs2bPC0dFR/PHHH0KIJ+91QEDAM+NHR0cLf3//F26LYsOHDxfHjx8XQghRUFAghg8fLg4fPixu3rwpunXrJhISEoQQT1ryXFxcRE5OjlixYoWYMWOGUKlUIicnR/j6+orZs2dr6oyIiBBCCKFWq8WwYcPEnTt3hBBCJCUlCUdHR5Geni7Onj0rHBwcxK+//iqEEGLbtm2aemfPni0GDRok8vLyhFKpFP7+/mLfvn1CiP+1rhw7dkx4eHiIrKwsIYQQS5cuFV999dUz6zds2DDRq1cv8d5774mePXsKZ2dnMX36dHH16lUhhBB37twRPj4+IiMjQwjx5DPh4uIiHj9+/NL1jI2NFTExMaJ3796aFp89e/aIfv36CbVa/cLPTVn7a0lP758v229Kbp89e/aIDh06aFqRQkNDRXBw8DPjP69FbuPGjUIIIa5evSqcnJyEQqEQ586dEx9++KHIy8sTQghx6tQp0bdv32fmFx0dLby8vEROTo4oKioS48aN07TIhYWFif379wshhFAoFMLHx0dzdqHkfvSi8V603crav0puk7JkZWUJb29vzTZ2cnISKSkpmr+vXLlSLF26tNQ0a9asKdUiJ4QQ8+bNE23bthWdOnUS77//vqZWqprYIkevRCaTwdTUtNSwunXrwsHBAf7+/ujRowd69OgBZ2fn507/dMtNSR988AEAoEWLFmjevDl+//33V6rx559/xvbt2yGTyWBsbIyhQ4ciMjIS48aNAwC8++67AIBWrVpBoVAgLy+v1C/X2NhYNGrUCG3atAEA2Nvbo3379jh//jy6dOnywuXKZDKIMp58V9Z8ZTJZmevk6uqq+eXeokWLUr/ES3re9o2Pj0dCQgLmzp2rGVZQUIA//vgDrq6uWLVqFYYPH45u3bohMDCwVCvG8zRo0ACOjo4AgLfffhv79u17Zpynt0Nubq6mZSUvLw/9+vXDhAkT8Ouvv+LRo0dYvXq15m/Xrl1DZmYmunbtCltbWwBPWvKsra0RFxeHkydPIiQkBHK5HBYWFvD398f169c1y+rYsSOAJ+/H119/jZ9++gmHDh3CrVu3IITQtAY6ODhoxh04cCBCQ0ORmZkJAOjduzfMzMwAPHmfnu7jdObMGfTt2xfVq1cHAE3Ly/MEBwejb9++yMjIwNixY1G3bl28/fbbAKBp4Ro5cqRmfJlMhoSEhJeuJwCcOnUKXl5esLa2BgAMGDAAS5YsQWJiIoDnf24qsr+W9LL95mmtWrVCvXr1ADz5nERHR790GQDg4+MDAHB0dIRCoUBubi5++ukn3L17F0OHDtWMl52djaysLNSoUUMz7MyZM+jTpw8sLCwAPHlfN2/eDACYNWsWTp8+jQ0bNiA+Ph4pKSnIy8t7ZvkvGu9F2+3mzZsv3L/atm370vVNSEjAxx9/jPbt22v2ESHEM8eEp1vJn7Z7924kJibi1KlTMDY2RkhICD7//HMsWLDgpTWQNDHI0Su5cuUKWrRoUWqYXC7Hli1bcOXKFZw5cwZLly6Fq6srgoODn5ne3Nz8hfMueaBSq9UwNDR8JhwVFRW9tEa1Wl3qIKhWq6FUKjWvi798isd5OnSoVKpnDqJCiFLzeJ62bdvi0qVLGDZsWKnhO3bsQH5+Pho3bvzC+RobG5e5niXDc1mB8XnbV6VSwdLSEgcOHNAMS0tLg6WlJUxMTBAdHY1z587h7NmzGDVqFEJDQ+Hu7v7C9SxPLa1bt8adO3eQmZmJmjVrwsLCQrP8L7/8EpmZmVCr1RBCYMeOHZrQlJGRARMTE+zdu/eF28rQ0LDUMp/+giveBnl5efD390fv3r3RsWNHDBw4EMeOHdNMa2Bg8EzdxcMMDf93iHzeOhoYGJSqLzs7G9nZ2WjYsOGLNhusra0RHh4OHx8ftGvXDh4eHlCr1XB2dkZ4eLhmvIcPH8LGxual6wk8+Ww/reRn9XnvVUX215Jett88rbyf2acVb/uSy1Gr1fDz88OsWbMAPFnvlJQUTZAuqeRySr7HM2bMgEqlQr9+/dCzZ088fPjwuTW9aLwXbTc/P78X7l8vc/bsWUyfPh1jxozRdDEBgPr16yMlJQW1a9cGAKSkpMDBwaHMeUVHR8PX11cTYt9//30sXrz4pTWQdPGqVaqwO3fu4KuvvkJQUFCp4deuXYOPjw+aN2+O8ePHY+TIkbhy5QqAJwfSlwWgYsUtO1evXkVCQgLatGkDa2tr3LhxA4WFhSgqKsIPP/ygGf9F8+7evTu2bNkCIQQUCgW+//57dOvWrdzr2bZtW9y+fRuxsbEAgBs3buDXX39F586dy5xuyJAhOH/+PA4ePKj5goiLi8OaNWvQokWLMudb1nqWpTzbt2nTpjA1NdV80Tx8+BA+Pj6Ii4vDtm3bEBISgu7du2PWrFno3r07/vjjj3Ituyx169bFiBEjMHXqVDx48EAz/P79+/jtt980rUxt27bFpk2bADwJQx988AGOHz8OZ2dn/PLLL7h37x6AJy0tDx8+RJs2beDm5oY9e/ZArVYjPz8fhw4dem6L5t27d5Gbm4tp06bB3d0d586dg0Kh0ISfa9eu4dq1awCAnTt3ol27dpq+jC/TrVs3REdHIzc3F8CTcPqvf/3rpdPZ2tpiwoQJWLJkCfLy8uDs7IzTp0/j1q1bAICTJ0/ivffeQ0FBQbnW09XVFUeOHNG0GO7Zs+eZvmFPK2t/1TVDQ0OoVKqXhrzu3bvj8OHDSElJAQBs374dgYGBz4zXo0cPREVFITs7G2q1ulS4+uWXX/Dxxx/Dy8sLAHD58mWoVCoApfejF433ou1W1v719LxLunr1KiZNmoTPP/+8VIgDnrR+7ty5EwCQlJSEU6dOoVevXmVuo+JWT6VSCSEEoqOjNa3/VDWxRY5eqrgTMvCkNcDExAQzZsxAz549S43n4OCAfv36YeDAgTA3N4epqSnmz58P4Ekn+ZUrV5arJe3evXvo378/ZDIZVq5ciRo1asDFxQWdOnVCv379UKdOHXTp0kVzeqlt27ZYu3YtJk2aVOoWA/Pnz8dnn30GX19fFBUVwdXVVdOBvjysra2xevVqLF68GAUFBZDJZFi2bBmaNm2qOWX1PDVq1MDmzZvxz3/+E+vXr4dcLoeZmRmWLFkCFxcXAHjhfG1tbV+4nmUpz/Y1NjbGV199hSVLluDbb7+FUqnE1KlT0aFDBzg6OuL8+fPw8vKCmZkZ6tevX67bNZTH9OnTcfDgQcycORP5+fnIyclB9erV4eXlpTmFtGLFCixevBi+vr5QKBTw8fHBe++9BwBYuHAhJk2aBJVKBVNTU3z99dewtLTE+PHjERoaCl9fX1haWqJWrVrPnO4HnnS879mzJ/r16wdjY2O0aNECdnZ2uHv3LoyNjVG7dm2Eh4fj/v37sLa2xvLly8u9bm5ubrh586amO4CdnV25Wz9Gjx6N/fv3Y926dZg5cyZCQ0MxY8YMCCFgaGiIdevWoVq1auVaTxcXF4wcORKBgYFQq9WaizDKOg1X1v6qa3Xq1EHr1q3h7e2NrVu3vnC87t27Y+zYsQgKCoJMJoOFhQUiIiKeCbZubm64fv06Bg4cCCsrKzg4OGhOl0+fPh0ff/wxzM3NYWFhgU6dOiEhIQFA6f3oReMNHjz4udutrP0LAPr27Yvhw4fjyy+/LHU2Y+XKlRBC4IsvvsAXX3wBAGjYsCHWrl2LyZMn49NPP4W3tzdUKhVmzZpV6sKq55kwYQKWLVsGb29vGBsbo2XLlli4cGHF3xSSDJkobzs3EVElcvjwYVhYWMDNzQ1qtRqTJ0+Gi4vLc6+ifJFz585prnKurF7HehJR1cVTq0QkSfb29li3bh38/Pzg4+MDGxsbDB48WN9lvXZvynoS0athixwRERGRRLFFjoiIiEiiGOSIiIiIJEoyV60WFBQgLi4OderUee59n4iIiIgqC5VKhdTUVDg5OT33ivrXRTJBLi4uTnOrAiIiIiIp2Lp1q+bpMdqg1SC3evVq/PDDD5DJZBg0aBBGjRqFkJAQXLx4UXMH90mTJqFPnz4vnVedOnUAPNkgxY97ISIiIqqMkpKSEBAQoMkv2qK1IHf+/HmcPXsWBw8ehFKphJeXF9zc3BAXF4ctW7bAxsamQvMrPp1ar169Mh9/Q0RERFRZaLs7mNaCXOfOnfHvf/8bhoaGSE5O1tyV/cGDB5g7dy6Sk5PRp08fTJo06Zm7jxc/r7CkpKQkbZVKREREJElaPbVqZGSENWvW4LvvvkPfvn2hVCrRtWtXLFy4UPOInd27d+P9998vNV1kZCQiIiK0WRoRERGR5OnkhsD5+fmYMGECvLy8MGTIEM3w6Oho7N+/H2vXri01/ota5AICAnD8+HGeWiUiIqJKLTExEe+++67Wc4vWWuRu3boFhUIBR0dHmJmZwcPDA0eOHEGNGjXg6ekJAJqHQz/NysoKVlZW2iqNiIiIqErQ2g2BExMTMX/+fCgUCigUChw/fhydOnXC0qVL8ejRIxQVFWHnzp3lumKViIiIiJ6ltRY5Nzc3xMbGon///jAwMICHhwcmTZqEmjVr4oMPPoBSqYSHhwd8fHy0VQIRERFRlaaTPnKvg67ONRMRERH9XbrKLVXiWasqtSSyqIbU6iUiIqLKSTKP6CqLgVyG3edT9V1GuQ3qrN27PBMREdGboUq0yBERERG9iRjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIohjkiIiIiCSKQY6IiIhIorQa5FavXg0vLy94e3tj06ZNAICYmBj4+vrCw8MDq1at0ubiiYiIiKo0Q23N+Pz58zh79iwOHjwIpVIJLy8vODs7Y+7cudi8eTPq16+P8ePH4+TJk3Bzc9NWGURERERVltaCXOfOnfHvf/8bhoaGSE5OhkqlQnZ2Nho3bgxbW1sAgK+vL6Kiop4JctnZ2cjOzi41LCkpSVulEhEREUmS1oIcABgZGWHNmjX47rvv0LdvX6SkpKBOnTqav9vY2CA5OfmZ6SIjIxEREaHN0oiIiIgkT6tBDgCmTJmCsWPHYsKECYiPj4dMJtP8TQhR6nWxwMBA+Pv7lxqWlJSEgIAAbZdLREREJBlaC3K3bt2CQqGAo6MjzMzM4OHhgaioKBgYGGjGSU1NhY2NzTPTWllZwcrKSlulEREREVUJWrtqNTExEfPnz4dCoYBCocDx48cxdOhQ3LlzB3fv3oVKpcKhQ4fQo0cPbZVAREREVKVprUXOzc0NsbGx6N+/PwwMDODh4QFvb29YW1tj8uTJKCwshJubG/r27autEoiIiIiqNK32kZs8eTImT55capizszMOHjyozcUSERERvRH4ZAciIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQIyIiIpIoBjkiIiIiiWKQq+SESqnvEipMijUTERFJkaG+C6CyyQwMkRX1pb7LqJAafSfruwQiIqI3glaDXEREBI4ePQoAcHNzQ3BwMEJCQnDx4kWYmZkBACZNmoQ+ffposwwiIiKiKklrQS4mJga//PIL9u3bB5lMhjFjxiA6OhpxcXHYsmULbGxstLVoIiIiojeC1vrI1alTB3PmzIGxsTGMjIzQvHlzPHjwAA8ePMDcuXPh6+uLNWvWQK1Wa6sEIiIioipNay1y9vb2mv/Hx8fj6NGj2Lp1K86fP4+FCxfC0tIS48ePx+7du/H++++XmjY7OxvZ2dmlhiUlJWmrVCIiIiJJ0vrFDjdu3MD48eMRHByMZs2aYe3atZq/DR8+HPv3738myEVGRiIiIkLbpRERERFJmlaD3MWLFzFlyhTMnTsX3t7euH79OuLj4+Hp6QkAEELA0PDZEgIDA+Hv719qWFJSEgICArRZLhEREZGkaC3IPXz4EB9//DFWrVoFZ2dnAE+C29KlS9G1a1eYm5tj586dzwQ2ALCysoKVlZW2SiMiIiKqErQW5DZu3IjCwkKEhYVphg0dOhTjxo3DBx98AKVSCQ8PD/j4+GirBCIiIqIqTWtBbv78+Zg/f/5z/8ZTpERERER/Hx/RRURERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEqXVIBcREQFvb294e3tj+fLlAICYmBj4+vrCw8MDq1at0ubiiYiIiKo0rQW5mJgY/PLLL9i3bx/279+Pq1ev4tChQ5g7dy6++uorHDlyBHFxcTh58qS2SiAiIiKq0gy1NeM6depgzpw5MDY2BgA0b94c8fHxaNy4MWxtbQEAvr6+iIqKgpubW6lps7OzkZ2dXWpYUlKStkolIiIikiStBTl7e3vN/+Pj43H06FEMGzYMderU0Qy3sbFBcnLyM9NGRkYiIiJCW6VRJaJUq2AoN9B3GRUixZqJiKhqKleQS05ORt26dUsNu3nzJuzs7F467Y0bNzB+/HgEBwfDwMAA8fHxmr8JISCTyZ6ZJjAwEP7+/qWGJSUlISAgoDzlkoQYyg2w/sYOfZdRIePth+q7BCIiIgAv6SOXlZWFrKwsjB07Fo8ePdK8TktLw6RJk14684sXL2LkyJGYOXMm/P39Ua9ePaSmpmr+npqaChsbm2ems7KyQsOGDUv9q1ev3iusHhEREVHVVWaL3MyZM3H69GkAQJcuXf43kaEhPD09y5zxw4cP8fHHH2PVqlVwdnYGALRp0wZ37tzB3bt30bBhQxw6dAgDBw78u+tARERE9EYqM8ht3LgRABASEoJly5ZVaMYbN25EYWEhwsLCNMOGDh2KsLAwTJ48GYWFhXBzc0Pfvn1foWwiIiIiKlcfuWXLluH+/ft49OgRhBCa4a1atXrhNPPnz8f8+fOf+7eDBw9WsEwiIiIielq5gtyaNWuwceNG1KpVSzNMJpPh+PHjWiuMiIiIiMpWriC3f/9+/Pjjj89cuUpERERE+lOuJzvUr1+fIY6IiIiokilXi5yzszOWL1+Od999F6ampprhZfWRIyIiIiLtKleQ27t3LwAgKipKM4x95IiIiIj0q1xB7sSJE9qug4iIiIgqqFxBbtOmTc8dPmrUqNdaDFFVI1QqyAyk9VxWKdZMRPSmKleQ++uvvzT/VygU+PXXXzVPayCiF5MZGCB39059l1EhFoOG6LsEIiIqp3LfELik5ORkzJs3TysFEREREVH5lOv2I0+rW7cu7t+//7prISIiIqIKqHAfOSEE4uLiSj3lgYiIiIh0r8J95IAnNwgODg7WSkFEREREVD4V6iN3//59KJVKNG7cWKtFEREREdHLlSvI3b17FxMnTkRKSgrUajVq1qyJ9evXo3nz5tquj4iIiIheoFwXO4SGhmLMmDH49ddfcfHiRXz00UdYtGiRtmsjIiIiojKUK8ilp6fD399f83rgwIHIzMzUWlFERERE9HLlCnIqlQpZWVma1xkZGVoriIiIiIjKp1x95IYNG4YhQ4agX79+kMlkOHLkCAIDA7VdGxERERGVoVwtcm5ubgCAoqIi3Lp1C8nJyejTp49WCyMiIiKispWrRW7OnDkICAjAiBEjUFhYiO3bt2Pu3LnYsGGDtusjIiIiohcoV4tcZmYmRowYAQAwMTHByJEjkZqaqtXCiIiIiKhs5b7YITk5WfM6LS0NQohyLSA3Nxc+Pj5ITEwEAISEhMDDwwN+fn7w8/NDdHT0K5RNREREROU6tTpy5Ej0798frq6ukMlkiImJKdcjui5fvoz58+cjPj5eMywuLg5btmyBjY3NKxdNREREROUMcoMGDYKTkxPOnj0LAwMDjB49Gi1atHjpdN9//z0WLlyoCX35+fl48OAB5s6dq7lgYtKkSZDLy9UwSEREREQllCvIAYCDgwMcHBwqNPMlS5aUep2WloauXbti4cKFsLS0xPjx47F79268//77pcbLzs5GdnZ2qWFJSUkVWjYRERFRVVfuIPc62NraYu3atZrXw4cPx/79+58JcpGRkYhMsi2ZAAAgAElEQVSIiNBlaURERESSo9Mgd/36dcTHx8PT0xMAIISAoeGzJQQGBpZ6JBjwpEUuICBAJ3USERERSYFOg5wQAkuXLkXXrl1hbm6OnTt3PhPYAMDKygpWVla6LI2IiIhIcnQa5BwcHDBu3Dh88MEHUCqV8PDwgI+Pjy5LICIiIqoydBLkTpw4ofl/QEAAT5ESERERvQa87wcRERGRRDHIEdErU6vL94SXykJq9RIRvYxO+8gRUdUil8sQd7pA32WUm5OLqb5LICJ6rdgiR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRDHJEREREEsUgR0RERCRRWg1yubm58PHxQWJiIgAgJiYGvr6+8PDwwKpVq7S5aCIiIqIqT2tB7vLly/jggw8QHx8PACgoKMDcuXPx1Vdf4ciRI4iLi8PJkye1tXgiIiKiKk9rQe7777/HwoULYWNjAwCIjY1F48aNYWtrC0NDQ/j6+iIqKuq502ZnZyMxMbHUv6SkJG2VSkRERCRJhtqa8ZIlS0q9TklJQZ06dTSvbWxskJyc/NxpIyMjERERoa3SiIjKRa1SQW5goO8yyk1q9RLR36e1IPc0tVoNmUymeS2EKPW6pMDAQPj7+5calpSUhICAAK3WSERUktzAAH8e26LvMsrNsfcwfZdARDqmsyBXr149pKamal6npqZqTrs+zcrKClZWVroqjYiIiEiSdHb7kTZt2uDOnTu4e/cuVCoVDh06hB49euhq8URERERVjs5a5ExMTBAWFobJkyejsLAQbm5u6Nu3r64WT0RERFTlaD3InThxQvN/Z2dnHDx4UNuLJCIiInoj8MkORERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdEREQkUQxyRERERBLFIEdE9AYSKqHvEipMijUTaZuhvgsgIiLdkxnIkP3jXX2XUSFWHo31XQJRpaOXIDd8+HBkZGTA0PDJ4kNDQ9GmTRt9lEJEREQkWToPckIIxMfH47///a8myBERERFRxem8j9zt27cBAEFBQXjvvfewZcsWXZdAREREVCXovEksOzsbzs7OWLBgAYqKijBixAg0bdoULi4upcbJzs4uNV1SUpKuSyUiIiKq1HQe5Nq1a4d27dppXg8aNAgnT54sFeQiIyMRERGh69KIiIiIJEXnQe7ChQsoKiqCs7MzgCd95p7uKxcYGAh/f/9Sw5KSkhAQEKCzOomIiIgqO533kcvJycHy5ctRWFiI3Nxc7Nu3D3369Ck1jpWVFRo2bFjqX7169XRdKhEREVGlpvMWuV69euHy5cvo378/1Go1Pvzww1KnWomIiIiofPRy/49p06Zh2rRp+lg0ERERUZXBR3QRERERSRSDHBERVTlqtVrfJVSYFGsm/eOjFYiIqMqRy+W4dOmSvsuokLZt2+q7BJIgtsgRERERSRSDHBEREZFEMcgRERERSRSDHBEREZFEMcgRERERSRSDHBEREZFEMcgRERERSRSDHBEREZFEMcgRERERSRSDHBEREZFEMcgRERFJjBAqfZdQYRWpWS2EFit5/fRZL5+1SkREJDEymQFyc/fru4wKsbDoX+5x5TIZTqalaLGa18utto3els0WOSIiIiKJYpAjIiIikigGOSIiIiKJYpAjIiIikigGOSIiIiKJYpAjIiIikigGOSIiIiKJ0kuQ+89//gMvLy94eHhg69at+iiBiIiISPJ0fkPg5ORkrFq1Cnv37oWxsTGGDh2KLl26wM7OTtelEBEREUmazoNcTEwMunbtiho1agAAPD09ERUVhUmTJmnGyc7ORnZ2dqnp7t+/DwBISkp67nwzUzO0VPHrl5hYWKHxs9OzXz5SJZKbmFih8R8lZ2qpEu1INKvY+uVlSmv9zCv4/qWkVezzrE+JiSYVniY5PUsLlWiHZQXfu9z05x9PK6vsRIMKjZ+SIp0nAwBAYgXfv7w86XzvAYC5ecXWLy0zXUuVvH6JBYpnhhXnFZVKu49T03mQS0lJQZ06dTSvbWxsEBsbW2qcyMhIREREPHf6gIAArdanCyv0XYDW/VvfBWjVRoTruwTtWrFK3xXQK/tS3wUQleFzfRegF6mpqWjcuLHW5q/zIKdWqyGTyTSvhRClXgNAYGAg/P39Sw1TKBS4d+8emjRpAgODiv0qexVJSUkICAjA1q1bUa9ePa0vT9eq8vpV5XUDuH5Sx/WTrqq8bgDX73VTqVRITU2Fk5OTVpej8yBXr149XLhwQfM6NTUVNjalHzZrZWUFKyurZ6Zt1qyZ1ut7Wr169dCwYUOdL1dXqvL6VeV1A7h+Usf1k66qvG4A1+910mZLXDGdX7XarVs3nDlzBhkZGcjPz8ePP/6IHj166LoMIiIiIsnTeYtc3bp1MX36dIwYMQJFRUUYNGgQWrduresyiIiIiCRP50EOAHx9feHr66uPRRMRERFVGQaffvrpp/ouorIyMTFBly5dYGJS8VsWSEFVXr+qvG4A10/quH7SVZXXDeD6SZFMCCH0XQQRERERVRyftUpEREQkUQxyRERERBLFIEdEREQkUQxylcDT3RTZbZGqgpKf4zfhM12Z1lGtVuu7BHqDafvZolWNEAJnzpx55ekZ5PSs+JFleXl5uH//PgBAJpNVqi8FXXveQUDfX0w8MFVM8ee6oKAARUVFzzyGr6pRqVSQyWQoLCxEZmamXmtRq9WQy+XIyMhAXFyc5rgiJcX7u1Kp1HMlr9ebcBxRq9UwMDBAamoqduzYgRs3bkChePaB8vQ/f/75Jz799FMcOXLklabn7Uf0qPiAm5ycjClTpuCXX37BtWvX4OLioglzVf0L8GnFBwG1Wo29e/fiypUraN68OYyNjfW2PUrWtHTpUpw/fx4pKSlwcHDQeS1SoFKpYGBggOTkZISEhODAgQNo2bIlateure/StKL485GUlIQ5c+YgOjoaarVaL58PpVKp2fYzZszAjRs3cP36ddSoUQN169bVeT2vovjzk5KSgk8++QQ5OTkwMDCQ/Ofn6YBjbGwMc3NzGBsb67u010omk2n2/bS0NFy7dg0GBgZo2LChTp6TLjVKpRJ169ZFgwYNsGbNGlSrVq3Cxw4GOT2SyWTIzMzE/PnzMWrUKLi7u2PlypV4/PgxOnfu/MaFOOB/rZFTp05FzZo1ceXKFezevRu9evWCqampXsJccU3BwcFwdHREixYtsGTJEtjZ2enkOXpSU9wa9MUXX8DDwwPVq1fH1q1b4ejoKPkv4+eRyWTIyMjAJ598gqFDh8LOzg7Lly9HgwYNYGdnp5MahBB49OgRzM3NkZ+fjzlz5mDUqFFo3749fvzxR6Snp8PIyEgSz8+Uy+VITU3FrFmz0LFjR1y7dg0PHz5EvXr1UKNGDX2X98pKBpz8/HxcvXoVQgjY2trC0FAv9+bXiqKiIoSHh2PAgAHo378/duzYgfj4eCiVSjRq1AhGRkb6LrFSkcvlSEpKwrfffgt7e3vs2bMHtWvXhr29ffnnocX66AVKnibMzs5GmzZtUL16dezduxfTp09HZGQkvvvuOz1WqB/Fp5OjoqJQp04dBAUFoaCgAM2aNcPRo0d1HuJKnt6+c+cOjIyM4OrqisOHD2PixIn4448/kJycrLN6Krvi7SWEwObNm3H58mV4eXlh7NixcHd3x9y5c3H9+nU9V/n6lNyPb9++jVatWsHW1haxsbEYMmQI5syZg+PHj+uklujoaPz8888AADMzM3Tp0gXW1tbYuXMn/Pz8cPv2bRw4cAB5eXk6qedVrFmzBo8ePQIAnDp1CgMHDkRgYCBycnJw4cIFfPfdd7hw4YKeq6wYIQQOHToE4EnLy7/+9S8EBgZizpw5SExMxP79+7F3715kZWXpudK/p3hfKCoqgpGREZo1a4aioiKEhYVh0aJFUKvV+O2331BUVKTnSisXIQTUajW2b9+OVq1aYeHChVi2bBnWrVuHXbt2lXs+DHI6plKpIJfLkZaWhtOnTyM9PR09e/bErl270K9fPzRr1gxdu3ZFr1699F2qzhT3GykOafb29hBCYPDgwRg8eDCCgoJw6dIlZGdn66ym4j5exWrUqIFatWphypQpcHV1hY+PD06fPl3l+vC8quLtlZ+fD5VKhSFDhuCtt97CggULAAAjR47EgAEDYGFhoedKX4/i/TgjIwPXrl2DhYUFunXrhrVr18LPzw9du3ZF+/bt0bx5c53U4+HhAS8vL4wePRqpqano3bs3fv31VwQFBaFFixYwNDTE1KlTYW5urpN6XkXfvn1hamqKxMREdOrUCRkZGZg9ezZWrlyJ3r17Izc3V3It4JmZmbC0tERRUREMDQ3RsmVL5OTkIDQ0FGFhYbC0tNS0zEmVUqnUdBFauHAhDhw4AHd3d+Tn56NNmzYAgKysLIwbNw7Vq1fXc7WVQ8nvPLlcDltbW9y4cQO5ubno2LEjunXrhoMHD+Lx48flmh9PreqYXC5HSkoKJk6cCJVKhdq1a6NTp05ISEhATEwMtm/fjsWLF6Np06b6LlUnSvY/W7x4MeLj43Hnzh3k5OTAwsICtWrVwurVqzFgwAC8/fbbOqmpuI+OWq3G9OnT8dNPPyEhIQG5ubmoXbs2hBDYsGEDRowYgbZt2+qkpsqsZF/PyZMn4+bNm8jPz8fIkSNx7tw5HD58GJ6enmjdujWsrKz0Xe5rUbwfjxs3Drm5uZog9+DBA5w5cwa7d+/G0qVL0aRJE63WURwolUolDA0Ncfv2bYSHh2PgwIFISEjAZ599hpMnT+KTTz7Rei2vqvhHQK1atXDkyBEsXLgQfn5+aNeuHQ4cOAADAwPs2rULCxYswFtvvaXvcstNCAFzc3M0adIEoaGhOHfuHMaMGYPU1FTk5uaiSZMmOHToEEJCQiTTf/F55HI5srKyMHbsWLi6uqJBgwZwcnJCcnIyVq1ahdOnTyM0NBTNmjXTd6mVghBCc7zcsGEDFAoF6tevj8LCQuzZswdpaWm4cOECFi9ejDp16pRrnnxElw4IIfD777+jVatWMDY2xmeffQZra2t8/PHHAIAdO3bg3r17cHR0xNtvv/3GfeCFEPjiiy9QUFCARo0aIT09HUVFRWjXrh1u3bqFdu3aoUuXLjo9tSqEwNdffw0A6NSpE/766y/cu3cPPXr0AABUq1YNrVu31kktUpCRkYFp06ZhyJAhyMjIwMWLF9G3b1+0bt0a3377LSZMmAAbGxt9l/m3/fXXX2jatClkMhlCQkLQqlUrjBw5EgCwceNGZGdnw8rKCm5ublrvH1ccoJOSkhAREQFPT0+4urrim2++waFDh7Bt2zYkJSXB0tKy0gaFklfYpqeno379+jhy5AgOHDiAZcuW4eTJkzh9+jRmzpxZoT5D+lb8Y/Dx48cwNDRESkoKli9fDnt7ewQGBiIwMBDGxsZYvHgxWrZsqe9yX0nxZ87e3h7Xrl3D1q1bsXjxYgDAiRMnkJaWBj8/Pzx+/BjW1tZ6rrZyKP68Z2dnY968eTAzM0PNmjVRvXp1dOzYEQ8ePMCDBw/g6elZodZ8tsjpQFxcHPLy8tCoUSMIIZCVlQW1Wg07OzsYGxvjzJkz6NKlC3r16oWaNWvqu1ydCw4ORkZGBpYtWwZHR0c8evQIhYWFGDJkCDp27KjpoK3tEFcyKK5duxa7d+/G4sWLNVfNXrx4EYMGDUKzZs0q7Rejvty6dQsWFhbo0aMHDh48CHNzc8TExAAAJk6cCEtLSz1X+Pf9/PPPKCwshK2tLQwMDHDv3j1YW1vDzs4OcrkcMTEx8PLyQu/evXXyxVV8kUVISAj69OkDIyMjJCcnw9XVVfPjaOzYsZV628tkMqSkpGDSpEkwMTGBmZkZunfvDgsLC4SGhmLatGkYNGhQuVsmKoPiswzFLdQmJiZo1KgRunfvjqioKNy6dQurV6+Gh4eHpFoYn9a8eXPY2Njg6NGjaNu2LZYtW4aGDRuiWbNmiI2NxYULF+Du7l5lulO8DjKZDI8ePcKyZcvQvn17zJw5EyYmJnjw4AHi4+MxaNAguLi4VPj4UXUulamk1Go13nnnHeTm5mLt2rWaMHfv3j0cPHgQSqUSP/zwAzw9PfVdqs4U/1ot5u/vjwULFuDixYvo0KEDrKys8PvvvyMnJwfm5uY6uWT96ZomTZqEmzdvIjw8HIsWLYJMJsP169eRnp5eqfsZ6Urx9lIoFFAqlWjWrBlu3bqFiIgIfPLJJzhz5gwOHz6M3r17V5kr8nr06IG8vDx8++23aNGiBYyNjXHz5k38+OOPUCgUOHHiBAYOHKiTWop/dPz+++9ISUlBkyZNsHjxYvTq1QsRERHYvHkz/P39K/XtHtRqNZRKJT799FMMHDgQbdq0wZYtW5Cfn4+AgACMGDECKpVKcp8fuVyOnJwchISEICgoCNWqVcPx48eRm5uLqVOnIjw8HBkZGZJtpSpuVTIyMkJCQgLWrVsHExMTREREYPLkyTh37hx+/fVXrFy5kleo/r+S3y8mJibIzc1FXFwc8vPz0blzZyiVSly6dOmVLwbhqVUtEUIgJSUFdevWRVpaGjZu3Ahzc3MkJyfD3d0dmZmZEELg8uXLGD16dKXtv/K6lex/FhYWBpVKBXd3dxQVFWHJkiXw8vJCQkIC/P39Nacxta34wKRWqzFt2jQYGRlBpVLhk08+wfz585GRkYHGjRtjwIAB6NKli05qqsyKQ8SDBw+wdOlSmJmZwcnJCX369MHs2bPh5OSEU6dOYfXq1Trr7K9NOTk5sLS0RFpaGjZt2oSCggLI5XK4ubnh5s2bUCqViIuLw9SpU7Xat1UIgW3btqFNmzZwcnLSDF+7di2MjIzg5uaGoqIiREZGYsmSJTAyMqqUtzDKzMwsdeZh+fLlyMvLQ0pKCj766CMcO3YMLi4u6Ny5sx6rrLji40jxrWCmTJkCDw8P/PDDDxgzZgz+85//YPbs2ahZs6bkwunTMjIyMH78eISGhkKhUOCf//wnAgMD4ezsjPj4eNSqVQv169fXd5mVQsn7au7atQv169fHgAEDEBwcjHr16mHixIkwMzNDQUEBTE1NX2kZPLWqBUIITJo0CbVr10aDBg0wbNgw9OjRA0FBQVAoFDh16hQaNmwIPz+/N+50avGBbtasWahVqxZcXV3x+eefo2vXrvDx8cHq1avh7+8Pb29vTUdubSrueAoAM2fOhJ2dHRYsWIBTp07hhx9+wNq1a3Hy5EkUFRVh7Nixmmkq4xekrshkMuTm5mLevHkICgpCkyZN8OWXX6Jr167o1q2b5gbXUg9xQgj84x//QIMGDWBlZYWgoCD4+PggKCgIt2/fxtWrV9G6dWsMGDAA7u7uWr9H3sGDBxEWFoazZ88iNzcXly9fRvv27dG5c2eYmJhg79692L17N2bOnIm6detWys/o6NGjcejQIQghUKNGDVhaWuKdd96BnZ0dGjVqhLy8POzatQtDhgyRzIUxQggsXLgQcXFxmv5ulpaWqF+/PgwMDNCzZ0+YmJggKioKfn5+km3RLz7uKZVKrFu3Do8fP8b777+PRo0awc7ODsuWLUP16tXh5uZWqU/n61rxhVFz5sxBq1atsHPnTqSlpWHu3LnYsmUL7t69i65du/6tcM8gpwWJiYmIi4tDp06dkJWVhd9++w1XrlzB4MGDYWdnh9zcXFy4cAFdunSBiYmJvsvViZK380hISMCJEyewZMkS2NrawsnJCStXrsSUKVPQsGFDLF68GB06dNB6/5HiX9DFfv75ZwwbNgzVq1fHu+++i/3796NLly4YOHAgNmzYgJs3b6JHjx6V8gtSF0q+h2lpaYiNjUXTpk2xfft2TJ8+HWfOnEG3bt3g7u5eJX6cXLt2DZcvX0aPHj2Qmpqqua+Tu7s72rZtiz/++AN//vknOnXq9Mq/pCvCwcEBJiYm6NSpE7p27Yrw8HAcO3YM9+/fh5WVFZo3b46BAwdW6gB97949WFhY4OrVq5p727Vr1w75+fnIysrCpk2bsGTJEkmdoXj8+DE2bdqEpKQkxMTE4Pr16ygsLISrqyvUajXOnj2LTZs2YenSpZLtE1f8o7qgoADGxsbIz89Hfn4+kpKSULduXTRr1gytW7eGnZ2dZAK4NgkhcPz4cZiamsLS0hJr165Fhw4dMGjQINy+fRsnT57E3bt38emnn8Le3v5v9yPkfeRes+I7dRsZGWHkyJG4dOkSIiMjUbduXU2Ljq+vL4KDg9+YTqAlTzksXboUDx8+RM2aNXH37l0AgKmpKSwsLJCbm4s+ffpg6dKlWm/dKG6JE0Jg3rx5OHLkCIQQuHLlCnJzc/HXX38hJSUFjx8/hlwux969ezFq1Cit1lSZFW+v7OxszU1bGzdujNDQUAwaNAi1a9fGuXPntN6CqkuNGjWCSqXC0KFDkZKSgmPHjuHKlStYtmwZAGD8+PGYPHkyzMzMtF6LEAJFRUXIzMyESqVCnTp18NZbb6Fbt25QKBQICwtDhw4d0KhRI63X8iqKe/DY29vDyspK04L73//+F6tWrcK8efNgamqKDRs26OxpGK+DWq2GhYUFvLy8MGbMGKxYsUJzz74VK1Zgw4YNGDRoENavXy+pq25LEkLAwMAADx8+xLx58xAWFoacnBzY2toiNTUVR44cQUZGBpycnCQbVF+3O3fuYM+ePfjpp5/w6NEjeHt7o1q1apg6dSqCgoLw4Ycf4uTJkygoKHgtF86xRe41KW52Lm6xyM3NRWFhIczNzdGgQQMMHToUBw4cwI8//ghvb+9K23/ldSsZmIKDg1G/fn34+/vjwoULOHPmDC5fvowdO3Zg5MiRaNmyJYQQaN68uVYfxVOyJW7q1KmwsrLCmDFjYGZmhn379iE2Nha7du3ClClT0LZtW83zK9/UX5rffPMNHBwckJOTg6lTp+LKlSs4ffo0jI2N0aZNG1y9ehVHjx7FvHnzKm2QeBXGxsZITExETk4ObGxs4OjoiAEDBuCzzz5DamoqunXrppOWOODJ6WwDAwM0a9YMc+fOxeHDhzFz5kz4+vrC2dkZvr6+qFatmk5qeRXFx7rGjRvjX//6Fy5evIgLFy5g0aJFeO+991C7dm00bdpUcreoKdlCvWnTJlhbW+PChQuYMGECHBwccO7cObi4uKBevXp6rvTVyWQyPH78GFOmTMGoUaNQUFCAw4cPw93dHVZWVrh37x46duz4xpxdehm1Wg1ra2s0bdoU0dHRePTokeZOB/n5+UhJScFPP/2EFStWvLa7H/Bih9ckODgYhYWF8PX1RcOGDeHg4AC1Wo3w8HDk5+fjww8/RNOmTZGcnPxG3rpCoVBgwIABcHFxQUhICABo+p5ZW1ujffv2Oq1HCIGCggLs2LEDe/fuRWRkJKytrZGQkABjY2Pk5uZKqmVAm6ZNmwZTU1MYGhqiQ4cO6N27N86ePYvo6GhMmDABcrkc1apVk9QtIl5k+vTpeOutt+Di4gIHBwfUrFkTycnJiIiIQL169RAYGAi5XI709HTY2trqtLbiHyBff/01jI2NNX1ujY2NJdFvs7j+s2fPIiwsDAsXLkS7du2e6eIgVStWrMDx48exaNEiyV2o8Twl35fk5GSEh4fj448/xqJFi9C/f3+kp6djwIABMDQ01NkPmsqueJvl5uZCLpfj0aNHCA8Ph5OTExo1aoSYmBj88ccfmD9//mu9f6D0955KoKCgAEqlEsnJyUhPT8f8+fPx9ddfIy4uDjNmzIBarcaRI0dQVFT0Roa45cuXY8eOHdi2bRvOnz+P9evXAwDc3NzQu3dvnYc4ANi/fz/GjBmDoUOHwtfXFxMmTEBmZiYaNWqEevXqMcThSfgGgPDwcNSuXRt//fUXnJycYGlpia5du8LU1BTW1tZo0qRJlQhx6enpSE5OxrVr13DlyhV89NFHiIqK0px+v3XrFvbt2wczMzOth7iSz3EFSl+U07JlS+zYsQOpqakwNjYGoP17LL6Kp9sIiutv0KABAGhacCpj7a+i+Fm7xSFOym0kJW9ce+/ePdSqVQsKhQLvvfcegoOD0aRJE0RFRSEvL48h7v+VvEH3lClTMGzYMFy6dAkzZ87En3/+iQcPHuDDDz/Ehg0bXvtNoHlq9W8SQsDIyAh2dna4c+cOpk6dCplMhsjISPz22284ceIEevbsCQ8PjzfmSp7nPad09+7dkMvlmDFjBhYtWoTc3Fx06tRJbzXa29sjLS0NW7duRXBwMFJTUxEeHo5BgwZVidaB18HAwADp6elIT0/Hu+++i9u3byM2NhZ2dna4dOkSoqOj4enpWalP6VWEubk5bGxs8ODBA8yePRt37tzB1q1bceTIEaSkpKB9+/bo2bOn1vu2Fn8hpKen4/Dhw6hVq1apY0fTpk2RkZEBBweHSntMKe4cr1AooFAoNLf0kcvlqF69OrKzs3H69Gm4urpCLpdLJswVr0PJY1zxs0bt7e2xefNmFBUV4Z133pHMOj2t+EdDamoqAgMDce3aNZw+fRoBAQHIyclBbGwsDhw4gEWLFlWprhR/l0wmQ2ZmJhYtWoQxY8agffv2mDFjBtq0aYM+ffrg+PHj6NWrl1aOHwxyf5NMJoMQAiqVCufPn0dKSgrOnTuHqVOnYtq0abhz5w769Okjub4fr+rWrVuoVasWACAqKgomJiaws7ODo6MjviMxHYkAACAASURBVP32W5iYmGDWrFkwMzPT/DLXtqNHj6Jx48YwMDDAzp07kZKSgubNm6NDhw6IjY3F9u3b8cknn8DV1bVKXG35d33zzTe4ceMGmjRpgokTJ+LChQs4fPgwhg8fjtu3b2ueD/iPf/yjynVuFkLg6tWrAIDz589j2rRpGDFiBGJiYnTyhIHiL9H09HTMmDEDCQkJ2LJlC9q3b19q2Z06daq0DyAvfrJBUlISFixYgD179sDBwQE2NjYoKiqCgYEBatSooQnFUgk8JZ/Y8O233yI2NhYdO3aEXC5HYWEhDA0NUbt2bXTp0kWyF7IV/4goKCjAyZMn0b59e0ycOBG//fYbYmNjMW/ePHTs2FHThYhK347q9u3byMzMxNtvv40TJ06gb9//Y+8846I6t7d9DcPQO6j0XkREUUAFKYoVFaNRY4kxxsQSozGKvcXeNbFEY9TYojmK3dgFQSyxodhRUVSUKiAgZYDZ7wfPzEty8j9JTgSGYa5PyQ8/rIFnnr32KvfdmalTpxISEkK/fv2q7FyoE7l3gEgkQl9fn5cvX7Jo0SLGjBlDUFAQAC1atFCZisWfMWfOHBITE2nTpg13797l6NGj5OfnKwY/MzMz2bdvH+Hh4dW2wbV48WISEhLo1q0bhYWFXLx4kdTUVGQyGQ4ODpSVlXH37l3c3NzU7VTe2snp6ekRHx/P9u3bGThwIGPHjiUtLY1Dhw4xZ84ccnJyGDBgAA4ODjUd7jvHxMSEuLg4vv32W6ZOnap4KIeEhFT591j+EH3z5g0TJ07k/fffZ9y4cUilUnbt2oWjo6NiNEOZq8byysSiRYvo2LEj1tbWzJ07l9atWyuSUTMzs1qnpya3RJs+fToODg4cOnSI+/fvExYWptAAc3BwUNoq6Z8hP3+ZmZmMHj2alJQUdHV1CQgIwMvLi/j4eK5du0Z4eHi1bGrXBuQV2sLCQgRBQFtbG1tbW7Zs2UKPHj1wdnbm0aNH9OrVS1HgqArUidz/QOUMXBAExf/LN/tat26Nqanpf7QYVZklS5ZQWFioME2WiyEnJCSQlpbGixcvSEhIYNKkSdVWjl++fDk5OTksX74cgKysLIUa/507d7h69SonTpxgwoQJeHp6VktMyszp06cxMDDAy8sLMzMzrl27hqmpKb6+vvj6+nLy5ElFm0BZq0H/BPml3KRJE/Ly8ujSpQu6urq/mU+rKiqbx+fm5hIdHU1qairh4eE0a9aM1NRUjhw5QseOHZXWdkt+35WUlHDgwAEuXrzI9OnTadKkCRKJhLFjx9KhQ4daZ00lPxelpaWsWLECfX19xo8fT9++fdm0aRMXL15UWCzW5vteJBKRn5/PokWLaN++PaGhoVy+fJnc3Fx8fX3x9/enWbNmtS4Br0o0NDTIyMhg4sSJPH/+nOjoaPz8/JBKpRw+fJh9+/axcOHCKtdFVCdyf5PKpWdNTU2F5IggCGhqanLgwAHu3r1L27Zta/WX+u8wadIktLS0kB+lnTt3cujQIcVGU2pqKkePHqVfv374+vpWS0zjxo0jPz+fpUuXArB79262bNlC9+7dcXNzo7S0lIyMDLp164afn1+1xKTsODs7Y2JiwrFjxxAEgaCgIG7fvs3Tp08pKCjg1KlT9OzZUyUucvnDWd7qg//vOqKhocFPP/2EVCrFx8enWr7H8irWyJEj8fT0ZNCgQZw5c4Zr164REhKCv78/QUFBSlvdl9+LWVlZzJgxg9DQUFJSUrh16xYBAQE0bdoUMzMz7OzsqlRa6F1TuZ26c+dOrKysiI2NxcrKCicnJ7p3786uXbto3bq10v5t/ipSqZRjx45x7tw5IiIi8PPzQ19fnyNHjlBUVKRO4v6NIAhcu3YNa2trCgsLGTt2LIMHD8bS0pKTJ0+io6ODvb099evX5+OPP8bZ2bnKY1Incn+DyqXnMWPGcPfuXQRBwMbGRvEwCA0NpWHDhipZsfgj8vPzFRe3r68vUVFRnDp1iq+++gpjY2OMjY1p2rQp3bt3x93dvdpkEi5evEhSUhL9+vXj6NGjHD58mNmzZ2NkZER2djbm5uZ06dIFR0fHWiHdUJXIk5pXr16xfPlyCgsLef36NaampjRs2JBt27Zx48YN5s+frxIzcZUfzpMnTyY9PR1NTU2FrZWmpibe3t44OjpW+cyk/OwJgsCWLVvIysqic+fO2NjY0KJFC6Kiorh37x5BQUFoa2sr7TmVV3OWLFmClZUVffv2xdXVlXv37hETE0NoaCiNGzeuVUkc/LZNLJef0dbWJjo6WrHg0LNnz1qZxMlkMtatW6fQOROLxdSrV4+ysjJu3LihqMabm5vTtGnTWvkZ3zWCIDB48GCOHj3Khx9+iEgk4smTJ/j4+PD999/z+eefU1xcTKNGjQgMDKy2mWt1Ivc3kH+pN23aRLNmzZBIJDx8+BB4u1IvFovR1NSsM0mcTCZDR0eHHj16sGjRIs6cOUNaWhqzZs3CxsaGq1evMn/+fAICAhTzAVX9IJI/GNu0acOTJ08YP3486enprF27FjMzM65fv87UqVMJCgpSzOso68OxupAncbNnz6Zdu3YMGDCAW7dukZGRgaGhIWFhYfTp00clhpvlFbfXr1+zatUqHB0dycnJ4eXLl+jo6CiEW83MzKr8Eq48X1NRUYG+vj5FRUW8fPkSIyMjbG1tCQ4OpkmTJkq7FFB5fOTVq1ecPHlSUa2ys7PDwsKClJQUGjZsWKuqOZU/V3R0NL/++iuhoaGKz1VYWMiFCxcIDAxUdGZqG/fv32fJkiW8ePGCo0ePKhxDfH19yc7O5ty5c5ibm9O8eXN1EsfbMzF16lSMjIwwMDAgPDwcDQ0NtmzZwpo1a1i8eDFisZjvvvuObt26VauAvDqR+wvIk4OKigoiIyPJz89n8uTJeHt78+zZMxISEhTl1LqE/HdiZGREhw4d+PHHH2nSpAnh4eEkJiayatUqBg8ejLe3d7XGJL+Eg4ODFevyn3zyCU+ePGHhwoWMGjWq2lq8ykzlh9Xt27dZu3YtXbt2xdnZGVtbW27evElhYaHKeKdWFuscO3Ys9erVIzIyEjc3N+7fv8/du3cxMjKqFq1HeUKZlpbGjBkzuHLlCqWlpZibm/P69WsePnxIvXr1sLa2VtoNyMrt1F9++QVtbW0aN27M1atXKSkpoX79+jg6OuLv71+rFgAqKioQi8Xk5eXx8OFDmjRpQklJCffu3VMk2K6urrRu3VppE+w/QxAEDAwMePXqFSNHjqRp06YcOXKEb775hnr16vH06VOaN2+Op6dnrUrAqwq5M5G9vT0TJkxg06ZNtGrVClNTUyIiIrhy5QoFBQXs3r27Wmbifo86kfsT5JdVaWkpEokET09PduzYgba2Nk2aNKFhw4ZkZmbSqlWrOnng5XNGRkZGdOzYkTVr1pCQkMCFCxcYMmSIYnu3qqncHhWJRIrZp4CAAFJTUxk/fjzXrl1j1KhRBAYGVktMykzl4fobN27QqFEjfH19mTVrFk2bNsXV1RVXV1caN26sEtZk8sQpMzOTkydPYmRkxPHjx2nWrBkuLi7Y2Njw7NkzAgICqnwjTyqVoqmpSUlJCVOmTGHIkCFYWVmxY8cOQkJCcHNz48WLF7Ro0UKptwNFIhFZWVkMGzaMxo0bs379eszMzPD39+f48ePIZDI8PT2RSCQ1HerfQi7qOmrUKPLy8oiKiiIkJITi4mLi4uKwtLTEzs6uVltSiUQiJBIJt27dIiYmBk9PTy5dukSPHj0oLi7m5s2b9OvXr04K2P8RycnJlJSUMGzYMMRiMYcPH6Zz584YGRkhEonw8fHBx8eH3r17Y2VlVf0BCmr+TyoqKgRBEIT09HTh008/FSZNmiTExsYKT548EcLDw4WffvqphiOsfsrLy//wv0tLSwVBEISXL18Kbdq0EU6fPl0jMeXm5v5HTIIgCEuWLBFOnTpVbTEpM/JznZGRIfTt21eYPXu20LdvXyE1NVWIjY0VfH19hcTExBqO8t1TUFAgDBgwQNi5c6cgCIKwY8cOoUuXLsL169cFQRCEsrKyKo/hwYMHwqNHj4T8/HyhoKBAGDdunHDx4kVh+PDhQlxcnLBu3Trh2bNn1RLLu2D37t2K32efPn2EFStWCI8ePRKePn0qpKen13B0f4+ioiJBEN5+PxYsWCCcPXtWKCwsFDp27Chs3LhRKCgoEHbt2iVkZGTUcKT/HJlMJgiCIEilUmHSpElCr169hF9//VXxM6lUWpPhKT2jR48Wbty4IQiCIOzfv18YP3688Pr16xqLR3nFiJQA+ezQ9OnT6dmzJyEhIaxcuZKsrCy+++479u7dS0FBQa22Yvk7yIfE5bMC33zzDSdOnADeGoxLpVKsrKw4ceIE7dq1q5bfS+WYhg4dyty5c5k2bRqCIChiApgwYQLt27evM3+r/4a8wixXIB8xYgQmJiZMmzYNW1tbVq9erTJznpWtrrKysjAzM+PmzZsADBgwgN69ezNnzhykUmm1yHpkZmaycuVKRowYwZs3b7C2tmbkyJEMGDCABg0aEBsbi4aGhkKXTFmpqKgAwNbWll27dtGrVy9++OEHGjVqxNatW7G2tq5V1Zz79+8rBN1FIhF6enocP36cL7/8kk2bNgFw8uRJPvjgA5UQd5d3L8RiMZaWljg5OdGyZUvFz2tbFbUqkT8zhH8L/8Pbqvrr16+JjY3l0KFDjBgxokY7F+rW6h8gnx2SSqWkpaUhk8lo0aIFR44cwdPTk5UrV9KiRQu++uordHV1a+WMxN9F+HdrShAEFixYgEQiwdvbm507d2JgYICLiwtisRhBEBCLxQpZlqqksqnzihUrsLGxYejQoVy7do0zZ87Qpk0bNDU1/6PtWheRyWTs2bOH6OhoGjRogIWFBWVlZejr6/Pjjz8ycOBAnjx5QlRUFKNHj65S8crqQj7rlJ2dzdmzZykvL6d58+ZkZWVx8eJFAgICaNasGeHh4ejp6VXp2ZDfKfb29pw+fZr09HQCAwPx9fVFLBZz5coVoqOjmT59Ok5OTlUWxz/hwYMHmJub8+rVK+bNm8ezZ88wNjbGwMCA1NRUzMzMWL9+PRMnTsTCwqKmw/1b6OjoMGvWLJYtW4aXlxfu7u4cPnwYJycnnJ2d+eGHHxg8eHCt27qVI7cR+721mFgsplGjRvz44484OTlha2tbZ+/I3yN/bsjHdCo/Q9LS0jh27Bj3799n0qRJuLi41Gis6kTud1SeHfr6669xd3fH0NCQ7du3M3ToUAwMDMjPz6d9+/Yq8bD7K1ROmPbt28fNmzf5+uuv8fLyol69eqxbtw4DAwPc3NyqJYGrHJMgCBw4cIArV67QsWNHGjVqhI+PD3FxcURHR9OhQ4c6fzHJZDLGjx+PVCqlpKREIfgrkUh4+vQp3t7eiMViHj16xNdff60Siw3w/8U6p0yZgq6uLtevX+fFixe0a9eOGzducPv2bVq2bImWllaVJ3HyO+Xx48eEh4djZGREdHQ07u7uNG/enJCQELp3715ttnV/l0OHDnHw4EH09PRYvXo1dnZ26OnpcenSJVq0aEHbtm15/Pgxn3/+ebXoZr0r5ImNlpYWgiCQlpaGg4MDzZo1w8PDg8zMTBISEoiMjKzxh/X/giAIPH36FDMzMzIyMvjpp594/vw5np6eCi9cTU1NiouLad26dZ2c8/6/EIlElJaWsnXrVurXr4+xsbHinnj48CH79u1j5cqVSnHe1Ync7xCJRLx+/Zovv/yS4OBgOnfuTL169UhMTCQlJYUdO3Ywe/ZslbQn+iMqJ0wLFy6kvLyc0tJSCgoKsLW1xd3dnfr161O/fn2FdENV8/vqoFgsxtjYmNTUVIyNjbG3t8fPzw8PD486k2z/NxYvXkz9+vWJjIwkJCQEMzMzZDIZRUVFJCUlcfr0afbt26fU1aD/lc2bNxMUFERwcDD/+te/8PPzw8rKCj8/P/z9/dHX16/SJE5+VjMyMvj8888xMjJCW1ubdu3akZ2dzZ49ezhw4AC9evVS2s3O5ORkAgICePbsGbGxsZiZmTFlyhTs7OwoKiri1KlTtG/fvtZtN1fWBT137hxNmjThgw8+YP369ZSXl6Onp0dERARt27atte3UkydPsmHDBurVq8eKFSswNzdn8+bNFBcX4+/vj1gsRiwW07hxY6U9f9WNPLmvqKhAEAROnjypsMeTSwbZ2dnRv39/pdHVVCdy/0b+BwLQ1NTk0KFDvHnzhg4dOqClpcXLly+RyWSMGDFC5R52/w25WOn48eOxs7Pj888/p6KigkePHpGZmYm9vT0eHh7VlsTJYwIYO3YsYrGYyMhIrK2tefjwIUlJSRgYGODg4KBO4nh7rmNjY+nduzempqaKc56amsrq1asZOHAgvr6+9O/fHzs7u5oO9x8jbyHJP2diYiL379/n2LFjTJo0iZycHB49ekSHDh2qRRtL/lY/Z84c+vTpg5+fH7t27WL//v188cUXNG7cmO7duyutbZVUKuXkyZNER0djZWWFrq4uz58/x9raGgcHBywtLZHJZLi5uSmtTMr/hUgkIjs7my+//BJbW1tkMhmurq60bduWvXv3curUKdq2bVtr26nFxcW4urpSUFDAtm3b8PLyIjIykk6dOrF8+XIyMzMJCAgAUFrbt5pAJBJRWFjIggULcHJywszMjDVr1hAaGqq4M3R0dJRKW0+97MBvld43btzImTNn2LJlC9nZ2QrbqX79+vHZZ5/VGWN1+VAnQFFREU+ePOHFixcAdOrUCVdXV5KTkykuLq6RmACaNWvG1atXSUtLw87Ojs6dO6OhoaESchnvCrFYjJGREbdv31accwA7Ozvy8/MpLy/HxcVFIY5cWxEEgaSkJDQ1NcnIyOC7777jwIEDfPDBB8THx2NpaUlBQQGHDh0iLCysytvtlc+qtrY2ZWVlxMXFsWDBAoYNGwbA5cuXcXZ2VtqlAPnCkLOzM9u2bePy5csMHz4cHx8fDh06REJCAvXq1aN3795K+xn+LwRBQCaTsX79epo0aUJYWBg///wzQ4cO5dSpU8yZM4eNGzcqbav7z0hJSWH58uXcv38fS0tLwsPDuXLlCrdv38ba2pr169cTHx9PTk6OegHs31T+Pchb6jNmzEBHRwdDQ0Nu3LhRg9H9d9QVOd5m4JmZmUydOhVLS0uio6N59eoVM2fOZN26dTx8+JDg4OA6M2slHxKXyWTExcXx5s0bRowYwYYNG3jx4gWtWrWiYcOGeHh4VNsFXnk7dd26dVy/fp1u3bohFotZuXIlISEhODg40KRJk1qflLxrnj9/zuXLl/Hw8EBHRwdNTU1OnDjB+fPnef/995Vaq+yvcubMGdavX4+xsTGrV6/GysqKzZs3o62tzYwZM7h37x7JycmMGDECNze3Ko2l8ovhnj17KCgo4JNPPsHT0xMzMzMEQeD48eN89NFHSl3FklcTNTU1sba2prS0lHv37vHZZ59x+fJl0tPT8fHxqVUbjvJKrfyOg7cJ9fXr15k4cSKmpqYUFBTQvHnzWqsTJ5PJMDU15erVq0yaNAlvb28GDx5MUVERMTExmJub4+HhQa9evap8tKA2Ia/E7d69mxYtWlC/fn3u3LmDpaUl8fHxPHr0iO7duyvl76vOJ3KCICAIAitXriQwMJBu3bqRmJjIjRs3ePr0KcuWLcPV1bVOzQ/It5tGjhyJRCJh69at5OTkMHnyZJYvX87Lly+r3SRa3uKNjIzEwcGB0tJSli9fzrRp0ygqKmLFihX07t27ygfXawMpKSkYGhoqRgW8vLy4ceMGly9f5sSJE6SkpLBv3z4WLlyoNDMe/4TCwkI8PDwoLS1lx44duLi4EBkZyXvvvcf8+fPJz89n3LhxBAUFVUu7XSQSkZGRwbRp09DW1ubGjRukpaXh4+PD1atX2bdvHzNmzFDqOVv5nNCMGTO4e/cuQ4YMwdramgsXLnD48GHc3d3p0aNHrap+V06wZ86cSWZmJtbW1gwePBiZTEZSUhI//fQTn332Wa2a9auMfO7v1atXZGVlYWNjQ3x8PKGhoQQFBfHy5UvOnTtH69ata6212LtGntzLq/qPHj3iu+++o2PHjuTl5dGxY0c+++wz/P39lVaWqc4mcnLdKPmXWyKRIBKJWLt2LSNHjkQkEnHy5Ek6d+5cawdd/y75+floa2sjk8nYvXs3IpGIMWPGEBMTw5s3b3BwcODTTz/F2Ni42loOT548UVyq9+7d4969ewwbNox9+/bRvHlzUlJSGDp0KK1bt8bc3LzOX0xRUVHs27cPe3t7zMzMFMlcYGAglpaWmJmZYWBgwMCBA6vdRqYqeP78OWvWrMHQ0BCZTKaQ93BxccHZ2ZnOnTuzfv16wsLCqk0qSCaTsXLlStq0aUPXrl2Jj4/nxYsXJCcn88UXXxAWFlYz6u9/A7nkQmBgIAcPHuTevXt07NgRT09PHj58SERERK1rO8qdKCZPnoyfnx+5ubncuXMHIyMjTExMiIuLY8KECbVyO1WOSCQiLy+PCRMm4OnpyYgRI8jMzGT16tWUl5ejr6/Pxx9/XOVyO7UF+fM/LS2NtWvXcvfuXXr16oW9vT1XrlwhKiqK8vJy2rRpo7RJHNTBRE4QBDIzMzE2NiYtLY0lS5ZQWlqKo6Mjurq6SCQSioqKiI2NZcmSJXUmicvJyeHbb79FT0+P0tJSjI2NSUxM5Mcff2T48OGEhISwf/9+wsLCqs08XSaTsXPnTvbu3UteXh4uLi5cunSJH3/8kb59+9K5c2e2bNlCYGCg0j8YqwsvLy8SExNJSEjAxsbmN8mthYUFrq6uuLm5KfWl9FeRyWSYmJjw4MEDJk6ciIeHB5988gkVFRVER0ejr6+Pu7t7tbSQKutzyTUodXV1WbduHZ9//jnZ2dncvXuXoKAgpR+el0qljB07loqKCho3bkybNm34/vvvSUxMpFu3brVqAUAmk7F27Vq8vb3R1NQkLi4OFxcXunbtyuHDh8nPz+fOnTv4+PjQt29fpV06+TMqn78DBw7w+PFj/Pz8cHZ2pkWLFpSWlpKQkED37t2rdTFN2RGJROTk5DBlyhS6d+9OXl4ea9asYdCgQXTq1Ing4GCaNGmi9OeiziVyhw8fZvjw4QQFBbF+/XpMTEw4f/68orQaFxfH5cuXmTBhQp3aTtXV1aWwsJCRI0cCEBERwS+//IKhoSEuLi4sWbKEnj17Vtvbqly2wdfXl9mzZ/P48WOGDRtGamoqeXl5mJiYsG7dOgYMGEDjxo2rJabaQF5eHgcPHuTZs2fcu3cPe3t7LCwsVO7tu7J0RGpqKm5ubkRHR9OqVStCQkJ49eoV586dIzAwsMpbSJXN448cOUJeXh729vbIZDKMjIzQ0tLi5MmTzJs3T2lfDOWJgCAIaGpqYmBgwI4dO9DR0cHT01MhWty+fftaM1Mpk8mYPHkyWlpahIaGKhLsV69esXnzZhYsWEB+fj5ZWVl06NCh1o7PyOf9CgoKyMzMxMrKCqlUSlZWFuXl5djZ2eHj40Pbtm3V88O8fbasX78eZ2dndHV1uXnzJrm5uQQEBLB//37ef/997t69i6urKzY2NkqfxEEdTOQ8PDzQ0NBg6tSpBAYGMn78eNzc3Dh58iSmpqb06NGD/v3715kKT+X5AHg7H3f69GlCQkKIiIigoqKCxMREPvjgA0JCQqo1prKyMoqKinB2diYpKYk7d+4wZswY6tevj56eHiEhIQQFBf3GuaEuU1ZWxpw5cwgLC2Pq1KmkpKQQGxuLtbU15ubmijarKiBvIU2ZMgU3NzeGDRtGaWkpy5Yto6SkBIlEwmeffVYtLaTK5vHe3t78+OOPlJaWYmRkxE8//cSVK1eYMmWK0r4YVk6KFy1aRFJSEoIg8N577zF37lwePHjApUuXmD9/fq3ZTpXJZEybNg1LS0siIyOBt0sNPj4+GBgYEBcXh46ODjt27ODrr7+utbOi8hfetLQ0Jk6cyPnz50lPT1ck20lJSejo6GBtba30tm/VhUgkYsuWLVy9epWWLVsikUiIjY1l586dTJ48GXNzcw4fPkzHjh3R0tKq6XD/EnUmkausE9e8eXP09fXZsGED4eHhuLi4UL9+fc6cOVOr38z+LpW3U7/77jtcXV15//33sbS0ZPz48TRo0ID69evz4YcfVpvGWOXt1EmTJqGjo0P79u3p1asX69ev58SJE7x+/ZqBAwcqZnTqchJX+VzLZDJOnDiBpaUlXl5e+Pv7s3HjRoqKimjRooVKaEVVbiEdOXKEBw8e4OPjg5ubGz4+PmhpaXHjxg169OhRrUnH0aNH8fT0pF+/fuzduxcbGxsCAgIYNGgQXbt2Vep5MnkiOmHCBJo2bYq3tzcbN27E0tKSQYMGkZ6ezogRI5R6OeP3fPHFFxQXFzN//nzgrYXf7du3adu2rWJs5N69e0ycOFEplPn/F7KystDX16e0tJSZM2cSERHBuHHjyMzM5MWLF3To0IH8/HxatWpVa6qo1UWXLl2IiYkhNjaW4OBgcnNzFW3WvXv3MmHCBKX+zv6eOpHIVd5WWrJkCc+ePaNPnz6Ympoyd+5cgoODadiwIUFBQUol8lfVyCtx48aNw8TEBAMDAyoqKvD29qZx48b8+OOPBAYGVqtQrLy989VXX+Hj44O9vT2JiYnk5OQwZswYbt26RZs2bVRCvPafIj/XWVlZXLlyBU1NTZo2bcq+ffsoKioiOzubBw8e8MUXX9SK9sCfIX/xyM/PJzU1FRsbG0WrrKSkBAcHB7y8vGjTpk21tZDkiXR+fj7r168nKiqKDRs2IJVKOXToEKGhoUr7EC0rK6OkpAQtLS2uXbtGRUUFo0aNws7ODkdHR65fv06PHj3w9/evVVucZWVl5Ofnk5+fj62tLfv37yc5OZk5c+Yg/yzbqwAAIABJREFUFou5ePEi4eHhdOnSpda2Gn/66Sdu3bqFlZUVBgYG/PLLL3Ts2JH69evj6enJ1q1bCQ0NpW3btkp7/qoTuTKF/L6wsrKiXbt2xMfH8+DBA3r37k3jxo3R1dWld+/etS65rxO1VnnbYObMmfj6+pKens6CBQuYMWMGZWVljBkzhr1799aZ0nPlVmR8fDyZmZmMHz+eWbNm4eXlpTDFbtq0abXpXFX2c83MzOTNmzfY2tqyadMm/Pz8iIuLo0mTJkydOvU/PkNdpLJ/51dffYW5uTkSiQRfX1+GDBnC9u3b0dTUVDhyqAJisZj09HSmTZuGRCLB0dERCwsLJBIJ586dQyKREBAQUOXtkAcPHuDu7s6rV69YtmwZbm5uuLi40L59e+Lj4zl//jwbNmxg+fLlStmakclkTJgwAQ0NDV6/fs26deuQSqVcvnxZ8W+Sk5NJS0tTGKvXJiQSCb1798bQ0FBR1d+1axfwtoq7ceNGVq1aVauS09/j4ODA+fPnOX36NJ06dSIsLIyDBw+iqalJbm4uhYWFSq1RWN1cunSJY8eOceTIEUQiEY0aNaKkpARPT082btzI3bt3WbVqVZVrTFYVKl2Rk0uMwNtNHjc3N8LDwzl9+jTFxcUcPnyYMWPG0LNnz2qTJqhpKrfi4O2l/ubNG65fv07Xrl1xc3Pj8uXL1SrXIH9YCIJAamoqgiCgra1NaWkpLVu2xM/Pj6ioKMLCwhSXU134W/035J7AmzZtwt/fnwkTJqClpcXly5cxNjZm1KhRKjPcnJ6ejoGBAVKplNmzZ9OlSxfGjRtHbm4uKSkpdO7cmaKiIlq2bFnlpt+13TxeEAQmTJiAo6Mj06dPp1OnTkgkEpydnXn48CGrV68mJyeHEydOMGXKlFq7KKOpqYmzszPa2trk5OTg7e3NjRs32LlzJwsWLKhVbeI/wsHBASMjIy5dusTr169p0KABEomEHTt2cOfOHSZNmlTrP+O7xNbWlnr16mFhYUFYWBgff/wx9erVw8TEBF1dXdLS0ggJCam12/wqWYKSD7q+fv0aY2NjFi5cSMOGDRWWW9OmTSMmJoZff/2VgoKCWtUL/yeUl5ejqampmD8TBIE+ffrw+eefc/v2bZ4+faqQS6hOVfPKMWlra2Nubk6TJk2wtbXl6tWrLF++nMjISPXaPL+tXCYlJZGYmIipqSmlpaUEBARQWlrKr7/+SmhoqEq8ke/YsYO8vDwiIiKwtbWltLRUsfkZERHBkSNHEASBDz/8sMpjSU5Opnv37mRlZbFnzx4sLCwYO3Ysr169QldXl4MHDzJu3Dg+/fTTKo/lf+Xs2bOYmZkxevRoAObOncvLly/JyclhzZo1BAQEUFFRQadOnWq9zqCWlhYRERFoa2szcuRIBEFg1apVSrt08mcMGzYMmUyGh4cHzZs3x8XFBV9fX1JSUpDJZISHh9OjRw8qKipU4rv/runUqRMFBQU8fPgQfX192rZti5aWFp07d67p0P4xKleRkxu829vbM2fOHPz8/NDR0cHCwgJdXV1evnyJIAhERUUxd+7cWrut9L8gn4kbO3Ysfn5+6Ovrc/jwYezs7BQboqGhodW2nXrx4kXs7OyQyWTMmTMHLy8v3nvvPTZv3ky9evWwtLTE3t6e4OBgWrZsWS0xKTOVVdtPnTpFs2bN8Pb25vTp02hra2NnZ4eLiwutWrVSmYu8tLSUpKQkMjIysLS0RFdXl4sXL6Kvr09KSgpnz56lZ8+eVf55VcU8vqSkhK1bt3Lnzh2OHTtGSkoKy5Yt482bN1y4cIGPP/4YFxeXWqMT92doamri4OCAoaEhgwcPVsoq6V+hoqKCrKwsrl69yqtXrzAxMeH777/n+fPnnD17lmPHjmFhYYGfn1+ttRZ71+zcuRMtLS2Flqa8pZqRkcH9+/fJzs7GyclJJUaqVC6RO3v2LCUlJXz55ZcALFmyhJ9//pmTJ0/i6+tLXFwcjx49IjIystZ+qf8umzZtQiqVYmtry+3bt8nKymL48OHExMRQVlbGsWPHcHZ2JiIiotrewp8/f86XX36Jk5MTjo6OXLp0iUaNGvHTTz/RvXt3JBIJgiDg5+enrsT9G7kn8OjRoykpKWHevHl89tlnODs7s337doyNjXF1dVXKuaz/FRsbGywsLLh06RJ5eXmYm5tjaGhIVFQU9+7dq5YWklxb7c2bNyxYsABdXV0mTZpEeno6V65cwcDAADc3Nzw9PZV+493CwgJbW1tKSkrw8/Nj0qRJ6Ovrk5ubS3p6OkFBQSolUwNvkzkPD49avfCjoaFB48aNMTc35/Xr1/Tq1YsRI0YQGhqKn58fjRo1IiQkRGUS8H9KcXExBw4cICUlReFoAyiSuWfPnils81ThvlS5RC41NZX169cjlUrZuXMnjx8/ZtasWVy9elUx5BsWFlZr9JD+KYsXLyY1NZVPPvkEgHr16pGamsr+/fuJiIigS5cu/PLLL3zwwQfVJlZaXl6Oqakptra27Nq1i8DAQPLy8pg4cSJdunShe/fuLFq0iJCQkGpzkagNlJaWsmDBAvr27cunn37KsWPH+OGHH+jbty+2trZ4eXkpdTXorzJixAj+9a9/cefOHYqKijA1NcXAwIAXL15QUlJChw4d6NGjB23btq0WvUdVM493cHBQVG5yc3O5cOECO3fu5IsvvsDCwqKmw6sSauOc3+8Ri8XY2tpSXFzM7t27MTExwcXFBSsrK7y9vdVJ3L8pKytDW1sbNzc3Nm/ezJMnTxRVZvk58Pb2xsvLS+lfvP4qKpfI2dvbIwgCb968wcvLi5kzZ2JiYkJZWRnPnz+nRYsWtebC/acsXLjwN1pKFy9eRFdXlxYtWnDhwgWuXLmiuMD9/PyqJaZly5Zx//59HB0d8fLyIj09HalUSteuXdHS0uLKlSucOnWKjz76iODg4GqJqbYgrwoVFxezadMmFi9ezN27dzl79iwjR46stYO6lSkrK1Ms3+Tm5mJlZcWGDRt4/vw58fHxHDt2DCMjI1q0aFEtb9KqaB4Pb1vFx48fZ8uWLTx8+FAhrKxGuZFIJDg5OSGTydi1axfW1tZ1Zsb7ryKXZJowYQIRERE8f/6ctLQ0LC0tf7OprEotaJEgl/RXAX4vSfHkyRNsbGw4deoUO3fuZM6cObXaEPnvsHXrVvbv38+OHTvQ19fn559/5vjx46xYsQJzc3OSkpLYv38/wcHBtG7dulpikslk9OzZE7FYjL6+PpGRkVy5coWXL18yffp0xGIxOTk5SCQSlXlTelfI5+MKCws5c+YM2dnZeHh4sH37diZOnFhrB7j/iDdv3nDx4kWio6MZMGAA3t7elJSU8PDhQ5KTk2nWrFm1beRJpVK0tLQoKipi8uTJ2NjYMHr0aF69esW2bdsYOHBgrd0OlEqlVFRUqIfjayHFxcXExMTg5+dXZ7pLf4fo6GhiY2OZO3cupaWlzJkzh6KiIkaPHq2SI1UqVZGTS2skJyeTnp5OfHw833zzDffv32fmzJm4urrWdIjVxsuXL9HS0kJTU5MzZ85w4cIFZs2ahaWlJbdu3SIpKYmhQ4cqKphV3XqQJyK2trZ4enri7u7OjRs3EIlEnD59mtzcXIUCuSq9Kf2v/F4mRi6UrK2tTVZWFvHx8ezZs4e5c+eqxMvJ8+fPFRVF+YAyQFRUlKJN0qBBAxo2bFhtLSRVMo//I8RiMRKJRCVmhOoaEolE6RdrqpPKto7yc71p0ybFDHZhYSE3btzgvffeU0mB5FqdyMn/ePL2h4aGBjdv3mTZsmW0bNmSTp060bZtW7p3715nvFPluLm5kZ+fT0xMDDExMcycORNnZ2euXbvG8uXLadu2rUIotqqTuA0bNpCVlYWuri42NjZs2rSJrl270qlTJ0xMTEhKSiI7O5vAwECV/JL9XSo7kRw5coSMjAycnZ0VfydLS0tatWpFz549VWKG8MCBA5w6dQpra2vFULLcH1JLS4uoqCjMzMywt7ev8lhU0TxejWqiCnN/74LK9+XEiRMV8iItW7Zk6dKlPHnyhGPHjrFw4UKVzQNqZSInCALXrl3D1taWjIwMNm3axM2bN9HX12fTpk30798ff39/RCIRenp6deaN8+XLl+jp6SkqOW5ubgrJEWtrax4/fszGjRsZOnQogYGB1RaXRCLhypUrxMTEYGNjg5+fH9988w2tWrXCycmJgIAAfHx8VCIpeReIRCIyMjKYOnUqIpGI27dv8/LlS3x8fBQ/19PTq3Lx2+pCR0eHZ8+ecffu3d/MsWhpadGgQQNMTExo1KhRlVcfVNE8Xo0aVUckEpGfn8/y5ctxd3fHysqK2NhY3N3d+fjjjzEzM6Nv377V8iJYU9TKRO7GjRtMnToVIyMjtm3bhpOTE8nJyeTl5dGrVy98fX1/Y65dFzhx4gQ7duzAwcFBoZsD4OTkRGFhISdPnmTXrl189dVXBAUFVWtsDRo0wMfHBxMTE+bOnYujoyNlZWXo6uri5OSEnp6eopWm5m2lefny5bRv357w8HDi4+NJTU0lKSmJgIAAlTnXlb+jUVFRpKWl8erVK8zMzBTbk9ra2jg7O1dLC0kVzePVqFF1SktLWbx4MRoaGkycOFEhobV3714cHBwICAiodctIf5dal8gJgoCVlRX29vasW7eOevXqMXHiRIKDgzl8+DB5eXn4+vqqzMPur+Lq6sqdO3dISEjAysrqN8mcvDLXs2dP/P39ayQ+iUSCnZ0drVu35saNG1y+fJkzZ87Qv3//Ove3+iPkYwJSqRSJREJ5eTl6enr88MMPDBs2jIyMDO7du0dQUJDKVOJEIhFv3rxh+PDhRERE0LlzZ16/fs2tW7ewsLD4jfZTVaKq5vFq1Kgqle9LbW1tSkpKuH37Nvr6+tjb22Nra4uBgQGenp51Yo6w1kkai0QiCgsLqVevHpMmTWLWrFmcOXOGtm3b4uPjQ2pqKhUVFbXO6PldkJOTw507d8jKymLkyJE0bNhQ0WYNCwur4eje4uDgwKeffkr//v159OiRyomP/i/Iz2tGRgazZ8+mY8eOODg4IJVKCQsLIz8/n+TkZObNm6cSlcvKNmMaGhrY29vTo0cP4G07denSpUgkEhwcHKpUKkjVzePVqFFF5DNx6enpLF68mLKyMhYsWIBEIuHYsWOUl5cTEhJChw4d6kyRoNY9RSsqKjh27Bi7du3CwMCA+fPns2rVKqZMmcLx48eJiIiokxfuwoULsbS0ZN++fXh6erJz507u379PRUVFTYf2H0gkEoyNjfH19a3pUJQCsVhMbm6uwjrN09OTZs2acfPmTf71r3+xcuVKxo4dqxKDuvIkLj8/n4cPH6Krq4uGhgajRo0C4MWLF+jr69O7d+8qTeIqm8cvXbqUNWvWIBaLad++PU2bNuWDDz5g/fr1HDp0iNGjR6OpqVlnHgpq1CgzGhoa5OTkMGvWLHr27ImZmRkDBw6kVatWtGrVinPnziGVSuvU97VW6MjJL3955SIlJYX4+HjS09Pp1q0bWVlZbN26lZkzZ9aZ+ZXKVcfy8nLmzJlDo0aN6NevHwCDBg3CycmJCRMm1InScm1k7ty5fPLJJ9ja2vL48WO2bNnCnDlzEASB5ORkrl+/rjB0VgVdPfn3WG4RZ25ujlgs5vvvvycyMhJNTU2Sk5NZvHhxlUuqxMXFce7cOaZNmwbAjBkzfmMe/+DBAyoqKnB1da315vFq1Kgav/zyC0+fPqV///5s2rSJ5ORk7ty5w86dOzE2Nlb5mbjfo/QzcpXnV2bOnImNjQ2urq6YmZlx9epVrl69SosWLRg0aJBKtJ3+CvLSsnx7V0tLCw8PD/bs2UNFRQV6enrEx8fz4Ycfqh9CSoyXlxcmJiYkJCRgb2/P5s2b8fT0pEGDBsTGxnL69GkiIiJUaiauoKCAZcuW8d577xEZGUl8fDyHDx9mxYoVdOzYkS5dulSLt25dM49Xo0aVsLS0pKCggI0bNzJixAg8PT25fPky7733Xp3JAyqjtImcTCZj/PjxxMTEcOjQISIiIrh69SqnT5/Gw8MDR0dHUlJSKC4uJiwsTCUqFn8FeVVDEARGjRrFhQsXSEhIQCQSERYWxs6dO7l8+TIffPBBtTk2qPl7lJeXK8Qrd+/ezbRp0wgLC6Nhw4YsX76cx48fK7T/VMH7svJ2anR0NOfPn8fV1ZVGjRrRoUMHjh07xqFDh+jWrRsSiaRaWiJ10TxejZrayO8F6wVBQEdHB0dHR4Uk0JEjR1i8eLFCG7WuoZStVUEQGD9+PI6OjowePZqSkhJ0dHSAt9ZT8fHxuLu7k5CQwLJly+qc/pggCGzatAmpVMrIkSOJiYnhzJkzBAUF0alTJ0pLS9XuCErOq1evGDNmDEuXLuXx48fMnDmTb7/9FhsbG7KzszEwMFAJD0X5i0dOTg4ZGRmYmppy8eJF7t69S8uWLWnfvj0AmZmZ1K9fv9rjEwRBsSB19+5dfv75Z2bOnKn2HVWjRgmQ3x8lJSXIZDJFd6KiooKSkhLOnDnDjRs36NevX51ybvo9Srm1evbsWczMzBg9ejQA8+fP5+XLl2RnZ7NmzRocHR1JTU2lV69edSaJqzwTl5iYyJkzZwgODqasrIyAgADKyso4deoUzZo1q5EHopo/R/5mKQgCBw8e5MWLFzRo0AArKyumT5/O4MGDWbFiBaGhoTUd6jtBEAQ0NDTIyMhg0qRJlJaWEhoaSlBQECKRiLi4OEQiEe3atauxMyuVSomPjyc6OhpNTU11EqdGjZJQeZt/4sSJNGzYEHt7ez788EOFX3e3bt3o2rVrnVps+COUsiJ3//59Jk2ahLe3N6WlpaSmprJy5Up27dpFTk4OX3/9dU2HWK1UbqeePXuW5s2b8/jxY7Zt20a3bt0ICAhAQ0ODgoKCOjkfUBuQ/w3fvHmDvr4+d+7c4cSJE2RnZzN+/HjMzMw4f/48tra2KrWwU1RUxLRp0xg4cCASiYTJkyfTpUsX/P39yczMJDAwsMbPrNo8Xo0a5SQnJ4fx48fTo0cPZDIZx44dIzw8XCFXpOYtSjkj92fzK61bt65T8ysikQiZTMbIkSN5+PAhS5cu5dNPP8XBwYGff/4ZHR0d3NzcVGYoXtWoXJmaOHEiqampXLt2jdDQUMrLy9m3bx8tW7bE3d1d5YbrX79+zdOnT3FxcSEqKooBAwawefNmzM3NiYiIUIrPqzaPV6NGeZg7dy6urq4YGRnx4MED9PT0CAgI4ODBg1hZWXHq1CmKiooUloVqlFhHLjg4WLGNkpKSwtGjR9mxYwd9+/atkzpxixYtIigoiJUrV2JnZ0evXr0wMzOja9eu2Nvb1/nSsjIjdzCIjIxk4MCBuLi48ODBAx4/fkxgYCCurq6UlZXVdJjvhJKSkt/8v4WFBeHh4Zw7d45OnTrh5uZGvXr16NKli7r6pUaNGgWCIJCUlMSkSZMUqhReXl40aNCAtWvX8tVXX+Hn54erq6vSCNwrC0pZkZMjlUo5fvw4W7Zs4eHDh0yZMqVOza9U3vbLzs7G0NCQ7du388UXX5CZmcmuXbsYM2aMSgzFqyK/9/tNSUmhVatWfPfdd3z22WeUlpbi4eFBcHCwSmxdP3nyhIsXL2JoaEhFRYViQcnCwoIXL16wfPlyYmJimDdvnloWR40aNb/h1q1bjB07FmtrazQ0NBg4cCAtWrQgJCSEw4cPk5GRwbZt25g5cyb29vY1Ha5SoZQzcpWpi/Mr0dHRtGvXDngrVaGpqUleXh4XLlzgyZMndO3alcWLF/PRRx8RGBhYw9Gq+SPkM3GvX78mOTmZ5s2bM3jwYIVbQ2FhIfPmzWPdunU0aNCgpsN9J2RkZPDdd9+RmJjI9OnT8ff3/42Yd0JCAtbW1tjY2NR0qGrUqFFCzp8/z+rVq5k6dSqCIDBu3DhWrlxJfn4+iYmJdOzYscrFwmsjSl2Rg7o3v5Kamsq2bdt4+PAhLVq0UCw56OrqUlhYyPnz51m3bh2jRo0iODj4PzR21NQ88pk4uedtXFwct27d4ptvvuHcuXMUFBSwe/duldE9klceDQwMOH/+PHl5eRgaGuLk5ISuri7w1lbHxsamzimuq1Gj5r9TUVGBhoYG5eXlODo6YmNjw7JlywgMDKRz584MGTKEHj160L17d8zMzGo6XKVE6StydY2ysjLu379PVFQU9evXV3hQwtv5o7y8PN68eaN+K1FSKuse7dmzB0tLS9q3b0+/fv3w8fFh8uTJFBUVUVJSohKXklwiICsri3v37tG6dWuSk5P55ZdfMDMzw9PTE2dnZ+rVq1fToapRo0bJkN+XGRkZzJ8/n+bNm+Pt7Y1MJuPbb79lzJgx6OjoYGxsrFLb/O8apV12qGvIze0lEgne3t706dOHvLw8Vq9erfg32traWFpaqpM4JUX+ZpmZmcmYMWM4cOAAt27dAuBf//oX58+fZ9q0aejp6alEEgcodJ7GjBnDnTt3iI2NxdXVFX9/fzIyMli8eHGd2jBXo0bNX0feuZg0aRLNmzcnNzeXw4cPY2BgwOjRo1m/fj3u7u7qJO5PUFfklAD5W4lMJmPChAk4ODjg7e2NqakpR48eRUtLi/Hjx9d0mGr+Ajk5OcyfP5/OnTvj4uLCyJEj6devH4MHDwbgxYsXKjUjVlFRoXBXad++PfPnz8fCwoI+ffrg5uZGfn6+yiStatSoeTfIn3lSqZSLFy/y6tUr2rVrx+zZsykrK0MkEtG/f3+aNWumWJpS83+jflVWAip7p3p4eCCTyYiJiaG4uJiOHTtSUlJCSkpKTYep5i+QmJhIbGwspqamODs7s2bNGn744Qe2b98OoBJJnLx6LJPJEIvFlJeX8+jRI+bPn09kZCRSqZSEhAQ0NTXVSZwaNWp+Q+UZ4g0bNigSt1mzZjF//nwCAgLQ0dHByclJncT9RZR+2UGVkbfi4G0CUF5ezvDhwzl58iRpaWncvXsXQ0NDPvzwQywtLWs4WjW/RxAEVq1aRUZGBg0bNqS8vBwXFxd0dHTYunUrrq6ueHl50aZNG5ydnTE2Nq7pkP8xlW1zNm7cSFJSEl9++SX+/v4KfceTJ08yZMgQlfi8atSoeXcUFxcjkUgoLCxkyJAhtGvXjk6dOmFgYEB0dDRaWlrs2LGDGTNm1Bn7zXeBUnqt1gUEQUAsFiOTydiwYQPe3t5IJBLmzp3LwIEDKSoqYtmyZfj4+KgfiErKzZs32b9/P1paWjx48ICioiJGjBjBgAEDsLW1ZerUqSxevJgmTZrUdKjvDPliw9SpU+nUqROHDx8mKSmJhQsX8urVKy5cuMC0adNUYhtXjRo174779+8rXnrLysrQ0NAgISGBLl26YGdnh52dHefPn2fRokXqmbi/iXpGrgaQa8NVVFQwdepUJBIJ8+bNo6CggOnTp+Pl5cXJkycZM2YMwcHBNR2umv/Cnj170NTUpE2bNkyePJknT54QGhqKq6srBgYGNGnSpNa/WcpkMqKjo2ndujV6enp8++231K9fn549e/Ltt99y9epVHB0dWbZsGeXl5UgkkpoOWY0aNUpGYWEhw4YN4+7du6xatQoXFxfmzJmDu7s7kZGRwFvd2LoiNfYuUc/IVTNPnz5ly5YtSKVSbt++jZmZGS9evCA3NxdDQ0N69OjBvXv3+Oqrr9RJXC2gtLSUmzdv8vr1a7S0tBgyZAhNmjRhy5YttGrVSiWSuLFjx3Lr1i2Fl2+HDh3Q19cnMjKSQYMGMWDAAO7du0d2drY6iVOjRs1vkMlkABgYGPD+++/j6urK8+fPsbS0ZNasWdy8eZNVq1YBqJO4/xF1Ra4GmDJlCkePHuWLL77go48+Yt26dbx+/ZrPP/8cS0tL9VtJLeOjjz4iLS2N+fPn07JlS0A13ixlMhmTJ0/GysqKsWPHAvD8+XPs7Ox4/vw5v/zyC0ZGRsTFxTFjxgx1O1WNGjW/Qb6dmpmZyfXr1/Hw8MDExISJEyfSunVrnJycqF+/PqampirjcFMTqCty1YR80w+gR48e+Pv7c/nyZbS1tRk+fDimpqasWLECqVSKpqZ6dLE2IP+b9urVi44dO9KyZUsqKioQBKHWV6YEQWDo0KHY29srkrglS5bwzTffIAgCMpmM/Px8zpw5Q2RkpDqJU6NGzX8g304dM2YM2dnZpKSkYGBgwNKlS7l37x5r167F0NBQncT9Q9QVuWqgsk7c8ePHsbe3p3HjxsybN4+UlBRGjBhBTk4O3t7eWFlZ1XS4av4A+bbmH1miPX36lIEDB7JkyRICAgJqKMJ3i0wmo1+/fjRv3pzJkyezZs0anjx5wqJFi5BIJCQnJ1NeXo6Tk1OtrzyqUaPm3VL5nlywYAEAn3zyCbNmzUIqldK1a1ciIiKQSqUYGhrWZKgqgTqRq2LkSZwgCEycOJG0tDQcHBzw8fGhT58+LF++nEuXLvHVV18RGBhY0+Gq+QPkf8OsrCyioqJo1qyZImGT/+zAgQP4+vqqRGVK/pnKy8sZPHgwBQUFuLu7s3TpUgAOHjzI/v37Wbp0qdp6S40aNX9IYWEhGRkZZGVlsXPnTvT19Rk9ejQJCQnk5uby0Ucf1XSIKoM6kasG5HpjBgYGfPrpp8TGxnLlyhVsbGwYMGAAeXl5mJiY1HSYav4LOTk5TJ48GUtLS86fP8/YsWPp1q2b4ud/VKmrzcgrkOXl5Xz55ZeYmZkxb948Tpw4we7du5k6daraKk6NGjV/iEwmY+/evdy+fZvu3bvTrFkzTp06RW5uLrt372bZsmU4OzvXdJgqg3oYq4qQPwgBMjMziY+Pp3nz5gC0bt2asrIyrly5wsuXL7G2tq7JUNX8Hxw9epSwsDDg7YJKq1atGDJkCBcvXmTt2rVIpVLef/99AJVI4iono2KxmLKyMiQSCatWreKTTz66a+JfAAAMaElEQVShd+/eGBsbM23aNPUlrEaNmt9QWVZLLBbj5+dHaWkpp0+fpry8HCsrK86fP8/SpUvV98c7Ru3sUAXIrYtkMhlxcXGIxWIiIiLYt28fRUVFNG3aFCcnJ7y8vNRDnkrKixcvALCysiIzM5PMzEyOHj1K586dcXd3x9zcnKioKNq1a6cSM2Jyl5GSkhIKCgrQ1dVVnGGxWEz37t1JSEhg7Nix6kqcGjVq/gP5HPj06dOxs7PD1dUVU1NTEhISuHPnDi1btqRnz56Ym5vXdKgqhzqRe8fI54sqKioYOnQoEomEH374AS0tLXr27MmmTZsoKCigefPmCl0uNcrFtWvX8PDwwNramoMHDxITE8OgQYMQiURs376dVq1a0ahRIzp27Ii+vn5Nh/uPkXsfpqWlMWHCBK5fv86vv/5Ko0aN0NfXV1TmOnTooPZOVaNGzW8YPnw4iYmJZGVl4erqysOHD4mOjsbV1RVHR0ceP35McXExQUFBKnFfKiNq+ZF3jFz88MCBA3h7ezNy5EjMzMxISkpCW1ubJUuW4OvrW8NRqvlvPH78mE6dOjFr1izMzc3R1dVl9+7dhIeH4+3tzezZs5HJZGhra9d0qP+Yly9fIhKJKCoqYv78+QqLsZiYGM6cOQNQ66VU1KhRUzUUFhYiFouRSqXk5OQwfPhwnJ2dyc3NZevWrSxZsoTjx48zePBgLCwsajpclUW97PCOWL9+Penp6VhaWjJ8+HAuXbrEtm3byMvLY/z48Whra7Nr1y6mTZumEq04VUReTQWIiIiguLiY06dP8+zZM/bu3YtUKuXDDz/EwMBAJZZTdu3aRXp6Ot27d8fGxobZs2cTGBjIoUOHGDlyJGfPnqVdu3Y0atSopkNV8//au7+Yqus/juPPc07mUY8jOcmZcTQLEJnjNFBPJ6FaWBAjKHXEhjlsZeZqoZNYBoSbNYW1zLxAZ2UsJRrmRK1AQTPbqKaTybxAGsRY/AnnRiInOHjO78JBP1frVz+R4zm8HlfwPdt37+/da5/P+/P+iNymTp06xSeffMLevXv54IMPOHnyJD6fj8HBQVJTU0lLS1M7xi2mFbkxUFpaSltbG0uWLMHpdAJgs9kICwtjypQpXLlyhaKiIpKSkhTiblMjIa6/v5/BwUHef/990tPTWb58OXPmzMHpdHLvvfcyderUgA9xPp+PxsZGYmJi8Hq9HD9+nNbWVubOncvOnTtJTU3FbDZz+vRp9bOIyN9auHAhDoeDQ4cO0dLSQnFxMZ9++ikZGRnk5OQoxI0DrcjdpNraWurr6yktLb3heUtLC83Nzdxxxx2cO3eOxx57DJfL5acq5e+MhLienh7y8vKIiooiMTGRpKQk3nnnHerr64mLi6OgoCAoesSamprIy8ujoKAAq9VKTU0NVquVkJAQenp66O7uprOzk40bNxIdHe3vckXkNrd9+3bKy8v58MMPWbRoEXDj5Aa5tTR+5CZ5PB7mz58P/HHyz+PxUFtbi81mIzMzk6VLl6rP6DZmNBpHt8BzcnL46aefOHjwIJMnT6agoIDFixcTExMTFCHO4/EQGxvLxo0bKS0tZf369aSlpfH1119jMplwuVxERkYyNDQUFN8rIrfOyMii1157jd7e3tHDDD6fTyFuHGlr9SbNmjWLs2fP0tbWNnqF05133onBYMDtdgOM9l3J7au9vZ3HH38cl8tFR0cHFouFsrIyqqqqSE5ODoobG+D6wYXu7m6OHj1KfHw8JSUl9Pb2kpqaSnt7O42NjUydOlUhTkT+J4PBMHr38vDwMN9///3ocxk/Gj9yk+666y7a29v55ZdfsFgs3H333TQ1NbF3715WrFjBPffcoyAXAKZNm0ZrayuHDx+moKCAkJAQmpubycnJwWKx+Lu8m1ZdXU1ISAjTp09n9+7d2O12Xn/9debPn8/WrVuJiopiyZIlxMfHa0SAiPxjBoMBk8nE/fffT0RERMD3EAci9ciNga6uLr788kvq6upYtGgRP/74I7m5uSQkJPi7NPkLO3fu5IEHHuCRRx4B/ujlGBwc5NVXXyU0NJSLFy/y7rvvBkWj7oULFzhy5AihoaGsWrWK2tpavvvuOzZv3ozFYuHtt9+mubmZPXv2YDab/V2uiIj8CwpyY8Tn89HW1obH48FkMhEZGenvkuQvDA0N8cUXX3DmzBkyMzNxuVx4vd7Rno7z589TV1fHsmXLuO+++/xd7pg5ceIEhw8fZsGCBTidTn744QdaWlqIi4ujvr6e4uJi5syZ4+8yRUTkX1KQkwnn999/p6amhm+++YasrCweeughAKqqqujr6yMnJyeoDqdcunSJwsJCwsLCMBgM2Gw2nE4nHR0ddHV1kZKSEhQrjyIiE5FOrcqEYzabefLJJ4HrQ3GtVivd3d1UVVWxZcuWgA9xPp+P8vJyVq9eDUBFRQULFy5kzZo1nD17luPHj9PQ0MALL7yga+JERAKcgpxMSCNhzmg0kpeXh9vtZteuXUGxMmUwGIiKisLtdjNlyhRmzJhBZ2cncH14Z01NDZ2dnQwODirIiYgEOG2tyoQ2ss0aGxsb8CHO5/ORl5dHbGwsq1ev5q233uLy5cu89957ZGdnEx8fT0REBDU1NWzZsgW73e7vkkVE5CYpyMmENzLUMtD99ttvLF++nGnTppGVlUV2djZr165l9uzZ5Ofns3//fgYGBkhOTiYqKsrf5YqIyBhQkBMJInV1dZw5cwaDwUBYWBjPP/88a9euxWw2s2PHDn+XJyIiY0yTakUCmM/n4/Lly6P/z5w5k59//hmn08mlS5fYt28fu3fvxmg00t3d7cdKRUTkVtCKnEgAe+6557h69SpPPPEEL7/8Mkajka+++orW1lZcLheVlZUsXryYrKwsf5cqIiK3gE6tigSoa9eukZSURH19PQcOHKC/v58ZM2YQHh6O3W4nLi4Oi8Wie1NFRIKYgpxIgDKZTKxcuZLw8HBOnTrF9OnTmTdvHtu3b6e3t5erV6+ycuVKf5cpIiK3kLZWRQLcwMAA9fX1nDhxgnXr1hEaGkpdXR0JCQnMnj3b3+WJiMgtpCAnEgRG5uEdOXKE3NxcHA6Hv0sSEZFxoK1VkSBgNptJSUlh0qRJ2Gw2f5cjIiLjRCtyIkEkWIYbi4jIP6M5ciJBRCFORGRiUZATERERCVAKciIiIiIBSkFOREREJEDp1KqIBKzo6GjmzZuH0WjEYDDgdruxWCxs3ryZ2NjY/+udPT095ObmUllZOcbVioiMPZ1aFZGAFR0dTUNDww3XkH300UccO3aMzz//3I+ViYiMD63IiUjQGB4epquri5CQkNFnZWVlHDt2DK/XS3h4OMXFxdhsNtrb23nzzTfp6+tj5syZ+Hw+MjIycDqdpKenc+7cOTweD9u2baOhoQGTyYTD4WDTpk1YLBaSkpJYtmwZDQ0NdHV18fTTT7N+/Xo/fr2ITETqkRORgJaTk0N6ejqJiYmkpKQAsHXrVgAOHTrExYsXqaqqorq6mkcffZTCwkIA8vPzSUtL4+jRoxQWFtLY2Pind5eVlfHrr79SXV1NdXU1Xq+X0tLS0d8HBgaoqKigsrKSjz/+mI6OjnH4YhGRP2hFTkQCWnl5OaGhoVy4cIGXXnqJBx98EKvVCsDJkydpampixYoVAHi9XtxuN319fZw/f559+/YBEBERgcvl+tO7v/32WzZs2MCkSZMAWLVqFa+88sro70uXLgXAZrNhtVrp6+vT/bYiMq4U5EQkKCxYsIBNmzbxxhtvEBMTg91ux+v18uKLL5KdnQ3A0NAQfX19mEwm4PpNGCNGnv03r9d7w5Blr9eLx+MZ/X/y5MmjfxsMBtRyLCLjTVurIhI0nnrqKRwOx+jWamJiIgcOHKC/vx+AHTt2kJ+fj8ViIT4+noMHDwLQ0dFBQ0PDn27GePjhh/nss8/weDx4vV72799PQkLC+H6UiMjf0IqciASVoqIiMjIyOH36NJmZmfT09PDss89iMBiYNWsW27ZtA6CkpISCggIqKiqw2WzY7XbMZvMN71q3bh0lJSU888wzDA8P43A4KCoq8sdniYj8JY0fEZEJqaysjOTkZCIiIrhy5QoZGRns2bOHyMhIf5cmIvKPaUVORCakuXPnsmHDBoxGI9euXWPNmjUKcSIScLQiJyIiIhKgdNhBREREJEApyImIiIgEKAU5ERERkQClICciIiISoBTkRERERAKUgpyIiIhIgPoP+fb+Z3oVhRMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib plot\n",
    "plt.rcParams[\"figure.figsize\"] = (10,4)\n",
    "# set the tick size\n",
    "plt.rcParams[\"xtick.labelsize\"] = 10\n",
    "sns.set_palette(\"pastel\")\n",
    "# https://stackoverflow.com/q/46623583 order countplot by count.\n",
    "chart= sns.countplot(df18.Region, order= df18['Region'].value_counts().index)\n",
    "# rotate axes labels to avoid overlap - see <https://www.drawingfromdata.com/how-to-rotate-axis-labels-in-seaborn-and-matplotlib>\n",
    "chart.set_xticklabels(chart.get_xticklabels(), rotation=45)\n",
    "plt.title(\"Distribution of Countries in Geographic Regions in in the dataset 2018\");\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of countries by clustered region.\n",
    "Here I will use the dataframe `c18` created above which has the clustered regions added. All other data in it is the same as the original dataframes.  The dataframe  `clusters` contains all the data from `df_years`s but with the addition of the predicted clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "      <th>cluster_pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>7.776209</td>\n",
       "      <td>10.935776</td>\n",
       "      <td>0.946864</td>\n",
       "      <td>72.779999</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>7.492804</td>\n",
       "      <td>10.954624</td>\n",
       "      <td>0.958796</td>\n",
       "      <td>73.059998</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>7.572137</td>\n",
       "      <td>10.955430</td>\n",
       "      <td>0.938334</td>\n",
       "      <td>73.199997</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016</td>\n",
       "      <td>7.458520</td>\n",
       "      <td>10.958175</td>\n",
       "      <td>0.927628</td>\n",
       "      <td>73.500000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017</td>\n",
       "      <td>7.473593</td>\n",
       "      <td>10.957976</td>\n",
       "      <td>0.949661</td>\n",
       "      <td>73.800003</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy  \\\n",
       "2  2012           7.776209        10.935776        0.946864        72.779999   \n",
       "3  2014           7.492804        10.954624        0.958796        73.059998   \n",
       "4  2015           7.572137        10.955430        0.938334        73.199997   \n",
       "5  2016           7.458520        10.958175        0.927628        73.500000   \n",
       "6  2017           7.473593        10.957976        0.949661        73.800003   \n",
       "\n",
       "   RegionCode  cluster_pred  \n",
       "2           3             2  \n",
       "3           3             2  \n",
       "4           3             2  \n",
       "5           3             2  \n",
       "6           3             2  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# see the top of the dataframe\n",
    "clusters.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 126 countries in the dataset. \n",
      "These countries are split over 10 geographic regions as follows: \n",
      "1    0.444444\n",
      "2    0.309524\n",
      "0    0.246032\n",
      "Name: cluster_pred, dtype: float64.3f %\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find how many values in total\n",
    "print(f\"There are {len(c18.cluster_pred)} countries in the dataset. \")\n",
    "# calculate the proportion of countries in each region\n",
    "CRprob=(c18.cluster_pred.value_counts()/len(c18.cluster_pred)).round(3)\n",
    "print(f\"These countries are split over 10 geographic regions as follows: \\n{c18.cluster_pred.value_counts()/len(c18.cluster_pred)}.3f %\", sep=\"\\n\")\n",
    "# mnake sure they sum to 1. \n",
    "CRprob.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot the distribution of countries in the clustered groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_palette(\"pastel\")\n",
    "# https://stackoverflow.com/q/46623583 order countplot by count.\n",
    "chart= sns.countplot(c18.cluster_pred, order= c18['cluster_pred'].value_counts().index)\n",
    "# rotate axes labels to avoid overlap - see <https://www.drawingfromdata.com/how-to-rotate-axis-labels-in-seaborn-and-matplotlib>\n",
    "chart.set_xticklabels(chart.get_xticklabels(), rotation=45)\n",
    "plt.title(\"Distribution of Countries in Geographic Regions in in the dataset 2018\");\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate some geographic regions.\n",
    "Here I use the [`numpy.random.choice`](https://numpy.org/doc/1.16/reference/generated/numpy.random.choice.html#numpy-random-choice) function to generates a random sample of regions from a one dimensional array of made-up regions using the proportions from the real dataset. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['SimReg1', 'SimReg2', 'SimReg0', ..., 'SimReg1', 'SimReg1',\n",
       "       'SimReg1'], dtype='<U7')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# makeup region names:\n",
    "Sim_regions = ['SimReg0','SimReg1','SimReg2']\n",
    "# assign countries to region based on proportions in actual dataset.\n",
    "p=[c18.cluster_pred.value_counts()/len(c18.cluster_pred)]\n",
    "# simulate regions using the probabilities based on proportion in actual dataset\n",
    "CR= np.random.choice(Sim_regions, 136, p=[p[0][0],p[0][1],p[0][2]])\n",
    "CR\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Make up some country names:\n",
    "Here I am just going to create some country names by appending a digit to the string 'Country_'. I don't have the imagination to start creating over 100 new countries!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a list of countries by appending number to 'country'\n",
    "countries =[]\n",
    "# use for loop and concatenate number to string\n",
    "for i in range(136):\n",
    "    countryname = 'Sim_Country_'+str(i)\n",
    "    # append countryname  to list of countries\n",
    "    countries.append(countryname)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a dataframe to hold the simulated data:\n",
    "I now have countries and regions for the simulated dataset which I will add to a dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sim_Country</th>\n",
       "      <th>Sim_Region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>SimReg1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>SimReg2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>SimReg0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>SimReg0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Sim_Country_132</td>\n",
       "      <td>SimReg2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Sim_Country_133</td>\n",
       "      <td>SimReg1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Sim_Country_134</td>\n",
       "      <td>SimReg1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>Sim_Country_135</td>\n",
       "      <td>SimReg1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Sim_Country Sim_Region\n",
       "0      Sim_Country_0    SimReg1\n",
       "1      Sim_Country_1    SimReg2\n",
       "2      Sim_Country_2    SimReg0\n",
       "3      Sim_Country_3    SimReg0\n",
       "..               ...        ...\n",
       "132  Sim_Country_132    SimReg2\n",
       "133  Sim_Country_133    SimReg1\n",
       "134  Sim_Country_134    SimReg1\n",
       "135  Sim_Country_135    SimReg1\n",
       "\n",
       "[136 rows x 2 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a dataframe to hold the simulated variables.\n",
    "sim_df = pd.DataFrame(data={'Sim_Country':countries, 'Sim_Region':CR})\n",
    "sim_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot of the distribution of simulated regions: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set the figure size\n",
    "plt.rcParams[\"figure.figsize\"] = (10,4)\n",
    "sns.set_palette(\"muted\")\n",
    "# countplot of simulated region, order by counts\n",
    "sns.countplot(sim_df.Sim_Region, order= sim_df['Sim_Region'].value_counts().index)\n",
    "# add title\n",
    "plt.title(\"Distribution of Simulated Regions in the Simulated dataset\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The countplot above shows the simulated regions in  the simulated dataset, ordered by the count of the countries in each region. Comparing it to the actual dataset shows that the split looks good."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"simlife\"></a>\n",
    "***\n",
    "## Simulate Life Satisfaction  / Life Ladder variable:\n",
    "\n",
    "The Life Ladder scores and rankings are based on answers to the Cantril Ladder question from the Gallup World Poll where the participants rate their own lives on a scale of 0 to 10 with the best possible life for them being a 10 and the worst a 0. The rankings are from nationally representative samples for the years between 2016 and 2018 and are based entirely on the survey scores using weights to make the estimates representative.\n",
    "\n",
    "The World Happiness Report shows how levels of GDP, life expectancy, generosity, social support, freedom, and corruption - contribute to making life evaluations higher in each country than they are in Dystopia, a hypothetical country that has values equal to the world’s lowest national averages for each of the six factors. \n",
    "The report itself looks at life evaluations for the 2016 to 2018 period and the rankings across all countries in the study. \n",
    "Here are the statistics for the Life Ladder variable for the 2018 dataset. \n",
    "\n",
    "Life Ladder / Life Satisfaction is a non-negative real number with statistics as follows. The minimum possible value is 0 and the maximum is 10 although the range of values in the actual dataset is smaller. The values in the dataset are national averages of the answers to Cantril Ladder question. The range of values vary across regions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Descriptive statistics of the Life Ladder variable in the dataset for 2018:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    136.000000\n",
       "mean       5.502134\n",
       "std        1.103461\n",
       "min        2.694303\n",
       "25%        4.721326\n",
       "50%        5.468088\n",
       "75%        6.277691\n",
       "max        7.858107\n",
       "Name: Life_Satisfaction, dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df18['Life_Satisfaction'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot of the distribution of Life Ladder for 2018:\n",
    "The distribution of Life Ladder is plotted below. The plot on the left shows the distribution for the dataframe containing 2018 data only and the plot on the right shows the distribution for the dataframe containing all years.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,axes=plt.subplots(1,2, figsize=(12,3))\n",
    "# distribution of the Life Ladder for 2018\n",
    "sns.distplot(df18['Life_Satisfaction'], label=\"Life Ladder 2018\", ax=axes[0])\n",
    "# distribution of life ladder from the dataframe with the clusters. some missing values\n",
    "sns.distplot(c18['Life_Satisfaction'], label=\"Life Ladder - 2018\", ax=axes[0])\n",
    "axes[0].set_title(\"Distribution of Life Ladder for 2018 only\")\n",
    "#axes[0].legend()\n",
    "# kdeplot of the life ladder for all years in the extended dataset (WHR Table2.1)\n",
    "sns.distplot(df_years['Life_Satisfaction'], label=\"Life Ladder - all years\", ax=axes[1])\n",
    "sns.distplot(c18['Life_Satisfaction'], label=\"Life Ladder - 2018\",ax=axes[1])\n",
    "axes[1].set_title(\"Distribution of Life Ladder for 2012 to 2018\");\n",
    "#axes[1].legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The distribution plots for the Life Ladder variable does suggest that it is normally distributed but there are some tests that can be used to clarify this. \n",
    "A blogpost on [tests for normality](https://machinelearningmastery.com/a-gentle-introduction-to-normality-tests-in-python/)[21] at machinelearningmastery.com outlines how it is important when working with a sample of data to know whether to use parametric or nonparametric statistical methods. If methods used assume a Gaussian distribution when it is not the case then findings can be incorrect or misleading. In some cases it is enough to assume the data is normal enough to use parametric methods or to transform the data to be normal enough. \n",
    "\n",
    ">Parametric statistical methods assume that the data has a known and specific distribution, often a Gaussian distribution. If a data sample is not Gaussian, then the assumptions of parametric statistical tests are violated and nonparametric statistical methods must be used.[21]\n",
    "\n",
    "Normality tests can be used to check if your data sample is from a Gaussian distribution or not.\n",
    "- Statistical tests calculate statistics on the data to quantify how likely it is that the data was drawn from a normal distribution.\n",
    "- Graphical methods plot the data to qualitatively evaluate if the data looks Gaussian.\n",
    "\n",
    "Tests for normality include the Shapiro_Wilk Normality Test, the D'Agostino and Pearson's Test, the Anderson-Darling Test.\n",
    "\n",
    "The histograms above show the characteristic bell-shape curve of the normal distribution and indicates that the Life Ladder variable is gaussian or approximately normally distributed.\n",
    "\n",
    "The **Quantile-Quantile Plot** (QQ plot) is another plot that can be used to check if the distribution of a data sample. It generates its own sample of the idealised distribution that you want to compare your sample of data to. The idealised samples are divided into groups and each data point in the sample is paired with a similar member from the idealised distribution at the same cumulative distribution.\n",
    "\n",
    "A scatterplot is drawn with the idealised values on the x-axis and the data sample on the y-axis.\n",
    "The resulting points are plotted as a scatter plot with the idealized value on the x-axis and the data sample on the y-axis. If the result is a straight line of dots on the diagonal from the bottom left to the top right this indicates a perfect match for the distribution whereas if the dots deviate far from the diagonal line.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### QQ plot of Life Ladder:\n",
    "Here a QQ plot is created for the Life Ladder sample compared to a Gaussian distribution (the default)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import the qqplot function \n",
    "from statsmodels.graphics.gofplots import qqplot\n",
    "# Life Ladder observations from the dataset. can use c18 dataframe or dfh\n",
    "data = c18['Life_Satisfaction']\n",
    "# plot a q-q plot, draw the standardised line\n",
    "qqplot(data, line='s') \n",
    "plt.title(\"QQ plot to test for normality of Life Ladder\");\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Tests for normality:\n",
    "The QQ plot does seem to indicate to me  that the Life Ladder is normally distributed. The scatter plots of points do mostly follow the diagonal pattern for a sample from a Gaussian distribution. I will use some of the normality tests as outlined on the [blogpost on tests for normality](https://machinelearningmastery.com/a-gentle-introduction-to-normality-tests-in-python/)[21]. These tests assume the sample was drawn from a Gaussian distribution and test this as the null hypothesis. A test-statistic is calculated and a p-value to interpret the test statistic. A threshold level called *alpha* is used to interpret the test. This is typically 0.05. If the p-value is less than or equal to alpha, then reject the null hypothesis. If the p-value is greater than alpha then fail to reject the null hypothesis.\n",
    "In general a larger p-value indicates that the sample was likely to have been drawn from a Gaussian distribution. A result above 5% doesn't mean the null hypothesis is true but that it is very likely true given the evidence available."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Shapiro-Wilk Normality Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stat=0.991, p=0.520\n",
      "The sample of Life Satisfaction/ Life Ladder looks Gaussian (fail to reject H0)\n"
     ]
    }
   ],
   "source": [
    "# adapted from https://machinelearningmastery.com/a-gentle-introduction-to-normality-tests-in-python/\n",
    "# import the shapiro test from scipy stats\n",
    "from scipy.stats import shapiro\n",
    "# calculate the test statistic and the p-value to interpret the test on the Life Ladder sample\n",
    "stat, p = shapiro(df18['Life_Satisfaction'])\n",
    "# interpret the test\n",
    "alpha= 0.05\n",
    "print('stat=%.3f, p=%.3f' % (stat, p))\n",
    "alpha = 0.05\n",
    "if p > alpha:\n",
    "    print('The sample of Life Satisfaction/ Life Ladder looks Gaussian (fail to reject H0)')\n",
    "else:\n",
    "    print('The sample of Life Ladder does not look Gaussian (reject H0)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### D’Agostino’s K^2 Test\n",
    "This test calculates the kurtosis and skewness of the data to see if the data distribution is not normal like.\n",
    "The skew is a measure of asymmetry in the data while hurtosis how much of the distribution is in the tails.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Statistics=2.435, p=0.296\n",
      "The sample of Life Ladder looks Gaussian (fail to reject H0)\n"
     ]
    }
   ],
   "source": [
    "# D'Agostino and Pearson's Test adapted from https://machinelearningmastery.com/a-gentle-introduction-to-normality-tests-in-python/\n",
    "# import from scipy.stats\n",
    "from scipy.stats import normaltest\n",
    "# normality test\n",
    "stat, p = normaltest(df18['Life_Satisfaction'])\n",
    "print('Statistics=%.3f, p=%.3f' % (stat, p))\n",
    "# interpret\n",
    "alpha = 0.05\n",
    "if p > alpha:\n",
    "    print('The sample of Life Ladder looks Gaussian (fail to reject H0)')\n",
    "else:\n",
    "    print('The sample of Life Ladder does not look Gaussian (reject H0)')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Anderson-Darling Test:\n",
    "This is a statistical test that can be used to evaluate whether a data sample comes from one of among many known data samples adn can be used to check whether a data sample is normal. The test is a modified version of the [Kolmogorov-Smirnov test](https://en.wikipedia.org/wiki/Kolmogorov–Smirnov_test)[22] which is a nonparametric goodness-of-fit statistical test.\n",
    "The Anderson-Darling test returns a list of critical values rather than a single p-value. The test will check against the Gaussian distribution (dist=’norm’) by default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Statistic: 0.235\n",
      "15.000: 0.560, data looks normal (fail to reject H0)\n",
      "10.000: 0.638, data looks normal (fail to reject H0)\n",
      "5.000: 0.766, data looks normal (fail to reject H0)\n",
      "2.500: 0.893, data looks normal (fail to reject H0)\n",
      "1.000: 1.062, data looks normal (fail to reject H0)\n"
     ]
    }
   ],
   "source": [
    "# Anderson-Darling Test - adapted from https://machinelearningmastery.com/a-gentle-introduction-to-normality-tests-in-python/\n",
    "\n",
    "from scipy.stats import anderson\n",
    "# normality test\n",
    "result = anderson(df18['Life_Satisfaction'])\n",
    "print('Statistic: %.3f' % result.statistic)\n",
    "p = 0\n",
    "# checking for a range of critical values\n",
    "for i in range(len(result.critical_values)):\n",
    "    sl, cv = result.significance_level[i], result.critical_values[i]\n",
    "    if result.statistic < result.critical_values[i]:\n",
    "        # fail to reject the null that the data is normal if test statistic is less than the critical value.\n",
    "        print('%.3f: %.3f, data looks normal (fail to reject H0)' % (sl, cv))\n",
    "    else:\n",
    "        # reject the null that the data is normal if test statistic is greater than the critical value.\n",
    "        print('%.3f: %.3f, data does not look normal (reject H0)' % (sl, cv))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The sample of Life Ladder for 2018 does appear to be normally distributed based on the above tests.\n",
    "Therefore I can go ahead and simulate data for this variable using the normal distribution using the sample mean and standard deviation statistics.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate Life ladder variable:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I will now simulate 'Life Ladder' using the [`numpy.random.normal`](https://numpy.org/doc/1.16/reference/generated/numpy.random.normal.html#numpy-random-normal) function. This takes 3 arguments - `loc` for the mean or centre of the distributon, `scale` for the spread or width of the distribution - the standard deviation, and `size` for the number of samples to draw from the distribution.\n",
    "Without setting a seed the actual values will be different each time but the shape of the distribution should be the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The mean of the sample dataset for 2018 is 5.500 \n",
      " The standard deviation of the sample dataset for 2018 is 1.098 \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(126, 7)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f\" The mean of the sample dataset for 2018 is {c18['Life_Satisfaction'].mean():.3f} \")\n",
    "print(f\" The standard deviation of the sample dataset for 2018 is {c18['Life_Satisfaction'].std():.3f} \")\n",
    "c18.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.458520</td>\n",
       "      <td>10.958175</td>\n",
       "      <td>0.927628</td>\n",
       "      <td>73.500000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2016</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.510035</td>\n",
       "      <td>10.728341</td>\n",
       "      <td>0.984940</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2016</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.557783</td>\n",
       "      <td>10.736206</td>\n",
       "      <td>0.954452</td>\n",
       "      <td>71.800003</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2016</td>\n",
       "      <td>Norway</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>7.596332</td>\n",
       "      <td>11.069128</td>\n",
       "      <td>0.959743</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1675</th>\n",
       "      <td>2016</td>\n",
       "      <td>Taiwan Province of China</td>\n",
       "      <td>Southeastern Asia</td>\n",
       "      <td>6.512851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.894989</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1685</th>\n",
       "      <td>2016</td>\n",
       "      <td>Hong Kong S.A.R. of China</td>\n",
       "      <td>Southeastern Asia</td>\n",
       "      <td>5.498421</td>\n",
       "      <td>10.904357</td>\n",
       "      <td>0.832078</td>\n",
       "      <td>75.953506</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1689</th>\n",
       "      <td>2016</td>\n",
       "      <td>Somalia</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>4.667941</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.594417</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1698</th>\n",
       "      <td>2016</td>\n",
       "      <td>South Sudan</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>2.888112</td>\n",
       "      <td>7.358760</td>\n",
       "      <td>0.532152</td>\n",
       "      <td>50.599998</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>142 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year                    Country              Region  Life_Satisfaction  \\\n",
       "5     2016                Switzerland      Western Europe           7.458520   \n",
       "12    2016                    Iceland      Western Europe           7.510035   \n",
       "24    2016                    Denmark      Western Europe           7.557783   \n",
       "32    2016                     Norway      Western Europe           7.596332   \n",
       "...    ...                        ...                 ...                ...   \n",
       "1675  2016   Taiwan Province of China   Southeastern Asia           6.512851   \n",
       "1685  2016  Hong Kong S.A.R. of China   Southeastern Asia           5.498421   \n",
       "1689  2016                    Somalia  Sub-Saharan Africa           4.667941   \n",
       "1698  2016                South Sudan  Sub-Saharan Africa           2.888112   \n",
       "\n",
       "      Log_GDP_per_cap  Social_Support  Life_Expectancy  RegionCode  \n",
       "5           10.958175        0.927628        73.500000           3  \n",
       "12          10.728341        0.984940        73.000000           3  \n",
       "24          10.736206        0.954452        71.800003           3  \n",
       "32          11.069128        0.959743        73.000000           3  \n",
       "...               ...             ...              ...         ...  \n",
       "1675              NaN        0.894989              NaN           6  \n",
       "1685        10.904357        0.832078        75.953506           6  \n",
       "1689              NaN        0.594417        50.000000           1  \n",
       "1698         7.358760        0.532152        50.599998           1  \n",
       "\n",
       "[142 rows x 8 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_years.loc[df_years.loc[:,'Year']==2016]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creating subsets of the data for each in order to be able to see how the distribution varies from year to year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# subset of the data for each year\n",
    "c17= Cy.loc[Cy.loc[:,'Year']==2017]\n",
    "c16= Cy.loc[Cy.loc[:,'Year']==2016]\n",
    "c15= Cy.loc[Cy.loc[:,'Year']==2015]\n",
    "c14= Cy.loc[Cy.loc[:,'Year']==2014]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the distribution of life satisfaction variable for each of the years 2014 to 2018\n",
    "sns.kdeplot(c14['Life_Satisfaction'], label=\"2014\")\n",
    "sns.kdeplot(c15['Life_Satisfaction'], label=\"2015\")\n",
    "sns.kdeplot(c16['Life_Satisfaction'], label=\"2016\")\n",
    "sns.kdeplot(c17['Life_Satisfaction'], label=\"2017\")\n",
    "sns.kdeplot(c18['Life_Satisfaction'], label=\"2018\")\n",
    "plt.title(\"Distribution of Life Satisfaction for each year 2014 to 2017\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot some simulated data.\n",
    "Here some data is simulated for the Life Satisfaction/Ladder variable is simulated using the mean and standard deviation for the 2018 data. As the variable appears to be normally distributed it would be ok to do this. However as mnay of the other varaibles are not normally distributed at the dataset level but do look gaussian at the clustered region level I will be simulating the other variables this way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.kdeplot(c18['Life_Satisfaction'], label=\"Life Satisfaction 2018\", shade=\"True\")\n",
    "# simulate data based on statistics from the 2018 sample dataset\n",
    "# simulate life ladder using sample mean and standard deviation\n",
    "for i in range(10):\n",
    "        x= np.random.normal(c18['Life_Satisfaction'].mean(),c18['Life_Satisfaction'].std(),130)\n",
    "        sns.kdeplot(x)\n",
    "# plot the distribution of the actual dataset\n",
    "\n",
    "# plot the simulated data \n",
    "plt.title(\"Actual data versus the Simulated data for Life Ladder 2018\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above plots of the distribution of Life_Satisfaction illustrate how the distribution changes slightly for each simulation due to the randomness. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next plot the distribution for the 4 clustered regions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_pred</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "cluster_pred                                                             \n",
       "0               31                 31               31              31   \n",
       "1               56                 56               56              56   \n",
       "2               39                 39               39              39   \n",
       "\n",
       "              Life_Expectancy  RegionCode  \n",
       "cluster_pred                               \n",
       "0                          31          31  \n",
       "1                          56          56  \n",
       "2                          39          39  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c18.groupby('cluster_pred').count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The distributions of Life Ladder for each of the 3 clustered regions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "\n",
    "# plot for countries in these regions, set axes to use, labels to use\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==0]['Life_Satisfaction'], label=\"Cluster region 0\", color=\"g\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==1]['Life_Satisfaction'], label=\"Cluster region 1\", color=\"b\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==2]['Life_Satisfaction'], label=\"cluster region 2\", color=\"r\", shade=True)\n",
    "#sns.distplot(clusters.loc[clusters.loc[:,'cluster_pred']==3]['Life Ladder'], ax=axes[3], label=\"cluster region 3\", color=\"y\")\n",
    "# add title\n",
    "plt.suptitle(\"Actual Life Ladder for the 3 clusters for 2017\");\n",
    "plt.legend();\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# separate out the clustered regions for all years from 2011 to 2018\n",
    "cluster0 =clusters.loc[clusters.loc[:,'cluster_pred']==0]\n",
    "cluster1 =clusters.loc[clusters.loc[:,'cluster_pred']==1]\n",
    "cluster2 =clusters.loc[clusters.loc[:,'cluster_pred']==2]\n",
    "## separate out the clustered regions for 2018 data\n",
    "c18_0 =c18.loc[c18.loc[:,'cluster_pred']==0]\n",
    "c18_1 =c18.loc[c18.loc[:,'cluster_pred']==1]\n",
    "c18_2 =c18.loc[c18.loc[:,'cluster_pred']==2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The distribution of the Life Satisfaction (Life Ladder) variable looks quite normal when taken over all the countries in the dataset. When shown for each of the 3 clustered regions, the distributions are all still normal looking but with very different shapes and locations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean and Standard deviation for each region group:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The mean of the sample dataset for 2018 is 4.230 \n",
      " The standard deviation of the sample dataset for 2018 is 0.614 \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(126, 7)"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cluster 0\n",
    "print(f\" The mean of the sample dataset for 2018 is {cluster0['Life_Satisfaction'].mean():.3f} \")\n",
    "print(f\" The standard deviation of the sample dataset for 2018 is {cluster0['Life_Satisfaction'].std():.3f} \")\n",
    "c18.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "simulate for each cluster based on their statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "LLc0= np.random.normal(c18_0['Life_Satisfaction'].mean(),c18_0['Life_Satisfaction'].std(),31)\n",
    "LLc1= np.random.normal(c18_1['Life_Satisfaction'].mean(),c18_1['Life_Satisfaction'].std(),39)\n",
    "LLc2= np.random.normal(c18_2['Life_Satisfaction'].mean(),c18_2['Life_Satisfaction'].std(),56)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "# life satisfaction distribution for cluster region 0\n",
    "sns.kdeplot(LLc0,color=\"y\", shade=True)\n",
    "# life satisfaction distribution for cluster region 1\n",
    "sns.kdeplot(LLc1, color=\"skyblue\", shade=True)\n",
    "# life satisfaction distribution for cluster region 2\n",
    "sns.kdeplot(LLc2, color=\"pink\", shade=True)\n",
    "# add title\n",
    "plt.suptitle(\"Distribution of simulated Life Satisfaction for 3 region clusters\");\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Illustrating how the distributions changed for each simulation due to random variation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Distributions of 5 simulations for Life Satisfaction for each of the 3 groups')"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,axes=plt.subplots(1,3, figsize=(13,3))\n",
    "for i in range(5):\n",
    "        sns.kdeplot(np.random.normal(c18_0['Life_Satisfaction'].mean(),c18_0['Life_Satisfaction'].std(),31), shade=True, ax=axes[0])\n",
    "    \n",
    "for i in range(5):\n",
    "        sns.kdeplot(np.random.normal(c18_1['Life_Satisfaction'].mean(),c18_1['Life_Satisfaction'].std(),39), shade=True, ax=axes[1])\n",
    "for i in range(5):\n",
    "        sns.kdeplot(np.random.normal(c18_2['Life_Satisfaction'].mean(),c18_2['Life_Satisfaction'].std(),59), shade=True, ax=axes[2])\n",
    "\n",
    "plt.suptitle(\"Distributions of 5 simulations for Life Satisfaction for each of the 3 groups\")\n",
    "       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "## Simulating Social Support\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Social Support:\n",
    "The variable 'Social support' was the result of a question in the Gallop World Poll with the national average of the binary responses for each country to the GWP question “If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?”.\n",
    "\n",
    "The distribution from the dataset shows that it is left skewed. The scatterplots above showed that it is positively correlated with life satisfaction, income levels and healthy life expectancy.\n",
    "The boxplots below show that the median values fall into roughly 3 groups by regions with Western Europe, North America and Australia and New Zealand having the highest scores,  while Southern Asia and Sub Saharan Africa have the lowest median scores and a wider spread. \n",
    "\n",
    "Like Life ladder variable, the values are the result of national averages to questions in the Gallup World Poll. In this case the question had a binary answer 0 or 1 and therefore the actual values in the dataset range between 0 and 1. Social Support is a non-negative real values. The statistics vary from region to region."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    136.000000\n",
       "mean       0.810544\n",
       "std        0.116332\n",
       "min        0.484715\n",
       "25%        0.739719\n",
       "50%        0.836641\n",
       "75%        0.905608\n",
       "max        0.984489\n",
       "Name: Social_Support, dtype: float64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df18['Social_Support'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot of the distribution of Social Support for 2018:\n",
    "The distribution of Life Ladder is plotted below. The plot on the left shows the distribution for the dataframe containing 2018 data only and the plot on the right shows the distribution for the dataframe containing all years.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,axes=plt.subplots(1,2, figsize=(12,3))\n",
    "# distribution of the Social support for 2018\n",
    "sns.distplot(df18['Social_Support'], label=\"Social Support 2018\", ax=axes[0])\n",
    "# distribution of social support from the dataframe with the clusters. some missing values\n",
    "sns.distplot(c18['Social_Support'], label=\"Social Support - 2018\", ax=axes[0])\n",
    "axes[0].set_title(\"Distribution of Social Support for 2018 only\")\n",
    "#axes[0].legend()\n",
    "# kdeplot of the Social Support for all years in the extended dataset (WHR Table2.1)\n",
    "sns.distplot(df_years['Social_Support'].dropna(), label=\"Social_Support - all years\", ax=axes[1])\n",
    "sns.distplot(c18['Social_Support'], label=\"Social_Support - 2018\",ax=axes[1])\n",
    "axes[1].set_title(\"Distribution of Social_Support for 2012 to 2018\");\n",
    "#axes[1].legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the distribution of life satisfaction variable for each of the years 2014 to 2018\n",
    "sns.kdeplot(c14['Social_Support'], label=\"2014\")\n",
    "sns.kdeplot(c15['Social_Support'], label=\"2015\")\n",
    "sns.kdeplot(c16['Social_Support'], label=\"2016\")\n",
    "sns.kdeplot(c17['Social_Support'], label=\"2017\")\n",
    "sns.kdeplot(c18['Social_Support'], label=\"2018\")\n",
    "plt.title(\"Distribution of Social_Support' for each year 2014 to 2017\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "\n",
    "# plot for countries in these regions, set axes to use, labels to use\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==0]['Social_Support'], label=\"Cluster region 0\", color=\"g\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==1]['Social_Support'], label=\"Cluster region 1\", color=\"b\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==2]['Social_Support'], label=\"cluster region 2\", color=\"r\", shade=True)\n",
    "#sns.distplot(clusters.loc[clusters.loc[:,'cluster_pred']==3]['Life Ladder'], ax=axes[3], label=\"cluster region 3\", color=\"y\")\n",
    "# add title\n",
    "plt.suptitle(\"Actual Social Support variable for the 3 clusters for 2017\");\n",
    "plt.legend();\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The distribution of Social Support for all the countries in 2018 is a left-skewed distribution with a long tail to the left. When this is broken down by cluster groups of regions, the distribution of each cluster looks more normal shaped although the centres of the distribution and the spread vary widely. Cluster region 0 (green) has social support values centred around different values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean and standard deviation for Social Support by clustered group:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_pred</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.415971</td>\n",
       "      <td>7.732756</td>\n",
       "      <td>0.669998</td>\n",
       "      <td>54.945161</td>\n",
       "      <td>1.290323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>5.322920</td>\n",
       "      <td>9.294176</td>\n",
       "      <td>0.820008</td>\n",
       "      <td>64.951786</td>\n",
       "      <td>3.946429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6.614540</td>\n",
       "      <td>10.401640</td>\n",
       "      <td>0.900387</td>\n",
       "      <td>71.515385</td>\n",
       "      <td>4.102564</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Year  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "cluster_pred                                                               \n",
       "0             2018.0           4.415971         7.732756        0.669998   \n",
       "1             2018.0           5.322920         9.294176        0.820008   \n",
       "2             2018.0           6.614540        10.401640        0.900387   \n",
       "\n",
       "              Life_Expectancy  RegionCode  \n",
       "cluster_pred                               \n",
       "0                   54.945161    1.290323  \n",
       "1                   64.951786    3.946429  \n",
       "2                   71.515385    4.102564  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c18.groupby('cluster_pred').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate data for the Social Support variable for each of the cluster groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "SSc0= np.random.normal(c18_0['Social_Support'].mean(),c18_0['Social_Support'].std(),31)\n",
    "SSc1= np.random.normal(c18_1['Social_Support'].mean(),c18_1['Social_Support'].std(),39)\n",
    "SSc2= np.random.normal(c18_2['Social_Support'].mean(),c18_2['Social_Support'].std(),56)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot the distributions of the simulated Social Support variable for the 3 groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "# life satisfaction distribution for cluster region 0\n",
    "sns.kdeplot(SSc0,color=\"y\", shade=True)\n",
    "# life satisfaction distribution for cluster region 1\n",
    "sns.kdeplot(SSc1, color=\"skyblue\", shade=True)\n",
    "# life satisfaction distribution for cluster region 2\n",
    "sns.kdeplot(SSc2, color=\"pink\", shade=True)\n",
    "# add title\n",
    "plt.suptitle(\"Distribution of simulated Social Support for 3 region clusters\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulating Social Support variable using non-parametric methods:\n",
    "\n",
    "When I first looked at simulating the social support variable I considered non-parametric ways of working with the data such as the bootstrap resampling method. Bootstrapping is a statistical technique for estimating quantities about a population by averaging estimates from multiple small data samples. Samples are constructed by drawing observations from a large data sample one at a time and then returning the observation so that it could be drawn again. Therefore any given observation could be included in the sample more than once while some observations might never be drawn. \n",
    "I referred to a blogpost on [Machinelearningmastery.com](https://machinelearningmastery.com/a-gentle-introduction-to-the-bootstrap-method/)[23] which outlines the steps to implement it using the  [scikit-learn resample function](http://scikit-learn.org/stable/modules/generated/sklearn.utils.resample.html)[24] which takes as arguments the data array, whether or not to sample with replacement, the size of the sample, and the seed for the pseudorandom number generator used prior to the sampling.\n",
    "\n",
    ">Bootstrapping is the practice of estimating properties of an estimator (such as its variance) by measuring those properties when sampling from an approximating distribution. One standard choice for an approximating distribution is the empirical distribution function of the observed data. In the case where a set of observations can be assumed to be from an independent and identically distributed population, this can be implemented by constructing a number of resamples with replacement, of the observed dataset (and of equal size to the observed dataset). \n",
    "The basic idea of bootstrapping is that inference about a population from sample data can be modelled by resampling the sample data and performing inference about a sample from resampled data. As the population is unknown, the true error in a sample statistic against its population value is unknown. In bootstrap-resamples, the 'population' is in fact the sample, and this is known; hence the quality of inference of the 'true' sample from resampled data (resampled → sample) is measurable.\n",
    "[Wikipedia wiki on Bootstrapping](https://en.wikipedia.org/wiki/Bootstrapping_(statistics))[25]\n",
    "\n",
    "The process for building one sample is:\n",
    "- choose the size of the sample\n",
    "- While the size of the sample is less than the chosen size\n",
    "    1. Randomly select an observation from the dataset\n",
    "    2. Add it to the sample\n",
    "The number of repetitions must be large enough that meaningful repetitions can be calculated on the sample.\n",
    "\n",
    "Based on the information above I use sampling with replacement to simulate the Social support variable using the sample size the same as the original dataset which is 136 observations. [numpy.random.choice](https://numpy.org/doc/1.16/reference/generated/numpy.random.choice.html#numpy-random-choice) function can be used for this purpose.\n",
    "The mean of the Social support variable in the dataset can be considered as a single estimate of the mean of the population of social support while the standard deviation is an estimate of the variability.\n",
    "The simplest bootstrap method would involve taking the original data set of N(136) Social support values and sampling from it to form a new sample  - the 'resample' or bootstrap sample that is also of size 136. \n",
    "If the bootstrap sample is formed using sampling with replacement from the original data sample with a large enough size then there should be very little chance that the bootstrap sample will be the exact same as the original sample. This process is repeated many times (thousands) and the mean  computed for each bootstrap sample to get the bootstrap estimates which can then be plotted on a histogram which is considered an estimate of the shape of the distribution.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sampling with replacement using np.random.choice:\n",
    "Here I use a loop to draw multiple random samples with replacements from the dataset. \n",
    "Additionally the means for each sample can be calculated and then all the means from the different samples are plotted to show their distribution but for this project I just need a simulated data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# using the Social support data from the dataset.\n",
    "social=df18['Social_Support']\n",
    "# create a list to store the means of the samples, set the number of simulations\n",
    "mean_social_sim, sims = [], 20\n",
    "# use loop to create 100 samples - takes very long to do 1000 \n",
    "\n",
    "# plot the distribution of social support variable from the dataset, add title\n",
    "sns.kdeplot(social, label=\"Actual Data\", shade=True)\n",
    "for _ in range(sims):\n",
    "    # draw a random sample from social with replacement and store it in social_sample\n",
    "    social_sample=np.random.choice(social, replace=True, size=len(social))\n",
    "\n",
    "    # plot the distribution of each sample\n",
    "    sns.kdeplot(social_sample)\n",
    "    # add title\n",
    "    plt.title(\"Simulating using random sample with replacement\")\n",
    "    social_mean = np.mean(social_sample)\n",
    "    # append the mean of each sample to mean_social\n",
    "    mean_social_sim.append(social_mean)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main use of the bootstrap is making inferences about an estimate for a population parameter on sample data. \n",
    "For the purposes of this project I just need to simulate a single dataset. However by calculating the bootstrap means and comparing them to the dataset I am attempting to replicate shows that it is a suitable method here when the data does not follow a particular distribution. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    136.000000\n",
       "mean       0.810544\n",
       "std        0.116332\n",
       "min        0.484715\n",
       "25%        0.739719\n",
       "50%        0.836641\n",
       "75%        0.905608\n",
       "max        0.984489\n",
       "Name: Social_Support, dtype: float64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df18['Social_Support'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.81230999310227"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(mean_social_sim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "## Simulating Log GDP per capita\n",
    "\n",
    "The GDP per capita in the World Happiness Report dataset are in purchasing power parity at constant 2011 international dollar prices which are mainly from the World Development Indicators in 2018. Purchasing power parity is necessary when looking to compare GDP per capita between countries which is what the World Happiness Report seeks to do. Nominal GDP would be fine when just looking at a single country. The log of the GDP figures is taken.\n",
    "\n",
    "Per capita GDP is the Total Gross Domestic Product for a country divided by its population and breaks down a country's GDP per person. As the World Happiness Report states this is considered a universal measure for gauging the prosperity of nations. \n",
    "\n",
    "The earlier plots showed that the distribution of log GPD per capita in the dataset is not normally distributed. Per capita GDP is generally a unimodal but skewed distribution. There are many regional variations in income across the world. The distribution of Log GPD per capita appears somewhat left skewed. \n",
    "\n",
    "The scatterplots above showed that it is positively correlated with life satisfaction, social support and healthy life expectancy. \n",
    "\n",
    "The log of GDP per capita is used to represent the Gross Domestic Product per capita. It is a non-negative real value. Because the log of the GDP per capita figures are used the range is between 6 and 12 although this varies from region to region. The "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1676.000000\n",
       "mean        9.222456\n",
       "std         1.185794\n",
       "min         6.457201\n",
       "25%         8.304428\n",
       "50%         9.406206\n",
       "75%        10.193060\n",
       "max        11.770276\n",
       "Name: Log_GDP_per_cap, dtype: float64"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Log_GDP_per_cap'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,axes=plt.subplots(1,2, figsize=(12,3))\n",
    "\n",
    "# distribution of social support from the dataframe with the clusters. some missing values\n",
    "sns.distplot(c18['Log_GDP_per_cap'].dropna(), label=\"Log_GDP_per_cap - 2018\", ax=axes[0])\n",
    "axes[0].set_title(\"Distribution of Log_GDP_per_cap for 2018 only\")\n",
    "#axes[0].legend()\n",
    "# kdeplot of the Social Support for all years in the extended dataset (WHR Table2.1)\n",
    "sns.distplot(clusters['Log_GDP_per_cap'].dropna(), label=\"Log_GDP_per_cap - all years\", ax=axes[1])\n",
    "axes[1].set_title(\"Distribution of Log_GDP_per_cap for 2012 to 2018\");\n",
    "#axes[1].legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmEAAAEJCAYAAADcuvDhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzs3XdA1VX/wPH35bKHMmQJiIqIJog5cSLiZIgjlRxp5irTJ8sI/VWmZZGPj1qaDTX1UUstxUHiSMtEcA9wISqgKDJF9oV77/n9Qd5HcjbwOs7rL+53nPs5d3z53M/3fM9XIYQQSJIkSZIkSY+Ugb4DkCRJkiRJehbJJEySJEmSJEkPZBImSZIkSZKkBzIJkyRJkiRJ0gOZhEmSJEmSJOmBTMIkSZIkSZL0QCZhUo3LyMigadOmhIWFERYWRmhoKOHh4Wzbtk23zWeffcamTZvu286iRYv4+eef77ru9v29vLzIz8//UzEmJiby/vvvA5CUlMTkyZP/1P5/hUaj4dVXX6VXr16sXr262rqFCxcya9asGo/hlp9//pnhw4fTu3dvevbsSXh4OHv37tWtj4yMpHPnzrr3MCgoiPfff5+cnBzdNl5eXoSGhhIWFka/fv0ICQnh66+/fmR9eBQiIyOJjIy8Y3lmZiYhISGEhYVx/PhxPUR2p27dupGUlKTvMKrZt28fAwYMICwsjP79+xMXF6db9+OPPxIUFETPnj2ZMWMGlZWV1fY9d+4cnTp1umu7iYmJeHt73/N7f79jx72Ul5czbdo0QkJCCA4OZtq0aZSXlwOQn5/PmDFjCAoKIiQkhGPHjlXbVwjBO++8w7Jly3TLJk+erPv+hIWF0apVKyZMmPCnYpKeQkKSatiVK1dEixYtqi3LyMgQ3bt3F9u3b3/odoYPHy5iY2MfuF3jxo1FXl7en4pxw4YNYty4cX9qn7/r6tWrwtvbW6jV6jvWff7552LmzJmPJI61a9eKPn36iOTkZN2ys2fPio4dO4qTJ08KIYR45513xNKlS3XrtVqt+PLLL0Xfvn118f/xdS8qKhLdunUTe/bseST9eBRmzJghPvjggzuWR0dHi5EjRz76gO4jICBAJCYm6jsMncLCQtG2bVtx/vx5IUTVZ6xVq1aiqKhIJCcniy5duoi8vDyh0WjElClTxDfffCOEEKKyslIsX75cdOjQ4Y7jiBBC5OXlif79+9/3e/+wx47bzZs3T7z99ttCo9EItVotpkyZIhYsWCCEEGLy5Mniyy+/FEIIcebMGdGpUydRWloqhBDiwoULYsSIEcLX17fad+Z2J0+eFF27dhXXrl37UzFJTx9ZCZP0wsXFhcmTJ+t+KUZGRur+/vzzzwkNDWXAgAG88sorZGdns2bNGk6dOsWcOXPYtWsXkZGRTJgwgeDgYP79739X2x9gwYIF9O/fn7CwMH755RcANm7cyPjx43Xb3HqcmZnJ559/zpEjR5g2bRoHDx4kJCQEgKKiIqZOnUpISAihoaHMmTMHtVoNgI+PDwsXLiQ8PJxu3brx3Xff3bWvR44cYfDgwbo+/fbbbxQXFzNmzBjUajUDBgzg8uXLD/3a3a09qKqsffLJJ/To0YMBAwbwwQcfMGLEiPu2VVFRwbx58/j0009p3LixbnmTJk2YOXMmWq32rvspFAomTJhAeXk5+/fvv+s2lpaWeHt7c+nSpfvGEBkZyYwZMxgyZAjdu3evVgW5ePEio0eP1lVPfvzxRwAOHjxI3759CQ8PJzQ0lIqKinu2X1JSwrRp0+jVqxdBQUHMmzcPIQSpqam8/PLLDB48mICAAF599VVUKhUAzz33HPPnz2fAgAH07t2bnTt3AuDr60uLFi2qtX/gwAEWLFhAUlKS7vVet24dISEh9O3bl9GjR5Oamqrr6+2f2z/as2cPgwYNol+/foSHh+uqarm5ubz22msMGTKEbt26MWLECPLy8gBITU1lxIgRBAcHExoaWq3CvG7dOgYMGEDXrl2ZP3/+Hc939OhRunbtqnufy8rKaN++Pfn5+WRlZTFx4kQGDBhAaGgoX331lW6/r776ikGDBhEaGkr37t3ZtWsXUFXBfeWVVwgNDWXq1KnVnquyspIZM2bg6ekJQKNGjRBCcOPGDXbv3k23bt2wtbXFwMCAIUOGsGXLFgDOnDlDcnIyixYtuiN+rVbL22+/zZQpU+7yzlf547Hjft/p27Vp04ZXX30VAwMDlEolTZs25dq1a6jVan799VcGDx4MQNOmTalfvz779u3TPd+gQYPo3bv3XeOpqKggMjKS6dOn4+zsfM+4pWeEvrNA6el3t0qYEEKcP39e+Pr6CiH+V2m5du2aaNmypVCpVEIIIZYtWyZ27dolhKj+a/add96pVnm4vVLTuHFj8fXXXwshhEhOThZt27YVeXl5d1S7bn98+98HDhwQwcHBQgghIiIixIcffii0Wq1QqVRi9OjRurYbN24sVq1aJYQQIikpSXh7e4vy8vJqfczPzxft27cXJ06c0PW5bdu24vLly/d8XYS4dyXsfu19//33YtiwYaK8vFwX6/Dhw+/a/i1nzpwRbdu2ve82QtxZCbtl0qRJYsmSJUKIOythFy9eFO3bt9dV0+7Xdr9+/URxcbFQqVRi2LBhYtWqVaKyslIEBQWJU6dOCSGqKil9+vQRx48fFwcOHBBNmjQRGRkZD4z9448/FlOmTBFqtVrX/oEDB0RUVJTYtGmTEEKIiooKERISoqvMNm7cWFfpuFWxuV919fbPT3x8vOjevbtu+w0bNog+ffoIrVZ7x+f2dqmpqSIkJETk5+cLIare244dO4qSkhKxYsUK3edOq9WKMWPGiGXLlgkhhOjXr59YvXq1EEKIa9euicDAQFFUVCQCAgLErFmzhBBCZGdnC29v77tWXvr27St+/fVXIYQQP/zwg5gyZYoQQogRI0aI3bt3CyGEKC8vFyNGjBA//fSTyMjIECNGjBBlZWVCCCFiYmJESEiIEKLqc9urVy9RWVl5n3ekyn/+8x8xYMAAIYQQ7733nq5/QgiRlpYm2rRpU237u31f5s2bp6tOPWwl7H7f6XvJyMgQHTt2FHv27NG9lrd76623xMqVK6stu9d3Zs2aNY9d1VTSH0N9J4HSs0uhUGBqalptmaOjI02aNKF///506dKFLl260L59+7vu36pVq3u2/eKLLwLQuHFjPDw8/vI4nd9++43vv/8ehUKBsbEx4eHhrFy5knHjxgEQGBgIQLNmzaioqKC0tBQTExPd/omJidSrVw9fX18APD09admyJYcOHaJdu3Z/Op77tbd3717CwsJ0zz9kyBBWrVp13/bEXe5aNnToUEpKSigvL6d58+Z3rdjcolAoMDMz0z0eOXIkBgYGaLVazMzMiIiIoHnz5g/sV//+/bGwsAAgLCyM3bt34+fnx+XLl5k+fbpuu/Lycs6cOYOHhwfOzs64uLg8sO34+HimTZuGUqlEqVTqxt+1adOG/fv3s2TJEtLS0sjOzqa0tFS33/Dhw4GqqmDjxo05fPgwvXr1euDz7du3j6CgIGxtbQEYMGAAs2fPJiMjA7j353b//v1kZ2czatQo3TKFQsHly5cZOXIkR44cYfny5aSlpZGSkoKvry8FBQWcO3eOQYMGAeDs7Fxt7NOtiq69vT116tQhLy/vjurLsGHDWL9+Pf7+/qxbt46IiAhKS0s5fPgwN2/e5LPPPgOgtLSUc+fOERQUxJw5c9i6dSvp6emcPHmSkpISXXstWrTA0PDe/1rUajVRUVH89ttvrFixArjzcyiEwMDg/idqfv31VxITE6tVwB/Gg77Tf3Tq1Clef/11hg8fTkBAAFlZWSgUijviVSqVD/X8K1eufKTjPaXHm0zCJL1JSkqqdgoMwMDAgNWrV5OUlERCQgIff/wxnTt3JiIi4o79zc3N79n27QdwrVaLoaEhCoWi2sH+jwN/70ar1VY74Gq12mqnLm4lPLe2+eM/E41Gc9cD9t1OfzyM+7X3x398D/onBuDh4YEQgvPnz+vei1unVTdu3MiOHTvuua8QgtOnT+uSFaj6B3Mr+fgzbv8HdusfsEajwcrKis2bN+vW5ebmYmVlxYkTJ+77/t/u1nt/S2ZmJqampsycORONRkOfPn3o2rUrmZmZ1d6/22PSarUP/U/2bqdwb3/P7xW3Vqulffv2LFiwoFqsDg4O/Pvf/yYxMZGBAwfSrl071Go1Qgjde357/y5dukTdunV1fb/lj5//W0JDQ5k3bx4HDhygtLSUNm3aUFxcjBCCtWvX6pLs/Px8TExMOH36NK+99hqjRo2iY8eOtGnThpkzZ+rau9/7cvPmTSZPnowQgnXr1mFjYwNUJY/Z2dm67bKzs3FycrpnOwAbNmzg+vXr9O/fX7ds5MiRfPzxx/j4+Nxzvwd9p2/3008/MXPmTN577z1CQ0MBsLOzQwhBQUEB1tbWungdHR3vGy9UnVpVq9W0bdv2gdtKzwY5JkzSi9TUVBYvXszo0aOrLT937hwhISF4eHgwfvx4Ro0apbvCS6lUPnTyEh0dDcDp06e5fPkyvr6+2NrakpKSgkqlorKyslqCca+2O3XqxOrVqxFCUFFRwfr16+nQocND97NFixZcunSJxMREAFJSUjh8+PBfPgjfrz1/f3+2bNlCRUUFarVa9xrcj4mJCVOnTmXq1KlcuHBBtzwvL4/9+/ffM5HTaDR88cUX2NjY0KZNm7/Ul9vFxsZSUVGBSqUiOjqagIAAGjRogKmpqS4Ju3UF4qlTp/5U2+3btyc6OhqtVktFRQWTJ0/m8OHDxMXFMXHiRIKCggA4efIkGo1Gt9+tq21Pnz5NamrqQ/ezc+fObNu2TXel3oYNG7C2tsbd3f2Bce7fv5+LFy8CsHfvXvr27Ut5eTlxcXGMHDmSfv36YWdnR3x8PBqNBktLS5o1a6aLNTMzkxdffJGioqKHfn3MzMzo27cv06dPJzw8HKgaz9eiRQuWL18OQGFhIS+++CK7d+/m8OHDeHt78/LLL9O2bVt2795d7XW7F41Gw7hx43B1deXbb7/VJWBQdSXnnj17yMvL0yVo3bt3v297CxcuJDY2ls2bN+s+IytXrrxrAnb79/thv9N79uzho48+YtmyZboEDKoS265du7J+/Xqg6ph18eLFh6psHzp0CD8/vzt+SEnPLlkJkx6J8vJywsLCgKoKjYmJCW+++SZdu3attl2TJk3o06cPAwcOxNzcHFNTU959912g6kA9b968h6pgXblyhX79+qFQKJg3bx7W1ta6X+19+vTB3t6edu3akZycDFQlN1988QWvv/56tcHs7777Lh999BGhoaFUVlbSuXPnP3VZua2tLZ999hkffvgh5eXlKBQKPvnkExo0aKA7PXUv69evr5ZIeXl5sXbt2nu25+7uTmpqKv369cPc3BxXV9dqpwrvZfDgwTg6OjJ79mzy8/MpKyvD2NiY7t27M3LkSN12K1asYMuWLSgUCjQaDT4+PnzzzTcP/Vrcj6mpKUOHDqWwsJBevXoxcOBADAwMWLx4MbNnz2bp0qWo1Wr+9a9/0apVKw4ePPjQbb/++uvMnj2bsLAwNBqNbhqEnJwcJk6ciLm5OZaWlrRp06baBRLHjh1j/fr1aLVa5s+fT+3atR/q+Tp27MioUaMYOXIkWq0WW1tbvv766wdWJhs1asSsWbN48803dVWuL7/8EgsLCyZOnMicOXP47LPPMDIyomXLlrpY//Of/zBz5kxWrVqFQqFg9uzZ2NvbP/TrA1WnTNevX0+/fv10y+bOncuHH36ou/Dh1oUGubm57Ny5kz59+qDVagkICODmzZsUFxff9zliY2M5ceIEpaWlDBw4ULd8zpw5NGnShIkTJzJy5EgqKyvx9fVl7Nixf6oP93P7seNhv9OffvopQgjd8QegZcuWzJgxgxkzZvDuu+8SEhKCQqFgzpw5WFlZPTCO9PT0hzqFLj07FOJu9WlJkp44cXFx5OXl6ZLdjz76CBMTE95++209R3Z/kZGReHp68sorr+g7FB0vLy8SEhL+0qnVJ40QgiVLlnD16tVqpxUlSap5shImSU8JT09Pli1bxtKlS9FqtTRp0oQPPviAjz/++J6Vo2nTpuHn51ejcV26dOmeUwjcOuVYk+3fPsZKulNgYCAODg4sXrxY36FI0jNHVsIkSZIkSZL0QA7MlyRJkiRJ0gOZhEmSJEmSJOnBYzkmrLy8nFOnTmFvb//Qc/NIkiRJkiTpg0ajIScnB29v7z81zvWxTMJOnTrFsGHD9B2GJEmSJEnSQ1uzZg2tW7d+6O0fyyTs1hw3a9aseeCsyZIkSZIkSfp0/fp1hg0b9qfn6Hssk7BbpyCdnJxwdXXVczSSJEmSJEkP9meHUMmB+ZIkSZIkSXogkzBJkiRJkiQ9eCxPR0qSJEmS9PgqLCwkOzv7oe7l+7SxsLDA1dX1gfeDfRgyCZMkSZIk6aEVFhaSlZWFi4sLZmZmKBQKfYf0yGi1Wq5evUpubi4ODg5/uz15OlKSJEmSpIeWnZ2Ni4sL5ubmz1QCBmBgYICjoyM3b978Z9r7R1qRJEmSJOmZUFlZiZmZmb7D0BsjIyPUavU/0pY8HSlJkvSYKyhWk3q9jJvFagpLNRSWqtFoBdYWhtS2MKS2pSGu9ibY1zbWd6jSM+JZq4Dd7p/su0zCJEmSHjNlKg0HzhaSlFrMqdQSruSo7tjGQAFaUX2Zk40xzepb4NPAgrZNamFjZfSIIpYk/Vq0aBGxsbEA+Pv7ExERQXx8PJ988gkqlYo+ffowZcqUavtERETg5+fHgAEDqi0/c+YMgwcP5tSpUzUet0zCJEmSHhOXMsvYdjCPPSduUKbSYmFqwHPuFnRvZYuXqzk2VobUMldiZWaIQgHFZRoKStRVlbLMMpLSSjhyvojdx2+gNAC/prXp1caWlp5WKA2e3cqF9HSLj48nLi6O6OhoFAoFY8aMISYmhrlz57Jq1SqcnZ0ZP348e/fuxd/fn6ysLGbMmEFCQgJ+fn7V2iorK+PDDz98ZFd9yiRMkiRJz06lFrN8RyZn0ksxMlTQxcea3m1taVrP4r7JUy0LQ2pZGFLPAZo3tCSsoz1CCNKyyvn52A1+PpbP/tM3cbA2YpC/A73b2GGolMmY9HSxt7cnMjISY+Oq0/EeHh6kpaXh7u6Om5sbAKGhoWzfvh1/f3+2bt1KYGAg1tbWd7QVFRXFyJEjOXbs2COJXSZhkiRJepKZr+Lb2EziTt3ErpYR44Lr0r2lDVbmf/3QrFAoaOBkxtggM0b2dOLg2UI27c/hi81XiY7LYVQvZzp5136mx/RI/6yfj+Wz80h+jbTds7Ut3Vva3ncbT09P3d9paWnExsYyfPjwavdxdHBwICsrC4AxY8YAcPTo0Wrt7N69m/Lycnr37v1Phf9AMgmTJEl6xCrVWtbszmLDvhyUBgqGd3dkYGcHTI3/2QvWjQ0N6OxjTSfv2hw6V8TyHZl8/F06jV3NeGOAGw2cn90r3KSnT0pKCuPHjyciIgKlUklaWppunRDivj88cnJy+PLLL1mxYkXNB3obmYRJkiQ9Qhk5KuasSyflahmBz9swqpczdWo//AB6rVZQfKOMwtxSCvNKUZeWgKoEoSrFwADMLI2wsjailp05Js71MDC1RKFQ0K5pLVp7WbHn+A2Wb89k8hcpDO/uyAudHVDKU5TS39C95YOrVTXt6NGjTJ48menTpxMcHMyhQ4fIycnRrc/Jybnv5Kq//vorBQUFDBs2TLcsLCyMNWvWYGlpWWNxyyRMkiTpERBCsOvoDb7cehUjpYL3htenQ7PaD9xPXanh2oV8rpzN4crZLG5klyK0D/WEmIhTWIs87JR5ONYqxcbDhXY+bWg1sj5f7S1hxY7rJJwpZOogN1ztTf9+JyVJDzIzM5k4cSLz58+nffv2APj6+pKamkp6ejqurq7ExMQwcODAe7YxaNAgBg0apHvs5eXF5s2bazx2mYRJkiTVsAq1ls83ZrD7+A2aN7Rg6uB6953TSwhBRnIup/alc+VsDupKLQYKLbZcx119A5PKMsy0xZhqS8DCgDIbY4qslKiUUCaMKVeboq0wx6DUktwye7K09ThTCGZHi3A4sBfnypW8YK6hj3szotNdefOzQiYN8aCzz50DlSXpcbds2TJUKhVRUVG6ZeHh4URFRTFp0iRUKhX+/v6PdKzXw1IIIcSDN3u0MjIyCAwMZPfu3bi6uuo7HEmSpL+sqFTNrNVpnEotYXigI+HdHO95xWOlSk3yoask/ZbGjevFmBppcCaF2iXXqaXKR6nQIFzrcMXDjBNO+WTWVlFprMDYwAQnUyfMleaYKs0wU1aN9SpWF1NUWUhpjhpNujFWVxwwz3RAgQILZRb1SlNxqMhAKBScNa6PiV8ngkf4ozRUPsqXSHrCnD17lqZNm+o7DL3642vwV/OWh6qEbd26lS+//BK1Ws3IkSOrnTMF2LVrF59//jlarRYfHx9mzZqFsbEx165d4+233yYvL48GDRowd+5cLCwsHjo4SZKkJ1lmvor3V6RyPb+Cd4bUo2sLm7tup9UKziVc4WBMMmXFFdhaluGrOIZ1QSYGWoHS1YErbb3Z53iFHMObWCjVNLduQ2dLD9wtGuBsWhcDxX0G9TcFlUbF5dI0UjIvkn4kn4IkK0o0fpypVUJdo9M0yU3DcO8lThzYRN0eXakTGICRzd3jlSTpn/HAJCwrK4v58+ezceNGjI2NCQ8Pp127djRq1AiA0tJSZs2aRXR0NHXq1GHKlClER0czZMgQZs6cydChQwkODuaLL75g8eLFvP322zXeKUmSJH1LvlLKjJWpaLSCT15piHeDuw/uvXYhj7gNZ8jNKMTBtpLnjfZgfP0mCoUBZq1bkPi8EbuME4FCmtX2pp9dB5rV9sHI4M/Nhm+iNMHTygtPKy9oDOWV5cQdPcz5n8vJzGpLul0zrK1P0/TqNW7EbKFg+zZsAgKoExyM4V3mU5Ik6e97YBIWHx+Pn5+fblKzXr16sX37dl5//XUAzM3N2bNnD0ZGRpSVlZGXl0etWrWorKzk8OHDfPHFFwAMGDCA4cOHyyRMkqSnXvKVUqYvu0gtc0M+fLnBXQe9q0or+e2HU6QcuYaFlZI2VgewykhDaJSYP+/DmUBndlbGo9Zq6Gjfmd5OwVgb/3PJkKmRKd39OhPYTpCcdJm4rYmUXm1LnF0BZi0P43O2AnbvpmDvXmy6dcMuOBhDK6t/7PklSXqIJCw7O/uOCc8SExOrbWNkZMTevXuJiIjAwcGBTp06cePGDSwtLTE0rHoKe3t73URpkiRJT6tzl0v4v28vUcvCkDljPbC3vnMAfubFfHatPEHJzXJ8PApxPB+LptQAY1dXKgYFskSxixuqZFrZtCGkbj8cTO99af3fpVAoaNLcHS+fepw9cpl9G5JQH+vOr01ScWp+ki4ZruTv2EHBvn04DhlC7c6d5USvkvQPeeDMgFqtttoX7l4Tnvn7+3Pw4EECAgL44IMP7rqd/OJKkvQ0u5WA1b5HAqbVaDn003k2fZaAARq62u3DPjEWrcqQOkMHc2ycLwvV6zAyMGKqVySjG46r0QTsdgqFgufauDNqRi+ada6H3bkGlCb25r9NykjrY4exsyOZ337L5U8/RZWZ+UhikqSn3QOTMCcnp/tOeFZQUEBcXJzucWhoKMnJydja2lJUVIRGo7nrfpIkSU+T8xmlugTs07skYOUlFWz54iBHtqfg0diEdoVr4FImxo6OmL83ma9cDvBLzm787QOY9tx7NLD00Es/TMyM6Dq4OQOndqKWeW3q7u7IoYK6rOp4GZOwrpRfvkzqe++RGxOD0D7MhGWSJN3LA5OwDh06kJCQQH5+PmVlZezcuZMuXbro1gshePvtt7l27RoA27dvp2XLlhgZGdG6dWu2bdsGwKZNm6rtJ0mS9LS4mlt1FaSV+d0TsILsEjb8J57rlwro2FpFg6QVqAvAtmc3iqYOYf6NJZRpynjd8w0G1xuKsYGJnnryP47u1gyf3g2X5s7YJ3lh+VsXFlsfJWt4MyxbtCDnxx+5smAB6uJifYcqSU+sByZhjo6OTJkyhZdeeol+/foREhJC8+bNGTt2LElJSdjY2PDhhx8yfvx4+vbtS2pqqm7w/YwZM1i/fj1BQUEcOXKEN954o8Y7JEmS9CjlF1Xy7reXEAg+ernhHQnYtQv5bPjPflSlFXRrcgHT36LRqI1wmfgqJ7vZsyTtG5xNXXin6bs0rdVMT724OyNjJf3GtsKrT1MM8+yov7UbMfkZxLRMx2boIErPnCH1/fcpvXBB36FKz7hFixYRHBxMcHAwc+bMAaouLAwNDaVnz57Mnz//jn0iIiLYuHGj7nF0dDSdOnUiLCyMsLCwu+7zT3uoecJCQ0MJDQ2ttmzJkiW6v7t370737t3v2M/FxYVVq1b9zRAlSZIeT6UqDe+vSOVGsZpPx3rgal+9gpVy5Cq7V5+klp0Zfua/UnEwDQNzc1zefodofuPA1f20smnD8PqjMDa49wz6+hYY1BADa3MOrTtJ/Z0dyGh/nC8abGXslJepWB5N+ief4Dh0KLaBgfoOVXoGxcfHExcXR3R0NAqFgjFjxhATE8PcuXNZtWoVzs7OjB8/nr179+Lv709WVhYzZswgISEBPz8/XTunTp0iMjKSkJCQRxa7vG2RJEnSX1Cp1vLR6jRSr5fxwUsN8HIzr7b+bMIVfvk+kboNrXm+fBOlSTmYONrhFDmNZTmrOVd0hj7OIQQ5h95/otXHREAHJ8qEgsM/JFE3vhUFN8357PkVvDJpFFYbD5G1ahXqGzewHzhQXoT1jFEl7abi5K4aadvYtwcmPvdP7u3t7YmMjMTYuOqHjIeHB2lpabi7u+Pm5gZUFZO2b9+Ov78/W7duJTAwUDf11i1JSUmkpaXx9ddf4+XlxXvvvUft2g++v+vf8fh/8yVJkh4zQggWb7nK8QvFvDHAjTZetaqtPx2Xzi/fJeLW2JbWJespPZeDeYO6OH8wkyU5K0kuOstw91GE1A17IhKwW4I6OlK/93OkG5pjfbopLntb8uVZUoStAAAgAElEQVT1laQNaIx1167kxcSQuWwZQq3Wd6jSM8TT05MWLVoAkJaWRmxsLAqF4o7ptW5NkzVmzJhqN+u+xd7entdee40tW7bg7OzMrFmzajx2WQmTJEn6k7bE57L9cD5DujrQo5VttXWJe1OJ+/EM7k3t8MlZRVFqCRae9bCfGsFXaV9ysTiFl+qPpq2d3z1af7yN6OnMrKxyziVdpcmVenjtUrKu52YCO3WiU+0wcjdvRl1YiOvEiRiY6P8CA6nmmfgEPrBa9SikpKQwfvx4IiIiUCqVpKWl6dbda3qt292aXB6qErUePXrUVKg6T85PMEmSpMfA0fOFfPPTNdo/V4uXejhVW3fy16oErIGPPc1zVlOSWoJlUw/qTI1gceoXXCq+wKgGY57YBAzAwEDB20PcUbnYc97SFoMsF3xiW7M7fz+/NL+J40svUZKUxJV589CqVPoOV3pGHD16lFGjRvHWW2/Rv3//B06v9UdFRUWsWLFC91gIgVJZ8zeyl0mYJEnSQ7qSXc4n36fj7mjK24PrYWDwv1/W5w5msH/DGRo0d8Anby3FqcVYNvPA4c2pfJ32JWklqbzccBytbdvqsQf/DAtTJTNGNOCqqRVX7e3R5LrQfFsrfstLYGf9yziPH0fp+fNkLFyItrJS3+FKT7nMzEwmTpzI3LlzCQ4OBsDX15fU1FTS09PRaDTExMTcd5osc3Nzli5dysmTJwFYvXr1I6mEydORkiRJD6G4TMPM/6ZiZGjAjJcaYGbyv1/JqYnX+eW7RFy97PAtieZmcj4Wnm7UfXMay9K+5mJxCqMajKGlTSs99uCfVbeOCZEvuvPeiks4eNaFFPD9CeKC49E6CHqPGknW8hVc++orXF57DcUjqCpIz6Zly5ahUqmIiorSLQsPDycqKopJkyahUqnw9/end+/e92xDqVSyYMECPvjgA8rLy6lfv75uqouapBBCiBp/lj8pIyODwMBAdu/ejaurq77DkSTpGafVCmatTuNIciFRYz3wrm+pW3c1JY+YxYewc6lFR6tfKUg4j6mLPfVmfMy6zLXsz93HILdwujrof8xMTfjvrut8vyeLsc2NuR5/CROHSxzrk0gHu470Pu9M9vffU6t9e+qOHYvCQJ58eRqcPXuWpk2b6jsMvfrja/BX8xb5jZAkSXqAdb9mc/BsIWOD61ZLwLIv32TbN0eoVcecTi5JFBw4j3GdWri/9xGxubHsz91HL6egpzYBAxjWzZFm9S1YfU5N0wAPVNkNab27EfH5+0nwLsd+wAAKExLIXrtW36FK0mNHJmGSJEn3cSS5kFU/XyeghTV929fRLS/KL2Pb14cxMTMisFU+BbviMbQ0pd77s9lfdIDYzBg62HUitG4/PUZf85RKBRFD6qFUKoi+qqBJezfKMrzxTahL7PUYzvnVxqZHD/J37qRg7159hytJjxWZhEmSJN3D9XwVn667jLujKZP7u+ouca8oq+Snrw6jrtDQo7cZBRs2ojA0xP3dmVwgg/WXv8e7tg/h7sOfiYlLHayNeWOgGynXyrlgZYe7twOa5DZ4Jdmx9soacno/h4W3N5n//S+l58/rO1xJemzIJEySJOkuKtRaZq9JRwjBe8PqY2pcNbBcq9GyY/lxCrKK6T7QlZLVX6JRK3Gd8iY3asOyS1/jZOrMyw3GoVQ8O4PROzarTYifHdHxuTj5e2JfrzYmxzrgdtmcZenfoB4ZhLG9PRkLF1KZm6vvcCXpsSCTMEmSpLtYuu0aF66VMXVQPerWqZp0VAjBvh9Pc+VsDp36N4If/0NlqQHOI15E4dmAry4sQqlQMqHR65gqTfXcg0fvlT51cbEzZuGWTLq93ApTK1Mc9/lR6yZ8c3UJtV4bhVCrufLZZ2jLy/UdriTpnUzCJEmS/mBfUgFbE/Lo37EOfs/9795xib+mcTruMs8HNsBm/xeU5WqxC+yEVUAgSy99TV5FLmM9XsXOpM59Wn96mRob8MYLbmQXVLB2fz69xrShXGNFs+3NUVWUsKI0GqdXx6PKyCBz5Up9hytJeieTMEmSpNtk5qtYsOEKXq7mvNzbWbf8yrlc4qPP0KC5I40KfqIw5SaWXu7YD3+FjRk/klx0lhfrjaCRpaceo9c/7/qW9G1fh60H8sgWRnR6wZu80np03FmPtJJLbKt9ijr9+lGYkMDN/fv1Ha70lFi0aBHBwcEEBwfr5veKj48nNDSUnj17Mn/+/Dv2iYiIYOPGjbrH2dnZjBs3jn79+hEeHk5GRkaNxy2TMEmSpN9VqLV88l06BgoF04a6Y2RYdYi8mVPCzuXHsHGywq/RNfJ+S8LYxhyXt/6Pw/kH+TV7N90cutO+Tkc99+DxMKqXE862xszfcAWPti40butCdtbztDtqTVzuXi60t8Xcy4vrq1ZR8ftNlSXpr4qPjycuLo7o6Gg2bdrE6dOniYmJYfr06SxevJht27Zx6tQp9v5+dW5WVhYTJkxgx44d1dqJiIggICCATZs2ERYWxty5c2s8dpmESZIk/e7b2ExSrpYx5QU3HG2MAagoVxO75AgA3YNrk7v2BxRKJW6R73NNncV36avwtGxMP9cX9Bn6Y8XUWMmUF9y4nl/Bih1ZdB3ig52zBarTHfC4bsbajO8QI4LBwICrX32FUKv1HbL0BLO3tycyMhJjY2OMjIzw8PAgLS0Nd3d33NzcMDQ0JDQ0lO3btwOwdetWAgMD6dOnj66N/Px8zp07R3h4OAADBw7kjTfeqPHY5W2LJEmSgP2nb7I5PpewDnXo0KxqHJjQCnavOsGN68UEjfamaMUM1ColrpMmoLazYsnZ2VgYmjO64fhn6krIh+HTwJLQ9nZsPZBLt+dt6D22Des+2YvrL97kDTrBtze+Y/LIYeR8uYScjRtxGDxY3yFLf9HBvHgScmvm1HL7Oh1pZ9fhvtt4ev5vCEBaWhqxsbEMHz4ce3t73XIHBweyfq+6jhkzBqi66fctV65coW7dukRFRXHkyBHs7e157733/smu3JWshEmS9My7nq9iwY9X8HQx45U+/xsHdnTnBVITs2jfrwlGsfMpvwF1enfDomUbVqQu40ZlPq80nEAto1p6jP7xNbKnM9aWhnyxOQNLO3M6veBNrsqFjjttya/IZ5tjMtb+/uTFxlJy5oy+w5WecCkpKYwePZqIiAjc3NyqzdEnhLjvnH1qtZozZ87g5+fHhg0bCAwMJDIyssZjlpUwSZKeaZVqLZ98n45AVBsHduVcDoe2ncezdV3q5e0gK/kGFo3cqDNkBNuv/8TpwiSGuA2loaWHnnvw+LIwVTIuqC6frrtM7KE8gtu7kZZ0ncun29Lp7G72NU3Au89oap87R+by5TT86CMMTEz0Hbb0J7Wz6/DAalVNO3r0KJMnT2b69OkEBwdz6NAhcnJydOtzcnJwcHC45/729vZYWFgQEBAAQEhICB999FGNxy0rYZIkPdOWb8/kfEYZUwa64WxblQAU3Shj18oT2DpZ4udbRs6OBAwtTKj75nTOF53jp2tbaGPrR2f7rvoN/gng72uNb0NLVu64zs0SNQFDfTExN0ZztBVuZeZ8f30tlsNfoDInh5zoaH2HKz2BMjMzmThxInPnziU4OBgAX19fUlNTSU9PR6PREBMTQ5cuXe7ZRr169XByctIN3v/ll19o1qxZjccukzBJkp5ZCWduEr0/l9D2dnT0tgZAo9ay89tjaNRaegyuT863X6HVKHGdMpUSo0qWpy7FwdSR8HrDnolbEv1dCoWC18JcKK/Usiw2EzMrEwKGP89NtR0+2x1RaypYb7KP2v5dyN+xg7K0NH2HLD1hli1bhkqlIioqirCwMMLCwti4cSNRUVFMmjSJoKAgGjZsSO/eve/bzsKFC1m6dCkhISH897//5eOPP67x2OXpSEmSnklZNyqY98MVGtU1Y0xQXd3y+OgzZKUV0HOUL+VrP0ZVaIBD/xBMPBrxTco8yjXlTG785jM5I/5fVc/BlAGd7Fm/N5terW3x9nbkuQ6unIkXdDuey/bnz5Ic0A/Xk7XJ/PZbGrz/PgpD+e9Jejjvvvsu77777l3Xbdmy5Z77RUVFVXvcsGFDVq1a9Y/G9iCyEiZJ0jPn1jgwragaB2b8+ziwlCNXSfotHd+ABtidX0/hhRIsGtfHtu9AYjNjOF+UzJB6Q6lr5qLnHjx5XuzmgIO1EYu3XEWjFXTo9xwWVoYUnfalaVltNuf/hFl4X1SXL5P3h/mbJOlp9VBJ2NatWwkKCqJnz56sWbPmjvU///wzYWFh9O3bl9dee42bN28CEB0dTadOnXTlwbvNWCtJkvSordh5neQrpbwx0I26dlXjwPIzi/jl+yScGtrQon4m2buPY2hhisu/3ia56CyxmTG0s2svJ2T9i0yNlYzu40zq9XJ+PpaPsZkRXcJbUKCuw3M7zVCiYKPtCSxbtSJ30yYqrl/Xd8iSVOMemIRlZWUxf/58vvvuOzZt2sS6deu4cOGCbn1xcTEffPAB33zzDVu2bMHLy4uFCxcCcOrUKSIjI9m8eTObN29mypQpNdcTSZKkh3DwbCEb9+UQ4mdHZ5+qcWAV5Wq2LzuKkYmSwH7OZC1fjlajxGXKWxQbV7IidSmOpk4McRum5+ifbF18rGniZs7KndcpU2lo0NyJBj72pBS0pluyGclFZ8kMboLC0JDr332n73AlqcY9MAmLj4/Hz88Pa2trzM3N6dWrl27WWYDKykpmzJiBo6MjAF5eXmRmZgKQlJREdHQ0oaGhTJ06VVchkyRJ0ofsggr+88NlGjqbMvb3cWBCCH75LpGb2SX0GOFNyX8/QVVkiH1YCKYejVh+aSkqrYoxDSdgopTTJ/wdCoWCccF1uVGk5sffqqYP6Dy4OQZGhpQfaUR9YcuPhduwCulFSWIixSdP6jliSapZD0zCsrOz7znrLICNjQ09evQAoLy8nG+++Ybu3bsDVfNuvPbaa2zZsgVnZ2dmzZr1T8cvSZL0UCrUWj5ek45aK5g+tD7GRlWHv8S9aVw8nkm7EC/MDy/jZqoKi8YNsAsbyLbMraQUJzOk3jCczeo+4Bmkh9HU3YIuza3ZsC+bnJsVWFqb4hfWjKwKN9r+rKRcU8Yur2yMHR3J+v57eUsj6an2wCRMq9U+1KyzRUVFjBs3jiZNmtC/f38AvvjiC1q1aoVCoWDMmDHs27fvHwxdkiTp4S3ddo3kjFLeesENlzpVFa3MS/kkRJ+lvo8jTazOkLsvGaWFGS6T3+Jc0Vm2Z/6En10H/PQ8EeXTZnRvZ7QC/ruzatyXdyd3HF3NuZDZEv98ew7dPIyqbwcqrl8nf/duPUcrSTXngUmYk5PTA2edzc7OZujQoXh5eTF79mygKilbsWKFbhshBEqlvLeaJEmP3q8nb7A1IY8Bnex184GVFqnY+e0xLG3N6NLDkuvfrUWjVuLyrykUGatZkboUJ1NnhtQbqufonz6ONsaEdajD7uM3uHC1FIWBgi5DW6LSmlJrjykOShvWWR3A3LsZuZs2oS4s1HfIklQjHpiEdejQgYSEBPLz8ykrK2Pnzp3VZp3VaDRMmDCBPn368H//93+6Kpm5uTlLly7l5O/n9FevXq07bSlJkvSopGeV89nGDJ5zN+fl3lX3hdRqBbtWHKe8tJKew5tQuOJTVEXG1AkLxdSzEctTl1ChVfFKw/EYG8hxYDUhPMARK3Ml326vGkNs71abpn4uXChuTveTBuRW5nKhhxtalYqcjRv1HK30uFu0aBHBwcEEBwczZ84coGpMe2hoKD179rzr7AwRERFs/P2zlZeXp5vJISwsjG7duvH888/XeNwPnA3P0dGRKVOm8NJLL1FZWckLL7xA8+bNGTt2LJMnT+b69eucOXMGjUbDjt/ndvH29mb27NksWLCADz74gPLycurXr697YSRJkh6FMpWG2d+lYWpswLQX62OorPqReOinZK6ezyNgqA+Gvywk77IWc08P6vTtz5Zrm7hQfJ6R9V+R48BqkIWpkiH+jizZdo3ES8U0b2hJu77PceHoNXKS3PBpbk6MNo43AjpRsGcvNgEBmLq76zts6TEUHx9PXFwc0dHRuuFPMTExzJ07l1WrVuHs7Mz48ePZu3cv/v7+ZGVlMWPGDBISEvDz8wPAzs6OzZs3A1XDsEaOHPlIZnR4qCmJQ0NDCQ0NrbZsyZIlAPj4+HDu3Lm77te6dWui5b3AJEnSAyEEn23M4GqOitmvNKRObSMA0pKyOLbzIk3bu+GuiiPj4GWU5pa4THqD00Wn2Hk9lo51OtPWzk/PPXj6BfvZsTEuh5U7M5k7vhHmVia0DvIiYTO0+uUKZ7tq2NeqgjYHzMn+8UfqvfWWvkOW7qJg/35u/vZbjbRdu0sXrDvef24+e3t7IiMjMTY2BsDDw4O0tDTc3d1xc3MDqvKY7du34+/vz9atWwkMDMTa2vqu7W3YsAEzM7M78p6aIGfMlyTpqRRzII+9iQWM6OFECw8rAG7mlrJ71Qns3WrRrnUlWRu2oqk0xOX1f3HTpJKVqctwNXNjkNuLeo7+2WBiZMDQQEfOpJdyOLkIgOZdG1LLWknKZW+6VNQjoewoBt39KElKojQ5Wc8RS48jT09PWrRoAUBaWhqxsbEoFIp7zuwwZswYBg0adNe2NBoNX331FW89ooRf3pxLkqSnzrnLJXzz0zXaelkx2L/qQqLKCg3blx4FoMcgdwqWTaO8yIQ6fUMx8fLki+Q5aIWWVxpOwMjASJ/hP1N6trLlx73ZrNyZSevGVigNDeg0+Hm2fXOE+ttTqNW/Fls80gi1rk32Dz/gftvYY+nxYN2x4wOrVY9CSkoK48ePJyIiAqVSSdptN4O/18wOf7Rv3z7q16+Pl5dXDUb6P7ISJknSU+VmiZqPv0vHrpYRUwfXw8BAgRCC39YlkXetkMARPmhi5nLzqmHVOLB+/dl09UfSS1MZXn8UDqYOD34S6R9jqFQwvLsTlzLLiTtVNaG3u7cDrg0tOJffnF7Z9lyqvExRoA9lFy7ICVyluzp69CijRo3irbfeon///g81s8Pd/PzzzwQFBdVkqNXIJEySpKeGRiv497rL3ChWM32oO1bmVcX+0/vSST50lTa9PbFL/YG8xHyU5ua4vD6Z4zeP80v2bgIcAnneppWee/Bs8ve1xt3RlP/uuo5GU1Wx6DDoeSqEKWJPJe4mLmx0PYuRgwM5GzYgtFp9hyw9RjIzM5k4cSJz584lODgYAF9fX1JTU0lPT0ej0RATE1NtZod7OXHiBK1bt67pkHVkEiZJ0lNj+fZMjqYU8VpfFxq7mgNwPfUGcRvP4N7MAW/nVHJ3JaBRG+Ly+mTyTVSsSVtBfYsG9HN5Qc/RP7uUBgpe6uHE1VwVe07cAKCOa20a+dpxvsSHwPPGFGgLyQxoiOrKFQoPHtRzxNLjZNmyZahUKqKionRTTGzcuJGoqCgmTZpEUFAQDRs2pHfv3g9s68qVKzg5OT2CqKvIMWGSJD0Vdh/LZ8PvN+bu09YOgNJCFTuWHcXSxoyuvWqR//W/KS8yp07//hh5ebD03CcoFUpeaTgeQwN5ONSn9s/VwqOuGWt/yaJbCxuUSgXtwny4mJhL/kElzbwasdnpNBPcXMjZuJFabdqgMJTvmQTvvvsu77777l3Xbdmy5Z77RUVF3bHs5CM+3S0rYZIkPfGSr5TyWXQGzRtaMD7EBQCtRsvO5cdQ/T4ha9kPURRmmWHetAl1QkP58cparpZl8FKD0dga2+m5B5JCoeDFbo5cy6tgb2IBALXtLXjOry4XSp+jY6Kacq2Ki13rUpmTQ0FcnJ4jlqS/TyZhkiQ90fIKK5m1KhU7KyOmD/3fhKwJW85x7UI+/uHemMR/QX6KGkOrWri8+hqHbhxgf+4+ejr1wbt2cz33QLqlfdNa1HcyZe0vWWi0AoDWwc+hVCrIOGZOa7Pn2GadhFH9euTFxMibe0tPPJmESZL0xCqv0DDzv6mUqrS8/1J9altUnZ66cOwaJ/ek4tPFHbeyveQdvPj7OLBJXDO8wffpq/G0bExI3TA990C6nYGBghcDHLmSoyLuVFU1zKK2Kc271ie9vDGtDpWAQsHZ9rWozM3lZkKCniOWpL9HJmGSJD2RNFpB1NrLXLxWxjvh9WjgZAZAfmYRe9Yk4tTAhtbNbpIfE42q2AT7F15A08CZby4uxtLQilcajkepUOq5F9IfdfSujZuDCWv3ZKP9vRr2fE8vjI0FF0/Z0NHUhx12ySjd6pIbE4PQaPQcsST9dTIJkyTpiSOE4OuYqxw8W8iEUBf8mtYGoKKsku1Lj2JkYkhgWB2KflxAUa4VFs19sO7dg2WXvqa4sohxHq9hZVRLz72Q7kZpoCC8qyNpWeUknKmaN8zE3Ijnuzfimsod7/35mChNSfIzpzIrS14pKT3RZBImSdITZ9P+XLYm5DGgsz2h7esAoNUKdq08QWFuKT1e9EQb8zEFGeYYWltTd9x4Nl2LJqU4mRfdR1DPQt4I+nHm39waFztjvtuThRBV1TCfgEaYGAvOJ9vQ1aQ5exzTMKjrSO7WrXLeMOmJJZMwSZKeKPuSCliy7RodvWvzSm9n3fKDW8+RfjqbTgOaUOvYIm6kVKJRK3Gd+DpHVYn8kv0zAQ6BtLNrr8fopYehVCoYEuDIpcxy3T0ljU0N8e3uyTVVfTz3X8fM0IJTfpZUZGZSdOSIniOW9G3RokUEBwcTHBzMnDlzAIiPjyc0NJSePXsyf/78O/aJiIhg48aNuscZGRkMGzaMsLAwRowYwdWrV2s8bpmESZL0xDh6vog56y7TtJ45b/9+SyKA5EMZHP/5Es061aNB0RZuJqahKjbCMTycq06C79JX0djKi/6uckLWJ0VACxvsaxvxw95s3bLmXRtibCxITrahq6kvvzino3CsQ+6WLbIa9gyLj48nLi6O6OhoNm3axOnTp4mJiWH69OksXryYbdu2cerUKfbu3QtAVlYWEyZMYMeOHdXa+eyzzwgODmbz5s33TNz+aTIJkyTpiXAmvYQPV6dRz8GEmSMbYmJUdfjKSrvBr98n4eJpR+u6pymM30txngW12rdH3cWXby4sxtbYjrENX0WpkJN7PikMlQr6d7LnVFoJZ9NLADA2M6JFNw+uqhrgGZ+FqZEFZ/1qocrIoPj4cT1HLOmLvb09kZGRGBsbY2RkhIeHB2lpabi7u+Pm5oahoSGhoaFs374dgK1btxIYGEifPn2qtaPVaikuLgagrKwMU1PTGo9dHpEkSXrsXcos4/0Vl6hTy5CPXm6IpVnVVY1FN8qIXXIUC2tTunYooTTmO25m18HE3Y3aI4Yw7+J/AMGrjSZhbmih305If1rvNrZ8vyeLH37L5v0RDQDw6daIE7svcu6MJV07Pc921zia2lmTFxuLVSt57099OHcwg3MHrtRI20383GjSzvW+23h6eur+TktLIzY2luHDh2Nvb69b7uDgQFZWFgBjxowBqm76fbt//etfhIeHs2rVKiorK1m3bt0/1Y17kpUwSZIeaxk55fzft5cwM1Hy8RgPbKyMgKorIX/66jDqCg09gq1Q7/icghx7DEzNqTvpNb7N+JZcVQ5jPV7FwdRRz72Q/gozEyWh7euQcKaQy9nlAJiYGeEb0ICrqoZ4xedgamTB+da1KLtwgdKUFD1HLOlTSkoKo0ePJiIiAjc3NxQKhW6dEKLa47t55513mDVrFvv27WPmzJm8/vrrugtDaoqshEmS9NhKzypn2tKLAHw8uiEO1sYAaDRadiw/TsH1Yvq86I7xrzO5kWuHukzg9vZEfiyOJbnoLMPdR+Fp5aXHHkh/V98OddiwL5sff8vmzRfqAdA8sDEnf0nl7ClTAjq2ZmeDvXhamJO3bRvm//qXniN+9jRp5/rAalVNO3r0KJMnT2b69OkEBwdz6NAhcnJydOtzcnJwcHC45/75+flcunSJ7t27A9CrVy9mzJjBjRs3sLW1rbG4ZSVMkqTHUur1Mt5ZchEU8OlYD9wcqsZnCCHYt/4UV87m0LmvO7WP/JuibFNUN7Q4vvgiu2udJSFvP72dgmlfp6OeeyH9XbUtDOnZ2pZfThSQc7MCqJo3zLuLOxmqhjQ5lI2RqQVpLWtTfPw4qmvX9Byx9KhlZmYyceJE5s6dS3BwMAC+vr6kpqaSnp6ORqMhJiaGLl263LMNGxsbTExMOPL7lbZHjx7FwsKiRhMwkJUwSZIeQxevlTF92UWMDA2IGuOBq72Jbt3xny9xJv4Kz3d1wTVlASWZKkqyTbAJDORkcwU7M2LpWKeLvCXRU2RgZwd+OpjHprhcxgbXBcA3sDEnf03n/ElBV782/Oz1K2MOGJEXG0vdV17Rc8TSo7Rs2TJUKhVRUVG6ZeHh4URFRTFp0iRUKhX+/v707t37nm0oFAoWLVrEhx9+SHl5ORYWFixcuLDGY5dJmCRJj5Wz6SW8vzIVM2MDosZ6UNfufwlY8uEMDmw5h4evPc/lL6Uss+D/2bvzuCjPe///r9kYmIFhH3ZQRFAEVNxwX3CPS2JMs9am2ZqkaRPbpM3plqSnPe1p05hf2iRNmrTZ98QF4467oKiooKKAIKvs+zADs9y/P8gX60miNlEH4fN8PPp4lGtm7rxvE2be3nPd10XrOW+MyUlUzI/jk/J/Msovldui77zk/A9x/Qjx92B6ih8bcxq5fVYI3l4avHz0DB8fzslsFwuOnSVzsCc1o3wgK4vgZcvQ+fu7O7a4Rn71q1/xq1/96isfW7du3de+7t9LG0BKSgoff/zxFc12KfJ1pBCiz8g60cqTr53BZNDwpwcuLGBnj9ey/Z08wuP8GK/5mO5zVbTW+KMPC6f9zhm8Vf4mQ70TuHvwfahV8tbW3yybGoy128XmQ429Y6PmDUNRqSk+aGGK73i2Dm8Al4vmraRoIUcAACAASURBVFvdmFSIyyfvVEKIPmF9dgO/f/csg8O8+MuDQwkNOF/AzpU0seWfuQSGezPVbyPOytO0NEag0nvSdd8NvFr9GhFeEfwg7mF0ap0bz0JcLXHhBpIHG1mX1YDT2XPHminQQFxyAGcswxlT1IXFT0vzCDPNO3bg7Ox0c2IhLk1KmBDCrVwuhX9tOseL66oYN8zEH+8bgp/3+ZkSjdVtbPj7QYy+emYEb4GKPFpaY3F1OXA+sJRXmt8hxDOUR+JX4qUxuPFMxNV24+Rg6lrsZH2xsTdA6g1JOBQdFXtrGe83jsykFlxWKy27d7sxqRCX57JKWEZGBgsXLmTu3Lm8++67X3p827ZtLF26lCVLlvDwww/T2trzC1JdXc2dd97J/Pnzeeihh7BYLFc2vRDiutZhdfLMW6V8tKuOheMD+fWdg/D0OP+21FJnIePFHLQ6NTPDd6A9d4w223Dsze247l3CK92fYvYM4cfxP8Fb6+3GMxHXwoThJkIDPFiz7/zSA4HhJqLjjJxuHcbkai21wQqdMQE0b92K4nS6MW3/5hrA20RdybXDLlnCamtrWbVqFe+99x5r1qzhww8/pLi4uPfxjo4Onn76aV599VXWrVtHQkJC7x0FzzzzDHfccQebNm0iKSmJl1566YoFF0Jc38pqbTz6YiGHi9r54ZIIHrkxAo3m/GT61noLa/+6H5fTxcyoPXg2HKNdGY2tqg6+ewOvaNYT7Gn+ooD5uPFMxLWiUau4cVIQJ8s6OV1x/uvGMYtT6Fa8qMksI9VvDPuSOrE3NtKem+vGtP2X0WikqqqK7u7uq76YaV+jKAqNjY1XbEujS94dmZWVRVpaGn5+fkDPAmabNm3ikUceAcBut/PUU08REtKzInVCQgIZGRnY7XYOHjzIiy++CMCyZcu46667eOKJJ65IcCHE9Wt3XgurPq3AS99zB2TSoAuvYrU1dLL2r/txdDmYHbUT7+aTWHQT6DxdRPfN03jdtIUQz1B+PPSnUsAGmDljA3hraw1r9tXz89tiAAiLDSAkXMfp2jimt2pYNcjBjAAjTVu2YBo3zs2J+5/IyEgaGhooKyvD4XC4O8415+npSWTklVmc9pIlrK6u7kv7L+Xl5fX+7O/vz5w5cwCw2Wy8+uqrfPe736W5uRlvb2+02p5/RHBwcO++TUKIgclic/LK+iq2Hm5meLSBX945iEDThRPp2xp7CpjdamdWyEZ8bFV0ek2i42gBHfNG8Wb4fmKNQ3hwyCOyH+QAZNBrmD8ukLVZ9dyzIIxg355dFEYtSGbz67l0bjtI4k0p5CYXMGFXEdaSErxiY92cun9Rq9WYzeaLrkAvLs8lv450uVyXtf9Se3s7DzzwAMOGDeOmm276yufJuj1CDFwnyyw88kIhmbnN3D7TzJ8eiPtSAWtt6GTtC/vpsnQxM2ANftpGrJ6TaT9aQFP6cN6IP0GSbwqPDF0pBWwAWzIpCEWB9dnnl6sYnBKKj0lFQU0kM5zRHB1mx6XX0bRlixuTCnFxlyxhoaGhl9x/qa6ujjvuuIOEhAR+//vfAxAQEEB7ezvOLyZGXmrfJiFE/2TrdvGvTed44pWeuaR/eiCOFXPD0Gou/EtZY3Ubq1dl0W2xMsP3UwL8XHTq02g7fIzq6TG8l1hMWuBk7h/yEB5qD3eciugjQvw9mDjClw05jdi6ez5j1GoVKekJNNjD8Nx1glC/GIqT9LQdPIi9qcnNiYX4apcsYZMmTSI7O5umpiasVitbtmy5YP8lp9PJgw8+yIIFC/jlL3/Ze7VLp9MxduxYNmzYAMCaNWsuum+TEKL/yTnVxoPPn+ajXXWkp/rztx/HM2LQl69g1ZQ2s/r5bOjuJN3nfczR/lhUo2g7cIjCyYF8llLNgrBF3BXzPTQqjRvORPQ1N00OpsPqJPNIc+/Y8Ekx6HQKJ4uNzPAcRfYIG4rLRXNmphuTCvH1LjknLCQkhJUrV7JixQrsdjvLly8nJSWF+++/nx//+MfU1NRw8uRJnE4nmzdvBiApKYnf//73PPXUUzz55JO8/PLLhIWF8dxzz131ExJCuF9dSzf/+LyavcdbiTLr+d/7h5AS+9VLSJQX1LPpH4fwUluYYfoE/7HTaDptw3Ish2OTDBwYY+XewQ+S6j/mGp+F6MsSYwwMjfBizb4GFowLRK1W4eGpJXFiFHm7FcYcOosmIYC6eBuanTsJWrIEtV5/6QMLcQ2plD54f2llZSXp6elkZmZesTsQhBBXX5vFwYe76sjIbkAF3D4rhJunBqPTfvVF95PZ5ez6IB9fXQszAj/Hb/Z3qdt8mM4zxeyZoaMqNZAfDHmECIO8D4gv23G0mT99WM5v7x7MuAQTAO1Nnbzz1HYSvPNwPDScnGPruflTJ6F3343/jBnuDSz6rW/aW2QDbyHEt9bZ5SQju4GPd9Vh7XKRnurPXbNDMft99dwtl0she/UJju0sI9SjnKmDjuE9+6dUvfUxXbW1bJ6vQTt6OD+LvV+WoBBfa0qSL69v1LJ6b31vCfMJMDB4hD9nTg5jSXErmyI8sYRC87Zt+E2fLjeIiT5FSpgQ4htr6bCzNquB9dmNdNicTBhu4u65oQwK9fra13TbHGx5dR/lRR0MNeSRNtWIesgjnH3pZbptnWxcomXMhOWkh8yRjbjFRem0ahZPDOKNzTWU1dqICelZQHPUvERKTrRwds9ZJt09mZzE7czcXknn6dMYhw1zc2ohzpMSJoT4j52tsbJ+fyNbDzdhdypMSvTllulmEqIuvndjU1Ujm17aS2ubmrFBhxl1+3xaqjuof/YvtHsrZN8Rwh3jHybaEHONzkRc7xaMC+T97bWs2VfPo8uiAAgd7I85zIPTdfHMbvDkT/EqpmXraN62TUqY6FOkhAkhLkuX3cWe/BY25jRysqwTrUZF+mh/lk8LJjL44lt4KIpCQcYu9m5rRaOyM3t0HYOX/ZCCT95GuzePyigV7XfO4OGht6PXyORpcflMRi3powPYmtvE9+aG9W7+Pmr+CLb86whNOw6RfNNYTiQeJiU3F3tTE7qAADenFqKHlDAhxNdyOhWOlXSw81gz+4630tnlIiJIz/0Lw0lP9cfXeOm3EFv5aXa/mUVxnZlgQytzvpuM1XcEh/78NL5VForG+ZL03R8Ra4q7Bmck+qOlk4PYkNPIhgON3JHes4Ve7MhQvL3h1LkwpruieW3EQZJzXTTv2IH55pvdnFiIHlLChBAXcDgV8ks7yD7Ryt7jrTR3ODDo1UxO8mV2agDJg42XNbnZUXuGys/XsDffTJvDTEqSk2F3zmf/9jcIyziJpwqa7pjMDXPukbW/xLcSbfZkzFAfNuQ08J0ZZrQaFWqNmuRZ8WSvA+3uY5inDKUqtgTt/1uuQqe79IGFuMqkhAkhaLU4OFLUzoFTbRw83YbF5kKvUzE2wcTMkX6MSzDhobv0JHlFUXCcPYYlZz25R1SctqTg5QXpK+I57X2Q7Bf+i7hCJx0xfsQ+9CiBoYOvwdmJgWDJpCCeerOUfSdamJ7iD0DilEEc3HCak6d1zJyTxOakQiLXdtGek4Pv5MluTiyElDAhBiSnS6GwopNDhe0cLmynsKoTRQGTUcPkJD8mJpoYHeeD/jKKF4DL1kF3/na6cj/nXLWLnLZ0Ohw+DBrnS/OEErbm/pmJu7vxsoFh6XyGLf0OKrXc+SiunLHxPoQFeLAuq6G3hOm9dAyfEM7xfQpjDhdjjTPTEdBAU2amlDDRJ0gJE2KAaG63c6iwnUOF7eQWtdNhdaJWQUKUgbvSQxkT70NchBca9eWto6R0ddJdtB97wR7sJbm0dRk51j2HylYznv5qlBkV7FVWM/MdF6kVLjQxkUTfcz+eMXLno7jy1GoViycG8ern1RRXdxIX3nOnbsrsYeTvq6bgYDMzx03lcNInTN9dgrWkBK/YWDenFgOdlDAh+ilFUSitsXGgoI0Dp9oorOy52hXgo2Vioomx8SZGx3njY7i8twFFceGsLcFx9hj20qM4yvPBaafLEM5J3R2crvZG0Sg0jymmafBJ0vLVzDzqQq3zwPzdW/CfOVOufomras6YAN7cUsO6rAZ+sjwaAN8gA4OHmSg+PYwbz7SwZYQ3jv0dNG/bhtcDD7g5sRjopIQJ0Y90210cPdNBzqk2ck61Ud9qR6WC+EgD350dyvhhJmLDPC85sV5RFJSOJhw1Z3CeK8JxrhBndSGKtQ0AdVAM1sRFHKgP49xxBcUBzUNLaUsuZFaFH9EfgMpmw5SWhvnWW9H5+V2L0xcDnLeXhvRUf7YebuLeBeG9d++Omp9E6alsSnflM+GeaZxM2EBKzgHMt92G1mRyc2oxkEkJE+I653Qp5JV0sONoM3uPt2LtcuHpoSZ1qA93zvZhfIIJf58v3wmmOOy4WutwtZzD2VyDq+WL/zWfw9lSA3ZbzxNVatSBUSjx46iKCqXIpqPqoB3VVh/ARXvsOQLHOllQp8FnjQpnSzneI0cSvHw5nlFR1/YPQwx4SyYGseFAI5sPNvKdGT3LVYTG+hMUouV04xDmNnrx4kgdKfldtOzaRdDixW5OLAYyKWFCXKdqm7vZcKCRbblNNLX3LCMxJcmXacl+pMR6o9OqUDrbcLWcobu8BmdLDa4vypazpQalrQFQzh9Qq0ftF4rGP4SuwSOo9/XinElHlc5GVXMt1pN2fHMUvJoMqLROvFLtjBpjJuxkB23v7sZltaJPSCD4oYcxJCS47c9FDGwxIZ6MHOLN+v2N3DzVjEajQqVSkTJnBNvfcdC84xBDlqZRGbUHzfZMAhcuRKWRJVKEe0gJE+I6oigKR4o7WL+/gQMFPV8NjhtmYk6SB6N9alA3HsRZVIFtfwWdDRUoXZYLXq/yDkDtF4ouOhm7XzBNvkYaDRoaPBzUudqo76qlzlaLxVmJ1uKFT2EI/lWRmKpG4utS4R2uI/HGaAZ5d2I7mEX785/T4nJhGjeOgPnzZaKz6BOWTAziv985y/6CViYn9XwVPjQ1jOxPj1FQGcQ0ZRAfp+wl8vMW2nNzMY0b5+bEYqCSEibEdcDlUsguaOO9zBpKztmIMlr5SVIlozxK0TYU49pUSdcXz1UZ/dAERuExYjqugDCaTUYavdQ06LqpszdRZ6ulvquGFvspcAA9XY4Ah5ngpmgS6uKhwouu2p6rZD4BXgyeFkJsjBZtaR6tGX+nvqUFjY8PAXPm4J+ejkdwsFv+XIT4KhOGmzD76cjIbuwtYRqdhhFTB3Noi8L4fYfRjR1Gx54CmjK3SQkTbiMlTIg+TFEUsk72lC977Vnm+pzgF+HFGNrL4CyoDH5oIhLQJc/AEhpJtY+WSkc9lZ0VVFuraOw+hmJR4IsLYkaNN2Z9CEOVEfhYgvFo8sbVoKG9qpu2BisAdq2akBg/YiYEE2bqQlV6nI79G2nNqAe1Gu+UFPymTsV75EhUWnkLEX2PRq1iUVoQ/9x0jrM1VgaFegEwYlosuVtLKDhhZ/qsiRxOKmBy1mlsFRUyf1G4hbyDCtFHFVd38saa0wTV7OdBryNEGqtAUaP1S0Q7ZgXN0bGU6q0UdRRR3H6U5pbt0AIqVJg1oUQ6hpDUmYZnuw/qNj3OFjWWpi7aGjvptLvoBKADnwAvgiJMjJgcQ1CQFkNLGbaCo1jWnqClowM0GoyJiQQuWoTP6NFyN5m4LswbG8A722rIyG7kRzdFAmD09WRIShAleQmk5p9hwygzzpxamjMzCbv7bvcGFgOSlDAh+pg2i4NPP8/DVLCOH2tz0Xk6UYfEoUt+gJrYWPKshRxryaWuZhse7Ub82sxEWVNItASiavWgu9mFpbULuwL1AHSi9ejCN8iAn9lIzAgzvsFGAsK88dF14ThbTGfhMaxbC+moraUD0JhMeKekYExKwnvkSDRGo3v/UIT4D5mMWmaO8ifzSDN3zw/Fx6vn4y5l9jCKjjVSuL+MiQ9M53T8RyRm7cN8yy3y37m45qSECdGH5OzLo3nHhyxRHUPx0KBLnktX6hSylRIOlR/EseMIxrpAgppSMTd5oth7XucEuk1aTEGeBA814BtkwBRswDfIiCnIgJe3BygKXVVVdJ4+jfVYIR0fF9LS0gKA2mjEMHQoftOnYxwxAn1UlCysKq57iycGsflQE1sPNbNsas+8xZBBfpjD9BTWxbOo2sbLIw0knrTQuncvAfPmuTmxGGikhAnRB7Q1NXH8vVdIaN2HXe1BV/Ji6lJHkHW6gKbVe/CuDCGsYyIAWg815hg/gob7EhDuTWCYCf9Qbzw8L/x1VhwObOXldO7dT+Pp03QWFeGy9EwO0wYEYBg2DEN8PF7x8ejDw6V0iX5nSLgXIwYZydjfwNLJQb1bciXPGUbmW13U7Mgm/rapnAvbjCZzK/5z5sjvgbimpIQJ4UaKy8mZzavxPPIB8UoXpSHptCeP5mhOGZqd9Wi7wwnUKoQnBDAoIYywIf4ERpjQaL78QaE4HFjPnMFy6hTWwkI6i4pQursB8AgNxTRmDF4JCRji49EFBV1y1Xwh+oMlE4P4w/tlHDrdzoThPfMZ40aHk/1JHqdqw5liNfNhipqwzQ1Yjh/HOyXFzYnFQCIlTAg3cdSXU/neHwm0lHGKeCqHzKamwIrmmAWdhx/Bw42MGTecmOGh6Dy+ejFJe3Mzlrw8OvLzsZw4gctqBZUKfWQkftOmYUhIwDB0KFrZNkgMUJNG+BJo0rEuu763hGm0akZMj+XgRgXH3mwMU0bTuecwjdu2SgkT15SUMCGuMUVR6Dj4OdbM13DZvfjE42666/WozoEr0EnsYgPp0yfjqff4ytc7WlpoO3SItpwcrIWFQM/Xi6bx4zGmpGAcNkwmGAvxBa1GxQ0TAnlraw2V9TYigz0BGDFlMIc3F1NwWs20uSPZPyKXcYfy6a6rw8NsdnNqMVBcVgnLyMjg5ZdfxuFw8L3vfY8777zzK5/3s5/9jLS0NJYtWwbA6tWr+ctf/kJgYCAAM2bMYOXKlVcouhDXH5ellcbVz6Eqy2WPZTo19gRUNjWd0bUkpUczZ9RctOqv2ufRQXtuLi27dmE5eRIUBX1kJMHLluE9ejT6yEj5elGIr7FgfADvba9lXXYDDy/pWa7CYNITNyqEkiN2xuTm0Tw2CuVwGc2ZmYTcfrubE4uB4pIlrLa2llWrVvHZZ5/h4eHBbbfdxoQJE4iLi7vgOU899RTZ2dmkpaX1jh8/fpwnn3ySRYsWXZ30QlxHHDVnaPngGWqbjOzquAeV3YPOkAb8lrp4YMIyfHVf/srQ3tBA886dtOzejbOtDV1gIEFLlmAaPx59RIQbzkKI64+ft47pKX5sO9zM9+aGYfTs+Xo/JT2ewtw6Cg/WMOHhmZyJfRv1nl0EL1uGWq93c2oxEFyyhGVlZZGWlobfF3NK5s2bx6ZNm3jkkUd6n5ORkUF6enrvc/6f/Px8zp49yyuvvEJCQgK//vWv8fX1vcKnIETf131qH02rX+BA80SqrEPpNnXQkX6amyYvJMnvy3NQus6do3H9elqzs0FR8B41Cv+ZMzEmJcndW0J8A4snBpF5pJltuU0sndSzXIU52peQSC8Kzw3nprONvDbah6HFbbTt34/f9OluTiwGgku+m9fV1RH8b/vCmc1mamtrL3jOfffdxy233PKl1wYHB/Pwww+zbt06wsLC+O1vf3sFIgtx/VAUBeve9yl+/20yapdTaY2jYUQRxhXN/HTej75UwLqqqqh66SVKfvEL2g4eJGDOHOKefZaoRx/FOyVFCpgQ31BClIGEKAMZ2Y24XErveMrsYXQ4fSnfdZiEkek0BELdtk0oinKRowlxZVzySpjL5bpgromiKJc99+TFF1/s/f/33Xcfc+bM+QYRhbg+KS4nHev/Pw5ndXDSspguUwfnpu1j0ei5TA2eccHvkaOtjfrVq2nZuRO1Xk/gDTcQMHeubBEkxBW0ZGIQf/6onCPF7YyJ7/ndih0VisGo4nT9IKa3Gfh4pI6g7eewFhdjGDrUzYlFf3fJv1aHhoZSX1/f+3N9fT3my7hzpL29nTfeeKP3Z0VR0Gi++jZ7IfobxWGn8aM/s3WXgZOWMTQNLaNleR4/mvoQ08wzewuY4nDQuHkzZ37+c1p27cJ/9mzinn0W8/LlUsCEuMKmJvvi761lXVZD75hGoyZpRhw13VFY9uzFJy2NLg+o37rJjUnFQHHJEjZp0iSys7NpamrCarWyZcsWpk2bdskDGwwGXnvtNY4dOwbAO++8I1fCxICg2G2UvfEs6/fHcM4eQdWkIxjmdvBE8pNEGaJ7n2ctKaHkN7+h7v338RoyhNjf/Y7QO+9E4+3txvRC9F86rZoF4wM5WNhOdWNX7/iIyTFo1AqnSgxM8RxGQaIay6Fc7F9s6yXE1XLJEhYSEsLKlStZsWIFN954I4sWLSIlJYX777+f/Pz8r32dRqPh+eef5+mnn2bBggWcOHGCJ5544oqGF6KvUbo6OfXy82zOG06b1oOSG3YTNyGUH8WvxFvrA4DLbqfuk084+7vf4bJaiXz0UaJ++lP04eFuTi9E/7dwQiBqFXy+v7F3zMtHz9AxYZRaEzAdzKE9LQ6VS6F5x3Y3JhUDgUrpg7MPKysrSU9PJzMzk8jISHfHEeKyKHYbx/76Itml8Vh9Ozg7fy9zB8/nhvBFvV8/Ws+e5dw//kFXVRW+U6cSctttsrCqENfYH94vI7ewnbf/azieX+xGUV/Rysd/2stoUzaGH82n+uXXiW72IvG5F1BpZV1zcXHftLfIrVZCXAGKw07OC6+TVTqMjsBWSm/YzS3xt7IoYjEqlQpFUWjevp2y3/0Op8VC1MqVhN97rxQwIdxgycQgOmxOth85/3VjcJQvoTFGCi0jiD1dSlmqP+q2Ttpzc92YVPR3UsKE+JZcTgd7nnuLw2cH0RFWS9mCvdwWu4Kp5p65ky6bjepXX6XmrbcwJCYy+He/w3vkSDenFmLgSowxMCTci3XZDRcsRTFydgIWp4myvfkkjJ1LqwmqN693Y1LR30kJE+JbcLmc7H3+PY5XhNI6qIKz6Qe4I+YeJodMBKCruprS3/6Wtv37CV62jKjHHkMrE++FcCuVSsWSiUGU1drIK7H0jg9ODsHoo+F00xBSG1ycGqlHOVOOrbzcjWlFfyYlTIhvYf/LH3P8bCDtgyqomHqUO6IeYFLoeAAsJ09y9r//G2d7O9GPP07QkiWy2KoQfcT0kX6YDBrWZZ9frkKtUZM8I47a7khad+/Gd8pU7Fqo2brBjUlFfyafCEJ8QzlvrOfoKR86o6oom5rL8pB7mRI+BoCW3bsp/8tf0AUGMvjppzGOGOHmtEKIf6fXqZk/LpD9J1upbe7uHU+cHI1GAwWVAUzUDaIwXo1l/0GcHR1uTCv6KylhQnwDRz7ZyaHDKrrDqyiZcZB0nzuZFTMOxeWi7pNPOPfPf2IcPpyYX/wCXWCgu+MKIb7CDWk9v5ufHzh/NczT6EH82HDOWhPQHdhD15QRqO1OGnbJchXiypMSJsR/6FRmLtm7LLhCqimafYhR6mXcPHw6isNB9T/+QeP69fjNmEHUY4+hMRjcHVcI8TXMfh5MTPRlU04TXXZX73jyzCE4FS2n8i2MGzyZykgV9Vs3ozidbkwr+iMpYUL8ByqPlbBzbSUqv3pOzTlEROccHhi7AFd3N5UvvkhbdjbBy5cT+r3vydpCQlwHlkwKot3qZOex5t6xoAgTEUNMFFqSCcs7RtX4EDQtFtoOH3JjUtEfSQkT4jI1VjSy6V95qD07KFiQg6F1PE9OXY7LZqPi+efpOHKEkO9+l6BFiy57k3shhHslDzYyKMSTdVn/d7mKeKwub4qzi0n8YrmKqo1r3ZhU9EdSwoS4DB0tVta/sAeXys7JhQdwtMXy9PQVKNZOyp99ls6CAsLuv5+A9HR3RxVC/AdUKhVLJgVRcs5Gfun55SpiEs34Bnpwui2RxLP1FKV6oyqtxlpa6sa0or+REibEJdi7HHy+ahvWLiicl0On3Y9fjH0QvaOb8mefxVpaSsQPf4jf5MnujiqE+AZmjfbHZNTw2d763jGVWsWo2fE02c1U7zlA+PS5dOugYsNqNyYV/Y2UMCEuQlEUtr26i8YmFRXTD9PmCd+PeYgwo4byv/wFW3k5kT/6EaaxY90dVQjxDel1ahZNCOJAQRuV9V294/HjI9F7qjhVP5ix7R4UJXpgP5yPvaXlIkcT4vJJCRPiIg6tPUppoY3WlBM0hrYwXXcfE6L9qHjuOWxlZUT+8If4jBrl7phCiG9pUVogWo2KNfvOXw3TeWhImj6Eyq7BdOzOxHPmJFQuheqtn7sxqehPpIQJ8TVKjlRyMLMaR2QZFSNLiGi4jdvGxFCxahXWM2eIePBBfFJT3R1TCHEF+PvomDXan225TbR3OnrHk6bGoFarKKgIYIJ3LGWD1LTt3IWru/siRxPi8kgJE+IrNFa3s+3NI6h9GiiccQyleC6PzxlH1d/+RmdhIeEPPIBp3Dh3xxRCXEE3TQ6iy66wIaexd8zo68nQMeGUWIejyt6OddoItJZu6vfudF9Q0W9ICRPi/7B12tnwtz0oahsF8w/RfnYkv0hfQOMbr2E5fpywe+7BNy3N3TGFEFfYoFAvUod6sy6rAbvj/OKtI2cNwaHoOF3gYHTcROqCoXZjBorLdZGjCXFpUsKE+DeKS2Hba1l0dDg4M/sgbW1mvp9wK9qNH9Gek4P51lvxmzrV3TGFEFfJsinBNLU72J13fvJ9UKSJyHh/TneOJPBwFrWTotDVt9N6NNeNSUV/ICVMiH9zeGMB5UUd1I/Jp9XgZCx3kHhmJy07dxJ4ww0ELljg7ohCiKsodagP0WY9n+6pv2Dx1tS58dicBgoP15I0dg7t3lD++SduTCr6AylhQnyh/GQdOZtK6I4qccbpAgAAIABJREFUozahAs+SW/iOtpjGjAz8pk8nePlyd0cUQlxlKpWKm6eaKa2xcbiwvXc8Ij6QoHAjBZZRRB/Po3xcILozNXSWlrgxrbjeSQkTAmhv6mTrPw+iMrZSPC2P1rz5PB6nouHDD/AZM6ZnL0jZikiIAWHmKD8CTTo+3l3XO6ZSqRg9N552hx+lB4qInbaAbh2cWfe+G5OK652UMDHgOR0uNr2yH7ujm8J5B2k+k8JP4gZjefs1vGJjCX/gAVRq+VURYqDQadXcNCWIvBILpys6e8eHjArFx9+Dk20pxJ+tpHSkD+qjRXQ3NLgxrbieySeLGPCyVx+nvtpK+ZRcLFYTi72m4r36NbT+/kQ++ihqvd7dEYUQ19iC8YF4e2r4eNf5q2FqjZrRs4fSaA+lOusgIelzACheL1fDxDcjJUwMaCXHasjbXUH70CLaQ1oIrbyBsfvfBkUh+ic/QWsyuTuiEMINDHoNN6QFknWy9YKtjBLSovD00lDQPJzkFhtlCXqcWUdwWiwXOZoQX01KmBiw2ho62f7WYVy+TVSNO4XlyBJW1GzB0dxM5GOP4REa6u6IQgg3WjopCK1Gxad7zl8N03loSJ45hKquwTTs2Yn3nJlou12c2fCRG5OK69VllbCMjAwWLlzI3Llzeffdd7/2eT/72c/47LPPen+urq7mzjvvZP78+Tz00ENY5G8Koo9wOlxsfu0Adlc3xbMPUXdsKo9bT2AvLSH8gQcwxMW5O6IQws38fXTMSQ1gW24zTW323vHkaTFodSpO1A9lpKKnfLAW2/a9uLq6LnI0Ib7skiWstraWVatW8d5777FmzRo+/PBDiouLv/ScBx98kM2bN18w/swzz3DHHXewadMmkpKSeOmll65seiG+oew1J6mv6qRs6hEsdRE80mFDVXAU8223yXZEQoheN08NxuVSWP1vG3t7Gj0YMXUQ5bahtO3ainbOJHRWJ6VbV7sxqbgeXbKEZWVlkZaWhp+fHwaDgXnz5rFp06YLnpORkUF6ejoL/m0hS7vdzsGDB5k3bx4Ay5Yt+9LrhHCHkmM15O0qoyWhGKuPhRnFUQQe34P/nDkEzJ3r7nhCiD4kPEjP1GQ/1u9vpNVyfmPv0emxqDUqTtTGMkYfwLkIDe2bM3HZ7Rc5mhAXumQJq6urIzg4uPdns9lMbW3tBc+57777uOWWWy4Ya25uxtvbG61WC0BwcPCXXifEtdbW2Mn2t3Ox+zfRMPIUIVnjSS3agndqKiG33y5rgQkhvuT2WSHYul2s+berYQaTJ4mTYyi1JWDZvQXmTEDfbufszs/dmFRcby5Zwlwu1wUfTIqiXNYH1Vc9Tz7ghDv1zAPLocvZTdmMQyh7JnJTZSaegwcT8YMfyFpgQoivFBPiyZQkX9ZlNdBu/berYbOHoFKpOVETw2ifEBrMalo2bpSNvcVlu+SnTmhoKPX159t/fX09ZrP5kgcOCAigvb0dp9P5H71OiKsle+1J6istVEw5gqpgEPdWHkRn8iFK1gITQlzC7bNC6OxysW7f+YVZvf29GJYWRYk1EduezdjTx+DV1EXZ3s0XOZIQ512yhE2aNIns7GyampqwWq1s2bKFadOmXfLAOp2OsWPHsmHDBgDWrFlzWa8T4moozashb2cZTcPOoHbZuPXUOXSKg6if/AStr6+74wkh+rjYMC8mJppYs68Bi83ZO546Jw4FNSdrIhlpjqbFX03D+gy5GiYuyyVLWEhICCtXrmTFihXceOONLFq0iJSUFO6//37y8/Mv+tqnnnqKjz76iIULF3Lo0CEee+yxKxZciMvV1tjJtrdy6QpopnPoKabt9sTH0kjkI4+gj4hwdzwhxHXi9lkhdNicZGSfvxpmCjIQPy6C4s4k7Hs2YksfibGuk/L929yYVFwvtJfzpMWLF7N48eILxv7xj3986Xl//OMfL/g5IiKCt99++1vEE+LbcTpcbH69Zx7Yuck5jNwYSUx7IWHf/z7GESPcHU8IcR0ZGmFgXIIPq/fWs3RSEF56DQBj5sVReLCKE9URjJoYTaH/USxrVhOdNlvmmoqLkv86RL+WvbaA+goLVZNzidsZRGpzIYGLFuE3fbq7owkhrkO3zwqhrdPJun+7GuZn9iZ+fARFncl07dmEbfZojHVWSvdtdGNScT2QEib6rZ55YGdpHFbC4LNWplaX4DN+PMHLlrk7mhDiOjU82sj4BB8+2VVPh/X83LBxC+JBpeF4bSwjA8w0B6hpWitzw8TFSQkT/VJbYydb3zqMNaCZIMNJJp5oxnPIEMLvu0++HhBCfCsr5obRYXPyye7ze0qaAg0MnxTNGWsinXu24ZozDmODjcJda92YVPR18mkk+h2n3cnnr+2n22XHlXiAcXvBI8C/ZykKDw93xxNCXOeGhHsxPcWPNfsaaG4/v0L+2PlDUWs05DcMI9lgoDlQQ1vGRlwOx0WOJgYyKWGi39n1aT7NlVaaxhxiUqaCQQeDfroSrcnk7mhCiH7irtmh2J0uPtx5/mqY0deTpKmDOGsdRkvWbtTz0vBu6ubkjo/dmFT0ZVLCRL9y6kAlp/ZV0Ti8kJn7G/FzWIl59Mfow8PdHU0I0Y9EBuuZOyaAzw80Utvc3TueOmcIGp2G/KYUElUums06rJ9n4rR3X+RoYqCSEib6jcbqNnZ8cBRLSAOTK04S1G4l/Pt3Yxw+3N3RhBD90B2zQlCp4N3Mmt4xLx89I2fFUm6Lo37/AfTzJuPd4iDv8zfdmFT0VVLCRL/QZbWz9pV9dOu6iNNlEXbOju8Ni/GfOtXd0YQQ/VSwnweLJgSSmdtMWa2td3zUrFg8DVqOtk5kSHMV9dGesDkLW0erG9OKvkhKmLjuKYrCxrcOYG124B2RzbCCLnSp4wlbLktRCCGurltnhuClV/PahureMb1Bx7iFCdR2hVOZV0XQ3Gl4WhWOfvJ3NyYVfZGUMHHdy9l2iurjrTgH5ZN2pBFXdByxD96HSqVydzQhRD/na9Ry+6wQDhW2c+h0W+944pRo/IINHO2YSnjhIepGBGDcU0BT7Vn3hRV9jpQwcV0rL6zjUMYZukIqmXm8kO6AUIY9+RNZikIIcc0smRhEeKAH/9hQjdOpAKDRqJl4UyJtdhOnz+gYnDYWlQInPpCrYeI8KWHiutXRYuXz1/fjMHYw4+xB7Hpfkn79MzQGg7ujCSEGEJ1Wzb0Lwimv62JjTmPv+KAkM+FDAzjemYbn4e20pA0i4GgNZ4sOujGt6EukhInrktPp4qNXtuPsUhjXsg8VGuJ/8XN0/v7ujiaEGIAmJppIiTXy9raa3u2MVCoVk29KpMvhwYmaGIbFRmH3UFHx3pu4ZDsjgZQwcZ1a9+FubJUQ5zqIj62TkB//FO8oWQtMCOEeKpWKB26IoN3q5P0dtb3jwVG+JIyP5HTnKDpzdtE9M5mg0g6O7/3UjWlFXyElTFx3du84zLlsC4HaQqLbKtHc9RBhKfHujiWEGOCGhHsxd0wA67IaKK87v2RF2pIENDotuS2TGKq00Bqko+uTjVit7W5MK/oCKWHiunKioJj8NdV46WpIas6jec5tJKaPdXcsIYQA4O55oXh6qPnrmkoUpWeSvtHXk/E3JFBtjaKioAnf2ePwbnNx6KMX3JxWuJuUMHHdqK6tY/s/89GqLYxp2k/tyBlMvnO+u2MJIUQvP28d9y4I43ipha2Hm3vHk6cPIjDch9yOGQSdPkBTUjB+u4uoKDvmxrTC3aSEietCR2cnn768C003jGndR0PUUGY+tsLdsYQQ4kvmjgkgMcbA6xurabU4AFBr1Ey7NYlOuxf55wYTNywaRQ1n3noVlyKT9AcqKWGiz+tydPPm3zPQNHqR0nEAq783k3/zU1mMVQjRJ6nVKn50YyQWm5PXN55fST8sNoDhE6N6JunnHsQxI5mQMxZydr/rxrTCnaSEiT7NqTj515ufoSr1ZqjtKHpvCyOfeQa9TuPuaEII8bUGhXqxbGowWw83k1fS0Ts+cekw9F46DrXPZLC1jI5APepPttPcXnuRo4n+SkqY6LNcios3Vn+C66gPkd2FhOjPEvWL32PyltXwhRB93x2zQgnx9+CF1ZV02Xu+cvQ0ejDxxkTqbWaKSj0JmjwM73aFI28+5+a0wh2khIk+SVEU3t/+GV07jATZK4nTHsO08reEhpjcHU0IIS6Lp4eaR5dFUtXQxb82nesdH5YWSdTwYI52TEVz8jBt46MIO1RLbs5qN6YV7iAlTPQ5iqLw6cG1tK7VYXI2kazJQnXPzxg0RBZjFUJcX0bH+bBkYhBrsxo4eqZnXTCVSsXM25NRe+g40JrOUE0TFj8d9nczaGqvcXNicS1dVgnLyMhg4cKFzJ07l3ff/fIEwoKCApYtW8a8efP45S9/icPRczfI6tWrmTJlCkuXLmXp0qWsWrXqyqYX/Y6iKKzOW0fdewpeThujVTvoWv4Dho9JdHc0IYT4Rr4/P4yIID3PfVyBxdazpZG3vxdTlidRbzNTWGYicFICplYXB996tnd9MdH/XbKE1dbWsmrVKt577z3WrFnDhx9+SHFx8QXPeeKJJ/jNb37D5s2bURSFjz76CIDjx4/z5JNPsnbtWtauXcvKlSuvzlmIfmPtyXXUvGHHw+5knGor3fOXMWrmJHfHEkKIb8zTQ80T34mmsd3O3zOqescTxkcwKMnMMcsk1KfzsIyNIepgA/sPfuTGtOJaumQJy8rKIi0tDT8/PwwGA/PmzWPTpk29j1dVVWGz2Rg1ahQAy5Yt6308Pz+f1atXs3jxYh5//HFaW1uv0mmI/mDt6bWce92G1q5mnGobzskTGb14sbtjCSHEt5YQZeDWGSFsy21m34mez0KVSsWM25PReXqwv202g5QqrL461O9soqa5zM2JxbVwyRJWV1dHcHBw789ms5na2tqvfTw4OLj38eDgYB5++GHWrVtHWFgYv/3tb69kdtFPKIrC6uJPOfeqBXW3J+NU21GPSSDltnvcHU0IIa6YO2aFMDTCi+c/raC2uRsAg8mT6bcm02gLJL96EEGjzHi3Kxx/5c90O7vdnFhcbZcsYS6X64JFMRVFueDniz3+4osvMmbMGFQqFffddx979uy5ktlFP+BSXLx/6l3qX7KidHmTqtmOR3IISXc/KouxCiH6Fa1GxX/dEYOiKPz+3bN0f7FsRVxqOCOmRFPQMZr20mbsaTFEnOpg19rn3ZxYXG2XLGGhoaHU19f3/lxfX4/ZbP7axxsaGjCbzbS3t/PGG2/0jiuKgkYjC2yK85yKg7eOv47lVXB2mxij3YEpwYvEe/8LlUpu3BVC9D9hAXoevyWaoiorr6w/v5r+5GWJBEWa2N8+j8D6M3QM9iP085McPr7BjWnF1XbJT7pJkyaRnZ1NU1MTVquVLVu2MG3atN7HIyIi0Ov1HD58GIC1a9cybdo0DAYDr732GseO9WxO+s477zBnzpyrdBrietPt6uafB1/C+ZoXDruJsbrtBMcpxN//NCqN1t3xhBDiqklL9GX5tGA25DSSmdsEgFanYd49qaDRk9Uyl2h/Cw5PDV3//JjqlrPuDSyumkuWsJCQEFauXMmKFSu48cYbWbRoESkpKdx///3k5+cD8Oyzz/KHP/yB+fPn09nZyYoVK9BoNDz//PM8/fTTLFiwgBMnTvDEE09c9RMSfV+Ho53X9vwZ7dsBdDtNjPfMJHiIwqD7/weVztPd8YQQ4qq7e24YSYON/HVNJaU1VgB8g43MvGskjV2B5FcPISDZH78mhWOv/gmrw+rmxOJqUCl9cEGSyspK0tPTyczMJDIy0t1xxBVUZ6vlgy1/xWdLIja8mWDcRlAURN3/R1R6g7vjCSHENdPUZudHfytEq1Gx6qGhBJh0AOz99AR5O88ywXc7+mANmiN1lKZHMf+uZ1DLVI0+6Zv2Fvm3Ka6Z4o4iPnn/Lxg3p9CFgcmmjYREK0Td9wcpYEKIASfApOOZ7w2mrdPJU2+WYu3qWch14o3DiRwWRE7bTDSNLVji/RmUWcG2bS+6ObG40qSEiWviQH0W+/7+CrpDaThVWmb6r8McrSPs3j+g8jS6O54QQrhFXISBJ2+LoeSclT9+UI7TpaDRqJl3Typ+IT7sa7uBQHsj1lADIR8dZt/RT90dWVxBUsLEVeVUHHxa9A4Vq9ZhOzsFRa0wN/gT/AYHE/L9P6L29HZ3RCGEcKsJw008tDiCnFNtvJJRhaIo6L103PDgODReXuxpXYTZZEHRa9G9lkF+eZa7I4srREqYuGra7W28vu8PaP52lrq2KajVXSwM/hDj0ATMK/5bvoIUQogvLJoYxM1Tg8nY38h723sWPDcFGlj4g/FYFW+ymmcREGHHy6ai5a+vcba+wM2JxZUgJUxcFaWWEj78+NcEvetLtWs0Bm0jS83v4Z0ygaDbfoVK6+HuiEII0afcMz+M2an+vLOtlg929BSxkEF+zLk7laauIHKapuMZq8a/0UXZc89S0VR8iSOKvk5KmLiiXIqLrRUZHHrhzxj3jKRGO4Rg/RmWBH+EcdJN+C5diUoti/YKIcT/pVareOzmKNJH+/Pmlho+2lUHQOzIUGavGEV9Vwh5zRPRxusIqnFS9NwfqWgpcXNq8W3Iqpjiimm1t/LZgRcJ+7SBtu5ZdGk9GeZzgJE+RzEuXIl+5Gx3RxRCiD5No1axcnkUTpfCvzadQ62C5dPMDB0bgculkPk2qBrHkpiQS+ipLgqe/x9UP/kVkaZB7o4uvgEpYeKKyG86wpHPXiUsJ5JSj5m4NE6mBX5OuLEZ03f+B110krsjCiHEdUGjVvH4LdEoCry+8RwdViffmxtKwvhIXE6FHe+BqhGGDzlI1BkHJ1f9Hh79LyL9Yt0dXfyHpISJb6XTYWFt/hsEfJSHZ/MYSvQRaLRt3BT4MR5BIfh+ZxWagHB3xxRCiOuKRqPiie9EY/BU8+HOOupaull5cxTDJ0ahKAq7PoCuVk9GxOwh4qyd4v/9PR0//iHDwlLdHV38B6SEiW8sv+kIuRmvEZ1l4oxuLl06PWHGU8zw2Y4ueRbe83+IykO2IRJCiG9Co1HxoxsjMft58OaWGpraHfz6rkEkTorGy0fP1n8e5kj7HFKiMgmq6qbxT3/lwA9vZ0LcXHdHF5dJJuaL/1hzdxPvZz9H7R9fwpQ1nAKPKXRqtEwO2sAMvz0Yb/gx3ot/IgVMCCG+JZVKxW0zQ3j8liiOl3bwk5eLqKizMTg5hKWPTsSh8+Nw2wIcYV74WED1/HtsyX2bPrgjofgKUsLEZXMqDjLL1rPx1Z8T/s96yjrncs5jEF6e57jD/BoxZiemu/+CftQ8VCqVu+MKIUS/kZ4awO/uiaXF4uDRF4vYeayZkEH+3Pz4FPT+vuxvW0ibfygeLjWhL2WSse5/sDpl0+++TkqYuCRFUTjRnM+7H/0Mzz9tQHNiPCc8p9Ch8WRsQCZL/ddgmLAUv/teQBs6xN1xhRCiXxo1xIe//SiewWGe/O8H5fxtTSVe/l4sf3wKUYkh5HVOodwwEquvB0NXF7H1r49T1nrG3bHFRcicMHFR5ZYydux/k6hN5QS3xpGvT8SpVmMylLHQtBG1nxnvxX+Uux+FEOIaCPb14H/vj+PNLef4ZHc9J8ssrFwexcIHxnF0ewn710GLxszQ0CyGHm2n9H9+R9n3lzI1Yal8Q9EHSQkTX6nWVsPOw+/jszmfyHMxlHguoFvviVPXyQL/DAK0LXhOuAmvKbej8vByd1whhBgwtBoV9y4IJ3mwNy+sruCxF4tYNjWYu2YPJjTWny2vH+Jo+1wGB+UT2lSM6i9rWDfzEJNv+jFBXmZ3xxf/RkqYuEBVZyV7jn2McWseoeXhlHjOxerpQ7fGQarvbpL1x9FEp2Cc/zs0QdHujiuEEAPW+GEm/v7YMF7fWM0nu+vJOtHKD5dGcusvZrBv9UlOH1BTZxxEpPoI8VsqyTv+JKrbFzAt6SY0Kvn47wvk34JAURSK2gvJzfkM0+4izNVRlOnnUeHlg13tIsHnEOO9clD5hmCc9XN0w6fKZW0hhOgDvL00PLosiukj/Xjhs0p++c8Sxgz14d4FCSSMi2Tnu0c41TyD1oBiIhpO4/X856wbv5ekZfczNFimkbiblLABrNvVzaG6LIr3fk7EgVYCWmKo0C+gy8uAXe1ksDGPycZ9qIx+GKc+jMeouag0OnfHFkII8X+MGuLD31cmsD67kfd31PLDvxYyO9Wf7/xwMpU55RzLhFr9YEI0RcTuL6T9yLOsmRbJ6EXfJ8YkN1S5i5SwAUZRFCqs5eSe2op970FCCgx4K0Mo0kXj8tTg0HST7J3FSK+jKAY/jGl3ox+7CJVO1vwSQoi+zEOrZtnUYOaM9efDHXWszWogM7eZKcl+LPrBRBoOl3EqR02dzxBCVEUM2nqG6gP/zbGpsaTO/S6RpsHuPoUBR0rYANHc3cSRyr3UZO/EP9+GV2MkbbqpHNf6g0pB59HEJO8sojwqUPyjME56DI8RM1Bp5cqXEEJcT3y8tNy3MJwbJwezNqueDQca2Z3XwsghJtJvCcFxsozS41rOeScQ6Kpg0IYiarY/Q+5YMzHzbiQ5PA21SlawuhakhPVjdbY68ir3UZe7H5/8dvS1oaBJplQbDJ4q0NiI8spnvPEAWo0Tbdx4DKn3oY1NRSW/gEIIcV0L8tVx74JwbpsZwsacRtZmNfDcmQ5MBh9mTAkh2tJEVb6aQ8ZBGFUNhGeX48h6g01xb+I1aTxJ4xYR7BXi7tPo16SE9SM2p42i1gJKCw9gzS/Au1ALraE4tMlUaPxBDyp1F6GehaQaDuOra8HpG4n3mLvwSJqF2tvf3acghBDiCjN6alg+zcxNU4I5UtTOlsNNbMhvw+HUERk2mHEGG+oaFUVKECpG4Vdeg1dxOUUf/oYDiZ74jZ9IYvJsAjyD3H0q/Y6UsOtYu72dktbTVJ05gqWgGE2xE4/GQDox06qZRaNKC3oFvaaNOM8jxHudwqRtxu4XjU/yDeiHT0ETLMtMCCHEQKBRqxibYGJsgolWi4O9x1vIOtHKujMOnK4IwgNcpHq0YGk0U6AJBxR8TjShPlZGnuYPdMZY0aXEEzlyCnFhI9GpZbrKtyUl7DrgUlw0dTdyrqWM2rMnaC8tp/usDV2dJ3T60aEOwKKegqJSgxb0qnbCPEqI8SohRF+FWqfGGZ6M3//f3r3HRlXnfRx/z7W3oYWhnZSUPsjKwzZbGi6ti5UKAVoQpqVaUC5KUORivBH/gHhLUIMXiIHEyEM0MZgoBBBFghrwArpAK4KJNBsEN6CUcmmnN2emc+nMOb/9A+mm1V1gn+35sfb7SiaZ35wzmc/3tJn55nduf5qP+w/jcAwaorskIYQQGmVlOPGPz8Y/Pptw1OCbk0G+/SFE7Wk3be5BZDkTFDraSUlk8FO8EBiFrdEg82wb8Q+/4qe0XSR9MVJGDib7j2MYevMYstNz5Viy63RNTdiePXvYtGkTyWSSRYsWce+99/ZY/v333/PMM8/Q2dlJSUkJzz//PE6nkwsXLrBy5UpaW1sZPnw4r776KhkZGX1SyH+7LjNOR1cHrW2NdAQa6WhsJnahg65AHNXhxBZNx0h6iNgz6bKP636f3dVFlqOVAvdpslObyHY1YaamYfhGkjViChnD/4QjdwQ2u0NjdUIIIW5UnjQHU8YOYsrYQSilaAzE+e50mO8bfNSdixBoieIzOrnZbMFlpBI0RqJMO1wCx8UEzQcC/Gh+gC01DJkx3IMhI28gA/9wM9n/80eyB+aT5pQ7q/wWm1JK/asVmpqamD9/Ph988AFut5t58+axfv16RowY0b1OZWUla9asYcyYMTz99NOMGjWKBQsWsHz5cmbNmoXf72fjxo1EIhFWrlx51VCNjY1MnTqVL774gqFDh/7/q7SQoQziRoxIMkos+jORnzvobP+ZaEeYWLCTaDBCLBQn2ZnA7EyiojZUlxuVTMUwUknY0uiypUCvi6E6iZHmCJFp78DramVQSgvprk5URgZ4h5KedzPe4f+LK3c4do9XU/VCCCF+b0LRJH9rjPLTpRhnm2M0XIwQvNRBbqyFPLMdtwLDSMNQPS9lZFcGbhXDRQyHPYrdGcfujmNPTeJIt+EakEJaVgbpmR48g7JI83rxeAeTnplNWuoAnDbnf82Fwf/dvuWqM2G1tbXceuutDBw4EIDp06ezd+9eHn30UQDOnz9PLBZjzJgxANTU1PDaa69x9913c/ToUTZu3Nj9+n333XdNTZhhGABcunTpmgu5XoYy+EvgAKFECKVMsv7aRMqFMO0/DyGZcAE2MOFyh2pDKVDKBorLz01+WWhDKTsKByg7Jg4UdkwuP+dXU7PuXx5XmDjowmmL4ra3k+KIkkWENOI4XUmcqQp3uhPHgCycA7xkZPvI9BWRMjgX0jK7/0ENIADQEbn8EEIIIf5DfGngGw5/Hm4DMlAqnUg8l7ZggpZggtZgkpbWGJHmNmgP4I604zZjxExQphPTTMFQGZj81glgBtB2+aH+hoMEdmWCzcSOATaFDQObzcSGAtsvP8A2BTa6n9t++cW22/8xj5HI9sBwN7dPKMaX2ndnel7pV670L9fqqk1Yc3MzOTk53WOfz0d9ff0/XZ6Tk0NTUxPt7e14PB6cTmeP169FIBAA+NVuTyGEEEKI6/V/Fn1OIBBg2LBh17z+VZsw0zR7TAcqpXqM/9ny3usB1zytOGrUKLZs2UJOTg4OhxzLJIQQQogbl2EYBAIBRo26vvtxXrUJy83N5dixY93jQCCAz+frsfzKzBVAS0sLPp8Pr9dLKBTCMAwcDsev3vevpKamUlJScj11CCGEEEJocz0zYFdc9VzS2267jbq6Otra2ohGo3z66adMnDixe3leXh4pKSl8++23AOzevZuJEydVJv2DAAAGqElEQVTicrkoKSnhk08+AeDDDz/s8T4hhBBCiP7sqmdHwuVLVLzxxhskEgnmzJnD0qVLWbp0KY8//jhFRUWcPHmSZ599lnA4TGFhIS+//DJut5vz58/z5JNP0traypAhQ1i/fj1ZWVlW1CWEEEIIcUO7piZMCCGEEEL8Z8mlbYUQQgghNJAmTAghhBBCA2nChBBCCCE0kCZMCCGEEEKDfteELVy4EL/fT3V1NdXV1Rw/flx3JMvt37+fmpoaZsyYwZo1a3THsdR7773X/bevrq6muLiYF154QXcsy+3evRu/34/f72ft2rW641juzTffZPr06VRVVbFp0ybdcSwTDoeprKyksbERuHxbuqqqKqZNm8aGDRs0p+t7vesHSCQSLFq0iCNHjmhMZp3e22D79u1UVlZSVVXFU089RVdXl+aEfat3/Vu3bsXv9zNz5kzWrl2L5ecqqn7ENE1VVlamEomE7ijaNDQ0qLKyMnXx4kXV1dWl5s+fr7788kvdsbT44YcfVEVFhWptbdUdxVKRSETdcsstqrW1VSUSCTVnzhx1+PBh3bEsc/jwYVVZWalCoZBKJpNq+fLlat++fbpj9bnvvvtOVVZWqsLCQnXu3DkVjUbVpEmTVENDg0okEmrx4sW/6++C3vUrpdTp06fV3LlzVVFRkfr66681J+x7vbfBmTNnVEVFhQqFQso0TbVq1Sq1efNm3TH7TO/6GxoaVEVFhers7FTJZFLNnTtXHTx40NJM/Wom7MyZMwAsXryYWbNm8e6772pOZL3PPvuMmTNnkpubi8vlYsOGDYwePVp3LC2ee+45nnjiCbxer+4oljIMA9M0iUajJJNJkskkKSkpumNZ5sSJE5SVleHxeHA4HNx+++18/vnnumP1uR07drB69eruO5fU19czbNgw8vPzcTqdVFVVsXfvXs0p+07v+gF27tzJkiVL+s13YO9t4Ha7Wb16NR6PB5vNxsiRI7lw4YLmlH2nd/35+fl8/PHHpKenEwwGCYfDZGZmWpqpXzVhwWCQ0tJSNm7cyNtvv822bds4fPiw7liWOnv2LIZh8NBDD1FdXc3WrVv75QV0a2tricVizJgxQ3cUy3k8HlasWMGMGTOYNGkSeXl5jBs3TncsyxQWFnLo0CE6OjqIx+Ps37+flpYW3bH63IsvvtjjdnDNzc3k5OR0j30+H01NTTqiWaJ3/QCrVq2ivLxcUyLr9d4GeXl5TJgwAYC2tja2bNnC1KlTdcXrc7/1P+ByudixYwfl5eXk5ORQUFBgaaZ+1YSNHTuWdevWMWDAALxeL3PmzOGrr77SHctShmFQV1fHSy+9xPbt26mvr2fXrl26Y1lu27ZtPPDAA7pjaHHy5Enef/99Dhw4wMGDB7Hb7bz11lu6Y1mmtLSUmpoaFi5cyJIlSyguLsblcumOZTnTNLHZbN1jpVSPseg/mpqaWLRoEbNnz2b8+PG641junnvu4ciRI2RnZ/P6669b+tn9qgk7duwYdXV13WOlFE7nVe9h/ruSnZ1NaWkpXq+X1NRUysvLqa+v1x3LUl1dXRw9epQpU6bojqLFoUOHKC0tZfDgwbjdbmpqavjmm290x7JMOBxm2rRp7Nmzh3feeQe3201+fr7uWJbLzc0lEAh0jwOBQI9ddaJ/OH36NPPmzeOuu+7ikUce0R3HUhcvXuy+77XT6cTv93Pq1ClLM/SrJiwUCrFu3Tri8TjhcJhdu3ZRUVGhO5alJk+ezKFDhwgGgxiGwcGDByksLNQdy1KnTp3ipptuIj09XXcULQoKCqitrSUSiaCUYv/+/RQVFemOZZnGxkYefvhhkskkoVCInTt39svd0qNHj+bHH3/sPkTho48+YuLEibpjCQuFw2EefPBBVqxYweLFi3XHsVwoFGLlypUEg0GUUuzbt4/i4mJLM/SraaDJkydz/Phx7rzzTkzTZMGCBYwdO1Z3LEuNHj2aJUuWsGDBAhKJBBMmTGD27Nm6Y1nq3Llz5Obm6o6hTVlZGSdOnKCmpgaXy0VRURHLli3THcsyBQUFTJs2jVmzZmEYBvfff7/lX7w3gpSUFF555RUee+wx4vE4kyZN4o477tAdS1ho586dtLS0sHnzZjZv3gzAlClTWLFiheZk1hg5ciTLli1j3rx5OBwOSkpKLD9MRW7gLYQQQgihQb/aHSmEEEIIcaOQJkwIIYQQQgNpwoQQQgghNJAmTAghhBBCA2nChBBCCCE0kCZMCCGEEEIDacKEEEIIITSQJkwIIYQQQoO/AwT0+aNfYFhuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the distribution of Log GDP per capita variable for each of the years 2014 to 2018\n",
    "sns.kdeplot(c14['Log_GDP_per_cap'], label=\"2014\")\n",
    "sns.kdeplot(c15['Log_GDP_per_cap'], label=\"2015\")\n",
    "sns.kdeplot(c16['Log_GDP_per_cap'], label=\"2016\")\n",
    "sns.kdeplot(c17['Log_GDP_per_cap'], label=\"2017\")\n",
    "sns.kdeplot(c18['Log_GDP_per_cap'], label=\"2018\")\n",
    "plt.title(\"Distribution of Log_GDP_per_cap' for each year 2014 to 2017\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlsAAAEYCAYAAABr4TMuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzs3XlcVFX/wPHPsC+yiYAKuMsigpomiOWeK4ipjzvYo6ZWSGU/00etLE2zzCy1RbPMLfMRNc0FlxQXErfcQQVcwAVQVBbZ5/7+IOZxBAUVGNDv+/Xi9WLm3nvOd+4Mw/eec+45KkVRFIQQQgghRLnQ03UAQgghhBDPMkm2hBBCCCHKkSRbQgghhBDlSJItIYQQQohyJMmWEEIIIUQ5kmRLCCGEEKIcSbJVxR06dAhXV1c+/PDDxzpux44dXL9+vUxiWLduHd7e3g/d7urqyu7du8ukrieVlpbGV199RY8ePWjWrBmtWrVi5MiR/PXXX1r7derUCVdXV81Ps2bNCAgIYO3atVr7zZ8/X2s/Nzc3WrZsyRtvvMGpU6cq8qU9Vzp16sSKFStKte+kSZMICQl54u0lWbFiBd7e3rRo0YLo6OgnLqeQoiisWbOG7OxsoOS/qycRHh5Onz598PLyokePHmzYsOGJyomMjMTV1ZWMjIynjiklJYVNmzY9dTmlFRsbi7+/P02bNmXu3LllUuaNGzcICQnB29ubtm3bMnnyZFJTUzXb09PTmTBhAq1ataJt27YsWLCA4mZdUhSFUaNGaX3GC891cT9P+v6JiifJVhW3ceNG6tWrx+bNm8nKyirVMVevXiU4OJi0tLRyjq5ySElJoX///hw4cIAJEyawZcsWVqxYgZubG6NGjSI8PFxr//Hjx7N//3727dvH+vXr6devH9OnT2fJkiVa+7m5ubF//37279/P3r17WbNmDfr6+owaNeq5ObcVbe3atfTr10/XYaBWq5k9ezZDhw7ljz/+oFGjRk9d5uHDh/nggw/Iy8srgwiLiomJITg4GD8/PzZv3syYMWOYOnUqBw8eLJf6SuuLL75gx44dFVbfzz//jJ6eHlu2bGHEiBFPXV5+fj5vvvkm9+7dY9myZXz33XdER0czceJEzT5TpkzhypUrLF++nOnTp7Ns2TJWrlypVY5arWb69Ons27dP6/kWLVpovmcKfwYMGICzszNdunR56vhFxTDQdQDiyeXk5BAWFsbkyZP56KOP2LZtG3369CnxuOdtHttZs2ahp6fHypUrMTY21jzv5uZGbm4uX3/9Ne3bt9c8b25ujp2dHQD29vY0aNAAfX19Pv/8c/r06YOtrS0A+vr6mv0K9/3www95+eWXiYyMlC/CclC9enVdhwBAVlYWOTk5tG7dGkdHxzIps7z/Lq9fv87AgQMZNWoUAM7Ozvzyyy9ERkbi4+NTrnU/SkV/H6WmpuLm5kadOnXKpLyzZ89y5swZ9u/fr/k+mDJlCkOGDCE1NZW0tDTCwsL4/fffcXV1xd3dnXHjxrF06VKGDRsGQHx8PBMnTuTGjRtYWlpqlW9kZKT1PXP69GlCQ0NZtmwZ1apVK5PXIMqftGxVYbt37yY9PZ327dvTtm1bQkNDtbZv27aN3r174+XlRa9evdi5cycAnTt3BsDf35/58+cX213xYBfLxo0bNU3vL7zwAmPHjiU5OblMXselS5d44403ePHFF/H29mbq1Kmkp6drtkdHRzN48GC8vLwICAjg559/plOnTqUqOzU1la1btzJu3DitRKtQcHBwkRar4vTt2xeVSlVid6iBQcH1i6GhYanic3V15b///S9+fn40b96cESNGEB8fr9menp7OBx98QOvWrfH29iYkJITExESt4+fNm4evry+9e/cmPz+/xDqjo6N57bXXaNGiBe3atePbb7/VbDt58iTDhw+nRYsWeHp60r9/f44dO1bqeO83b948Xn31Va3ndu7cScuWLcnOzubevXtMmzaNl156CQ8PD9q3b68VS2BgINOmTaNHjx60adOG2NhYrW7Eko4HyMzM5L333sPLy4tOnTqxZcuWh56XEydOMGjQIDw9PenatSuLFy9GrVYX2S8hIYEWLVoAMHz4cAIDA4FHf44jIyPx9vZm9uzZtGzZski3f0JCAkFBQQC88MILrFu3TrNtyZIlvPTSSzRv3pyQkBCtVtPSxgzw8ssvM3XqVKCgNWbr1q3ExsbSunXrh56TgwcPMnDgQJo1a0aXLl1Ys2ZNsfs9OFTgwW7GHTt24Ofnh6enJ506deLHH38ECrrj169fT1hYGK6urgDk5uYyZ84c2rZtS8uWLRk5ciRxcXGasjt16sTnn39Ohw4daN++PXfv3uW3337jlVdeoWnTpnTv3v2h3WuBgYGEhYWxYcMGXF1dSUhIICcnh2+++YZOnTrh6enJ4MGDOXHixCPru5+TkxOLFy/WSohUKhUA2dnZHD9+HAsLC83rA3jxxReJj48nKSkJgOPHj+Pi4sK6deuwsLB46PsBBS2B3bp1o1WrVo/cT1Qyiqiy3nzzTWXIkCGKoihKaGio4urqqly5ckVRFEWJiIhQ3NzclB9//FG5dOmSsnTpUsXDw0O5cOGCcuLECcXFxUWJjIxU0tPTldDQUKV169ZaZU+cOFEZN26coiiKcvToUcXDw0NZv369kpCQoERERCjt27dXPvnkE03dDx5/PxcXF+XPP/8sdtvt27eVNm3aKOPGjVPOnTunREZGKt27d9fUnZqaqrRp00aZNGmSEhMTo6xfv15p3ry50rFjx1KdowMHDiguLi5KUlJSqfbv2LGjsnz58mK39erVS5k1a5aiKIryzTffKK+++qrW9ps3byrjx49XfHx8lNTU1FLV5+LiorRu3VrZvHmzcu7cOWXEiBFK165dlZycHEVRFOXdd99Vhg4dqpw4cUI5d+6cEhISovj5+Sm5ubma4zt16qScP39eOXv2bIn13bp1S2ndurUyYcIE5cKFC0p4eLjSqlUrZc2aNUp6errSunVrZdasWcrly5eVs2fPKkFBQYqfn1+p471fTEyM4uLioly6dEnz3DvvvKNMmjRJURRF+eCDD5SAgADlxIkTypUrV5TFixcrLi4uyqlTpxRFUZRhw4YpHh4eyt69e5UTJ04oiqL9/pR0/MSJExUXFxdl+vTpSkxMjPLLL78obm5uyuHDhzXbCz9nN2/eVFq2bKksWLBAuXjxorJnzx6lQ4cOyg8//FDkdeXl5SlXrlxRXFxclLCwMOX27dslfo4PHjyouLi4KGPHjlUuX76sXLx4sUiZYWFhiouLi3LlyhUlMzNTCQ0NVVxcXJQxY8Yo58+fVyIjI5XWrVsrc+bMeeyY75eYmKi4u7srLi4uygcffPDQ/WJiYhQPDw9l9uzZSlxcnLJp0ybFw8ND2b9/v+b1pKenK4pS9G/8/u3JycmKh4eHsmbNGiUhIUHZunWr4uHhoURERCjp6enK22+/rYwZM0bzNzpnzhzFz89PiYyMVGJiYpTp06crvr6+mr+pjh07Kq1atVJOnDihnDx5Ujl9+rTi4eGh7Ny5U0lISFBWrFihuLq6FjnHilLwfTNmzBjl7bffVpKSkpS8vDxlypQpSrt27ZQ9e/YoMTExygcffKC0aNFCSUxMLLa+0hg3bpzyyiuvKIqiKEuWLFF69eqltf3WrVuKi4uL5nN9v0d9B/3999+Kq6urEhMTU6o4ROUh3YhV1N27dwkPD+f//u//gIKrL319fUJDQ3nnnXf49ddf6dSpEyNHjgQKrsDv3btHZmampivG2toac3PzEusyMTFh+vTpmi5KR0dHOnfuTExMzFO/jj/++AO1Ws3nn3+OiYkJAJ999hkDBgzg4sWLHDp0CJVKxccff4yRkRENGzYkJibmkS0U90tJSQEKXmuhwtab+23evJnatWs/siwLCwutFreoqChNC0d+fj7Z2dk0bNiQefPmlXh1er+goCB69uwJwOzZs+nQoQMRERE0aNCAzZs3s3fvXhwcHICCq1pvb2/27dtHx44dARg4cCCNGzcuVV1bt27FwMCAGTNmYGRkRKNGjfjoo4/Q09MjKyuLUaNG8e9//1vTQjdkyBDeeeedUsV7f1csQMOGDWnSpAlbt25l7NixZGZmsmfPHhYsWAAUtOAMHDgQDw8PAEaNGsXChQuJiYmhadOmAHh7e/Pyyy8X+1pKc3z9+vWZMmUKKpWKhg0bEhkZya+//lqkVWDlypV4enry1ltvAVCvXj3Gjx/PjBkzGD16tNa++vr6mr8hKysrrK2tWbFixSM/x4XGjBlTbPeVvr4+VlZWQEFXaWEZKpWKmTNnaurr0qWLZjD+48R8P3Nzc9auXcv58+eZPn06tWvXZuzYsUX2W7t2LY0bN+b999/XnMsHW3VKIykpidzcXGrVqoWjoyOOjo7UqFGDevXqYW5ujomJCWq1Gjs7O7Kysli6dClLly6lZcuWAEydOpV9+/bx+++/a7rdevTogZeXF1DQaqanp6cpe+jQodSrV6/YLmdra2uMjIwwMTHBzs6O1NRU1q1bx9y5czWf32nTpnH06FFWrlzJu+++W6S+kixatIjt27fz/fffAwWtq0ZGRlr7FD7Oycl5rHO5atUq2rVrR8OGDR/rOKF7kmxVUVu3biU3N5euXbsCBV8irVu3Zv369YSEhGjuuLnfG2+8ARR0WTyOJk2aYGJiwoIFC4iLiyM2NpYLFy5ovgyfxoULF3B3d9f8cwHw9PTE0NCQ2NhYzp07h5ubm9aXVfPmzUudbBUmWampqZqxVm5ubppuhkuXLjF69OiHdr3cLz09XSuJatSokSZx0NPTw9LSUvMP83Hc/4+/Ro0aODo6cuHCBU1M3bt319o/MzOTixcvapItZ2fnUtcVExODq6ur1vn08/PT/P6vf/2LlStXEh0dzaVLl4iKiipybh4W74PJVmHZGzduZOzYsezevRtzc3PN+KDevXuze/dufv/9d01d9+7d06rvUeNqSnN8s2bNNF06UPDZ2rp1a7Hn5dChQ5rkGQoGLGdlZXH79m1sbGweGgeU/Dku/Nw87jghCwsLraTB0tKSK1euPFXM5ubmNGnShCZNmpCcnMySJUuKTbZiY2M1SWuhoUOHAgXdhKXl7u6Ov78/I0eOxNnZmQ4dOhAQEECNGjWK7HvlyhVycnIYOXKk1vuWnZ2tlbTefx5ffvllXnjhBQICAmjcuDEdOnSgb9++RcY+FefixYvk5+drnUM9PT1atGjBhQsXiq3vURYuXMg333zDlClT6NChA1BwsfpgUlX42NTUtFTlFh6zY8cOPv3001IfIyoPSbaqqI0bNwJoDcJWq9UoisL+/fsxNDTU+rJ6lOL2u/+OqIiICEaPHk2vXr148cUXee2119i4cSPnzp17yleB1j+nB6nVagwMDEqVCD2Mh4cHBgYGHDt2jFdeeQUouKqsW7cugOY2+5JkZWVx8eJFTUshFIzLKiznaejr62s9VqvV6Ovrk5+fj6GhIevXry/yHt2f1D3qHD7oUZ+LpKQk+vbtS8OGDWnXrh3+/v7cunVL03paUrzF8fPzY86cOVy8eJEtW7bQo0cPzb6TJ08mIiKCPn360KdPH6ZNm0ZAQIDW8Y96baU5Xk9Pe1iqWq0udjxdXl4eXbt2LdKKB5SqlbKkz3Gh4sYNPsqD8d/vcWOOiooiPT2dF198UfOci4sLqamp5OfnF3kPH+c75EH3jx1UqVTMmTOHkSNHsmvXLsLDw1m1ahUzZ84sckNP4XE//fST5uKo0P2Dwe8/3yYmJvz8888cO3aM3bt3s2fPHpYtW8YPP/xAmzZtHhnnw94PRVG03rfS/I19+umnLF++nI8++oghQ4Zonq9Zs2aR8a2FY7Xs7e1LLLfQkSNHyM/PL/aiRlR+MkC+Crp69SrHjh1j3LhxbNiwQfOzbt06zM3NCQ0NpV69epw5c0bruJEjR7J06dIiX6CGhobcu3dP6wvy/tav1atX07NnT2bPnq0ZqH758uUyuYuoYcOGREdHa01bcfr0aXJzc2nQoAGNGzfm/PnzWleGjzOPlY2NDd27d2fhwoXFJlY3btwoVTnr16/HwMBAc7Vals6ePav5PTk5mevXr+Pm5kaDBg3Izc0lMzOTunXrUrduXezs7Pj888+5dOnSE9VVr149zp07R25urua5hQsXEhISwo4dOzAyMmLp0qWMHDkSX19fzfm5/71+WLzFcXBwoFWrVmzevJl9+/ZpWlvT09P5/fffmT17NuPHj6dnz54YGhqSlpZWqs9VaY9/8ILgxIkTxU7T0LBhQ+Li4jTnuW7dusTGxrJw4cJHJjz3H/+oz3FpPG5i87gxh4WFMXXqVK0k4tSpU9SrV6/YZLm475CpU6fy2WefFdm38NwXuv+miejoaGbNmoW7uzvBwcH897//pUePHmzevLnI665Tpw4GBgakpKRoXlOdOnWYP38+J0+eLPY8REZG8t1339GyZUv+7//+jz/++IMmTZoQFhb2sFOnUbduXQwNDfn77781zymKwokTJ0r9vgF8/fXXrFixgs8++0wr0YKCqRvu3LmjNezi8OHDODs7aw2qL8nff/9NkyZNSjX0Q1Q+kmxVQRs3bsTY2JigoCBcXFw0P02aNOHVV19l165dBAYGsnPnTlasWMGVK1dYtmwZhw8f5uWXX8bMzAwouNJNS0vD09NTc0dOfHw8ixYt0vqHam1tzcmTJzlz5gwXL17kq6++Yu/evY813uDMmTPs3btX6ycxMRF/f3+MjY15//33OX/+PEeOHGHKlCn4+vrSqFEjTRfXtGnTiI2NZcuWLSxfvvyxztcHH3yAWq1m0KBBhIWFER8fz9mzZ/n8888JDg7GxcVFa0xXRkYGycnJJCcnExcXx5IlS5g9ezbvvPOO1n5l5bvvviM8PJxz584xceJEGjVqROvWrWnQoAGdOnXi/fff58iRI8TGxjJx4sTH/kdwv8I7Fj/++GPi4uIIDw/nl19+oUOHDlhbW3Pz5k327NlDQkIC69at47vvvgO0x5Y8LN5H1blkyRIcHBw0416MjY0xNTVlx44dxMfHc/ToUcaNG4eiKKX6XJX2+KioKObMmUNsbCxLlixh//79xc6tNHToUC5fvsyMGTOIi4sjIiKCDz/8EFNT01IlWyV9jkuj8O/yzJkzpZos9HFj7tevH0lJSXz22WdcunSJDRs2sGTJEs2YrwcNGTKE8+fPM2/ePC5fvswff/zB77//XmzLiqenJz///DOxsbH89ddf/PTTT5ptVlZW/PrrryxcuFDzXh0/fhxPT0/N67569SpXr17F3NycwYMH8+mnnxIeHs7ly5f55JNP2LVr10PHKZmamrJw4ULWrFnD1atX2bdvH3FxcZryH8XU1JRhw4Yxa9YswsPDiY2NZfr06cTHxzNgwIASj4eCi4/vv/+eESNG0LZtW813R3JyMnl5edSuXZsuXbrw/vvvc/r0aXbv3s38+fMfe46vc+fO4eLi8ljHiMpDuhGroE2bNtGzZ89ixyQMHTqUlStXcubMGWbPns3ChQuZPXs2DRo0YOHChZovrP79+zN16lQGDRrElClT+M9//sOPP/7IsmXL6Nq1K8OHD+fy5csAhISEMHnyZIYNG4axsTEtWrRg4sSJLFiwoNTdcPPnzy/y3KxZs+jbty8//vgjM2fOpH///piZmdGtWzcmTJgAFHwZ/vDDD5ouokaNGtG/f/8iE5E+irW1NWvWrGHZsmV8++23XLlyBZVKhZubG5MnT6Zv375aY5jmzp2rmVna2tqaBg0aMHPmTM2g8LI2YMAAZs6cSVJSEr6+vixatEjT0jB79mxmzZrFW2+9RU5ODs2aNeOnn34q1XiU4lSrVo3Fixczc+ZMzbiZsWPH0rdvX9RqNX///TeTJk0iNzeXxo0bM2PGDMaPH8/p06c1Y/QeFW9xunXrxieffKI1NszQ0JAvv/yS2bNns3btWuzt7QkICMDS0rJIa0pxSnt87969uXjxIn369KF27dp8/fXXxf7DqlmzJj/++CNz5swhICAAKysrevbsWaQL9WFMTU0f+TkuDRcXFzp27MiIESN47733Shz/97gxOzs7ay4cfvvtN+zs7Jg4cSK9evUqdn9HR0e+//575syZw48//oijoyMzZsygTZs2RcZsffjhh3zwwQeav9H33nuPcePGAVCrVi3mz5/PvHnzWLRoEdWqVcPPz08zTuzVV19l586d9OzZk507d/L+++9jYGDA5MmTSU9Px83NjcWLFz903JSXlxeffvopP/zwA9OnT8fW1pZ///vfpZ78dvz48ahUKv7zn/+QkZGBp6cny5Yto169eqU6PiwsDLVazY8//qiZ0qLQpk2bcHFxYebMmXz00UcMGzaMatWq8dprrxVpASvJrVu3ymTYgtANlVIWfUFClJP4+HiuXr2qNenijz/+yN69e1m2bJkOIysbrq6ufP/995rB7pVdVYtXCCEqA+lGFJVaRkYGI0eOZOPGjVy9epX9+/ezdOnSh16NCyGEEJWNdCOKSs3NzY1PPvmEhQsXcu3aNezs7HjttdcYMGAAYWFhTJo06ZHHHzhwQDMWpiIVN5fXgx5c3PppVebzIYQQzzPpRhRVVkZGBjdv3nzkPnXq1Hni29efRk5ODtevX3/kPrVq1Soy2eHTqMznQwghnmeSbAkhhBBClCMZsyWEEEIIUY4k2RJCCCGEKEeSbAkhhBBClCNJtoQQQgghypEkW0IIIYQQ5UiSLSGEEEKIciTJlhBCCCFEOZJkSwghhBCiHEmyJYQQQghRjiTZEkIIIYQoR5JsCSGEEEKUI0m2hBBCCCHKkYEuK8/KyuL06dPY2dmhr6+vy1CEEEIIIR4pPz+f5ORkmjZtiomJSamP02mydfr0aYYOHarLEIQQQgghHsvKlStp1apVqffXabJlZ2cHFARds2ZNXYYihBBCCPFIN27cYOjQoZr8pbR0mmwVdh3WrFkTJycnXYYihBBCCFEqjzv0SQbICyGEEEKUI0m2hBBCCCHKkU67EYUQQohngVqtJiEhgYyMDF2HIsqAoaEh9vb2WFpalkl5kmwJIYQQT+nmzZuoVCpcXV3R05NOo6pMURQyMzO5evUqQJkkXPKJEEIIIZ7SnTt3cHBwkETrGaBSqTAzM8PR0ZGkpKQyKVM+FUIIIcRTys/Px9DQUNdhiDJkampKbm5umZRVqmRr06ZN9OzZk65du7Jy5coi28+cOUO/fv3o3bs3Y8aMITU1tUyCE0IIIZ6EOiuL1MOHSQkLI/n338n+p0uoPKlUqnKvQ1Scsnw/S0y2EhMT+eqrr1i1ahUbNmzgt99+IyYmRmufTz/9lJCQEDZu3Ej9+vVZsmRJmQUohBBCPI6048eJnTyZqwsXkvjrr9xcv564KVO4MncuOTdu6Dq8CpGens7HH3+Mn58fAQEBBAYGcubMGQAiIyMJDAx87DLT0tJ46623yjrUUjt16hRTpkx56nIURWH27Nl0796dnj17cvTo0TKI7tFKHCAfERGBj48P1tbWAHTr1o1t27YRHBys2UetVmvuwMjMzMTKyqqcwhVCCCGKpygKSatXkxIWhlGtWtR87TUMbGxQ1Goyjh8n9dAhLs2aRb3//AejZ3jVErVazeuvv463tzcbNmzAwMCAgwcP8vrrr7N58+YnLvfu3btERUWVYaSPx9PTE09Pz6cuJywsjNjYWLZs2cLly5cZM2YMW7ZswcCg/O4ZLLFlKykpSWtaent7exITE7X2mTRpElOnTuWll14iIiKCQYMGlX2kQgghxCOkbNtGSlgYVm3bUjMoCCMHB/SMjNA3McHSxwf7wYNRcnO5/Nln5JTRwOfKKDIykuvXrxMSEqJJIHx8fJg1axZqtVpr38DAQCIjIwFISEigU6dOQMHwoYCAAPr27UtISAjZ2dnMmDGDpKQkTevWhg0bePXVVwkICGDy5MlkZ2dr6ho1ahQBAQFaY54iIyPp378/ffv2ZeLEiWRkZDBx4kT69u1LQEAAf/zxBwC5ublMnjyZbt26ERQUxPDhw4mMjNRqkbt48SKBgYH4+/szcOBATp48CRTkIzNmzGDw4MF06tSJ0NDQIucnPDycnj17oqenR/369alVqxZ///13mZ3/4pSYxqnVaq1+S0VRtB5nZWUxZcoUli5dipeXFz///DMTJ05k0aJF5ROxEEII8YDUQ4dI+u03qjVvjmW7dvBAUgFgZGeH/aBBJK1eTcKCBdT/6CNUj7nsSmlF3orgr5sHyqXsNjXa4m3r+9DtZ8+exc3Nrcidke3btwcoMhSoOPPmzWPNmjXY2toye/Zs4uLimDp1KkFBQSxcuJALFy6wZs0aVq9ejbGxMV9++SVLlizhzTff5Pbt25qWtQddunSJ3bt3Y2FhwZw5c/Dw8GD27Nmkp6czaNAgmjVrxp49e8jMzGTbtm1cu3YNf3//IuVMmDCB0aNH07VrV44fP87bb79NWFgYULB+4apVqzh//jxBQUH069dP69ikpCTs7e01j+3s7LhRzt3LJSZbNWvW5MiRI5rHycnJWkGeP38eY2NjvLy8ABg4cCBff/11OYQqhBBCFJWbksL1n37CpH59qnfvXmyiVcjIzo7qXbtyc8MGUsLCsO3ZswIjrRh6enoYGxs/VRkdO3Zk8ODBdOnShW7duuHu7k5CQoJme2RkJJcvX2bAgAFAQWtUkyZNNNubNWtWbLn169fHwsICKBimlJWVpWl9unfvHhcuXODAgQMMGDAAlUqFo6Mjbdq00SojIyODK1eu0LVrVwCaN2+OlZUVcXFxALRt2xaVSoWLiwt37twpEkNxjUjlPWVHicmWr68v8+fPJyUlBVNTU7Zv38706dM12+vWrcuNGzeIi4ujQYMG7Nq1q0z6VIUQQojSSFy5EiU/H1t/f1CUEvc3dXHB1MWF5PXrsWjVCqP7GhDKiret7yNbn8pT06ZNWbVqVZGeqLlz5+Lr61vkLjvln3OWl5eneW7q1KlER0cTHh7OhAkTCA4OpmXLlprt+fn59OjRg6lTpwIFCVB+fr5mu4mJSbGx3f+8Wq23+C2LAAAgAElEQVTmiy++wMPDAyiYGNbKyorQ0NAi3Z3Fxfvgc4X1FyaaD7ubsGbNmlrzZ928eVOrEak8lJjKOTg48O677xIUFESfPn3w8/PDy8uL119/nVOnTmFlZcWsWbN455138Pf3JzQ0lJkzZ5Zr0EIIIQRA2t9/k3b0KDavvIK+qWmpjlGpVNh06QJ6etxYtqycI6x4rVq1wtbWlgULFmgSkH379rFu3ToaNWqkta+NjY2mW3Hnzp1AQdLVtWtXbGxsGDNmDAEBAURFRWFgYKBJyLy9vdmxYwe3bt1CURSmTZvGL7/88lhx+vj48OuvvwIFXXu9e/fm+vXr+Pr6smXLFhRFITExkUOHDmklTtWqVcPJyYnt27cDcPz4cW7evEnjxo1LVW+7du3YtGkT+fn5XL58mUuXLpV7I1Gpht77+/sX6TNdvHix5vf27dtr+oKFEEKIiqDOyeHG8uUY1a6N+WP+szSwsMCqTRvu7NlDZlwcpg0alFOUFU+lUvHtt98ya9Ys/Pz8MDAwwMbGhkWLFlGjRg1iY2M1+44aNYpJkyYRGhpK586dATAwMCAkJIQRI0ZgbGyMra0tn332GZaWltSuXZvAwECWL19OcHAww4cPR61W4+7uzujRox8rzuDgYKZNm4afnx/5+flMmDCBOnXqMGDAAKKjo/H398fOzo7atWtjYmJCZmam5tgvvviCadOmMX/+fAwNDZk/fz5GRkalqrd79+6cPHmS3r17AwXTVz2sJa6sqJTi2uMqSEJCAp07d2bXrl04OTnpKgwhhBBVUMqOHSSuXEnNESMwuu+u+dJSZ2dz7fvvMXNzw/mdd54qlqioKNzd3Z+qDFFgz549KIpCx44dSUtLo0+fPoSGhmqmoKpID76vT5q3yELUQgghqhx1Tg63Nm/GtHFjjBwcHjko/mH0jI2xaNmSuwcOkJWQgIlc9FcKDRs25P3332fevHkAhISE6CTRKkuSbAkhhKhy7oSHk3fnDjX69n2iRKtQtZYtST18mJubNuH0xhtlGKF4Us7OzpqxXM8KWYhaCCFElVKkVesp6JuaUq15c9IOHyb39u0yilAIbZJsCSGEqFJS//qLvDt3sHrppadq1SpUrXlzUKu5u39/GUQnRFGSbAkhhKgyFEUhZedOjGrXxvApW7UKGdrYYOzszJ29e4udw0mIpyXJlhBCiCoj8/x5suPjsWzTBlUZJkbVvLzITU7m3rlzZVamEIUk2RJCCFFlpOzYgZ65OaYNG5ZpuaaurqiMjbmzZ0+Zlqsr6enpfPzxx/j5+REQEEBgYCBnzpwB0FrQ+XGkpaVpFqHWhVOnTjFlypQyK+/cuXP06tWrzMp7FLkbUQghRJWQe+sWaUePYt2hw0OXYnlSeoaGmLu7k3b0KPn37qFvZlam5VcktVqtWQh6w4YNGBgYcPDgQV5//XU2b978xOXevXuXqKioMoz08Xh6epbZTO8bNmzgyy+/xNDQsEzKK4m0bAkhhKgS7oSHA1CtnJZWMW/aFCU3l7Rjx8ql/IoSGRnJ9evXCQkJwcCgoE3Fx8eHWbNmFVlzMDAwkMjISKBgws5OnToBsGnTJgICAujbty8hISFkZ2czY8YMkpKSNK1bGzZs4NVXXyUgIIDJkyeTnZ2tqWvUqFEEBASQm5urFVf//v3p27cvEydOJCMjg4kTJ9K3b18CAgL4448/gIJFrSdPnky3bt0ICgpi+PDhREZGarXIXbx4kcDAQPz9/Rk4cCAnT54EYNKkScyYMYPBgwfTqVMnzSLX90tLS2PXrl3MnTu3zM55SaRlSwghRKWnqNXc2b8fMzc39MzMSrXg9OMyql0bfUtLUiMjsX7ppTIvv6KcPXsWNzc39PS021MKl9UrXAvxUebNm8eaNWuwtbVl9uzZxMXFMXXqVIKCgli4cCEXLlxgzZo1rF69GmNjY7788kuWLFnCm2++ye3btzUtaw+6dOkSu3fvxsLCgjlz5uDh4cHs2bNJT09n0KBBNGvWjD179pCZmcm2bdu4du1akeUCASZMmMDo0aPp2rUrx48f5+233yYsLAyAGzdusGrVKs6fP09QUBD9+vXTOtbCwoL58+eTkJBQ6nP6tCTZEkIIUellnDlDXkoK1bt1K5dECwrWFDRzcSHt77+fuitx57EUth9JKcPo/qdrq+p0eaH6Q7fr6elhbGz8VHV07NiRwYMH06VLF7p164a7u7tWchIZGcnly5cZMGAAUNAa1aRJE832Zs2aFVtu/fr1sbCwACAiIoKsrCxN69O9e/e4cOECBw4cYMCAAahUKhwdHWnTpo1WGRkZGVy5coWuXbsC0Lx5c6ysrIiLiwOgbdu2qFQqXFxcuHPnzlOdh7IiyZYQQohK787eveibm2Pi7Fyu9Zi5uZF25Ajpx49j5etbrnWVl6ZNm7Jq1SoURdEa2zZ37lx8fX2LjHcrnO4iLy9P89zUqVOJjo4mPDycCRMmEBwcTMuWLTXb8/Pz6dGjB1OnTgUKEqD8/HzN9oct7Hz/82q1mi+++AIPDw8Abt68iZWVFaGhoUW6O4uL98HnCusvTDTLelzf05BkSwghRKWWl5ZG2rFjWLVtC+X8D9Sodm30LSy4e/DgUyVbXV54dOtTeWrVqhW2trYsWLCAN998E319ffbt28e6desICgoiNjZWs6+NjQ0xMTH4+Piwc+dOoCDp6tmzJ8uXL2fMmDHk5uYSFRWFt7e3JiHz9vbmp59+4o033qB69epMmzaNOnXqMG7cuFLH6ePjw6+//qoZC9anTx9Wr16Nr68vW7ZsoXPnziQlJXHo0CGGDx+uSbKqVauGk5MT27dv13Qj3rx5k8aNG5fhWSxbkmwJIYSo1FIPHoT8fMz/aQEpT4VdieknTpCfmYm+qWm511nWVCoV3377LbNmzcLPzw8DAwNsbGxYtGgRNWrU0Eq2Ro0axaRJkwgNDaVz584AGBgYEBISwogRIzA2NsbW1pbPPvsMS0tLateuTWBgIMuXLyc4OJjhw4ejVqtxd3dn9OjRjxVncHAw06ZNw8/Pj/z8fCZMmECdOnUYMGAA0dHR+Pv7Y2dnR+3atTExMSEzM1Nz7BdffMG0adOYP38+hoaGzJ8/HyMjo7I5geVApehwutyEhAQ6d+7Mrl27cJLV1oUQQhTj4iefoOTk4BAYWCbL85QkOyGBxJUrqT12LFY+PqU6JioqCnd393KO7PmwZ88eFEWhY8eOpKWl0adPH0JDQ7G2tq7wWB58X580b5GpH4QQQlRaOcnJZMXFYe7lVSGJFhR0JeqZmlb5KSCqqoYNG7Jo0SICAgIYNmwYISEhOkm0ylKpuhE3bdrEd999R15eHsOHD2fo0KGabVFRUUyaNEnzOCUlBSsrK818GUIIIcSTSv1nDqiynjH+UVR6epg0aEDG6dMoajUqPWmXqEjOzs78+uuvug6jTJWYbCUmJvLVV1+xbt06jIyMGDRoEN7e3jRq1AgAd3d3fv/9dwAyMzP517/+xbRp08o1aCGEEM+H1MhITOrVQ9/cvNymfCiOacOG3DtzhszYWMwq8cBrUTWUmK5HRETg4+ODtbU1ZmZmdOvWjW3bthW77w8//MCLL75Iq1atyjxQIYQQz5fsa9fIjo/HvGnTCk20AEzr1weVivS//67QesWzqcRkKykpCTs7O81je3t7EhMTi+yXlpbGmjVrCA4OLtsIhRBCPJdSDx0ClQqTBg0qvG49ExOMnZxIO368wusWz54Sky21Wq01MdiDk6QV2rhxI126dMHW1rZsIxRCCPHcURSF1MhITBs21Nn0C6YNG5Jz7Rq5t27ppH7x7Cgx2apZsybJycmax8nJydjb2xfZb+fOnfTs2bNsoxNCCPFcyk5IIOf6dczuWwKmohUOyk87cUJnMYhnQ4nJlq+vL3/99RcpKSlkZmayfft22rVrp7WPoiicOXOGFi1alFugQgghnh+pkZGgp1cwdkpHDGxt0beyIuPkSZ3FUJYCAwOJ/OfuzsexZs0anc4wMGXKFE6dOvXU5ezcuZOAgAB69+7Nm2++yd27d8sgutIpMdlycHDg3XffJSgoiD59+uDn54eXlxevv/665sWnpKRgaGj41AtfCiGEEJouxMaN0XvIGnsVQaVSYVK3Lveio1HuW/fveXPs2DFycnJ0Vv+nn36Kp6fnU5WRnp7OtGnTWLRoERs3bsTV1ZX58+eXUYQlK9U8W/7+/vj7+2s9t3jxYs3vtra2HDhwoGwjE0II8VzKuniR3ORkrF56SdehYFKvHhknT5J16VKFzvX1NBRFYc6cOezcuRN9fX0GDhzI8OHDNdsjIyNZsGABy5cvB2DSpEm0bt2arl27Mn78eG7evAnAW2+9hampKX/++ScHDx7Ezs4Od3d3PvzwQ27cuIFKpeK9997D19eX+fPnc/z4ca5fv86wYcMYMmSIpr7AwECsrKy4cOEC8+bNIzk5mW+++Ya8vDycnJyYPn06NjY2REZGMmPGDPT19WnevDmxsbEsX76cwMBAgoOD8fb25vvvv2fjxo3o6+vTtm1bJkyYwPXr1wkODqZx48ZERUVha2vL119/rTURam5uLh999BEODg4AuLq6smnTpop4OwBZG1EIIUQlkxoZCfr6mOiwC7GQSd26AKSfOvVYydadAwe4u3dvucRk1a4d1m3bPnT7tm3bOHbsGJs2bSI3N5chQ4aUakz1jh07cHR0ZNGiRURFRbFx40YmTpxIp06daN26NS+//DLvvvsu/fr10ywSPWTIEDZs2ABATk4OW7ZsKbZsV1dXFixYQEpKCpMmTWLZsmVYWVmxevVq5syZw7Rp03j//ff54YcfcHNzY8aMGUXKCA8P588//yQ0NBRDQ0PGjRvH6tWrad++PdHR0cycOZMmTZowbtw4Nm3aRGBgoOZYGxsbXnnlFQCysrJYtGiR1vbyJsmWEEKISkNRq0k9dAgzNzf0DA11HQ76ZmYYOjiQcfo0dn366DqcUjl8+DA9evTAyMgIIyMjzcTjJWnRogVz584lMTGRDh068NZbbxXZJyIigri4OL755hsA8vLyiI+PB8DLy+uhZRduO3HiBNevXycoKAgomPHAysqK8+fPY2tri5ubGwD9+/fn008/1Srj4MGD9OrVC9N/7k7t168fGzZsoH379tja2tLkn5spGjdu/NDxWGlpabz11lu4ubnx6quvluq8lAVJtoQQQlQamTEx5N2+jU3nzroORcOkXj3SjhxBnZVV6jFk1m3bPrL1qTwZGBhoTdGUkJBA9erVNY9VKhXKfZPE5ubmAlCvXj22bt3Kvn372L17Nz/99FORliq1Ws0vv/yi6aJLSkrC1taWnTt3YvKIc1O4LT8/nxdeeIHvv/8egOzsbDIyMkhKSkJdwtqXxW3Py8sD0Boz/uDrK5SUlMTIkSPx8fFh8uTJj6yrrMmCT0IIISqN1MhIVIaGGNerp+tQNEzr1YP8fO6dO6frUErlxRdfZPv27eTm5pKZmcmoUaO0JiO3sbEhPj6e7Oxs7ty5w9GjRwFYsWIF8+fPp0ePHnz00UekpKSQnp6Ovr4++f/cIODj48OqVasAiImJwd/fn8zMzFLH1qxZM44fP87FixcB+Pbbb/n8889p0KABqampnPvnHBc3nsrHx4fNmzeTlZVFXl4eoaGh+Pj4lKre/Px8xo4dS48ePZgyZUqx84WWJ2nZEkIIUSko+fmkHj6MWZMm6Onr6zocDSNHR9DXJ/3UKao1a6brcEr0yiuvcPr0afr27YtarSYoKIj6941/a9y4Me3bt6dXr144OjrSsmVLAPr06cP48ePx9/dHX1+fCRMmYGlpia+vL3PnzsXCwoKpU6fy4Ycfam6a+/zzz6lWrVqpY7Ozs2PmzJm88847qNVqHBwc+OKLLzAyMuLzzz9n4sSJ6OnpUb9+/SItZR07diQqKop+/fqRl5fHSy+9xLBhw7hx40aJ9f7555+cPXuW/Px8wsLCAGjatGmRrsryolKKa2urIAkJCXTu3Jldu3bh5OSkqzCEEEJUAhlnznDliy+wHzgQk0rUsgWQuHo1Sm4uDWfOLHZ7VFQU7u7uFRzVs0OtVjNnzhyCg4MxMzPj559/JjExkUmTJuk0rgff1yfNW6RlSwghRKWQGhmJytgYozp1dB1KESbOztw9cID8jAz0zc11Hc4zR09PD2tra/r374+hoSGOjo4V1upUESTZEkIIoXNKXh6pR49i3rQpenqVbzixcZ06sH8/986fx0JWSykXo0ePZvTo0boOo1xUvk+0EEKI50766dOoMzIwd3XVdSjFMq5VC/T1yTh7VtehiCpIki0hhBA6l3boEHpmZhg5O+s6lGKpDAwwrl2be9HRD91Hh0OgRTkoaSqKxyHJlhBCCJ1S5+SQduwY5p6eVOwN+Y/H2NmZ7IQE8u/dK7LNxMSEW7duScL1DFAUhZycHK5evYp5GY3PkzFbQgghdCr95EnUWVmVtguxkEmdOqRGRJB54UKRKSCcnJxISEggOTlZR9GJsmRgYICVlRU1atQom/LKpBQhhBDiCaUeOoS+hQWGtWtDJW4ZMqpdG/T0yDh7tkiyZWhoqDWXlRD3k25EIYQQOqPOyiL9+HHMvbxQVeJEC0DP0BDjWrUeOW5LiOJIsiWEEEJn0o4fR8nJwczFRdehlIpxnTpkxcejzsrSdSiiCpFkSwghhM6kRkaib2WFYc2aug6lVIydnUGt5l5MjK5DEVVIqZKtTZs20bNnT7p27crKlSuLbI+LiyMwMJDevXszcuRI7t69W+aBClFZZOVncS3zKlfvJZCv5Os6HCGqrPyMDDL+WW9QVYa32ZcnY0dHUKnIOHNG16GIKqTEAfKJiYl89dVXrFu3DiMjIwYNGoS3tzeNGjUCCm6RfOONN5gyZQrt2rVjzpw5LFq0iAkTJpR78EJUlMsZFwm7sZULaee4l/+/276N9Yypb94AV0t32tl1xETf5BGlCCHul3bsGEpeXpXpQgTQMzLCqFYt7p07p+tQRBVSYrIVERGBj48P1tbWAHTr1o1t27YRHBwMwJkzZzAzM6Ndu3YAjB07ltTU1HIMWYiKczE9lj+u/U50WhRm+mY0sfTEytCSagYW5Cl53Mi6ztXMBH6/uo4/E3fi79iHNrZt0VNJD70QJUk9dAgDW1sMatSo1HchPsjYyYm0o0dRZ2ejZ2ys63BEFVBispWUlISdnZ3msb29PSdPntQ8vnLlCjVq1GDy5MlERUXRoEEDPvjgg/KJVogKoigKe5P3sDZ+NdUMqtG1Zg/cLNxQqfS19mtkUXBFnph5g30397Dq8jL2Ju1mZIOx2JvY6yJ0IaqEvLQ0Ms6cwbp9+0p/F+KDTOrUIe3QITJjYzFv0kTX4YgqoMTLb7VajUr1vzl9FUXRepyXl8ehQ4cYPHgw69evx9nZmc8++6x8ohWiAuSp81h9ZQVr4lfhaunO8HqjcLf0KJJo3c/BtCb9nAbSs1ZvbuXcYs65WcSlx1Zg1EJULWlHjoBajWkV6kIsZOzkVDBuS9ZJFKVUYrJVs2ZNrRlxk5OTsbf/3xW7nZ0ddevWxdPTEwA/Pz+tli8hqpJcdS7fxnzD/pt7aWfXka4OPdDTK12XoEqlorGFC/9yHoyhypCvz3/J37ePlnPEQlRNdyMiMHJwwMDGRtehPDY9Y2MM7e1l3JYotRL/i/j6+vLXX3+RkpJCZmYm27dv14zPAmjRogUpKSlE/zPJ259//omHh0f5RSxEOVErapZf+plzaVEE1O7LCzateJKF2myMbPiX82DsTexZEvcDR1Iiyz5YIaqwnKSkgiVvWrSocl2IhUycncm6eBF1bq6uQxFVQInJloODA++++y5BQUH06dMHPz8/vLy8eP311zl16hQmJiYsXLiQqVOn0qtXLyIjI5k0aVJFxC5Emdp0bQNHbx+mq0MP6ldriMKT/xMwMzDjVcf+OJo6sezSz1xIkytgIQrd/esvgCp1F+KDjJ2dUfLyyLp0SdehiCqgVGsj+vv74+/vr/Xc4sWLNb83a9aMtWvXlm1kQlSgA8l72X5jK62r+9DEsulTJVqFDPQM6VU7gLXxv/JD7ELec51ELdPaZRCtEFWXoiikRkRg2rgxemZmVeouxPsZOzkBcC8qCrPGjXUcjajs5P508dy7nHGJ1VdW4Wrhhm+Nl1FUZfflb6JvQm/Hvuihz8ILX3M3Vyb8Fc+3rLg4chITMffyqrKJFoC+mRkGtrZkyLgtUQqSbInnWo46h18uLcHC0IKuDt3LpEXrQZaGVvg79iEtL5WlFxejVqrGTNlClIe7ERGoDA0xrV9f16E8NWMnJ7JiY1GqyOz3Qnck2RLPtY1X15GYdYNetXqjp1eqXvUn4mBSk/b2nTmfdo7tN7aWWz1CVGZKXh6pkZGYN22KyqD8/t4qiomTE+qsLLKvXtV1KKKSk2RLPLeiU6PYnbQLH9u22Js4lHt9HpZNcbVwY/O1jcSlyyK24vmTfuoU+enpmHt6VukuxELGzs4A3PvnbnwhHkaSLfFcyszPZMWlpdgZ29O6uk+5dB8+SKVS0dH+FSwMLfkpbhH38jLKvU4hKpO7Bw6gb2GBce1n40YRfUtL9C0sZL4tUSJJtsRzaev1P7idm0LPWv5aKyKUN2N9Y7rX7MXd3Lv8dmVVhdUrhK7lZ2SQfvw41Zo3fyZataDgAsrYyYnMCxdQnpHXJMqHJFviuZOYdYPdibtoZdMaG6PqFV5/TdNavFjdhyO3D3H67qkKr18IXUg9fBglLw8zd3ddh1KmjJ2cyLt7l9ybN3UdiqjEJNkSzxVFUVgb/xtGeoYV1n1YnFbVW2NrVINfLy8nMz9TJzEIUZHuRkRg6OCAQfWKv8ApT5r5ts6f13EkojKTZEs8V07fPcnZ1NO0t++Eob6RzuIw0DOgi0M37uTe5veEUJ3FIURFyL5+nczz57F44YUquzzPwxja2aEyMeFeVJSuQxGVmCRb4rmRq84lNGEN9sYOuFk20XU41DStRQvrluy7Gc6FNLkqFs+uO+HhoK+PmZubrkMpcyqVCmNHRzIvXNB1KKISk2RLPDf2J4eTnJ1EZ4euug5Fo02NtlgZWvHr5eXkK3m6DkeIMqfOzeXugQOYN22KnrGxrsMpF8ZOTuQkJpKXlqbrUEQlJcmWeC5k5Wex7cYWGlVrTE2TWroOR8NQz4h2dp1IzC4YtC/Esyb92DHy09Ko1qzZM3MX4oNM/hm3lSnjtsRDSLIlngt7knaRnpeGb42XUVO5ltZoUK0h9c0bsvn6Ju7k3NZ1OEKUqdvh4RhUr46Ro6OuQyk3RjVrgr4+GTK5qXgISbbEM+9eXgY7E7fjbtmE6ka2ug6nWO3tOpKv5BGasEbXoQhRZrJv3ODe2bNYvvgiqmd4/UCVgQHGtWrJHYnioSTZEs+8nYnbycy/R5vqbXU21UNJrIysaWXTmmO3j3A+Ta6OnzdqtUJmdj6303JJSctFra6cn9PHdXvXroKB8R4eug6l3Bk7O5MdH486O1vXoYhKqOqvBCrEI6TlprI7aRdeVs2xNLKutMkWFMy9FZ12lt+urGJyk4/QV+nrOiRRDrJz1RyPSedcfAax1zKJvZ7FrdRcrX0M9FXYWxtSs7oRzRpUw9vdijr2xhW62sHTys/M5O6+fVg0b46ekdEzO16rkLGjI6jVZMbGYt5E93c7i8pFki3xTNuZuJ1cdQ7e1dtU6kQLwEDPkJdqdGDz9d85kLyXdvYddR2SKCPZuWoOnL5LxJm7HDmfRnauGj09cLQ1xs3ZlOoWlhgaqjDS10OtKNzNyON2Wh43bufwc9gNfg67QU0bI7q8YEPvtjWwMK38X913DxxAnZVFtRdeeOYTLbhvctPoaEm2RBGl+ovdtGkT3333HXl5eQwfPpyhQ4dqbV+wYAGhoaFYWloCMGDAgCL7CFHRMvIy2Je8By/r5pgbVqv0yRZAw2qNcDatw6ZrG2hZvTXmBua6Dkk8hesp2Ww+eIvtR1JIy8zHppoBL3la0aSOGY41jNHTU5WYh6Tdy+Ncwj3OXspgxa5EQvcn4+9Tg1dfqoF1NcOKeSGPSVGrub1rF8Z162JYowY8w+O1CukZG2Po4CDjtkSxSky2EhMT+eqrr1i3bh1GRkYMGjQIb29vGjVqpNnn9OnTzJ07lxYtWpRrsEI8jj1Ju8hWZ9PKpnWVSLSgYILEl+078uvlZWy+tpEBdQbrOiTxBC7dyGTVn4nsP30XlQpauVjQxt0SRztjFOV/XYGlafCxMDOglYslrVwsuZGSTfjJO/w3PInNkTcZ4+dIlxdsKl33Ysbp0+Rcv47dv/71XCRahYwdHck4fRolPx+VvgwDEP9T4gD5iIgIfHx8sLa2xszMjG7durFt2zatfU6fPs0PP/yAv78/n3zyCdkyQFDoWFZ+FnuSdtHEsikWhpa6Duex2Bnb0dTKi33Je7iReV3X4YjHcDkxi5mrLvHG1+c5cj4NP29bPhxWj/7t7Kldw0Qr0XoSNasbM7CDA+P/5UzN6kbMXRvPh0svknw3p4xeQdm4tXUrBtbWmDZooOtQKpSxkxNKTg5Zly/rOhRRyZSYbCUlJWFnZ6d5bG9vT2JiouZxRkYG7u7uTJgwgfXr15Oamsq3335bPtEKUUr7ksO5l3+PF6tXnVat+/nYtsVQz5D/xq9GeQ7Gu1R1t9Nymb8+gTe/PseR82n0bmPLlKF1ecnTGlNj/TIfsmRvbcSonrXp07YGJy+m88a8cxw5l1q2lTyhzLg47kVFYfXSS7oOpcLJotTiYUpMttRqtVYTtaIoWo/Nzc1ZvHgxDRs2xMDAgBEjRhAeHl4+0QpRCjnqHHYlbqdxNRdsKum8WiUxMzCjtW0botPOcib1lK7DEQ+Rm6dmzZ5ERn4ZTdiRW3RpacPkIXVp23lyvccAACAASURBVNQaQ/3ynVlHT6WiTRMr3unrjHU1Az765SIbDiTrPDm/tWULeqammLm76zQOXTCwsMDA2pp7MrmpeECJ3wY1a9YkOTlZ8zg5ORl7e3vN42vXrrF27VrNY0VRMDCo/HfKiGfXwVsRpOWl0roK3IH4KM2sW2BjWJ218b+Rp5Z1EyubUxfTeWv+eX4Ou4FHXXMmD65LlxbVMTKo2OkLbS0NGePniEc9c3744xrfrE8gN08346RyEhNJO3oUyzZtUOk9n9M4Gjs5kRkTo/OkV1QuJf41+Pr68tdff5GSkkJmZibbt2+nXbt2mu0mJiZ88cUXxMfHoygKK1eu5JVXXinXoIV4GLWi5s/EHdQxq4udsX3JB1Ri+ip9XrZrT3J2EnuTd+s6HPGP1Iw8vgqN5/1FsWTnqBnXx5GBHeypZmags9Te2FCPIZ0d6NTcmm2HU5i56rJOEq6bf/yBSl+/YB3E55SxkxP56enk3Lih61BEJVJisuXg4MC7775LUFAQffr0wc/PDy8vL15//XVOnTpF9erV+eSTT3jjjTfo3r07iqLw73//uyJiF6KI03dPkpydRCsbbxRV1b+yrGfegHpm9dl8bSNpuWm6Due5pigKO4+l8PpX0ew6lkIvb1ve7eeMk50JlWHCdz2Vim4v2hLgW4ODUal8uvISORWYcOUkJXH3wAEs27QpmMT0OSXjtkRxStXf5+/vj7+/v9Zzixcv1vzerVs3unXrVraRCfEE/kzciY2hDXXM61bpLsRCKpWKl+06sOLyUjZd28CQuoG6Dum5dPVmNvM3JHAiNh0XJ1P6+dthbVE557jy9bBCpeL/2bvv8KjOO+//73OmjzTqGlUkikCid1NMr6aDnUqyTp7dOJtfnmzxcz3ZK7/N/p4nu9ndbPfGjp0ExzUGG1e66QZMMWAwvQoV1Hsbaeo59+8PAbEdYwkY6WhG9+u6fOFBI+mDNJr56r6/53uz6Ug9//haCX/37YG9srVZv3UrismEa9KkHv9cfZk5KQnV6aTjyhUSZ882Oo7UR/TPTXUpKpV13OS65yqTk6ZGRaF1W5ItmbEJ4zla/yEVHeVGx+lXhBBs+6ie//n0NQorOnh8YRrfW5rRZwut26aNiOfRGSmcvNrGLzaUomk9+/MQqKmRq1q3KIrS2bd1/brRUaQ+RBZbUtTYX7MHm2pjmCvf6ChhNyV5GjbVzltlr8vG217S2Brk/7xczLObK8gf4OBvvp7DyIGxDzwrq7dMGR5/Z0vxua0VPfq4qdu0qXNVa+LEHvsckcSWnU2wvp5gU5PRUaQ+QhZbUlRoDjTzceNJJiROwqRG39WwdpODqSnTue65xtnmT4yOE/U+PN/MD/77KueKPXxrvptvL0jDbo28ieDTR8Yzd2wCO443sPFAbY98Dl9pKa0ffUT8zJn9flXrttt9W3J1S7pNFltSVDhU9wECnZFxo42O0mNGx48lxZrKu+VvEdSDRseJSh6vxr9vvMk/byjFnWjlx1/NYcxgV8SsZn2RRZOTmJAXyyu7q9l7ujGsH1sIQe2bb2KKiSFOrmrdYU1LQ7FYaJfztqRbZLElRbyA7udw3UFGxI0kxhJrdJweoyoqM1Pn0BCo54PavUbHiToXS9r54S+vcuBcE6unp/D9pRnExUT+KqmqKDw2y83QLAf//U45F0vaw/ax2y9coP3iRRLmzYN+Olfriyiqii0ri46rV42OIvUR8qdDinjHG47RrrUzLmGC0VF6XE5MLoNj89hZtZ2WYLPRcaKCEIK3D9XyN88Xoqrw468OYPrIeOhjhzs/CLNJYe38NBJdZv5pfQn1LQ++MipCIWo3bsSSkkJMP5wW3xVbVhaBykq0jg6jo0h9gCy2pIjWOcR0L9mOHFIifIhpd81ImU1QD7Kl4j2jo0S8Nm+Iv/99CS+8X8XkYXH81aPZJMVZo+ha1j9w2kz8yYJ0OvwaP3+tmEDwwWZwNe3bh7+8nKQlS8KUMLrYBgwAIfAWFhodReoDZLElRbRLrReo9dcwKWkyRM9CxJdKtCYyPnEixxuOUdpeYnSciFVa4+Ovn73OqWttfGu+m8dmpWCK8q2w9CQrX5vt5lq5l2c3l9/3FYqh5mbqNm3COWIE1qysMKeMDtaMDFBVuZUoAbLYkiLcvpo9xFsSyHEONDpKr5qcNBWHycnbZW/IURD34ejFFp587jpev86Tj2UzNsKb4O/FqEGxzB+fyO5TTez6+P4a5mvffBM9ECBx3jwU+fj7QqrVijUtjXZZbEnIYkuKYGUdN7nWdoXJSVNQoqi/pjtsJhvTUh6mqP0Gp5pOGh0nYggheH1/DT9/rYSsFBtPPjaAlPjo3Db8MgsmJDI0y8FzWyoorvbe0/u2X7xIy9GjJM6ZgykmpocSRgdbdjb+khL0oLx6uL+TxZYUsT6o3YtVtTLMVWB0FEOMiBuF2+bmvfK3Ceh+o+P0eSFN8NQ7Zby6p5qZo+P53tIMbNb++RSoqgpfn+PGYVX55/WleP1at95P9/upevllLG43sf38WJ7usA0YgAiF8JWUGB1FMlj/fKaRIl5LsJmPG08wPmEiFrVvH53SU1RFZVbqXJqDTeyt3m10nD6t3afxf14uYs+pJtY8nMLKacn9bjX081xOM1+f46ai3s+zmyu69T51771HsK6O5JUr+0uL5AOx3epn65Dztvo9WWxJEelQ7QF0oTM6fozRUQyV5RzA0Nh8dle/T1MgvAMro0VTW5C/WVfIuSIP/+ORdKaNjEfvJ/1ZXcnLcjJ/QiL7Pmliz6kvf/x4Cwtp3LWLuGnTsKak9FLCyGZyOjEnJ8smeUkWW1LkCegBPqw7yPC4EcRa4oyOY7gZqbPQ0dlU/o7RUfqcuuYAP153g4p6Pz9anc3wATHIfu7Pmj8+kcEZdp7bUkFV4xdvR+t+P5XPP485MZGEGTOQX8Tus2dn4y0sROgPNmpDimyy2JIizomGj2jXPIxLmIjod63NfyzOEs/ExMl83HSCIs8No+P0GZX1fv73bwtpagvyF2uyyUy2yUfLF1BVha/NdqMA/7bxJpr2x1+l2jffJFBTQ8qaNXJS/D2yZWej+3z4K7q3VStFJ/lTI0UUXejsr91DliMbty3N6Dh9xsSkh4gxxfJW2evoQv4GXV7n43+vK8Qb0PmrR7NJjZcHJH+ZRJeFVQ+ncOVmB28e/OyB1Z5z52jat4/42bOxpqYalDBy2QYMAGTfVn/XrWJr69atLF26lEWLFrF+/fq73u/AgQPMmzcvbOEk6fMut16kxlfNpKQpCEWuU9xmVa08nDqTmx2lfNRw1Og4hqps8POT391A1+Gv1mSRENs/L6C4V+PzXIzPi+W1vdVcLes8YibY1ETl889jzcoibupUuX14H0xxcZhcLtm31c91WWzV1NTw1FNPsWHDBjZt2sTGjRsp/ILjB+rr6/nXf/3XHgkpSbftr9lDnCWegTGDjI7S5xS4RpDpyOa98rdoC7YZHccQNU0B/t/f3SAQEvzF6kxcTllo3YtV01OIjzHzbxtL8fmCVPz61+iBAKmPPSavPrxPiqJgy87Ge/26HEDcj3VZbB09epSpU6eSkJCA0+lk8eLF7Ny584/u93d/93f86Ec/6pGQkgRQ4S3nSttlHkqaanSUPklRFOa5F+DTfLxb/qbRcXpdfUuQn/zuBu0+jb9YlSULrfvgsJn4yqxUKhsCHPzlerzXrpG6Zg0mh8PoaBHNNmAAoZYWgrW1Xd9ZikpdFlu1tbWkfmqf3u12U1NT85n7vPrqq4wYMYKxY8eGP6Ek3bK/pnOIaX4/HWLaHcm2FCYmPcSJxo+42nrZ6Di9ps0b4u9eKqKlPcSPVmUTL7cO71telpNVaXVkXz6APnoy9kFyFflB2XNzAfBcvGhwEskoXRZbuq5/ZvifEOIzt69du8bu3bv54Q9/2DMJJQloDbbyceNxxidMxNxPh5h210NJU0iwJPD6zd8T1KP/mBB/UOcfXi2hot7P/7Mik6Q4+fh4IG0tzLy2iXprMr/0TcUf6N50eenuzImJmFwu2i9cMDqKZJAui6309HTq6uru3K6rq8Ptdt+5vXPnTurq6njsscf4/ve/T21tLWvXru2ZtFK/dajuA0IixOgEuXraFbNqYY57AXX+OnZUbjU6To/SdMG/bbzJxdJ2vrcknfREm9GRIpuuY3rvFdRgAN+8RynzmHnjjCy2HpSiKNhzc+m4elXO2+qnuiy2pk+fzrFjx2hsbMTr9bJ7925mzZp15+1/+Zd/ya5du9i8eTPr1q3D7XazYcOGHg0t9S93hpi6RhJrdhkdJyLkxgxkeNxI9tbsoqzjptFxeoQQgt9sreDoxRbWznUzONMp52g9IPXQ+6gl1zAtWE5WmpOp2TrbLulcqZUFwoOyDxyI3t6Ov6zM6CiSAbosttLS0njyySd5/PHHWb16NcuXL2fMmDE88cQTnD9/vjcySv3cycbjeEJtjE+UQ0zvxazUOThMDl4teQlNhIyOE3Zbjtaz7aMGlk1JYlyeS04leEBK8VXUQztRRk8kmJGLEIKlQwUJdsGzR0L4Q/IL/CBsOTmA7Nvqr7o1Z2vFihVs27aNXbt28cQTTwDw/PPPM3r06M/cLzs7m/3794c/pdRvCSHYX7OHTHuWHGJ6j+wmB3PTFlDpLWd39R9fQRzJTl5tZd32Sibnu5g9NgFd1gEPxtOK6b1XUFJSEZNmoIc6tw7tZvjKCJ2qNuR24gMyu1yYk5Nl31Y/JSfIS33axdYLVPuqeCh5qhxieh+GxA5lmKuA96u2UemNjuNCSqq9/OL1UnLT7Dw2MxUhD5V+MLf6tBSfF9PCVYQ+d1zP0GTkdmKY2HNzO89JDEXfSrP05WSxJfVpe6t3kWBJIFcOMb1vs1PnYVWtvFL8AiE9sp/kW9tD/OzVEhxWle8uTv/MldHS/VEP70Ytvopp/lL81i+epyW3E8PDnpuLCATw3pBnmPY3stiS+qzS9mKue64yJXm60VEimtPsZJ57EeXeMt6v2mZ0nPum6YJ/f/MmDa1Bvrc0A7vVZHSkiKeUFqIe3I4ychzBjIHcrSXy09uJb52T24n3y56TA4qCR24l9juy2JL6rD01u7CbHOS78o2OEvHyXEMZHjeSXdU7KPZE5m/Vr++v4eNrbayd5yY5Th4s/cC87Z3bh4nJiMmz0btofBuaDJMydbZc1ClpktuJ90O127Gmp9Mum+T7HVlsSX1Svb+OM02neShpCooiVzDCYXbqPGLNLl4peRG/5jc6zj05caWV9ftqmDU6nlEDY4yOE/mEwLR1A4qnFdPClYS6eYXBsqECp0Xw66Mamrwq4b7Yc3PxlZSgeb1GR5F6kSy2pD5pX80eVEVlZNwYo6NEDZvJxqL0R6jz1/FOBJ2dWNXo59833mRgup2lU5IR8kjkB6aeOox65SzqrIUE7N2fXRdjhRXDBDcaBDuvytWt+2HPzQVdp+PqVaOjSL1IFltSn+MJtXGs/gjjEiZgM8mJ4OGU7cxhYuJkjtQf4nTTx0bH6ZI/qPOPr5UgEPzJgjTZEB8OtZWou99FGZJPaFAB4h4HlI1LFxSkCDZ8olHnkatb98qalQUmkxwB0c/IYkvqcw7WfkBQBJggh5j2iGkpD5Nhz2R9ySvU++u6fgeDCCF4dnM5RVU+/sfidGIdZqMjRb5gAPM7L6HY7IjpC9C1e1+dUhRYXaAjhGDdR6F7Ltb6O9ViwZadTfulS0ZHkXqRLLakPiWg+zlU9wHD40YSI4/m6REmxcQjGcsQwAtFv+2z4yB2nmxkz6kmVk1LISfti0cSSPdG3bcZpa4KdeFKQg/QC5nkgEVDBJ9UCo6WyO3Ee2XPzSVQWUmotdXoKFIvkcWW1Kd81HAMT8jDpMTJclWrB8VZ4lmQtpibHaVsrnjH6Dh/5Fp5B89tqWDM4BgeHhUnj+IJA6X4KqYTB1EnTSeYkPLAH29GjiA7TvDCCQ2PX36D7oU9NxdArm71I7LYkvoMXejsq9nNAGcuydZUo+NEvTzXUMYlTGB/7V7ON581Os4d7T6NX2woJTHWzNfnuGVDfDj4vZi2vAbJqeijJiHCcCWhqnTO3vIEBK+ekrO37oU1PR3V4cBz5ozRUaReIostqc840/wJ9f46piTJo3l6y8Mps3Db0ni15EWaAo1Gx0EIwX+/U0ZtS4DvLk7HbJJPUeFg2v0uSmszpnnLCIVx1y/TBbNyBfsLdS5Uy+3E7lJUFfvAgbRfuIDQ5detP5DPZFKfIIRgb/UuUqypZDtzjI7Tb5hVM49kLCckQrxYtA5NGLtCseNEA4cvtPCVmamkxsvBpeGgXLuA+skx1CmzCDjjw/7xFwwWJDsEvzkWIqDJX5K6yzF4MJrHg6+01OgoUi+QxZbUJ1z3XKO0o5gpydNkr1YvS7QmMs+9kKL2G2yr3GxYjuIqL7/dVsnYwbFMynfJR0E4eNsxbdsA7gz0grE9cuWg1QRrhutUt8F75+V2YnfZB3We9yq3EvsHWWxJfcLOqu24zHEMjs0zOkq/lB83nFFxY9hd/T5nm3v/yd/r1/jn10uJdZj4yqwUhJB9WuFg2vk2SocHde7SsG4fft6wZBiXrvPeBZ2KFlkmd4cpJgZrRgaec+eMjiL1AllsSYYr8tzgattlpqfMQFXkQ9Ios93zSLOn80rxC1T7qnr1cz+3pYKKej/fWZSO1SKPZwoHpfAS6vmTqNPmELTH9vjnWzFMYFbl7K17YR80qPPoHo/H6ChSD5OvbJLh3q/aRow5lnxXgdFR+jWzamZpxkpUReW3hc/i1Xrn7La9pxvZe7pznlZmsjwxICwCfkw7NkKKG33Y6F4pflw2WDpUcLFGcKhINn13h2PwYBACj5wmH/W6VWxt3bqVpUuXsmjRItavX/9Hb9+zZw8rVqxg2bJl/OQnPyEQCIQ9qBSdbraXcqn1AtOSH0aRq1qGi7PEsSRjOXX+Ol4tfhFd9OyLZlmtj2c3VzA8x8m0kXKeVrioB3egNDdgmv0IoV5sWn8oS5AbL3j5Y402n/xmdsWakYHqcNB2+rTRUaQe1uWrW01NDU899RQbNmxg06ZNbNy4kcLCwjtv7+jo4B/+4R946aWX2L59O36/n/fee69HQ0vRY2f1NhwmB8NdI4yOIt0ywJnDzNTZnGs5w+7q93vs8/iDOr94vRSLWeGbc9NAztMKj6oy1I8+QBn3EAFXYq9+alWBR4frtAcEvz8tm+W7oqgqjiFDOkdAhPrmSQ5SeHRZbB09epSpU6eSkJCA0+lk8eLF7Ny5887bnU4n+/fvJyUlBa/XS0NDA3FxcT0aWooOFR3lnG0+w9Sk6aiq7NPpS8YlTKDANZxtlZu52HK+Rz7Hum2VFFf7+O6idGxWuaoZFrqOadsGFGcMYuyUsAwvvVcZLpiZ0zl761KN3E7siiMvD72jg47r142OIvWgLp/hamtrSU39wzRvt9tNTU3NZ+5jsVg4ePAgc+bMoampiRkzZoQ/qRR1tldtwa7aGRk/2ugo0ucoisK8tEWk2FJ5qfh5an21Yf34B881seNEA8umJDHAbQ/rx+7P1BMHUavKUOcsJmTgFZ0LhwgS7YLffhQiKGdvfSn7oEFgMtF26pTRUaQe1GWxpes6ivKHH1ohxGdu3zZ79myOHz/O3Llz+dnPfhbWkFL0udleytnmT5ieMgOTajY6jvQFLKqFZZkrEQLW3XgWn+YLy8etrPfzy3fLGZbtYPaYRNmnFS4tTagfbEUZUkAoNcvQKFYTrC7QqWiBrZfk6taXUa1W7AMH4vnkE3kVZxTrsthKT0+nrq7uzu26ujrcbved283NzRw+fPjO7RUrVnD16tUwx5SizbbKzThNMYyMk6tafVm8JYFHMpZR7avileIXHrhhPhDU+efXSzGpCt+anyYHl4aRac97KELA1NnoBmwfft7wVBjtFrx1TqO6zfg8fZkjL49gQwOBykqjo0g9pMtia/r06Rw7dozGxka8Xi+7d+9m1qxZd94uhODHP/4xlbceJDt37mTChAk9l1iKeEWeG1xsPd85V0v2avV5uTEDmZU6l3MtZ9j+gBPmf7ejkhuVXr67KB27VX7vw0Upvop66TTqlJkEzX1nfMbKfB0VwfNy9taXcgwZAkCr3EqMWl0WW2lpaTz55JM8/vjjrF69muXLlzNmzBieeOIJzp8/T2JiIj//+c/58z//c1auXElxcTE//vGPeyO7FKG2V24m1uxiRNxIo6NI3TQ2YTyj4saws3oHJxuP39fH+PB8M1s/amDJ5CRy02SfVthoGqadb0NCEvrQUfSl5cJ4OyzOE5ytEhwtkduJd2N2ubBmZND28cdGR5F6SLeaZVasWMGKFSs+83fPP//8nf9fsGABCxYsCG8yKSpdb7vKlbbLPJK+TM7ViiCKojAnbT5NwUZeK3mZVJubgTGDuv3+VY1+/vudMoZmOZgzLpE+sMsVNdSTh1DqqlCXf51AH6xnpg8QnK4SvHRSY1yWSoxVjvj4Is5hw2g+eJBgfT2WlBSj40hhJl/tpF4jhGBzxbvEWxIY5so3Oo50j0yKiaUZK3GaYvht4bM0B5q69X6BkM4vNpSiKPCt+Wk9nLKf8bSiHtyOMjifUEq60Wm+0O3ZWy0+2PCJnL11N478zufElhMnDE4i9QRZbEm95kzzaYrbi5idOleuakUop9nJiqzV+HQvv73xLAG969MiXthRxfWKzj4th032aYWTad9mlGAQpszqE03xd5MdBw/n6Oy+qnOtrg8uv/UBlsRELGlptJ08aXQUqQfIVzypV2gixJaKd0m3ZzA4Ns/oONIDSLGlsjh9KTc7bvJayctf2vi873QjW47Vd/ZppTt6MWX0U8qKUM8eR508naC1739tFw0RxNk6Z29pfbgwNJIzPx9fcTHBhgajo0hhJostqVccqT9Mrb+W2anzEH2pg1e6L4Nj83g4ZSanmk6yq3rHF96nsKKDp98rZ+RAJ3PHy3laYaXrmHa+Ba549IJxfaop/m7s5s6rE0ubYPtlubr1RZy3thJb5epW1JHFltTjfJqPHZVbGRQzhAx7ptFxpDCZmDiZAtcItlZu4kzTZw/SbWkP8fPXSohzmlk7N00WWmGmfnIUpaoMdcYCQyfF36tRbhiRKnjjjEadRz4oPs+SlITF7aZV9m1FHVlsST1uX81u2kKtzEqdg1DkE2y0UBSF+WkLSbdn8ErJC5R13ARA0wT/8nopTZ4QTyzLwGyWTzNh1eFB3b8FJWcwobRso9PcE0WBVfk6IPjdCTl764s4CwrwFRURrK83OooURvJZUOpRjYEG9lTvYkz8WBKtSUbHkcLMrFpYnrkKq2rjN4W/ojXYysu7qzhzw8PjC9NIjLUYHTHqqB9sQ/H5UKbP7dNN8XeT6ICFgwWnygUnyiIvf0+LGT4cgJZjxwxOIoWTLLakHrWp/B1AMD1lpuzVilIx5liWZ67CE2rjH/a9w9uH6lgwIZGCnBj5HQ+3qjLUU0dQJ04laIs1Os19m5EjyIgVvHA8hDcoHyWfZk5IwJadTcuRI3LlL4rIYkvqMYWe65xqOsmMlFnYTHJieDRLs6czwbySS4dHk+RuY8GERHTZAx1eQsf0/psozhj0kRMj+oXYpHbO3mrywhtn5Oytz3OOHEmguhr/zZtGR5HCRBZbUo/Qhc7bZW8Qb0lgdMJYo+NIPazdK9i7Mwu7DWInv8Up3y6jI0Ud5dxJ1PJi1JmR1RR/N7kJMDVbZ8cVnaIGWZl/mjM/H1SVliNHjI4ihYkstqQe8VHDUco6bjLfvVAOMI1yIU3w4jsBmlsF31wYx8CYQZzy7aIwcLrrd5a6x+fFtHcTZOWgZQ40Ok3YPJIncFkFvzmmydlbn2JyOHAMGULLRx8h5BJxVJCvglLYtYfa2VzxDrnOQeQ4BxodR+pBQgg27ghSeFOweq6DmNgQI83zSFKyOdD+OtWhEqMjRgX14HaUDg/qwwvQtOh58XVYYPkwQVGjYNfV6Pl3hUPMyJFora20X7hgdBQpDGSxJYXd5op36Qh1sCBtkRz1EOX2HNU4cV5nwRQbmekaAjApZiZYlmNXYtnl+R1tWqPRMSNbTQXqiYOo4x4i6HQZnSbsxqYJhiULNnyi0dAhny9uc+TloTocNB04YHQUKQxksSWFVbHnBkfqDzEt5WFcljij40g96OOLGtsPhphQYGHkUIH+qYZtq+JgonkVmtB437MOv/AamDSCCYFpx5sodif6mIcQUbjVpiiwpkBH0wUvnQgZHafPUEwmYkaNwnPmDKHWVqPjSA9IFltS2GhC4/WbrxFvSWBi4mQ56iGKXSnW2LA1yJBsE7MmmdG+4Mq4WDWJ8ZZlNOt17PW8gi7kVWf3Sjl/ErXsBqZZC6OiKf5ukp0wf7Dgo5uC0+VyO/G22DFjQNdpPnzY6CjSA5LFlhQ2B2s/oMJbzqL0R2RTfBQrq9J58Z0gackqy2fZCIm7r0akqDmMMs+jPHSVo95NvZgyCvi8mPa8B1k5hLIGGZ2mx83KFaTFCNYdD+GTs7cAsKSkYM3KovngwYge9SF1s9jaunUrS5cuZdGiRaxfv/6P3r53715WrVrFypUr+eEPf0hLS0vYg0p9W4O/nq2VmyhwjSDLPsDoOFIPqWvU+c3GADF2hUfn29GUYJfvM8A0msGmiVz0H+aC78NeSBkd1IPbUdo9mGYuRAtF/6qg+dbsrfp2eOtc9P97uyt2zBiCNTV4r10zOor0ALostmpqanjqqafYsGEDmzZtYuPGjRQWFt55u8fj4Wc/+xnr1q1jy5Yt5Ofn88wzz/RoaKlvEUKwofRVFGCue75sio9STa2C514PIITC1xY5wNR1oXVbvmkGaeoQjnrf42bwcg+mjBK3m+InTCFgj9xJ8fdqUCJMztLZXhCoRgAAIABJREFUdkmnpEluJ0LnWYmq3U7jnj1GR5EeQJfF1tGjR5k6dSoJCQk4nU4WL17Mzp0777w9GAzyf//v/yUtLQ2A/Px8qqqqei6x1OccazjClbbLLEx7BKvJZnQcqQe0eAS/Wh+gwwffXOLAbOt+oQWgKCpjzY/gUlLZ43mZ+lB5DyWNAp9qihejJ0dlU/yXWZoncFgEzx2Rs7cAVKuVmNGjaTt9mmBTk9FxpPvUZbFVW1tLamrqndtut5uampo7txMTE1m4cCEAPp+PdevWsWDBgh6IKvVFzYFm3i1/k8ExQ8iLHWZ0HKkHeNoFz20I0OoRrF3ixO64t0LrNrNiZZJlFRbs7PD8llatIcxJo8Onm+KDUdwUfzcxVlhdoFPUKNhySa5uAbgmTABdp2nfPqOjSPepy2JL13UU5Q8/8EKIz9y+ra2tje9///sUFBSwZs2a8KaU+iQhBG/cfI2QHmJh2mK5fRiF2jsEz70RoKFZsPYRJzEx91do3WZXYplsWU1IhNjh+S1e3ROmpFHiM03xA41OY5jRbhjlFrx5RqOiRT6vmBMScOTl0XzgAHogYHQc6T50WWylp6dTV1d353ZdXR1ut/sz96mtrWXt2rXk5+fzT//0T+FPKfVJHzUc5XzLWeanLcJudhodRwqztnbBM+sD1NQLvrHYiSsuGJZhHrFqMhMtK2nTm9jp+R1BIV88blM/2PqHSfGh/ruqc3v2lsUk+NWRkNxOBFwTJ6J5PLSeOGF0FOk+dFlsTZ8+nWPHjtHY2IjX62X37t3MmjXrzts1TeMHP/gBS5Ys4ac//ekXrnpJ0afeX8dbZa8zJHYoBa4RRseRwqz1Vo9WfZNg7VInCQnhKbRuS1KzGGdeQq1Wyj7Pq3IGF6CUFaGe/BB14rSonBR/r1w2WJkvuF4v2HGl/xaet9lyc7GkptKwfbs8LzECdVlspaWl8eSTT/L444+zevVqli9fzpgxY3jiiSc4f/48+/fv59KlS+zatYtVq1axatUqfvrTn/ZGdskgutB5pfhFFBQWpT0itw+jTHOr4JnXAjS2CL61xEl8mFa0Pi/dlMdI8zxKQxc53PFO/54jFApi2rYBJT4BfVT/a4q/m/HpghGpnUf5lDf376+JoijETZlCoKoKz7lzRseR7pG5O3dasWIFK1as+MzfPf/88wCMHj2aK1euhD+Z1GftrdlFUXsha7K+Kq8+jDI1DTq/fj2A1wffXuokJrZnCq3bck1j8QsPlwPHiFETmOhY1IOfre9Sj+xFqatGXb2WgCy07lAUeGy4zn8dU3n6cIh/XmrGrPbf3RNnQQHNH35I/ZYtxI4dK3eSIogc8y3dk9L2YrZVbmZ0/FhynQONjiOFUVmVztO/DxAMKfzJCifOHi60bhtqmk62OoKPfe9z0dcPjyWpq0Y9vAtlxDhCie6u79/PuGydw06LGgXvnu/f22eKyUTc5Mn4iorkkNMII4stqdu8WgcvFK0jzhzH7NS5cvswilwr0XhmfQCrWeHbyxzY7A921eG9UBSFUeYFpKlDOOx9h6v+ftQALPTO7UOrFSbPQNf6dzFxN6PTYEKGztvnNArr+/fXKGbMGFSnk7otW4yOIt0DWWxJ3dI5Jf73NAUaWZm1BpParR1oKQKcOK/xmzeCJMWprF3qwGztvULrNlUxMc68lBQ1h4Mdb1AUONPrGYygnjqCWlaEafZigkI+HX+ZVfkCl1Xw9OH+fXaiarEQ99BDdFy8SIdc3YoY8qdb6pbD9Yc43fQx89MWkWhNNjqOFAZCCHZ+GGL91iCDs018dZHtno7gCTeTYmaCeSWJSib72l+jJHDesCy9oqkede8mlIFDCWbkGp2mz3NY4Gsjdapa4aWT/fvq1dgJE1BjYqh9++3+fWFJBJHFltSlso6bvFO2kWGx+YyMG43olU4eqSeFQoIN24K8/2GISSMsLJtpQVdCRsfCrFiYaFlFnOJmd/vLFAei9KoroWPa8hoKCsxcKLcPu2loMswdpLOvUOdIcf8tuFSLhfhp0/Beu0bHpUtGx5G6QRZb0pdqD7Xz/I1f4zTHsCBdjnmIBq0ewa82BDhxXmfBFBsPT1AI0XdeuCyKjcmWNSQoaexpf4WiwFmjI4WdevwAamkhprlLCMot+XuycLAgN17wm480atr67/NR7NixmOLiqH3rLbm6FQFksSXdlS50Xi7+Hc3BJtZkPYZFtRgdSXpA5dU6//myn/JqwTcWOxgxVKD1wSdqi2JjkmUNCUo6e9tf5br/lNGRwqeuGnXfFpShIwhm5iIXiu+NSYVvjtZBCJ46FCLUT0dlKGYz8Q8/jK+khNbjx42OI3VBFlvSXb1ftY1LrRd4JH0Z8dZEo+NID+jkBY1f/j4AQuG7K52kpoTQ+2ChddvtFa4kNYv9Ha9xznfQ6EgPTtMwbX4VxWqD6XPl9uF9SnLAYyN0ChsEvz/Vd1Zle1vM6NFY0tKo3bhRnpnYx8liS/pC55rPsKNqKxMSJzE0Nt/oONIDCIUEb+4M8tqWIAPSTHx7mR2bo3dmaD0os2Jlknk16epQjnk3cdy7PaK3TNTDu1Erb6IuWE5QmIyOE9HGpMHMHJ3tl3UOFfXPgktRFBLnzSPU1ETDzp1Gx5G+hCy2pD9S0VHOS8W/Y4Ajhxkps2SfVgRrbBH88vcBjpzWmD3Ryso5FjAZ3wh/L0yKmfHmpeSYxnLGt5f9HesJReDh1UpFKeqH76OMHE8oJcPoOFFh6VDB4ETBb45plDT2z1VCe04OjmHDaNi2jWBjo9FxpLuQxZb0GW3BVn594xkcJjsrMtegKPIhEqku39D49xf91DYK1i5xMG4EBCP0wGdFURlpmku+aQaFgVNsafsV7XqL0bG6z9eB6Z0XUVwJiMkz5fZhmJhU+NZoHYdZ8G8HQnj8/fMXw8S5c0HXqf79742OIt2FfCWV7gjqQdbd+DWeYBuPZn8Ni0k2xEciXRe8fyjIbzcGSYhV+dNVMSQnhdAivJFYURSGmCcz0bySRq2ad1v/i5pQidGxuiYEpq2vo7Q2YVq8ipCss8LKZYNvj9FpaIf/PBgiqEX24/x+mBMSiH/4YTyffELb6dNGx5G+gCy2JKDzysPXSl6mqL2QVVmPEWeJNzqSdB+a2wS/fiPIzsMaE0dY+NpiG6olEBH9Wd2VZhrCNMs3AJXNbc/wiW8vQvTdCkY9dRj18ieosxYRcMYZHScq5SbAV0bonK8WrPtIi+i+vvvlmjwZS2oq1b//PZrXa3Qc6XNksSUBsKXiXT5uOsHCtEfIdg4wOo50H85e0fjX3/kpqdBZM8/eOT9LRFZ/VnfFqSk8bPkmGepQTni3s93zm765rVhdjrrrHZS8ArTBwxERvrrYl03MFCwYrPPBDb1fHlitmEwkLVpEqLmZ2jfeMDqO9Dmy2JI4ULufPTW7mJI8TU6Ij0D+gOD17UFefDdIcryJP1vtJDtD65Pzs8LJotgZa17CGPMiqkPFvNnyL1zyH+07q1wBP+Z3XkRxxsCMhWihyOyXiyQLBwsmZOi8fkbjw354haItOxvX5Mk0HzyI52z0DQOOZLLY6ufONJ3m7bI3GBE3imnJM+SVhxGmtFLn314IcPysxrzJNr6y0IrJGhljHcJBURSyTSOZYfk28WoaH3a8xea2Z2gIVRobTAhMW9ejNNZhWrSKoK4Ym6efUBT4ygjBkETBr45onCzrI4V3L0qYORNLaiqVL75IyOMxOo50iyy2+rHLrZd4qfh5cpy5LExbLFe0IoimC3YfCfHfrwbQNPjuKiej8gVBPTq3DbsSoyYyybyGceZHaNJqeLvtP9jX/hotWp0hedSje1EvnkadtZCASw4E7k1mFb4zTicrTvCfB0OcqehfBZdiNpO8bBlaWxtVL7zQL/vX+qJuFVtbt25l6dKlLFq0iPXr19/1fn/zN3/Du+++G7ZwUs8p8txg3Y1nSbW5WZm5uvNXQikiVNbq/PcrAbYfDDFmqIXHlzuIiQ326WnwvUFRFDJNw5ll/S55pocoDpxjY+u/cKD9DRpCFb2X4/rFzuN4RowjNHiE7NMygN0MfzpeJy1G8K8HQlyo7l8FlzUtjYQ5c/B88gmNu3cbHUeiG8VWTU0NTz31FBs2bGDTpk1s3LiRwsLCP7rPD37wA3bt2tVjQaXwKe8o47nCp4kzx7Mm+6uo8iDciKBpgl2HQ/zHiwEam+FrixzMnqygKUGjo/UpVsXOMPN0Zlu/y0DTOAoDp3m77T/Y3Po01/2nCAhfz33yhhpM776Mkp6JmDpHztMykNMCfzZBJ9kh+MW+EGcq+9f3wjVpEo5hw6jduBHv516zpd7XZbF19OhRpk6dSkJCAk6nk8WLF7Pzc8cCbN26lfnz57NkyZIeCyqFR4W3nGeu/xc21cpXB3xdHi4dIcprdP7z5QA7DoUYPdTCn6524E4NRX0T/IOwK7EMN89mrvV7jDDPpk1vZn/Ha7za/P+x0/M7rviP06LVhW+bxe/FvPF5FJOKunAVITlQy3CxVnhigk6yU/CL/SEOF/efpnlFUUhesgRzXBzlv/oVweZmoyP1a10uadTW1pKamnrnttvt5ty5c5+5z/e+9z0ATp06FeZ4UjhVeMt5+tp/YlLMfC1nLVaT3ehIUhdCmmD34RB7jmnEOBS+ucRBWopOSJerWd1lVewMNE0gVx1Ps6iiVr9BVeg6pcGLADgUF2nmgSSa0klQU4k3uXGqcTiUWMxKN38Z0XVM770CDbXw6Fo8io6u+NDQ0NHRlM4/VRRUYUJFxSqsWLCgILfwe5LLBn8+UeeVsyq//FCjzQ9LCvrHuZSq3U7KmjXUrF9P+dNPk/uTn6BarUbH6pe6LLZ0XUf5VD+PEOIzt6XI8OlC6+s5a3GYnEZHkrpwvUTjrV0hahoEE0dYeHicBV0Jygnk90lRFBKVTBLVTIaJGbSLJppFFS2iioZQJaXBiwg++8W1YMOiWDEpFky3ni71zvIJXXT+KYTG9ANeRl4LcmC2yoXMjd0PJcCKFafuJEbEEKPH4NLjSNATSNASSNQTMXf9NC11wWGBPxuvs+GCygsnNKpaBY9PMmFWo/+1zOp2k7x0KfWbNlH10ktkfv/78jXcAF3+FKenp/Pxxx/fuV1XV4fb7e7RUFJ4lbQX89z1X2JWLbLQigAtHsHmfUFOXdRJjlf41lIHKckamlzNChtFUYhVkogliWxGAiCEjpc2OkQTQeElgI8AXjSCt4qrzis9FVRURUXFhILK4BOVDDvfSvnELNSh6YxtV1CEioqKqiud9xcKKioCga50lmshVSOoBgkqQXyqF6/qpdnUTLvlGrcXuxShkKQnkaqlkhZKI1PLIk6Pk6th98Figm+P1tlxXWHHFShpEvyvWWYSHNH/tXTm5xM/axYthw5hSU7G/ZWvGB2p3+my2Jo+fTrPPPMMjY2NOBwOdu/ezc9//vPeyCaFwdXWy/z2xrPEml18Nfvr2EwOoyNJd6HpgsOnNHYcChEKwYKHbIwcqqIRQvZZ9zxFUXESj1Pp/lFVsRcv4D5yjMDwEdjyJ5DX+uCjN3R02s3teMxttJhbabY0UWwu5or1CgAxegzZoWxyg7lkhwZgRW4LdZdJhRX5gux4nbcvqfx4W5D/NcvM8LTon4IUN3UqWmsrDdu2YU5IIGnBAqMj9StdFltpaWk8+eSTPP744wSDQb7yla8wZswYnnjiCf7yL/+S0aNH90ZO6T6cbf6EF4vWkWJL5bHsr2GWzfB9VkmFzps7g1TUCAoGmpn3kBWzNYQWpcftRANHSTGpu3YSzM2lbcIEgsHwfK9UVFwhF66QiwwyARAI2k0e6mz11FvrKbYUc9V6FVWoZIWyGBocxqDgICzIn/HuGJ8uSIvReO2cyv/ZFWLFCJVvjDdhNUXvKpeiKCQuXIjW0UHN+vWodjsJM2YYHavfUISBE8/Ky8uZP38++/btIzs726gYUelA7X7eLnuDAc4cVmauwSTHO/RJjS2CbQc6twzjXQqPTLeTnhr9R+1EOltVFRlvvoGemEjrwkX4wlRodZeOTqO1kRpbNeW2ctpN7ZiFmcHBwQwNDiMrlIUqZ1Z3yReC9wtVjpUpZMXD/5xuZlhqdH/dRChE3bvv4ispIfPP/5z4qVONjhRR7rduka/AUUYXOu+Vv8X+2r2MiBvFgrTFshmyD/L6BHuPhThwQkNRYO4kG2Pyb20ZyjqrT7NWV5H+9puImBg88+b3eqEFnatfKYEUUgIpjGgbSaOlgTJHGcW2Yq5Zr+HUYxgaHMqIwAji9e5vi/Y3djOsKdAZmQpvXzLxt++HmDNEZe14E0nO6HzeVMxmUlavpu6dd6hctw6EIH7aNKNjRT1ZbEURn+bj1ZIXONt8hmnJM3goeRrII3j6FE0THD2j8f6hEO1emDjcwtQxFlRLEK2vHKAs3ZW1upqMt94Eu4O2R5bSoRv/PVNQSA6mkBxMYTRjqLFXU2Yv45z1LGdtZxgQzGFUYBQ5oRzZWH8Xw5LhyakaB0pVPizWOVaqs3qkiaXDVWKs0fc1U61WUh99lLr33qNy3Tr0QIDE2bONjhXVZLEVJWp9Nfz2xrPU+KpZkr6cgrgR6Bj/QiB1EkJw/prOtgOdoxzyBpiYO9mGMyaEpgeRu4Z9X2ehtRHsdjxLlvSJQuvzTJjI9GWR6cvCp/oocZRQ7Czi/ZgdxGlxjAyMoiBQgA2b0VH7HIcFluTpTMns3FrceFZj6yWNRwpUlhWYiI+yqxZVm43Uxx6jfvNmql96Ca21leTly+VOSA+RxVYUuNBynpeLn0dFZW3O46Ta3bLQ6iOEEFy4rrPzwxDlNQJ3ksraJXZSkzU0EZRXGUYIa001GW+/CTY77UuW0d4HC63Ps+t2CtoLGNY+jCp7FUXOGxxzHOWk/QTDAsMYExhDgi4Pyf68JCd8a4zOnDY4WKry3nmdbZd0Hh6osmCYyrAUJWoKEtViIXX1ahp27qTunXcIVFeT/t3volrkhRbhJoutCKaJEFsrNrGnZheZjmxWZqzGZrYj5Nah4YQQXCzsLLLKqgUpCQqPzbczIEMQErIvK5I4SkpI27IJYbfTvmQJnggotD5NRSXLl0WWL4sWcwtFzhtcsV/hku0SOcFcxvrHkKllyS3Gz8lywdpROgsHw5GbKkdLdT64oTMgQWHOYJWpuSpprsj/milmM8nLlmFJSqLlww8J1NWR/Rd/gdnlMjpaVJFXI0aoen8dLxY9T2lHMQ8lTWVq8sNR89tWJBNCcOmGzvsfhiirEiQnKMyZaCMnUxCMsBdpCWIvnCd19y605GQ88xfQoUdHlexTfJQ6Syh03sCv+kjWkhnjH0teMA8T/eMom3vlC8H5WoWPK1WKmzr/bnCywpQclbEZCoOSFEwRPpG+/coVGrdvx5yUxIC//mtsmZlGR+pz7rdukcVWhBFCcKzhMO+UvYWiwLKMVWQ7B8jVLIOFNMHpizr7j4eoqhMkxSvMnmAjN1sQkkVW5BGChGNHSTp6hGBuLp4ZM/EacNVhT9PQKHeUU+i8Tou5BafuZGRgFCMCI3AIOQD5bpq8cKFO4XyNSsmt851jrDAqXWFMhsqYDJV0FxH5C7C/ooK6995DhEKkP/448dOnR+S/o6fI0Q/9QIO/ng2lr3Kl7TJDYvJYlP4IVpPcNjRSh1dw5BONQx+HaPVARorKmnk2cjMFIaHJcwwjUShEyt49xF04T2DESNrGj8cfhYUWdDbU53pzyfHmUGer44azkJP2E5y2nSI/kM/owBgSZV/XH0l0wMwcwcwcDU8AbjQqFDWrXK0THL+pARqpMVDgVhmWqjAsVSE3UYmIsxhtWVmkP/44DTt2UPX887SfP0/6d76DySGL7wchi60IENJDHKjbz47KLQAsy1jJ0Nh8hCKLLKPUN+kcPKnx0VmNQBCG5ZpZOcdCSqJOSNcIyW9NRDK1tpK2ZTP26ir8U6bQMmQooSgttD5NQcHtd+P2u2kztXIjpogr9qu3+rpyGOMfS5bs6/pCsVYYmy4Ym64hBDR64UaTwo0mlXNVOh8Wd97PaoIhycqt4quz0T6xj87yMsfF4f7a12g9fpyWw4fx3rhB1g9+gGPIEKOjRSxZbPVxl1sv8VbZ69T4qilwDWeOez42uZpliFBIcO6azrEzGtdKdEwqjC+wML7ATEyMTkgPyZWsCOa8UUjqzvdRNI2OR5bQmpiEHor+QuvzXFoc41rHMbxtOCXOEm44C9kWu5VkLZnR/jEMDQ6VfV13oSiQ7IRkp+ChrM7iq8UPZa0K5a0qpc2CbZcF2sXOJ4qUGBiWqpJ/a/VrYKKCpY8cGaSoKvHTpmHPyaFh2zZK/umfSFq4kJTVq+Uq132QxVYfVdZxk60Vm7jYep5kawpfH/AtMh1ZcqSDAWrqdY6e0Th5XqPdC0lxCgun2hiaq2K2aOhCFlmRTAkESD54gLizZwi53bTPnoNHUUHTjI5mKJuwkd+eT157HhWOcgqdhRxwfsBx/SOGBfMZHiiQoyO6oCiQYIcEu2C0u/PxFNKhyqNQ1qJQ1qpwpUbnaEnn/a2mzqb7/FSF/NTOLcgEg+d72bKySP/Od2j+8EMad++m9fhx0tauxTV5suzlugey2OpjKr0V7KjayidNp3CanCxMe4QRcSNBUWSh1Yva2gVnr2qcuqBRVC5QVRidZ2H0UDOpSfqtKwt1ouTitH7LUVxMyp7dWFpb8E+cRFtBAYF+sG14L0yYyPHmMsCbQ721jiJn8Z3p9OmhdAoCwxkSHCIPwe4mswoD4gQD4v7w5NHi51bxpVJya/Vr863Vr7TYztWvYamdRVhuYu9f9aja7SQtXEjMqFE07dlDxXPPETNqFGnf/Ca2rKxezRKp5NWIfYAQgmttV9hbs5tLrRewqTamJc9gdPwYVFUu1/cWT4fg3FWNTy7rXC/VEQLcSSoTCqwMyVExmUPoctR7VDC3tJB06ACxV6+iJSXRMWMm7c4YdHnlaLf4VT9ljpuU2EtoNbdiERbygnnkBfLI0DLlIdgPKKRBpQdutijcbO0cNdHi63yb3dzZ+5XvvrX6laLgsvde8SV0Hc+ZMzQfOoQIBIibMoWUlSv7zZgIeTViBOoItXOi8SOO1H9IpbeCWLOL+e6FFMSNwKzK3xJ7Q2OL4EqRxtkrOtdKOleqUhJU5kyyMSRbJSZGQxOdVxfJVazIp3Z0kHDyBHGnT6EoCr6pU/EMyetczZKFVrfZdBt57UMZ0p5Hk7WJUkcJ123XuWy9jF23MzA0iMHBwWSFsmR/130wmyAnHnLiBdDZ+9V8a/Xr5q3er00XBPqt81Qz47iz7VjgVsiKV1B7aItPUVVcEybgLCjAc/o0rSdP0nr8OHFTp5KyYkW/KbrulSy2ellQD3Kp9QKnGk9yrvkMQREk2zGAFZmrGRQzRO6B9zB/QHC9VOdqsc6VIp3axs4KKjleYdZEG0MGqLhi9VuzsXQ56T1KmFtaiDt9irizZ1G0EMHhw2kfPQYfCkJuG943BYWkQBJJgSRGM4Zaey1VtkoKbde5Yr2MVVgZGBxITiiXrFCWnN11nxQFEu2QaBeMSevs/QpqUNGm3Fr9UjhZpvPBjc77Oy3cueoxP1VhaIqCM8wHapucTuJnzCB2wgTaTp2i7eOPaT12DGdBAQlz5uCaOFEe+/MpstjqBa3BVi63XuBiywUutpzHp/uIMcUwPnESI+JGkmhNkv1YPcTTLiip1Cmt1CkqExSX62g6WMwwZICZySNNZKSqxDg1NNFZYMlm9yihaThLinFdOI+zsBCAYEEB3hGj8Fost7YMZTUdLmbMZPoyyfRlMp4J1NpqqbJXUmIt4Zr1GgBJWhJZoWyyQllkhDLkgdgPwGKCgQmCgQm3HsMCGrydVz7evNX7dbZSQwAKMCBBYUiywsCkzmn3g5IUHJYHL8BMTicJM2fimjCB9kuX8Jw5Q+VvfoPJ5SL+4YeJmzwZ+6BBKGr/3lruVs/W1q1b+fWvf00oFOI73/kO3/rWtz7z9suXL/PTn/6U9vZ2Jk2axN///d9jNnddx0Vjz5YQgpZgMzc8hdzwFFLouUaFtxwAl9lFvms4ebFDSXNkGJw0+rR7BTX1gptVncVVaaWgobnz4a0qkJGqMiTbzIB0lZQkEOiyByvKKH4/ztISHEVFOItuYO7oQHc4CI4ahXfgIHwms+zL6mU6Oi2WFuqtddRZ66iz1KEpGopQSNaTSdFSSNFSSdFSSNaSZaN9GPlCUN7aedXjzRaFshZo9f/h7ekuGJSkMjCxc+sxK14h3cUDjZ8QQuC7eZP2c+fouHIFdB1TfDyuceOIHT+emIICVLs9DP86Y/TYcT01NTV885vf5N1338VqtfKNb3yD//qv/yIvL+/OfZYvX84//uM/Mm7cOP72b/+WUaNGsXbt2h4L3Vd0hDqo8VdT66umyltFubeM8o6btIXaALCqVgY4c8h1DmKAM4dES5IcRPqA/AFBc5ugsaWzsKppENTU69Q0CDwdf7hfgkshJ91MZqpKaqJKYrxAUXU0WVxFDyEweTzYaqqx1tbiuHkTe2UFiq6j22yEcgcSGDwIX2IygX4+xqEv0dFptDZSb62jydJEo7kRv9pZAShCIUFPIElLJl6PI06PJ06PI06PI0bEyKGqD0gI8AQ6R09UtatUtEJ5C9R/6rlTVcAdS2fxFafgjlVIiVVIiYHUGAWnpfvHEGk+H76SEnxFRXRcu4bw+0FRsA0YgCMvD2deHvZBg7CmpqJ0Y4GmL+ixBvmjR48ydepUEhISAFi8eDE7d+7kRz/6EQAVFRX4fD7GjRsHwKOPPsrTTz/drWKrr9GFjl/30RHy0qG149W8eLUOPME2moJNNAeaaA420RRoojnQjE/33nlfFZU0ezpDXfm4bWmk2twk2ZJRUO4MIJVypaQ/AAAJTUlEQVSDSD9LCIGmgz/QeexNuxc6fIIOb+cqVbtX0OqB5jZBc6ugpU3Q4fvsx3DawZ1kYsQglaR4lTiXQmIcOOwCTdcR3BrRAHLHKNLoOqrfj+rzYmrvwNLagrm1FXNrC+bmFmx1dZi8na8SAtDcbgITJxLIyMQf6yKoaQgh+v28rL5GRSUlkEJKIAXofF70qz5aLC20WFpoNjdTa66hyHLjM7+cmoQJl+7CKZw4dScO4cAhnDj1zj9twoZVWLAIK1ZhxYJFXhX5OYoCLhu4bIJhyX/4ufBr0NChUN8B9V6V2naobhWcqxQEP7cQ7LBASoxCshPi7AouW+efcTaIv3U7xgoOi4LdYsMxLJ+YggKSFi/GX15OoLISf2UlLUeO0Lx/f+cHNZmwut1Y09OxZWRgTkzEnJBw5z9TbCyqzRbRW5FdFlu1tbWkpqbeue12uzl37txd356amkpNTU23Prl260mwurq624HvVUiE2FqxidZgCyERIqRraAQJCQ1ND3X+KUJoukZABO5aECkoxJhiibW4cJljGWgahNMcS5zZ9f+3d3chUawNHMD/s59q26mj6bsgvnYVgorQ1gnT9GRqmZq0Cn1AWKYVRUk3QhAYfXflRRdREL6cMLKMiLroCwv86BvCC7HAIpXKVsV0X3V3duZ5LzY96HvIOrbnGev/k4F9Zljm73Mx/HdmZwcO21w4LHODxUoVgAqo3gB68XXzMJsIIfDwhY7BIQFdBD8p6XrwgKnrf47Ht6kBQA0IBALB14GA+LwuuEx3omlOuIJfIhTMnWNCVLQCR7iCsDAFEWHA3AjAZtcn9gUA0IHhQWA45DNBM2HyevHro4cw+X1QNA3QNCiaDkULQNE0mPx+mHy+Se8RAFQA/vBw6A4H9Oho6L/Oh+r4BWpEBDRFga5rwMhIcKFZxQIrorAAUfizhI2ZfRgx/xdjyhhGLaMYMY9gUPmED6Ze+Ew+BJQv39xgFmZYhAVmmKDABLP4/EqYYRr/+7xu/KxZhAiHy7f0p7uL0gLAaQleWsTc4DoBYMQfvPTo9QNDfhOG/cGfofjwEXitBtf7prnHxGoC7BbAbjXDosTBYv43rP/6DVGBT4jy9WG++gm/DA7B8eEl5jx6DEX89aV+3WKDJdwOi90OxW6HyW4HzGYoJlNwsVgw//ffERYf/z2nZpLxvqJ944e4acuWruuTThkKISaNp9v+JR6PBwD+7ztgREREsvwHF2VHoL/rjz/+kd14PB7Ef0Opm7ZsOZ1OPHv2bNIOYmJiJm0fL00A0NfXN2n7lyQlJaGurg7R0dEwm3+uTxFEREQ0u2iaBo/Hg6SkpG9637Rla/ny5Th9+jQGBgYQHh6OO3fu4MiRIxPbY2NjYbfb8fz5c7hcLly/fh0ZGRlftfOwsDAsWbLkmwITERERyfItZ7TGffVPP5w9exaqqqKkpAQVFRWoqKjAvn37kJycjI6ODhw8eBBerxeJiYk4ceIEbDbb3/oniIiIiH4kUp+NSERERPSjm733URIRERHNAixbRERERCHEskVEREQUQixbRERERCHEskVEREQUQixbkjQ2NsLtdiMvLw9Hjx6VHcfQrly5gqKioonF5XLh8OHDsmMZ1vXr15Gfn4/8/HycOnVKdhzDO3fuHFavXo3CwkKcOXNGdhzD8nq9KCgoQE9PD4Dgc3MLCwuRm5uLmpoayemMZepcAYCqqigtLcXjx48lJjOmqfNVX1+PgoICFBYW4sCBA/D7/ZITfgeC/nFdXV0iPT1dvH//Xvj9frFp0ybx4MED2bFmhVevXomcnBzR398vO4ohjYyMiKVLl4r+/n6hqqooKSkRLS0tsmMZVktLiygoKBDDw8MiEAiInTt3itu3b8uOZTgvXrwQBQUFIjExUXR3d4vR0VGRmZkpurq6hKqqoqysjMewz6bOlRBCdHZ2ig0bNojk5GTx6NEjyQmNZep8vX79WuTk5Ijh4WGh67qoqqoStbW1smPOGM9sSXD37l2sXbsWTqcTVqsVNTU1SElJkR1rVjh06BD279+PyMhI2VEMSdM06LqO0dFRBAIBBAIB2O122bEMq729Henp6XA4HDCbzVixYgXu3bsnO5bhXL58GdXV1ROPYmtra0N8fDzi4uJgsVhQWFiIW7duSU5pDFPnCgAaGhpQXl7O4/xfmDpfNpsN1dXVcDgcUBQFixYtwrt37ySnnDmWLQnevn0LTdOwa9cuFBUV4eLFi5g3b57sWIbX2tqKsbEx5OXlyY5iWA6HA5WVlcjLy0NmZiZiY2OxePFi2bEMKzExEc3NzRgcHITP50NjYyP6+vpkxzKcY8eOTXq02sePHxEdHT0xjomJQW9vr4xohjN1rgCgqqoK2dnZkhIZ29T5io2NRVpaGgBgYGAAdXV1WLVqlax43w3LlgSapuHhw4c4fvw46uvr0dbWhmvXrsmOZXiXLl3Ctm3bZMcwtI6ODly9ehX3799HU1MTTCYTzp8/LzuWYaWmpsLtdmPLli0oLy+Hy+WC1WqVHcvwdF2HoigTYyHEpDHRTPX29qK0tBTFxcVYtmyZ7DgzxrIlwYIFC5CamorIyEiEhYUhOzsbbW1tsmMZmt/vx9OnT5GVlSU7iqE1NzcjNTUVUVFRsNlscLvdePLkiexYhuX1epGbm4sbN27gwoULsNlsiIuLkx3L8JxOJzwez8TY4/FMumxGNBOdnZ3YuHEj1q9fjz179siO812wbEmwcuVKNDc3Y2hoCJqmoampCYmJibJjGdrLly+xcOFCREREyI5iaAkJCWhtbcXIyAiEEGhsbERycrLsWIbV09OD3bt3IxAIYHh4GA0NDbxM/RVSUlLw5s2bia9E3Lx5ExkZGbJj0Q/A6/Vi+/btqKysRFlZmew4341FdoCfUUpKCsrLy7F582aoqoq0tDQUFxfLjmVo3d3dcDqdsmMYXnp6Otrb2+F2u2G1WpGcnIwdO3bIjmVYCQkJyM3Nxbp166BpGrZu3QqXyyU7luHZ7XacPHkSe/fuhc/nQ2ZmJtasWSM7Fv0AGhoa0NfXh9raWtTW1gIAsrKyUFlZKTnZzChCCCE7BBEREdGPipcRiYiIiEKIZYuIiIgohFi2iIiIiEKIZYuIiIgohFi2iIiIiEKIZYuIiIgohFi2iIiIiEKIZYuIiIgohP4HsY3HczK6pZ4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "\n",
    "# plot for countries in these regions, set axes to use, labels to use\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==0]['Log_GDP_per_cap'], label=\"Cluster region 0\", color=\"g\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==1]['Log_GDP_per_cap'], label=\"Cluster region 1\", color=\"b\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==2]['Log_GDP_per_cap'], label=\"cluster region 2\", color=\"r\", shade=True)\n",
    "#sns.distplot(clusters.loc[clusters.loc[:,'cluster_pred']==3]['Life Ladder'], ax=axes[3], label=\"cluster region 3\", color=\"y\")\n",
    "# add title\n",
    "plt.suptitle(\"Actual Log_GDP_per_cap variable for the 3 clusters for 2017\");\n",
    "plt.legend();\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When the distribution of Log GDP per capita is broken down by cluster groups of regions, the distribution of each cluster looks more normal shaped although the centres of the distribution and the spread vary widely as with the other variables. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean and standard deviation for Log GDP per capita by clustered group:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_pred</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.415971</td>\n",
       "      <td>7.732756</td>\n",
       "      <td>0.669998</td>\n",
       "      <td>54.945161</td>\n",
       "      <td>1.290323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>5.322920</td>\n",
       "      <td>9.294176</td>\n",
       "      <td>0.820008</td>\n",
       "      <td>64.951786</td>\n",
       "      <td>3.946429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6.614540</td>\n",
       "      <td>10.401640</td>\n",
       "      <td>0.900387</td>\n",
       "      <td>71.515385</td>\n",
       "      <td>4.102564</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Year  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "cluster_pred                                                               \n",
       "0             2018.0           4.415971         7.732756        0.669998   \n",
       "1             2018.0           5.322920         9.294176        0.820008   \n",
       "2             2018.0           6.614540        10.401640        0.900387   \n",
       "\n",
       "              Life_Expectancy  RegionCode  \n",
       "cluster_pred                               \n",
       "0                   54.945161    1.290323  \n",
       "1                   64.951786    3.946429  \n",
       "2                   71.515385    4.102564  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c18.groupby('cluster_pred').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate data for the Log GDP per capita variable for each of the cluster groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "GDPc0= np.random.normal(c18_0['Log_GDP_per_cap'].mean(),c18_0['Log_GDP_per_cap'].std(),31)\n",
    "GDPc1= np.random.normal(c18_1['Log_GDP_per_cap'].mean(),c18_1['Log_GDP_per_cap'].std(),39)\n",
    "GDPc2= np.random.normal(c18_2['Log_GDP_per_cap'].mean(),c18_2['Log_GDP_per_cap'].std(),56)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot the distributions of the simulated Log GDP per capita variable for the 3 groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "# life satisfaction distribution for cluster region 0\n",
    "sns.kdeplot(GDPc0,color=\"y\", shade=True)\n",
    "# life satisfaction distribution for cluster region 1\n",
    "sns.kdeplot(GDPc1, color=\"skyblue\", shade=True)\n",
    "# life satisfaction distribution for cluster region 2\n",
    "sns.kdeplot(GDPc2, color=\"pink\", shade=True)\n",
    "# add title\n",
    "plt.suptitle(\"Distribution of simulated Log GDP per capita for 3 region clusters\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Healthy Life Expectancy\n",
    "\n",
    "According to the World Happiness Report, Healthy life expectancies at birth are based on the data extracted from the World Health Organization’s (WHO) Global Health Observatory data repository. Some interpolation  and exterpolation was used to get the data for the years covered in the 2018 report. As some countries were not covered in the WHO data, other sources were used by the researchers.\n",
    "\n",
    "The values are non-negative real numbers between 48 and 77 years but this varies from year to year as the statistics showed. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    132.000000\n",
       "mean      64.670832\n",
       "std        6.728247\n",
       "min       48.200001\n",
       "25%       59.074999\n",
       "50%       66.350002\n",
       "75%       69.075001\n",
       "max       76.800003\n",
       "Name: Life_Expectancy, dtype: float64"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df18['Life_Expectancy'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Year', 'Life_Satisfaction', 'Log_GDP_per_cap', 'Social_Support',\n",
       "       'Life_Expectancy', 'RegionCode', 'cluster_pred'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c18.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,axes=plt.subplots(1,2, figsize=(12,3))\n",
    "\n",
    "# distribution of Life_Expectancy from the dataframe with the clusters. some missing values\n",
    "sns.distplot(c18['Life_Expectancy'].dropna(), label=\"Life_Expectancy - 2018\", ax=axes[0])\n",
    "axes[0].set_title(\"Distribution of Life_Expectancy for 2018 only\")\n",
    "#axes[0].legend()\n",
    "# kdeplot of the Life_Expectancy from 2012 to 2018)\n",
    "sns.distplot(clusters['Life_Expectancy'].dropna(), label=\"Life_Expectancy - all years\", ax=axes[1])\n",
    "axes[1].set_title(\"Distribution of Life_Expectancy for 2012 to 2018\");\n",
    "#axes[1].legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the distribution of Life_Expectancy variable for each of the years 2014 to 2018\n",
    "sns.kdeplot(c14['Life_Expectancy'], label=\"2014\")\n",
    "sns.kdeplot(c15['Life_Expectancy'], label=\"2015\")\n",
    "sns.kdeplot(c16['Life_Expectancy'], label=\"2016\")\n",
    "sns.kdeplot(c17['Life_Expectancy'], label=\"2017\")\n",
    "sns.kdeplot(c18['Life_Expectancy'], label=\"2018\")\n",
    "plt.title(\"Distribution of Life_Expectancy' for each year 2014 to 2017\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "\n",
    "# plot for countries in these regions, set axes to use, labels to use\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==0]['Life_Expectancy'], label=\"Cluster region 0\", color=\"g\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==1]['Life_Expectancy'], label=\"Cluster region 1\", color=\"b\", shade=True)\n",
    "sns.kdeplot(c18.loc[c18.loc[:,'cluster_pred']==2]['Life_Expectancy'], label=\"cluster region 2\", color=\"r\", shade=True)\n",
    "#sns.distplot(clusters.loc[clusters.loc[:,'cluster_pred']==3]['Life Ladder'], ax=axes[3], label=\"cluster region 3\", color=\"y\")\n",
    "# add title\n",
    "plt.suptitle(\"Actual Life_Expectancy variable for the 3 clusters for 2018\");\n",
    "plt.legend();\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the Life Expectancy variable by cluster group, the distribution looks normal for the cluster region 1 while the other two groups are less so. There seems to be two peaks in the distribution for cluster group 0 which probably needs to be broken out more.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean and standard deviation for Healthy Life Expectancy at birth  by clustered group:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>RegionCode</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_pred</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.415971</td>\n",
       "      <td>7.732756</td>\n",
       "      <td>0.669998</td>\n",
       "      <td>54.945161</td>\n",
       "      <td>1.290323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>5.322920</td>\n",
       "      <td>9.294176</td>\n",
       "      <td>0.820008</td>\n",
       "      <td>64.951786</td>\n",
       "      <td>3.946429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>6.614540</td>\n",
       "      <td>10.401640</td>\n",
       "      <td>0.900387</td>\n",
       "      <td>71.515385</td>\n",
       "      <td>4.102564</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Year  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "cluster_pred                                                               \n",
       "0             2018.0           4.415971         7.732756        0.669998   \n",
       "1             2018.0           5.322920         9.294176        0.820008   \n",
       "2             2018.0           6.614540        10.401640        0.900387   \n",
       "\n",
       "              Life_Expectancy  RegionCode  \n",
       "cluster_pred                               \n",
       "0                   54.945161    1.290323  \n",
       "1                   64.951786    3.946429  \n",
       "2                   71.515385    4.102564  "
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c18.groupby('cluster_pred').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate data for the Life Expectancy variable for each of the cluster groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "LEc0= np.random.normal(c18_0['Life_Expectancy'].mean(),c18_0['Life_Expectancy'].std(),31)\n",
    "LEc1= np.random.normal(c18_1['Life_Expectancy'].mean(),c18_1['Life_Expectancy'].std(),39)\n",
    "LEc2= np.random.normal(c18_2['Life_Expectancy'].mean(),c18_2['Life_Expectancy'].std(),56)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot the distributions of the simulated Healthy Life Expectancy at birth variable for the 3 groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matploptlib figure, \n",
    "# https://seaborn.pydata.org/examples/distplot_options.html?highlight=tight_layout#distribution-plot-options\n",
    "sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
    "# life satisfaction distribution for cluster region 0\n",
    "sns.kdeplot(LEc0,color=\"y\", shade=True)\n",
    "# life satisfaction distribution for cluster region 1\n",
    "sns.kdeplot(LEc1, color=\"skyblue\", shade=True)\n",
    "# life satisfaction distribution for cluster region 2\n",
    "sns.kdeplot(LEc2, color=\"pink\", shade=True)\n",
    "# add title\n",
    "plt.suptitle(\"Distribution of simulated Life_Expectancy for 3 region clusters\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a dataset with the simulated variables.\n",
    "\n",
    "Now that the individual variables have been simulated, the next step is to assemble the variables into a dataframe and ensure that the overall distributions and relationships are similar to an actual dataset.\n",
    "Because of the variations between the three groups I will create a dataframe for each group and then concatenate the three dataframes together. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Simulated Dataframe for Group0:\n",
    "Here I create 31 countries and add the simulated data created earlier using numpy.random functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a list of countries by appending number to 'country'\n",
    "G0_countries =[]\n",
    "# use for loop and concatenate number to string\n",
    "for i in range(31):\n",
    "    countryname = 'Sim_Country_'+str(i)\n",
    "    # append countryname  to list of countries\n",
    "    G0_countries.append(countryname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a dataframe and add the columns\n",
    "G0=pd.DataFrame()\n",
    "G0['Country']=G0_countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add columns based on simulations\n",
    "G0['Life_Satisfaction']=LLc0\n",
    "G0['Log_GDP_per_cap']=GDPc0\n",
    "G0['Social_Support']=SSc0\n",
    "G0['Life_Expectancy']=LEc0\n",
    "# add group column\n",
    "G0['Group']='Group0'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>4.832239</td>\n",
       "      <td>7.954537</td>\n",
       "      <td>0.576985</td>\n",
       "      <td>54.335308</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>4.467750</td>\n",
       "      <td>8.305551</td>\n",
       "      <td>0.768666</td>\n",
       "      <td>54.181906</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>5.438583</td>\n",
       "      <td>7.713437</td>\n",
       "      <td>0.491684</td>\n",
       "      <td>53.581250</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>4.020669</td>\n",
       "      <td>7.984861</td>\n",
       "      <td>0.699109</td>\n",
       "      <td>56.451956</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Sim_Country_27</td>\n",
       "      <td>4.110597</td>\n",
       "      <td>8.482766</td>\n",
       "      <td>0.597189</td>\n",
       "      <td>55.757277</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Sim_Country_28</td>\n",
       "      <td>4.604313</td>\n",
       "      <td>8.530728</td>\n",
       "      <td>0.628325</td>\n",
       "      <td>55.697414</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Sim_Country_29</td>\n",
       "      <td>4.007946</td>\n",
       "      <td>6.820538</td>\n",
       "      <td>0.541564</td>\n",
       "      <td>52.697467</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sim_Country_30</td>\n",
       "      <td>4.950610</td>\n",
       "      <td>7.712536</td>\n",
       "      <td>0.700499</td>\n",
       "      <td>58.674700</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>31 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "0    Sim_Country_0           4.832239         7.954537        0.576985   \n",
       "1    Sim_Country_1           4.467750         8.305551        0.768666   \n",
       "2    Sim_Country_2           5.438583         7.713437        0.491684   \n",
       "3    Sim_Country_3           4.020669         7.984861        0.699109   \n",
       "..             ...                ...              ...             ...   \n",
       "27  Sim_Country_27           4.110597         8.482766        0.597189   \n",
       "28  Sim_Country_28           4.604313         8.530728        0.628325   \n",
       "29  Sim_Country_29           4.007946         6.820538        0.541564   \n",
       "30  Sim_Country_30           4.950610         7.712536        0.700499   \n",
       "\n",
       "    Life_Expectancy   Group  \n",
       "0         54.335308  Group0  \n",
       "1         54.181906  Group0  \n",
       "2         53.581250  Group0  \n",
       "3         56.451956  Group0  \n",
       "..              ...     ...  \n",
       "27        55.757277  Group0  \n",
       "28        55.697414  Group0  \n",
       "29        52.697467  Group0  \n",
       "30        58.674700  Group0  \n",
       "\n",
       "[31 rows x 6 columns]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Simulated dataframe for group 1\n",
    "Here I create a dataframe for the 39 group 1 simulated data points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a list of countries by appending number to 'country'\n",
    "G1_countries =[]\n",
    "# use for loop and concatenate number to string\n",
    "for i in range(39):\n",
    "    countryname = 'Sim_Country_'+str(i)\n",
    "    # append countryname  to list of countries\n",
    "    G1_countries.append(countryname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>6.104646</td>\n",
       "      <td>7.605432</td>\n",
       "      <td>0.766122</td>\n",
       "      <td>65.593067</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>6.730420</td>\n",
       "      <td>7.546884</td>\n",
       "      <td>0.780479</td>\n",
       "      <td>62.433074</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>4.757041</td>\n",
       "      <td>10.021645</td>\n",
       "      <td>0.834583</td>\n",
       "      <td>66.025079</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>6.280318</td>\n",
       "      <td>9.607126</td>\n",
       "      <td>0.805516</td>\n",
       "      <td>60.704252</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Sim_Country_35</td>\n",
       "      <td>4.620600</td>\n",
       "      <td>9.078406</td>\n",
       "      <td>0.916114</td>\n",
       "      <td>67.081704</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Sim_Country_36</td>\n",
       "      <td>4.609395</td>\n",
       "      <td>9.588953</td>\n",
       "      <td>0.846324</td>\n",
       "      <td>59.479723</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Sim_Country_37</td>\n",
       "      <td>6.084480</td>\n",
       "      <td>9.305039</td>\n",
       "      <td>0.847234</td>\n",
       "      <td>70.202946</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Sim_Country_38</td>\n",
       "      <td>4.974988</td>\n",
       "      <td>9.251449</td>\n",
       "      <td>0.918559</td>\n",
       "      <td>66.929811</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>39 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "0    Sim_Country_0           6.104646         7.605432        0.766122   \n",
       "1    Sim_Country_1           6.730420         7.546884        0.780479   \n",
       "2    Sim_Country_2           4.757041        10.021645        0.834583   \n",
       "3    Sim_Country_3           6.280318         9.607126        0.805516   \n",
       "..             ...                ...              ...             ...   \n",
       "35  Sim_Country_35           4.620600         9.078406        0.916114   \n",
       "36  Sim_Country_36           4.609395         9.588953        0.846324   \n",
       "37  Sim_Country_37           6.084480         9.305039        0.847234   \n",
       "38  Sim_Country_38           4.974988         9.251449        0.918559   \n",
       "\n",
       "    Life_Expectancy   Group  \n",
       "0         65.593067  Group1  \n",
       "1         62.433074  Group1  \n",
       "2         66.025079  Group1  \n",
       "3         60.704252  Group1  \n",
       "..              ...     ...  \n",
       "35        67.081704  Group1  \n",
       "36        59.479723  Group1  \n",
       "37        70.202946  Group1  \n",
       "38        66.929811  Group1  \n",
       "\n",
       "[39 rows x 6 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a dataframe and add the columns\n",
    "G1=pd.DataFrame()\n",
    "G1['Country']=G1_countries\n",
    "# add columns based on simulations\n",
    "G1['Life_Satisfaction']=LLc1\n",
    "G1['Log_GDP_per_cap']=GDPc1\n",
    "G1['Social_Support']=SSc1\n",
    "G1['Life_Expectancy']=LEc1\n",
    "# add group column\n",
    "G1['Group']='Group1'\n",
    "G1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Simulated dataframe for group 2\n",
    "Here I create a dataframe for the 56 group 1 simulated data points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a list of countries by appending number to 'country'\n",
    "G2_countries =[]\n",
    "# use for loop and concatenate number to string\n",
    "for i in range(56):\n",
    "    countryname = 'Sim_Country_'+str(i)\n",
    "    # append countryname  to list of countries\n",
    "    G2_countries.append(countryname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>5.385795</td>\n",
       "      <td>10.655436</td>\n",
       "      <td>0.748666</td>\n",
       "      <td>73.781418</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>6.358164</td>\n",
       "      <td>10.793122</td>\n",
       "      <td>0.890609</td>\n",
       "      <td>70.576719</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>8.142938</td>\n",
       "      <td>10.876471</td>\n",
       "      <td>0.875233</td>\n",
       "      <td>71.810983</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>5.740609</td>\n",
       "      <td>9.993025</td>\n",
       "      <td>0.978514</td>\n",
       "      <td>73.414892</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Sim_Country_52</td>\n",
       "      <td>6.451683</td>\n",
       "      <td>10.954437</td>\n",
       "      <td>0.867026</td>\n",
       "      <td>71.133910</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Sim_Country_53</td>\n",
       "      <td>7.136838</td>\n",
       "      <td>10.620231</td>\n",
       "      <td>0.851049</td>\n",
       "      <td>72.649691</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Sim_Country_54</td>\n",
       "      <td>6.090275</td>\n",
       "      <td>10.501391</td>\n",
       "      <td>0.973984</td>\n",
       "      <td>73.793844</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Sim_Country_55</td>\n",
       "      <td>6.454728</td>\n",
       "      <td>10.038287</td>\n",
       "      <td>0.923564</td>\n",
       "      <td>69.123699</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>56 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "0    Sim_Country_0           5.385795        10.655436        0.748666   \n",
       "1    Sim_Country_1           6.358164        10.793122        0.890609   \n",
       "2    Sim_Country_2           8.142938        10.876471        0.875233   \n",
       "3    Sim_Country_3           5.740609         9.993025        0.978514   \n",
       "..             ...                ...              ...             ...   \n",
       "52  Sim_Country_52           6.451683        10.954437        0.867026   \n",
       "53  Sim_Country_53           7.136838        10.620231        0.851049   \n",
       "54  Sim_Country_54           6.090275        10.501391        0.973984   \n",
       "55  Sim_Country_55           6.454728        10.038287        0.923564   \n",
       "\n",
       "    Life_Expectancy   Group  \n",
       "0         73.781418  Group2  \n",
       "1         70.576719  Group2  \n",
       "2         71.810983  Group2  \n",
       "3         73.414892  Group2  \n",
       "..              ...     ...  \n",
       "52        71.133910  Group2  \n",
       "53        72.649691  Group2  \n",
       "54        73.793844  Group2  \n",
       "55        69.123699  Group2  \n",
       "\n",
       "[56 rows x 6 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a dataframe and add the columns\n",
    "G2=pd.DataFrame()\n",
    "G2['Country']=G2_countries\n",
    "# add columns based on simulations\n",
    "G2['Life_Satisfaction']=LLc2\n",
    "G2['Log_GDP_per_cap']=GDPc2\n",
    "G2['Social_Support']=SSc2\n",
    "G2['Life_Expectancy']=LEc2\n",
    "# add group column\n",
    "G2['Group']='Group2'\n",
    "G2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create one dataframe from the three group dataframes:\n",
    "Now I add the three dataframes together using the pandas [pd.concat](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#concatenating-objects) function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>4.832239</td>\n",
       "      <td>7.954537</td>\n",
       "      <td>0.576985</td>\n",
       "      <td>54.335308</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>4.467750</td>\n",
       "      <td>8.305551</td>\n",
       "      <td>0.768666</td>\n",
       "      <td>54.181906</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>5.438583</td>\n",
       "      <td>7.713437</td>\n",
       "      <td>0.491684</td>\n",
       "      <td>53.581250</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>4.020669</td>\n",
       "      <td>7.984861</td>\n",
       "      <td>0.699109</td>\n",
       "      <td>56.451956</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sim_Country_4</td>\n",
       "      <td>5.160103</td>\n",
       "      <td>6.428954</td>\n",
       "      <td>0.570764</td>\n",
       "      <td>56.635865</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Country  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "0  Sim_Country_0           4.832239         7.954537        0.576985   \n",
       "1  Sim_Country_1           4.467750         8.305551        0.768666   \n",
       "2  Sim_Country_2           5.438583         7.713437        0.491684   \n",
       "3  Sim_Country_3           4.020669         7.984861        0.699109   \n",
       "4  Sim_Country_4           5.160103         6.428954        0.570764   \n",
       "\n",
       "   Life_Expectancy   Group  \n",
       "0        54.335308  Group0  \n",
       "1        54.181906  Group0  \n",
       "2        53.581250  Group0  \n",
       "3        56.451956  Group0  \n",
       "4        56.635865  Group0  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using the pandas concat function to add the dataframes together.\n",
    "result=pd.concat([G0,G1,G2])\n",
    "result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 796.475x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(result, hue='Group', palette=\"colorblind\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_pred</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "cluster_pred                                                       \n",
       "0                            31               31              31   \n",
       "1                            56               56              56   \n",
       "2                            39               39              39   \n",
       "\n",
       "              Life_Expectancy  \n",
       "cluster_pred                   \n",
       "0                          31  \n",
       "1                          56  \n",
       "2                          39  "
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2018 =c18.drop(['Year', 'RegionCode'], axis=1)\n",
    "data2018.groupby('cluster_pred').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">Life_Satisfaction</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Log_GDP_per_cap</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Social_Support</th>\n",
       "      <th colspan=\"8\" halign=\"left\">Life_Expectancy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Group0</th>\n",
       "      <td>31.0</td>\n",
       "      <td>4.422543</td>\n",
       "      <td>0.615711</td>\n",
       "      <td>2.909746</td>\n",
       "      <td>4.065187</td>\n",
       "      <td>4.556024</td>\n",
       "      <td>4.945726</td>\n",
       "      <td>5.438583</td>\n",
       "      <td>31.0</td>\n",
       "      <td>7.734934</td>\n",
       "      <td>...</td>\n",
       "      <td>0.699804</td>\n",
       "      <td>0.768666</td>\n",
       "      <td>31.0</td>\n",
       "      <td>55.259923</td>\n",
       "      <td>2.475357</td>\n",
       "      <td>49.272071</td>\n",
       "      <td>53.747705</td>\n",
       "      <td>55.301478</td>\n",
       "      <td>56.548758</td>\n",
       "      <td>60.638536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group1</th>\n",
       "      <td>39.0</td>\n",
       "      <td>5.371623</td>\n",
       "      <td>0.664994</td>\n",
       "      <td>4.032521</td>\n",
       "      <td>4.791150</td>\n",
       "      <td>5.343593</td>\n",
       "      <td>5.866724</td>\n",
       "      <td>6.730420</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.260510</td>\n",
       "      <td>...</td>\n",
       "      <td>0.886052</td>\n",
       "      <td>1.033914</td>\n",
       "      <td>39.0</td>\n",
       "      <td>65.235205</td>\n",
       "      <td>3.073510</td>\n",
       "      <td>59.479723</td>\n",
       "      <td>62.890154</td>\n",
       "      <td>65.593067</td>\n",
       "      <td>67.170527</td>\n",
       "      <td>71.912801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group2</th>\n",
       "      <td>56.0</td>\n",
       "      <td>6.615244</td>\n",
       "      <td>0.672666</td>\n",
       "      <td>5.357937</td>\n",
       "      <td>6.239783</td>\n",
       "      <td>6.478841</td>\n",
       "      <td>7.084465</td>\n",
       "      <td>8.142938</td>\n",
       "      <td>56.0</td>\n",
       "      <td>10.510371</td>\n",
       "      <td>...</td>\n",
       "      <td>0.922224</td>\n",
       "      <td>1.001420</td>\n",
       "      <td>56.0</td>\n",
       "      <td>71.715760</td>\n",
       "      <td>1.843169</td>\n",
       "      <td>66.785619</td>\n",
       "      <td>70.557719</td>\n",
       "      <td>71.703480</td>\n",
       "      <td>73.217038</td>\n",
       "      <td>75.534256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Life_Satisfaction                                                    \\\n",
       "                   count      mean       std       min       25%       50%   \n",
       "Group                                                                        \n",
       "Group0              31.0  4.422543  0.615711  2.909746  4.065187  4.556024   \n",
       "Group1              39.0  5.371623  0.664994  4.032521  4.791150  5.343593   \n",
       "Group2              56.0  6.615244  0.672666  5.357937  6.239783  6.478841   \n",
       "\n",
       "                           Log_GDP_per_cap             ... Social_Support  \\\n",
       "             75%       max           count       mean  ...            75%   \n",
       "Group                                                  ...                  \n",
       "Group0  4.945726  5.438583            31.0   7.734934  ...       0.699804   \n",
       "Group1  5.866724  6.730420            39.0   9.260510  ...       0.886052   \n",
       "Group2  7.084465  8.142938            56.0  10.510371  ...       0.922224   \n",
       "\n",
       "                 Life_Expectancy                                             \\\n",
       "             max           count       mean       std        min        25%   \n",
       "Group                                                                         \n",
       "Group0  0.768666            31.0  55.259923  2.475357  49.272071  53.747705   \n",
       "Group1  1.033914            39.0  65.235205  3.073510  59.479723  62.890154   \n",
       "Group2  1.001420            56.0  71.715760  1.843169  66.785619  70.557719   \n",
       "\n",
       "                                         \n",
       "              50%        75%        max  \n",
       "Group                                    \n",
       "Group0  55.301478  56.548758  60.638536  \n",
       "Group1  65.593067  67.170527  71.912801  \n",
       "Group2  71.703480  73.217038  75.534256  \n",
       "\n",
       "[3 rows x 32 columns]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.groupby('Group').describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "data2018\n",
    "data2018['cluster_pred']=data2018[\"cluster_pred\"].replace(0,'Group2')\n",
    "data2018['cluster_pred']=data2018[\"cluster_pred\"].replace(1,'Group0')\n",
    "data2018['cluster_pred']=data2018[\"cluster_pred\"].replace(2,'Group1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 796.475x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data2018, hue='cluster_pred', palette=\"bright\", hue_order=['Group0','Group1','Group2']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulated Life Satisfaction / Life Ladder variable:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Compare statistics from actual data for 2018 to simulated data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_pred</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Group0</th>\n",
       "      <td>5.322920</td>\n",
       "      <td>9.294176</td>\n",
       "      <td>0.820008</td>\n",
       "      <td>64.951786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group1</th>\n",
       "      <td>6.614540</td>\n",
       "      <td>10.401640</td>\n",
       "      <td>0.900387</td>\n",
       "      <td>71.515385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group2</th>\n",
       "      <td>4.415971</td>\n",
       "      <td>7.732756</td>\n",
       "      <td>0.669998</td>\n",
       "      <td>54.945161</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "cluster_pred                                                       \n",
       "Group0                 5.322920         9.294176        0.820008   \n",
       "Group1                 6.614540        10.401640        0.900387   \n",
       "Group2                 4.415971         7.732756        0.669998   \n",
       "\n",
       "              Life_Expectancy  \n",
       "cluster_pred                   \n",
       "Group0              64.951786  \n",
       "Group1              71.515385  \n",
       "Group2              54.945161  "
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2018.groupby('cluster_pred').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Group0</th>\n",
       "      <td>4.422543</td>\n",
       "      <td>7.734934</td>\n",
       "      <td>0.624332</td>\n",
       "      <td>55.259923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group1</th>\n",
       "      <td>5.371623</td>\n",
       "      <td>9.260510</td>\n",
       "      <td>0.807343</td>\n",
       "      <td>65.235205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group2</th>\n",
       "      <td>6.615244</td>\n",
       "      <td>10.510371</td>\n",
       "      <td>0.888373</td>\n",
       "      <td>71.715760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy\n",
       "Group                                                                      \n",
       "Group0           4.422543         7.734934        0.624332        55.259923\n",
       "Group1           5.371623         9.260510        0.807343        65.235205\n",
       "Group2           6.615244        10.510371        0.888373        71.715760"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.groupby('Group').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot actual vs simulated Life Satisfaction:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x648 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the subplots, style and palette\n",
    "sns.set(style=\"ticks\", palette=\"colorblind\")\n",
    "f,axes=plt.subplots(2,2, figsize=(9,9))\n",
    "# plot the distributions of each of the main variables. first simulated and then actual for 2018\n",
    "sns.kdeplot(result['Life_Satisfaction'], ax=axes[0,0], shade=True, label=\"simulated\")\n",
    "sns.kdeplot(data2018['Life_Satisfaction'], ax=axes[0,0], shade=True,label=\"actual\")\n",
    "# set axes title\n",
    "axes[0,0].set_title(\"Distribution of Life Ladder\")\n",
    "# plot the distributions of each of the main variables. first simulated and then actual for 2018\n",
    "sns.kdeplot(result['Log_GDP_per_cap'], ax=axes[0,1], shade=True, label=\"simulated\")\n",
    "sns.kdeplot(data2018['Log_GDP_per_cap'].dropna(), ax=axes[0,1], shade=True, label=\"actual\")\n",
    "# axes title\n",
    "axes[0,1].set_title(\"Distribution of Log GDP per capita\")\n",
    "# plot the distributions of each of the main variables. first simulated and then actual for 2018\n",
    "sns.kdeplot(result['Social_Support'].dropna(), ax=axes[1,0], shade=True, label=\"simulated\")\n",
    "sns.kdeplot(data2018['Social_Support'].dropna(), ax=axes[1,0], shade=True, label=\"simulated\")\n",
    "axes[1,0].set_title(\"Distribution of Social Support\");\n",
    "# plot the distributions of each of the main variables. first simulated and then actual for 2018\n",
    "sns.kdeplot(result['Life_Expectancy'], ax=axes[1,1],shade=True, label=\"Simulated\");\n",
    "sns.kdeplot(data2018['Life_Expectancy'], ax=axes[1,1],shade=True, label=\"Simulated\");\n",
    "axes[1,1].set_title(\"Distribution of Simulated Life expectancy\");  \n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "They are not perfect matches but it will do for now!\n",
    "Every time a numpy.random function is run it will produce different numbers from the same distribution unless the seed is set. Now I will just check the correlations and any relationships in the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparing Relationships between the variables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Relationships between the simulated variables:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib figure\n",
    "f,axes=plt.subplots(1,3, figsize=(12,4))\n",
    "# regression plot with x as a predictor of y variable. set the axes.\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Log_GDP_per_cap\", data=result, ax=axes[0])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Social_Support\", data=result, ax=axes[1])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Life_Expectancy\", data=result, ax=axes[2])\n",
    "axes[2].set_ylim(0,10); axes[2].set_xlim(40,90)\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Relationships between the actual variables:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib figure\n",
    "f,axes=plt.subplots(1,3, figsize=(12,4))\n",
    "# regression plot with x as a predictor of y variable. set the axes.\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Log_GDP_per_cap\", data=data2018, ax=axes[0])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Social_Support\", data=data2018, ax=axes[1])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Life_Expectancy\", data=data2018, ax=axes[2])\n",
    "axes[2].set_ylim(0,10); axes[2].set_xlim(40,90)\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x648 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the subplots, style and palette\n",
    "sns.set(style=\"ticks\", palette=\"colorblind\")\n",
    "f,axes=plt.subplots(2,2, figsize=(9,9))\n",
    "# plot the distributions of each of the main variables. At global level first. Look at Regional after\n",
    "sns.distplot(result['Life_Satisfaction'].dropna(), ax=axes[0,0], bins=10, color=\"r\");\n",
    "# set axes title\n",
    "axes[0,0].set_title(\"Distribution of Simulated Life Ladder\");\n",
    "sns.distplot(result['Log_GDP_per_cap'].dropna(), ax=axes[0,1], bins=10, color=\"g\");\n",
    "axes[0,1].set_title(\"Distribution of Simulated Income\");\n",
    "sns.distplot(result['Social_Support'].dropna(), ax=axes[1,0], bins=10, color=\"b\");\n",
    "axes[1,0].set_title(\"Distribution of Simulated Social Support\");\n",
    "sns.distplot(result['Life_Expectancy'].dropna(), ax=axes[1,1], bins=10, color=\"y\");\n",
    "axes[1,1].set_title(\"Distribution of Simulated Life expectancy\");  \n",
    "plt.tight_layout();\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x648 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the subplots, style and palette\n",
    "sns.set(style=\"ticks\", palette=\"colorblind\")\n",
    "f,axes=plt.subplots(2,2, figsize=(9,9))\n",
    "# plot the distributions of each of the main variables. At global level first. Look at Regional after\n",
    "sns.distplot(data2018['Life_Satisfaction'].dropna(), ax=axes[0,0], bins=10, color=\"r\");\n",
    "# set axes title\n",
    "axes[0,0].set_title(\"Distribution of Actual Life Ladder\");\n",
    "sns.distplot(data2018['Log_GDP_per_cap'].dropna(), ax=axes[0,1], bins=10, color=\"g\");\n",
    "axes[0,1].set_title(\"Distribution of Actual Income\");\n",
    "sns.distplot(data2018['Social_Support'].dropna(), ax=axes[1,0], bins=10, color=\"b\");\n",
    "axes[1,0].set_title(\"Distribution of Actual Social Support\");\n",
    "sns.distplot(data2018['Life_Expectancy'].dropna(), ax=axes[1,1], bins=10, color=\"y\");\n",
    "axes[1,1].set_title(\"Distribution of Actual Life expectancy\");  \n",
    "plt.tight_layout();\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>cluster_pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7.508587</td>\n",
       "      <td>10.975945</td>\n",
       "      <td>0.930291</td>\n",
       "      <td>74.099998</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>7.648786</td>\n",
       "      <td>10.755594</td>\n",
       "      <td>0.958219</td>\n",
       "      <td>72.400002</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>7.444262</td>\n",
       "      <td>11.085626</td>\n",
       "      <td>0.965962</td>\n",
       "      <td>73.199997</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>7.175497</td>\n",
       "      <td>10.701248</td>\n",
       "      <td>0.922719</td>\n",
       "      <td>73.599998</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1658</th>\n",
       "      <td>3.775283</td>\n",
       "      <td>6.541033</td>\n",
       "      <td>0.484715</td>\n",
       "      <td>53.400002</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666</th>\n",
       "      <td>4.022895</td>\n",
       "      <td>7.287405</td>\n",
       "      <td>0.596354</td>\n",
       "      <td>54.700001</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1693</th>\n",
       "      <td>4.834088</td>\n",
       "      <td>9.156214</td>\n",
       "      <td>0.864215</td>\n",
       "      <td>56.500000</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1695</th>\n",
       "      <td>4.922099</td>\n",
       "      <td>7.376554</td>\n",
       "      <td>0.684800</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>126 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy  \\\n",
       "7              7.508587        10.975945        0.930291        74.099998   \n",
       "26             7.648786        10.755594        0.958219        72.400002   \n",
       "34             7.444262        11.085626        0.965962        73.199997   \n",
       "47             7.175497        10.701248        0.922719        73.599998   \n",
       "...                 ...              ...             ...              ...   \n",
       "1658           3.775283         6.541033        0.484715        53.400002   \n",
       "1666           4.022895         7.287405        0.596354        54.700001   \n",
       "1693           4.834088         9.156214        0.864215        56.500000   \n",
       "1695           4.922099         7.376554        0.684800        55.000000   \n",
       "\n",
       "     cluster_pred  \n",
       "7          Group1  \n",
       "26         Group1  \n",
       "34         Group1  \n",
       "47         Group1  \n",
       "...           ...  \n",
       "1658       Group2  \n",
       "1666       Group2  \n",
       "1693       Group2  \n",
       "1695       Group2  \n",
       "\n",
       "[126 rows x 5 columns]"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2018"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The simulated data:\n",
    "The final simulated dataframe containing the 6 variables is called `result`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>6.267685</td>\n",
       "      <td>10.803498</td>\n",
       "      <td>0.795049</td>\n",
       "      <td>60.806682</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>5.110587</td>\n",
       "      <td>9.080027</td>\n",
       "      <td>0.640821</td>\n",
       "      <td>66.785900</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>5.540722</td>\n",
       "      <td>8.922393</td>\n",
       "      <td>0.839534</td>\n",
       "      <td>64.794915</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>5.336537</td>\n",
       "      <td>8.070281</td>\n",
       "      <td>0.747437</td>\n",
       "      <td>69.162369</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Sim_Country_52</td>\n",
       "      <td>6.323531</td>\n",
       "      <td>9.556789</td>\n",
       "      <td>0.881490</td>\n",
       "      <td>75.690192</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Sim_Country_53</td>\n",
       "      <td>6.869105</td>\n",
       "      <td>9.599043</td>\n",
       "      <td>0.929405</td>\n",
       "      <td>72.560246</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Sim_Country_54</td>\n",
       "      <td>5.694291</td>\n",
       "      <td>10.437149</td>\n",
       "      <td>0.870270</td>\n",
       "      <td>72.142102</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Sim_Country_55</td>\n",
       "      <td>7.036823</td>\n",
       "      <td>10.386843</td>\n",
       "      <td>0.843862</td>\n",
       "      <td>70.846795</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>126 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "0    Sim_Country_0           6.267685        10.803498        0.795049   \n",
       "1    Sim_Country_1           5.110587         9.080027        0.640821   \n",
       "2    Sim_Country_2           5.540722         8.922393        0.839534   \n",
       "3    Sim_Country_3           5.336537         8.070281        0.747437   \n",
       "..             ...                ...              ...             ...   \n",
       "52  Sim_Country_52           6.323531         9.556789        0.881490   \n",
       "53  Sim_Country_53           6.869105         9.599043        0.929405   \n",
       "54  Sim_Country_54           5.694291        10.437149        0.870270   \n",
       "55  Sim_Country_55           7.036823        10.386843        0.843862   \n",
       "\n",
       "    Life_Expectancy   Group  \n",
       "0         60.806682  Group0  \n",
       "1         66.785900  Group0  \n",
       "2         64.794915  Group0  \n",
       "3         69.162369  Group0  \n",
       "..              ...     ...  \n",
       "52        75.690192  Group2  \n",
       "53        72.560246  Group2  \n",
       "54        72.142102  Group2  \n",
       "55        70.846795  Group2  \n",
       "\n",
       "[126 rows x 6 columns]"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using the multivariate normal distribution function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An alternative way to simulating the dataset could be to use the multivariate normal distribution function. While the variables are not all normally distributed at the dataset level, when broken down by the regions they do appear to be gaussian with each groups distributions having very different centres and spreads to each other.\n",
    "\n",
    "There is a [numpy.random.multivariate](https://numpy.org/doc/1.16/reference/generated/numpy.random.multivariate_normal.html#numpy-random-multivariate-normal) function that can generated correlated data. \n",
    "\n",
    "I found a thread at stack overflow referencing how to use the multivariate function to [generate correlated data]\n",
    "(https://stackoverflow.com/a/16026231)[26]\n",
    "Here I filter the data for each group and calculate the covariance on the first three variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">Life_Satisfaction</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Log_GDP_per_cap</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Social_Support</th>\n",
       "      <th colspan=\"8\" halign=\"left\">Life_Expectancy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_pred</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Group0</th>\n",
       "      <td>31.0</td>\n",
       "      <td>4.415971</td>\n",
       "      <td>0.730419</td>\n",
       "      <td>2.694303</td>\n",
       "      <td>3.997857</td>\n",
       "      <td>4.379262</td>\n",
       "      <td>4.924668</td>\n",
       "      <td>5.819827</td>\n",
       "      <td>31.0</td>\n",
       "      <td>7.732756</td>\n",
       "      <td>...</td>\n",
       "      <td>0.739598</td>\n",
       "      <td>0.864215</td>\n",
       "      <td>31.0</td>\n",
       "      <td>54.945161</td>\n",
       "      <td>2.912598</td>\n",
       "      <td>48.200001</td>\n",
       "      <td>53.450001</td>\n",
       "      <td>55.299999</td>\n",
       "      <td>57.100000</td>\n",
       "      <td>59.599998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group1</th>\n",
       "      <td>39.0</td>\n",
       "      <td>6.614540</td>\n",
       "      <td>0.740771</td>\n",
       "      <td>5.004403</td>\n",
       "      <td>6.109656</td>\n",
       "      <td>6.665904</td>\n",
       "      <td>7.205219</td>\n",
       "      <td>7.858107</td>\n",
       "      <td>39.0</td>\n",
       "      <td>10.401640</td>\n",
       "      <td>...</td>\n",
       "      <td>0.930485</td>\n",
       "      <td>0.965962</td>\n",
       "      <td>39.0</td>\n",
       "      <td>71.515385</td>\n",
       "      <td>2.043286</td>\n",
       "      <td>68.300003</td>\n",
       "      <td>69.450001</td>\n",
       "      <td>72.300003</td>\n",
       "      <td>73.199997</td>\n",
       "      <td>75.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Group2</th>\n",
       "      <td>56.0</td>\n",
       "      <td>5.322920</td>\n",
       "      <td>0.704197</td>\n",
       "      <td>3.561047</td>\n",
       "      <td>4.840304</td>\n",
       "      <td>5.296465</td>\n",
       "      <td>5.902972</td>\n",
       "      <td>6.626592</td>\n",
       "      <td>56.0</td>\n",
       "      <td>9.294176</td>\n",
       "      <td>...</td>\n",
       "      <td>0.882849</td>\n",
       "      <td>0.984489</td>\n",
       "      <td>56.0</td>\n",
       "      <td>64.951786</td>\n",
       "      <td>2.692346</td>\n",
       "      <td>58.500000</td>\n",
       "      <td>63.574999</td>\n",
       "      <td>65.950001</td>\n",
       "      <td>67.025000</td>\n",
       "      <td>68.199997</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Life_Satisfaction                                          \\\n",
       "                         count      mean       std       min       25%   \n",
       "cluster_pred                                                             \n",
       "Group0                    31.0  4.415971  0.730419  2.694303  3.997857   \n",
       "Group1                    39.0  6.614540  0.740771  5.004403  6.109656   \n",
       "Group2                    56.0  5.322920  0.704197  3.561047  4.840304   \n",
       "\n",
       "                                           Log_GDP_per_cap             ...  \\\n",
       "                   50%       75%       max           count       mean  ...   \n",
       "cluster_pred                                                           ...   \n",
       "Group0        4.379262  4.924668  5.819827            31.0   7.732756  ...   \n",
       "Group1        6.665904  7.205219  7.858107            39.0  10.401640  ...   \n",
       "Group2        5.296465  5.902972  6.626592            56.0   9.294176  ...   \n",
       "\n",
       "             Social_Support           Life_Expectancy                       \\\n",
       "                        75%       max           count       mean       std   \n",
       "cluster_pred                                                                 \n",
       "Group0             0.739598  0.864215            31.0  54.945161  2.912598   \n",
       "Group1             0.930485  0.965962            39.0  71.515385  2.043286   \n",
       "Group2             0.882849  0.984489            56.0  64.951786  2.692346   \n",
       "\n",
       "                                                                     \n",
       "                    min        25%        50%        75%        max  \n",
       "cluster_pred                                                         \n",
       "Group0        48.200001  53.450001  55.299999  57.100000  59.599998  \n",
       "Group1        68.300003  69.450001  72.300003  73.199997  75.000000  \n",
       "Group2        58.500000  63.574999  65.950001  67.025000  68.199997  \n",
       "\n",
       "[3 rows x 32 columns]"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2018.groupby('cluster_pred').describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [],
   "source": [
    "# select clusters for each group\n",
    "group0 =data2018.loc[data2018.cluster_pred=='Group0']\n",
    "group1 =data2018.loc[data2018.cluster_pred=='Group1']\n",
    "group2 =data2018.loc[data2018.cluster_pred=='Group2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get the covariances for each cluster group\n",
    "group0cov = group0.iloc[:,:4].cov()\n",
    "group1cov = group1.iloc[:,:4].cov()\n",
    "group2cov = group2.iloc[:,:4].cov()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get the mean of the variables for each group:\n",
    "group0mean=group0.iloc[:,:4].mean()\n",
    "group1mean=group1.iloc[:,:4].mean()\n",
    "group2mean=group2.iloc[:,:4].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Group0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use number of samples based on number of countries in the grup\n",
    "num_samples=31\n",
    "# using group0 means of each variable\n",
    "mu=group0mean\n",
    "# using group0 covariances for each grouo\n",
    "r=group0cov\n",
    "# generate the random samples using `multivariate` function\n",
    "g0=np.random.multivariate_normal(mu,r,size=num_samples)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Group1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(39, 4)"
      ]
     },
     "execution_count": 311,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use number of samples based on number of countries in the grup\n",
    "num_samples=39\n",
    "# using group0 means of each variable\n",
    "mu=group1mean\n",
    "# using group0 covariances for each grouo\n",
    "r=group1cov\n",
    "# generate the random samples using `multivariate` function\n",
    "g1=np.random.multivariate_normal(mu,r,size=num_samples)\n",
    "g1.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Group2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(56, 4)"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use number of samples based on number of countries in the grup\n",
    "num_samples=56\n",
    "# using group0 means of each variable\n",
    "mu=group1mean\n",
    "# using group0 covariances for each grouo\n",
    "r=group1cov\n",
    "# generate the random samples using `multivariate` function\n",
    "g2=np.random.multivariate_normal(mu,r,size=num_samples)\n",
    "g2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Country</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.926105</td>\n",
       "      <td>7.510145</td>\n",
       "      <td>0.622229</td>\n",
       "      <td>51.814517</td>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.883166</td>\n",
       "      <td>6.292586</td>\n",
       "      <td>0.562239</td>\n",
       "      <td>52.022762</td>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.282169</td>\n",
       "      <td>8.944670</td>\n",
       "      <td>0.709677</td>\n",
       "      <td>54.773639</td>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.410668</td>\n",
       "      <td>7.771072</td>\n",
       "      <td>0.630599</td>\n",
       "      <td>53.133430</td>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>6.451842</td>\n",
       "      <td>10.783218</td>\n",
       "      <td>0.924872</td>\n",
       "      <td>73.078582</td>\n",
       "      <td>Sim_Country_52</td>\n",
       "      <td>group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>6.531446</td>\n",
       "      <td>10.020468</td>\n",
       "      <td>0.873093</td>\n",
       "      <td>68.993780</td>\n",
       "      <td>Sim_Country_53</td>\n",
       "      <td>group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>6.742441</td>\n",
       "      <td>10.773313</td>\n",
       "      <td>0.856621</td>\n",
       "      <td>75.822891</td>\n",
       "      <td>Sim_Country_54</td>\n",
       "      <td>group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>7.798454</td>\n",
       "      <td>11.225295</td>\n",
       "      <td>0.989368</td>\n",
       "      <td>74.232556</td>\n",
       "      <td>Sim_Country_55</td>\n",
       "      <td>group2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>126 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Life_Satisfaction  Log_GDP_per_cap  Social_Support  Life_Expectancy  \\\n",
       "0            4.926105         7.510145        0.622229        51.814517   \n",
       "1            3.883166         6.292586        0.562239        52.022762   \n",
       "2            5.282169         8.944670        0.709677        54.773639   \n",
       "3            5.410668         7.771072        0.630599        53.133430   \n",
       "..                ...              ...             ...              ...   \n",
       "52           6.451842        10.783218        0.924872        73.078582   \n",
       "53           6.531446        10.020468        0.873093        68.993780   \n",
       "54           6.742441        10.773313        0.856621        75.822891   \n",
       "55           7.798454        11.225295        0.989368        74.232556   \n",
       "\n",
       "           Country   Group  \n",
       "0    Sim_Country_0  group0  \n",
       "1    Sim_Country_1  group0  \n",
       "2    Sim_Country_2  group0  \n",
       "3    Sim_Country_3  group0  \n",
       "..             ...     ...  \n",
       "52  Sim_Country_52  group2  \n",
       "53  Sim_Country_53  group2  \n",
       "54  Sim_Country_54  group2  \n",
       "55  Sim_Country_55  group2  \n",
       "\n",
       "[126 rows x 6 columns]"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create dataframe from multivariate normal, u\n",
    "MV0 =pd.DataFrame(g0)\n",
    "# using countries from earlier as simulated earlier\n",
    "MV0['Country']=G0_countries\n",
    "# add a group column\n",
    "MV0['Group']='group0'\n",
    "# create dataframe\n",
    "MV1 =pd.DataFrame(g1)\n",
    "# using countries from earlier as simulated earlier\n",
    "MV1['Country']=G1_countries\n",
    "# add a group column\n",
    "MV1['Group']='group1'\n",
    "# create dataframe\n",
    "MV2 =pd.DataFrame(g2)\n",
    "# using countries from earlier as simulated earlier\n",
    "MV2['Country']=G2_countries\n",
    "# add a group column\n",
    "MV2['Group']='group2'\n",
    "# concat the three dataframes\n",
    "MV = pd.concat([MV0,MV1,MV2])\n",
    "# get the column names\n",
    "MV.columns\n",
    "# https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename.html#pandas-dataframe-rename\n",
    "# rename the columns\n",
    "MV=MV.rename(columns={0: \"Life_Satisfaction\", 1: \"Log_GDP_per_cap\",2:\"Social_Support\",3:\"Life_Expectancy\"})\n",
    "MV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.857240</td>\n",
       "      <td>0.813335</td>\n",
       "      <td>0.827770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <td>0.857240</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.890068</td>\n",
       "      <td>0.932760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social_Support</th>\n",
       "      <td>0.813335</td>\n",
       "      <td>0.890068</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.869135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <td>0.827770</td>\n",
       "      <td>0.932760</td>\n",
       "      <td>0.869135</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "Life_Satisfaction           1.000000         0.857240        0.813335   \n",
       "Log_GDP_per_cap             0.857240         1.000000        0.890068   \n",
       "Social_Support              0.813335         0.890068        1.000000   \n",
       "Life_Expectancy             0.827770         0.932760        0.869135   \n",
       "\n",
       "                   Life_Expectancy  \n",
       "Life_Satisfaction         0.827770  \n",
       "Log_GDP_per_cap           0.932760  \n",
       "Social_Support            0.869135  \n",
       "Life_Expectancy           1.000000  "
      ]
     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MV.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.762152</td>\n",
       "      <td>0.731221</td>\n",
       "      <td>0.740537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <td>0.762152</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.792845</td>\n",
       "      <td>0.852848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social_Support</th>\n",
       "      <td>0.731221</td>\n",
       "      <td>0.792845</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.757044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <td>0.740537</td>\n",
       "      <td>0.852848</td>\n",
       "      <td>0.757044</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "Life_Satisfaction           1.000000         0.762152        0.731221   \n",
       "Log_GDP_per_cap             0.762152         1.000000        0.792845   \n",
       "Social_Support              0.731221         0.792845        1.000000   \n",
       "Life_Expectancy             0.740537         0.852848        0.757044   \n",
       "\n",
       "                   Life_Expectancy  \n",
       "Life_Satisfaction         0.740537  \n",
       "Log_GDP_per_cap           0.852848  \n",
       "Social_Support            0.757044  \n",
       "Life_Expectancy           1.000000  "
      ]
     },
     "execution_count": 315,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2018.iloc[:,:4].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the matplotlib figure\n",
    "f,axes=plt.subplots(1,3, figsize=(12,3))\n",
    "# regression plot with x as a predictor of y variable. set the axes.\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Log_GDP_per_cap\", data=MV, ax=axes[0])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Social_Support\", data=MV, ax=axes[1])\n",
    "sns.regplot(y =\"Life_Satisfaction\",x=\"Life_Expectancy\", data=MV, ax=axes[2])\n",
    "# change the axis limited for Life expectancy\n",
    "axes[2].set_ylim(0,10); axes[2].set_xlim(40,90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"conclusion\"></a>\n",
    "# 4. Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The aim of the project was to create a data set by simulating a real-world phenomenon of our choosing. Then rather than collect data related to the phenomenon, model and synthesis such data using Python and the `numpy.random` package.\n",
    "In this notebook I first analysed an actual dataset for the phenomenon of World Happiness in order to understand the type of variables and the type of distributions they were likely to have come from and also to see how they were related to each other. \n",
    "\n",
    "I then simulated the dataset, mainly using the `numpy.random` package but exploring some functionality from the scikit-learn package.\n",
    "\n",
    "Finally I compared the results of the simulation to a real world dataset. \n",
    "\n",
    "I believe the synthesised dataset closely matches the actual dataset. The results will change each time the code is run as the random seed is not set. In reality data samples would also vary from sample to sample due to randomness.\n",
    "\n",
    "The dataset was a little more complicated that it first appeared to be, given the regional variation and also variation within regions. Given that the number of datapoints for a dataset such as this is limited, the number of datapoints that could be simulated is limited but I am satisfied with the results.  Overall this project was a very good learning experience. \n",
    "It was also very eye-opening to see the levels of inequality across the globe. \n",
    "\n",
    "The last section below lists the references used for this project. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The simulated dataset:\n",
    "\n",
    "pd.options.display.max_rows=8 \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Life_Satisfaction</th>\n",
       "      <th>Log_GDP_per_cap</th>\n",
       "      <th>Social_Support</th>\n",
       "      <th>Life_Expectancy</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>4.832239</td>\n",
       "      <td>7.954537</td>\n",
       "      <td>0.576985</td>\n",
       "      <td>54.335308</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>4.467750</td>\n",
       "      <td>8.305551</td>\n",
       "      <td>0.768666</td>\n",
       "      <td>54.181906</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>5.438583</td>\n",
       "      <td>7.713437</td>\n",
       "      <td>0.491684</td>\n",
       "      <td>53.581250</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>4.020669</td>\n",
       "      <td>7.984861</td>\n",
       "      <td>0.699109</td>\n",
       "      <td>56.451956</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sim_Country_4</td>\n",
       "      <td>5.160103</td>\n",
       "      <td>6.428954</td>\n",
       "      <td>0.570764</td>\n",
       "      <td>56.635865</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Sim_Country_5</td>\n",
       "      <td>4.242171</td>\n",
       "      <td>7.809745</td>\n",
       "      <td>0.647433</td>\n",
       "      <td>55.029355</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Sim_Country_6</td>\n",
       "      <td>5.022303</td>\n",
       "      <td>8.346845</td>\n",
       "      <td>0.752324</td>\n",
       "      <td>53.277792</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Sim_Country_7</td>\n",
       "      <td>2.923470</td>\n",
       "      <td>8.415365</td>\n",
       "      <td>0.752652</td>\n",
       "      <td>56.461650</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sim_Country_8</td>\n",
       "      <td>4.556024</td>\n",
       "      <td>7.802063</td>\n",
       "      <td>0.764483</td>\n",
       "      <td>54.363260</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sim_Country_9</td>\n",
       "      <td>4.109705</td>\n",
       "      <td>9.005313</td>\n",
       "      <td>0.538347</td>\n",
       "      <td>53.842117</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sim_Country_10</td>\n",
       "      <td>4.581402</td>\n",
       "      <td>7.729789</td>\n",
       "      <td>0.569938</td>\n",
       "      <td>55.301478</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Sim_Country_11</td>\n",
       "      <td>4.585434</td>\n",
       "      <td>7.157559</td>\n",
       "      <td>0.714820</td>\n",
       "      <td>57.871060</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Sim_Country_12</td>\n",
       "      <td>5.037641</td>\n",
       "      <td>6.686651</td>\n",
       "      <td>0.575100</td>\n",
       "      <td>59.463959</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sim_Country_13</td>\n",
       "      <td>4.621235</td>\n",
       "      <td>7.329555</td>\n",
       "      <td>0.566648</td>\n",
       "      <td>58.132118</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sim_Country_14</td>\n",
       "      <td>5.002786</td>\n",
       "      <td>8.761313</td>\n",
       "      <td>0.424965</td>\n",
       "      <td>54.969960</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Sim_Country_15</td>\n",
       "      <td>3.975284</td>\n",
       "      <td>9.081068</td>\n",
       "      <td>0.692273</td>\n",
       "      <td>52.951953</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Sim_Country_16</td>\n",
       "      <td>3.417133</td>\n",
       "      <td>6.930615</td>\n",
       "      <td>0.537136</td>\n",
       "      <td>49.272071</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sim_Country_17</td>\n",
       "      <td>4.934614</td>\n",
       "      <td>8.031422</td>\n",
       "      <td>0.579652</td>\n",
       "      <td>55.766907</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Sim_Country_18</td>\n",
       "      <td>4.210346</td>\n",
       "      <td>7.192087</td>\n",
       "      <td>0.584974</td>\n",
       "      <td>54.040780</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sim_Country_19</td>\n",
       "      <td>5.006668</td>\n",
       "      <td>8.508099</td>\n",
       "      <td>0.743774</td>\n",
       "      <td>50.065262</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Sim_Country_20</td>\n",
       "      <td>2.909746</td>\n",
       "      <td>7.174338</td>\n",
       "      <td>0.672582</td>\n",
       "      <td>53.653294</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sim_Country_21</td>\n",
       "      <td>4.140897</td>\n",
       "      <td>7.895540</td>\n",
       "      <td>0.641978</td>\n",
       "      <td>57.764259</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sim_Country_22</td>\n",
       "      <td>4.498378</td>\n",
       "      <td>6.936735</td>\n",
       "      <td>0.688187</td>\n",
       "      <td>56.443739</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Sim_Country_23</td>\n",
       "      <td>3.957360</td>\n",
       "      <td>6.376612</td>\n",
       "      <td>0.705228</td>\n",
       "      <td>53.182312</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Sim_Country_24</td>\n",
       "      <td>4.966146</td>\n",
       "      <td>7.299382</td>\n",
       "      <td>0.504108</td>\n",
       "      <td>56.757984</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Sim_Country_25</td>\n",
       "      <td>3.866445</td>\n",
       "      <td>7.973869</td>\n",
       "      <td>0.492063</td>\n",
       "      <td>55.794617</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sim_Country_26</td>\n",
       "      <td>4.940841</td>\n",
       "      <td>7.405068</td>\n",
       "      <td>0.630838</td>\n",
       "      <td>60.638536</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Sim_Country_27</td>\n",
       "      <td>4.110597</td>\n",
       "      <td>8.482766</td>\n",
       "      <td>0.597189</td>\n",
       "      <td>55.757277</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Sim_Country_28</td>\n",
       "      <td>4.604313</td>\n",
       "      <td>8.530728</td>\n",
       "      <td>0.628325</td>\n",
       "      <td>55.697414</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Sim_Country_29</td>\n",
       "      <td>4.007946</td>\n",
       "      <td>6.820538</td>\n",
       "      <td>0.541564</td>\n",
       "      <td>52.697467</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sim_Country_30</td>\n",
       "      <td>4.950610</td>\n",
       "      <td>7.712536</td>\n",
       "      <td>0.700499</td>\n",
       "      <td>58.674700</td>\n",
       "      <td>Group0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>6.104646</td>\n",
       "      <td>7.605432</td>\n",
       "      <td>0.766122</td>\n",
       "      <td>65.593067</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>6.730420</td>\n",
       "      <td>7.546884</td>\n",
       "      <td>0.780479</td>\n",
       "      <td>62.433074</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>4.757041</td>\n",
       "      <td>10.021645</td>\n",
       "      <td>0.834583</td>\n",
       "      <td>66.025079</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>6.280318</td>\n",
       "      <td>9.607126</td>\n",
       "      <td>0.805516</td>\n",
       "      <td>60.704252</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sim_Country_4</td>\n",
       "      <td>5.756331</td>\n",
       "      <td>9.173207</td>\n",
       "      <td>0.789374</td>\n",
       "      <td>63.673494</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Sim_Country_5</td>\n",
       "      <td>6.274267</td>\n",
       "      <td>10.044621</td>\n",
       "      <td>0.628170</td>\n",
       "      <td>64.544921</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Sim_Country_6</td>\n",
       "      <td>5.527486</td>\n",
       "      <td>9.419568</td>\n",
       "      <td>0.889325</td>\n",
       "      <td>67.486165</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Sim_Country_7</td>\n",
       "      <td>5.913383</td>\n",
       "      <td>9.459292</td>\n",
       "      <td>0.882779</td>\n",
       "      <td>67.037615</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sim_Country_8</td>\n",
       "      <td>4.614052</td>\n",
       "      <td>8.832165</td>\n",
       "      <td>0.929929</td>\n",
       "      <td>63.964308</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sim_Country_9</td>\n",
       "      <td>4.556527</td>\n",
       "      <td>8.716749</td>\n",
       "      <td>0.575667</td>\n",
       "      <td>68.106314</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sim_Country_10</td>\n",
       "      <td>5.238783</td>\n",
       "      <td>8.276989</td>\n",
       "      <td>0.844645</td>\n",
       "      <td>67.259350</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Sim_Country_11</td>\n",
       "      <td>5.284715</td>\n",
       "      <td>9.947500</td>\n",
       "      <td>0.708318</td>\n",
       "      <td>64.492971</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Sim_Country_12</td>\n",
       "      <td>4.032521</td>\n",
       "      <td>11.603410</td>\n",
       "      <td>0.835945</td>\n",
       "      <td>59.994373</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sim_Country_13</td>\n",
       "      <td>6.100510</td>\n",
       "      <td>9.332144</td>\n",
       "      <td>0.770634</td>\n",
       "      <td>68.538375</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sim_Country_14</td>\n",
       "      <td>5.491264</td>\n",
       "      <td>10.239855</td>\n",
       "      <td>0.505786</td>\n",
       "      <td>64.360299</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Sim_Country_15</td>\n",
       "      <td>4.523367</td>\n",
       "      <td>9.156979</td>\n",
       "      <td>0.937943</td>\n",
       "      <td>64.535614</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Sim_Country_16</td>\n",
       "      <td>6.445705</td>\n",
       "      <td>9.631644</td>\n",
       "      <td>0.704098</td>\n",
       "      <td>62.692963</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sim_Country_17</td>\n",
       "      <td>5.545921</td>\n",
       "      <td>8.414212</td>\n",
       "      <td>0.790268</td>\n",
       "      <td>61.853833</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Sim_Country_18</td>\n",
       "      <td>5.398830</td>\n",
       "      <td>9.462521</td>\n",
       "      <td>0.832630</td>\n",
       "      <td>65.719342</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sim_Country_19</td>\n",
       "      <td>5.529013</td>\n",
       "      <td>9.582633</td>\n",
       "      <td>0.803248</td>\n",
       "      <td>68.756907</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Sim_Country_20</td>\n",
       "      <td>5.153127</td>\n",
       "      <td>9.836633</td>\n",
       "      <td>0.820408</td>\n",
       "      <td>67.880261</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sim_Country_21</td>\n",
       "      <td>5.581732</td>\n",
       "      <td>11.046055</td>\n",
       "      <td>0.665441</td>\n",
       "      <td>66.744153</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sim_Country_22</td>\n",
       "      <td>5.343593</td>\n",
       "      <td>9.478280</td>\n",
       "      <td>0.750343</td>\n",
       "      <td>60.476931</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Sim_Country_23</td>\n",
       "      <td>5.550896</td>\n",
       "      <td>9.283892</td>\n",
       "      <td>0.843230</td>\n",
       "      <td>66.882609</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Sim_Country_24</td>\n",
       "      <td>6.187242</td>\n",
       "      <td>8.232684</td>\n",
       "      <td>0.822070</td>\n",
       "      <td>67.802730</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Sim_Country_25</td>\n",
       "      <td>4.825258</td>\n",
       "      <td>9.685896</td>\n",
       "      <td>1.033914</td>\n",
       "      <td>64.783934</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sim_Country_26</td>\n",
       "      <td>6.441212</td>\n",
       "      <td>8.821607</td>\n",
       "      <td>0.753419</td>\n",
       "      <td>64.973794</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Sim_Country_27</td>\n",
       "      <td>5.820064</td>\n",
       "      <td>9.497145</td>\n",
       "      <td>0.913300</td>\n",
       "      <td>60.766096</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Sim_Country_28</td>\n",
       "      <td>4.717544</td>\n",
       "      <td>8.434034</td>\n",
       "      <td>0.826417</td>\n",
       "      <td>66.435632</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Sim_Country_29</td>\n",
       "      <td>5.319248</td>\n",
       "      <td>9.891236</td>\n",
       "      <td>0.796973</td>\n",
       "      <td>61.889893</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sim_Country_30</td>\n",
       "      <td>5.024835</td>\n",
       "      <td>8.606389</td>\n",
       "      <td>0.908110</td>\n",
       "      <td>63.087346</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Sim_Country_31</td>\n",
       "      <td>5.097651</td>\n",
       "      <td>9.040929</td>\n",
       "      <td>0.893794</td>\n",
       "      <td>61.501589</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Sim_Country_32</td>\n",
       "      <td>4.720469</td>\n",
       "      <td>9.185022</td>\n",
       "      <td>0.922589</td>\n",
       "      <td>71.912801</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Sim_Country_33</td>\n",
       "      <td>4.872955</td>\n",
       "      <td>8.579291</td>\n",
       "      <td>0.657708</td>\n",
       "      <td>70.709151</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Sim_Country_34</td>\n",
       "      <td>4.442912</td>\n",
       "      <td>8.242370</td>\n",
       "      <td>0.734961</td>\n",
       "      <td>66.859590</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Sim_Country_35</td>\n",
       "      <td>4.620600</td>\n",
       "      <td>9.078406</td>\n",
       "      <td>0.916114</td>\n",
       "      <td>67.081704</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Sim_Country_36</td>\n",
       "      <td>4.609395</td>\n",
       "      <td>9.588953</td>\n",
       "      <td>0.846324</td>\n",
       "      <td>59.479723</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Sim_Country_37</td>\n",
       "      <td>6.084480</td>\n",
       "      <td>9.305039</td>\n",
       "      <td>0.847234</td>\n",
       "      <td>70.202946</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Sim_Country_38</td>\n",
       "      <td>4.974988</td>\n",
       "      <td>9.251449</td>\n",
       "      <td>0.918559</td>\n",
       "      <td>66.929811</td>\n",
       "      <td>Group1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sim_Country_0</td>\n",
       "      <td>5.385795</td>\n",
       "      <td>10.655436</td>\n",
       "      <td>0.748666</td>\n",
       "      <td>73.781418</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sim_Country_1</td>\n",
       "      <td>6.358164</td>\n",
       "      <td>10.793122</td>\n",
       "      <td>0.890609</td>\n",
       "      <td>70.576719</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sim_Country_2</td>\n",
       "      <td>8.142938</td>\n",
       "      <td>10.876471</td>\n",
       "      <td>0.875233</td>\n",
       "      <td>71.810983</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sim_Country_3</td>\n",
       "      <td>5.740609</td>\n",
       "      <td>9.993025</td>\n",
       "      <td>0.978514</td>\n",
       "      <td>73.414892</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sim_Country_4</td>\n",
       "      <td>7.096271</td>\n",
       "      <td>9.666603</td>\n",
       "      <td>0.913630</td>\n",
       "      <td>73.184367</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Sim_Country_5</td>\n",
       "      <td>7.311090</td>\n",
       "      <td>10.144854</td>\n",
       "      <td>0.934530</td>\n",
       "      <td>70.500719</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Sim_Country_6</td>\n",
       "      <td>5.495667</td>\n",
       "      <td>10.386107</td>\n",
       "      <td>0.878044</td>\n",
       "      <td>72.278470</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Sim_Country_7</td>\n",
       "      <td>7.036180</td>\n",
       "      <td>11.028117</td>\n",
       "      <td>0.779110</td>\n",
       "      <td>66.785619</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sim_Country_8</td>\n",
       "      <td>6.263355</td>\n",
       "      <td>10.300038</td>\n",
       "      <td>0.852054</td>\n",
       "      <td>69.650947</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sim_Country_9</td>\n",
       "      <td>5.418116</td>\n",
       "      <td>10.033773</td>\n",
       "      <td>0.894144</td>\n",
       "      <td>74.594088</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sim_Country_10</td>\n",
       "      <td>7.428183</td>\n",
       "      <td>10.885637</td>\n",
       "      <td>0.984029</td>\n",
       "      <td>71.320306</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Sim_Country_11</td>\n",
       "      <td>6.305144</td>\n",
       "      <td>9.938123</td>\n",
       "      <td>0.838539</td>\n",
       "      <td>70.716988</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Sim_Country_12</td>\n",
       "      <td>6.032281</td>\n",
       "      <td>11.077448</td>\n",
       "      <td>0.908822</td>\n",
       "      <td>71.742547</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sim_Country_13</td>\n",
       "      <td>6.472369</td>\n",
       "      <td>11.247026</td>\n",
       "      <td>0.987376</td>\n",
       "      <td>73.587537</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sim_Country_14</td>\n",
       "      <td>5.716624</td>\n",
       "      <td>10.566214</td>\n",
       "      <td>0.883228</td>\n",
       "      <td>71.664412</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Sim_Country_15</td>\n",
       "      <td>7.080530</td>\n",
       "      <td>10.805455</td>\n",
       "      <td>0.942796</td>\n",
       "      <td>71.879084</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Sim_Country_16</td>\n",
       "      <td>7.206828</td>\n",
       "      <td>10.550329</td>\n",
       "      <td>0.924847</td>\n",
       "      <td>70.270879</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sim_Country_17</td>\n",
       "      <td>6.351447</td>\n",
       "      <td>10.477653</td>\n",
       "      <td>0.918169</td>\n",
       "      <td>70.933843</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Sim_Country_18</td>\n",
       "      <td>7.060860</td>\n",
       "      <td>10.629714</td>\n",
       "      <td>0.848884</td>\n",
       "      <td>70.471617</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sim_Country_19</td>\n",
       "      <td>7.064228</td>\n",
       "      <td>10.112762</td>\n",
       "      <td>0.848102</td>\n",
       "      <td>69.678281</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Sim_Country_20</td>\n",
       "      <td>6.408565</td>\n",
       "      <td>10.732158</td>\n",
       "      <td>0.900605</td>\n",
       "      <td>71.790901</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sim_Country_21</td>\n",
       "      <td>6.289552</td>\n",
       "      <td>10.477686</td>\n",
       "      <td>0.904666</td>\n",
       "      <td>71.132421</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sim_Country_22</td>\n",
       "      <td>5.357937</td>\n",
       "      <td>10.313633</td>\n",
       "      <td>0.887228</td>\n",
       "      <td>68.773793</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Sim_Country_23</td>\n",
       "      <td>6.450912</td>\n",
       "      <td>10.852811</td>\n",
       "      <td>0.832739</td>\n",
       "      <td>73.315052</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Sim_Country_24</td>\n",
       "      <td>6.464413</td>\n",
       "      <td>11.400024</td>\n",
       "      <td>0.950097</td>\n",
       "      <td>72.384161</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Sim_Country_25</td>\n",
       "      <td>7.856610</td>\n",
       "      <td>11.041495</td>\n",
       "      <td>0.845997</td>\n",
       "      <td>75.534256</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Sim_Country_26</td>\n",
       "      <td>7.804383</td>\n",
       "      <td>10.517030</td>\n",
       "      <td>0.823343</td>\n",
       "      <td>74.806099</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Sim_Country_27</td>\n",
       "      <td>6.434984</td>\n",
       "      <td>10.730994</td>\n",
       "      <td>0.825368</td>\n",
       "      <td>72.237413</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Sim_Country_28</td>\n",
       "      <td>7.003235</td>\n",
       "      <td>10.110517</td>\n",
       "      <td>0.829412</td>\n",
       "      <td>71.388692</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Sim_Country_29</td>\n",
       "      <td>6.741389</td>\n",
       "      <td>10.311341</td>\n",
       "      <td>0.885497</td>\n",
       "      <td>69.948491</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sim_Country_30</td>\n",
       "      <td>6.777978</td>\n",
       "      <td>10.445278</td>\n",
       "      <td>0.849097</td>\n",
       "      <td>71.427516</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Sim_Country_31</td>\n",
       "      <td>5.809379</td>\n",
       "      <td>10.486830</td>\n",
       "      <td>0.968003</td>\n",
       "      <td>72.228996</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Sim_Country_32</td>\n",
       "      <td>7.160268</td>\n",
       "      <td>10.325579</td>\n",
       "      <td>0.933449</td>\n",
       "      <td>73.405233</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Sim_Country_33</td>\n",
       "      <td>6.516064</td>\n",
       "      <td>10.359375</td>\n",
       "      <td>1.001420</td>\n",
       "      <td>71.067603</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Sim_Country_34</td>\n",
       "      <td>5.869133</td>\n",
       "      <td>10.458408</td>\n",
       "      <td>0.921777</td>\n",
       "      <td>69.915442</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Sim_Country_35</td>\n",
       "      <td>7.134501</td>\n",
       "      <td>9.815683</td>\n",
       "      <td>0.909203</td>\n",
       "      <td>73.798394</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Sim_Country_36</td>\n",
       "      <td>6.231583</td>\n",
       "      <td>10.760661</td>\n",
       "      <td>0.878525</td>\n",
       "      <td>73.360915</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Sim_Country_37</td>\n",
       "      <td>6.242516</td>\n",
       "      <td>10.547722</td>\n",
       "      <td>0.886741</td>\n",
       "      <td>72.421965</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Sim_Country_38</td>\n",
       "      <td>6.485313</td>\n",
       "      <td>11.124590</td>\n",
       "      <td>0.865801</td>\n",
       "      <td>74.167433</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Sim_Country_39</td>\n",
       "      <td>5.592858</td>\n",
       "      <td>9.964702</td>\n",
       "      <td>0.905046</td>\n",
       "      <td>72.623291</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Sim_Country_40</td>\n",
       "      <td>6.207162</td>\n",
       "      <td>9.957856</td>\n",
       "      <td>0.899553</td>\n",
       "      <td>69.450971</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Sim_Country_41</td>\n",
       "      <td>7.171160</td>\n",
       "      <td>11.108812</td>\n",
       "      <td>0.790887</td>\n",
       "      <td>73.516170</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Sim_Country_42</td>\n",
       "      <td>7.435241</td>\n",
       "      <td>11.305930</td>\n",
       "      <td>0.753479</td>\n",
       "      <td>72.497571</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Sim_Country_43</td>\n",
       "      <td>6.905585</td>\n",
       "      <td>10.615498</td>\n",
       "      <td>0.950932</td>\n",
       "      <td>75.445552</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Sim_Country_44</td>\n",
       "      <td>7.071821</td>\n",
       "      <td>10.147285</td>\n",
       "      <td>0.892022</td>\n",
       "      <td>71.275062</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Sim_Country_45</td>\n",
       "      <td>6.857933</td>\n",
       "      <td>10.142169</td>\n",
       "      <td>0.900854</td>\n",
       "      <td>68.482111</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Sim_Country_46</td>\n",
       "      <td>7.789755</td>\n",
       "      <td>10.095109</td>\n",
       "      <td>0.909472</td>\n",
       "      <td>71.210309</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Sim_Country_47</td>\n",
       "      <td>7.469692</td>\n",
       "      <td>11.065426</td>\n",
       "      <td>0.860713</td>\n",
       "      <td>71.189024</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Sim_Country_48</td>\n",
       "      <td>7.051640</td>\n",
       "      <td>9.813195</td>\n",
       "      <td>0.920164</td>\n",
       "      <td>69.344251</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Sim_Country_49</td>\n",
       "      <td>6.398131</td>\n",
       "      <td>10.641334</td>\n",
       "      <td>0.861340</td>\n",
       "      <td>71.517016</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Sim_Country_50</td>\n",
       "      <td>5.619556</td>\n",
       "      <td>10.272818</td>\n",
       "      <td>0.923834</td>\n",
       "      <td>68.393623</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Sim_Country_51</td>\n",
       "      <td>6.744205</td>\n",
       "      <td>10.356544</td>\n",
       "      <td>0.836665</td>\n",
       "      <td>72.487978</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Sim_Country_52</td>\n",
       "      <td>6.451683</td>\n",
       "      <td>10.954437</td>\n",
       "      <td>0.867026</td>\n",
       "      <td>71.133910</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Sim_Country_53</td>\n",
       "      <td>7.136838</td>\n",
       "      <td>10.620231</td>\n",
       "      <td>0.851049</td>\n",
       "      <td>72.649691</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Sim_Country_54</td>\n",
       "      <td>6.090275</td>\n",
       "      <td>10.501391</td>\n",
       "      <td>0.973984</td>\n",
       "      <td>73.793844</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Sim_Country_55</td>\n",
       "      <td>6.454728</td>\n",
       "      <td>10.038287</td>\n",
       "      <td>0.923564</td>\n",
       "      <td>69.123699</td>\n",
       "      <td>Group2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country  Life_Satisfaction  Log_GDP_per_cap  Social_Support  \\\n",
       "0    Sim_Country_0           4.832239         7.954537        0.576985   \n",
       "1    Sim_Country_1           4.467750         8.305551        0.768666   \n",
       "2    Sim_Country_2           5.438583         7.713437        0.491684   \n",
       "3    Sim_Country_3           4.020669         7.984861        0.699109   \n",
       "4    Sim_Country_4           5.160103         6.428954        0.570764   \n",
       "5    Sim_Country_5           4.242171         7.809745        0.647433   \n",
       "6    Sim_Country_6           5.022303         8.346845        0.752324   \n",
       "7    Sim_Country_7           2.923470         8.415365        0.752652   \n",
       "8    Sim_Country_8           4.556024         7.802063        0.764483   \n",
       "9    Sim_Country_9           4.109705         9.005313        0.538347   \n",
       "10  Sim_Country_10           4.581402         7.729789        0.569938   \n",
       "11  Sim_Country_11           4.585434         7.157559        0.714820   \n",
       "12  Sim_Country_12           5.037641         6.686651        0.575100   \n",
       "13  Sim_Country_13           4.621235         7.329555        0.566648   \n",
       "14  Sim_Country_14           5.002786         8.761313        0.424965   \n",
       "15  Sim_Country_15           3.975284         9.081068        0.692273   \n",
       "16  Sim_Country_16           3.417133         6.930615        0.537136   \n",
       "17  Sim_Country_17           4.934614         8.031422        0.579652   \n",
       "18  Sim_Country_18           4.210346         7.192087        0.584974   \n",
       "19  Sim_Country_19           5.006668         8.508099        0.743774   \n",
       "20  Sim_Country_20           2.909746         7.174338        0.672582   \n",
       "21  Sim_Country_21           4.140897         7.895540        0.641978   \n",
       "22  Sim_Country_22           4.498378         6.936735        0.688187   \n",
       "23  Sim_Country_23           3.957360         6.376612        0.705228   \n",
       "24  Sim_Country_24           4.966146         7.299382        0.504108   \n",
       "25  Sim_Country_25           3.866445         7.973869        0.492063   \n",
       "26  Sim_Country_26           4.940841         7.405068        0.630838   \n",
       "27  Sim_Country_27           4.110597         8.482766        0.597189   \n",
       "28  Sim_Country_28           4.604313         8.530728        0.628325   \n",
       "29  Sim_Country_29           4.007946         6.820538        0.541564   \n",
       "30  Sim_Country_30           4.950610         7.712536        0.700499   \n",
       "0    Sim_Country_0           6.104646         7.605432        0.766122   \n",
       "1    Sim_Country_1           6.730420         7.546884        0.780479   \n",
       "2    Sim_Country_2           4.757041        10.021645        0.834583   \n",
       "3    Sim_Country_3           6.280318         9.607126        0.805516   \n",
       "4    Sim_Country_4           5.756331         9.173207        0.789374   \n",
       "5    Sim_Country_5           6.274267        10.044621        0.628170   \n",
       "6    Sim_Country_6           5.527486         9.419568        0.889325   \n",
       "7    Sim_Country_7           5.913383         9.459292        0.882779   \n",
       "8    Sim_Country_8           4.614052         8.832165        0.929929   \n",
       "9    Sim_Country_9           4.556527         8.716749        0.575667   \n",
       "10  Sim_Country_10           5.238783         8.276989        0.844645   \n",
       "11  Sim_Country_11           5.284715         9.947500        0.708318   \n",
       "12  Sim_Country_12           4.032521        11.603410        0.835945   \n",
       "13  Sim_Country_13           6.100510         9.332144        0.770634   \n",
       "14  Sim_Country_14           5.491264        10.239855        0.505786   \n",
       "15  Sim_Country_15           4.523367         9.156979        0.937943   \n",
       "16  Sim_Country_16           6.445705         9.631644        0.704098   \n",
       "17  Sim_Country_17           5.545921         8.414212        0.790268   \n",
       "18  Sim_Country_18           5.398830         9.462521        0.832630   \n",
       "19  Sim_Country_19           5.529013         9.582633        0.803248   \n",
       "20  Sim_Country_20           5.153127         9.836633        0.820408   \n",
       "21  Sim_Country_21           5.581732        11.046055        0.665441   \n",
       "22  Sim_Country_22           5.343593         9.478280        0.750343   \n",
       "23  Sim_Country_23           5.550896         9.283892        0.843230   \n",
       "24  Sim_Country_24           6.187242         8.232684        0.822070   \n",
       "25  Sim_Country_25           4.825258         9.685896        1.033914   \n",
       "26  Sim_Country_26           6.441212         8.821607        0.753419   \n",
       "27  Sim_Country_27           5.820064         9.497145        0.913300   \n",
       "28  Sim_Country_28           4.717544         8.434034        0.826417   \n",
       "29  Sim_Country_29           5.319248         9.891236        0.796973   \n",
       "30  Sim_Country_30           5.024835         8.606389        0.908110   \n",
       "31  Sim_Country_31           5.097651         9.040929        0.893794   \n",
       "32  Sim_Country_32           4.720469         9.185022        0.922589   \n",
       "33  Sim_Country_33           4.872955         8.579291        0.657708   \n",
       "34  Sim_Country_34           4.442912         8.242370        0.734961   \n",
       "35  Sim_Country_35           4.620600         9.078406        0.916114   \n",
       "36  Sim_Country_36           4.609395         9.588953        0.846324   \n",
       "37  Sim_Country_37           6.084480         9.305039        0.847234   \n",
       "38  Sim_Country_38           4.974988         9.251449        0.918559   \n",
       "0    Sim_Country_0           5.385795        10.655436        0.748666   \n",
       "1    Sim_Country_1           6.358164        10.793122        0.890609   \n",
       "2    Sim_Country_2           8.142938        10.876471        0.875233   \n",
       "3    Sim_Country_3           5.740609         9.993025        0.978514   \n",
       "4    Sim_Country_4           7.096271         9.666603        0.913630   \n",
       "5    Sim_Country_5           7.311090        10.144854        0.934530   \n",
       "6    Sim_Country_6           5.495667        10.386107        0.878044   \n",
       "7    Sim_Country_7           7.036180        11.028117        0.779110   \n",
       "8    Sim_Country_8           6.263355        10.300038        0.852054   \n",
       "9    Sim_Country_9           5.418116        10.033773        0.894144   \n",
       "10  Sim_Country_10           7.428183        10.885637        0.984029   \n",
       "11  Sim_Country_11           6.305144         9.938123        0.838539   \n",
       "12  Sim_Country_12           6.032281        11.077448        0.908822   \n",
       "13  Sim_Country_13           6.472369        11.247026        0.987376   \n",
       "14  Sim_Country_14           5.716624        10.566214        0.883228   \n",
       "15  Sim_Country_15           7.080530        10.805455        0.942796   \n",
       "16  Sim_Country_16           7.206828        10.550329        0.924847   \n",
       "17  Sim_Country_17           6.351447        10.477653        0.918169   \n",
       "18  Sim_Country_18           7.060860        10.629714        0.848884   \n",
       "19  Sim_Country_19           7.064228        10.112762        0.848102   \n",
       "20  Sim_Country_20           6.408565        10.732158        0.900605   \n",
       "21  Sim_Country_21           6.289552        10.477686        0.904666   \n",
       "22  Sim_Country_22           5.357937        10.313633        0.887228   \n",
       "23  Sim_Country_23           6.450912        10.852811        0.832739   \n",
       "24  Sim_Country_24           6.464413        11.400024        0.950097   \n",
       "25  Sim_Country_25           7.856610        11.041495        0.845997   \n",
       "26  Sim_Country_26           7.804383        10.517030        0.823343   \n",
       "27  Sim_Country_27           6.434984        10.730994        0.825368   \n",
       "28  Sim_Country_28           7.003235        10.110517        0.829412   \n",
       "29  Sim_Country_29           6.741389        10.311341        0.885497   \n",
       "30  Sim_Country_30           6.777978        10.445278        0.849097   \n",
       "31  Sim_Country_31           5.809379        10.486830        0.968003   \n",
       "32  Sim_Country_32           7.160268        10.325579        0.933449   \n",
       "33  Sim_Country_33           6.516064        10.359375        1.001420   \n",
       "34  Sim_Country_34           5.869133        10.458408        0.921777   \n",
       "35  Sim_Country_35           7.134501         9.815683        0.909203   \n",
       "36  Sim_Country_36           6.231583        10.760661        0.878525   \n",
       "37  Sim_Country_37           6.242516        10.547722        0.886741   \n",
       "38  Sim_Country_38           6.485313        11.124590        0.865801   \n",
       "39  Sim_Country_39           5.592858         9.964702        0.905046   \n",
       "40  Sim_Country_40           6.207162         9.957856        0.899553   \n",
       "41  Sim_Country_41           7.171160        11.108812        0.790887   \n",
       "42  Sim_Country_42           7.435241        11.305930        0.753479   \n",
       "43  Sim_Country_43           6.905585        10.615498        0.950932   \n",
       "44  Sim_Country_44           7.071821        10.147285        0.892022   \n",
       "45  Sim_Country_45           6.857933        10.142169        0.900854   \n",
       "46  Sim_Country_46           7.789755        10.095109        0.909472   \n",
       "47  Sim_Country_47           7.469692        11.065426        0.860713   \n",
       "48  Sim_Country_48           7.051640         9.813195        0.920164   \n",
       "49  Sim_Country_49           6.398131        10.641334        0.861340   \n",
       "50  Sim_Country_50           5.619556        10.272818        0.923834   \n",
       "51  Sim_Country_51           6.744205        10.356544        0.836665   \n",
       "52  Sim_Country_52           6.451683        10.954437        0.867026   \n",
       "53  Sim_Country_53           7.136838        10.620231        0.851049   \n",
       "54  Sim_Country_54           6.090275        10.501391        0.973984   \n",
       "55  Sim_Country_55           6.454728        10.038287        0.923564   \n",
       "\n",
       "    Life_Expectancy   Group  \n",
       "0         54.335308  Group0  \n",
       "1         54.181906  Group0  \n",
       "2         53.581250  Group0  \n",
       "3         56.451956  Group0  \n",
       "4         56.635865  Group0  \n",
       "5         55.029355  Group0  \n",
       "6         53.277792  Group0  \n",
       "7         56.461650  Group0  \n",
       "8         54.363260  Group0  \n",
       "9         53.842117  Group0  \n",
       "10        55.301478  Group0  \n",
       "11        57.871060  Group0  \n",
       "12        59.463959  Group0  \n",
       "13        58.132118  Group0  \n",
       "14        54.969960  Group0  \n",
       "15        52.951953  Group0  \n",
       "16        49.272071  Group0  \n",
       "17        55.766907  Group0  \n",
       "18        54.040780  Group0  \n",
       "19        50.065262  Group0  \n",
       "20        53.653294  Group0  \n",
       "21        57.764259  Group0  \n",
       "22        56.443739  Group0  \n",
       "23        53.182312  Group0  \n",
       "24        56.757984  Group0  \n",
       "25        55.794617  Group0  \n",
       "26        60.638536  Group0  \n",
       "27        55.757277  Group0  \n",
       "28        55.697414  Group0  \n",
       "29        52.697467  Group0  \n",
       "30        58.674700  Group0  \n",
       "0         65.593067  Group1  \n",
       "1         62.433074  Group1  \n",
       "2         66.025079  Group1  \n",
       "3         60.704252  Group1  \n",
       "4         63.673494  Group1  \n",
       "5         64.544921  Group1  \n",
       "6         67.486165  Group1  \n",
       "7         67.037615  Group1  \n",
       "8         63.964308  Group1  \n",
       "9         68.106314  Group1  \n",
       "10        67.259350  Group1  \n",
       "11        64.492971  Group1  \n",
       "12        59.994373  Group1  \n",
       "13        68.538375  Group1  \n",
       "14        64.360299  Group1  \n",
       "15        64.535614  Group1  \n",
       "16        62.692963  Group1  \n",
       "17        61.853833  Group1  \n",
       "18        65.719342  Group1  \n",
       "19        68.756907  Group1  \n",
       "20        67.880261  Group1  \n",
       "21        66.744153  Group1  \n",
       "22        60.476931  Group1  \n",
       "23        66.882609  Group1  \n",
       "24        67.802730  Group1  \n",
       "25        64.783934  Group1  \n",
       "26        64.973794  Group1  \n",
       "27        60.766096  Group1  \n",
       "28        66.435632  Group1  \n",
       "29        61.889893  Group1  \n",
       "30        63.087346  Group1  \n",
       "31        61.501589  Group1  \n",
       "32        71.912801  Group1  \n",
       "33        70.709151  Group1  \n",
       "34        66.859590  Group1  \n",
       "35        67.081704  Group1  \n",
       "36        59.479723  Group1  \n",
       "37        70.202946  Group1  \n",
       "38        66.929811  Group1  \n",
       "0         73.781418  Group2  \n",
       "1         70.576719  Group2  \n",
       "2         71.810983  Group2  \n",
       "3         73.414892  Group2  \n",
       "4         73.184367  Group2  \n",
       "5         70.500719  Group2  \n",
       "6         72.278470  Group2  \n",
       "7         66.785619  Group2  \n",
       "8         69.650947  Group2  \n",
       "9         74.594088  Group2  \n",
       "10        71.320306  Group2  \n",
       "11        70.716988  Group2  \n",
       "12        71.742547  Group2  \n",
       "13        73.587537  Group2  \n",
       "14        71.664412  Group2  \n",
       "15        71.879084  Group2  \n",
       "16        70.270879  Group2  \n",
       "17        70.933843  Group2  \n",
       "18        70.471617  Group2  \n",
       "19        69.678281  Group2  \n",
       "20        71.790901  Group2  \n",
       "21        71.132421  Group2  \n",
       "22        68.773793  Group2  \n",
       "23        73.315052  Group2  \n",
       "24        72.384161  Group2  \n",
       "25        75.534256  Group2  \n",
       "26        74.806099  Group2  \n",
       "27        72.237413  Group2  \n",
       "28        71.388692  Group2  \n",
       "29        69.948491  Group2  \n",
       "30        71.427516  Group2  \n",
       "31        72.228996  Group2  \n",
       "32        73.405233  Group2  \n",
       "33        71.067603  Group2  \n",
       "34        69.915442  Group2  \n",
       "35        73.798394  Group2  \n",
       "36        73.360915  Group2  \n",
       "37        72.421965  Group2  \n",
       "38        74.167433  Group2  \n",
       "39        72.623291  Group2  \n",
       "40        69.450971  Group2  \n",
       "41        73.516170  Group2  \n",
       "42        72.497571  Group2  \n",
       "43        75.445552  Group2  \n",
       "44        71.275062  Group2  \n",
       "45        68.482111  Group2  \n",
       "46        71.210309  Group2  \n",
       "47        71.189024  Group2  \n",
       "48        69.344251  Group2  \n",
       "49        71.517016  Group2  \n",
       "50        68.393623  Group2  \n",
       "51        72.487978  Group2  \n",
       "52        71.133910  Group2  \n",
       "53        72.649691  Group2  \n",
       "54        73.793844  Group2  \n",
       "55        69.123699  Group2  "
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# change the max numbers of rows to display the simulated dataset.\n",
    "pd.options.display.max_rows=130\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"references\"></a>\n",
    "# 5. References\n",
    "\n",
    "- [1] Programming for Data Analytis Project Instructions. \n",
    "\n",
    "\n",
    "- [2] [Website: Python.org](https://www.python.org/)\n",
    "      https://www.python.org/\n",
    "\n",
    "\n",
    "- [3] [Website: Official Seaborn Tutorial](https://seaborn.pydata.org/tutorial.html)  \n",
    "      https://seaborn.pydata.org/tutorial.html\n",
    "   \n",
    "   \n",
    "- [4] [Website: 10 minutes to pandas](https://pandas.pydata.org/pandas-docs/version/0.23.4/10min.html)\n",
    "      https://pandas.pydata.org\n",
    "    \n",
    "    \n",
    "- [5] [Website: Numpy.random](https://docs.scipy.org/doc/numpy-1.16.0/reference/routines.random.html)\n",
    "      https://docs.scipy.org/doc/numpy-1.16.0/reference/routines.random.html      \n",
    "      \n",
    "\n",
    "- [6] Crump, M. J. C., Navarro, D., & Suzuki, J. (2019, June 5). Answering Questions with Data (Textbook): Introductory Statistics for Psychology Students. https://doi.org/10.17605/OSF.IO/JZE52 Online Textbook: https://crumplab.github.io/statistics/\n",
    "\n",
    "\n",
    "- [7] John F. Helliwell, Haifang Huang and Shun Wang. The Distribution of World Happiness  \n",
    "   [The Distribution of World Happiness](https://s3.amazonaws.com/happiness-report/2016/HR-V1Ch2_web.pdf)\n",
    "\n",
    "- [8] [The World Happiness Report](https://worldhappiness.report/ed/2019/)  \n",
    "     - website: https://worldhappiness.report\n",
    "     - [2019 Chapter2 Online Data](https://s3.amazonaws.com/happiness-report/2019/Chapter2OnlineData.xls)  \n",
    "     - [2019 Chapter2 Appendix1](https://s3.amazonaws.com/happiness-report/2019/WHR19_Ch2A_Appendix1.pdf)  \n",
    "\n",
    "- [9] [Website: www.Kaggle.com](https://www.kaggle.com/)\n",
    "\n",
    "- [10] John F. Helliwell, Haifang Huang and Shun Wang [Statistical Appendix 1 for Chapter 2 of World Happiness Report 2019](https://s3.amazonaws.com/happiness-report/2016/HR-V1Ch2_web.pdf)\n",
    "\n",
    "- [11] [Website: The Balance](https://www.thebalance.com/gdp-per-capita-formula-u-s-compared-to-highest-and-lowest-3305848)\n",
    "\n",
    "\n",
    "- [12] [Online Lecture: Introduction to Economic Growth Lecture MIT](https://economics.mit.edu/files/1489)\n",
    "         <https://economics.mit.edu>\n",
    "         \n",
    "\n",
    "- [13] [Sustainable Development Econometrics Lecture](http://www.columbia.edu/~so33/SusDev/Lecture_1.pdf)\n",
    "        Prof. Sharyn O’Halloran. Lecture 1: Data and Models.\n",
    "        http://www.columbia.edu     \n",
    "        \n",
    "\n",
    "- [14] [Eurostat](https://ec.europa.eu/eurostat/web/products-datasets/-/tps00150).\n",
    "        https://ec.europa.eu/eurostat\n",
    "        \n",
    "        \n",
    "- [15] [Website: www.who.int](https://www.who.int/gho/mortality_burden_disease/life_tables/hale_text/en/).\n",
    "        www.who.int\n",
    "        \n",
    "\n",
    "- [16] [Join and Merge Pandas Dataframe](https://chrisalbon.com/python/data_wrangling/pandas_join_merge_dataframe/)\n",
    "        https://chrisalbon.com \n",
    "         \n",
    "\n",
    "- [17a] [Stackoverflow: Pandas: Return only rows with missing values](https://stackoverflow.com/a/30447205)  \n",
    "- [17b] [Stackoverflow: Generate correlated data](https://stackoverflow.com/a/16026231)\n",
    "       \n",
    "\n",
    "- [18] [Wikipedia.org: Kernel Density Estimation](https://en.wikipedia.org)  \n",
    "        https://en.wikipedia.org\n",
    "    \n",
    "\n",
    "- [19] [Website: pythonprogramming.net](https://pythonprogramming.net)\n",
    "    -[Unsupervised machine learning - flat clustering](https://pythonprogramming.net/flat-clustering-machine-learning-python-scikit-learn/)\n",
    "\n",
    "\n",
    "- [20] [Website: Drawing from data](https://www.drawingfromdata.com/how-to-rotate-axis-labels-in-seaborn-and-matplotlib)\n",
    "    - [how to rotate axis labels in Seaborn and matplotlib](https://www.drawingfromdata.com/how-to-rotate-axis-labels-in-seaborn-and-matplotlib)  \n",
    "    \n",
    "\n",
    "-  [21] [Website: Machine Learning Mastery](https://machinelearningmastery.com)    \n",
    "     -[Statistical Hypothesis Tests in Python](https://machinelearningmastery.com/statistical-hypothesis-tests-in-python-cheat-sheet/)   \n",
    "     -[Normality Tests in Python]( https://machinelearningmastery.com/a-gentle-introduction-to-normality-tests-in-python/)  \n",
    " \n",
    " \n",
    "-  [22] [Wikipedia: Kolmogorov–Smirnov_test](https://en.wikipedia.org/wiki/Kolmogorov–Smirnov_test)\n",
    " \n",
    "  \n",
    "-  [23] [Machinelearningmastery: A Gentle introduction to the bootstrap method](https://machinelearningmastery.com/a-gentle-introduction-to-the-bootstrap-method/)\n",
    "\n",
    "    \n",
    "-  [24] [Website: Official sklearn tutorial](http://scikit-learn.org/stable/tutorial/basic/tutorial.html)\n",
    "\n",
    "    -[scikit-learn tutorial](http://scikit-learn.org/stable/tutorial/basic/tutorial.html)  \n",
    "    -[sklearn.utils.resample](http://scikit-learn.org/stable/modules/generated/sklearn.utils.resample.html)   \n",
    "    \n",
    "\n",
    "-  [25] [Wikipedia: Bootstrapping (statistics)](https://en.wikipedia.org/wiki/Bootstrapping_(statistics))\n",
    "\n",
    "\n",
    "-  [26] [towardsdatascience: Introduction to the bootstrap resample method](https://towardsdatascience.com/an-introduction-to-the-bootstrap-method-58bcb51b4d60)  \n",
    "   https://towardsdatascience.com\n",
    "      \n",
    "\n",
    "- [27] [Website:investopedia.com]\n",
    "    - [Per Capita GDP](https://www.investopedia.com/terms/p/per-capita-gdp.asp)\n",
    "\n",
    "\n",
    "-  [28] Crump, Matthew J. C. (2017). Programming for Psychologists: Data Creation and Analysis (Version 1.1). https://crumplab.github.io/programmingforpsych/\n",
    "\n",
    "-  [29] Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. An Introduction to Statistical Learning. \n",
    "    [Online pdf corrected 7th edition](http://faculty.marshall.usc.edu/gareth-james/ISL/ISLR%20Seventh%20Printing.pdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### End"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}