{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# How Can Poland Increase its Sustainable Development?\n", "\n", "This project analyzes Poland's progress toward the UN's Sustainable Development Goals (SDGs). These 17 goals are the standards that countries have agreed to reach by the year 2030. As a resident of Poland and an environmentalist, I am interested in figuring out what the SDGs suggest are areas where Poland can and needs to improve - and whether these agree with my existing knowledge and opinions.\n", "\n", "The 17 SDGs are:\n", "\n", "1. No Poverty\n", "1. Zero Hunger\n", "1. Good Health and Well-Being\n", "1. Quality Education\n", "1. Gender Equality\n", "1. Clean Water and Sanitation\n", "1. Affordable and Clean Energy\n", "1. Decent Work and Economic Growth\n", "1. Industry, Innovation and Infrastructure\n", "1. Reduced Inequalities\n", "1. Sustainable Cities and Communities\n", "1. Responsible Consumption and Production\n", "1. Climate Action\n", "1. Life Below Water\n", "1. Life on Land\n", "1. Peace, Justice and Strong Institutions\n", "1. Partnerships for the Goals\n", "\n", "The data set used has been collected by the Sustainable Development Solutions Network and Institute for European Environmental Policy for their publication *The 2020 Europe Sustainable Development Report: Meeting the Sustainable Development Goals in the face of the COVID-19 pandemic* (SDSN and IEEP, Paris and Brussels, 2020). Here are the [full data](https://github.com/sdsna/ESDR2020) and [source website](https://sdgindex.org/reports/europe-sustainable-development-report-2020/).\n", "\n", "The data cover 27 EU countries as well as 4 European Free Trade Association countries (Iceland, Liechtenstein, Norway, Switzerland), the UK and the combined EU. There are 17 Sustainable Development Goals, each comprising several sub-indicators that are measured numerically. The SDSN normalized and averaged these sub-indicator scores to create an overall score for every SDG for each country.\n", "\n", "For this analysis, we created two csv files from the [SDSN Online Database Excel file](https://github.com/sdsna/ESDR2020/blob/main/ESDR2020%20Online%20Database.xlsx) : \n", "\n", "- 'SDG_Full_Database.csv': This contains the most current data on goals and sub-indicators for all countries\n", "- 'SDG_Europe_data.csv': This contains data on historical trends in sub-indicators, where available\n", "\n", "Both files are housed in the github directory for this project.\n", "\n", "## Summary of Results\n", "\n", "By analyzing the goals and sub-indicators, we arrive at the following priority areas for Poland in order to increase its performance relative to the EU average:\n", "\n", "- Innovation & Industry: Increasing patents & building digital skills\n", "- Gender Equality: Increasing the number of women in leadership\n", "- Clean Energy: Increasing renewable energy & decreasing carbon emissions\n", "- Sustainable Cities: Decreasing air pollution\n", "\n", "In this report we present the data supporting these priorities and discuss their scope and limitations.\n", "\n", "We begin by reading in and cleaning the first data set." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Cleaning the Data\n", "\n", "We read in the data, verify its format, check which countries are represented, and analyze null values." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "sdg_current = pd.read_csv('SDG_Full_Database.csv', sep = ';', decimal = ',')" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Size: (39, 503)\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Countryid2020 EU SDG Index Score (0-100)2020 EU SDG Index RankPercentage Missing ValuesSub-regionSpillover ScoreLNOB Score2020 PopulationGoal 1 Dashboard...Goal 8 ScoreGoal 9 ScoreGoal 10 ScoreGoal 11 ScoreGoal 12 ScoreGoal 13 ScoreGoal 14 ScoreGoal 15 ScoreGoal 16 ScoreGoal 17 Score
0FinlandFIN81.101.01.75Northern Europe66.7386.695540718.0green...90.31891.26294.94685.65560.95154.69888.23180.46890.68970.168
1SwedenSWE81.022.02.63Northern Europe72.7882.4710099270.0yellow...86.97995.47889.29182.17052.49963.39668.32974.46584.21290.756
\n", "

2 rows × 503 columns

\n", "
" ], "text/plain": [ " Country id 2020 EU SDG Index Score (0-100) 2020 EU SDG Index Rank \\\n", "0 Finland FIN 81.10 1.0 \n", "1 Sweden SWE 81.02 2.0 \n", "\n", " Percentage Missing Values Sub-region Spillover Score LNOB Score \\\n", "0 1.75 Northern Europe 66.73 86.69 \n", "1 2.63 Northern Europe 72.78 82.47 \n", "\n", " 2020 Population Goal 1 Dashboard ... Goal 8 Score Goal 9 Score \\\n", "0 5540718.0 green ... 90.318 91.262 \n", "1 10099270.0 yellow ... 86.979 95.478 \n", "\n", " Goal 10 Score Goal 11 Score Goal 12 Score Goal 13 Score Goal 14 Score \\\n", "0 94.946 85.655 60.951 54.698 88.231 \n", "1 89.291 82.170 52.499 63.396 68.329 \n", "\n", " Goal 15 Score Goal 16 Score Goal 17 Score \n", "0 80.468 90.689 70.168 \n", "1 74.465 84.212 90.756 \n", "\n", "[2 rows x 503 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Checking data/columns\n", "print('Size:', sdg_current.shape)\n", "sdg_current.head(2)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "0 Finland\n", "1 Sweden\n", "2 Denmark\n", "3 Austria\n", "4 Norway\n", "5 Germany\n", "6 Slovenia\n", "7 Switzerland\n", "8 France\n", "9 Czech Republic\n", "10 Iceland\n", "11 Estonia\n", "12 Belgium\n", "13 Netherlands\n", "14 United Kingdom\n", "15 Poland\n", "16 Slovak Republic\n", "17 Ireland\n", "18 Hungary\n", "19 Latvia\n", "20 Spain\n", "21 Portugal\n", "22 Italy\n", "23 Croatia\n", "24 Lithuania\n", "25 Luxembourg\n", "26 Malta\n", "27 Greece\n", "28 Cyprus\n", "29 Romania\n", "30 Bulgaria\n", "31 Liechtenstein\n", "32 European Union\n", "33 Baltic States\n", "34 Central and Eastern Europe\n", "35 EFTA Countries\n", "36 Northern Europe\n", "37 Southern Europe\n", "38 Western Europe\n", "Name: Country, dtype: object" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#List of countries/regions\n", "sdg_current['Country']" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total null values: 2160\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#Checking null values\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "import seaborn as sns\n", "\n", "print('Total null values:' , sdg_current.isnull().sum().sum())\n", "\n", "fig = plt.figure(figsize =(16,4))\n", "sns.heatmap(sdg_current.notnull()).set(xticklabels = [])\n", "plt.title('Null Values in Black')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It seems most of the null values are in the last rows (the region rows), as well as country #31 (Liechtenstein). We will fill the region rows further below. For Liechtenstein, we verify that most entires are null, and then since it is a tiny country with little data we drop it from the analysis.\n", "\n", "There are also a few columns at the end with many null values, which we see below are related to goals 14-16. Hence, we'll need to be aware of this when working with those goals." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total null values in countries: 1248\n", "Total null values in Liechtenstein: 369\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "print('Total null values in countries:' , sdg_current[0:32].isnull().sum().sum())\n", "print('Total null values in Liechtenstein:', sdg_current.iloc[31].isnull().sum().sum())\n", "\n", "fig = plt.figure(figsize =(16,4))\n", "sns.heatmap(sdg_current.iloc[:, 385:475].notnull().transpose())\n", "plt.title('Null Values in Goals 14-16')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "#dropping Liechtenstein\n", "sdg_current.drop(31, inplace = True)\n", "\n", "sdg_current.reset_index(inplace = True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Verifying Score Calculation\n", "Next we'll verify that the normalized scores agree with the process described in the SDSN report. Namely, sub-indicators are normalized to a 0-100 scale and then averaged to create an overall 0-100 score for each SDG. The SDSN Excel file provides full documentation on how the minimum and maximum of each sub-indicator have been chosen.\n", "\n", "We will verify for SDG 1: No Poverty, which has 3 sub-indicators shown below." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
People at risk of income poverty after social transfers (%)Normalized Score sdg1_transfercol_sdg1_transferTrend sdg1_transferSeverely materially deprived people (%)Normalized Score sdg1_materialcol_sdg1_materialTrend sdg1_materialPoverty headcount ratio at $5.50/day (%)Normalized Score sdg1_550povcol_sdg1_550pov
011.654.688green2.492.357green0.1699.238green
117.133.203yellow1.894.268green0.8296.095green
212.551.172green2.691.720green0.3798.238green
\n", "
" ], "text/plain": [ " People at risk of income poverty after social transfers (%) \\\n", "0 11.6 \n", "1 17.1 \n", "2 12.5 \n", "\n", " Normalized Score sdg1_transfer col_sdg1_transfer Trend sdg1_transfer \\\n", "0 54.688 green ↑ \n", "1 33.203 yellow ↓ \n", "2 51.172 green ↑ \n", "\n", " Severely materially deprived people (%) Normalized Score sdg1_material \\\n", "0 2.4 92.357 \n", "1 1.8 94.268 \n", "2 2.6 91.720 \n", "\n", " col_sdg1_material Trend sdg1_material \\\n", "0 green ↑ \n", "1 green ↑ \n", "2 green ↑ \n", "\n", " Poverty headcount ratio at $5.50/day (%) Normalized Score sdg1_550pov \\\n", "0 0.16 99.238 \n", "1 0.82 96.095 \n", "2 0.37 98.238 \n", "\n", " col_sdg1_550pov \n", "0 green \n", "1 green \n", "2 green " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sdg_current.iloc[0:3, 44:55]" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of Unequal Scores:\n", "Sub-indicator 1: 0\n", "Sub-indicator 2: 0\n", "Sub-indicator 3: 0\n" ] } ], "source": [ "#columns to check\n", "sdg1_indicators = ['People at risk of income poverty after social transfers (%)', \n", " 'Severely materially deprived people (%)', 'Poverty headcount ratio at $5.50/day (%)']\n", "sdg1_norm_cols = ['Normalized Score sdg1_transfer', 'Normalized Score sdg1_material', 'Normalized Score sdg1_550pov']\n", "\n", "#min and max from SDSN documentation\n", "sdg1_bounds = [[25.6,0], [31.4,0], [21,0]]\n", "\n", "#copy of dataframe for checking normalized scores, with countries only\n", "sdg_check_norm = sdg_current[0:32].copy()\n", "print('Number of Unequal Scores:')\n", "for i in range(3):\n", " #create column with new norm, using formula: (x - min(x))/ (max(x) - min(x))\n", " sdg_check_norm['norm{}'.format(i+1)] = round(\n", " (sdg_current[sdg1_indicators[i]] - sdg1_bounds[i][0]) / (sdg1_bounds[i][1] - sdg1_bounds[i][0]) * 100,3)\n", " #count unequal values:\n", " print('Sub-indicator {}:'.format(i+1), sum(sdg_check_norm['norm{}'.format(i+1)] \n", " != round(sdg_check_norm[sdg1_norm_cols[i]],3)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The normalized scores appear conistent with their documentation. Next we sum the normalized scores and check that this gives us the total Goal 1 score:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Normalized Score sdg1_transfercol_sdg1_transferTrend sdg1_transferNormalized Score sdg1_materialcol_sdg1_materialTrend sdg1_materialNormalized Score sdg1_550povcol_sdg1_550povTrend sdg1_550pov
054.688green92.357green99.238green
133.203yellow94.268green96.095green
251.172green91.720green98.238green
\n", "
" ], "text/plain": [ " Normalized Score sdg1_transfer col_sdg1_transfer Trend sdg1_transfer \\\n", "0 54.688 green ↑ \n", "1 33.203 yellow ↓ \n", "2 51.172 green ↑ \n", "\n", " Normalized Score sdg1_material col_sdg1_material Trend sdg1_material \\\n", "0 92.357 green ↑ \n", "1 94.268 green ↑ \n", "2 91.720 green ↑ \n", "\n", " Normalized Score sdg1_550pov col_sdg1_550pov Trend sdg1_550pov \n", "0 99.238 green ↑ \n", "1 96.095 green ↑ \n", "2 98.238 green ↑ " ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sdg_current.filter(regex = 'sdg1_', axis = 1).head(3)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number Unequal Goal 1 Scores: 0\n" ] } ], "source": [ "#create column with mean of goal 1 sub-indicators\n", "sdg_check_norm['goal_1_check'] = round(sdg_check_norm.filter(\n", " regex = 'Normalized Score sdg1_', axis = 1).mean(axis=1),3)\n", "\n", "print('Number Unequal Goal 1 Scores:', \n", " (sdg_check_norm['goal_1_check'] != round(sdg_check_norm['Goal 1 Score'],3)).sum())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again, the scores match. Lastly, we check that the mean of the 17 SDG scores matches the overall score:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number Unequal Totals: 0\n" ] } ], "source": [ "#mean of 17 SDG goals for each country\n", "sdg_totals = round(sdg_current.filter(regex = 'Goal [0-9]* Score').mean(axis=1),2)\n", "\n", "#compare unequal entries\n", "print('Number Unequal Totals:', \n", " (sdg_totals[0:32] != round(sdg_current['2020 EU SDG Index Score (0-100)'],2)[0:32]).sum())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Calculating Regional Averages\n", "\n", "The regions other than the EU lack total scores for each goal as well as an overall score, as noted above. We will fill each region with the mean score of its members, so that we can make comparisons across regions and compare countries to their regions." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
CountryGoal 1 ScoreGoal 2 ScoreGoal 3 ScoreGoal 4 ScoreGoal 5 ScoreGoal 6 ScoreGoal 7 ScoreGoal 8 ScoreGoal 9 ScoreGoal 10 ScoreGoal 11 ScoreGoal 12 ScoreGoal 13 ScoreGoal 14 ScoreGoal 15 ScoreGoal 16 ScoreGoal 17 Score
31European Union69.57756.39384.15770.15264.68986.03264.24572.69272.37382.26165.91862.05366.40867.00177.25374.74665.135
32Baltic States60.51260.39171.70680.75856.71886.53964.35775.99144.35354.97367.93858.69565.08083.99295.19084.38947.428
33Central and Eastern Europe65.84859.06177.02161.55353.62182.34561.88371.02043.85678.72858.54463.66471.58374.66085.42974.58552.093
34EFTA Countries81.34650.01491.92278.31080.28878.82096.53786.75087.64892.10674.41347.23536.83369.45861.01485.06964.942
35Northern Europe78.99858.48090.62587.37279.64791.05388.87388.26193.32594.40478.61555.07757.72279.36680.90088.34981.227
36Southern Europe64.46650.67184.16366.05555.44078.29956.97667.17851.26779.41156.20154.76567.45061.30167.55074.90260.635
37Western Europe76.26352.24087.24874.13268.49486.71361.74778.77484.32288.73172.88851.00552.47873.93175.29378.65454.426
\n", "
" ], "text/plain": [ " Country Goal 1 Score Goal 2 Score Goal 3 Score \\\n", "31 European Union 69.577 56.393 84.157 \n", "32 Baltic States 60.512 60.391 71.706 \n", "33 Central and Eastern Europe 65.848 59.061 77.021 \n", "34 EFTA Countries 81.346 50.014 91.922 \n", "35 Northern Europe 78.998 58.480 90.625 \n", "36 Southern Europe 64.466 50.671 84.163 \n", "37 Western Europe 76.263 52.240 87.248 \n", "\n", " Goal 4 Score Goal 5 Score Goal 6 Score Goal 7 Score Goal 8 Score \\\n", "31 70.152 64.689 86.032 64.245 72.692 \n", "32 80.758 56.718 86.539 64.357 75.991 \n", "33 61.553 53.621 82.345 61.883 71.020 \n", "34 78.310 80.288 78.820 96.537 86.750 \n", "35 87.372 79.647 91.053 88.873 88.261 \n", "36 66.055 55.440 78.299 56.976 67.178 \n", "37 74.132 68.494 86.713 61.747 78.774 \n", "\n", " Goal 9 Score Goal 10 Score Goal 11 Score Goal 12 Score Goal 13 Score \\\n", "31 72.373 82.261 65.918 62.053 66.408 \n", "32 44.353 54.973 67.938 58.695 65.080 \n", "33 43.856 78.728 58.544 63.664 71.583 \n", "34 87.648 92.106 74.413 47.235 36.833 \n", "35 93.325 94.404 78.615 55.077 57.722 \n", "36 51.267 79.411 56.201 54.765 67.450 \n", "37 84.322 88.731 72.888 51.005 52.478 \n", "\n", " Goal 14 Score Goal 15 Score Goal 16 Score Goal 17 Score \n", "31 67.001 77.253 74.746 65.135 \n", "32 83.992 95.190 84.389 47.428 \n", "33 74.660 85.429 74.585 52.093 \n", "34 69.458 61.014 85.069 64.942 \n", "35 79.366 80.900 88.349 81.227 \n", "36 61.301 67.550 74.902 60.635 \n", "37 73.931 75.293 78.654 54.426 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#create DF of regions and Goal mean scores\n", "region_goal_scores = round(sdg_current.groupby('Sub-region').mean().filter(\n", " regex = 'Country|Goal [0-9]* Score', axis = 1),3)\n", "\n", "#resetting index manually to match DF\n", "region_goal_scores.reset_index(inplace = True)\n", "region_goal_scores.index = region_goal_scores.index + 32\n", "region_goal_scores\n", "\n", "#Fill null region values\n", "sdg_current.fillna(region_goal_scores, inplace = True)\n", "\n", "#Check it's worked\n", "sdg_current.filter(regex = 'Country|Goal [0-9]* Score', axis = 1).tail(7)\n", "\n", "#Note: this seems like an inelegant solution.\n", "#How to fill a row in a DF with the column mean of only a SUBSET of the column that matches this row in another column?\n", "#i.e. find mean of Region's 'Goal x Score' and fill Region's 'Goal x Score' with this?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We compute the new overall index score for each region and visualize these scores graphically." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "#calculating overall score\n", "sdg_current['2020 EU SDG Index Score (0-100)'].fillna(\n", " round(sdg_current.filter(regex = 'Goal [0-9]* Score', axis = 1).mean(axis = 1),2), inplace = True)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#renaming score column\n", "sdg_current.rename({'2020 EU SDG Index Score (0-100)': 'overall_score'}, axis = 1, inplace = True)\n", "\n", "region_totals = sdg_current.tail(6)[['Country', 'overall_score']].sort_values('overall_score')\n", "ax = plt.subplot()\n", "sns.barplot(y = 'Country', x = 'overall_score', data = region_totals, \n", " palette = 'winter', ax = ax, alpha = 0.85).invert_yaxis()\n", "plt.title('Overall SDG Score by Region', size = 16)\n", "plt.ylabel('')\n", "plt.xlim((0,100))\n", "plt.xlabel('% Achieved', size = 14)\n", "plt.tick_params(labelsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that there is variation in the region's scores, as visualized below. Within the EU, Northern and Western European countries have a higher average than Baltic, Central/Eastern and Southern European countries. As we'll next be focusing on Poland which is in the Central/Eastern Europe category, we will compare to both this region and the EU as a whole." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## EU Overall Progress on SDGs\n", "\n", "We graph the 17 SDGs scores of the EU average and of Poland. As there are many goals, we color code from most complete (blue) to least complete (red)." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "#Creating DF with all countries' average scores for comparison\n", "goals = sdg_current.filter(regex = 'Country|Goal [0-9]* Score', axis = 1).set_index('Country').transpose()\n", "\n", "goals.reset_index(inplace = True)\n", "goals.rename({'index' : 'goal'}, axis = 1, inplace = True)\n", "goals['goal'] = goals['goal'].str.extract(r' ([0-9]*) ')" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize = (12,6))\n", "ax1 = plt.subplot(1,2,1)\n", "\n", "#calculate min & max for color-coding\n", "eu_min = goals['European Union'].min()\n", "eu_max = goals['European Union'].max()\n", "\n", "import matplotlib as mpl\n", "sns.barplot(y = 'goal', x = 'European Union', data = goals, ax = ax1, \n", " #color-coding bars from blue to red based on rescaled values\n", " palette = mpl.cm.coolwarm(1 - (goals['European Union'] - eu_min ) / (eu_max - eu_min)))\n", "plt.title('EU: Completion of SDG Goals', size = 16)\n", "plt.xlabel('% Complete')\n", "plt.ylabel('')\n", "plt.xlim((0,100))\n", "ax1.set_yticklabels(['No Poverty 1','Zero Hunger 2','Good Health and Well-Being 3','Quality Education 4',\n", " 'Gender Equality 5', 'Clean Water and Sanitation 6','Affordable and Clean Energy 7',\n", " 'Decent Work and Economic Growth 8', 'Industry, Innovation and Infrastructure 9',\n", " 'Reduced Inequalities 10', 'Sustainable Cities and Communities 11',\n", " 'Responsible Consumption and Production 12','Climate Action 13',\n", " 'Life Below Water 14','Life on Land 15','Peace, Justice and Strong Institutions 16',\n", " 'Partnerships for the Goals 17'])\n", "\n", "ax2 = plt.subplot(1,2,2)\n", "\n", "pol_min = goals['Poland'].min()\n", "pol_max = goals['Poland'].max()\n", "\n", "sns.barplot(y = 'goal', x = 'Poland', data = goals, ax = ax2, \n", " palette = mpl.cm.coolwarm(1 - (goals['Poland'] - pol_min ) / (pol_max - pol_min)))\n", "plt.title('Poland: Completion of SDG Goals', size = 16)\n", "plt.xlabel('% Complete')\n", "plt.ylabel('')\n", "plt.xlim((0,100))\n", "\n", "sns.despine()\n", "ax1.tick_params(axis = 'both', left = False, bottom = False)\n", "ax2.tick_params(axis = 'both', left = False, bottom = False)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Immediately we see that the EU has made the most progress on Goals 3, 6, and 10: Health, Sanitation and Inequality. Poland is also high in these categories, as well as Life on Land (Goal 15). This makes sense, as Europe generally has a high standard of basic safe living conditions for most of its population.\n", "\n", "The bottom two goals for Europe are Zero Hunger (2) and Responsible Consumption/Production (12). Poland's lowest categories, meanwhile, are Industry, Innovation & Infratstructure (9) and Sustainable Cities (11). This suggests that while Poland may be doing well in similar categories to other European countries, its greatest challenges may be specific to it." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualizing Comparative Progress\n", "\n", "The graphs above highlight highest and lowest achievements, yet are less useful in comparing Poland and the EU more holistically. Below we create polar charts to more easily compare Poland with other countries/regions. We use the [plotly module](https://github.com/plotly/plotly.py/tree/6387cb3bbea7dcd891ca8a72ee630fca5d53e132) to create these charts." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "marker": { "color": "crimson", "line": { "color": "navy", "width": 2 } }, "opacity": 0.6, "r": [ 74.92, 58.94, 78.009, 78.225, 56.791000000000004, 89.385, 57.785, 72.09, 46.941, 78.178, 56.733999999999995, 69.123, 70.936, 61.983999999999995, 88.385, 78.156, 67.158 ], "showlegend": false, "subplot": "polar", "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "barpolar", "width": 1 }, { "fill": "toself", "line": { "color": "crimson" }, "opacity": 0.9, "r": [ 74.92, 58.94, 78.009, 78.225, 56.791000000000004, 89.385, 57.785, 72.09, 46.941, 78.178, 56.733999999999995, 69.123, 70.936, 61.983999999999995, 88.385, 78.156, 67.158 ], "showlegend": false, "subplot": "polar2", "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" } ], "layout": { "height": 500, "polar": { "angularaxis": { "color": "navy", "direction": "clockwise", "rotation": 90, "tickfont": { "size": 16 }, "tickprefix": "SDG" }, "bgcolor": "powderblue", "domain": { "x": [ 0, 0.45 ], "y": [ 0, 1 ] }, "radialaxis": { "angle": 90, "color": "navy", "range": [ 0, 100 ], "showline": false, "showticklabels": false, "tickangle": 90, "tickfont": { "size": 10 }, "ticksuffix": "%", "tickvals": [ 25, 50, 75 ] } }, "polar2": { "angularaxis": { "color": "navy", "direction": "clockwise", "rotation": 90, "tickfont": { "size": 16 }, "tickprefix": "SDG" }, "bgcolor": "powderblue", "domain": { "x": [ 0.55, 1 ], "y": [ 0, 1 ] }, "radialaxis": { "angle": 90, "color": "navy", "range": [ 0, 100 ], "showline": false, "tickangle": 90, "tickfont": { "size": 10 }, "ticksuffix": "%", "tickvals": [ 25, 50, 75 ] } }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "sequentialminus": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "Poland: Percent of SDG Goals Completed", "x": 0.5 }, "width": 1000 } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.graph_objects as go\n", "from plotly.subplots import make_subplots\n", "\n", "fig = make_subplots(rows=1, cols=2, specs = [[{'type': 'polar'}, {'type' : 'polar'}]])\n", "\n", "fig.add_trace(\n", " go.Barpolar(\n", " r=goals['Poland'],\n", " theta=goals['goal'],\n", " width=1,\n", " marker_color = 'crimson',\n", " opacity = 0.6,\n", " marker_line_color=\"navy\",\n", " marker_line_width=2,\n", " showlegend = False),\n", " row=1, col=1\n", ")\n", "\n", "fig.add_trace(\n", " go.Scatterpolar(\n", " r=goals['Poland'], \n", " theta = goals['goal'], \n", " line_color = 'crimson', \n", " opacity = 0.9, \n", " fill = 'toself',\n", " showlegend = False),\n", " row = 1, col = 2\n", ")\n", "radialaxis_layout = dict(range=(0,100), \n", " color = 'navy', \n", " showline = False, \n", " angle = 90, \n", " tickvals = [25,50,75], \n", " tickangle = 90,\n", " tickfont_size = 10, \n", " ticksuffix = '%')\n", "\n", "angularaxis_layout = dict(rotation = 90, \n", " direction = 'clockwise', \n", " color = 'navy', \n", " tickprefix = 'SDG', \n", " tickfont_size = 16)\n", "\n", "fig.update_polars(radialaxis = radialaxis_layout, \n", " angularaxis = angularaxis_layout,\n", " bgcolor = 'powderblue')\n", "\n", "fig.update_polars(radialaxis_showticklabels = False, col = 1)\n", "\n", "fig.update_layout(height=500, width=1000, \n", " title_text=\"Poland: Percent of SDG Goals Completed\", \n", " title_x = 0.5)\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These two graphs present the same information slightly differently. On the polar bar chart at left, each wedge represents the percentage of progress toward the optimal level in that goal. On the polar scatter chart at right, the points representing each goal's percentage are connected to form a polygon. The larger the overall area of this polygon, the more overall progress a country is making toward all goals.\n", "\n", "As before, we can see that goals 6 and 15 are highest, and goal 9 is lowest. The left graph is slightly easier to read, yet the graph at right is easier to overlay with other countries, so we will use it in what follows. First we compare Poland's progress with that of the EU." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "fill": "toself", "line": { "color": "dodgerblue" }, "name": "EU", "opacity": 1, "r": [ 69.577, 56.393, 84.15700000000001, 70.152, 64.689, 86.03200000000001, 64.245, 72.692, 72.373, 82.26100000000001, 65.918, 62.053000000000004, 66.408, 67.001, 77.253, 74.74600000000001, 65.135 ], "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" }, { "fill": "toself", "line": { "color": "crimson" }, "name": "Poland", "opacity": 0.9, "r": [ 74.92, 58.94, 78.009, 78.225, 56.791000000000004, 89.385, 57.785, 72.09, 46.941, 78.178, 56.733999999999995, 69.123, 70.936, 61.983999999999995, 88.385, 78.156, 67.158 ], "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" } ], "layout": { "polar": { "angularaxis": { "color": "navy", "direction": "clockwise", "rotation": 90, "tickfont": { "size": 16 }, "tickprefix": "SDG" }, "bgcolor": "gainsboro", "radialaxis": { "angle": 90, "color": "navy", "range": [ 0, 100 ], "showline": false, "tickangle": 90, "tickfont": { "size": 10 }, "ticksuffix": "%", "tickvals": [ 25, 50, 75 ] } }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "sequentialminus": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "SDG Progress: EU vs Poland", "x": 0.5 } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = go.Figure()\n", "fig.add_trace(go.Scatterpolar(r=goals['European Union'], theta = goals['goal'], \n", " name = 'EU', line_color = 'dodgerblue', opacity = 1 ))\n", "fig.add_trace(go.Scatterpolar(r=goals['Poland'], theta = goals['goal'], \n", " name = 'Poland', line_color = 'crimson', opacity = .9))\n", "fig.update_traces(fill='toself')\n", "\n", "fig.update_polars(radialaxis = radialaxis_layout, \n", " angularaxis = angularaxis_layout,\n", " bgcolor = 'gainsboro')\n", "\n", "fig.update_layout(title_text=\"SDG Progress: EU vs Poland\", \n", " title_x = 0.5)\n", "\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From the above we can see that Poland appears to be doing similarly to the EU average on many goals. This agrees with its overall middle-of-the-pack ranking of 16/31. \n", "\n", "Poland is below the EU average in:\n", "- SDG 9: Industry, Innovation and Infrastructure - far below average\n", "- SDG 3: Health and Wellbeing\n", "- SDG 5: Gender Equality\n", "- SDG 7: Affordable and Clean Energy\n", "- SDG 11: Sustainable Cities & Communities\n", "- SDG 14: Life Below Water\n", "\n", "It's furthest above average in:\n", "- SDG 4: Quality Education\n", "- SDG 15: Life on Land\n", "\n", "Most surprisingly to me, it is overperforming the average in 12&13 - Responsible Consumption/Production & Climate Action. This is surprising given Poland's heavy reliance on coal and reluctance to commit to EU decarbonization goals. \n", "\n", "Let's visualize how Poland compares to the highest and lowest ranked countries, to get a sense of the amount of variation within Europe." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 Finland\n", "30 Bulgaria\n", "Name: Country, dtype: object" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sdg_current.loc[(sdg_current['2020 EU SDG Index Rank'] == 1) | \n", " (sdg_current['2020 EU SDG Index Rank'] == 31),'Country']" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "fill": "toself", "line": { "color": "mediumblue" }, "name": "Finland", "opacity": 0.8, "r": [ 82.094, 48.349, 87.53200000000001, 91.771, 80.691, 92.601, 88.34, 90.318, 91.262, 94.946, 85.655, 60.951, 54.698, 88.23100000000001, 80.468, 90.689, 70.168 ], "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" }, { "fill": "toself", "line": { "color": "crimson" }, "name": "Poland", "opacity": 0.9, "r": [ 74.92, 58.94, 78.009, 78.225, 56.791000000000004, 89.385, 57.785, 72.09, 46.941, 78.178, 56.733999999999995, 69.123, 70.936, 61.983999999999995, 88.385, 78.156, 67.158 ], "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" }, { "fill": "toself", "line": { "color": "mediumseagreen" }, "name": "Bulgaria", "opacity": 0.8, "r": [ 42.083, 46.325, 66.916, 39.477, 51.123000000000005, 78.97, 44.742, 62.355, 25.289, 52.25, 50.448, 63.408, 75.85300000000001, 63.898, 82.79700000000001, 65.098, 37.025999999999996 ], "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" } ], "layout": { "polar": { "angularaxis": { "color": "navy", "direction": "clockwise", "rotation": 90, "tickfont": { "size": 16 }, "tickprefix": "SDG" }, "bgcolor": "gainsboro", "radialaxis": { "angle": 90, "color": "navy", "range": [ 0, 100 ], "showline": false, "tickangle": 90, "tickfont": { "size": 10 }, "ticksuffix": "%", "tickvals": [ 25, 50, 75 ] } }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "sequentialminus": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "SDG Progress: Finland, Poland and Bulgaria", "x": 0.5 } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = go.Figure()\n", "fig.add_trace(go.Scatterpolar(r=goals['Finland'], theta = goals['goal'], \n", " name = 'Finland', line_color='mediumblue', opacity = .8))\n", "fig.add_trace(go.Scatterpolar(r=goals['Poland'], theta = goals['goal'], \n", " name = 'Poland', line_color = 'crimson', opacity = .9))\n", "fig.add_trace(go.Scatterpolar(r=goals['Bulgaria'], theta = goals['goal'], \n", " name = 'Bulgaria', line_color = 'mediumseagreen', opacity = .8 ))\n", "\n", "fig.update_traces(fill='toself')\n", "\n", "fig.update_polars(radialaxis = radialaxis_layout, \n", " angularaxis = angularaxis_layout,\n", " bgcolor = 'gainsboro')\n", "\n", "fig.update_layout(title_text=\"SDG Progress: Finland, Poland and Bulgaria\", \n", " title_x = 0.5)\n", "\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finland has made almost full progress on goals 3-11, 14, and 16. This suggests that these goals might be easier to address than goals such as Goal 2 (No Hunger) and 13 (Climate Action) that are low across Europe. Policies enacted in successful countries could be studied and possibly adapted to Poland. \n", "\n", "By comparing Poland's relative position between Bulgaria and Finland, we can also see that it has the greatest room for growth in goals 5, 7, 9, 11, and 14.\n", "\n", "Lastly, we'll compare Poland to the Central & Eastern Europe region average, to determine whether Poland matches this region more closely than the EU overall." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "fill": "toself", "line": { "color": "crimson" }, "name": "Poland", "opacity": 1, "r": [ 74.92, 58.94, 78.009, 78.225, 56.791000000000004, 89.385, 57.785, 72.09, 46.941, 78.178, 56.733999999999995, 69.123, 70.936, 61.983999999999995, 88.385, 78.156, 67.158 ], "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" }, { "fill": "toself", "line": { "color": "turquoise" }, "name": "Central/East Europe", "opacity": 0.8, "r": [ 65.848, 59.061, 77.021, 61.553, 53.621, 82.345, 61.883, 71.02, 43.856, 78.728, 58.544, 63.664, 71.583, 74.66, 85.429, 74.585, 52.093 ], "theta": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17" ], "type": "scatterpolar" } ], "layout": { "polar": { "angularaxis": { "color": "navy", "direction": "clockwise", "rotation": 90, "tickfont": { "size": 16 }, "tickprefix": "SDG" }, "bgcolor": "gainsboro", "radialaxis": { "angle": 90, "color": "navy", "range": [ 0, 100 ], "showline": false, "tickangle": 90, "tickfont": { "size": 10 }, "ticksuffix": "%", "tickvals": [ 25, 50, 75 ] } }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ], "sequentialminus": [ [ 0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "SDG Progress: Poland vs Central/East Europe", "x": 0.45 } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = go.Figure()\n", "fig.add_trace(go.Scatterpolar(r=goals['Poland'], theta = goals['goal'], \n", " name = 'Poland', line_color = 'crimson', opacity = 1))\n", "fig.add_trace(go.Scatterpolar(r=goals['Central and Eastern Europe'], theta = goals['goal'], \n", " name = 'Central/East Europe', line_color = 'turquoise', opacity = .8 ))\n", "\n", "fig.update_traces(fill='toself')\n", "\n", "fig.update_polars(radialaxis = radialaxis_layout, \n", " angularaxis = angularaxis_layout,\n", " bgcolor = 'gainsboro')\n", "\n", "fig.update_layout(title_text=\"SDG Progress: Poland vs Central/East Europe\", \n", " title_x = 0.45)\n", "\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Poland's progress appears to be close to average within the Central & Eastern Europe region for most goals, through it does outperform on SDGs 1 (No Poverty), 4 (Education), and 17 (Partnerships), and underperforms on Goal 14 (Life on Water).\n", "\n", "## Determining Priority SDGs for Poland\n", "\n", "Based on the data above, we suggest the following goals might be good candidates for Poland to focus on because (1) they are below the EU average, so there is an opportunity for bigger change, and (2) Finland has much higher scores, so this change has been attainable in at least one European country.\n", "\n", "- Goal 9 (Industry, Innovation, Infrastructure)\n", "- Goal 14 (Life below Water)\n", "- Goal 5 (Gender Equality)\n", "- Goal 7 (Clean Energy)\n", "- Goal 11 (Sustainability)\n", "\n", "The last three are also low-scoring goals for the EU overall, on average." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Correlation between Goals\n", "\n", "Before we investigate each of these goals, we check whether there are any significant correlations between the SDG goals. It would make sense to work strategically on correlated goals as they're more likely to benefit each other." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "\n", "#df: rows are countries, cols are goals\n", "goals_transpose = goals.set_index('goal').transpose().reset_index()\n", "\n", "goals_corr = round(goals_transpose.corr(),2)\n", "\n", "#creates upper triangular matrix of 1s with same size as goal_corr\n", "mask_ut=np.triu(np.ones(goals_corr.shape)).astype(np.bool)\n", "\n", "#plot heatmap of correlations\n", "fig = plt.figure(figsize = (20,10))\n", "ax = plt.subplot(1,2,1)\n", "sns.heatmap(goals_corr, annot = True, vmin = -1, vmax = 1, cmap = 'Spectral', ax = ax)\n", "\n", "ax2 = plt.subplot(1,2,2)\n", "sns.heatmap(goals_corr, annot = True, mask = mask_ut, vmin = -1, vmax = 1, cmap = 'Spectral', ax = ax2)\n", "\n", "plt.suptitle('Heatmaps: Correlation Between Goals', size = 20)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the above we can see positive correlations represented as green/blue and negative as orange/red. From the left graph one can more easily see the correlations of individual goals (rows) and on the right we can more easily see the overall trend of correlation. The strongest correlations are between:\n", "- Goals 1 and 10 - eliminating poverty and reducing inequality. This is intuitively reasonable. \n", "- Goals 3 and 9 - health and industry/innovation. This is more surprising, but could perhaps reflect better health care systems and medical technology in countries that score highly in both Goals.\n", "\n", "Goals 3-11 appear to be the most strongly correlated with other goals (especially each other). This could be due to many European countries having higher scores in these goals. Interestingly, SDG 13 (Climate Action) is negatively correlated with most other goals including SDG 7 (Affordable and Clean Energy). Although it is outside the scope of this analysis, it is worth further investigation. SDGs 2, 12, 15, 17 also have more negative or weak correlations; all but SDG 15 were in the lower averages.\n", "\n", "## Individual SDG Analysis\n", "\n", "Let's investigate some of the SDGs we identified earlier as being potential priorities for Poland. We see that SDG 9 (Innovation) is most strongly correlated with goals 3, 11, 5, and 1 in that order. Since correlation is only valid for linear data, we use a scatter plot to verify it is linear." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(12,8))\n", "\n", "goal_list = [3, 11, 5, 1]\n", "ylabel_list = ['Goal 3: Good Health', 'Goal 11: Sustainable Cities', 'Goal 5: Gender Equality', 'Goal 1: No Poverty' ]\n", "\n", "for i in range(4):\n", " num = goal_list[i]\n", " ax = fig.add_subplot(2,2,i+1)\n", " #plot goal i\n", " ax.scatter(goals_transpose['9'],\n", " goals_transpose['{}'.format(goal_list[i])],\n", " color = 'dodgerblue')\n", " #plot Poland as separate point\n", " ax.scatter(goals_transpose.loc[15, '9'], \n", " goals_transpose.loc[15, '{}'.format(num)], \n", " marker='o', s=50, color = 'red', label = 'Poland')\n", " ax.set_xlim(0,100)\n", " ax.set_ylim(0,100)\n", " ax.set_xlabel('Goal 9: Innovation', size = 12)\n", " ax.set_ylabel(ylabel_list[i], size = 12)\n", " ax.tick_params(labelsize = 12)\n", "\n", "plt.suptitle('Correlations with Goal 9: Innovation', size = 16)\n", "sns.despine()\n", "plt.subplots_adjust(wspace=0.4, hspace=0.4)\n", "plt.legend(loc = 'upper right', bbox_to_anchor = (1.4, 2.5))\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data does indeed appear linear and encompasses a wide range in each variable. In particular, in SDGs 5 (Gender Equality) and 11 (Sustainabile Cities) Poland is significantly lower than the top countries, so could make progress on these in tandem with SDG 9 (Innovation).\n", "\n", "For the other possible priority goals, Goal 7 (Affordable and Clean Energy)'s highest correlation is with Goal 5 (Gender Equality), but r = 0.67, which is only moderate. Still, it seems that most of the chosen goals are interrelated. Goal 14 (Life Below Water) is the exception - its only correlation above 0.5 is with Goal 15 (Life on Land), at r = 0.55. It seems reasonable that biological preservation in water and on land would be connected, and we will investigate this further later. Next we'll focus on Goal 9, as it is the furthest from the EU average." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Goal 9 : Innovation, Industry and Infrastructure\n", "\n", "Each goal is composed of several sub-indicators. As stated in the documentation, the sub-indicators for Goal 9 are:\n", "\n", "Label | Explanation\n", " :--- | :---\n", "sdg9_eurd | Gross domestic expenditure on R&D (% of GDP) \n", "sdg9_rdperson | R&D personnel (% of active population)\n", "sdg9_epo | Patent applications to the European Patent Office (per 1,000,000 population)\n", "sdg9_bband | Households with broadband access (%)\n", "sdg9_bbandgap | Gap in broadband access, urban vs rural areas (p.p.)\n", "sdg9_digital | Individuals aged 55 to 74 years old who have basic or above basic digital skills (%)\n", "sdg9_lpi | Logistics performance index: Quality of trade and transport-related infrastructure (worst 1–5 best) \n", "sdg9_qs | The Times Higher Education Universities Ranking: Average score of top 3 universities (worst 0–100 best)\n", "sdg9_articles | Scientific and technical journal articles (per 1,000 population)\n", "\n", "These absolute values have been normalized onto a 0-100 scale based on the SDSN's expert judgments; roughly, 100% represents the goal being completely met, 0% represents the lowest possible value or lowest among all countries.\n", "\n", "Below we find Poland's score for each sub-indicator." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Countrysdg9_eurdsdg9_rdpersonsdg9_eposdg9_bbandsdg9_bbandgapsdg9_digitalsdg9_lpisdg9_qssdg9_articles
15Poland27.93139.1183.94563.88973.07718.33358.70859.13478.333
\n", "
" ], "text/plain": [ " Country sdg9_eurd sdg9_rdperson sdg9_epo sdg9_bband sdg9_bbandgap \\\n", "15 Poland 27.931 39.118 3.945 63.889 73.077 \n", "\n", " sdg9_digital sdg9_lpi sdg9_qs sdg9_articles \n", "15 18.333 58.708 59.134 78.333 " ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Creating df of Goal 9 scores for all countries\n", "goal9 = sdg_current.filter(regex = 'Country|^Normalized Score sdg9', axis = 1)[0:30].copy()\n", "\n", "#shorten column names\n", "goal9.columns = [item[-1] for item in goal9.columns.str.split()]\n", "\n", "goal9[goal9['Country'] == 'Poland']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that Poland scored lowest in patents, digital skills, R&D spending and personnel. Below, we compare these scores to the overall distribution of Europe's scores, as well as to the SDSN report's \"green\" threshold, which indicates a sub-indicator is achieved or on track to be achieved by 2030." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize = (8,6))\n", "\n", "#boxplot of all countries\n", "goal9.boxplot(vert = False, ax = ax, color = '#1e90ff').invert_yaxis()\n", "ylabels = ['R&D Spending', 'R&D Personnel', 'Patents', 'Broadband Access', 'Broadband Gap',\n", " 'Digital Skills', 'Logistics', 'Higher Ed', 'Articles']\n", "ax.set_yticklabels(ylabels)\n", "ax.grid(False)\n", "ax.yaxis.set_ticks_position(\"right\")\n", "ax.tick_params(axis = 'y', labelsize = 12)\n", "\n", "#mark poland\n", "poland_x = goal9[goal9['Country'] == 'Poland'].iloc[0,1:10].tolist()\n", "from numpy import arange\n", "y_coords = arange(1,10)\n", "plt.scatter(x = poland_x, y = y_coords, marker = \"d\", color = 'crimson', label = 'Poland')\n", "\n", "#mark threshold for \"green\"; values taken from documentation\n", "green9 = np.array([1.5, 1, 80, 80, 10, 35, 3, 30, 0.7])\n", "max9 = np.array([3.3, 2, 240, 96, 0, 65, 4.2, 50, 1.2])\n", "min9 = np.array([0.4, 0.3, 3, 60, 26, 5, 1.8, 0, 0])\n", "\n", "#calculate normalized green threshold\n", "green9_norm = (green9 - min9)/(max9 - min9) * 100\n", "\n", "plt.scatter(x = green9_norm, y = y_coords, marker = \">\", color = 'seagreen', label = 'Green Threshold')\n", "plt.xlabel('% Achieved')\n", "plt.legend()\n", "sns.despine(right = False, left = True)\n", "\n", "plt.title('Goal 9: Innovation Subindicator Achievement in EU', size = 16)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we see that Poland is in the lowest 25% of European countries in terms of Digital Skills, Number of Articles, Higher Ed Rankings, and Patents. All nine sub-indicators are below the median. Despite this, Poland is still above the \"green threshold\" for several sub-indicators - including Articles - because much or all of Europe is. When considering both relative position and green threshold, it appears that Digital Skills, Patents, and R&D Spending could be areas of strategic focus.\n", "\n", "## Trends in Sub-indicators\n", "\n", "We can get additional context for progress in these sub-indicators by looking at trends over time. For this we'll use the second database containing trend data." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "sdg_trends = pd.read_csv('SDG_Europe_data.csv', sep = ';', decimal = ',')" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(819, 101)\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
countryidyearpopulationSub-regionsdg1_transfersdg1_materialsdg1_550povsdg2_obesitysdg2_trophic...sdg16_homicidesdg16_crimesdg16_crimepovsdg16_justicesdg16_adminsdg16_powersdg16_cpisdg16_detainsdg16_rsfsdg17_euoda
0AustriaAUT20008069276.0Western Europe12.0NaNNaN14.02.4...1.0NaNNaNNaNNaNNaNNaNNaNNaNNaN
1AustriaAUT20018097755.0Western Europe12.0NaNNaN14.32.4...1.0NaNNaNNaNNaNNaNNaNNaNNaNNaN
2AustriaAUT20028134403.0Western EuropeNaNNaNNaN14.72.4...0.9NaNNaNNaNNaNNaNNaNNaNNaNNaN
3AustriaAUT20038175855.0Western Europe13.23.3NaN15.02.4...0.6NaNNaNNaNNaNNaNNaNNaNNaNNaN
4AustriaAUT20048216810.0Western Europe13.03.8NaN15.42.4...0.89.8NaNNaNNaNNaNNaNNaNNaNNaN
\n", "

5 rows × 101 columns

\n", "
" ], "text/plain": [ " country id year population Sub-region sdg1_transfer \\\n", "0 Austria AUT 2000 8069276.0 Western Europe 12.0 \n", "1 Austria AUT 2001 8097755.0 Western Europe 12.0 \n", "2 Austria AUT 2002 8134403.0 Western Europe NaN \n", "3 Austria AUT 2003 8175855.0 Western Europe 13.2 \n", "4 Austria AUT 2004 8216810.0 Western Europe 13.0 \n", "\n", " sdg1_material sdg1_550pov sdg2_obesity sdg2_trophic ... \\\n", "0 NaN NaN 14.0 2.4 ... \n", "1 NaN NaN 14.3 2.4 ... \n", "2 NaN NaN 14.7 2.4 ... \n", "3 3.3 NaN 15.0 2.4 ... \n", "4 3.8 NaN 15.4 2.4 ... \n", "\n", " sdg16_homicide sdg16_crime sdg16_crimepov sdg16_justice sdg16_admin \\\n", "0 1.0 NaN NaN NaN NaN \n", "1 1.0 NaN NaN NaN NaN \n", "2 0.9 NaN NaN NaN NaN \n", "3 0.6 NaN NaN NaN NaN \n", "4 0.8 9.8 NaN NaN NaN \n", "\n", " sdg16_power sdg16_cpi sdg16_detain sdg16_rsf sdg17_euoda \n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN NaN \n", "\n", "[5 rows x 101 columns]" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print(sdg_trends.shape)\n", "\n", "sdg_trends.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exploring and Cleaning the Trends Data \n", "\n", "As seen above, each row represents a country in a particular year. Not all indicators have data for each of the years.\n", "Columns include country, id, year, population, and region in addition to each SDG sub-indicator.\n", "\n", "We confirm the date range of our data and the that the countries are as expected:" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,\n", " 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020])" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sdg_trends['year'].unique()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['Austria', 'Belgium', 'Bulgaria', 'Switzerland', 'Cyprus',\n", " 'Czech Republic', 'Germany', 'Denmark', 'Spain', 'Estonia',\n", " 'Finland', 'France', 'United Kingdom', 'Greece', 'Croatia',\n", " 'Hungary', 'Ireland', 'Iceland', 'Italy', 'Liechtenstein',\n", " 'Lithuania', 'Luxembourg', 'Latvia', 'Malta', 'Netherlands',\n", " 'Norway', 'Poland', 'Portugal', 'Romania', 'Slovak Republic',\n", " 'Slovenia', 'Sweden', 'European Union', 'Baltic States',\n", " 'Central and Eastern Europe', 'EFTA Countries', 'Northern Europe',\n", " 'Southern Europe', 'Western Europe'], dtype=object)" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sdg_trends['country'].unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data ranges from 2000-2020, as expected.\n", "\n", "In addition to the 32 countries expected, there are aggregate rows for the EU, Baltic States, Central and Eastern Europe, EFTA Countries, Northern Europe, Southern Europe, and Western Europe. (move this to earlier)\n", "\n", "We check null values to address any gaps in the data:" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total null values: 31541\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0EAAADxCAYAAAAN37wxAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAABI4klEQVR4nO29e9RfVXnv+3m4KSpULaKQpAV2E/YItmqr6JayRVGLFs3Y46glHg1i0mwtF7VlCClj7Np9kmG8JJU9NJvmIFWPYIi3mm3RCO7BUc8mBGF7A2obCeqboBgv9YYJb/KcP9YK/Ai/3/r93vVbc63nmev5jJGR913vusz7nM+cz/xOUVWCIAiCIAiCIAj6wmFdByAIgiAIgiAIgqBNwggKgiAIgiAIgqBXhBEUBEEQBEEQBEGvCCMoCIIgCIIgCIJeEUZQEARBEARBEAS9IoygIAiCIAiCIAh6RTIjSETOEZFvi8gOEbk81XeCIAiCIAiCIMgTEblGRO4XkW+N+LuIyH8rbY5viMgfTvLeJEaQiBwOfAB4GbAYWCoii1N8KwiCIAiCIAiCbPkQcE7F318GLCz/rQT++yQvTbUSdDqwQ1XvUdV9wCZgSaJvBUEQBEEQBEGQIar6JeAnFbcsAT6iBduAJ4rICePee0RTATyEecD3B36fAZ47eIOIrKSw1tiwbvUfrVi2NFFQ5sbRJ57Z+Dsf2P3lxt85DSni6IUu8qIqvavCUzef6sbRWrmomzZe4t92WZwmfm3nRV3arjNV5FKfUmApLNPgpa2pwtr4ZBSW0qwrZvftkq7DMBce3HOPTnrvUU/5d/+Z0iYo2aiqG+fwuWF2xzzgvqqHUhlBwzLqEYlRRm4jzC2hUpNDozYNuXROlkjRybTdcVky1qZ9ts13WiL3+I0jhzqTCkv1uw8GaTB3xpULS3nsZdLIEoM2QU3G2h3DSGUEzQALBn6fD+xO9K3AAJ46/GDuRB7WIzq8YBie2ssop0EQ1OLA/ja/VsvuSGUE3QYsFJGTgV3AecBrE33LBH3oKNqe2bPk2jINdQfC1uIRBNZJ0dZYWkECe0aSd7owSD0ZwV5oO01jtWcC9s+2+bUtwEUisoli+82/qWqlKxwkMoJUdVZELgK2AocD16jqnSm+5QFrFcJLJcylo/CS3oEdrLUZgR1StItR3oYzTdwjTYO+o3qgsXeJyMeAs4DjRGQG+BvgyOI7ehVwA/ByYAfwa+CCid6r2v12HEt7gqrow8qEFzzNwoQwwnC6GGB4imPThDDCaPqwD8VLvfDU7vXdy6FprNUZa3gTRtg3883JhRHm/34ncUvlDpclljqRvhPpHdQh90FEFePar9zTxtKqu7X2q27ZSFFuop/tL6kmxoKOaHAlKBVhBAWPIDogH+Q+YB1H3+PfNJGezZNLmlrat5hLmgbBMLIr3+0KI9RiaiNIRA4HvgrsUtVzReTJwPXAScC9wGtU9afTfsc62RXeIfTZtaULcolHELSFF2GEmPG2Qwgj5EGkqUF6shL0FuBu4Njy98uBL6rqWhG5vPz9sga+EzSEl8G1l3DmQqS3HSztsxmHtfDkTgz22iPKdh5EPnaDtqsOV4uphBFEZD7wYWAN8JflStC3gbNU9T4ROQG4WVVPrXqPJWGEVIOP6JyCJkmxUb2LMupl5r4KT3XbUv7nLkZgTYQlByyVX09YqmtdSMBb6hOmCcuRx53iShhh77/+r4nH9o9Z+PxO4jatEfQJ4J3AMcClpRH0M1V94sA9P1XVJw15diWwEmDDutV/tGLZ0trhaItc3LP63FmkygtLaRrqcHbib6nudzFosTT4qMLSIDEVlgwIL2e6TPPeKiyVUy9Yq09d4E0dbu+/fGVyI2jRH/tShxORc4H7VfV2ETlrrs+r6kZgI/hZCbJGisGHpY6yCi/hDPxgyXhKQZ8HUF0QbVQ9It2CYcQhwg7JXBjhDOCVIvJy4LHAsSLyUeCHInLCgDvc/U0EtC08DYQsDWra7rg8NXiWzsSoi7WBiZeyH9jBUj5FfaqHl3AG/cZa/e4MB8IIjRyWWq4EHXSHew/w4wFhhCer6turnre0EtQHLLmvVOHFQBiHl3jE4Cuog5f2pApPcfDSngT18FQWvWDJxbJXe4K+dePk7nBPf4kvd7gK1gKbRWQ58D3g1Qm+0RvadnmzhJdwBvWI/B2Np4GQtfDkTtv7lyJ/6xFpagdL6d2rcnGgJytB02JpJSjFLFuvlj+DIOgV0fYFQWCZXIRPvAkj/ObrN0w8tn/sM16ezUpQL+nCuvckhWwFa7K1lvYLWVKIGkcOkxWe3B3bdv2wlBe5tJeW4uil3Qs10dG0nW7TpJml9O4VDvYEhRF0CF467VRY6iiDwANe6oyXcKai72IiVVhyw/GUbkF79EEdzlI9bAQH7nBTGUEi8jZgBaDAN4ELgMcB1wMnAfcCr1HVn04VSgdkV3iHYGl2pw8dZR/iWBcv9c1LOKvoIg45pFsX9DnderXXIngU0V8aJOeVIBGZB1wCLFbVB0RkM3AesBj44oA63OXAZY2ENmgELx1CF+orXuhDHHMghStkF250uZc3S+5g4+jzgC6XgW4u8egzXtrvTtn/YNchGMu07nBHAEeLyIMUK0C7gVXAWeXfPwzcTM+NoGjU2iUaoHp4Spsc8rhuu9CFRLKXNsxLubCWnm1LCLdNF+ntpSymIIfJn2nwFNak5OwOp6q7ROS9FDLYDwBfUNUviMhTVfW+8p77ROT4Yc+LyEpgJcCGdatZsWxp3aA0Su6dAdjrgEfhJZzQ/oC2Ci/72qzVi7p46bi7EEZIQYq6ZsnVN9U3LQlxtF2e6n5vXFiq3pv7YN9SeeqCjtThWv/mVGTuDvckYAlwMvAz4OMi8rpJn1fVjcBGsCWRnWK21JM7iaXBzjjqhNVTXuSOtbywFJYU5BI/L4NLTxu5Lam1pQhLVVvzwO4vm8qLPtOH1eoqcmmjHyLnlSDgxcBOVf0RgIh8Cng+8EMROaFcBToBuL+BcJrHUufbBV0YT3Xe24e88MI0eeElH/veLgSjGZX/OQzmrOFpci8IsiFzI+h7wPNE5HEU7nBnA18FfgWcD6wt///MtIH0QB8GNClm9qroYu9DXbyctVCFFze6IBhFDvVwGjyFtQ4p4teFgZR7PnWBJRfLKvrUX2rOwgiqequIfAK4A5gF/jeFe9sTgM0ispzCUHp1EwHtK7l0znXIJX5eGj0v4ewDfa73fcfagc5BPfouDtBnUu0Rjj1BzSOq3W/HsbQnKNXqQ3QyQRAEQRAEQR1m9+2SrsMwFx744saJx/ZHn72yk7hNK5EdlIybvbE0g9Nng8zaLKulDcl9V4ez5DKRgi4meLwoSOWiDleFpX0xllyXUqkmVmGpbFhqo6qwlGbBhDhYCRprBInINcC5wP2q+vTy2nuAVwD7gO8AF6jqz8q/rQKWA/uBS1R1a5qgpyGHRm0aLHWUudC2H3sK+lAuvAwG6pJ7/MYRdWY0lsqGpbAEdvDkbRPujiWZCCN8CHg/8JGBazcCq1R1VkTeRXFA6mUishg4DzgNOBG4SUQWqer+ZoNtj+wK7xAszep6GmDUjYelMmUtTYNgGJbqTBWppIC9xN8SnvqSYDSW8jHKTUkOK0Gq+iUROemQa18Y+HUb8Kry5yXAJlXdC+wUkR3A6cAtzQQ3aAIvHWUusynWwhPYx1P5zoFI72AYqfLe0oA9qEcu45OkzM52HYKxNLEn6I3A9eXP8yiMooPMlNcehYisBFYCbFi3mhXLljYQFJtEhQiCIAiaIMXgK/qo5ok0DXpPDitBVYjIFRTy2NcevDTktqHqEKq6kUJS25Q6XBWWNt1OQw4zTZ46dC/CCJ5IkceWNodb26hvqUx5EbDw1M7mIlTQNnXrsLU+qg5tx8FauUglg12FO4nsTPYEDUVEzqcQTDhbH9bZngEWDNw2H9hdP3jtY62iBcOJfAqaps8HbXoJpydyGeh7wcvkRxD0hlxXgkTkHOAy4AWq+uuBP20BrhOR9RTCCAuB7VOHskX63pC27WoR1KPvg1ZL8fcy42spzabBS3pX4am9jHIaWMCTOlxdsiv7OawEicjHgLOA40RkBvgbCjW4xwA3igjANlV9k6reKSKbgbso3OQu7IMyHGRYeIdQN45tG5a55EUu8egzkYftksNqnicDKQe6qKPRLjRP1BuD5LASpKrDFAs+WHH/GmDNNIEK0uKlAfYSzlyI9K5H2/uTrOWTtfDkTB9mw/uOp7rvhUi3juiJOlxW5LDhOvBDitUuL26LfTgrJUWatl1mUuFl83QuK9I59EPWynDbeCmL1vogL/HPDrWveRZG0Bzw0gCNow+dxShyUYeLRrZ5vKiO1SWVOlwOZdGLQTYNlgyIFO1eiu9N894qcqgzVaRwnZ8mnyzVxVCHs8Uke4KuoVCBu19Vnz5w/WLgIoq9P/+kqm8vr68ClgP7gUtUdWuKgKcixez00See6aZhs9RRpqCLvEjxPUtxmEYqtO19Zine6cVY9dIGpcJaeltqTy1J9XeRT5byIhhOH+pTdm10DkYQ8CHg/cBHDl4QkRcCS4A/UNW9InJ8eX0xcB5wGoU63E0isqgP4gi9KthD8GI89SEvvNCHvOhDHIN6jCobltrLPhDpHQSJaFgYoVSmvhI4HLhaVdce8vffAj4K/A6FffNeVf2HqndOIozwJRE56ZDLbwbWqure8p77y+tLgE3l9Z0isgM4Hbhl3He804fBTqjD1aOugWwpHjFQGI2lfOo7ObgnWZvxzr18hzpcHng58LdXeb+/ufUPETkc+ADwEoozSW8TkS2qetfAbRcCd6nqK0TkKcC3ReRaVd036r119wQtAs4UkTXAb4BLVfU2YB6wbeC+mfLasAitBFYCbFi3mhXLhonQ5cG4Cth2ZfJSCb2sLo3DS3oHdohONBhFKtfUpul7ObUkDtD3vAg6oll3uNOBHap6D4CIbKJYeBk0ghQ4Roqze54A/IRiy85I6hpBRwBPAp4HPAfYLCKnADLk3qHyEKq6EdgI8OCee+xLSNDNBso+bNitwzSdiCWlmBR46fCm2RPkRcUxl3rvqUzVwVp654AXIyBVvejzSkGq+FmqU11MOOQsjDC4MFKysbQTDjIP+P7A7zPAcw95zfuBLcBu4Bjgz1SrffLqGkEzwKdUVYHtInIAOK68vmDgvvllYNxgaSAUjMbSYGcaclntqoOnvKjCizBCXbyEM6hPn9uhwAdRDh0yhz1BgwsjI5hkkeVPgK8BLwL+HXCjiHxZVX8+6qV1jaB/LD9ys4gsAo4C9lBYYNeJyHoKYYSFwPaa3+gES7PIXRCdYbvkYsy1jaX4e6kzltKsCyzt7bFULsZhKd2C/mJtr1wKciv7eqBRJ69JFlkuoNArUGCHiOwE/j0VdsgkEtkfA84CjhORGeBvgGuAa0TkW8A+4Pzyo3eKyGYKH71Z4MI+KMNBfoV3GF7cyDzlhaewBoF1LLlXVpGLS1AO9OHwzj6Qy6RDVjS7J+g2YKGInAzsolCifu0h93wPOBv4sog8FTgVuKfqpZOow41SLHjdiPvXAGvGvTfoDi8NsJdwToMld6k+pLcXLJWLcVgLT+7EYK89PB2uHYwm0q0jGlSHU9VZEbkI2EohkX2Nqt4pIm8q/34V8H8BHxKRb1K4z12mqnuq3lvXHS6YA110TLlX+lxWiayFJ2iPtjfWduHqa2n1OIe6lkr0JYe9sNbiYEm8xUvZz73+9o6GD0tV1RuAGw65dtXAz7uBl87lnZO4wy2gOCj1acABCsWGK0XkycD1wEnAvcBrVPWn5TOrgOXAfuASVd06l0BZpYsGyFJDGjSPpY7bk4qdl3phSSEqlTHjpT3xlN4pvmnJKPGiDjeN0Wmp7qegbTdRL+1MSnJWh+uKSVaCZoG/UtU7ROQY4HYRuRF4A/BFVV0rIpcDlwOXichiCl+90yjEEW4SkUU57A3qg++wl0bISzjHkUs8csBSXcvhe9awlN7W6naKsKaQh7eWbkF7hDCCQ9T+6TeT7Am6D7iv/PkXInI3hV73EgrBBIAPAzcDl5XXN6nqXmCniOygOOTolqYDH9ih7Y7LU4NnbWN1098Ld88gmBvW6pMXot4HHoj6XZLJStBDiMhJwLOAW4GnlgYSqnqfiBxf3jYP2Dbw2Ex5LWv60Dh3cfBjDj7QdV0fvMRhmndaimPb5OASYw0v6nBVWJvxzr0sdpHeuadpF3hxsexV3jcrkZ2EiY0gEXkC8Engrar6c5Fh5xYVtw659qiUGDwddsO61axYNkqErt/0vTL1IY59JfJ2NJ7qvbXw5E7b+5f6nr9tG9aRF81jKd16lb8NqsOlQnQCnz0RORL4LLBVVdeX174NnFWuAp0A3Kyqp5aiCKjqO8v7tgLvUNWR7nAP7rnHjLmYYuWhV8ufQRD0imj7giCwTC7CJ7P7do1cfbDIr955/sRj+8ev+nAncZtEHU6ADwJ3HzSASrYA5wNry/8/M3D9OhFZTyGMsJCK01pzwZN13+eBiadzHzxJIdfBmjpcXby4bHahDucljrkMkqqwlBe5tHs5uF/WxVM+WauLvSETd7gzgNcD3xSRr5XX/prC+NksIsspTml9NUB5eNFm4C4KZbkLPSnDpaignvY+5D6r6ykvcmeavLCUh17qjKU06wJLe3sslYtUhDpc0CTW9sqlILs2WjMQRlDVrzB8nw/A2SOeWQOsmSJc7siu8A4hh5lET/nkKax1yD1+0I84WsJLeueyCto2cTZNMIrIR4NkshIUZIaXjjIXQ8daeAL7eCrfORDpHbRJlCn/5DI+ScqsfSewMIJaIM5RaRdrDZC18IzCUlhywdIZWV1I1beNl7pmDUt7qepirYy2vSeqCkv5VEWq+mvJFbZX5OAOJyILgI8ATwMOABtV9cqBv18KvAd4iqruKa+tApYD+4FLVHVrgrC3Tg4dBdjrLILheNp4Wgdr50flPvjoQhihLm2/00udGUfbRqClemgtD3NfKejiEHBr9a1tZvft6joIcyMTd7hZ4K9U9Q4ROQa4XURuVNW7SgPpJRTCCACIyGLgPOA0CnW4m0RkkSdxhFGEz2kQ2CcHsYUUeIqfF9UtawPvulgySqKfDUYRZcMXeiCDlSBVvQ+4r/z5FyJyNzCPQv3t74C387A8NsASYJOq7gV2isgO4HRg5DlBgR1SzF5F49Q8nga0KfAS/xxmfIPmifayHuHWFORMduUtk5WghxCRk4BnAbeKyCuBXar69eIooYeYB2wb+H2mvHbou1YCKwE2rFvNimVL5xZyY2RXeIfQ9gx7Lu6HXlYmcpnVtoS1spg7XlaQqpjGJcjSapcXuohf7mnaBV5cnXvVX+ZkBInIE4BPAm+lcJG7AnjpsFuHXHtUSqjqRmAjwIN77rGfUhnhpQH2Es5xWBpgVdGrxtk4XsoM2AtP7rS9tyfytx59P+LBEpaO9+gV++3vgpnICBKRIykMoGtV9VMi8vvAycDBVaD5wB0icjrFys+CgcfnA7sbDXVC+rB5NvBBdKKjsRTHtuu3pc3o02Bpo36Kd1pTorT0zrpYK8N1qRtWS2XRUztkqd+zFJbUaA4rQVJYOR8E7lbV9QCq+k3g+IF77gWerap7RGQLcJ2IrKcQRlgIbE8Q9tq0vbfFWqH31Fk0TR8GJtbKWwosdepVWMqLVO1XDmUxxQSXtXa27YmTFP2stUnKHNwv69L2WGmafLJUF6cJS6jDNc8kK0FnAK8HvikiXyuv/bWq3jDsZlW9U0Q2UwgnzAIX5qAMB/nMQlXRhzi2TQ5++rmUC0sSwpbysA9YqofW6oyltOl7OQ2G40k+u++eGg+RiTrcVxi+z2fwnpMO+X0NsGaqkDkju8I7BEtuRp4G5XXjYalMWUvTuoThkTd9T+++x78OkWZ5YGlMkEt/OTWZrAQFmeGl0Z+mUbMUR0thscTRJ54ZaTOCXs0WGsCT4loMsPwTddg/sdozAWEEBRAVom0iTX2QSz7lslcw8EHbZ7lFOa2HJU+GyMOgC3R/Bu5wIrIA+AjwNOAAsFFVrxSRZwJXAY+l2PvzF6q6vXxmFbAc2A9coqpb0wS/Hn0/tyaHmURPHXrfhThSYG2DdNNYE37wUqasbcjOgbYH5Z6+V9ed2VofVYe+u5i1rfAHIYyQgklWgmaBv1LVO0TkGOB2EbkReDfwt6r6ORF5efn7WSKyGDgPOI1CHe4mEVmUgzhCdJR2iPQOmsaa4dE0XgZXqUixUd/SbP80WCobntItaA9PwghBQRYS2ap6H3Bf+fMvRORuYB7FAajHlrf9Fg+fBbQE2KSqe4GdIrIDOB24peGwu8HT3ofcO3xPeZE70+RF5GHgmRjQNU+0CYF3sivDORhBg4jIScCzgFuBtwJbReS9wGHA88vb5gHbBh6bKa8d+q6VwEqADetWs2LZ0jkG3RbZFd4htD1g7YM7WA5uEXVJtTncUrpZCksfaPvcllT562VSqW3aFqnow+GduRB1xiD2twRNbgSJyBOATwJvVdWfi8hq4G2q+kkReQ3FgaovZric9qPMQVXdCGwEeHDPPfbNxYzw0gB7Cec0WIqjpbD0HS9GHtgLT+7EYC9vPNV9L0S6dYPO2reCJjKCRORICgPoWlX9VHn5fOAt5c8fB64uf54BFgw8Pp+HXeV6SS4dk6VzgnKh7ThaGkD1oWNKkaa5bP73cjhtLivSlup3Dq7V4EccwFpZHEUuBmAu8Zga+zbQROpwQrHKc7eqrh/4027gBcDNwIuAfy2vbwGuE5H1FMIIC4HtDYY5KX2Qp+xC1cQKqfIih7TpO5YGiSlIpYLVdoefov1KYSBZaxPaNi4s9TNdqMNVkcMguW1lU2v1qS59UofLQhgBOAN4PfBNEflaee2vgT8HrhSRI4DfUO7vUdU7RWQzcBeFstyFOSjDBbboQ2NZFy+daB/wkhdewgm26n4OcuxBEARJyGElSFW/wvB9PgB/NOKZNcCaKcIVBJV4GkTkcBaQpYFnKtpeDfBkeATN0of6VEUfXOWC/hLltMDDSpCodh/IEEZoFy8DMy8Gwji8xMPLLHpgCy/tSRWe4tB2e+Kl/UrBuLjnEMcUWKtPllwsp4n/kcedMmpBwiQ/WfKCicf2T/7M/9tJ3CbZE/RY4EvAY8r7P6GqfyMi7wFeAewDvgNcoKo/K59ZBSwH9gOXqOrWNMH3gbWG1EvDnctsSi7xCNrD2iAisEOK9iTaoeF0IePfh33JQT/Q2a5DMJ6xK0GlMMLjVfWXpUrcVyhU4Y4F/qeqzorIuwBU9TIRWQx8jOKA1BOBm4BFVfuCPK0E5TArlkuHZ2mzdhVtd4apOu4UWNpY3IfBR9sbli3VtXFYEnFIgaXJmC4Oi7XU1nopF+Poc7p1wey+Xa5Wgva8bPKVoOM+Z3QlSAsr6Zflr0eW/1RVvzBw2zbgVeXPS4BNqroX2CkiOygMolsaC3VC+jAQyoU6eRV5MRprA6G2yb1jzmECJxW5G0Ce8GIA9Z0wgIKxNCyMICLnAFcChwNXq+raIfecBbyPwlbZo6ovqHrnpOcEHQ7cDvwe8AFVvfWQW94IXF/+PI/CKDrITHnt0HeupFSU27BuNSuWLZ0kKMnpewWNzsIHfRiYVmEp/pbCUoWXcKbCktuxp7bUUrpV4SlNg7nTxeph2+TWRmuDRlBph3wAeAmFXXGbiGxR1bsG7nkisAE4R1W/JyLHj3vvREZQ6cr2zPIDnxaRp6vqt8qPXkEhhX3twXAMe8WQd24ENoIvd7hR5FZ4h+HFtSWXvMglHkHQFpbcK6uw5rKaQ1tTNw5dGKu5GMiWiDS1R5NGEIVH2Q5VvQdARDZReJ7dNXDPa4FPqer3AFT1/nEvncgIOoiq/kxEbgbOAb4lIucD5wJn68Obi2aABQOPzac4WDUwgpcOz0s4cyHS2w6W9tmMw1p4cicGe8NJUWce2P3lXqdpLkQb1Q26f/JtPoPeYSUby8WSg8wDvj/w+wzw3ENeswg4srRTjgGuVNWPVH13EnW4pwAPlgbQ0cCLgXeVvnmXAS9Q1V8PPLIFuE5E1lMIIywEto/7Ts500YjmXumtrRJFRxkMI0W58OSLb2n1OJc2MURB5k4X7XMfymLTRJrlxVxWgga9w0YwiZfZERTnl54NHA3cIiLbVPVfRr10kpWgE4APl/54hwGbVfWzpeDBY4AbCwE5tqnqm1T1ThHZTLFENQtcWKUM5wlrA++6xIC9eSzJ1nqZKU4VzhgIDidVmqYo320LFeQijGBpEOlFItqay5ulNqOKtt1ELfVdXTG7b1fXQZgTeqBRwbdJvMxmKMQQfgX8SkS+BDwDqG8Eqeo3gGcNuf57Fc+sAdaMe7c3+lBBvcTRSzit4SXdrEno1sXSYMfa4Cr3+Hupa2CrbHhKt6A9QhjBHw3vCboNWCgiJwO7gPMo9gAN8hng/SJyBHAUhbvc31W9dE57goJgFG13XJ4aPGsbq5v+Xrh7jsZLOIN26cOALgVRnwIPWOsvu0K1uZWg8kzSi4CtFBLZ15SeZ28q/36Vqt4tIp8HvkEh0H31QRG3UYw9LLUNclCH84Sl2ekqcnE/zJ3Ip37jpT2pwlIcPO3BskQXe6X6nN6esOQ5ME05PfK4U1wdljrz3BdNPLaff+v/tHlYqog8FvgSxf6fI4BPqOrflH+7GLiIYu/PP6nq28vrq4DlwH7gElXdmib4+ZNK8cYDXsI5DksDrCr6NENlHS9lJmieLvI3h/JmbcU9xZ4oL3nRd6IvLTgwB3W4rhi7EiSF6sHjVfWXInIk8BXgLRTKC1cAf6qqe0XkeFW9X0QWAx+j0PQ+EbgJWFQljmBpJSj3zehBEARBEASBL2b37bJvVQzw3T988cRj+9+94yabK0Hl+T+/LH89svynwJuBtaq6t7zv4KFES4BN5fWdpYrc6cAtDYfdFKlmb8IoaxZPs6yepJDr0MUsawq8zPh2oQ5nLR6j8BLOabDULuTS7nk5nDcFMTYJxtGwOlwSJhJGKOWxbwd+D/iAqt4qIouAM0VkDfAb4FJVvY3iQKNtA4/PlNcOfedDByNtWLeaFcuWThWRprDUUXRBNFDBMKJc1MNS2ngZXKWi72IidbGkmlj1XA6GRd/pYsI4BZYmjbrEgOTAWCYygkpXtmeKyBOBT4vI08tnnwQ8D3gOsFlETmGyA40ecTCSJXe4uuRWeIeRwwy7JyzF0VqaeqlvlvIwF7woUVaF09oZWW1jbf9OYINpDARLbW207QXZrAQdRFV/JiI3A+dQrPB8qnSX2y4iB4DjmOxAoyAYS8ymBN7xcpBo37E04RLy2fWIOuMfT/kU45PxNCmRnYpJ1OGeAjxYGkBHAy8G3kWxT+hFwM2la9xRwB5gC3CdiKynEEZYCGxPFP7G6bufq6Ww9tnfugsibXzgaeBtqS562UvUBZba/RR0Eb8UdaYuXsppLuXQS3qnZr8DdbhJVoJOAD5c7gs6DNisqp8VkaOAa0TkW8A+4PxyVehOEdkM3EUhnX1hlTKcNVL4I497bzCcVK4tXvKiD0v4lgxdT8IQo0g18Mp91tNSXqT6pqW8yGXSsIrc60wKPK2CdhGW2X27Wv/mNGSxEqSq3wCeNeT6PuB1I55ZA6yZOnTGiEbNP5EXdrCWF7kMhEdhLb3bJoQRRmOpbKToZ62ldzCccfkbeeyL7PYEBfkTHZAPLA1ausBL/C0NvAM7RHtZjxQHhEd626Hv7Vdu8c9GHS4YT26FdxgpOqAq2j4vIhVtp1tdvLiRBcEoLLlX1mUalyBrbZ8HujCQIp+ax5qAySj61F9mtRJU7gn6KrBLVc8VkScD1wMnAfcCr1HVn5b3rgKWA/uBS1R1a8Ph7g0pOjwvDbCXcI7Dy6Cliz1IluKfAi8HqU6DtfDkjqVze3KniwOdIy+aJwcRFo/sP3BY10EYy1xWgt4C3A0cW/5+OfBFVV0rIpeXv18mIouB84DTKNThbhKRRV7EETypw0VF80/b5c1SJ9rFACMFbatA5VLvvezB8rQibSn+KcjFra3tum+p3a+iDytvlsKSGg/ucKIThFJE5gMfphA7+MtyJejbwFmqep+InADcrKqnlqtAqOo7y2e3Au9Q1VtGvd/SYameGtIqcuks2sSTMk2QN14MhFzoQ3vZhzi2TQ4uUZbcyCyli0Vm9+2y7182wNd+95UTj+2f+d0tncRt0pWg9wFvB44ZuPZUVb0PoDSEji+vzwO2Ddw3U157BCKyElgJsGHdalYsWzq3kAdBw+TinhWdTD0i3YImifIUBP0k6n5BFhLZInIucL+q3i4iZ03wzmGxfpQ1qKobgY1gayUoCIIgCIIgCOrQJ0OnCg/ucJOsBJ0BvFJEXg48FjhWRD4K/FBEThhwh7u/vH8GWDDw/Hxgd5OBDoIqctgvEwRBe8SgJQiCNujTKtGBHFaCVHUVsAqgXAm6VFVfJyLvAc4H1pb/f6Z8ZAtwnYispxBGWAhsbzzkQfb0qbFokkgb/4SxHgS+iXY46Du5qcMdylpgs4gsB74HvBpAVe8Ukc3AXcAscKEXZThIM/COQUs9rEmMetkEm3s4IU0ee4p/21haXbV05kcVMQgeTR824+cwlrB0xl8u9SmXeEyCA2+4uRlBqnozcHP584+Bs0fct4ZCSc4dfSqgnol8CprGi/GUgj4YZG3jJZzj6HO9CIKgPh7c4SaSyE5NLsIIXlxYulhhsdQhejlHpopUcYjVkGYZl545xN9Su2cpLNNgaTUkl3SztDLjZSVoGnJYIW6bcely5HGn2LcqBvj/nvaqicf2Z/zgE6YlshGRw4GvArtU9dyB65cC7wGeoqp7ymurgOXAfuASVd3aaKiN4qmBqkPbrmR96CgshTUMoHbpe/xTkGJQ2kU+WXIX88I0eWjJzSyHwXwX9Sn3NPXIga4DMAFzcYd7C3A3cOzBCyKyAHgJxZ6gg9cWA+cBp1EII9wkIos87QvKHS8dnpdw5kKkd/PkMigP7BCDvSDonmiHx6NDT8yxxURGkIjMB/6UYp/PXw786e8oDlH9zMC1JcAmVd0L7BSRHcDpwC2NhDgxOWy4DvLAkktMCqwJI9Sl7XTztOk4B5eYXFak+9wP5RJ3S2XRUl2zhqX+qUtmHewJmnQl6H0Uxs4xBy+IyCspXOO+LvKIiM4Dtg38PlNeewQishJYCbBh3WpWLFs6p4B3wTQV1FLBz6WhqYulQXKfXVuOPvFMU2H1ZATWIVX7lYOhk8JAtNbOepkA8ZK/495bhaWJE0ttsKe9xV20C7P7dtV+tguyWAkSkXOB+1X19vKcIETkccAVwEuHPTLk2qM2R6nqRmAj2BJG6Lv7iqWOsgpLg7KgHtbywsuAvS7W0rsubdf93MsF2BIN8NIHBe2Te9nIpY0+SC57gs4AXikiLwceS7En6P8BTgYOrgLNB+4QkdMpVn4WDDw/H9jdZKADe7TdOHlq8HJouK3FIbfOIugX1upTDqRoE6KdCeoQ9bsgi5UgVV0FrAIoV4IuVdX/Y/AeEbkXeLaq7hGRLcB1IrKeQhhhIbC92WDbow+NZdszqZb8n6chh3j0qeFuEkt52AdyWMn35BLUNm0bOqkk7mOQ3DxeXCz71CfkshI0J1T1ThHZDNwFzAIX9l0ZbpqGtM+VKZeOIvd8Cpqnz/U+qKbt/Ut9Lm+5iLcEQRfsd7ASFIelHoIn5aUgCIIgCIIgf2b37bJvVQzwP562dOKx/St+8DHbh6UG1Xia9emzUdZFXlhSXqrCSzjBVn2zFJYqclGHq8KS66m1dtbSRJ0X16Vp3luFpTqTgjhqJAA44GAlKIygQ+h7BbXUUQajyaGjnAZL8bcUliq8hDMVlvb2eGpLLaVbFZ7SNJg7fdgrl1sbbcbFq4KJjSARORz4KsXZQOeKyDOBqygU42aBv1DV7eW9q4DlwH7gElXd2nTArZFb4R1Gn2d1uyCXeARBW3iZmU+1ClqXPrc1XRirfU7vVOQy6ZATuQkjvAW4m0IiG+DdwN+q6udK+ex3A2eJyGLgPOA0CnW4m0RkUd/FEYK5k0ujlks8gvbI3V0mqEcqtbIcsGasBnnjxUW4Sw5IJu5wIjIf+FNgDfCX5WXlYYPot3j4LKAlwCZV3QvsFJEdwOnALU0F2htxjko9clE6shaeUVgKSy5YOiOrD25GXupaXR7Y/WVTZaoKL54D05BiIOwlL9ouh57qr6ewpsTDysekK0HvA94OHDNw7a3AVhF5L3AY8Pzy+jxg28B9M+W1RyAiK4GVABvWrWbFsqVzCXcyvDRAqfA04LFECoOtLl4Gu9aEESzlRQq6EEawlE+WBqWpsDSItJTe1lzeLOVTFW1PuHiqh12EZ3bfrta/OQ0HGl4IEpFzgCuBw4GrVXXtiPueQ2GH/JmqfqLqnWONIBE5F7hfVW8vD0s9yJuBt6nqJ0XkNcAHgRfDUDmIR+2PUtWNwEawJZFtaQDVBV4aIS/hDPxgafCRglzi1/bg0sssujX6MBAO2qMPwgi50aQ6XKlL8AHgJRSLK7eJyBZVvWvIfe8CJtIimGQl6AzgleW+n8cCx4rIR4FXUOwTAvg4cHX58wywYOD5+TzsKpctVW4KR594ZjYDkFG03XFNMxtsSe3IS8OdogOaJi9yr09B3lgb0OXQRlVR1dakcjEM+ksOq4BN0PDqxunADlW9B0BENlFsv7nrkPsuBj4JPGeSl441glR1FbCq/OhZwKWq+joRuRt4AXAz8CLgX8tHtgDXich6CmGEhcD2SQLjndwK8KF4mdnrIh8sGVYpyCWfgrzxog43jhhEDSdVuoz6e6jD+aEP4wxvzMUdbnCLTMnG0mPsIPOA7w/8PgM895B3zAP+E4VN0owRVMGfA1eKyBHAbygDr6p3ishmCutsFrgwlOHqEx2ef/qch0E9oswEowj3vPboYt9i1H3/RH0qmItE9uAWmRFMstXmfcBlqrpfJlSmE9Xut+NY2hOUYiNgVIggCIIgCIKgLrP7dtnXnB7gg/NfN/HYfvnMRyvjJiL/AXiHqv5J+fsqAFV958A9O3nYWDoO+DWwUlX/cdR7p1kJCgbwdH5D340yS65kKYxnT+IeObgvWQpLFV2ow1nKiyr6sLpiaaLOkutSF323pTpTly7qmrU6FVTT8GGptwELReRkYBfFeaSvHbxBVU8++LOIfAj4bJUBBJOfE3Qv8AsK2e9ZVX22iLyHQhxhH/Ad4AJV/Vl5/ypgeXn/Jao6kUqDBXIYlE2DpY4yBdb8+y29s+73uugMPdUpK/Q9zXKoM6mwVL8tTeL0vc5Yw0ud8jJplJomjSBVnRWRiyhU3w4Hrim337yp/PtVdd47l5WgF6rqnoHfbwRWlQF7F4V4wmUispjCQjuNQhjhJhFZlPu+oNwK7zAszep6aQyhfjwslSlraWoJS/nUd7zkhbUzsnIglCb7jaUxQfSXBdqw856q3gDccMi1ocaPqr5hknfWdodT1S8M/LoNeFX58xJgk6ruBXaKyA4Kabtb6n4raBYvjX4usynWwhPYx1P5zoFI79H0Pf4piDT1Ty7jk5Q07A6XhEmNIAW+ICIK/P0hsnUAbwSuL3+eR2EUHWSmvNZbPO21yAFrDZC18IzCUlhywdIZWX3wxfdS16yRgyuZtThY8mTwUvZT1V9LrrB9woP716RG0BmqultEjgduFJF/VtUvAYjIFRRS2NeW904iY/cITfAN61azYtnSOQc+BZ4aoGkODPWOpaXvVOSuVJgqnLGnYDjTlCcvZaoKS4PSVFgyAi2ld93vTSOaECsFcyeXepiK2X27ug7CnJjLOUFdMZERpKq7y//vF5FPU7i3fUlEzgfOBc7Wh7W2Z4AFA4/PB3YPeedDmuCWJLItDaCC0UR65824epi7wZKC3OM3jhw26qfCUtkI4yEYRhd9QjAdWbjDicjjgcNU9Rflzy8F/quInANcBrxAVX898MgW4DoRWU8hjLAQ2N580IMUpOiAonFqnhQDOk/5FAOewDO51MO2iXof5Exu5TsLIwh4KvDp8vTVI4DrVPXzpeDBYyjc4wC2qeqbSsm6zcBdFG5yF+auDAf5Fd5heBl455IXXvyY+z5oi9lpO1g64iAXOf4g8ICXcUaf+kszLl4VyMNebN1hyR3OE7kMvnKJxyg8xc/SoYleSJW/nspNDvQ5vfscd/Cz/9JaXlg6nNgSqdLlyONOcbDL5mHe/buvm3hs//bvfrSTuNWWyM6VFJ1BF5Z/LrMNucSjDincDy254fTBQEiVpnXeaynvIU0+eUnvVFhSI0yBtTLs5fwZS3Wtizy01CdYCktqPLiAhRE0Byw1QNNgqVNrG2sDkxQKf9bKWwosdepVtB3OLhT3ciiLXsrTNFiaxEul1tb096Z5bxW51xlr+WSpLk4TFnfqcA4c4iYygkTkXuAXFIbdrKo+u7x+MXARxd6ff1LVt5fXVwHLy/svUdWtzQc9DZY6ii6wNtOWAzl0lH0oFzkMPlI8lwtRZ+phKd2C/uJJHS73SaNJyUUY4SAvVNU9B38RkRcCS4A/UNW95RlCiMhi4DzgNAp1uJtEZFHu4gi5Fd5h5HDOxNEnnukmHpbKVCo3G0txDPzjpTz1wRXUC54G18FoLE06RJkpsL8ONJ073JuBtaq6F4ozhMrrS4BN5fWdpYrc6cAtU4U0CAaIgYB/Ip8CK+TSnuQSDyv0YY9KUI9Y7RlPTitBCnxBRBT4+/Kg00XAmSKyBvgNcKmq3gbMA7YNPDtTXnsEIrISWAmwYd1qVixbWj8WxrFWIbxUQkszO9PgJb0DO1hrMwI7pGgXo7wNp4sVOy97E4NgHLNify1oUiPoDFXdXbq83Sgi/1w++yTgecBzgM0icgowTObuUSlRGlIbwY9Edggj2MHTLEzbnaG18paCHFQc23aF7GIDeNtYqjM5tLNgSxjB2vfq1mFrfVQd2o6DtfqUYsJhHN6EETwM7CcyglR1d/n//SLyaQr3thngU1ocNLRdRA4Ax5XXFww8Ph/Y3WioOyKXlYkciPQOmib3jtvL4CoVljb4WyoXYKts5G48BPWIvVv+yMIdTkQeDxymqr8of34p8F+BXwIvAm4WkUXAUcAeYAtwnYispxBGWAhsTxT+oGE8ddxBf/Ey4PESziAIgqBbcusvcpHIfirwaRE5eP91qvp5ETkKuEZEvgXsA84vV4XuFJHNwF0U0tkX5q4MB/kV3mFYUlWrIpe8yCUefSZmrtvFixx9qr0mudN2XoQwgh9iAtce9k2gCYwgVb0HeMaQ6/uA1414Zg2wZurQBUnw0gB7CWcuRHrbwZPxZC08uRODvfbwtIc0GE2kWzdk4Q7XN3LYcB34oe2TtS0NoHI5K6XtDbLWTmOv+80UpDrPqg7WBl459EOW2q8u8FIWrfVBXuKfG/sdrAWFEXQIfVDr6kNnMYpUeWHpMDZr5c0LnozAOqRqv3JoT3IXxQBbk3jTHHbd5vemeW8VOYwl2h4rTZNPlupin9ThslkJEpEnAlcDT6dw83sj8G3geuAk4F7gNar60/L+VcByYD9wiapubTjcybBUWbrAy0ybl3AGfvCynyQFXsLpiWijgiDoM5rRStCVwOdV9VWlIMLjgL8Gvqiqa0XkcuBy4DIRWQycB5xGoQ53k4gs8iKOYGm2zBNtd/ie0juH1UVrAzpLg3ZLYanCSzhTYSn+1upTFZbamqC/eFqRDpn3gixWgkTkWOA/Am+AhwQR9onIEuCs8rYPAzcDlwFLgE2quhfYKSI7KM4VuqXhsJsit8I7jLpx7IPLQA6GThWWOpggGEUOq3meBns5YG2PSuRvPbwcwGupX09NLhLZpwA/Av5BRJ4B3A68BXiqqt4HoKr3icjx5f3zgG0Dz8+U1x6BiKwEVgJsWLeaFcuW1o6EByxVCi+VsO5g4OgTzzQVR0thsYS1fLKEpfYisEWKwV6Ut+FYE2/JZULNUniCdNg3gUCKo30qbhB5NoVRc4aq3ioiVwI/By5W1ScO3PdTVX2SiHwAuEVVP1pe/yBwg6p+ctQ3Htxzj5m0srahLwiCwDLR9gVBYJlchE9m9+2S1j86BX9+0qsnHtv/3/d+vJO4TbISNAPMqOqt5e+foNj/80MROaFcBToBuH/g/gUDz88HdjcVYKt4mknr88DE07kPbc/6eVJHs1TfvMzOplLBirwYjrV21pKxmku756WtrcLa+GQUuajD9YkshBFU9Qci8n0ROVVVvw2cDdxV/jsfWFv+/5nykS3AdSKynkIYYSGwPUXgU5BDozYNljrKIBiFpY7bS52xlGZdYMnt2FK5GEekW2CBPuyVy62NzkIYoeRi4NpSGe4e4ALgMGCziCwHvge8GkBV7xSRzRRG0ixwoRdluGnIrfAOo8+zul2QSzxGEb7hQdN4EUZItQpaFy/1sIu8sLSpPhhNpKk9slgJAlDVrwHPHvKns0fcvwZYUz9YQUpy6PA8NWpe0rttIl1GY8nFLPBDlI1m8dTPBO3ixUW4S3JaCQqmoO/nqLSNtQbIy4pWn8tMF6RQ8qrC2upDCqzVfS/ksLpkrYzmXhbbFpHylGaewpqS/WOE1ywwkREkIk8ErgaeTqF690ZVvaX826XAe4CnqOqe8toqYDmwH7hEVbc2H/T28TKYHYe1zqLP5LJBuA7WhBFyGAhW0YUwgiXaHmB1kS6WBpFtC8JUkctZQJbak7bjZ62d6UgdrvVvTkMu5wQBXAl8XlVfVe4LehyAiCwAXkKxJ4jy2mLgPOA0CmGEm0RkUQ77gjxV0Lp4iaOXcAZ+sDTASEHu8RuHpZVVa22UpbLhKd2C9ghhBH9ksSdIRI4F/iPwBgBV3QfsK//8d8DbeVgZDmAJsElV9wI7RWQHcDpwS3PBDqzRdseVQ4MX1Ce3ziLoFzHQb55oE4LAFrnsCToF+BHwDyLyDOB24C0Uogi7VPXrIo8442gexeGqB5kprz0CEVkJrATYsG41K5YtrRUBK/ShAa4bxz6fjg3tp1tdLLmRBUEdvKjDVTHNjLe1tq9p2laH8+Qq13csuVhW0af8zcUd7gjgD4GLVfVWEbkSeAfF6tBLh9w/7NTXR6WEqm4ENgI8uOce+ymVEV46Si/hHIeXQUufGmfreCkzYC88udP2/qU+56+1fYtBPSzth+sTTbvDicg5FNtzDgeuVtW1h/z9/wQuK3/9JfBmVf165Tt1jHqDiDwN2KaqJ5W/n0lhBP0+8OvytvnAbgq3twsAVPWd5f1bgXccFFIYhiUjqA8b+oIgCJoi2r4gCCyTi/DJ7L5dwxYZzPKffucVE4/tP/29/1EZNxE5HPgXCh2CGeA2YKmq3jVwz/OBu1X1pyLyMgrb47lV7x27EqSqPxCR74vIqar6bQo3uDtU9aEzgkTkXuDZqrpHRLYA14nIegphhIXA9nHfscIDu79cq3CPe8bSzE/fByaWZoWsKQhZUojz4g7pacY3d1nbVAp4dbHU1lpy38nlgNIc3C+nwVK6pXgumI6G3eFOB3ao6j0AIrKJQoPgISNIVf/XwP3bKBZoKplUHe5i4NpSGe4eytWeYajqnSKyuQzYLHChN2W4OhU0l0Yt91ndLvLC2onzo7BmrHmqN17IIU29GMdV38yhLR3HNOndZl71IS9S0EU99DI+8TJplJq5CCMM6gSUbCy3zRxkHvD9gd9ngKpVnuXA58Z9dyIjSFW/Bjy74u8nHfL7GmDNJO/OhdwK7zAszep6aQyhfjwslSlraRr0F0v1oi6x18QOnvqSYDSW8jHKTcFc9gQN6gSMYCK9AQAReSGFEfTH47476UpQkBFeOspcZlOshSewj6fynQOR3qPpc/xTxb3PaZoLuYxPUtKwO9wMsGDg94NaBI9ARP4AuBp4mar+eNxLwwhqCUt7LXLH2v4sLw2ipbDkgrUzsiztC0mBl7pmDU8uhqPoooymGAhbknPughR12JrMfV8YJ7w2R24DForIycAu4DzgtYM3iMjvAJ8CXq+q/zLJSycygkTkiRSW1dMplp/eCDwAXAU8lmLvz1+o6vby/lUUS1H7gUtUdesk32kSSypvD+z+sqlK4WVAU0UfZmG8bDqtizWXoNwHH0efeGatOI5rv7y0J223C12ki5c4WjICrJ0FZKnNqCJVmlbto/PS1qRidt+uroMwJ/Y3uBKkqrMichGwlUIi+5pSg+BN5d+vAv4L8NvAhvL80llVHbmVByZfCboS+LyqvqoUR3gcsBn4W1X9nIi8HHg3cJaILKaw0E6jUIe7SUQWeRFH6Hsl80LkU9A0loyntvEy8PKEJ8PRU1iDIPBB04elquoNwA2HXLtq4OcVwIq5vHOsESQix1IcjPqG8iP7gH0iosCx5W2/xcO+eUuATaq6F9gpIjsopO1GnhNkiT4PhMDP8n7f6fug1VL8LYWlCi/hTIWl+HtqL8OVKLBAF7LqbZNb2W/YHS4Jk6wEnQL8CPgHEXkGcDvwFuCtwFYReS9wGPD88v55FPrcB5kprz2CQTm8DetWs2LZ0ppRsEFuhXcYbfvj5uCnDvn7MefQ+QR5kMO5LdMM9qy1fR6wdmZRUA9LLpZV9Km/bHolKAWTGEFHAH8IXKyqt4rIlcDlFKs/b1PVT4rIa4APAi9mQhm7QTm8B/fcYz+lMsJLA+wlnOPIfdCSQxys4anMWAtP7uS+18QaIaTjH0vpZiksqZmLRHZXTGIEzQAzqnpr+fsnKIygP6ZYEQL4OIVwwsH7x8rY9YlcLH9LnUEutL2x2JIbjjVhhBRYUoezlPdg68Dfuu+swlI5BFv121I+ecJSWWy7bbNWn6rIJR7Tsj8HdzhV/YGIfF9ETlXVbwNnA3dRuMm9ALgZeBHwr+UjW4DrRGQ9hTDCQmB7grAnwdKyaSrqxjGHTqaLvIjOwge51/1U0tpeyqIX5bRUtG0EW5qMaVvJbBxe6kwVqZR0m36nNaaJhzd1uFzc4QAuBq4tleHuAS4APgNcKSJHAL+h3N9TStZtpjCUZoELvSjDQcxC9aERapu2O4sUWCsXKeLvZfBRl9zjN46+15kqLJWNvvfBwXA8CSPkMGnUBNkYQar6NeBQre2vAH804v41wJqpQha4wlOHHwRB0CXRXjZPbgPIIPBOLupwwQT0oQEOdbh65DDzEwOzwAM5uCd5mvHOAWsHqQb18OJi2ae8z2IlSEROBa4fuHQKxams84BXAPuA7wAXqOrPymdWAcuB/cAlqrq12WD7YpoK0efKlMtsae75FDRPn+t9UE2KdjHK23C6EG/JfW9i0B+yUIcrxRCeCSAihwO7gE8DpwKrVHVWRN4FrAIuE5HFwHnAaRTCCDeJyCJP+4JG0cXKRCiyDcfTLEzbnWEuxmPb9c3S4MPaRv1Qcps7nupaFZZm0a19r+q9OewFtYS1+tSFwJQ3YYT9eqDrIIxlru5wZwPfUdXvAt8duL4NeFX58xJgk6ruBXaKyA7gdOCWaQPbBqlUcvrceKVgmgaoz3lhyUAalxeWBkpVWOucR/HA7i+bmiDIvR56cmuz1C6koKqtGVcvgmap2wdHPvkjxz1B5wEfG3L9jTzsMjePwig6yEx5zQU5+JRPQ+6doae8qCKHeHhaIa3CUljG4SmsTWMp7p7aUi/GsSX3s2A0qdr9HPLRUhvVBFnsCTpIKY/9Sgq3t8HrV1BIYV978NKQxx+VEiKyklJWe8O61axYtnTSoJgkt8I7DC+uebnkRS7xCIK28DKJlWqvSZ9J4XrahTBC5G89Ik3tkcWeoAFeBtyhqj88eEFEzgfOBc7Wh9e9ZoAFA8/NB3Yf+jJV3QhsBHhwzz32UyojvAyuvYQzFyK97eBpZdlaeHInBnvtEWU7DyIfu+FAZu5wSxlwhRORc4DLgBeo6q8H7tsCXCci6ymEERYC2xsIq2ty6Jy8rAR5ou04WhtAeZm5r0uqPYZ1sLZHJcQW2sVS/obrWj0slcUu2jZrdWoUXvqn1HhYCZJJNi6JyOOA7wOnqOq/ldd2AI8Bflzetk1V31T+7QqKfUKzwFtV9XNV70+xEmSpsUxV6KMjmTt9V4erwtIgaRxelPMsdXhdGE+5l0VPbamlPsFSPexCNTGHQXLu/ZNFZvftGrbdxCz//vjnTDy2/+f7b+skbhOtBJUrPb99yLXfq7h/DbBmuqB1Q98rqKWOsgov4Qzax5IstSU8xc/S5ECKd1proyylt6fjD4L2sLaSnYLcynBu7nBBMJK2jZIcGjxPWDM6vXQWMWhrHmtlsQ6e4hDlNAjmhqf6nRIP7nBhBDVEHzoKL+o7ueSFpYa0Tw33XAlDxw45uCf1YcY7CJrG0jjDUnvSJVmsBInIqTx8BhDAKcB/UdX3icjFwEUUe3/+SVXfXj6zClgO7AcuUdWtjYc8qI2XSuglnF0QaeODFPvBIu/904X0chWWXAwtfW8apjnQexSe4h8Mp0/562ElaCJhhIduFjkc2AU8l8IYugL4U1XdKyLHq+r9IrKYQkXudAp1uJuARaq6f9R7cxBGsDRrHwRBEARBEOSDN2GE3/3tP5h4bP/dH3/DrjDCAGcD31HV74rIe4C1qroXQFXvL+9ZAmwqr+8sVeROB25pKtAW8WTd99koC3W40ViaOBiHpfrmZRY9lQpW5MVwrLWzltoFL65L07y3Ckt1pi6590/B9MxlkaUr5moEncfDZwUtAs4UkTXAb4BLVfU2YB6wbeCZmfLaIxCRlcBKgA3rVrNi2dI5BiUNfa+gsaLlAy8dZSr6Hv869D3NLLlu9aEtDZXGoEn6sFcut7J/wIE73MRGkIgcBbwSWDXw7JOA5wHPATaLyCnAsCWtR6WEqm4ENkIad7i2ya3wDsPSrO4Du7+cxWxaFTnEoS9EXtkgxeqiJ2ntce1iXUaF9+gTz3Rf9rsyVr2nmzX6PulgkdxWgl4G3KGqPyx/nwE+pUUst4vIAeC48vqCgefmA7ubCGzQDF4aXy8uOOOwFp6gWdp2pYry1DxeBkmTGDlNl4+q9+VeFlPFL/d06wO5jE9SkoU63ABLedgVDuAfgRcBN4vIIuAoYA+wBbhORNZTCCMsBLY3ElqnxDkq7WKtAbIWnlFYCksuWDojK9UeLEt4qWvWsLSXqi7W+tm294JWYSmfqkhVfy25wvYJD+pwExlBIvI44CXAfx64fA1wjYh8C9gHnF+uCt0pIpuBuyiksy+sUobzRA4dBfgZ0PSd3DeeWhNG8BT/OnQhjGCJtg2kLtLFSxwtGQFdyJXnbqx7OVPQG7P7dnUdhDmxXw90HYSxTGQEqeqvgd8+5No+4HUj7l8DrJk6dMaoW0E9+U17aYT6kBe5Yy0vLIUlBbnHbxzWZoO9tKdt07bxkGofVdAsnupTXSzVwybIbU9QUJPcCvYw2jaeclmVq0sO8fDk3hAETVMlNhAMx9JqVhAE1eS2JyiooA+DsrYlT3MxdLy4RXhxIwuCUeRwbss0M97W2j4PWHOVC+phycWyij71l9msBInI24AVFFLX3wQuAB4HXA+cBNwLvEZVf1revwpYDuwHLlHVrU0HvC+kWv73gJdwjsPLoKVPjXNbpNgcbanMgL3w5E6oEbZHF/sWIy+ax9P+y5zwcE6QjLPURGQe8BVgsao+UIoe3AAsBn6iqmtF5HLgSap6mYgsplCRO51CHe4mYFGVOEKKc4IsbXKOChEEQa5E2xcEgWVycaOc3bdr2DmcZjn28adMPLb/+a/u6SRuk7rDHQEcLSIPUqwA7aY4NPWs8u8fBm4GLgOWAJtUdS+wU0R2UBhEtzQXbHt4mr3p88DEk0R2qMONJtTh5k6q8uRFkawKL+GcBkvGqiXXpVSqiVV4Gi9YYZp8slYX+0IW6nCquktE3gt8D3gA+IKqfkFEnqqq95X33Ccix5ePzAO2Dbxiprz2CERkJbASYMO61axYtnS6mDSElwFUKix1lLlg6cT5FN+zdj6HpXdaqjO5DK68uBJZqzNVWJqMyaWcBs3iSR3OSxuVmiyEEUTkSRSrOycDPwM+LiJDpbEPPjLk2qNSQlU3AhshjTtc2+RWeIdhaeba0wCjbjwslSlraeoFS3nYB7ykt7VV0D4TaZYHlsYE0V8W5CKM8GJgp6r+CEBEPgU8H/ihiJxQrgKdANxf3j8DLBh4fj6F+1xgBC+Nfi6zKdbCE9jHU/nOgUjv0fQ9/imINPVPLuOTlGjDwggicg5wJXA4cLWqrj3k71L+/eXAr4E3qOodVe+cxAj6HvA8EXkchTvc2cBXgV8B5wNry/8/U96/BbhORNZTCCMsBLZPEsFciQoRBEEQNEGKwVf0Uc1jyZMh8jDogiZXgkTkcOADwEsoFltuE5EtqnrXwG0vo7A5FgLPBf57+f/o904SSBH5W+DPgFngf1PIZT8B2Az8DoWh9GpV/Ul5/xXAG8v736qqn6t6f6jDBUEQ+CTaviAILJPLfk9v6nBHHDVv4rH9uLiJyH8A3qGqf1L+vgpAVd85cM/fAzer6sfK378NnHVQv2AoqmruH7AynrPxzXjOzjfjOTvfjOfsfDOes/PNeM7ON+M5O9/sIo7e/lEIpX114N/KQ/7+KgoXuIO/vx54/yH3fBb444Hfvwg8u+q7h2GTlfGcmW/Gc3a+Gc/Z+WY8Z+eb8Zydb8Zzdr4Zz9n5ZhdxdIWqblTVZw/823jILZOIrk0kzDaIVSMoCIIgCIIgCIJgEtG1OQuzhREUBEEQBEEQBIFVbgMWisjJInIUcB6FENsgW4BlUvA84N+0aj8Qk6nDdcGhy2DxXHffjOfsfDOes/PNeM7ON+M5O9+M5+x8M56z880u4pgVqjorIhcBWykksq9R1TtF5E3l368CbqCQx95BIZF9wbj3TqQOFwRBEARBEARBkAvhDhcEQRAEQRAEQa8IIygIgiAIgiAIgl4RRlAQBEEQBEEQBL0ijKAgCIIgCIIgCHpFGEFBEARBEARBEPSKMIKCIAiCIAiCIOgVYQQFQRAEQRAEQdAr/n/ZzYqNKY/VTQAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "print('Total null values:' , sdg_trends.isnull().sum().sum())\n", "\n", "fig = plt.figure(figsize =(16,4))\n", "sns.heatmap(sdg_trends.notnull()).set(xticklabels = [])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are numerous sub-indicators with null values so we'll need to watch this as we select specific ones. There's also a gap in data around row 400 corresponding to Liechtenstein, so we'll drop Liechtenstein's rows from the set as well. The other horizontal groups of null values are frequently for years 2019-20." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "sdg_trends = sdg_trends[sdg_trends['country'] != 'Liechtenstein'].reset_index().copy()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Goal 9 Subindicators\n", "\n", "Let's examine the trend data for goal 9 sub-indicators for Poland to determine if there is any useful information." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "year 21\n", "sdg9_articles 19\n", "sdg9_rdperson 19\n", "sdg9_eurd 19\n", "sdg9_epo 16\n", "sdg9_bband 12\n", "sdg9_bbandgap 10\n", "sdg9_lpi 5\n", "sdg9_digital 4\n", "dtype: int64" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sdg9_sub_poland = sdg_trends.filter(regex = 'year|sdg9', axis = 1)[sdg_trends['country'] == 'Poland']\n", "\n", "sdg9_sub_poland.notnull().sum().sort_values(ascending = False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We'll graph all indicators with 10 or more data points." ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1AAAAILCAYAAADmJX2xAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAACGkElEQVR4nOzdd3gUVfvG8e+z6SEJAQKhCxY6VsRe0Nculp+9i7299o4gItiwi70g9t6w914QKyoq2AAhIYGQ3vf8/pgNb4yUTdjNJLv357r2yu7slHs3k8k+e86cMeccIiIiIiIismYBvwOIiIiIiIi0FyqgREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRMKqBERERERETCpAJK2i0zO9bMXKNbqZl9Z2ZnmFliM9f1vpm9H6Woq9tuw2vo18zl/mzy2ld6i1LscDM+aGZ/RmA9Ef3dhNb3caTW11aY2X5mdu5Kpu8Y2h92bOU8ATMbY2YzzWyZmZWb2W9m9oSZjWzB+hpex39amKdfaPkTWrL8KtY5oenfWWgbEyK1jZVsb6dorFtERMLXrA+ZIm3UQcBCICt0/zagGzDez1BRtj+Q0ujxHUACcLI/caLqNL8DtBP7Af8Bbmwy/WtgK+CnVs5zPXAmcDMwAagFBuDtu1sAM1s5T2vZCu94FA2XA5OBd6O0fhERCYMKKIkF3zrn5oXuv2lm6wNnE8MFlHPum8aPzawESHTOfb6qZczMgCTnXE2080WSc661P/jHFOdcCbDK/SIazCwNOB24zTl3fqOn3gJuN7OY7f2wur/Btqa9HhNERPwWs//EJK59CWSaWTcAM9vdzD4zs0ozKzazF8xs4OpWYGapZnaTmf1gZmVmlmdmM8xsUJP5GrrgbWlmj5pZiZktMrNbzSy1ybzrmtkrZlZhZgVmdgv/bEWKqFA3v0fM7Dgz+xmoAfYKPbeRmb1kZkWh9+UTM9uuyfIPmtlCM9vEzD4K5Z5rZqesZFs7m9nXZlYV6qb1r5YwM0s0sytDz1eZWaGZfWxm267hdfyjC1+jrlz7mNnU0HoKQq81uwXvU0PXrpPNbKKZLTaz5aHfd+8m8za8p4ea2ZxQt7RZK3sNZnakeV1KG17rw2bWo9Hzr5rZVytZroeZ1ZnZ2aHHXc3sbjP7NfQ7WGBmj5lZr0bLPAgcA/Sy/3Xh/LPJ+7Vjo/nNzM4xs1/MrCb0mqeaWVaTLM7MJpnZmWb2h3ndZD8ws6FreFs7AMlA3sqedM4FG2e3lXT1bPp7b6RjaJmi0N/bo2bWZQ15VspCXfDMbIPQ32aZmf1lZuOtSZHX6O+gysz+NrNxgK1knf/qwhf6e3vezJaG/t5+MbNLGj2/a2h/WBz6Hf9gZueZWULj9Ybujm30O57Q6PnV7m+heVZ6TLAW/m2KiMQrtUBJLOoP1ANlZrY78Apel5dDgAxgIvCxmW3snPt7FetIATKBScBioDNeV7LPzWyQc67pB8OHgceB/8PrwjMBKMLrcoOZJeN9+97wzfwSvO52/9d0w6EPRZcD/Z1zfzb71f/TKGBj4IrQNv80s02Bj4BvgBOBCuAU4G0z29o51/hDfRbwGF43rInAGOBOM/vFOfdeKO9g4FVgFnAo3ns3Ae+9rm+0rouAc4CxwLehdY/Ae29b4hbgZeBwYCBwXWh7x7RwfZcAnwLH4XUBvQF4FNihyXzbhbY3DqgCrgReNrN+zrnlAGZ2EnA38GRovT2Bq4AtzGxT51wZ8BDwuJkNadLKdnjo5+Ohn51D27kEKAit6zzgk9C+2JChK7A5sE9ouerVvNbJofXdDswAhoTWsZGZ7dC4wAGOBH4BzsIriqYAL4a2XbeylTvnCs3sD+B8MysGXnXOzV9Nnua4GXgbOAzYAO997Ym3r7fU88A04CZgNN7fy4LQNMwsB+8Ykoe3f1UDFwB917Ri8873eh+Yh7f/Lwzl3rDRbOsC7+B1P67C+7uYgPc7vTg0z1bAZ8CDePsWoXWFu781+Ncxgcj/bYqIxDbnnG66tcsbcCzg8D7MJgKd8IqSeuCF0DyzgLl43dsaluuPdz7GjY2mvQ+8v5ptJQDpQClwzkoyXNFk/peBXxs9PjE035aNpgWAH0PT+zWaPh6oA9ZpxnvxPvBxk2l/4hVH3ZtMfweYAyQ3eX1zGt630LQHQ9lGNZqWAhQC9zSa9mhoWodG0/rgfbv9Z5P35LkW/J7/8bsBdgzlmt5kvql4Hz6tOe8V0C+0vg+azHd+aHrPJu9pEdCp0bQRofkOb/Re5gPvNVnftqH5zgw9TgOKgaubzPctXsGxun2xT2hd+zf5fS1cyfwN79eOoccNBdmDTeY7MjTfPo2mOby/n6RG0w4MTd96De/zlqH3y4VufwP3AyObzPdg4/0kjN/7603mOyI0fec15Gn4PZ/QaNqE0LQxTeadDbzZ6PHk0P7ct9G0Dnj7vWuyrAMmNHr8IV4xlh7m/m54x7OxoX0t0GTdk1ayP6xxf2u0/67smNCiv03ddNNNt3i9qQufxIKf8QqiZXiDKTwKHGdmHYBNgSddo2/KnXN/AJ/w75aFfzCzg83sCzNbjlfQlOO1qqys+98rTR7P5p/fTm8FLHCNzo9w3rf8TzVdkXNuonMu0Tn31+ryhelz16i1zLxzU3YAngaCoa47iXgf2t4Gtm+yfIULtTSFslXjfaBu+tpedc6VN5pvAd573NiXwJ5mNtnMtg21yq2Nlb3nKUBuBNcH/25l+Mw5V7Sa+QbitWA92ngh59zHwF+E9jvnXCXwLHCEmRmAmQ0HNsJrnVrBzE4Ndc8qw9sXG1pzVtsVdRW2xHufHmky/YnQupv+XbzlnKtt9HhV78s/hPb1gcAeeK15f+K13nxmZke3IHeDpn8zTwNBvP0QM0to2K9Dt3D+zzX93f/Av/fxz12jVrTQ/j5jdSs1s3RgG+BR51zFaubrYV43zb/wCrVavNbvbLx9aXXC2t8a+ccxISTSf5siIjFNBZTEgv3xui4NwmsFOdo5twyvRcrwuuA1lcdquqeY2Wi87jBz8LpUbRHaRgGQupJFljV5XM0/z2/qgfctcVMrmxZJTV97Z7xvrMfhfUhrfDsD6NTkA2cR/1bNP9+DcF/bVXhdE/fB60K41MymhbpHtcTK3nNY+e8nkuv7x3yhorLxfA37VTj73UN4rUk7hh4fhdfK+WLDDGb2X7wvBt7G6/I5Eq8IWlm2cKw0X+hLhqX8+++ixe+zc67aOfe6c+5859w2eF0F8/j3SIHN8Y/9ynkDIBQBDeeEvcM/9+twBpNZ2WtsyT7eVCe8/7OrHJUv9Pf2ErA3XtG0E96xZnJoljW9z83Z31Y1X6T/NkVEYprOgZJY8IP73yh8jRXhdWHpvpLnuuN9WFyVQ4F5zrljGyaYWRItPydgMbCyE+9b2loSrqbXglqO92397TRp5VixwD/PfwnHYlb+Ov4xLdSKcS1wrZl1x/vAeCNe18hDmrnNtqzhw/iq9rtZjR5/gNeadKSZfYB3Xs8zodapBocC7zjnzmuYYGb9I5Tvx0brTAS6sPq/i7XinPvVzJ4EzjGzbs65JXjdCVfW4rGqLP/Yr0KtJZ3wugiC1403s9Esi9Y6eJj7+EoU4f299VrNPOvhdQM9yjm3olUw9CVOOJqzv8G/jwnx9LcpIhIRaoGSmBXqYvMVcFCT0azWAbbG+/C6Kul43ZkaOwqv9aYlPgP6mFlDy0HDN88Ht3B9LRJ6Tz7C6yb2tXNuVtNbC1b7GV73nw4NE8ysD17XpVXlyHPO3YfXqjKsBdtsy37Ba5k4tPFEM9saWIdG+51zzuF1vToQ2BPozb8L23S8lpTGxqxku9V451WtyeeheQ9tMv0QvC/VVvd3ERYzSzKzVRUXg4BKvPO/wOtmltu4tcPM1mPV3ROb/s0chPe/7DMA59wvTfbpSBRQnwFbhvbrhowd8AacWKVQt72P8QrkVf1u0kM/V/yOQ1/WHLGSeWv49+847P0tHDH+tykiEhFqgZJYNw7v/IaXzewOvHOYrsD78HbDapZ7HdjPzG7CO8F6M7yLgi5vYY7peKNpPWdml+KNfnUK3mhX/2Bm4/G6Ha0XofOgmjoX78T2N8zsfrxv13PwzhdLcM5dvLqFV2IS3ofYN81sCl5rwhU06d5kZi8C3+Fd2LUI2ATYnf+NKBYTnHP1od/h3Wb2CN65Rr3wumTNJTSyWyMP4Y2cdhfeYANNP/C+DlwU2m9m4nXxOnAlm/4J6Gxmp+K1OlQ552Y3nck5t8zMbgQuMbNyvBEUB+P9Hj/m3+cDtURHYL6ZPRVa/0K8FqVD8c6Juq5R18en8UYAfDSUKwfv/ShcxbqHmtk0vHO2BuC9rx84596JQO5VuQlvFM43Q6NkNozCV7m6hULOx/udfmZmN+C9F+sCGzvn/ovXTfgvYLKZ1eMVUuesYl0/4Q07/jre39Ai59yiZu5v/xIvf5siIpGiFiiJac651/GufZSNd/L5XXgfWLZdwzfT9+J9ADkE70TxvfC+bS5ezTKry1ED7II3wtodeAXVH3gfWpsK4LV0/esaM5HgnPsa7xyLpcCtwJt4Q4IPxyusmru+OXitJ+l4541dgzfUdNMPtB8Cu+KNxPY6cCre0OMXtuBltGnOuXvwWiyH453PdB3eMPY7uH8OKY1z7me8gqcX8EioVaqxiXgfZM/BG257Q2C3lWz2Pryi4iq8Qmt1AxyMxSuk98D7guBivEJurxZ04VyZEuAyvC5uU/D2hYfwWkRO5n9DcxPqfnsg3ut/AW9/OBf4dRXrPgvvb+NJvNf6MisvKCPGOVcI7IxX1E3H6wL7OvBAGMt+idcauwBvmPJX8YqvhaHna4D98M5Xeii07g/x/o6aOgNvMJsZeAM/nBRaR9j72yrEzd+miEgk2L//V4uIiIiIiMjKqAVKREREREQkTCqgREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRMKqBERERERETCpAJKREREREQkTCqgREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRMKqBERERERETCpAJKREREREQkTCqgREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRMKqBERERERETCpAJKREREREQkTCqgREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRMKqBERERERETCpAJKREREREQkTCqgREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRMKqBERERERETCpAJKREREREQkTCqgREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRMKqBERERERETClOh3ABERERGR9uirr77qlpiYeB8wDDVMxIog8ENdXd0Jm2222ZKVzaACSkRERESkBRITE+/r3r374K5duxYFAgHndx5Ze8Fg0AoKCobk5eXdB+yzsnlUKYuIiIiItMywrl27lqh4ih2BQMB17dq1GK9VceXztGIeEREREZFYElDxFHtCv9NV1kkqoERERERERMKkAkpEREREpJ1KSEjYbNCgQUM22GCDoXvssce6paWlq/x8f+utt3Y5+uij+0Ziu+eee27P8ePH50ZiXe2NCigRERERkXYqJSUl+PPPP/80d+7cH5OSktwNN9zQ1e9MsU4FlIiIiIhIDNh2223L5s2bl5Kfn5/wn//8Z70BAwYM2WijjQZ98cUXaU3nfeyxxzpuuOGGgwYPHjxk6623HrBgwYJE8FqWDjrooH4jR44c2Lt37+GTJk3q1rDMRRdd1L1fv37Dtt566wFz585Nac3X1pZEfRjznJwc169fv2hvRkQkKr766qtC51zcfJunY7aItGd+HrOXnHl1n5qff0+P5DqTB61b0e3WSxaEM29tbS1vvPFG1q677lpy4YUX9txoo40q3n777d9eeumlzGOOOab/zz///FPj+XfZZZeyQw899OdAIMCNN96YM3HixO733nvvQoB58+alfvrpp78sX748YfDgwcMuuOCCgpkzZ6Y9//zznWfPnv1TbW0tG2+88ZBNNtmkIpKvt72IegHVr18/Zs2aFe3NiIhEhZn95XeG1qRjtoi0Z/F2zAaorq4ODBo0aAjAFltsUXrWWWcVbrLJJoOfffbZeQD77LNP6UknnZS4dOnShMbL/fHHH8n77bdf74KCgqSamppAnz59qhue23XXXZenpaW5tLS0us6dO9cuXLgw8b333svYc889l2dmZgYb5mnFl9mm6EK6IiIiIiJrKdyWokhrOAeq8TTn/j2yupn9Y+IZZ5zR96yzzso74ogjil9++eXMiRMn9my0zhXzJiQkUFdXZ6F1RDx/e6RzoEREREREYsiWW25ZOm3atC4AL7/8cmanTp3qOnfuHGw8T2lpaULfvn1rAR588MEua1rnTjvtVPbKK69kl5WVWVFRUeCtt97Kjkr4dkAtUCJxxNXXw0q+lWoPLFGHKxGRts45R/3iAhJ7dlvzzBI111577aLDDz+834ABA4akpaUFH3zwwT+azjN27NhFhx122Hq5ubk1I0aMKJ8/f/5qB4XYdtttK/bff/9lw4YNG9qrV6/qkSNHlkXvFbRttrImvkgaMWKEU396Ef+Vv/EJ+SdNwFVU+R2l2RJ757LON8/4sm0z+8o5N8KXjfsgZ92ebt+rTvY7hoi0U3V5hdT+uYiUDQcQSE9t9e0/cNiEVj1mf/fdd39utNFGha21PWk93333Xc5GG23Ub2XP6StdkThQ89t8lpx6JUn9e5Mxeke/4zRbIKuD3xFERGQNgqXl1P7xN4HsTMyH4kmktaiAEolxwbIK8o69DJIS6f7w1ST16e53JGnD+nXuyf2HXu53DBFpZ+qWLGPhzsdjqcn0fmsqCdmZvuR44LAJvmxX4osKKJEY5pyj4Jxrqf31L3o8dYOKJxERiThXV0f+iZcTLC6l1+N3+VY8ibQWjcInEsOK736KshfepfOlJ5K+Q9ycxiMiIq1o6cS7qPr0W7recAEpw9b3O45I1KmAEolRlZ98w9IJd9Jhr+3JPvMIv+OIiEgMKnv+HYrvfJKs4/+PzIN28zuOSKtQASUSg+oWF5B/4uUk9e9Ft9su1YXvREQk4mp+/oMlZ19L6ubDyJl4ht9xRFqNCiiRGONqask7bhzB8iq6PziJQKZGsBMRkciqLykj75hLCWSkkfvAlVhykt+R4taCBQsSR48e3b93797Dhw4dOnjjjTce9NBDD2W31vaPOuqovoMGDRqy3nrrDU1NTd100KBBQwYNGjRk2rRpnUaOHDnwww8/TI/k9n755ZfkDTbYYGhzljnggAP6TZs2rVPT6S+//HLmqFGjmt3vVINIiMSYwstuo3rWj+TeN5Hkgf39jiMiIjHGBYMsOWMytfMX0/O5W0jsnuN3pLgVDAYZPXr0+ocffvjSGTNm/AHw66+/Jj/99NPZTeetra0lKSnyhe7DDz88H7zCZu+9997g559//qnhuTvvvHONV1SOVq5oUguUSAwpffJ1SqY9T8fTDyVj31F+xxERkRi0/JZHqHjtY7pMOJ20rTbyO05cmzFjRmZSUpK78MILCxqmDRgwoGbs2LFLAG699dYue+yxx7o77bTT+tttt92AkpKSwEEHHdRv2LBhgwcPHjzkkUceyQaoq6vj5JNP7j1s2LDBAwYMGDJlypQc8FpoRo4cOXD33Xdft3///kP32Wef/sFgsFkZH3/88U7Dhw8f3K9fv2Gvv/56RnNyzZo1K3X48OGDBw0aNGTAgAFDZs+enQJQX1/PoYceus76668/dJttttmgrKzMAD799NO0jTbaaNCAAQOG7LLLLusVFBQkNM3zzDPPZPXv33/oZpttNvCZZ57Jbv67rhYokZhR/f2vFJw/hdRtN6XLZSf7HUdERGJQxbtfsOzq+8g4YBc6nnSg33HalPGv39VnXuGCiHZXWz+nT8XE3U9ZsKrnZ8+enbbhhhtWrG4dX3/9dcb333//Y25ubv0ZZ5zRa9SoUSVPP/30n4WFhQkjRowYvM8++5Tcc889nTt27Fj/ww8/zKmsrLTNN9980OjRo0sA5syZk/btt9/+3q9fv9rNNtts0FtvvZWx2267lYX7Gurq6mz27NlznnzyyY4TJ07sufvuu/8abq7bbrut62mnnZZ/6qmnLquqqrK6ujr+/vvvpPnz56c+8sgjv2+99dZ/7bnnnus+9NBDnU477bRlxx57bP+bbrpp/l577VV29tln97zooot6PvDAAyvev4qKCjvjjDP6vfXWW78MHTq0eu+991433NfRmFqgRGJAfVEJecddRqBzNrn3TMAS9d2IiIhEVu38xeSfMpHkwf3pesMFGqCoDTrqqKP6Dhw4cMiwYcMGN0zbbrvtSnJzc+sB3n///aybbrqpx6BBg4Zsu+22A6urq23evHnJb7/9dtZTTz3VZdCgQUM22WSTwUVFRYk//fRTKsDw4cPL11tvvdqEhASGDh1a8dtvvyU3J9NBBx1UBLD11luXL1y4cMWy4eTaaqutym+44YYeY8eO7T537tzkjIwMB9CrV6/qrbfeuhJgk002qfjzzz9Tli5dmlBaWpqw1157lQGceOKJSz///POMxlm+/fbb1N69e1cPHz68OhAIcMQRRyxtyfusT1ki7Zyrryf/lInULS6k10u3kdj1X+dIioiIrJVgZTV5x46F+iDdp00m0CHN70htzupaiqJl+PDhlS+++OKKf/wPP/zw/MWLFyeOGDFiRQGVnp6+os+dc45nnnlm3kYbbVTdeD3OObvhhhvmH3DAASWNp7/88suZKSkpruFxQkICdXV1zaqcU1NTHUBiYiL19fUrlg0n16abblq13XbblT///PMd99hjjwF33HHHnwMHDqxOTk5unMlVVlaG3SgUicJfLVAi7VzRlGlUvvsFOVedRepmzRqURkREZI2ccxReeAM1s+fS7c7LSFq3t9+RJGT06NGl1dXVdu2113ZtmFZWVrbKz/ejRo0queGGG3IbzmP65JNP0gB22WWX4jvvvLNrdXW1AXz//fcpJSUlrVYnrCrXTz/9lDx48ODqyy67bMmuu+66/Ntvv11l5d6lS5f6rKys+obzrO6///4uW2211T+6Gm688cZVCxcuTP7xxx9TAJ544onOLcmrAkqkHSt/4xOKbphO5mF7knX0Pn7HERGRGFQy/UVKn3iNTucdQ4ddt/E7jjQSCASYMWPGbx999FFmr169hg8fPnzwkUce2W/ChAkLVzb/Nddcs6iurs4GDRo0ZIMNNhh62WWX9QI455xzCgcNGlQ1fPjwwRtssMHQE088cZ3a2tpW66O5qlwPP/xw5wEDBgwdNGjQkLlz56aefPLJq+1yN23atD8uuuii3gMGDBjy/fffp11zzTWLGj+fnp7ubrvttr/23nvv9TfbbLOBffr0qWlJXnPOrXmutTBixAg3a9asqG5DJB7V/r6QhbucSGK/nvR6+Q4CaSl+R4pJZvaVc26E3zlai47ZItJY1awf+XufM0jbbjN6PHYtlvCvQc3alNY+Zn/33Xd/brTRRoWttT1pPd99913ORhtt1G9lz6kFSqQdCpZXen3REwJ0nzZJxZOIiERc3ZJl5B03jsSeXcm9a3ybL55EWosGkRBpZ5xzFJx7HTU//0GPJ68nqW8PvyNJG2Bmx4Uzn3PugWhnEZH2z9XVkX/SBIJFxfR65U4SOmX5HUmkzVABJdLOFN/zDGXPvU3nS08kfdRIv+NI23FUGPM4QAWUiKzR0ivvpuqTb+g2dSwpGw7wO05bFgwGgxYIBKJ7Toy0qmAwaMAqrxisAkqklZW9/AHlr37YsoWDjrIX3yV9j23JPuvIyAaTds05N8rvDCISG8pe+ZDiO54ga8z+ZB6yu99x2rofCgoKhnTt2rVYRVRsCAaDVlBQ0BH4YVXzqIASaUWVn3xD/gmXE+iUSSCjZRcrT9t2U7pNHYsFdAqjrJqZdQH2BLo756aYWU8g4Jxb6chMIiLgdRMvmvIAyYPXJWfSf/2O0+bV1dWdkJeXd19eXt4wNLZArAgCP9TV1Z2wqhlUQIm0krrFBeSfeDlJ/XrS+617CWR28DuSxCgz2wF4FpgFbANMATYAzgdG+xhNRNq46m9/pubH38iZch6WnOR3nDZvs802WwLoOiJxRgWUSCtwNbXkHTeOYHkVPZ+/RcWTRNvNwCHOuXfMrCg07QtAJ82JyGqVPvIylp5Kxv/9x+8oIm2WCiiRVlB42W1Uz/qR3Psmkjywv99xJPb1c869E7rf0Ce/Bh3zRWQ1gmUVlD77Fhn7jCIhK8PvOCJtlvpqikRZ6ZOvUzLteTqedigZ++o8f2kVP5nZbk2m/QeY7UcYEWkfyl58D1deSeaRe/sdRaRN07eRIlFU/f2vFJw/hdRtNqHLuJP9jiPx4zzgZTN7BUgzs7vxzn3a199YItKWlTwyg6QB65A6crjfUUTaNLVAiURJfVEJecddRqBTR3LvvQJL1PcV0jqcc58DGwE/4l336Q9gpHPuS1+DiUibVT3nd6pn/UjWUaMxM7/jiLRp+kQnEgWuvp78UyZSt6iAXi9NJbFrJ78jSZxxzv0NXOd3DhFpH0ofeRmSk8g8qGnvXxFpSgWUSBQUTZlG5btfkDPlPFJHDPU7jsQZM+uMN2T5xsA/zgR3zm3vRyYRabuCVdWUPv0GGXtuR0KXbL/jiLR5KqBEIqz8jU8oumE6mYftSdYxOuVEfPEYkAI8BVT4nEVE2rjyVz8iWFRC5pG6TJxIOFRAiURQ7e8LWXLaJJI3HEDOteeqH7n4ZWugq3Ou2u8gItL2lT4yg8R1epC23aZ+RxFpFzSIhEiEBMsryTt2LCQE6D5tEoG0FL8jSfz6HujtdwgRaftq//ibyo++JuvwvbGAPhaKhEMtUCIR4Jyj4NzrqPn5D3o8eT1JfXv4HUni27vA62Y2Dchr/IRz7gF/IolIW1Ty6MsQCJB5+J5+RxFpN1RAiURA8T3PUPbc23S+9ETSR430O47IdsBCYJcm0x3esOYiIrjaOkoff5X0XbYisXuO33FE2g0VUCJrqfKz71g64XbS99iW7LOO9DuOCM65UX5nEJG2r+KtT6lfsoysozR4hEhzqIASWQt1eYXkHz+epHV60m3qWPUflzbFzLrx72HMf/cpjoi0MSWPvExC9xzSd97C7ygi7YoKKJEWcjW15B83jmB5JT2fu5mErIw1LyTSCsxsd+B+oOnJeA5IaP1EItLW1C1aQsU7X5B91pFYoj4OijSHvi4XaaHC8VOp+vIHut1yMcmD+vsdR6Sx24ErgQ7OuUCjm4onEQGg5PFXIRgk6/C9/I4i0u5E/SuHP5ct4vgnroj2ZkSaLVhRhauta9GyrryC2opFJJ43mKSqj+CJjyKcTmStdALuds45v4OISNvjgkFKH32FtB1GkNSvp99xRNqdFhVQZjYKqHfOfRjhPCKtoq6giNq5f63VOgJZGSSuo3880ibdD4xBI+6JyEpUfjCLugV5dBl3it9RRNqlsAooM/sAuNQ594mZXQScC9SZ2e3OuatWt2y/zj25/9DLIxBVJDKqf5jH33ueQsomg+l80fEtW0kgQOomg7CU5MiGkzbngcMm+B2hJbYEzjSzi/n3daC29yeSiLQVJQ/PINC5Ix323M7vKCLtUrgtUMOAz0P3TwR2BMqAT4DVFlAibUl9UQl5x15KIDuL3Psmkti1k9+RRKLhvtBNROQf6gqKKH/9Yzoe/3/6ElCkhcItoAKAM7P1AHPOzQEwM336lHbDBYMsOfVK6hYV0OulqSqeJGY556b7nUFE2qayp16H2jqyjtzb7ygi7Va4BdTHwFS8IXGfBwgVU4VRyiUScUVTplHxzufkTDmP1BFD/Y4jElVmNgY4CugF/A087Jyb5m8qEfGTc46SR14mdfNhJA/U6LEiLRXuMObHAsuB74EJoWmDgFsinkgkCsrf/ISi6x8k89A9yDpmX7/jiESVmY0FLgaeAM4M/bwwNF1E4lTV599TO28+mUeN9juKSLsWVguUc24pcGmTaa9EJZFIhNX+vpAlp04iecMB5Fx3HmbmdySRaDsB2NE5t2KoSTN7A/gQmOxbKhHxVckjLxPI7EDGPqP8jiLSroXVAmVmKWY22cx+N7Pi0LRdzeyM6MYTWTvB8kryxoyFhADdp00ikJbidySR1tABKGgybSmQ5kMWEWkD6otLKZ/xHhkH/IdABx0KRNZGuF34bsIbie8IoOHCjD8Cp0YjlEgkOOcoOG8KNXP+IPfuy0nq28PvSCKt5XXgUTMbaGZpZjYImA684XMuEfFJ2bNv4yqryTpS3fdE1la4BdT+wOHOuc+AIIBz7m+8k5NF2qTie5+l7Nm36HzxCaSPGul3HJHWdAZQCnyHd8mJ74AK4L9+hhIRfzjnKHl4BsnDNyBlo4F+xxFp98ItoGpocr6UmXXF6xIi0uZUfv49Sy+fSvru25J99pF+xxFpVc65Eufc0UA63uipac65o5xzy/1NJiJ+qPn+V2p+mKvWJ5EICbeAehqYbmb9AcysB96w5k9EK5hIS9XlFZJ//DiS+vag2+1jsUC4u7lIbDCzIWaW65wL4rU8XW5m480s3e9sItL6Sh6egaWlkHHAf/yOIhITwv1keSnwJzAbyAbmAouAK6KSSqSFXE0t+cePJ1hWQe6Dk0nIyvA7kogfHsM7VgNcD2wPbAXc7VcgEfFHsLyS0mffosPoUSR0zPQ7jkhMCHcY8xrgbODsUNe9QuecW/1SIq2vcPxUqmbOJveeCaQMXtfvOCJ+6eec+8W8Mfv3B4YClcAf/sYSkdZW9uK7uLIKsnTtJ5GIWWUBZWar+/SZ2XAtHefc75EOJdISpU+/Qcn9z9HxlIPJ2H9nv+OI+KnazDKBIcAC51yhmSUCqT7nEpFWVvLIyyRtsA6pWwz3O4pIzFhdC9Q8vCHLV3fVUQckRDSRSAtU/zCPgvOmkLrVRnQZr9H1Je49BrwHZOCdrwqwKWqBEokrNT//QfWXP9DlitN1EXmRCFplAeWc05n30i7ULy8lb8xYAh0zyb1vIpYUVs9UkZjlnDvHzHYFap1z74UmB4FzfIwlIq2s5JEZkJRI5sG7+R1FJKaE9UnTzHoBFc65okbTOuENjbsoWuFE1sQFgyw5dSJ1fy+h14u3kdits9+RRHxlZgnAr8AQ51x1w3Tn3Cz/UolIa3PVNZQ+9QYd9tiOhJxOfscRiSnhtjK9APRuMq038HxE04g0U9H1D1Lx9ufkTDqT1M2H+R1HxHfOuXqgHp3vJBLXyl79kGBRiQaPEImCcPs6DXDOzW48wTk328wGRSGTtED17LksOWMSwZJyv6O0qrqF+WQcvDtZY/bzO4pIW3Iz8JSZXQUsxDtfFdDAPyLxwNXXU3zvsyT27UHa9pv5HUck5oRbQBWY2frOuXkNE8xsfWBpdGJJc9QvKybv2LG46hrSR430O06rSujamU7nH6uTY0X+qWHgiF2aTNfAPyJxYNnV91H95Q90vfUSXUxeJArCLaAeAJ41s7HA78B6wJXAfdEKJuFx9fXknzKRurxCes2YSuqmQ/yOJCI+0yBAIvGr/NUPWX7LI2QeNZqsw/b0O45ITAq3gLoGqMW7on0fYAFe8XRjlHJJmIqum0blezPpesMFKp5E5B/MrA/Qyzn3ud9ZRCT6aubNJ//0yaRsMpiuV5/tdxyRmBVWAeWcCwJTQjdpI8pf/5iiG6eTefheZOokUREJMbO+wOPAxnjd9jLM7EBgd+fcCX5mE5HoCJZVkHfsWCwlie7TrsRSkv2OJBKzVllAmdn2zrkPQ/d3WtV8zrl3oxFMVq/mtwUsOW0SKRsNJOfac3QOkIg0djfwCrAd/ztX9S3gBt8SiUjUOOdYctY11M6dT49nbiSxV67fkURi2upaoO4AGsaFvn8V8zhg3YgmkjUKlleSP+YySEokd9okAqkpfkcSkbZlJLCXcy5oZg7AOVdsZh19ziUiUVB855OUv/QencefQvp2GnVPJNpWWUA554Y1ut+/deLImjjnKDjnWmp++ZMeT15PUp/ufkcSkbYnH1gf74K6AJjZEGC+b4lEJCoqP/mGpRPvosPeO5B9xuF+xxGJC2GN1GRmL65i+nORjSNrUnz305Q9/w6dLzmB9B039zuOiLRN1wMvm9kYINHMDgOeBK71N5aIRFLdoiXknTCepHV70+22S9WdX6SVhDsK36hVTN8xQjkkDJWffsvSCXfQYc/tyD7rSL/jiEgb5Zx7wMyWASfhjZp6NDDOOfeCr8FEJGJcdQ15x43DVVbT/aXJBDLS/Y4kEjdWW0CZ2cTQ3eRG9xusC/wVlVTyL3V5heSfcDlJ/XrSbepYfcskIitlZrvinb/6jXNOF4ERiVGFl91K9Vc/kfvAlSRvsI7fcUTiypq68PUJ3QKN7vcBeuN9q3lQVNMJAK6mlrzjxhEsr6T79MkEMjv4HUlE2iAzuwh4HjgUmGFmp/scSUSioOTxVyl58EWy/3s4GaN39DuOSNxZbQuUc26MmQWAT4GHnHPVrRNLGiscN5XqL38g976JJA/UeB4iskonAzs75z43s22Ae4Dbfc4kIhFU/d0vFF5wA2nbbUrnS0/0O45IXFrjIBKhi+jeqOLJH6VPvU7JA8/R8bRDydh3VaeiiYgAkOOc+xzAOfcJoGE6RWJI/bJi8sZcRkJONrn3TMASwz2VXUQiKaxR+IAPzWzLqCaRf6mePZeC86aQus0mdBl3st9xRKQdME/AzBL+99ACDTe/84lIy7j6evJPvoK6/KXkTptEQk4nvyOJxK1wv7r4C3gtNJz5ArwL6ALgnBsfjWDxrr6ohLwxYwl06kjuvVfoWyYRCUcGUNfosTV6bHjH7oTWDiUia2/ZtQ9Q+f6XdL3xAlI3Gex3HJG4Fu6n8jTghdD93o2m6x9xFLhgkCWnXknd4kJ6vXQbiV31LZOIhEUnSYrEoPLXPmL5TQ+RecReZB21j99xROJeWAWUc25M48dmtiHedUV0yesoKJoyjYp3Pifn+vNJ3Wyo33FEpJ1wzunSEiIxpua3+Sw5fTIpGw8i55pz/I4jIoR/DhRm1tXMzjKzr4FvgBHAWVFLFqfK3/yEousfJPOwPck6Wt8yiYiIxKtgWQV5x14GSYnkPnAlgdQUvyOJCGu+kG4SsA9wLLAbMA94HOgHHOycWxLlfO1O9fe/Uv7GJy1b2DmK736a5A0HkHPtubpYroiISDsWLK+k5OGXCJZWtGj5qi++p/bXv+jx1A0k9dGgmiJtxZq68OUDQeBB4HLn3NcAZnZalHO1S7W/L2TR/mcRLClr8ToS+3Sn+7RJBNL0LZOIiEh75ZxjyVnXUP7iuy1fSWICXa44nfQdRkQumIistTUVUN8D2wJbAHPN7A/nXFH0Y7U/wfJK8o4dCwkB+s56ksS+PVq8LrU8icjaMrM0IBtY7pyr9DmOSNwpvutJyl98l86XnUz2mUe0eD36TCDS9qz2HCjn3I7AesCbwPlAnpnNADoASVFP10445yg49zpqfv6D3LsvJ2mdnphZi28iIi1lZqPMbCZQCiwESs1sppnt7HM0kbhR+ck3LL3iLjrstQPZZx6hzwQiMWaNg0g45/5yzl3pnNsA2BlYjNet7zszuy7aAduD4nueoey5t+l8yQmkjxrpdxwRiVNmNgJ4FfgC2AUYAuwKzARmmNnmPsYTiQt1i5aQf+LlJK3bm263XaIiSCQGNevqrM65j4GPzexMYH+8oczjWuVn37F0wu2k77Et2Wcd6XccEYlvFwDXOecubzTtF+BdMysIPX+wL8lE4oCrriHv+PEEK6ro+cKtBDI7+B1JRKIg7GHMG3POVTnnHnfO7RHpQO1JXV4h+cePJ2mdnnSbOhYLtOjtFBGJlK2Au1fx3L3A1q2YRSTuFI67jepZP9Lt1ktIHtDP7zgiEiXNaoGS/3E1teQfN45geSU9n7uZhKwMvyOJiGQ75xat7Ann3CIz69jagUTiRckTr1Ey7QWyzziMjH1G+R1HRKJIBVQLFY6fStWXP5B77xUkD+rvdxwRkXA4vwOIxKLq73+l8ILrSd12UzqPPcnvOCISZSqgWqD06Tcouf85Op56CBn77eR3HBGRBh3MbP4qnjMgvTXDiMSD+mXF5I25jEDnbHLvmYAl6qOVSKzTX3kzVc+eS8F5U0jdemO6jD/F7zgiIo3pGx2RVuTq68k/ZSJ1eYX0mjGVxK6d/I4kIq1ABVQz1BeVkDdmLIHsLHLvvULfMolIm+Kc+2B1z5tZQmtlEYkHy659gMr3ZtL1hgtI3XSI33FEpJVo2LgwuWCQJadeSd2iAro/cCWJ3Tr7HUlEZLXM7GkzO9nMkkMDSLzhdyaRWFH+2kcsv+khMg/fi8yjRvsdR0RakQqoMBVNmUbFO5+TM/lMUkcM9TuOiEg43gC2AGYDnwOF/sYRiQ01v81nyemTSdloIDnXnqOL5YrEGfVBC0P5m59QdP2DZB6yO1nH7ud3HBGRlTKzjYAi59x8AOfcfWb2JvAB0Ak41sd4IjEhWFZB3rGXQVIiudMmEUhN8TuSiLQytUCtQe3vC1ly6iSSh29AzpTz9S2TiLRlDwIdGh6YWR/gPbyL6x4ATPYnlkhscM5RcM611P76F7l3X05Sn+5+RxIRH6gFajWC5ZXkjRkLAaP7tEkE0vQtk4i0aes65+YAmFlf4F3gOufc3aEBJJ70NZ1IO1d891OUvfAunceeRPqOm/sdR0R8ogJqFZxzFJw3hZo5f9DjiSkkrdPT70giImuyyMyOA/4C7gMudc49HnquL1DpWzKRdq7yk29YOuFOOuy1PdlnHel3HBHxkQqoVSi+91nKnn2LzpecSPpOW/gdR0QkHGfhdeOrAb4EjjCzRUA9MAV4fNWLisiq1C0uIP/Ey0nq34tut12q7vwica5NF1B1BUW46ppW327Nz3+w9PKppO++Ldln61smEWkfnHNvAiuay83sYryiKRF4Ghi/xnXU1FK7MD9qGWNNIC2FhC7Zrb5dV1sHAcMS2telveqLSwmWVvgdo3mCQfJPmUiwvIqez99CILPDmpcRkZjWZguo4nufofDSW3zbftK6vel2+1gsoHE2RKR9cs5dA1zTnGVq5vzO/E0OjFKiGBQI0PXmi8g6bM9W22SwrIK/9zoV65BOz+dubjejwFV+/DWLD73Aly9GIyH3vokkD+zvdwwRaQPaZAFV+em3FI6bStpOW5Cxz6jWD2CQvvOWJGRltP62RUSiwMw2BMY55w5a3XyJfbrT9cqLWylV+1f61OsUXnADKUPWI2WjgVHfnnOOJf+9ipqf/4RgkMJLb6HbjRdGfbtrq+7vfPJOvJzEvj3IPv0wv+M0W1K/nqRts4nfMUSkjWhzBVRdXiH5J1xOUr+edL/vCjWVi4iEyczSgUuAjYG5wAQgB7gB2AWYvqZ1JHTuSNYRe0UvZIzpsNvWLPzPCeSNuYzeb99HQueOUd3e8qmPUf7yB3SZcBr1y4pZfuujpG46hKwj947qdteGq64h77hxuMpqur80meQN1vE7kojIWmlT/dNcTS15x40jWF5J9+mTVTyJiDTP7cBo4CfgP8CzeBfR/RHo55w73cdsMSkhpxO50yZRl7+U/JOvwNXXR21bFR/OYtmke+iwzyg6nnYonS89kbQdRlB48U1Ufftz1La7tgrH3kr113PodtulKp5EJCa0qQKqcNxUqr/8gW63XKx+xiIizbcbsKtz7iJgT2Bn4HDn3GXOuUJ/o8Wu1E0G0/Wac6h8/0uWXXN/VLZRuzCf/JMmkLR+H7rdcjFm3gASuXdfTkLXTuSPuYz6pcujsu21UfLYK5RMf5Hs/x5Oxugd/Y4jIhIRbaaAKn3qdUoeeI6Opx5Cxn47+R1HRKQ9ynDOLQFwzi0EypxzH/mcKS5kHTWazCP3ZvnND1P+WmTf8mBVNfnHjcNV19J9+lUEMtJXPJfQJZvcaZOoLyiKegtYc1V/9wuFF95I2nab0vnSE/2OIyISMW2igKqePZeC86aQuvXGdBl/it9xRETaq0QzG2VmO5nZTgCNHzdMk+jIufpsUjYexJLTJ1Pz2/yIrbfw0luo/mYO3aaOJXn9vv96PnXjQeRccw6VH8xi2VX3Rmy7a6N+WTF5Yy4jISeb3HsmYIlt7pRrEZEW8/2IVl9UQt6YsQQ6dST33it0kBURabklwAONHi9t8tgB67ZqojgSSE0hd9okFv7nePKOGUvv1+/+R2tRS5Q88jKlD88g+8wjyNhr+1XOl3Xk3lR9/RPLb32UlE2HrHbeaHP19eSffAV1+Uvp9fLtJOR08i2LiEg0+NoC5YJBlpx6JXWLCuj+wJUkduvsZxwRkXbNOdfPOdd/NTcVT1GW1DuX3HsmUDt3PkvOvhbnXIvXVfXtzxRefBNpO4wIqwtc16vPJmWTwSw5YzI1c/9q8XbX1rJr7qfy/S/pes3ZpG4y2LccIiLR4msBVTRlGhXvfE7O5DNJHTHUzygiIiIRkb79CDqPPYnyF9+l+K4nW7SO+qXLyR9zGQldO5F79+VYQsIal7GUZLpPuxJLSSLv2LEEyypatO21Uf7aRyy/+WEyj9iLrKP2afXti4i0Bt8KqPI3P6Ho+gfJPGR3so7dz68YIiIiEZf938PpsNcOLL3iLio/+aZZyzZ0gasvKCJ32iQSumSHvWxir1xy772C2nkLWHLm1WvVAtZcNb/NZ8npk0kJnZMlIhKrfCmgan9fyJJTJ5E8fANyppyPmfkRQ0REJCrMjG63XULSur3JP/Fy6hYtCXvZZVfdS+UHs8i55hxSNx7U7G2nb7cZnS87ifIZ71N8xxPNXr4lgmUV5B0zFpISyX3gSgKpKa2yXRERP7R6ARUsryRvzFgIGN2nTSKQpoOsiIjEnkBmB7o/OIlgRRV5x4/HVdescZmyVz5k+a2PknnUaLKO3LvF284+43A67L0DSyfeReXHX7d4PeFwzrHk7GupnTuf3HsmkNSne1S3JyLit1YtoJxzFJw3hZo5f5B79+UkrdOzNTcvIiLSqpIH9KPbrZdQPetHCsfdttp5a+b+xZIzJpOy6WC6Xn32Wm3XawG7lKT1+pB34uXU/Z2/VutbneK7nqT8xXfpfOmJpO8wImrbERFpK1q1gCq+91nKnn2LzhcdT/pOW7TmpkVERHyRsc8oss84jJJpL1DyxGsrnSdYVkHesWOx1GS6P3AllpK81tsNZKTTffpkXFUNeceNC6sFrLkqP/mGpVfcRYe9tif7zCMivn4Rkbao1Qqoys+/Z+nlU0nfbRuyzzmqtTYrIiLiu85jTyJ1200pvOB6qr//9R/POedYcubV1M5bQO49E0jslRux7SZvsA7dbruU6q/nUDj21oitF6Bu0RLyT7ycpP696HbbpTqfWUTiRqsUUHV5heQfP46kPj3odvtYLODr6OkiIiKtyhITyb1nAoHO2eSNuYz6ZcUrniu+4wnKZ7xP53Enk77dZhHfdsbeO5D93yMomf4iJY+9EpF1uuoa8o4fT7Ciiu4PTiKQ2SEi6xURaQ+iX8k4R/7x4wmWVZA7fTIJHTOjvkkREZG2JrFrJ7pPu9L7UvGUibj6eio//pqlE++iw+gdyT79sKhtu/OlJ5C2/WYUXngj1d/9stbrKxx3G9WzfqTbrZeQPLB/BBKKiLQfUS+g6hYtoWrmbLrefBEpg9eN9uZERETarNRNh9D16rOpfG8mhRffRN6Jl5O0fh+63XpJVLvAWWIiuXdfTkLOv1vAmqvkidcomfYC2WccRsY+oyKYUkSkfUiM9gbqC5fT8aKDyNz/P9HelIiISJuXedRoqr76iZIHX8Qy0un+4GQCGelR325CTidyp03i771P5+/dTyGxd7cWrafqyx9I3XZTOo89KcIJRUTah6gXUIGMdLpcflq0NyMiItIumBk5154DASNj9I4kb7BOq207dZPB5N41nuJ7n8HV1LVoHek7b0XOlPOwxKh/hBARaZOifvRLWq8PlqSDrIiISINAagrdbrrIl21njN6RjNE7+rJtEZFYoOHwREREREREwqQCSkREREREJEwqoERERERERMKkAkpERERERCRM5pyL7gbMSoG1v2qfyMrlAIV+h5CYNtA5FzdXANcxW1qBjtsSTXF1zBZ/tMbweL8450a0wnYkDpnZLO1fEk1mNsvvDK1Mx2yJKh23JZri8JgtPlAXPhERERERkTCpgBIREREREQlTaxRQ97TCNiR+af+SaIu3fSzeXq+0Pu1jEk3avyTqoj6IhIiIiIiISKxQFz4REREREZEwqYASEREREREJU7MLKDPrY2bvmdkcM/vRzM4KTe9sZm+Z2dzQz06NlrnEzOaZ2S9mtluj6ZuZ2ezQc7eamUXmZUl71dz9y8y6hOYvM7OpTdal/Uv+pQX72C5m9lVoX/rKzHZqtK42v4/pmC3RpuO2RFO8HbOlfWhJC1QdcJ5zbjCwJXC6mQ0BLgbecc5tALwTekzouUOBocDuwB1mlhBa153AScAGodvua/FaJDY0a/8CqoBxwPkrWZf2L1mZ5u5jhcBo59xw4Bjg4Ubrag/7mI7ZEm06bks0xdsxW9qBZhdQzrnFzrmvQ/dLgTlAL2BfYHpotunAfqH7+wJPOOeqnXN/APOAkWbWA8hyzn3mvJEsHmq0jMSp5u5fzrly59zHeP+QV9D+JavSgn3sG+fcotD0H4FUM0tpL/uYjtkSbTpuSzTF2zFb2oe1OgfKzPoBmwBfALnOucXg7exAt9BsvYAFjRZbGJrWK3S/6XQRIOz9a1W0f8katWAfOwD4xjlXTTvcx3TMlmjTcVuiKd6O2dJ2JbZ0QTPLAJ4FznbOlaymG+nKnnCrmS7SnP1rlatYyTTtX7JCc/cxMxsKXAvs2jBpJbO12X1Mx2yJNh23JZri7ZgtbVuLWqDMLAlvJ37UOfdcaHJ+qHm0oRl+SWj6QqBPo8V7A4tC03uvZLrEuWbuX6ui/UtWqbn7mJn1Bp4HjnbO/Raa3G72MR2zJdp03JZoirdjtrR9LRmFz4D7gTnOuRsbPfUS3sl6hH6+2Gj6oaH+p/3xTtqbGWpuLTWzLUPrPLrRMhKnWrB/rZT2L1mV5u5jZpYNvAJc4pz7pGHm9rKP6Zgt0abjtkRTvB2zpX0w7zy6Zixgti3wETAbCIYmX4rXH/UpoC8wHzjIObcstMxY4Di8kVTOds69Fpo+AngQSANeA/7rmhtIYkoL968/gSwgGVgO7Oqc+0n7l6xMc/cxM7sMuASY22g1uzrnlrSHfUzHbIk2HbclmuLtmC3tQ7MLKBERERERkXi1VqPwiYiIiIiIxBMVUCIiIiIiImFSASUiIiIiIhImFVAiIiIiIiJhUgElIiIiIiISJhVQIiIiIiIiYVIBJSIiIiIiEiYVUCIiIiIiImFKjPYGcnJyXL9+/aK9GRGRqPjqq68KnXNd/c7RWnTMFpH2LN6O2eKPqBdQ/fr1Y9asWdHejIhIVJjZX35naE06ZotIexZvx2zxh7rwiYiIiIiIhEkFlIiIiIiISJhUQImIiIiIiIQp6udA/blsEcc/cUW0NyMiIhGgY7aIiMjqqQVKREREREQkTOaci+oGRowY4TSik4i0V2b2lXNuhN85WouO2SLSnsXbMVv8oRYoERERERGRMKmAEhERERERCZMKKBERERERkTCpgBIREREREQmTCigREREREZEwqYASEREREREJkwooERERERGRMKmAEhERERERCZMKKBERERERkTCpgBIREREREQmTCigREREREZEwqYASEREREREJkwooERERERGRMKmAEhERERERCZMKKBERERERkTAlhjOTma200HLOBSMbR0REREREpO0KtwWqDqhtejOzajP7w8xuMLOMaIUUERERERFpC8ItoP4LvAvsCgwGdgPeAS4ETgW2Bm6OQj4REREREZE2I6wufMC5wKbOueLQ41/NbBbwlXNuPTObDXwVlYQiIiIiIiJtRLgtUFlAepNp6UDH0P08IC1SoURERERERNqicFugHgLeMrNbgAVAb+AsYHro+V2BXyIfT0REREREpO0It4C6AJgLHAr0BBYDtwP3hp5/D3g/0uFERERERETakrAKqNBw5XeFbit7viqSoURERERERNqicFugMLNdgY2BfwxX7pwbH+FMIiIiIiIibVK4F9KdChyM11WvotFTLhqhRERERERE2qJwW6AOAzZ2zi2IZhgREREREZG2LNxhzJcCy6OYQ0REREREpM0LtwXqBuBRM7sayG/8hHPu94inEhERERERaYPCLaDuDP3cu8l0ByRELo6IiIiIiEjbFe4w5uF29RMREREREYlZKoxERERERETCtMoWKDN73Tm3e+j+R6xiyHLn3PZRyiYiIiIiItKmrK4L30ON7t8X7SAiIitT8sRr1Pz0G10uOxlLTvI7joiIiMS5VRZQzrnHGt2f3jpxRET+py6vkKWX3Ury4PUgUePViIiIiP9W14XvuHBW4Jx7IHJxREQ8zjkKLrwBV11D15svwgI6ZVNERET8t7oufEc1um/ANkAesADoA3QHPgZUQIlIxJW/8C4Vr31MlwmnkbxeH7/jiIiIiACr78I3quG+md0GvOCcu7nRtLOA9aKaTkTiUn1hEQWX3kzKpoPpeMrBfscRERERWSHcC+keCeQ0mTYVKATOjGgiEYl7hWNvJVhcRrdbLsESdO6TiIiItB3hnlSQB+zTZNpoYElk44hIvCt//WPKnnubTucdQ/Kg/n7HiSlmNsrMdOkJERGRtRBuAXUm8KCZfWpmT5rZZ8B04L/RiyYi8aa+uJSC868neeh6dDrzSL/jtHtm9oGZbRO6fxHwBPC4mV3qbzIREZH2K6wufM65t8xsXWBPoCfwCvCKc25pNMOJSHxZOv526guX0+PRa7GkcHsYy2oMAz4P3T8R2BEoAz4BrvIpk4iISLsW9ieUULH0cBSziEgcq3j/S0ofe4XsM48gZaOBfseJFQHAmdl6gDnn5gCYWSd/Y4mIiLRfYRVQZtYfmAxsDGQ0fs451zfysUQkngTLKig49zqS1u9LpwvG+B0nlnyMN+BPD+B5gFAxVehnKBERkfYs3Baox4DfgPOAiujFEZF4tHTS3dQtzKfXy7cTSE3xO04sORbvuF0AXBeaNgi4xa9AIiIi7V24BdRQYBvnXDCaYUQk/lR+9h0l9z9Hx5MOInXkcL/jxJqdnHP/GDDCOfeKmR3oVyAREZH2LtxR+D4ENolmEBGJP8HKagrOvobEdXrQ+dIT/Y4Ti+5fxfR7WjWFiIhIDAm3BepP4A0zew7vmlArOOfGRzqUiMSHouvup/b3hfR49iYCHdL8jhMzQqOmAgRC57Bao6fXBapaP5WIiEhsCLeA6gDMAJKAPtGLIyLxouqbOSy/40kyjxpN+vYj/I4Ta+YBDq9w+q3Jc3nAhNYOJCIiEivCvQ6UhsUSkYhxNbUUnHUNCbld6DLhNL/jxBznXAC8C+k653bwO4+IiEgsCfs6UGY2GDgQyHXOnWFmA4EU59z3UUsnIjGp6OaHqZnzO90fvZaErIw1LyAtouJJREQk8sIaRMLMDsIbSKIXcHRociZwY5RyiUiMqv5xHkU3PUTGQbvSYdet/Y4T08ysv5k9ZmY/mdn8xje/s4mIiLRX4bZATQR2cc59a2aHhKZ9B2wUnVgiEotcXZ3Xda9TFjmTzvQ7TjzQNfxEREQiLNwCqhtewQTeickNP93KZxcR+bfldzxJ9Xe/kHv/RBI6d/Q7TjzQNfxEREQiLNzrQH0FHNVk2qHAzMjGEZFYVTNvPkXXPUCHvXcgY59RfseJF7qGn4iISISF2wJ1JvCmmR0PdDCzN4ABwK5RSyYiMcMFgxScdQ2WlkLONef4HSee/Imu4SciIhJR4Q5j/rOZDQL2Bl4GFgAvO+fKohlORCInWFlN+Ssf4CqrW33b1T/Oo2rmbLrdPpbE3C6tvv04pmv4iYiIRFjYw5g75yrM7BPgD2CRiieR9qP294XkHTeOmh/n+Zahw17bk3HQbr5tPx7pGn4iIiKRF1YBZWZ9gUeBLYEioJOZfQEc4Zz7K4r5RGQtlb38AQVnXg2JCXSfPpmUjQf5kiOhR1fMzJdtxzNdw09ERCSywm2Bmo43kMTuzrlyM8sArgxN3zFK2URkLbjaOpZeeRfFdz5JyqaDyb1vIkl9uvsdS1pR6Bp+dwDPAocDZ+Bdw+8a4D8+RhMREWm3wi2gNgN2dc7VAjjnyszsImBp1JKJSIvVLVpC/gmXU/XlD3Q84QC6XHE6lpzkdyxpfbqGn4iISISFW0B9DowEPmk0bQTwWcQTichaqXj/S/JPuQJXVUPuPRPI2H9nvyOJf3QNPxERkQgLt4D6DXjVzF7BG4GvD7An8JiZTWyYScPiivjH1ddTdONDFE2ZRtLAfnSfNonk9fv6HUv81XANv4caTdM1/ERERNZCuAVUKvBc6H43oBp4Hkjjf0Pj6htNEZ/UFxaRf+qVVL7/JRkH70bX684j0CHN71jiP13DT0REJMLCvQ6UhsIVaaOqZs4m74TLCS4rpuuNF5B55GiNdieAruEnIiISDastoMysA4Bzrjz02IATgGHAZ865J6KeUERWyjlH8d1PsfSKO0nsnUuvV+8kZcMBfseSNsTMbnXOnQk81WT6zc65s/1JJSIi0r4F1vD8E8D/NXp8Pd7wtz2BW83svGgFE5FVqy8pI3/MOJaOm0qHXbem99v3qXiSlTl2FdOPas0QIiIisWRNXfhGEPpHa2bJwInAvs6598xsJN6JyTdEN6KINFY9ey75x4+ndv5iulxxOh1PPURd9uQfzOy40N3ERvcbrAsUtnIkERGRmLGmAirdObc8dH8EUOecew/AOTfTzHpEM5xIW1S/rJil46dS++ciX7Zf/d3PBLKz6PnCraRtuaEvGaTNa2hhSuafrU0OyAeOafVEIiIiMWJNBdQiM9vQOfc93qhNHzU8YWbZeKPxicSNqq9+JP/48dQVFJE6cjh+NPx02Gcnukw4jcSunVp/49IuOOdGAZjZJOfcZX7nERERiSVrKqCuxxsC91NgN/55PtRuwPfRCibSljjnKLnvWQovv53EHl3p9codpG48yO9YIqvVuHgKDQJkjZ4L+hJKRESknVttAeWcu9/M5uF137vROfdxo6crgSuiGU6kLQiWlrPk7Gspf+k90nfdmm63X0ZCdqbfsUTWyMx6ArcD2wPZTZ5OaPVAIiIiMWCN14Fyzn0AfLCS6S9FJZFIG1L902/kHzeO2j/+pvO4U8g+4zAssKbBK0XajLuBCmBnvOP49sAE4FUfM4mIiLRrYV1IVyQelTzxGoUX3kAgswM9n7uZtG028TuSSHNtDfR1zpWbmXPOfWdmxwOfAvf6nE1ERKRdUgEl0kSwsprCS2+m9JGXSd1mE3LvvpzE3C5+xxJpiXqgLnR/uZl1BUqAXv5FEhERad9UQIk0UvvH3+QdN46aH+aSffZRdL7oOCxRfybSbn0B7Ak8D7wBPIl3/uosP0OJiIi0Z2GfzGFmaWbWw8zSohlIxC9lr3zIwp2Pp25hHt0fvZYuY09S8STtkpmlm9lVeKPu7WhmKcDZwLvAD8DhPsYTERFp19ZYQJnZKDObCZQCC4FSM5tpZjtHPZ1IK3C1dRSOn0r+sWNJWr8vvd99gA67bu13LJG1MRUYDfyEN4DE9c65SufcJOfcRc65xf7GExERab9WW0CZ2Qi80Zq+AHYBhuBdUHcmMMPMNo96QpEoqltcwKL9zqT4zifJOv7/6DVjKkl9uvsdS2Rt7QHs6py7MHR/b5/ziIiIxIw19U+6ALjOOXd5o2m/AO+aWUHo+YOjFU4kmio+mEX+KVfgKqvJvWcCGfurUVViRoeGVibn3AIz6+h3IBERkVixpgJqK+CcVTx3L15LlEi74oJBim6cTtF100ga2I/uD1xJ8gbr+B1LJJISzWwU3jlQK3uMc+5dX5KJiIi0c2sqoLKdc4tW9oRzbpG+1ZT2pn7pcvJPvZLK92aScfBudL3uPAIdNC6KxJwlwAONHi9t8tgB67ZqIhERkRixtkOMuYikEGkFVV/+QN4JlxNcupyuN15A5pGjMbM1LyjSzjjn+vmdQUREJFatqYDqYGbzV/GcAekRziMScc45iu95hqUTbiexVzd6vXIHKRsN9DuWiIiIiLRDayqgdmqVFCJREiwtZ8mZV1P+8gek77Et3W67lISOmX7HEhEREZF2arUFlHPug9U9b2YJkY0jEjnVP84j/7hx1P61mC4TTqPjaYeqy56IiIiIrJU1Xki3MTN72sxONrPk0AASb0Qpl8haKXnsFf7e/WSC5ZX0fP4Wsk8/TMWTiIiIiKy15g4i8QawNXAuEAS+i3gikbUQrKym8OKbKH3sFdK225Rud11OYrfOfscSERERkRix2gLKzDYCipxz8wGcc/eZ2ZvAB0An4NioJxQJU81vC8g/fhw1P/5Gp/OOodMFY7AE9TIVERERkchZUxe+B4EODQ/MrA/wHnA3cAAwOWrJRJqhbMb7LPzPCdQtKqD741PofPEJKp5EREREJOLW1IVvXefcHAAz6wu8C1znnLs7NIDEk9EOKLI6rqaWpVfcSfE9T5Oy2RBy75tIUu9cv2OJiIiISIxaUwG1yMyOA/4C7gMudc49HnquL1AZzXAS+6q/+4Xy1z8G17JrMle8/yXVX/1ExxMPpMuE07DkpAgnFBERERH5nzUVUGfhdeOrAb4EjjCzRUA9MAV4fNWLiqxa44vbUlcPLRwhL5CdSe59E8nYd1SEE4qIiIiI/NuargP1JtCz4bGZXYxXNCUCTwPjo5pOYlKwtJwlZ11D+Yz3Sd89dHHbbF3cVkRERETavmYNY+6cuwa4JkpZJA40vrht58tP1fWZRERERKRdadaFdBszsw3N7OlIhpHY1vTitp3OOFzFk4iIiIi0K2u6DlQ6cAmwMTAXmADkADcAuwDToxtPYoEubisiIrJmdflLqf76J6q+8m41P84jdcRQOp5yMGnbbaYvHUXaiDV14bsd2AR4A9gDGA4MwiucTnTOFUY3nrR3/7i47bnH0OlCXdxWREQkWFVNzfe/UvX1T1SHCqa6BXnek4kJpAxdn/Rdtqbi3c+pOOAckoeuR8eTDybz//6DpST7G341guWV1C0uILF7DoGMdL/jiETFmgqo3YCNnXNLzOw2YD6wg3Puo+hHk/aubMb7LDnzaiwpke6PT6HDf7b0O5KIiEirc85R98ffVH31I1VfeQVT9Y/zoLYOgMTeuaRsOoSOJxxAymZDSNlwIIG0FMArtMqefZvldz1JwZlXs+zKu8k6fn86HrMvCTmd/HxZBEvLqZ49l+rvf6X6+1+o/v5XaufOh2AQgECXjiT17Uli3x4k9e0e+tmDxHV6kNgrl0Bqiq/5RVrK3Gquv2NmJc65rFU9DseIESPcrFmz1iKitDeuppalE++k+O6nSdl0MLn3X6mL20q7ZWZfOedG+J2jteiYLbL2nHPU/raAirc/p/KDL6n6eg7BZcUAWHoaKZsMInXTIaSOGELKpkNI7J4T1jorP5jF8jufpPLdL7DUZDIO2o3skw8ieWD/aL8k6otLqf7+V2q+/5Xq70LF0m8LVjyf0D2HlA0HkLLhAJL69aIur5C6+Yupnb+Yur8WU7swb0XB2HiZhoIqqU8Pr8BapwfJwzZo8ei88XbMFn+sqQUq0cxGASs63TZ97Jx7N0rZpB2q+zufvBMnUP3lD3Q84QC6XHG6Lm4rIiIxL1hRReXHX1Px9udUvPs5dX8tBiBpvT502H3bFcVS8qD+LerKbmak77g56TtuTs0vf1B8zzOUPvU6pQ/PIG2nLcg+9RDSdhix1udJufp66vMKqfn1L69l6btfqJ79K3V/LloxT2LvXFI2HEDmQbuRHCqaEnO7rH69wSD1eYXU/rXYK6wWhAqr+Yup+uw7yp59e0XLVe49E8jYf+e1eh0i0bSmFqg/gVXPAM45t+7qNqBvM+NHxbtfkH/qlbjqGrrdfDEZ++3kdySRtRZv32bqmC0SnsatTBXvfE7VZ9/hqmuw9FTStt2U9J23JH3nLUhap+eaV9ZC9YVFlEx/ieL7n6O+YBnJg9el40kHkXHgLqvsHueco76giLoFjVqH5i+mbkHeSluKEvv1JGX4AFI2Gui1MA3fICpdB11tHXV/L6F2/iKSB63b4sGm4u2YLf5YbQEVCfpnHPtcfT1FN0yn6PoHSR7Un9wHriR5/b5+xxKJiHj7Z6xjtsiqBcsrqfzkayre/uKfrUwbrEP6zluQvvOWpG65Yauf2+Oqayh9/h2K73qKmh/nEcjJpuOY/Ukesp7X2vPX4v8VTAvycBVV/1g+kJNNUsP5SX1CXerW7U3K8AHt7kL38XbMFn9EvYDaML2TmzHQh2bYxESyTz2ErDH7tdqwn8GyCgovu5XKD+Lrw4errqG+oIiMg3en65TzCKSn+h1JJGLi7Z+xCiiJJa62jor3v6Ts+bep/X0hlpLc5Jbk/UxOwlKTseRkAinJkJJEICV5xbT6omIq3vnCl1am5nDOUfnx1xTf9RQVb366YnogK2PF+UWJfbr/77yjvj1J7J0bU6PlxdsxW/yxpnOg1logI520bTeN9mb+pfaPvym86EaqPv+OrjdeGPWDQ82vf5I35jJq586nw+gd466ISNt+MzIO3FXXqBAREV8556ie9SOlz7xF2UvvEixcTiA7k5SNBuJqagmWlOGqanA1tbjqGlxVdaP7NbCKL5aTNliHrDH7+dbKFA4zI327zUjfbjNq/1xEsLiUxHV6trtWJJG2LuoFVGLfHnS77dJob+ZfXDDI8lseYdk191P9wzy6P3AlyYOiM0pN6bNvUXDuFCw9hR5P30j6DvriQ0REpDXV/PqnVzQ99xZ1fy3GUpNJ321bMg/chfRRI8O6dpJzDurqvWKqOlRkVdVgqckk9ujaCq8icpL6tY1WMZFYFPUCyi8WCNDpnKNJ3XwY+SddwcLdTqLr9eeTedBuEduGq66hcNxtlEx7gdQtNiT33gnt7gArIiLSXtUtLqDs+XcofeZNambPhUCAtO03o9P5Y8jYa3sCmR2atT4zg6RELCkRYqhbm4hEVswWUA3Stt2U3u/eT/5JE1hy2iSqvphNl0n/Xeum99r5i8k/fjzV3/5Mx9MPpcvYk70DroiIiERNfXEp5TM+oPTZt6j65BtwjpRNBtNl0plk7LfTGofTFhFZW3HxiT+xew49n7uZZVfdx/LbHqXqmzl0v//KFjdvl7/5CUtOnwxBR/fpk+mw5/YRTiwiIiLB8krq8gqoX1xI7fzFVLz5KeVvfQY1tSSt25tOF4wh4//+Q/J6ffyOKiJxJC4KKABLTKTL+FNI3WI4S06fxMKdj6fb7WPpsPu2Ya/D1dWx7Or7WH7royQP38Arwvr3imJqERGR2OOcI1hcRt3iAuoXFVC3aAl1eYXez0UF1C8uoG5xAcHlpf9YLqFbZzqO2Y+MA3YhZeNBGrhIRHwRNwVUgw67bUPvd+4n//jx5B11Cdn/PZzOl56IJa7+rajLKyT/5Cuo+vRbso7ehy6Tz2yTI/CIiIj4IVhVTXBZMfWFy6lfVkz9smKCS0P3lxaHfi5fURw1vRYRZiR07URiz24k9utJ6lYbk9izK4k9ckjs2Y2EHjkk9euFJST48wJFRELiroACSFqnJz1fvp2l46ey/LbHqPryR28AiO45K52/8pNvyD9xAsHyCrrdPpbMg3dv5cQiIiJrz9XXU/vn39QvLvRGmKurw9XWQ21d6H4dhKb9737ouZrQ4+pa6ou8Qim4rHhFgeQqKle+UTMCnbJI6NyRhM4dSR62Aem7bu0VRj26kdizKwk9upKY2wVLTmrdN0REpAXisoACCKSm0PW680jdYkMKzr2OhTsdR7e7xpO+/f+GIHfBIMtvfZRlV99H0rq96fnczVEbCl1ERCRSvEJpEbW//EHNz39S8+uf1Pz8B7Xz5uOqa1q20oYR6pKTSOjSkYTO2STkdCJpYD8SumR7BVKXjgQ6h+7neD8D2ZlqNRKRmBK3BVSDzAN2IWXY+uQdN47FB51H5wuPI/ucowgWl7Hk9ElUvPUZGfvv3CoX4xURkfbFBYO4ympcZRXB0E9XWU2woqrJtCqCFY2eD02zlGQCWRkEsjoQyAz9zMog0DGDQKZ3PyGrwyqvYeTq66n7a/GKAqkmVDDVzvvLuyhsSGLvXJIH9idtxxEkD+xPUt8e3sixSYlYYmjY7qSE/90P/fTuJ3j3VQSJiAAqoABIHtif3m/cQ8H517Psmvuo/Pw7an9bQF1eITnXnEPWcfvrRFURkRhUt2gJNXPnEyyrwJVXECyrJFhegSurJFhWQTA0bcVzZRW48obnKlfdbW11zLD0VCwtBVdVgyurWPMiKcmhIqsDgY6ZBLI6UL+s2GtRqqxeMV9ir24kDexP2vabkTywH8mD+pM8oJ++ABQRiSAVUCGBjHS63TmO1C03pHDsrSR260yvl28nddMhfkcTEZEoKXvxXZaOv/3fT5hhHdIIZKQTCP20jHQSe3b17jd6ztJTCaSlYmmpWHrKivuBtBQsPQ1LSyGQ/r9pJCf940s5V19PsLSCYEkZwZJy72dp+Uoee/fri73HCTmdSNt2U5IH9veKpYH9mn3hWBERaT4VUI2YGR2P3Y/0/2xFQqj7hIiIxK6MfUaRsvHg/xVJDT/TU1ut54ElJJCQnUlCdmarbE9ERNaOCqiVSOqd63cEERFpBYm9cknspWO+iIiEL+B3ABERERERkfZCBZSIiIiIiEiYVECJiIiIiIiEyZxz0d2AWSnwS1Q3IvEsByj0O4TEtIHOubg5u1/HbGkFOm5LNMXVMVv80RqDSPzinBvRCtuROGRms7R/STSZ2Sy/M7QyHbMlqnTclmiKw2O2+EBd+ERERERERMKkAkpERERERCRMrVFA3dMK25D4pf1Loi3e9rF4e73S+rSPSTRp/5Koi/ogEiIiIiIiIrFCXfhERERERETCpAJKREREREQkTM0uoMysj5m9Z2ZzzOxHMzsrNL2zmb1lZnNDPzs1WuYSM5tnZr+Y2W6Npm9mZrNDz91qZhaZlyXtVXP3LzPrEpq/zMymNlmX9i/5lxbsY7uY2VehfekrM9up0bra/D6mY7ZEm47bEk3xdsyW9qElLVB1wHnOucHAlsDpZjYEuBh4xzm3AfBO6DGh5w4FhgK7A3eYWUJoXXcCJwEbhG67r8VrkdjQrP0LqALGAeevZF3av2RlmruPFQKjnXPDgWOAhxutqz3sYzpmS7TpuC3RFG/HbGkHml1AOecWO+e+Dt0vBeYAvYB9gemh2aYD+4Xu7ws84Zyrds79AcwDRppZDyDLOfeZ80ayeKjRMhKnmrt/OefKnXMf4/1DXkH7l6xKC/axb5xzi0LTfwRSzSylvexjOmZLtOm4LdEUb8dsaR/W6hwoM+sHbAJ8AeQ65xaDt7MD3UKz9QIWNFpsYWhar9D9ptNFgLD3r1XR/iVr1IJ97ADgG+dcNe1wH9MxW6JNx22Jpng7ZkvbldjSBc0sA3gWONs5V7KabqQre8KtZrpIc/avVa5iJdO0f8kKzd3HzGwocC2wa8OklczWZvcxHbMl2nTclmiKt2O2tG0taoEysyS8nfhR59xzocn5oebRhmb4JaHpC4E+jRbvDSwKTe+9kukS55q5f62K9i9ZpebuY2bWG3geONo591tocrvZx3TMlmjTcVuiKd6O2dL2tWQUPgPuB+Y4525s9NRLeCfrEfr5YqPph4b6n/bHO2lvZqi5tdTMtgyt8+hGy0icasH+tVLav2RVmruPmVk28ApwiXPuk4aZ28s+pmO2RJuO2xJN8XbMlvbBvPPomrGA2bbAR8BsIBiafClef9SngL7AfOAg59yy0DJjgePwRlI52zn3Wmj6COBBIA14Dfiva24giSkt3L/+BLKAZGA5sKtz7iftX7Iyzd3HzOwy4BJgbqPV7OqcW9Ie9jEdsyXadNyWaIq3Y7a0D80uoEREREREROLVWo3CJyIiIiIiEk9UQImIiIiIiIRJBZSIiIiIiEiYVECJiIiIiIiESQWUiIiIiIhImFRAiYiIiIiIhEkFlIiIiIiISJhUQImIiIiIiIRJBZSIiIiIiEiYEqO9gZycHNevX79ob0ZEJCq++uqrQudcV79ztBYds0WkPYu3Y7b4I+oFVL9+/Zg1a1a0NyMiEhVm9pffGVqTjtki0p7F2zFb/KEufCIiIiIiImFSASUiIiIiIhImFVAiEtNqF+T5HUFEQmrnL/Zlu845nHO+bFtEYo8KKBGJSfXFpeSfPpkF2xxJ7e8L/Y4jEveqZ89lwTZHsvzOJ1p1u8GqahYfcj5/73oS9cWlrbptEYlNKqBEJOZUvDeTBdsdQ9mzb5F9+mEk9s71O5JI3Esesi7pu2zN0vG3U/rk662yTVdXx5JTJlL53kyqf5xH3hEXE6yoapVti0jsUgElIjEjWFZBwQXXs/jg8whkptPr9bvofNHxWHKS39FE4p4lJJB75zjStt+MJWddQ/mbn0R1e845Cs6/nvJXPqTL5LPIvXM8VTNnk3/i5bjauqhuW0RimwooEYkJlZ9+y4Idj6Vk+kt0PP1Qer9zP6kbD/I7log0YinJdJ9+FSnDNyD/+PFUfv591La1bPI9lD76Cp3OPYbskw4kY99R5Fx3LhVvfkrBOdfigsGobVtEYpsKKBFp14KV1RSOu41F+50JFqDnS1PJmXA6gdQUv6OJyEoEMtLp8fh1JPbKJe/Ii6j+6beIb2P5XU+y/JZHyDpmXzpdfPyK6R2P3Y9OFx9P6ZOvs3TinRHfrojEBxVQItJuVX39Ewt3Pp7iu54ia8z+9Hl/Gmlbbuh3LBFZg4ScTvR4+kYsPY3FB59H7V+LIrbu0qdeZ+m4qXQYvSM5156Dmf3j+U7nHkPW8f9H8e1PUHTboxHbrojEDxVQItLuuJpall51L3/veRquopIez9xE12vPIdAhze9oIhKmpD7d6fnUDbjqGhYfdB51S5at9TrL3/yUJWdeQ9p2m5J75zgsIeFf85gZOVedRcb//YdlE++i5NFX1nq7IhJfEqO9gT+XLeL4J66I9mZEJE4EyyupmTcfV15JwhnrkdS/F7b4FXhCH4JE2pvkQf3p8dh1LDrwHBYfej69XryNQGaHFq2r8ovvyT9hPCnD1qf7Q1djKcmrnNcCAbrddin1RSUUnHsdCZ2z6LDHdi19GSISZ9QCJSLtgnOO2oX5VH//K9TUkjx4XZLX77vSb5hFpP1I3XwY3R+YRM2c31l81CUEq6qbvY7qn34j74iLSOzZjR5PTCGQkb7GZSw5ie7TJpGyySDyT5xA5afftiC9iMQji/aVuUeMGOFmzZoV1W2ISGyrmfsXS86YTPXXc8jYbydyrj2XhM4dW2XbZvaVc25Eq2ysDdAxW/xS+uxbLDllIh322p7c+67AEsPrJFP71yL+3us0MKPXq3eS1Kd7s7Zbv6yYv0efTv3iQnq+eBspwzdoSXxpI+LtmC3+iHoXPhGR5nDOUZ9XSM3Pf1Dz8+/U/PQ7ZS+8g6WlknvPBDL239nviCISBZkH7EL90mKWjr2FggtuoOuNF/5rAIim6gqKWHzQebjqGnrNuL3ZxRNAQueO9HzqBv7e6zQWH3I+vV65g6T+vVr6MkQkDqiAEhHf1BUUUfPz79T+/Ac1v/xJzZzfqfnlD4LFZSvmCeRk02HP7eky8QwSc7v4mFZEoi37pAMJLl1O0Y3TSeiSTZfLTl7lvMHSchYfch51eQX0fOYmkgf1b/F2E3vl0uPpG/l779NZdPC59JpxO4ndc1q8PhGJbSqgRCTqgmUVVM+eS80vf1Az5w/v58+/E1xavGKeQHYmyYPWJWP/nUke2N87x2lgPxJyOvmYXERaW6eLj6d+6XKW3/IICTnZZJ9yyL/mCVZVs/joS6mZ8zvdH76G1JHD13q7yRusQ4/Hr2PR/mez+NAL6PnirSR0zFzr9YpI7FEBJSJRESyroPyNTyh78V0q3vkCamoBsIx0kgf1p8Me23mF0iDvlpDbZY3ddUQk9pkZOdeeQ/3S5SwdN5WEzh3JPHj3Fc+7+nqWnHIlVR9/Tbc7x9HhP1tGbNupmw6h+/TJLD78QvKOvIQeT91AIE0X5RaRf1IBJSIRE6yoouKtzyh74R0q3v4MV1VDQo+udByzH2k7bE7y4HVJ7NVNhVIrMLMEYEugJ7AI+Nw5V+9vKpHwWEICuXeNZ/FhF7DkzGsIZGfRYdetcc5RcMENlL/yAV0mnUnmgbtGfNvpO25O7h3jyD9pAvknTaD7tCvDHtBCROKDjggislaCVdVUvvsFZS+8S/kbn+IqKkno2pnMI/YmY7+dSR05DAvoigmtycw2BF4AUoGFQG+gysz2d85952c2kXBZSjLdH7qaRfudSf4J4+nx9I1UvP05pQ/PIPvso8g++aCobTtjv52oX1ZM4UU3UnDuFLrecrG++BGRFVRAiUizuZpaKt7/0uue99rHBEvLCXTpSOZBu5Kx306kbrWRrs/krweA24EbnXPOvE9+54Smb+ZrMpFmCGSk0+OJKfy99+ksPvAcXFUNmUeNpvOlJ0Z92x2P25/6pcspuu4BEnKy6TL+1KhvU0TaBxVQIhIWV1tH5UdfUfbie5S/+iHB5aUEOmbQYfSOZOy3E2nbbool6ZDSRgwAbnahC/2FiqhbgAm+phJpgYScTvR4+kYW7XcmqZsOpuuU81qtNajT+cdSn7+U5bc9Rsb/7ULKsPVbZbsi0rbp046IrFHVrB/JO24c9YsLsIx0Ouy5HRn77kT6jptjyUl+x5N/exXYB3i+0bTRwCv+xBFZO0l9utN35uOt3rJtZnS+7GRKn36T5Xc8Tu4d41p1+yLSNqmAEpHVKnv+HZb89yoSeuSQ++Bk0nfegkCqRqVq4xKAJ8zsK2AB0Aev696LZvZQw0zOuaN9yifSbH51C07IziTr6NEU3/csXcaeRGKvXF9yiEjboQJKRFbKOcfyGx9i2TX3kbrFhnSfPpmELtl+x5Lw/BC6NfgJeMOnLCLtXseTD6b43mdZfvfT5Ew8w+84IuIzFVAi8i+uuoYl515H2VNvkHHQrnS76SIsJdnvWBIm59wVfmcQiSVJvXPJ2H8nSh56iU7nHaML7IrEOY0tLCL/UL90OYsOPJeyp96g08XH0+32y1Q8tUNmlmxmw81slJnt1HDzO5dIe5V9+uG48kpKHnzR7ygi4jO1QInICjVz/2Lx4RdRv7iA3HsmkLH/zn5HkhYws22Bp4EUIAsoATLxzoda18doIu1WyrD1Sdtxc4rveZrsUw7WF0sicUwtUCICQMVHX/H3Hqfgyivo+cKtKp7at5uA65xznYHS0M8rgTv8jSXSvmWfcTj1S5ZR+vSbfkcRER+pgBIRSh6eweKDzyOhR1d6vX43qSOG+h1J1s4A4JYm067Bu5iuiLRQ2vabkTxsA5bf8QQuGPQ7joj4RAWUSBxzwSBLr7iDgnOvI227zej1yh0k9e3hdyxZe8V4XfcAFpvZEKATkOFfJJH2z8zIPuMwauf+RcVbn/kdR0R8ogJKJE4FyyvJH3MZy6c+TtaY/enx2LUkZOnzdYx4DtgzdP9+4D3gK7zzokRkLWTsM4rEPt1ZPvVxv6OIiE80iIRIHKpbXMDiIy+m5od5dJl8Fh1PPAAz8zuWRIhz7uxG928ws5l4rU+6FpTIWrKkRDqefDBLL7uVqlk/qsuzSBxSC5RInKn+/lcW7nYytb8toPvDV5N90oEqnmKcc+4j59xrzjmdtCESAVlH7EUgO1OtUCJxSi1QIu1MsKoaXMuWrXzvC/JPvZKETln0euUOUoauH9lw4isz2xzYwzk3MfR4Dt5Q5g0Ods7N8iWcSAwJZKSTdex+LL/lEWp+W0Dyen38jiQirWi1BZSZPUwYH9Wcc0dHLJGI/EvNb/Mpe+Fdyl98j5o5v6/VulI2GUz3h64isXtOhNJJG3IB8ESjxz2B/wvd3xy4CDiotUOJxKKOJxxA8Z1PUnzXk3Sdcr7fcUSkFa2pBWpeo/s5wDHADOAvoC8wGpgenWgi8a32r0WUvfAuZS+8S80PcwFI3WJDOl10HJbcsgs4BjLSyTx0DwLpqZGMKm3HSLzjdIOgc+4dADP7GPjZl1QiMSgxtwsZB+9G6eOv0enC40ns2snvSCLSSlZbQDnnrmi4b2ZvAHs55z5qNG1bYFz04onEl7q/8yl78T3KXniX6m/mAJCy2RC6XHmGN/JTz24+J5Q2rgtQ1ejxjo3u1+J9ESYiEZJ92qGUPvIyJfc/S+eLT/A7joi0kuacA7Ul8HmTaV8AW0Uujkj8qcsrpOyl9yl/4R2qvvwBgOQNB9B5/Clk7LuTrsskzVEIDALmADjnvmv03GBgqR+hRGJV8vp9Sd99G4ofeJ7s/x5BoEOa35FEpBU0p4D6BrjKzMY75yrNLA24Avg2KslEYlhdQRHlL79P2QvvUvXZd+AcyUPWpfMlJ9Jh31E6IVla6nngZjPb1zm3oiUqdLy+Ae/6UCISQZ3OOJy/X/uY0sdeoeOJB/odR0RaQXMKqGOBx4BiMyvCu6r9LOCIKOQSiTn1RSWUv/wBZS++S+VHX0MwSNIG69Dp/GPJ2G8nkgf08zuitH/j8S6a+1uo23Ue0APYFVgMXO5jNpGYlDpyOKmbD2P5XU+RNWY/LFEDHIvEurD/yp1zfwJbm1kfvJGdFjvn5kcrmEgsqC8po/zVjyh/4V0qPvgS6upJ7NeL7DOP8IqmIevpGkwSMc65MjPbBjga2Blv5L2lwATgIedctY/xRGJW9hmHkXfMWMpnfEDG/jv7HUdEoqwlX5NUAwVAopmtC+CcW7txlUViSLCsgvLXP6bshXepeG8m1NSS2Kc72aceQsa+O5G84QAVTRI1zrka4L7QTURaQfru25K0Xh+W3/44HfbbScd4kRgXdgFlZrsD9+N1B2nMAQmRDCXS3gTLK6l46zOvaHrnM1xVDQk9utLxuP3J2G8nUjYdon+oIiIxygIBsk8/lIJzp1D58dekb7eZ35FEJIqa0wJ1O3AlMN05VxmlPCLtRrCqmop3vqD8hXcof/NTXEUVCd06k3nE3mTstzOpI4dhgYDfMUVEpBVkHLQby66+n+VTH1cBJRLjmlNAdQLuds65aIURaQ9cbR1Lx0+l5InXcGUVBLp0JPPg3byiacsNsQQ1yIqIxJtAagodTziAZVffS/WP80gZur7fkUQkSprz9fj9wJhoBRFpD1xdHfmnTKT4vmfpsOf29Hj6Rvr98AJdp5xP2jabqHgSEYljWWP2w9LTWH7HE35HEZEoau6FdM80s4vxhsZdwTm3fURTibRBrr6eJadPpvyl9+gy8XSyTz3U70giK5jZw3jnpK6Wc+7oVogjEpcSOmWRdeTeFD/wHF0uPZHEXrl+RxKRKGhOC9R9wEnAZLzWqMY3kZjm6utZcubVlD33Np3HnaLiSdqiecBvoVsxsB/eAD8L8Y71+wLLfcomEjc6nnIwOFh+zzN+RxGRKGnOdaCmRzOISFvlgkEKzrmOsqfeoPMlJ9LpTF07Wtoe59wVDfdDF9Hdyzn3UaNp2wLj/MgmEk+S+nQnY99RlDz0Ep3OPZqEjpl+RxKRCGvWEGFmlmtmo81sjJkd13CLVjgRv7lgkILzr6f08VfpdMEYOp2r3k/SLmwJfN5k2hfAVj5kEYk72acfhiuroGT6S35HEZEoCLuAMrP98LqGTATuBv4b+nlUVJKJ+Mw5R+HFN1H68Ayyzz6KThdoDBVpN74BrjKzNIDQz8nAt36GEokXKRsOIG2HERTf8zSuusbvOCISYc1pgZoEjHHObQKUh36eBHwVlWQiPnLOsXTsrZRMe4HsMw6j86Un6kK40p4cC2wDFJtZPt45UdsCx/gZSiSeZJ9+GPX5Syl99i2/o4hIhDVnFL6+zrmnm0ybjjci3/mRiyTiL+ccSyfcQfG9z9Dx5IPoPP5UFU/Srjjn/gS2NrM+QE9gsXNuvr+pROJL2o6bkzx0fZbf/jjJg9dt0TosECB56HpYYnM+rolItDXnL3KJmeU65/KBP81sK6AQb5QnkZjgnGPZlXdTfMcTZB3/f3S58r8qnqQ9qwYKgEQzWxfAOff76hb4c9kijn/iitXNIiJhqjuwI7W//gXTLm3xOpL69SKxZ9cIphKRtdWcAupevC4gzwI3Ae8BQeCGKOQS8UXRNfez/LZHyTp2X3KuPlvFk7RLZrY73iUmejR5yqEvvURaTUJOJywpCYLBFi1f+8dC6otLVUCJtDHm3Bqvu7jyBc36Ah2cc3NWN9+IESPcrFmzWrQNkda07PppFF37AJlH7k3XGy7AAs0apFJilJl95Zwb4XeO5jCz34ApwHTnXGVzltUxW6TtWHLWNZS/9hH9fnlZX+iFqT0es6X9ae4w5glmto2ZHQT0AX6NTiyR1lV000Ne8XTI7iqeJBZ0Au5ubvEkIm1L6sjhBItKqJ2nUxhF2pLmDGO+ITAXeBq4IPRzrpltFKVsIq2iaOpjLLvqXjIO3IWut1ys4kliwf2Axt0XaedSRw4DoOqL2T4nEZHGmvNJ8QHgdqCXc24k0AuYGpou0i4tv+tJll1xJxn77US32y7FEnR6iMSELYE7zexXM/uw8c3vYCISvqT1+xLolEXVlz/4HUVEGmnOIBIDgJtd6KQp55wzs1uACdEIJhJtxfc9y9JxU+mw9w50u3OchomVWHJf6CYi7ZiZkbr5MKpmqgVKpC1pzifGV4F9gOcbTRsNvBLRRCJRFiwtp3D8VEofeZn0PbYl954JKp4kpjjnpvudQUQiI3XkcCre/JT6pctJ6JLtdxwRYQ0FlJk9jDfsLXhD3z5hZl8BC/AGkdgMeDGqCUUiqOKjryg482rqFhWQfeYRdL7oeCxJxZPEHjPLBUYCOcCK4bucc+p2LdKOpI4cDkDVrB/psNs2PqcREVhzC9S8Jo8bd8L9CXgjsnFEoiNYUcWyK++i+L5nSVqvD71euYPUEUP9jiUSFWa2H/AI3sA/Q4EfgWHAx+i8VZF2JWXjQZCUSNUXs1VAibQRqy2gnHO6HL20e1UzZ7Pkv1dR+/tCOp50EJ3HnkQgPdXvWCLRNAkY45x72syKnHObmNkYvGJKRNqRQFoKKRsO0EASIm3Imrrw7RTOSpxz70YmjkjkuOoall37AMtvf5zEXt3o+fwtpG27qd+xRFpDX+fc002mTQfygPN9yCMiayF15HBKpj2Pq6nFkpP8jiMS99bUhe/+Jo974Z0TtRTogtevfiGwbuSjibRc9Xe/kH/GZGp//oPMo0aTM/EMAhnpfscSaS1LzCzXOZcP/GlmWwGFeOeyikg7k7r5MIrvfJLq739V93ORNmBNXfj6N9w3s0vxiqZxzrkKM0sHJuIVUyJtgquto+jmhym6cToJOZ3o/vgUOvxnS79jibS2e4FtgWeBm4D3gCBwg5+hRKRlUjcPXVD3y9kqoETagOYMP3YO0NM5VwsQKqIuARYBV0cjnEhz1Pz8B/mnT6Lm+1/JOGhXcq46m4TsTL9jibQ659y1je4/ZGbvAx2cc3P8SyUiLZXYPYfEdXpQ9cUPcKrfaUSkOQVUOd6QuJ80mrY5UBHRRCLN5OrrWX7nkyy7+j4CWR3InTaJjL138DuWiK/MLAHYEuiJ90XX5/4mEpG1kTpyOJXvz8I5h5mteQERiZrmFFDjgNfNbAb/uw7U3sDp0QgmEo6a3xZQ8N+rqPryBzrstQM5U84jsWsnv2OJ+MrMNgReAFLxzlPtDVSZ2f7Oue/8zCYiLZM6cjhlT79J3V+LSerX0+84InEtEO6MzrmHgS2AOUAW8DOwZWi6SKsrf/1jFu50HDW//km3O8eRO+1KFU8ingeA24FezrmReAMATUXXgBJpt1acBzXze5+TiEhzWqBwzv2EdwFdEV+Vv/kJeceNI2X4BnR/cDKJPbr6HUmkLRkA3OyccwDOOWdmtwATfE0lIi2WPKg/gcwOVM38gcyDd/c7jkhca1YBZWb7ADsAOXhDmAPgnDs6wrlEVqninS/IGzOOlKHr0+PpG0nIyvA7kkhb8yqwD/B8o2mjgVf8iSMia8sSEkgZMZSqL2f7HUUk7oXdhc/MLgfuDi1zEN7w5bsBy6OSTGQlKj6YRd4xl5I8sJ+KJ5FGzOxhM3vIzB7Cu97TE2b2qZk9aWafAk+i60CJtGupI4dRM+cP6otL/Y4iEtea0wJ1HLCLc+4HMxvjnDvHzB4HLotSNpF/qPz4a/KOupik9fvQ85mbNES5yD/Na/L4h0b3fwLeaMUsIhIFqSOHg3NUf/UT6Ttt4XcckbjVnAIq2znX8A+5xsySnHMzzUzjRUvUVX76LYuPuIjEdXp6xVPnjn5HEmlTnHNX+J1BRKIrddMhEAhQNXO2CigRHzWngPrNzIY6537E+2bzVDMrAoqiE03EUzVzNosPu5DEXrn0fPZmEnI00p5IU2a2UzjzOefejXYWEYmOQEY6yUPXo2qmzoMS8VNzCqjLgC6h+5cAjwIZwGmRDiXSoOqrH1l0yPkk9sih53M3k9its9+RRNqq+5s87gU4vPNVu+AN/LMQWLeVc4lIBKWOHE7p46/h6uqwxGaNBSYiERL2X55z7tVG978A1o9KIpGQqm9/ZvFB55GQ04mez99CYvccvyOJtFnOuf4N983sUryiaZxzrsLM0oGJeMWUiLRjqSOHU3L/c9T8+BspGw30O45IXGruMOYbAIfhfbP5N/C4c25uNIJJfKv+/lcWH3gOgc5Z9HrhFl3nSaR5zgF6OudqAUJF1CXAIuBqX5OJyFpJHTkc8Lq3q4AS8UdzhjEfDXwFDAKWAQOBWaFrQ4lETPWP81h04DkEMjvQ87lbSOyV63ckkfamHBjZZNrmQIUPWUQkgpJ655LQsxtVX/6w5plFJCqa0wJ1FbCvc+69hglmtiMwFXgpsrEkXlXP+Z1FB5yNpaXS8/lbSerbw+9IIu3ROOB1M5sBLAD6AHsDp/uaSkQiInXzYRpIQsRHYbdAAb2Bj5pM+zg0XWSt1fz6J4sPOBtLSqLnczeT1K+n35FE2iXn3MPAFsAcIAv4GdgyNF1E2rnUkcOp+3sJdX/n+x1FJC41pwXqW+A84NpG084NTRdZKzW/zWfR/meBGT2fv4Xk9fr4HUmkXXPO/YR3AV0RiTGpI4cBUDXzBzL2Vzd3kdbWnALqVGCGmZ3F/7qElAM6B0rWSu3vC1m031m4YJBeL9xK8vp9/Y4k0u6Fzk/dAcjBG8IcAOfc0b6FEpGISBm6PpaeStXM2WTsv7PfcUTiTlhd+MwsAPQENgEOBm4I/RzinJsTvXgS62rnL2bR/52Fq6ml53O3kDyw/5oXEpHVMrPLgbvxjvEH4Q1fvhuw3MdYIhIhlpRIyqZDNJCEiE/CKqCcc0HgRedcmXPuY+fcU6GftVHOJzGu8MIbCZZW0PPZm0kZrOt7ikTIccAuzrlzgJrQz9FAP19TiUjEpG4+jOof5hEs0+CaIq2tOYNIfGhmW0YticSdmp//oOKdz8k+7VBShum6zCIRlO2ca/hqusbMkpxzM/G69IlIDEgdORzq66n6Rh2BRFpbc86B+gt4zcxexDsHyjU84ZwbH+lgEvuW3/kklpZC1pj9/I4iEmt+M7OhzrkfgR+AU82sCCjyOZeIREjq5kMBqJ75A+nbbeZzGpH40pwCKg14IXRfQ5fLWqnLK6T0mTfJOnI0CZ07+h1HJNZcBnQJ3b8EeBTIAE7zLZGIRFRCx0ySBvWncuZsOvkdRiTOhF1AOefGNNw3s27AtsAcDSIhLVF8/3NQW0f2KQf7HUUk5jjnXm10/wtAfWRFYlDayOGUvfAuLhjEAs05K0NE1sYa/9rMrJeZPWdmP5vZNDMbindxxruA78zs0KinlJgSLKug5MEX6LDX9iT17+V3HJGYZGYbmNl4M7s79HMDvzOJSGSlbD6MYEkZNb/86XcUkbgSztcVd+H1mz8H71oibwAnOOe64Q2Pe2n04kksKn38VYLLS8k+/TC/o4jEJDMbDXwFDAKWAQOBWaFrQ4lIjEgbORyAqpmzfU4iEl/C6cK3NdDDOVdjZh8AxYTOhXLOvWhmD0Uxn8QYV1fH8rufInXkcFJHDPU7jkisugrY1zn3XsMEM9sRmAq85FMmEYmwxP69SOjaiaqZP9DxmH39jiMSN8JpgUpyztUAOOcqgFLnnGv0vK18MZF/K3/lI+r+Wkz26er5KRJFvYGPmkz7GA0AJBJTzIzUzYepBUqklYXTApVoZqP4X6HU9HFCVJJJzHHOsfz2x0latzfpu23jdxyRWPYtcB5wbaNp54ami0gMSR05nPJXP6JuyTISu3X2O45IXAingFoCPNDo8dImj5dENJHErKrPv6f6mznkTDkPS1DdLRJFpwIzzOwsvOv29QHKAZ0DJRJjUhvOg/ryBzL22t7nNCLxYY0FlHOuXyvkkDiw/I4nCHTpSObBu/sdRSRmmVkA6AlsAmwcur8I+MI5V+tjNBGJgpQNB2ApyVTNnK0CSqSVNOdCuiItVjNvPhWvf0yn848lkJ7qdxyRmOWcC5rZi865TLzznkQkhllKMikbDdR5UCKtSFddk1ZRfOeTWEoyWcf9n99RROLBh2a2pd8hRKR1pI4cRvV3vxCsqvY7ikhcUAuURF1dQRGlT75O5iG7k9i1k99xROLBX8BrZvYi3jlQK0ZOdc6N9y2ViERF6sjhMPVxqr/9hbQtN/Q7jkjMUwuURF3JA8/hqmvoeOohfkcRiRdpeNfrc3hDl/cJ3TSMuUgMSt18GP/f3r3HVlnfcRz/fHvjUNp6lEvpAO/ouHQLDjunzGzLZERnWOYQdIzN3Qw6p1Pm5mXZIsk2I5rFTTSGGS8xXBa8JZMZNCxujllQthS5TCYbIgUG2FLAU3r57o8+6hFbe057nvNwzvN+JU3P+T2370m+/bbfPs/zeyQptY7L+IB84AwUQtV9JKXWh55U5Yxpqjjz5KjDAWLB3a+KOgYA+VM64kSVnz5WqcaNOdlf5+59OvLnddIHHvuZP0MvmKLyk+siOTaQCRoohKpt+Sp1H2hV8hoenAtEwcxGSZomaZO7b4k6HgDhSDTU6/Dqv8ndZWb9b9CHzl179dbF89X5VnRPqaldcgcNFI5rNFAIjXd1qfX+FRpyzgQluCYbCJ2ZjZH0W0kTJa2VtEjSi5K6JCXNbJ67L4swRAAhSTTUq23ZKnW88aYqzhjYFR9dB1q1a9aN6j54WB976l6VjRud4ygzUzo8GclxgUzRQCE0h//0kjq271TtbXcM6r9hADL2gHoebv4jSbMlPSfpu+7+pJnNlLRQEg0UUIQSDcF9UC83DaiB6j78jpqvvFmd/21W3fJFGnrBlFyHCBQNJpFAaFrvW6qyU+o07JLPRh0KEBfnS5rv7qskXSOpVj2TScjdn5Z0SnShAQhT+fhTVJKsHtDzoPxoh3ZfdbvaN2xR7YM/p3kC+kEDhVCkGpuUWrdRyasvl5VxohPIk3J3PypJ7n5EUpv7B+4C51QwUKSspESJqZOUWpfdRBLe3a291/1S76xp1Mi7f6xhF18YUoRA8eAvW4SiZfFylSSrVX3FxVGHAsRJmZl9Xu83Sse+L40mLAD5kGio15Hn/66utw+q9MSaftd3d+2/7V4deuJ5nXT71aqZ++U8RAkUPhoo5FzHGzt1+NkXlbx+rkqqKqMOB4iTvZIeSnu//5j30U2rBSB0iYZ6SVJq3UYNm35+v+u33POoWpes1AnzZyv5w6+HHR5QNGigkHMtD6yQyst0wne+GnUoQKy4+6lRxwAgOkOmTJDKSpVqbOq3gWp9+Ckd+PUSVV0+Q8N/cQ2TPQFZ4B4o5FTX/ha1LXtW1V+brrLRI6IOBwCA2CipTGhI/Vn9TiRx6Jk12nfzPaq86DMa9ZufyEr4cxDIBj8xyKnWh5+Sv9Ou5PzZUYcCAEDsJBomq33DZnlHZ6/Lj7y4XnvmL1Ti3MmqXXKHrJyLkYBs0UAhZ7pT7WpdslKVXzxPFR8/LepwAACIncS59fLUUbU3/etDy1L/2KLd825VxZnjNPrxO1VSmYggQqDw0UAhZw794Tl172tR8torog4FAIBYSnw6mEjimMv4jm7boeY5C1Q6PKm65XerNFkdRXhAUaCBQk54d7daFi9XxSfOUoIH8AEAEImy0SNUNm60Uo3vPw+qc9deNc+6UVZSoroVd3OPMjBINFDIiSOr16pj2w4lr72CmXwAAIhQoqFeqcYmubu63j6oXZffpK6WNtUtvUsVZ4yLOjyg4NFAISda7luqsrG1qrr0c1GHAgBArCUa6tW1Z7+Obtmu5itvVsf2t1T32K805JNnRx0aUBSYegWDlnp1k1Jr/6nhC3/AbD4AAEQsce5kSVLzrBvV9b+3VfvQQg2ddk7EUQHFgzNQGLSWxctVUlOlmrmXRh0KAACxVzHxdFlVpbr27NfIRQtUdcmFUYcEFBVOF2BQ3F2lyWqd8L3LVFJVGXU4AADEnpWW6qQF35ING6qab/DPTSDXaKAwKGamkYsWRB0GAABIwyNFgPBwCR8AAAAAZIgGCgAAAAAyRAMFAAAAABmigQIAAACADJm7h3sAszZJW0M9COJshKR9UQeBona2u1dHHUS+ULORB9RthClWNRvRyMcsfFvdfWoejoMYMrP15BfCZGbro44hz6jZCBV1G2GKYc1GBLiEDwAAAAAyRAMFAAAAABnKRwP1YB6OgfgivxC2uOVY3D4v8o8cQ5jIL4Qu9EkkAAAAAKBYcAkfAAAAAGSIBgoAAAAAMpR1A2Vm48xsjZltNrPXzOz6YPwkM1ttZq8H309M2+YWM9tmZlvN7Etp458ys6Zg2b1mZrn5WChU2eaXmQ0P1j9kZr87Zl/kFz5kADl2kZm9EuTSK2b2hbR9Hfc5Rs1G2KjbCFPcajYKw0DOQHVKusndJ0g6T9K1ZjZR0k8lveDu4yW9ELxXsGyOpEmSZkhabGalwb7ul/R9SeODrxmD+CwoDlnll6SUpJ9JWtDLvsgv9CbbHNsn6VJ3r5f0TUmPpe2rEHKMmo2wUbcRprjVbBSArBsod29291eD122SNksaI2mmpEeC1R6R9JXg9UxJy9y93d23S9omqcHM6iTVuPta75nJ4tG0bRBT2eaXux9297+q5xfye8gv9GUAObbB3XcF469JSpjZkELJMWo2wkbdRpjiVrNRGAZ1D5SZnSppiqSXJdW6e7PUk+ySRgWrjZH0ZtpmO4OxMcHrY8cBSRnnV1/IL/RrADl2maQN7t6uAswxajbCRt1GmOJWs3H8KhvohmZWJWmlpBvc/eBHXEba2wL/iHEgm/zqcxe9jJFfeE+2OWZmkyTdKWn6u0O9rHbc5hg1G2GjbiNMcavZOL4N6AyUmZWrJ4kfd/cnguE9wenRd0/D7w3Gd0oal7b5WEm7gvGxvYwj5rLMr76QX+hTtjlmZmMlPSlpnrv/OxgumByjZiNs1G2EKW41G8e/gczCZ5J+L2mzu9+TtugZ9dysp+D702njc4LrT09Tz017jcHp1jYzOy/Y57y0bRBTA8ivXpFf6Eu2OWZmSUl/lHSLu7/07sqFkmPUbISNuo0wxa1mozBYz310WWxgNk3SXyQ1SeoOhm9Vz/WoKySdLGmHpFnufiDY5jZJ31bPTCo3uPuqYHyqpIclDZW0StJ1nm1AKCoDzK//SKqRVCGpRdJ0d99EfqE32eaYmd0u6RZJr6ftZrq77y2EHKNmI2zUbYQpbjUbhSHrBgoAAAAA4mpQs/ABAAAAQJzQQAEAAABAhmigAAAAACBDNFAAAAAAkCEaKAAAAADIEA0UAAAAAGSIBgoAAAAAMvR/+41xR/ZG85YAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sdg9_sub_poland_list = sdg9_sub_poland.notnull().sum().sort_values(ascending = False)[1:7].index\n", "\n", "ylabels = ['Articles', 'R&D Personnel', 'R&D Spending', 'Patents', 'Broadband', 'Broadband Gap']\n", "\n", "green9_list = [0.7, 1, 1.5, 80, 80, 10]\n", "\n", "fig = plt.figure(figsize = (12,8))\n", "for i in range(6):\n", " ax = plt.subplot(3,2,i+1)\n", " sns.lineplot(x = 'year', \n", " y = sdg9_sub_poland_list[i], \n", " data = sdg9_sub_poland, \n", " ax = ax, color = 'crimson', label = 'Poland', legend=False)\n", " plt.xlim((2000,2019))\n", " plt.axhline(green9_list[i], color = 'seagreen', label = 'Green Threshold')\n", " ax.set_xticks([2000, 2010, 2020])\n", " ax.set_xlabel('')\n", " ax.set_yticks([])\n", " ax.set_ylabel(ylabels[i], size = 12)\n", "\n", "plt.legend(bbox_to_anchor = (1.5,3.5))\n", "plt.suptitle('Poland: Trends in Innovation Sub-Indicators', size = 16)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We identified Research Spending, Patents and Digital Skills as areas of potential improvement. The last we lack historical data for, but we can see in the above that Research Spending is consistently increasing and is likely to reach the green threshold if current patterns continue. Patents, on the other hand have been quite stagnant; policy or other intervention will be needed to increase them.\n", "\n", "Below, we identify countries in Europe and in the Central/Eastern region with highest scores for patents & digital skills, as they could suggest policies that might be useful in Poland." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Top 4 Patents:\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
countrysdg9_epo
81Switzerland935.4
438Luxembourg708.9
732EFTA Countries635.4
501Netherlands414.5
\n", "
" ], "text/plain": [ " country sdg9_epo\n", "81 Switzerland 935.4\n", "438 Luxembourg 708.9\n", "732 EFTA Countries 635.4\n", "501 Netherlands 414.5" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print('Top 4 Patents:')\n", "sdg_trends[sdg_trends['year']==2018][['country','sdg9_epo']].sort_values('sdg9_epo', ascending = False).head(4)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Top Central/East Europe Patents:\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
countrysdg9_epo
627Slovenia48.2
123Czech Republic23.3
543Poland13.7
\n", "
" ], "text/plain": [ " country sdg9_epo\n", "627 Slovenia 48.2\n", "123 Czech Republic 23.3\n", "543 Poland 13.7" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print('Top Central/East Europe Patents:')\n", "sdg_trends[(sdg_trends['year']==2018) & \n", " (sdg_trends['Sub-region']=='Central and Eastern Europe')\n", " ][['country','sdg9_epo']].sort_values('sdg9_epo', ascending = False).head(3)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Top 3 Digital Skills:\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
countrysdg9_digital
376Iceland69.0
523Norway64.0
502Netherlands64.0
\n", "
" ], "text/plain": [ " country sdg9_digital\n", "376 Iceland 69.0\n", "523 Norway 64.0\n", "502 Netherlands 64.0" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print('Top 3 Digital Skills:')\n", "sdg_trends[sdg_trends['year']==2019][['country','sdg9_digital']].sort_values('sdg9_digital', ascending = False).head(3)" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Top Central/East Europe Digital Skills:\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
countrysdg9_digital
124Czech Republic34.0
628Slovenia26.0
313Croatia22.0
607Slovak Republic22.0
334Hungary21.0
544Poland16.0
\n", "
" ], "text/plain": [ " country sdg9_digital\n", "124 Czech Republic 34.0\n", "628 Slovenia 26.0\n", "313 Croatia 22.0\n", "607 Slovak Republic 22.0\n", "334 Hungary 21.0\n", "544 Poland 16.0" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print('Top Central/East Europe Digital Skills:')\n", "sdg_trends[(sdg_trends['year']==2019) & \n", " (sdg_trends['Sub-region']=='Central and Eastern Europe')\n", " ][['country','sdg9_digital']].sort_values('sdg9_digital', ascending = False).head(6)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In Central & Eastern Europe, Czechia and Slovenia appear to be the best countries to model, while the Netherlands may be a useful exemplar for both.\n", "\n", "We will now analyze Goals 14, 5, 7, and 11 in a similar though less detailed fashion, to identify any sub-indicators that could be effective targets for improvement.\n", "\n", "## Goal 14: Life Below Water" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Countrysdg14_bathsdg14_fishstockssdg14_trawlsdg14_discardsdg14_biomarsdg14_cpma
15Poland3.93334.00260.27285.2898.989.514
\n", "
" ], "text/plain": [ " Country sdg14_bath sdg14_fishstocks sdg14_trawl sdg14_discard \\\n", "15 Poland 3.933 34.002 60.272 85.28 \n", "\n", " sdg14_biomar sdg14_cpma \n", "15 98.9 89.514 " ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "goal_list = [14, 5, 7, 11]\n", "\n", "#create dictionary of subindicators for each of the four goals above\n", "priority_goals = {}\n", "\n", "for num in goal_list:\n", " regex = 'Country|^Normalized Score sdg{}'.format(num)\n", " df = sdg_current.filter(regex = regex, axis = 1)[0:30].copy()\n", " df.columns = [item[-1] for item in df.columns.str.split()]\n", " priority_goals[num] = df[df['Country'] == 'Poland']\n", " \n", "priority_goals[14]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The lowest normalized scores, from the documentation, are sdg14_bath : Bathing sites of excellent quality (according to bacterial tests), and sdg14_fishstocks: Fish caught from overexploited or collapsed stocks (% of total catch)\n", "\n", "We investigate the trends in these scores. Values below are the non-normalized values; bathing sites range from 25-100 with green threshold of 80+, while fishstocks ranges from 90.7 - 0 with a green threshold of 10 or below." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
yearsdg14_bathsdg14_fishstocks
536201167.383.0
537201268.381.7
538201366.881.0
539201455.759.9
540201560.9NaN
541201666.2NaN
542201766.8NaN
543201828.0NaN
\n", "
" ], "text/plain": [ " year sdg14_bath sdg14_fishstocks\n", "536 2011 67.3 83.0\n", "537 2012 68.3 81.7\n", "538 2013 66.8 81.0\n", "539 2014 55.7 59.9\n", "540 2015 60.9 NaN\n", "541 2016 66.2 NaN\n", "542 2017 66.8 NaN\n", "543 2018 28.0 NaN" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sdg_trends[(sdg_trends['country']=='Poland') & \n", " (sdg_trends['sdg14_bath'].notnull())\n", " ][['year','sdg14_bath', 'sdg14_fishstocks']]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It seems that Poland was above the red threshold every year except the last, which indicates either a sharp change or an issue with data collection. \n", "\n", "For fish stocks, the scores appears to be based on data from 2014 and prior, so may or may not reflect the current situation. Given the issues with quality and quantity of data in these scores, more research would need to be done to make meaningful analysis of this category.\n", "\n", "\n", "## Goal 5: Gender Equality" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Countrysdg5_paygapsdg5_empgapsdg5_caringsdg5_wparlsdg5_wmanagesdg5_wsafe
15Poland78.062.43958.83341.84247.0NaN
\n", "
" ], "text/plain": [ " Country sdg5_paygap sdg5_empgap sdg5_caring sdg5_wparl sdg5_wmanage \\\n", "15 Poland 78.0 62.439 58.833 41.842 47.0 \n", "\n", " sdg5_wsafe \n", "15 NaN " ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "priority_goals[5]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The last entry is null because it was deleted from the raw data, but from their published data we can insert Poland's value:" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Countrysdg5_paygapsdg5_empgapsdg5_caringsdg5_wparlsdg5_wmanagesdg5_wsafe
15Poland78.062.43958.83341.84247.052.632
\n", "
" ], "text/plain": [ " Country sdg5_paygap sdg5_empgap sdg5_caring sdg5_wparl sdg5_wmanage \\\n", "15 Poland 78.0 62.439 58.833 41.842 47.0 \n", "\n", " sdg5_wsafe \n", "15 52.632 " ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "priority_goals[5].loc[15,'sdg5_wsafe'] = round((63 - 33)/(90-33)*100,3)\n", "\n", "priority_goals[5]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The two lowest normalized scores are % of women in parliament and % of women in management. Let's examine whether these are on track, and how they compare to the average EU progress." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set_style('darkgrid')\n", "\n", "fig, axes = plt.subplots(1,2, sharey=True, figsize = (12,4))\n", "\n", "plt.suptitle('Women in Leadership Positions', size = 16)\n", "\n", "sdg_trends[sdg_trends['country']=='Poland'].plot(x = 'year', \n", " y = ['sdg5_wparl', 'sdg5_wmanage'], \n", " label = ['Parliament','Management'],\n", " ax = axes[0],\n", " title = 'Poland',\n", " legend = False)\n", "\n", "sdg_trends[sdg_trends['country']=='European Union'].plot(x = 'year', \n", " y = ['sdg5_wparl', 'sdg5_wmanage'], \n", " label = ['Parliament','Management'],\n", " ax = axes[1],\n", " title = 'EU',\n", " legend = False)\n", "for axis in axes:\n", " axis.axhline(40, color = 'green', label = 'Green Threshold')\n", " axis.set(ylim = (0,50), \n", " ylabel = 'Percentage', \n", " xticks = [2004+4*i for i in range(0,5)], \n", " xlabel = 'Year', \n", " )\n", " axis.tick_params(labelsize = 12)\n", "\n", "plt.legend(bbox_to_anchor = (1.05,1))\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is slight but slow progress, considerably less than the EU average. This is an area that will likely need active intervention to achieve at least 40% women.\n", "\n", "\n", "## Goal 7: Affordable and Clean Energy" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Countrysdg7_warmsdg7_eurenewsdg7_co2twh
15Poland88.017.62667.729
\n", "
" ], "text/plain": [ " Country sdg7_warm sdg7_eurenew sdg7_co2twh\n", "15 Poland 88.0 17.626 67.729" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "priority_goals[7]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The lowest normalized score is certainly sdg7_eurenew, representing how much of Poland's energy comes from renewable sources. It is well-known that Poland is still heavily dependent on coal. This is reflected in the graphs below." ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, (ax1, ax2) = plt.subplots(1,2, figsize = (12,4))\n", "\n", "sdg_trends[sdg_trends['country']=='Poland'].plot(x = 'year', \n", " y = 'sdg7_eurenew', \n", " ax = ax1,\n", " label = 'Poland',\n", " color = 'crimson'\n", " )\n", "sdg_trends[sdg_trends['country']=='European Union'].plot(x = 'year', \n", " y = 'sdg7_eurenew', \n", " ax = ax1,\n", " label = 'EU',\n", " color = 'dodgerblue'\n", " )\n", "ax1.set(ylim=(0,50),\n", " ylabel = '%'\n", " )\n", "ax1.set_title('Percentage of Energy from Renewables', fontsize = 14)\n", "ax1.axhline(30, color = 'green')\n", "\n", "sdg_trends[sdg_trends['country']=='Poland'].plot(x = 'year', \n", " y = 'sdg7_co2twh', \n", " ax = ax2,\n", " label = 'Poland',\n", " color = 'crimson'\n", " )\n", "sdg_trends[sdg_trends['country']=='European Union'].plot(x = 'year', \n", " y = 'sdg7_co2twh', \n", " ax = ax2,\n", " label = 'EU',\n", " color = 'dodgerblue'\n", " )\n", "ax2.set(ylim =(0,6),\n", " ylabel = 'MtCO2 / TWh')\n", "ax2.set_title('CO2 emissions per unit electricity output', fontsize = 14)\n", "ax2.axhline(1, color = 'green')\n", "\n", "for axis in (ax1,ax2):\n", " axis.set(xticks = [2000+4*i for i in range(0,6)],\n", " xlabel = ''\n", " )\n", " axis.tick_params(labelsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that Poland has made very little progress on either goal in the past fifteen years, and in fact appears to be worsening in 2016-17, both in absolute terms and relative to the EU.\n", "\n", "## Goal 11: Sustainable Cities and Communities" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Countrysdg11_urbgreensdg11_crowdingsdg11_recyclesdg11_dwellingsdg11_transportsdg11_eupm25sdg11_pipedwat
15Poland50.433.55955.32380.068.44210.47698.935
\n", "
" ], "text/plain": [ " Country sdg11_urbgreen sdg11_crowding sdg11_recycle sdg11_dwelling \\\n", "15 Poland 50.4 33.559 55.323 80.0 \n", "\n", " sdg11_transport sdg11_eupm25 sdg11_pipedwat \n", "15 68.442 10.476 98.935 " ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "priority_goals[11]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here the lowest categores are sdg11_eupm25: exposure to PM 2.5 and sdg11_crowding: overcrowding rate in lower-income communities. Below we analyze how these are trending." ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "fig, (ax1, ax2) = plt.subplots(1,2, figsize = (12,4))\n", "\n", "sdg_trends[sdg_trends['country']=='Poland'].plot(x = 'year', \n", " y = 'sdg11_eupm25', \n", " ax = ax1,\n", " title = 'Exposure to PM 2.5 Pollution',\n", " legend = False\n", " )\n", "ax1.axhline(10, color = 'green')\n", "ax1.set(ylim=(0,40))\n", "\n", "\n", "sdg_trends[sdg_trends['country']=='Poland'].plot(x = 'year', \n", " y = 'sdg11_crowding', \n", " ax = ax2,\n", " title = 'Overcrowding in Low-Income Areas',\n", " legend = False\n", " )\n", "ax2.axhline(35, color = 'green')\n", "ax2.set(ylim=(0,80))\n", "\n", "for axis in (ax1,ax2):\n", " axis.set(xticks = [2004+4*i for i in range(0,5)],\n", " xlabel = ''\n", " )\n", " axis.tick_params(labelsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that overcrowding appears to be declining sufficiently quickly to reach the green threshold, but particulate air pollution has only marginally decreased and, like clean energy trends, has reversed in recent years. This agrees with my own experience of poor air quality in Warsaw in recent years.\n", "\n", "## Areas of Strength\n", "Before making final conclusions, we look at the two Goals where Poland is most outperforming the EU: Goals 4 and 15. These may indicate strengths Poland can use to make changes.\n", "\n", "## Goal 4: Education" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set_style('white')\n", "goal4 = sdg_current.filter(regex = 'Country|^Normalized Score sdg4',axis=1)[0:32]\n", "\n", "fig = plt.figure(figsize = (12,6))\n", "ax = plt.subplot()\n", "goal4.boxplot(vert = False, ax = ax).invert_yaxis()\n", "\n", "#Mark Poland\n", "poland_4 = goal4.iloc[15,1:10].tolist()\n", "plt.scatter(x = poland_4, y = arange(1,10), marker = \"d\", color = 'red', label = 'Poland')\n", "\n", "y_labels = ['Early education', 'Dropout rate', 'PISA score', 'Science achievement', 'Science achievement equity', \n", " 'Resilience', 'Adults with college degree', 'Adult learning', 'Adult numeracy']\n", "\n", "ax.set_yticklabels(y_labels)\n", "ax.set_title('Normalized Scores, Goal 4: Education', size = 16)\n", "ax.yaxis.set_ticks_position(\"right\")\n", "\n", "plt.xlabel('% Achieved')\n", "plt.legend()\n", "sns.set_style('whitegrid')\n", "ax.grid(False)\n", "ax.tick_params(labelsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Poland is in the top 25% of European countries in these categories:\n", "- Early leavers from education and training (% of population aged 18 to 24)\n", "- PISA score (worst 0–600 best)\n", "- Underachievers in science (% of population aged 15)\n", "- Resilient students (%)\n", "\n", "This indicates that there is a strong secondary education system, particularly in science. In contrast, Adult learning and literacy are the lowest categories.\n", "\n", "## Goal 15: Life on Land" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAApAAAAEXCAYAAAAa6HStAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAABWRUlEQVR4nO3dd3yN5//H8dfJCSJipSpmUW2s2FVU1N6tECNmrVq1tYgRae29ErvaohohghbVVlVrNXQZrV2xJWqLkXHu3x/55XxFiByy8H4+Hh7Oucd1fe7r3OecT677uu5jMgzDQEREREQkiezSOgARERERebYogRQRERERmyiBFBERERGbKIEUEREREZsogRQRERERmyiBFBERERGbKIEUEREREZsogUwGHTt2pEyZMoSGhiZYd+jQIYoVK0ZISEjqB5ZEtWvXZsyYMQCEhIRQrFgxDhw4kKJ1ent788477yS6za1bt5g+fTr169fHzc2NypUr0717d3799dcUjS2tnDx5kk8++YR69epRpkwZ3nzzTbp27cpPP/2UIvX5+flRvnz5JG/ft29f63lyvzFjxlCsWLEE/44ePZqssdx/ngKsX7+et99+mzJlyrB48eIk1/Uw165dY9q0aTRo0IDSpUvj7u5Or1692L1791OVG8fWtk5uHTt2pGfPnmlWv4g8f+zTOoDnxb179/Dx8WHZsmWYTKa0DueJlSpVisDAQIoWLZqmcRiGwfvvv094eDg9e/akcOHC3LhxgzVr1tClSxfmzZtHrVq10jTG5PTTTz8xePBgChUqxPvvv0+RIkW4ceMGmzZtolevXgwfPpzOnTunSWyGYTB16lR++OEH2rdvn2D9kSNHaNSoUYL4XnnllWSNw9/fn2zZslmfT5gwgWLFitGvXz8KFiz4xOWGhobSpUsXoqOj6dKlC6VKleLatWusW7eOzp0707dvX/r165cchyAi8txQAplMsmbNyp49ewgKCqJVq1ZpHc4Tc3Jyoly5cmkdBnv37uXPP/9k1apVlC1b1rq8Tp06eHl5MXfu3OcmgQwLC2Po0KHWnrSMGTNa19WtWxcXFxemT5/OO++8Q65cuVI1tjNnzjBu3Dh2796Ng4PDQ7c5evQo77zzToqfNyVLloz3/Nq1a7z99ttUqlTpicuMiYmhX79+ZMiQgTVr1uDs7Gxd16BBA2bPno2/vz+lSpWidu3aT1yPiMjzRpewk0nFihWpVasWU6ZM4dKlS4lue/bsWQYMGMBbb71F+fLl6d27d7zL335+fnh6ejJhwgTeeOMN2rRpw9mzZylWrBhbtmyhc+fOlC1bljp16vD9999z/Phx2rVrR9myZWnWrBn79++3lhUVFcWcOXNo0KABbm5uVKpUib59+3LhwoWHxnb/Jey4Oh/2z9vb27rPzp07adWqFWXKlOHtt99m9uzZxMTEWNdHR0czbdo0qlWrRoUKFZg4cWK89Q9z+fJlACwWS7zldnZ2DBo0CE9Pz3jLAwMDadKkCWXKlKFhw4asWrXKus4wDFatWsW7775LmTJlqF+/Pl988UW8/YsVK8aCBQto0qQJlStXZvPmzQAcPHiQTp06UbZsWapUqcLYsWO5c+eOdb9Lly4xYMAAKleuTNmyZWnXrh179uxJ9Nge9NVXX3Hz5k0+/vjjeMljnF69elGtWjWuXr1qXfa4cwhg+/btdOjQgfLly1O6dGk8PDz4/vvvbYpt4sSJXLp0iYCAAF566aUE68+fP8+NGzcoVqzYI8uIO4/8/PxsqvtBcZew485RgKlTp8are8OGDbz77ruULl2aunXrsnz58kTL/Omnnzh69CgfffRRvOQxTt++fXnllVdYsGCBdVmxYsUIDg5m0KBBlC9fnsqVKzN+/Hiio6Of6viS8l6tXbs2ixcvxtfXlzfffJMKFSowbNgwbt26Zd0mIiKCUaNG8eabb1K5cmUWLVr0VHGJiDyMEshk5OvrS3R0NGPHjn3kNhcvXqRVq1acOnUKX19fJk6cyNmzZ2nXrh1hYWHW7Y4cOcKBAwfw8/OjV69e1uUjR46kWrVqzJ8/nzx58jBs2DD69OlDkyZNmD59Ordu3WLIkCHW7SdOnMiXX35J9+7d+eyzzxg4cCC7d+9mwoQJjz2e3LlzExgYGO+fl5cXZrMZDw8PAHbv3k337t0pUKAA/v7+dOvWjc8//5xx48ZZy5kwYQLLly+ne/fuzJgxg8OHD/Ptt98mWnelSpVwdHSkb9+++Pn5sW/fPusX9FtvvUW7du2s237++ef4+vpSvXp1FixYQMOGDfHx8WHDhg0AzJgxg48//pjatWszb948GjZsyJQpU5g5c2a8Ov39/Wnfvj0ff/wxb7zxBsePH6dDhw6YTCZmzZrFRx99xKZNmxg4cKB1n+HDh3P69GkmTpzIvHnzyJw5Mz179uTatWuPbd84P/30E8WLF6dIkSIPXZ89e3YWLFjA66+/DiTtHNq/fz89evTg9ddfZ968ecycOZPMmTPz4YcfcuXKlSTHNmjQINasWUOpUqUeuv7IkSMABAcHU61aNdzc3OjatSv//vuvdZu48yi5eubjhllA7Ni+uMdr167lww8/pFKlSsyfP59mzZoxceJEPv3000eWtXPnTuzs7HB3d3/oerPZTJ06ddi3b1+8dpswYQLOzs7MmzeP9u3bs2zZsnh/tDyJpL5XFy5cyI0bN5gxYwYDBw5k48aNzJ8/37p+8ODB/PDDDwwdOpTx48ezceNG/vzzz6eKTUQkAUOeWocOHYwePXoYhmEYS5cuNVxdXY0tW7YYhmEY//zzj+Hq6mr8+uuvhmEYxsSJE41y5coZly9ftu5/+fJlo3z58sbEiRMNwzCMOXPmGK6ursb+/fut25w5c8ZwdXU1Ro8ebV32yy+/GK6uroafn5912apVqwxXV1fj+vXrhmEYxoABA4zVq1fHi3fs2LHGm2++aX1eq1Yt45NPPjEMwzB+/fXXBHXH+eOPP4xSpUoZ8+fPty5r3bq10aZNm3jbrV271ihevLhx5swZ4+rVq0aJEiWMhQsXWtffvXvXqFq1qtGkSZNHN6phGLt37zZq1qxpuLq6Gq6urka5cuWMXr16Gdu3b7duExMTY7z55pvG8OHD4+07ePBg4+OPPzauXLlilCpVypg2bVq89dOmTTNKlSplfR1cXV2tr2GcQYMGGbVr1zbu3btnXbZ3717D1dXV2LNnj2EYhlG2bFljwYIF1vVhYWHGpEmTjPPnzyd6bPerUKGC0a9fvwTLo6Ki4v2LiYkxDCNp51BQUFCCMv/++2/D1dXV2Lp1q2EYsedZuXLlkhzn/edJnPnz5xuurq7G4MGDjV9//dXYuHGj0ahRI+Ott96KF9/jJCWWB+t3dXU1Pv30U8MwYs8Dd3d348MPP4y3j7+/v1G+fHkjIiLioWV2797dqFq1aqL1Ll++3HB1dTUOHjxorff999+Pt02zZs2Mnj17PrKMpBxfUt+rTZo0MSwWi3VZnz59jHfeeccwDMM4dOiQ4erqamzcuNG6PiwszHBzc0twfouIPA2NgUxmHTp0YMOGDYwZM4bKlSsnWL93714qV64c73KZs7MzVatWTXDp82ETWcqUKWN9HDcernTp0tZlOXPmBODGjRtky5aNWbNmAbHj7P7991/+/fdf/vjjDyIjI206rrCwMPr164e7u7t1NuedO3fYv38/gwYNinf57u2338ZisRASEkKuXLmIiYnh7bfftq7PlCkTNWrUeOxM7ypVqrBlyxZCQkL45Zdf+PXXX/npp5/YunUrPXv2ZPDgwZw8eZJr164lGJ82ffp0ALZt20ZUVBQNGzaMt75JkyYsWrSIffv2WcdSPtjeISEh1KlTBzs7O+vxlStXDicnJ3bv3k2lSpUoX748c+bM4ciRI9SoUYMaNWowbNgwW5oWi8WSYOLVX3/9hZeXV7xl7du3Z/To0Uk6h1q0aEGLFi24ffs2J06cIDQ01Dp73dbXPjHvvPMOJUuWpHr16tZjKFeuHA0aNCAgIIA+ffokW12JOXnyJOHh4dSsWTPBuThnzhz2799PlSpVEuxnGAZmsznRsh+2/v5xuQAuLi7cvn37CaOPldT3aunSpeOdL3ny5OHQoUMA/PHHHwDx3m+5c+dOF+OaReT5ogQymdnZ2TF27Fg8PT2ZPn06rVu3jrf+xo0blChRIsF+L730EsePH7c+d3R0xNHRMcF2WbJkSbDsUZMbIPYL5eOPP+bIkSNkzZqVEiVKkClTJlsOicjISPr374+DgwNTpkyxfnnduHEDi8XC9OnTrQnb/S5dumQd0xeX2MZJ6mQQs9nMW2+9xVtvvQXEjqcbMWIEixYtomXLltZLxQ8bvwZw/fr1h9YXN57v/rFjD47xu3btmvXS/cOODWDmzJnMnTuXb7/9lo0bN5IhQwY8PT0ZNWrUQ8czPky+fPk4f/58vGWurq4EBQVZn/fu3dv6OCnn0O3btxk9erR1qECRIkUoXrw4EJs0JZcCBQpQoECBeMvy5ctH0aJFrZe3U0PcefDhhx/y4YcfJlj/qHHJ+fPnZ/fu3dy7d++R74tz584BkDdvXuuyzJkzx9vGzs7uqds1qe/VB+s2mUzWum/cuEGGDBlwcnKKt83LL79MRETEU8UnInI/JZApoFixYnTr1o1Fixbx2muvxVuXPXt2/vvvvwT7/Pfff+TIkSNZ47h58ya9evWiQoUK+Pn5UahQIQCmTJnC4cOHk1zOmDFjOHToECtXrox3G5W4ZLZ3797UqVMnwX65c+e23gvwypUruLi4WNc9bozggAEDiI6OZu7cufGWFyhQgBEjRuDh4cHJkyetX+oPjus7efIkV69etbbpf//9F6/+uNcgsTZ3cnKiTp06tG3bNsG6uIQ4R44cjBw5kpEjR3Lo0CG+/vprPv/8cwoUKECPHj0SPcY4NWvW5LPPPiMsLMwao6OjY7ye5fuT0aScQ2PHjmXnzp0sWrSISpUqkTFjRo4fP84333yTpJiSatu2bdZjuN/du3eT/XxOTNasWQEYPXp0vF76OA8muXFq1apFQEAAP/30U4JeaohNtrdu3Urp0qUf+UdKckiu92qOHDmIioqyXoGIc+3aNTJkyJDscYvIi0uTaFJInz59KFSoEDNmzIi3vGLFioSEhMRLeK5cucLu3bupUKFCssbw77//cv36dTp16mT9QrJYLOzatSvJvSVfffUVq1evZvTo0Qluo+Lk5ETx4sU5c+YMpUuXtv7LkCEDM2bM4OLFi5QvX56MGTPGm/0bHR3Nzp07E623QIEC/Pzzzxw7dizButDQUOzs7Hj11Vd59dVXyZEjhzWRiTN79mymTJlijSduVnWcTZs2YW9v/9BkI07FihX5999/cXNzsx5b3rx5mT59OseOHePKlSvUrFmTH374AYASJUowbNgw8uXL98hZ7g/TsWNHnJycGDFiBHfv3k2wPiwsLF5PaVLOob/++ovq1atTrVo1a/K5fft2IHl7IL/99ltGjRoVb2b6kSNHOHXqFG+++Way1fM4cedBWFhYvHPx2rVrzJ49O1773c/d3Z3SpUs/8u4JCxcu5MSJE0n+Y+BJJcd7FbC2+f3vt+vXr/PXX38la7wiIuqBTCGZMmXik08+oVOnTvGWd+7cmbVr19K1a1c++OADDMNg/vz5ZMyYMcG2T+vVV18lS5YszJs3D4vFwt27d/nqq684fPiw9bJXYjc9//PPP5kwYQK1atWiZMmS7Nu3z/plljFjRkqWLEn//v3p06cPTk5O1KtXj6tXrzJr1izs7OxwdXUlc+bMdOvWjcWLF5MpUyZKlixJQEAA//33X6I3mu7WrRvff/897du357333qNChQqYTCZ+//13PvvsMzp06GC9eXTPnj2ZOnUqOXPmpGrVquzdu5fNmzfj7++Ps7MzHTt2ZMmSJZjNZipVqsTevXtZsmQJXbp0IXv27I+M4YMPPqBNmzYMGDCAFi1aEBkZybx587hw4QIlS5bE2dmZQoUKMW7cOCIiIsibNy/btm3j3Llz1KtXD4hN7E6fPs1rr72W4LJinDx58jBz5kwGDRpEs2bNaNu2La6urty9e5ddu3YRFBRExowZqV69OpC0c6h06dJs3bqVtWvXkjdvXn799VeWLFkC8NAk9Ul16dKFTZs20adPHzp37szly5eZNWsWpUqVonHjxkDsEIh//vmHPHnykCdPnkeWFRUVleD2ShDbo1+1atVE47C3t6dfv35MmjQJgKpVq3L27FmmT59O4cKFH9kDaTabmTFjBt26daN58+a8//77lCxZkhs3brBhwwa+/fZbevXqRf369ZPYIo+W2PG5ubk91Xs1zquvvkrTpk2ZMGEC9+7dI1++fCxcuPCpbzEkIvIgJZApqEqVKrRo0YI1a9ZYl+XNm5cVK1YwdepUhg0bhtls5s0332TmzJmJfrk+iaxZs+Ln58eUKVPo3bs3OXPm5I033mD27Nn079+fffv2JTq4fseOHURFRfHTTz8l+Dm9/Pnzs3XrVurUqcO8efOYO3cuwcHBODk58dZbb/HRRx9Zx2oNGDAABwcHvvrqK27cuEH9+vVp3bp1oj9J6OzszKpVq1i0aBEbN2603oqlaNGieHt7x7slTNeuXcmUKRNLly7liy++oHDhwsyYMYO6desCMGTIEHLmzElgYCCffvop+fPnZ+jQoY9N2N3c3Fi6dCmzZs2if//+ZMqUiQoVKjBlyhTrpeYZM2YwZcoUpk2bxrVr1yhSpAjTp0+3jtnctm0bw4cPZ9myZQ+dVBXH3d2dr7/+muXLl7Ny5UouXLiAnZ0dr732Gr1798bLy8ua7CblHPL29ubu3bvWW8AULVoUf39/JkyYwJ9//knz5s0TPfakKl68OEuXLmXmzJkMHDiQDBkyULduXYYMGYKdXewFjvDwcLy8vB77iy5RUVFMnDgxwXIvL6/HJpAQO4HNwcGBL774gs8++4wcOXLQsGFDBg0alGjy9corrxAUFMSyZctYvXo1Z8+eJUuWLJQpU4bPP//c+lo+rccd39O8V+83fvx4nJ2d8fPzIyoqipYtW+Li4pKsfziIiJiM5LyeJSIJDB06lHbt2mkmrIiIPDc0BlIkBf3zzz/s27cv0V9qERERedaoB1IkBV25coV79+7FuwWMiIjIs04JpIiIiIjYJNFJNH/99ZfNN50WERF5lt27d09jlkUeI9EEMlOmTA/9xQsREZHnVdxPQ4rIo2kSjYiIiIjYRAmkiIiIiNhECaSIiIiI2MTmX6KJiori7Nmz+lUDwMHBgQIFCpAhQ4a0DkVEREQk1dicQJ49e5asWbNSuHDhJP026/PKMAwuX77M2bNnKVKkSFqHIyIiIpJqbL6EfffuXV566aUXOnkEMJlMvPTSS+qJFRERkRfOE42BfNGTxzhqBxEREXkR2XwJ+4mdOwf586dadSIiSVXYe2Nah2DlWGQmt08OSpaysmfOwD7f+slSlojI/VIngdy+HWrUgF9+AXf3py4uJCSEgQMH8tprrwGxvxrw7rvv0rFjxwTbnj17lsGDB7Nq1aonru+XX35h06ZNTJo06YnLEJH0LXRSk7QOAYDSS72TLZb0lBiLyPMl5RPI6Gjo3BkMI/b/w4fB/umrrVKlCjNnzgQgMjKShg0b4uHhQbZs2Z66bBERERF5tJRPIP38ICws9vHFi+DvDwMHJmsVt27dws7OjqNHjzJ9+nTMZjOZMmVi7Nix8bbbvHkzK1assD6fPXs2x44dY/HixWTIkIGzZ8/SuHFjevfuzYkTJxgxYgSZM2cmc+bMZM+ePVljFhEREXlWpWwCefEi+PhARETs84gIGDUK2rYFF5enKvrXX3+lY8eOmEwmMmTIgI+PDxMmTGD8+PGUKFGCLVu2MGnSJIYOHWrdJzQ0lEWLFpE5c2ZGjx7Njh07cHFx4fz583z99ddERkZSvXp1evfuzezZs+nfvz/VqlVj0aJF/Pvvv08Vr4hImtI4dBFJRin7SzQBARATE39ZTEzs8qdUpUoVli9fzrJly1iyZAk1atQgPDycEiVKAFCpUiWOHTsWb5+XXnqJYcOGMXz4cI4cOUJ0dDQArq6u2Nvb4+joiIODAwDHjh2jTJkyAFSoUOGp4xVJL9zc3NI6BElt27dDwYKwY0daR2ITnasi6VfKJpDt2oHZHH+Z2RzbA5kCcufOzeHDhwHYu3cvhQsXtq67efMmc+bMYebMmYwbN45MmTJhGAbw8NvxvPrqq/z5558AHDx40OZYAgICcHNzw2w24+bmRkAyJM3PA7VL2vv777/TOgRJTQ+OQ///P5yfBenxXD179iwlSpTAw8PD+q9p06YEBQXZXNa2bduYPXv2E8eyf/9+Ro8ebfN+Y8aMwc/PL8Hy4OBgevbs+cTxPE7Pnj0JDg5OsfIldaXsJWwXFxg79n+XsbNkgXHjnvry9aOMGzeOsWPHYhgGZrOZCRMmWNc5OTlRoUIFmjdvjqOjI9myZSM8PJwCBQo8tCxfX18GDRrEkiVLcHZ2JlOmTEmOIyAggJEjR7JkyRLc3d3ZsWMH3bp1A6BtCiXPzwK1i0gaSIVx6C8aBwcH1q9fb30eFhbGO++8g5ubG8WLF09yOQcOHOD69etPHMfx48cJi3ttRVJZyk+i6dcP5s6FEycgTx7o2/epi6xcuTKVK1dOsLxkyZLxJsnEibuFz6P+0ru/rJ07dwKxvZkPKyspxo8fz5IlS6hVqxYAtWrVYsmSJfTr1++FTpTULiJpIIXGocv/uLi4UKhQIUJDQ/nnn38ICgrizp07ODk5sXz5cubOncvGjRsxm80UKVIEHx8fzp8/z8qVK4mJiSFr1qwMGjSI1atXExAQgMViIUeOHPj4+FC0aFEiIiIYN24cf/zxB2azmbp169K2bVvmzJnDzZs3GT58OBMnTmTr1q3Mnz+fqKgoHBwcGDZsGOXLl+fWrVuMHDmSw4cPkzt3bsxmMxUrVrTpGH/66ScWLlxIZGQkV65coVmzZgwcOJCQkBBmzpxJwYIFOXbsGNHR0XzyySdUrFiRsLAwvL29CQ8PJ1++fFy+fDmFXgFJCymfQNrbw+efx94H8osvkuUWPundoUOHcH/gfpfu7u4cOnQojSJKH9Qu6YfuD/jiKNw3MOHCmb+lfiDPkCtXruDp6Wl97uXlhZeX1yO3//PPPzl9+jRly5Zl9+7dHD9+nK1bt+Lk5MSaNWvYvn07QUFBODo64ufnh7e3N0uWLKFNmzZcvXqVQYMGsWfPHtatW8eKFSvInDkzO3bsoG/fvnz77bfMmTOHe/fusWnTJmJiYujatSvVqlWjf//+fPfdd0ycOJHQ0FBmzpzJsmXLyJkzJ8eOHaNLly58//33zJkzBwcHBzZv3szVq1dp3ry5TQmkYRh89tlnTJo0icKFCxMWFkatWrV47733gNhL6b6+vpQoUYLPPvuMmTNn8uWXXzJmzBjKli3LwIEDOXXqFM2aNXvi10TSn9TJ5qpXhzNnXpgZgCVKlGDHjh3WnjaAHTt2WCf4vKjULulHerlpdnrxPCfUof5e/+uBhNihRCdOPBM9kKbJaVOvs7NzomP17t69i4eHBwAxMTHkzJmTqVOnkjdvXgCKFSuGk5MTEPtDFJ6enjg6OgLw3nvvsWDBAiIjI+OVuW3bNk6dOkWbNm2sy27cuMG1a9fYtWsXw4cPx2w2Yzab+fLLLwHixbhz507Cw8Pp3LmzdZnJZOL06dPs3r2bESNGYDKZcHZ2pl69eja1h8lkYsGCBWzbto0NGzZw4sQJDMPgzp07AOTLl8/6OV6yZEnWrl0LwK5duxg2bBgAhQoVeuiVQ3l2PVECaRiG7b8D/Rwmj3GTcB40cuRIunXrlmCs3/jx41M5wvRF7SKSBlJxHPqL4sExkA+KSxYBLBZLvO9Li8VivQPI/SwWCx4eHgwZMsT6PDw8nOzZs2Nvbx+vjAsXLljvGHL//lWrVmXWrFnxtsudOzcQ//vK/ODk1se4ffs2zZs3p27durzxxhu0aNGCLVu2WMu8PxaTyRRvgur99dq/AFcgXyQ2z8J2cHDg8uXLj0yeXhSGYXD58uUEb2KInRAyfvx4+vXrh4ODA/369WP8+PEv/Dg/tYtIGujXL3b8OSTbOHRJuurVq7NmzRpu374NwPLly6lUqRIZM2bEbDZbk0l3d3c2btxIeHg4EDvpsFOnTgBUrVqVtWvXYrFYiIyMpH///uzduzfe/lWrVmXnzp2cOHECgJ9//pmmTZty9+5dqlevTlBQEBaLhevXr/Pjjz/adAynTp3i1q1bDBw4kNq1axMSEkJkZCQWi+Wxxx4YGDuE4vz584SEhNhUr6RvNv85UKBAAc6ePculS5dSIp5nioODwyNncbdt21aJ0UOoXURS2Qs4Dj09admyJRcuXKBVq1ZYLBYKFSrEtGnTgNj7GX/00UeMHTsWHx8funfvTteuXTGZTDg5OeHv74/JZKJv376MHz8eDw8PYmJiaNy4MfXr1+fUqVPMnTuXvn374u/vz5gxYxg8eDCGYWBvb8/8+fPJkiUL/fr1w9fXl0aNGuHs7Iyrq+sj492+fTvly5e3Ps+aNSvbtm2jZs2aNGrUiIwZM+Lq6sprr73GqVOnyJgx4yPL8vX1Zfjw4TRq1Ig8efLYNENd0j+TkUhX4qFDhzQ+TeQ54+bm9kT3Nn2eFfbemG7GhZZeWpoDnQ4kS1nxjusZ/CWatDpX9d0n8ngpeyNxEUl3lDy+oJ6x5BF0roqkZ0ogRURERMQmSiBFRERExCZKIEVERETEJpqOJyIvvOyZM6Sbm4k7FnFJtliyZ86QLOWIiDxICaSIvPD2+dZP6xDukz5mg4uIJEaXsEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJvZpHYCIvJgKe29M6xCeO45FZnL75KBUrTN75gzs862fqnWKSNpTAikiaSZ0UpO0DuG5Unqpd6q3qf4QEHkx6RK2iIiIiNhECaSIiIiI2EQJpKQbbm5uaR2CiDzOuXNpUq0+H0TSFyWQkm78/fffaR2CiCRm+3YoWBB27Ej1qvX5IJK+aBKNiIg8XnQ0dO4MhhH7/+HDYP/ifYWcPXuWevXq4erqal1mGAbvvfceLVu2tKmsbdu2sW/fPgYMGPBEsezfv5+goCDGjBlj035jxowhZ86c9OvXL97ykJAQunfvTpEiReItb9OmDW3btn2iGO/n5+fH1atXGT169FOXdb8nbQd5Oi/eu19ERGzn5wdhYbGPL14Ef38YODBNQ0orDg4OrF+/3vo8LCyMd955Bzc3N4oXL57kcg4cOMD169efOI7jx48TFveaJJNXXnkl3rE9C1KiHeTxlECKiEjiLl4EHx+IiIh9HhEBo0ZBMvRKPQ9cXFwoVKgQoaGh/PPPPwQFBXHnzh2cnJxYvnw5c+fOZePGjZjNZooUKYKPjw/nz59n5cqVxMTEkDVrVgYNGsTq1asJCAjAYrGQI0cOfHx8KFq0KBEREYwbN44//vgDs9lM3bp1adu2LXPmzOHmzZsMHz6ciRMnsnXrVubPn09UVBQODg4MGzaM8uXLc+vWLUaOHMnhw4fJnTs3ZrOZihUr2nSMISEhjB8/HkdHRyIiIlizZg07dux4aH0nTpxg5MiRREZGYhgGLVu2pH379gD8+++/dOzYkUuXLpErVy5mzJjBpk2b+Pvvv5k6dSpRUVFUrlyZkSNH0qJFC3777TcmT55MYGAgEyZMYN++fURERGAYBuPGjSNfvnxJbgc/Pz/++usvwsPDKVasGNOmTUuJ0+GFoQRS0hXdU04kHQoIgJiY+MtiYmKX8/pz9769cuUKnp6e1udeXl54eXk9cvs///yT06dPU7ZsWXbv3s3x48fZunUrTk5OrFmzhu3btxMUFISjoyN+fn54e3uzZMkS2rRpw9WrVxk0aBB79uxh3bp1rFixgsyZM7Njxw769u3Lt99+y5w5c7h37x6bNm0iJiaGrl27Uq1aNfr37893333HxIkTCQ0NZebMmSxbtoycOXNy7NgxunTpwvfff8+cOXNwcHBg8+bNXL16lebNmz8ygTx9+jQeHh7W53nz5mXBggUAHDt2jC1btpA/f/5E61uyZAm1a9emR48eXLp0iQkTJlgvgZ85c4bVq1fj7OzMBx98wOrVq2nevDkLFy7EYrHw+++/4+joyK5du2jRogVbt26lfv367Nu3j/DwcAIDA7Gzs2PRokUsXryYBQsWJLkdAM6dO8eGDRuwfwGHXyQ3taCkK7qx9IvjeUs6nmvt2sX2QN7PbI7tgZz5W6q8b02TU7wKK2dnZ4KDgx+5/u7du9YkKyYmhpw5czJ16lTy5s0LQLFixXBycgLgl19+wdPTE0dHRwDee+89FixYQGRkZLwyt23bxqlTp2jTpo112Y0bN7h27Rq7du1i+PDhmM1mzGYzX375JUC8GHfu3El4eDidO3e2LjOZTJw+fZrdu3czYsQITCYTzs7O1KtX75HHltgl7Lx585I/f/7H1levXj2GDRvG/v37qVq1KqNGjcLOLnbObrVq1XB2dgagePHiXLlyhXz58pE3b14OHjzI9u3b6dGjB4sWLcIwDLZu3cqiRYt45ZVXyJ49OytXruTMmTOEhISQJUuWBDEmFhdAuXLllDwmE7WiiIgkzsUFxo7932XsLFlg3LjY5S+gB8dAPiguWQSwWCyYTKZ4z6OjoxPsY7FY8PDwYMiQIdbn4eHhZM+eHXt7+3hlXLhwAQcHhwT7V61alVmzZsXbLnfu3EDsRJ84ZrM5iUea+HE9qr7ixYvz3XffsWvXLnbv3s3cuXOtye79yZvJZLLGVbduXX755Rd27tzJwoUL2bBhA5s2bcLBwYFXXnmFbdu2MX78eLp06UKdOnV49dVX+frrrxPEmFhcP/zwQ7xjkKej2/iIiMjj9esHefLEPs6TB/r2Tdt4nhHVq1dnzZo13L59G4Dly5dTqVIlMmbMiNlstiaT7u7ubNy4kfDwcAACAgLo1KkTAFWrVmXt2rVYLBYiIyPp378/e/fujbd/1apV2blzJydOnADg559/pmnTpty9e5fq1asTFBSExWLh+vXr/Pjjj099XInV9+GHH7Jp0yaaNGmCr68vTk5O1h7AR6lfvz7ffPMNFosFFxcXqlWrxtSpU6lfP/Z31nfu3EmtWrVo164dbm5ubNmyhZj/H1aR1HaQ5KUeSEk3SpUqldYhiMij2NvD559DjRrwxRepfgufZ/XzoWXLlly4cIFWrVphsVgoVKiQdfJGlSpV+Oijjxg7diw+Pj50796drl27YjKZcHJywt/fH5PJRN++fRk/fjweHh7ExMTQuHFj6tevz6lTp5g7dy59+/bF39+fMWPGMHjwYAzDwN7envnz55MlSxb69euHr68vjRo1wtnZOd4tiJ7Ua6+99sj6PvjgA0aOHElgYKB10k+lSpUICQlJtDyTyUTVqlWB2IR63rx5NGjQAIi9ldCHH37Iu+++S3R0NNWqVeP777/HYrFQrly5JLWDJC+TcX+/9gMOHTpEiRIlUjMeEXlBFPbeqDGvyaz00tIc6HQgZSs5dw7+fxwcPJ+vo777RB5Pl7BFRCTp7kseReTFpQRSRERERGyiBFJEREREbKJJNCKSJrJnzqB7QSYzxyIuqd6m2TNnSNX6RCR9UAIpImlin2/9tA7hOfR8TWYRkfRLl7BFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCb2aR2AiIjEKuy9MdXrdCwyk9snB6V6vffLnjkD+3zrp2kMImIbJZAiIulI6KQmqVpf6aXeqV7ng9IicRaRp6NL2CIiIiJiEyWQIiIiImITJZAiIolwc3NLnYrOnUudep4zqfb6iEg8SiBFRBLx999/p3wl27dDwYIpX89zKFVeHxFJQJNoRETSUnQ0dO4MhvG/5/b6aE7vAgICCAgIIDo6GpPJRMmSJRk0aBD58uVL69ASCAgI4ObNm/To0SPJ+3h7e7Nz506cnZ0BsFgs3L59mzZt2tC9e3fCwsIYMGAAK1euTKmwJZ3Tp5SISFry84OwsP899/eHgQPTLBx5vMmTJ3P48GEWLlxI3rx5sVgsfP3113h5ebF69Wry5MmT1iHG07Zt2yfar3PnznTr1s36/Pz58zRu3JjatWtTtGhRJY8vOF3CFhFJKxcvgo8PRET8b9moUfETSklXLl68yMqVK5k1axZ58+YFwM7OjmbNmtGgQQMWLlzIf//9h7u7Oz///DMAs2bNokuXLvz+++/UrFkTi8UCwJ07d6hatSpXrlxh//79eHp68u6779KnTx+aN29OSEgIAFu3bqVVq1Y0a9aMNm3a8OeffwLg5+eHt7c33bp1o2HDhnTq1Inw8PAEMfv5+TFmzBgAateujZ+fH+3ataNWrVrMmjXLpmM3DAMnJyfOnj1L+fLliYmJoUaNGhw8eNC63cCBA/nqq68AmD9/Ps2bN8fDw4MPPviAsP8/tzt27Ejfvn1p3Lgxy5cv5/vvv6d58+Z4enrSqlUr9u7da8vLImlAPZAiIo+Rovcp7BsY/3lMDAQEvHC9kOnpXpBXrlzB09PT+tzLywsvLy8A9u3bx6uvvkr27NkT7PfWW28xa9YscuXKxaRJkxgxYgQ+Pj6sW7eO4OBgnJ2dyZ49O9u3b6dGjRps3LiRqlWrki1bNvr168eYMWOoUaMGv/76K507dwYgNDSUmTNnsmzZMnLmzMmxY8fo0qUL33//PQC//fYb69atw8nJiV69erFy5Ur69++f6PHdvn2br776irCwMOrVq0eLFi0o+JAxuF988QVff/01t27d4tatW1SsWJGFCxfi4uLC2bNnATCbzbRo0YLg4GDc3Ny4fv06u3fvZuzYsaxbt46jR4+yevVq7O3tCQwMZNSoUSxevBiAbNmysWnTJgDq1q3LtGnTKFeuHDt27CAkJIRKlSrZ+MpJalICKSLyGCl2o+2wMCha1NoDWXjYBjCb4QkvOT7LnrSNTZOTORDA2dmZ4ODgR66Pjo5+6PLIyEhMJhMA7u7uNG7cmH79+vHll19axxK2b9+eVatWUaNGDQIDAxk6dChHjx4FoEaNGgBUqVKF119/HYCdO3cSHh5uTSgBTCYTp0+fBuDNN9/EyckJgJIlS3L9+vXHHl+dOnUAcHFx4aWXXuL69esPTSDjLmHfvn2bQYMGkTFjRipXrpxguxYtWtCyZUu8vb3ZsGEDtWvXJmvWrPz0008cOHCAFi1aALHjKO/cuWPd74033rA+btKkCX379qVGjRpUq1aN7t27P/Y4JG3pEraISFpxcYGxYyFLlv8tGzcudrmkS+XKlePUqVNcunQpwbqQkBDKly8PgGEYnDhxgly5cvHXX39Zt3n33Xf5/fff+fXXX7l9+zaVKlXCbDZjxE2i+n9msxmITbqqVq3K+vXrrf9WrVplTTAdHBys+5hMpgTlPEymTJls2sfR0ZEpU6awd+9evvjiiwTr8+fPT8mSJdm2bRvBwcG0bNnSGvv7779vjXvNmjUEBATEKzfOoEGD+Oqrr3BzcyM4OJj27ds/9jgkbSmBFBFJS/36wf2TLvr2TbtY5LFcXFzo2LEjgwcPto7nA1izZg3ff/+9tefsiy++4Pbt26xZs4YvvviC/fv3A5A5c2aaNm3KiBEjaNOmDQBFixYlY8aM/PLLLwDs37+fo0ePYjKZqFq1Kjt37uTEiRMA/PzzzzRt2pS7d++m5mGTPXt2hg0bxpw5c+Idd5zWrVuzePFi7ty5Q8WKFYHYXtigoCBu3boFwOzZsxk6dGiCfaOjo6lduzZ37tyhbdu2+Pr6cuTIESIjI1P2oOSp6BK2iEgiSpUqlbIV2NvD55/D/1++1C18bJPir89DfPjhh6xevZrevXsTGRlJZGQkpUuXZuXKleTPn59//vmHBQsWEBQUhIuLCyNGjODDDz9k7dq1ODk54enpyapVq2jWrBkA9vb2+Pn54evry4wZMyhcuDC5cuXCwcGB1157jTFjxjB48GAMw8De3p758+eT5f5e61TStGlTVq9ezeTJkxk8eHC8dbVr1+aTTz6Jd+m5VatWhIWF0bp1a0wmE3nz5mXSpEkJyrW3t2fEiBF89NFH2NvbYzKZmDBhAhkzZkzxY5InZzIS6bs+dOgQJUqUSM14REReTOfOUdjvr5Qbb/kIpZeW5kCnA6la54MKe29M9eNOTEp+9xmGweLFizl37hyffPKJdfnkyZPp1q0buXLl4sKFC3h4eLBlyxayZcuWInGIPC39qSsikh7kzw/8ldZRSAqrU6cOuXPnZt68efGW58+fn86dO2Nvb49hGIwbN07Jo6RrSiBFRERSydatWx+6vEOHDnTo0CGVoxF5cppEIyIiIiI2UQ+kiEg6kT1zhlS/obZjEZc0v4l39swZ0rR+EbGdEkgRkXRin2/9NKg1/UxeEZFnhy5hi4iIiIhNlECKiIiIiE2UQIqIiIiITZRAioiIiIhNlECKiIiIiE2UQIqIiIiITZRAioiIiIhNlECKiIiIiE2UQIqIiIiITZRAioiIiIhNlECKiIiIiE2UQIqIiIiITZRAioiIiIhNlECKiIiIiE2UQIqIiIiITZRAioiIiIhN7NM6ABGR+xX23pjWITwzHIvM5PbJQalSV/bMGdjnWz9V6hKR9E8JpIikO6GTmqR1CM+E0ku9U62tlNiLyP10CVtEREREbKIEUkRERERsogRSRERERGyiBFKeKW5ubmkdgoikI/pMEEkbqZJABgQE4Obmhtlsxs3NjYCAgNSoVp5Df//9d1qHICLpSGp/Jpw9e5ZixYqxevXqeMuXLFmCt7c3ALNnz2bdunUA+Pv7s2XLFpvreZL9AgICWLRokc11pQebN2+mY8eOaR2G2CDFZ2EHBAQwcuRIlixZgru7Ozt27KBbt24AtG3bNqWrFxERSVZ2dnZMnjyZihUr8uqrryZYP2DAAOvjkJAQXnvtNZvreJL99J0qqSnFE8jx48ezZMkSatWqBUCtWrVYsmQJ/fr108kuIiLPHAcHB7p06cJHH33EypUryZgxY7z13t7evP766zg4OHDw4EGmTJmC2Wzmxx9/5Nq1a5w5c4aaNWvSsmVLxowZQ0REBJcuXaJ48eLMmjWLoKCgePvVqFGDadOmsXfvXmJiYihZsiSjRo3CyckpXr1+fn5cvXqV0aNHU7t2bZo3b87u3bu5cOECHh4eDBw4MMGx7N+/n48//pioqCheeeUVzp8/b+1JHT9+PI6OjkRERLBmzRrWrl3L8uXLsbOzI1euXPj4+FCkSBHr8cZ1Dt3/PLE4Zs+ezTfffEOOHDkoVKhQ8r9QkqJSPIE8dOgQ7u7u8Za5u7tz6NChlK5anlO6H51I2nhR3ntXrlzB09PT+tzLywsvL6942/Tu3Zvdu3czc+ZMhg0b9tBy2rdvz+bNm2nfvj316tXjxx9/5O7du2zcGNuOkydPplmzZnh4eBAVFYWnpyfbtm1LsJ+/vz9ms5ng4GBMJhMzZsxg2rRpfPzxx4kex+3bt/nqq68ICwujXr16tGjRgoIFC1rXR0dH069fP8aMGUONGjX49ddf6dy5s3X9sWPH2LJlC/nz52f37t18+umnBAYG4uzsTHBwMH369LEei61xHDlyhO+//55169bh4OBAnz59HluOpC8pnkCWKFGCHTt2WHsgAXbs2EGJEiVSump5Tukm08+3FyVJeRalx/eeaXLylxmXICXGzs6OqVOn0qxZswSdJImpWLGi9fGQIUPYuXMnixcvJjQ0lPDwcG7fvp1gn23btnHz5k127doFQFRUFC+99NJj66pTpw4ALi4uvPTSS1y/fj1eAnn06FEAatSoAUCVKlV4/fXXrevz5s1L/vz5Adi+fTuNGzfG2dkZAE9PT8aPH8/Zs2efKI7du3dTr149ay9qixYtWL58+WPLkvQjxRPIkSNH0q1btwRjIMePH5/SVYuIiKSYvHnz8sknnzBs2DCaNWuWpH0cHR2tjwcPHkxMTAyNGjWiZs2aXLhwAcMwEuxjsVgYMWKENdGLiIjg3r17j60rU6ZM1scmkylB2Waz+aHLHharxWJJUL5hGERHRycoOyoqKklx3L/P/fXKsyHFZ2G3bduW8ePH069fPxwcHOjXrx/jx4/X+EcREXnmNWzYkLfffpulS5c+dL3ZbCY6Ovqh63bs2EGfPn1o3LgxAPv27SMmJibBfu7u7qxYsYLIyEgsFgs+Pj7MmDHjqWMvWrQoGTNm5JdffgFix0MePXoUk8mUYNvq1auzadMmrly5AsCaNWusYxdz5szJwYMHAQgLC2PPnj2Prfvtt99m8+bN3LhxA4vFwvr165/6eCR1pcpvYbdt21YJo4iIPJdGjRrF77///tB1tWvXZsaMGQl65QAGDRpEnz59cHR0xMnJiUqVKnH69OkE+33wwQdMnjyZ5s2bExMTQ4kSJawTXZ6Gvb09fn5++Pr6MmPGDAoXLkyuXLlwcHDgzp078batVq0anTt3plOnTlgsFpydnVm4cCF2dnZ07NiRjz76iAYNGlCgQAGqVKny2Lpr1KjBkSNHaNGiBdmyZaN48eJcvXr1qY9JUo/JeFh/+f87dOiQxipKuuLm5mb9S1eeT4W9N6bLsXbpUemlpTnQ6UCq1JVeX5eU+Ex4kb77Jk+eTLdu3ciVK5d1lvSWLVvIli1bWocm6Vyq9ECKJBcljyJyP30mPJ38+fPTuXNn7O3tMQyDcePGKXmUJFECKSIi8oLq0KEDHTp0SOsw5Bmk38IWEREREZuoB1JE0pXsmTPoXpBJ5FjEJdXaKnvmDKlSj4g8G5RAiki6ss+3flqH8AxJf5NaROTFoEvYIiIiImITJZAiIiIiYhMlkCIiIiJiEyWQIiIiImITJZAiIiIiYhMlkCIiIiJiEyWQIiIiImITJZAiIiIiYhMlkCIiIiJiEyWQIiIiImITJZAiIiIiYhMlkCIiIiJiEyWQIiIiImITJZAiIiIiYhMlkCIiIiJiEyWQIiIiImIT+7QOQETkWVDYe2Nah2ATxyIzuX1yUFqHkajsmTOwz7d+WochIk9ACaSISBKFTmqS1iEkWeml3uk+3mctKReR/9ElbBERERGxiRJIEREREbGJEkgREUk+586ldQQikgqUQIo8BTc3t7QOQST92L4dChaEHTuStVi9z0TSH02iEXkKf//9d1qHIJI+REdD585gGLH/Hz4M9snzFZPe3mfFihXD1dUVO7v4fTBz586lQIECSS6nZ8+eNGjQAE9Pz+QOMUUkFu/ixYvZsGEDhmFgsVioXr06gwYNImPGjMkaw4EDB1i8eDFz5sxJ1nLFdkogRUTk6fn5QVhY7OOLF8HfHwYOTNOQUtLSpUtxdnZO6zDShW+//ZYtW7YQGBiIg4MD9+7do3///vj7+zN48OBkrat06dJKHtMJJZAiIvJ0Ll4EHx+IiIh9HhEBo0ZB27bg4pK2saWykJAQZs6cScGCBTl27BjR0dF88sknVKxYkbCwMLy9vQkPDydfvnxcvnzZul9QUBCBgYFERUVx/fp1unfvTrt27QgODuaHH37Azs6OU6dO4eDgwOTJkylatCinTp1ixIgRXL9+nZdffhnDMGjatCmenp788ccfTJs2jTt37mBnZ0ffvn2pVasWwcHBBAUFcefOHZycnFi+fDmrV68mICAAi8VCjhw58PHxoWjRoonGe79Lly4RExPD3bt3cXBwIFOmTPj4+HDlyhUAvL29yZQpE4cPH+by5ctUq1aNUaNGkSFDBk6cOMH48eO5du0aMTExdOzYkZYtW1rb5PPPP8fOzo6cOXMyefJkTp8+zdixY9mwYQORkZFMmzaNvXv3EhMTQ8mSJRk1ahROTk589dVXrFy5kgwZMpApUybGjBnDa6+9lvInwAtECaTIU9K97OSFFxAAMTHxl8XExC5/TC9kenz/XLlyJd5lWi8vL7y8vOJt06lTp3iXsAsUKMDcuXMB2L9/P76+vpQoUYLPPvuMmTNn8uWXXzJmzBjKli3LwIEDOXXqFM2aNQMgIiKC1atXs2jRInLmzMlff/1Fly5daNeuHQB79+5lw4YN5MmTh7Fjx7Jo0SImT57M0KFD8fDwoF27dpw4cYIWLVrQtGlTrl+/zvDhw1myZAkFChQgLCyM1q1bU6xYMQCOHz/O1q1bcXJyYs+ePaxbt44VK1aQOXNmduzYQd++ffn2228fGe+DmjdvzrZt23B3d6dUqVKUL1+eOnXqUKlSJes2+/fv58svvyRDhgx07dqVwMBA2rRpQ//+/ZkyZQqlSpXi5s2beHl58dprr+Hg4MC0adNYu3YtefPm5YsvvmD+/Pk0afK/e5suWrQIs9lMcHAwJpOJGTNmMG3aNHx8fJgwYQJbt24ld+7crFu3jt9//10JZDJTAinylNL7zZoleaTHRCfdaNcutgfyfmZzbA/kYyTl/WOa/KSBPRlnZ2eCg4MT3SaxS9j58uWjRIkSAJQsWZK1a9cCsGvXLoYNGwZAoUKFqFy5MgBZsmRhwYIF/Pzzz4SGhnL48GFu375tLa9UqVLkyZPHWt4PP/zA9evXrUkZQNGiRalSpQoAf/31F5cuXaJPnz7WMkwmE0eOHAFix3A6OTkBsG3bNk6dOkWbNm2s2964cYNr1649Mt4HZc2alc8++4wzZ87w66+/smfPHnr06EG7du0YMmQIEJtkZsmSBQAPDw9+/PFHqlSpwunTpxkxYoS1rLt37/LPP/9w79493N3dyZs3LwCdO3cGYnt442zbto2bN2+ya9cuAKKionjppZcwm800bNiQNm3aULNmTdzd3alRo8ZDY5cnpwRSRESejosLjB37v8vYWbLAuHEv3OXrOA4ODtbHJpMJwzASPAaw//9JRhcvXsTLy4vWrVtTsWJFGjZsyE8//ZRoeWazGSBeeXHLYmJiKFq0KKtXr7auCwsLw9nZmW+++QZHR0frcovFgoeHhzXRs1gshIeHkz179kfG+6DFixdTsWJFKlSoQMGCBWnVqhW//fYb3bt3t5YbF1tczHZ2dsTExJA1a1bWr19vXffff/+RNWtWAgMDMZlM1uV3797l3AO3iLJYLIwYMcKaHEZERHDv3j0Apk2bxtGjR9m1axeLFi1i/fr1zJ49+6Hxy5PRbXxEROTp9esH/99LRp480Ldv2saTDlWvXp3AwEAAzp8/b+1NO3jwIM7OznzwwQe4u7tbk8eYB4cF3MfJyYkKFSpYe0rPnDnD7t27MZlMlCtXjlOnTrF3714ADh06RIMGDQiLm+R0H3d3dzZu3Eh4eDgAAQEBdOrUKdF4H3T37l2mT5/OtWvXrMuOHj1KyZIlrc+//fZbIiMjuXfvHmvXrqVWrVoUKVIEBwcHawJ54cIF3nnnHQ4ePEjlypXZvXu3Na6VK1cyderUBLGvWLGCyMhILBYLPj4+zJgxgytXrlCjRg1y5MhB586dGThwIAcOHHhkW8qTUQ+kiIg8PXt7+PxzqFEDvvgi2W7hk149OAYSYPDgwfF6Cx/k6+vL8OHDadSoEXny5KF48eIAVKtWjaCgIBo2bIjJZOLNN9/E2dmZU6dOJRrD5MmTGTlyJF999RUuLi4UKFAABwcHnJ2dmTNnDlOmTOHevXsYhsGUKVMoUKAAe/bsiVeGu7s73bt3p2vXrphMJpycnPD398dkMj0y3gd98MEHmEwm2rRpg8lkwmKx4ObmxqxZs6zbODg40K5dO27cuEGDBg1o0aIFdnZ2zJs3j/Hjx/Ppp58SHR3NgAEDqFixIgBDhgzh/fffB+Dll19mwoQJhIaGxqt38uTJNG/enJiYGEqUKIG3tzdOTk707t2bzp074+DggNlsZty4cYm2pdjOZNzfP/2AQ4cOWcdxiEhCbm5uHDx4MK3DkFRQ2HvjMzXetfTS0hzolAa9LufOQf78Sdo0qW2a2u+zZ+W7b/78+dSvX5+iRYty8+ZNmjZtyuLFi9PdZBFvb29ef/11unXrltahSDJ6vv9EFElhSh5FHpDE5NEWep89XOHChRk0aJB1PGH37t3TXfIozy8lkCIiIs+gRo0a0ahRo7QO47EmTZqU1iFICtAkGhERERGxiXogRUSSIHvmDM/UvSAdi7ik+3izZ86Q1iGIyBNSAikikgT7fOundQg2enYm/IjIs0eXsEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQm9mkdgIg82wp7b0zrEJ47jkVmcvvkoDSpO3vmDOzzrZ8mdYvIs0MJpIg8tdBJTdI6hOdK6aXeadam+oNARJJCl7BFRERExCZKIEVERETEJkognwNubm5pHYKIPM/OnUv1KvW5JpK+KYF8Dvz9999pHYKIPK+2b4eCBWHHjlStVp9rIumbEkgREXm46Gjo3BkMI/b/6Oi0jijNjRs3Dg8PDzw8PHBzc6NBgwbW53fv3qVYsWJcuXIlxer39/dny5YtNu3TtWtXm2Pq2LEjtWvXxsPDg6ZNm9KoUSP8/f2t67t3787x48dtKrNnz54EBwcD4OHhwY0bN2za31azZ89m3bp1wJO1m6+vL7Vr12bmzJkpEF18T9KeyeFJ2iWOZmGLiMjD+flBWFjs44sXwd8fBg5M05DS2qhRo6yPa9euzbRp0yhdunSq1R8SEsJrr71m0z47d+58orqGDh1Kw4YNAbhx4waNGzematWqVKxYkcWLFz9RmXHWr1//VPsnxYABA6yPn6TdAgMD2bZtG3ny5Enu0BJ42vZ8Uk/SLnGUQIqISEIXL4KPD0RExD6PiIBRo6BtW3BxSdvY0jk/Pz/27dvHtWvX6NatG+3btyc4OJigoCDu3LmDk5MTy5cvZ/Xq1QQEBGCxWMiRIwc+Pj4ULVqUkydPMmbMGCIiIrh06RLFixdn1qxZBAUFcfDgQaZMmYLZbCZnzpxMmjQJi8UCxPbwNWjQIF4sw4cPB6BTp04sWrSIW7duMWbMGK5du4bJZKJr1640a9bssccU8f/nQc6cOYHY5Hn27NmULl2awMBAli9fjp2dHbly5cLHx4ciRYoQFhaGt7c34eHh5MuXj8uXL1vLK1asGLt37+aDDz6gS5cu1rinTp0KwJAhQx7ZPt7e3ly7do0zZ85Qs2ZNatWq9dB28Pb25vXXX8fBwcHabpGRkYwdO5ZVq1ZRpEgRADp37kyHDh2oW7euNb527dphGAbdu3fH19eXoUOHUqZMGY4cOcLgwYMpXLjwQ9sxJCSEGTNmkDdvXk6ePEnmzJnp0aMHy5cv5+TJk9SvX58RI0YkaN+49rx9+3aS9g8JCWHatGnky5ePf//9FwcHByZNmkTRokW5efMmn3zyCYcPH8ZkMlG9enUGDx6Mvb09bm5u1KlTh8OHD/Puu+/afD7dTwnkc0L3bhOR5GL9POkbmHDlzN9SN5g0cOXKFTw9Pa3Pvby88PLySvL+BQsWxNfXl3/++QcvLy9at24NwPHjx9m6dStOTk7s2bOHdevWsWLFCjJnzsyOHTvo27cv3377LatWraJZs2Z4eHgQFRWFp6cn27Zto3379mzevJn27dtTr149OnXqRJcuXWjSpAmHDx8mMDAwwRf+xIkTCQ4OZunSpWTLlo2OHTsydOhQ6tevT1hYGK1ataJQoUKUL18+wXFMmTKF+fPnEx0dzalTp2jcuLE16Yqze/duPv30UwIDA3F2diY4OJg+ffqwceNGxowZQ9myZRk4cCCnTp16aKLaqlUrgoODadCgATExMXz99dcsX7480fYBuHv3Lhs3xp6nj2uH+9utYcOGHDhwgNWrVzN06FBOnz5NaGgotWrVihfXV199RbFixVi6dCnOzs4AvP7668yaNYvo6GgaNmz40HYEOHDgAL6+vpQsWZL333+fRYsWsWzZMm7dusXbb79Nt27dcEnkj7Ck7A9w8OBBhg0bxhtvvEFAQABDhgwhODiYcePGkSNHDr755huioqLo3bs3n332GT169CAqKopatWoxe/ZsILYH0pbz6X5KIJ8TupGzpBX98fL8CZ3UJPbSddGi/+uBBMiSBU6cSJUeSNPkFK/ikeISoSf1zjvvAFCiRAkiIyO5desWENvr5uTkBMC2bds4deoUbdq0se5348YNrl27xpAhQ9i5cyeLFy8mNDSU8PBwbt++naCeRo0aMWbMGLZu3cpbb73F4MGDE40rNDSUe/fuUb9+7C8Nubi4UL9+fbZv3/7QBPL+S9hXrlyhR48eLFq0iJ49e1q32b59O40bN7YmWZ6enowfP56zZ8+ya9cuhg0bBkChQoWoXLlygjoaN27MlClTuHTpEv/88w+FCxemcOHCrFq16pHtA1CxYsUnbod27drRoUMHBg0aRGBgIC1btsRsNie6D8Abb7zx2HasXLkyBQoUoGTJkgC88sorZM2alYwZM+Ls7EyWLFm4fv16oglkUvYHKF68uDWmFi1aMGbMGK5evcovv/xCQEAAJpOJjBkz0qZNG5YuXUqPHj3iHceDbG1HJZAiIpKQiwuMHfu/y9hZssC4cbp8nQT29rFfrSaTCQDDMABwdHS0bmOxWPDw8GDIkCHW5+Hh4WTPnp1BgwYRExNDo0aNqFmzJhcuXLCWcb82bdpQq1Ytdu7cyfbt2/H392fz5s1kypTpoXHFxMRYY4pjGAbRSZgc5ezszDvvvMOOHTviJZBxlzsfVqbJZIoXd1y73C9z5sw0aNCADRs28Oeff9KqVavHtg/Eb8tHtcOjFClShGLFivHjjz+yYcMGVq1a9djjv7/Ox7VjxowZ46172HEnJqn7PyzpNZvNWCyWePFZLJZ4r/H9bXc/W88nzcIWEZGH69cP4iYQ5MkDffumbTzPEXd3dzZu3Eh4eDgAAQEBdOrUCYAdO3bQp08fGjduDMC+ffuIiYkBYhOEuGSgTZs2HDp0CE9PT8aOHcuNGze4dOlSgrri9nn11Vext7fn+++/ByAsLIzvvvuOt95667HxRkVFsXPnTsqUKRNvefXq1dm0aZN1lveaNWvIkSMHhQoVonr16gQGxg6DOH/+PCEhIQ8tu3Xr1qxdu5Y//vjDesk0sfZ5UFLa4f52g9heyClTplCmTJlEewMf5mnaMTkdPnyYw4cPA7ETfsqXL0+2bNlwd3fnyy+/xDAMIiMjWbVq1SNje5LzKY56IJ8DpUqVSusQROR5ZG8Pn38ONWrAF1/EPk8lz/vnmru7O927d6dr166YTCacnJzw9/fHZDIxaNAg+vTpg6OjI05OTlSqVInTp08DsZMtZsyYQVRUFB999BETJkxg1qxZmEwm+vbtS4ECBRLU1bBhQzp27Iifnx/z5s1j3Lhx+Pn5ERMTQ58+fahSpcpDY4wbA2kymbhz5w5VqlShV69e8bapVq0anTt3plOnTlgsFpydnVm4cCF2dnb4+voyfPhwGjVqRJ48eShevPhD63Fzc8NsNtOwYUNrb1di7fOgpLTD/e3WvHlzatWqxahRo+JdIk+qDBkyPLIdH5Ukp4RcuXIxa9Yszp07h7OzM1OmTAFi7xQwbtw43n33XaKioqhevXqC1y3Ok5xPcUzGw/rF/9+hQ4coUaLEUx6iiDzPCntv1BjcZFZ6aWkOdDqQJnU/9PU8dw7y50+TeNKCvvuef3/++SejRo1iw4YND01K07uQkBDGjh3Lhg0b0iwG9UCKiEjiXqDkUZ5/w4YNY8+ePcycOfOZTB7TCyWQIiIi8sKYPDkNp/gnk8qVK6dp7yNoEo2IiIiI2Eg9kCLyVLJnzqB7QSYzxyIuadam2TNnSJN6ReTZogRSRJ7KPt/6aR3Cc0iTkkQkfdMlbBERERGxiRJIEREREbGJEkgRERERsYkSSBERERGxiRJIEREREbGJEkgRERERsYkSSBERERGxSaL3gbx37x6HDh1KrVhERETS3L1799I6BJF0z2QYhpHWQYiIiIjIs0OXsEVERETEJkogRURERMQmSiBFRERExCZKIEVERETEJkogRURERMQmSiBFRERExCapkkBu27aNd999lwYNGtC/f39u3bqVGtU+89avX0/Tpk3x8PCgTZs2HDhwgJiYGMaPH0/Dhg2pV68eAQEBaR3mM2HLli2UL18eQG34BI4cOULHjh1p1qwZnp6eHDx4UO1oox9++IF3330XDw8P3nvvPU6fPq02TCLDMBg2bBhLliwBEn8Ph4aG0r59exo3bkzLli05ceJEWoUt8nwzUtjly5eNKlWqGCdPnjQMwzCmTJli+Pr6pnS1z7wTJ04Y1apVM8LCwgzDMIxt27YZNWrUML788kvj/fffN6Kiooxr164ZDRo0MPbt25fG0aZvJ0+eNOrWrWuUK1fOMAxDbWij27dvG9WqVTO2bdtmGIZh/PDDD0aDBg3Ujja4c+eOUbZsWSM0NNQwDMP4/PPPje7du6sNk+D48eNGx44djbJlyxqffvqpYRiJv4dbtGhhfP3114ZhxH5uNmnSxLBYLGkWv8jzKsV7IHfs2EHp0qUpXLgwAG3btuWbb77B0P3LE5UxY0bGjRtH7ty5AXBzc+O///5j8+bNeHp6Ym9vT/bs2WnSpAlff/11Gkebft25c4chQ4bg7e1tXbZlyxa1oQ127txJwYIFqVGjBgB16tRh1qxZakcbxMTEYBgGN2/eBCAiIoJMmTKpDZNgxYoVtGrVioYNG1qXPardwsLC+Pfff2nSpAkANWrU4Pbt2/zzzz9pFb7IcyvFE8iLFy+SJ08e6/M8efJw69YtIiIiUrrqZ1qBAgWoWbMmEHv5ZuLEidSuXZtLly6RN29e63Z58uTh4sWLaRRl+jd69Gi8vLwoVqyYddmFCxfUhjY4efIkL7/8MiNGjMDT05MuXboQExOjdrRBlixZ+OSTT2jTpg3u7u6sWLGCjz76SG2YBKNHj+bdd9+Nt+xR7XbhwgVy586Nnd3/vtpcXFzUpiIpIMUTSIvFgslkSlixnebvJMXt27cZMGAAp0+fZty4cRiGEa89DcNQWz7CihUrsLe3p2XLlvGWqw1tEx0dzc8//4yXlxfBwcF06NCBHj16EBkZqXZMoiNHjjB37lw2bdrEjh076NWrF/369Uvw+ag2TJpHvYcf9n1jGAZmszm1QxR57qX4J1XevHkJDw+3Pg8LCyN79uw4OjqmdNXPvPPnz9OmTRvMZjPLli0jW7ZsCdozPDw8Xg+v/M/atWs5cOAAHh4e9OjRg7t37+Lh4YGLi4va0Aa5c+emaNGilC1bFoC6desSExNDwYIF1Y5JtGPHDipUqMArr7wCQPv27Tl27Bj58uVTGz6BR30O5suXj0uXLsUbIqU2FUkZKZ5Auru7s2/fPkJDQwFYuXIlderUSelqn3m3bt2iY8eO1K9fn5kzZ+Lg4ADEjj9bs2YN0dHR3Lhxg40bN1K3bt00jjZ9CgoKYsOGDaxfv55Fixbh4ODA+vXrqVevntrQBm+//TZnz57l4MGDAOzduxeTyUTdunXVjklUsmRJ9u7dy3///QfEjuErUKCA3s9P6FHtlidPHl555RU2bdoEwPbt27Gzs8PV1TWNIxZ5/tindAUvvfQSEydOpH///kRFRfHKK68wefLklK72mbdixQrOnz/PDz/8wA8//GBdvmTJEk6fPo2HhwdRUVF4eXnx5ptvpmGkz562bduqDW3w8ssvM3fuXD755BPu3LlDxowZ8fPzo1y5cmrHJKpatSrdunWjY8eOZMiQgezZszNv3jyKFCmiNnwCib2HZ8yYgY+PD/PnzydjxozMnj1bwwJEUoDJ0HRoEREREbGB/iwTEREREZsogRQRERERmyiBFBERERGbKIEUEREREZsogRQRERERmyiBFLFBREQE7733Hl5eXhw+fBiA3377jUWLFj1yn02bNlGuXDnCwsISLdvb25tffvkl3rJLly7x8ccfP3XcD5o2bRrBwcHJXq6IiLwYlECK2GDnzp3Url0bX19fgoKCMAyDZcuW0alTp0fus3r1ajp06MCqVatsru/ll19OkQRSRETkaSiBFLGBo6Mjd+7c4fbt2zg6OvLNN99Qr149MmXK9NDtz5w5w/Xr1+nZsyfr168nKioKgNDQUDp06ICXlxedOnXiypUrAAQGBvLee+/h6enJ/v37OXv2LK1btwZgz549tG3blg4dOjB8+HCioqLo27cve/bsAWD//v307t2bqKgoRowYQfv27Wnbti0hISEAfPfddzRr1oyuXbuyb9++lG4qERF5jimBFLHBW2+9xeXLlwkICKB169Zs2bKF4sWLM3r0aBYvXpxg+6CgIFq0aEHWrFkpV66c9VeFJk+eTI8ePQgMDMTLy4t//vkHgFKlSrFs2TI6dOgQ7xKzYRj4+Pjg7+/Pl19+iYuLC2vXrqVVq1asXbsWiP3t79atW7N69Wpy5szJihUrmDdvHmPGjAFg6tSpfP755yxZssT605giIiJPQgmkiA3s7OwYNWoU06dPZ+PGjbz33nvMnz+fgQMHcuHCBU6ePGndNiYmhm+++YbNmzfTrVs3QkND+fLLLwE4efIk5cuXB6Bx48a4u7sDsQkkQK5cubh79661rCtXrhAeHs7AgQPp2LEjO3fu5Pz581SvXp0DBw5w7do1fvvtN95++22OHj3KL7/8QseOHenfvz/R0dH8999/ODk5kTNnTkwmk7VuERGRJ5Hiv4Ut8jy6fPkyoaGh9OzZkyVLlmA2mzGZTNy5c8e6zc8//4ybmxtz5syxLmvQoAGHDx+maNGiHDhwgLfeeouvv/6a69evA2AymR5aX86cOcmTJw/z5s0ja9as/Pjjjzg6OmJnZ0fDhg35+OOPqVu3LmazmVdffZU8efLQq1cv7t69y/z588mWLRs3b97kypUrODs7c+DAAfLkyZOyjSQiIs8tJZAiT2D+/Pn06tULgHbt2tGtWzfy5ctH8eLFrdusWrWKVq1axduvZcuWrFixgqFDhzJ69Gjmz5+Pg4MDU6dO5e+//35kfXZ2dowcOZIePXpgGAZZsmRhypQpALRo0YK6devy3XffAdCmTRtGjRpFhw4duHXrFu3atSNjxoxMnDiRbt26kT17duzt9dYXEZEnZzIMw0jrIERERETk2aExkCIiIiJiEyWQIiIiImITJZAiIiIiYhMlkCIiIiJiEyWQIiIiImITJZAiIiIiYhMlkCIiIiJik/8DxFMK1QYCE0kAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "goal15 = sdg_current.filter(regex = 'Country|^Normalized Score sdg15',axis=1)[0:32]\n", "\n", "fig = plt.figure(figsize = (8,4))\n", "ax = plt.subplot()\n", "goal15.boxplot(vert = False, ax = ax).invert_yaxis()\n", "\n", "#Mark Poland\n", "poland_15 = goal15.iloc[15,1:7].tolist()\n", "plt.scatter(x = poland_15, y = arange(1,7), marker = \"d\", color = 'red', label = 'Poland')\n", "\n", "ax.set_yticklabels(['Protected Land', 'Protected Freshwater', 'Oxygen in Rivers', 'Nitrate in ground', \n", " 'Endangered Species', 'Threats to Biodiversity from imports'])\n", "ax.set_title('Normalized Scores, Goal 15: Life On Land', size = 16)\n", "\n", "ax.yaxis.set_ticks_position(\"right\")\n", "\n", "plt.xlabel('% Achieved')\n", "plt.legend()\n", "sns.set_style('whitegrid')\n", "ax.grid(False)\n", "ax.tick_params(labelsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Poland is in or near the top 25% of countries protecting biodiversity by most measures. This is interesting, as there has been much news coverage of the current government rolling back protections - for example, increasing logging in Białowieża National Park. It would be worthwhile to research further to determine which measures are most contributing to effective protection and whether they are continuing at present.\n", "\n", "## Conclusions\n", "\n", "The Sustainable Development Goals provide a top-level summary of countries' progress in many different areas. In order to compare across countries, they must be broad and may be based on old or sparse data. In addition, the choice of model, namely averaging all sub-indicator scores with equal weights, affects the final outcomes. Hence, these conclusions are only a tentative starting point for considering Poland's particular situation and should not be considered as extremely precise measurements. Despite these limitations, some interesting trends can still be observed.\n", "\n", "To improve in the categories in which Poland lags the EU average, the data suggest the following are key issues to address:\n", "- Innovation & Industry: Increasing patents & building digital skills\n", "- Gender Equality: Increasing the number of women in leadership\n", "- Clean Energy: Increasing renewable energy & decreasing carbon emissions\n", "- Sustainable Cities: Decreasing air pollution\n", "\n", "Poland's existing strong secondary education system, especially in science, could be harnessed by policymakers to address these issues. For example: the government, nonprofits and/or relevant businesses could support programs in secondary & tertiary education that encourage students - particularly women - to pursue innovation in sustainable energy as scientists or entrepreneurs.\n", "\n", "Existing effective policies for protecting biodiversity might also provide a blueprint for further environmental protection policies. Finally, policies from comparable countries such as Slovenia and Czechia who are outperforming in these areas could also be studied and adapted for Poland.\n", "\n", "While this analysis represents only the tip of the iceberg and deeper analysis would doubtless uncover other issues and nuances, it does represent a snapshot of Poland's progress and challenges in sustainable development." ] } ], "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }