{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# E-commerce: Product Range Analysis\n", "\n", "---\n", "(This was the final project in the Data Analytics course by Practicum by Yandex. Due to copyright, the raw dataset is unavailable for examination, but here is my analysis of the dataset we were provided)\n", "\n", "\n", "## Project Goal:\n", "Find ways to improve profits for the coming year by analyzing how the company did this year.\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Project Description\n", "\n", "\n", "\n", "**PROBLEM:** How can we improve profits -- which means asking the questions:\n", "* What are the best selling products? Are they the most profitable because they sell the most, sell at the highest, or combination?\n", "* Who are the top customers? Do they make up a large percentage of total sales, or does the majority of sales come from many small purchases?\n", "\n", "**SOLUTION:** \n", "* Analyze sales data to answer the questions posed.\n", "\n", "\n", "Description of the data\n", "\n", "\n", "\n", "* ```InvoiceNo``` — order identifier\n", "* ```StockCode``` -- item identifier\n", "* ```Description``` -- item name\n", "* ```Quantity```\n", "* ```InvoiceDate``` -- order date\n", "* ```UnitPrice``` -- price per item\n", "* ```CustomerID```\n", "\n", "\n", "\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# Table of Contents\n", "\n", "Opening Data\n", " \n", "### Step 1: [Data Preprocessing](#preprocessing)\n", " * Rename variables to lower-cased with underscores between words\n", " * Feature engineering\n", " * Check for NULLS\n", " * Check for duplicates\n", " * Check for outliers\n", " \n", "### Step 2: [Carry out EDA](#data_analysis)\n", "\n", "### Step 3: [Testing hypothesis](#testing_hypothesis)\n", "\n", "### Step 4: [Conclusion](#conclusion)\n", "\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Opening the Data" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "sns.set() # Setting seaborn as default style even if use only matplotlib\n", "sns.color_palette(\"tab10\") # Set default color codes for seaborn\n", "\n", "%matplotlib inline\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# DISPLAY OPTIONS (uncomment and customize to activate)\n", "\n", "# prevent annoying tendency of not displaying 'middle' columns if data is very wide\n", "# change the max_columns value for even wider datasets\n", "\n", "# pd.options.display.max_columns = None\n", "# pd.options.display.max_columns = 40\n", "\n", "# see \"all\" the rows if needed\n", "# change max_rows to desired number\n", "\n", "# pd.options.display.max_rows = 105\n", "\n", "# pd.reset_option('^display.', silent=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Custom Functions\n", "I'ved coded up some functions that I seem to use regularly" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# A helper function for my other functions\n", "# returns the name of a DataFrame variable -- can be utilized in automation\n", "def get_df_name(df):\n", " name = [x for x in globals() if globals()[x] is df][0]\n", " return name" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# checks a single dataframe for duplicates, as well as show corresponding % of total\n", "def show_info_on_duplicates(df):\n", " # Percentage of rows that are duplicates\n", " print(\"There are:\\n\" + str(df[df.duplicated()].shape[0])\n", " + \" duplicate rows, making up\\n\"\n", " + (str(round(df[df.duplicated()].shape[0] / df.shape[0] * 100, 2))) \n", " + \"% of the total \" \n", " + str(df.shape[0]) \n", " + \" rows.\")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def show_info_on_nulls(df):\n", " '''This function takes a dataframe and an optional column name and prints out the\n", " total number of rows that contain NaN's, either anywhere in the dataframe (by default),\n", " or in the specified column_name given as the second argument. The function also\n", " will print out the percentage of the total dataframe that these found NaN's make up.\n", " \n", " PURPOSE: help the user decide whether or not s/he should consider dropping these particular rows\n", " \n", " REQUIREMENT: get_df_name()\n", " \n", " RETURNS: None. Displays a printout.\n", " \n", " Version: 2020-09-28\n", " '''\n", " print(\"DataFrame: \" + get_df_name(df))\n", " total_rows = df.shape[0]\n", " \n", " raw_data = {'Feature': df.columns}\n", " new_df = pd.DataFrame(raw_data, columns = ['Feature'])\n", " \n", " print(\"Observations (rows): \" + str(total_rows))\n", " print()\n", " num_of_nans = []\n", " percent_of_total = []\n", " for each in df.columns:\n", " num_of_nans.append(df[df[each].isnull()].shape[0])\n", " percent_of_total.append(round(df[df[each].isnull()].shape[0] / df.shape[0] * 100, 2))\n", " new_df['NaNs'] = num_of_nans\n", " new_df['% total'] = percent_of_total\n", " print(new_df)\n", " print()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "import re\n", "\n", "def rename_variables(original_list):\n", " '''This function takes a list of an original CamelCase-name-styled variables -- the list can\n", " simply be the column names from df.columns -- and returns a list with all the variable names converted\n", " to lowercased versions, and with underscores between previously capitalized words.\n", " \n", " Librar(ies) required: re\n", " \n", " PURPOSE: make variable names for readable or 'Pythonic'\n", " \n", " RETURNS: a list of pythonically named variable names\n", " '''\n", " new_list = []\n", " \n", " for each_name in original_list:\n", " \n", " # Splitting on UpperCase using re - but not consecutive capital letters like 'ID' for example\n", " single_variables_names_list = re.findall(r'[A-Z](?:[A-Z]*(?![a-z])|[a-z]*)', each_name)\n", "\n", " lowercased_string_list = [each_string.lower() for each_string in single_variables_names_list]\n", " \n", " # if original list doesn't have any capital letters, we'd have an empty list -- let's check\n", " if not lowercased_string_list:\n", " return original_list\n", " else:\n", "\n", " # Recombine using underscores\n", " new_list.append('_'.join(lowercased_string_list))\n", " \n", " return new_list" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Read in the data" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# Set the correct path -- uncomment the one you want to use\n", "\n", "# Practicum path - uncomment the following line for reviewer to use on Practicum platform\n", "# path = \"/datasets/\"\n", "\n", "# local path - uncomment the following line to use inside project file\n", "path = 'datasets/'" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(path + 'ecommerce_dataset_us.csv', sep = '\\t')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Check the basics" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 541909 entries, 0 to 541908\n", "Data columns (total 7 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 InvoiceNo 541909 non-null object \n", " 1 StockCode 541909 non-null object \n", " 2 Description 540455 non-null object \n", " 3 Quantity 541909 non-null int64 \n", " 4 InvoiceDate 541909 non-null object \n", " 5 UnitPrice 541909 non-null float64\n", " 6 CustomerID 406829 non-null float64\n", "dtypes: float64(2), int64(1), object(4)\n", "memory usage: 28.9+ MB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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7306854227884688BEACH HUT DESIGN BLACKBOARD601/25/2019 10:434.2514911.0
43299957390223409PHOTO FRAME LINEN AND LACE LARGE610/30/2019 14:513.7517428.0
31320556447321495SKULLS AND CROSSBONES WRAP2508/23/2019 12:330.4216722.0
16139655047416235RECYCLED PENCIL WITH RABBIT ERASER204/16/2019 13:580.42NaN
24046355810223239SET OF 4 KNICK KNACK TINS POPPIES106/24/2019 14:064.1517372.0
32863856579623200JUMBO BAG PEARS1009/05/2019 10:072.0814916.0
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50936757929785123aWHITE HANGING HEART T-LIGHT HOLDER111/27/2019 11:236.63NaN
407579C57189622494EMERGENCY FIRST AID TIN-210/17/2019 14:181.2516533.0
25228555910723091ZINC HERB GARDEN CONTAINER107/04/2019 11:226.2515334.0
22580455673321564PINK HEART SHAPE LOVE BUCKET106/12/2019 11:532.9516919.0
4244053998821354TOAST ITS - BEST MUM212/21/2018 16:061.2518116.0
5503654097772801C4 ROSE PINK DINNER CANDLES101/10/2019 15:012.51NaN
50672557915222734SET OF 6 RIBBONS VINTAGE CHRISTMAS611/26/2019 13:262.8912479.0
8839254380222379RECYCLING BAG RETROSPOT102/11/2019 12:032.1013742.0
11115354571385049gCHOCOLATE BOX RIBBONS103/05/2019 10:122.46NaN
456092C57566923462ROCOCO WALL MIRROR WHITE-111/08/2019 15:0019.9512417.0
53511958118823295SET OF 12 MINI LOAF BAKING CASES812/05/2019 16:470.8317735.0
26559956022522322BIRD DECORATION GREEN POLKADOT507/13/2019 16:270.83NaN
19269155346420725LUNCH BAG RED RETROSPOT5005/15/2019 11:071.6516218.0
2330753819722746POPPY'S PLAYHOUSE LIVINGROOM312/08/2018 10:562.1014419.0
4861454046922966GINGERBREAD MAN COOKIE CUTTER301/05/2019 14:041.2512484.0
41615357255221770OPEN CLOSED METAL SIGN110/22/2019 17:079.9614096.0
45059457517623377PACK OF 12 DOLLY GIRL TISSUES111/06/2019 18:290.83NaN
\n", "
" ], "text/plain": [ " InvoiceNo StockCode Description Quantity \\\n", "181401 552468 21136 PAINTED METAL PEARS ASSORTED 8 \n", "134500 547850 22284 HEN HOUSE DECORATION 1 \n", "479735 577175 22899 CHILDREN'S APRON DOLLY GIRL 6 \n", "104591 545188 22554 PLASTERS IN TIN WOODLAND ANIMALS 3 \n", "444255 574722 85071A BLUE CHARLIE+LOLA PERSONAL DOORSIGN 4 \n", "33857 539300 22629 SPACEBOY LUNCH BOX 1 \n", "504418 578949 22300 COFFEE MUG DOG + BALL DESIGN 6 \n", "85499 543474 22470 HEART OF WICKER LARGE 3 \n", "178184 552229 20731 POSY CANDY BAG 1 \n", "335253 566281 22297 HEART IVORY TRELLIS SMALL 24 \n", "176220 551997 22970 LONDON BUS COFFEE MUG 2 \n", "453261 575477 23522 WALL ART DOG AND BALL 2 \n", "200014 554110 82482 WOODEN PICTURE FRAME WHITE FINISH 6 \n", "63782 541592 85173 SET/6 FROG PRINCE T-LIGHT CANDLES 1 \n", "111502 545721 21033 JUMBO BAG CHARLIE AND LOLA TOYS 10 \n", "238078 557896 22175 PINK OWL SOFT TOY 1 \n", "248548 558861 23052 RECYCLED ACAPULCO MAT TURQUOISE 4 \n", "476807 577034 21070 VINTAGE BILLBOARD MUG 36 \n", "26521 538515 22550 HOLIDAY FUN LUDO 36 \n", "313529 564510 85019B BLOSSOM IMAGES NOTEBOOK SET 24 \n", "24054 538312 22576 SWALLOW WOODEN CHRISTMAS DECORATION 3 \n", "77147 542711 21485 RETROSPOT HEART HOT WATER BOTTLE 1 \n", "350402 567634 22569 FELTCRAFT CUSHION BUTTERFLY 48 \n", "234166 557502 20979 36 PENCILS TUBE RED RETROSPOT 1 \n", "393211 570807 22993 SET OF 4 PANTRY JELLY MOULDS 12 \n", "300672 563209 23228 FILIGREE HEART BIRD WHITE 6 \n", "73068 542278 84688 BEACH HUT DESIGN BLACKBOARD 6 \n", "432999 573902 23409 PHOTO FRAME LINEN AND LACE LARGE 6 \n", "313205 564473 21495 SKULLS AND CROSSBONES WRAP 25 \n", "161396 550474 16235 RECYCLED PENCIL WITH RABBIT ERASER 2 \n", "240463 558102 23239 SET OF 4 KNICK KNACK TINS POPPIES 1 \n", "328638 565796 23200 JUMBO BAG PEARS 10 \n", "129783 547390 37448 CERAMIC CAKE DESIGN SPOTTED MUG 12 \n", "509367 579297 85123a WHITE HANGING HEART T-LIGHT HOLDER 1 \n", "407579 C571896 22494 EMERGENCY FIRST AID TIN -2 \n", "252285 559107 23091 ZINC HERB GARDEN CONTAINER 1 \n", "225804 556733 21564 PINK HEART SHAPE LOVE BUCKET 1 \n", "42440 539988 21354 TOAST ITS - BEST MUM 2 \n", "55036 540977 72801C 4 ROSE PINK DINNER CANDLES 1 \n", "506725 579152 22734 SET OF 6 RIBBONS VINTAGE CHRISTMAS 6 \n", "88392 543802 22379 RECYCLING BAG RETROSPOT 1 \n", "111153 545713 85049g CHOCOLATE BOX RIBBONS 1 \n", "456092 C575669 23462 ROCOCO WALL MIRROR WHITE -1 \n", "535119 581188 23295 SET OF 12 MINI LOAF BAKING CASES 8 \n", "265599 560225 22322 BIRD DECORATION GREEN POLKADOT 5 \n", "192691 553464 20725 LUNCH BAG RED RETROSPOT 50 \n", "23307 538197 22746 POPPY'S PLAYHOUSE LIVINGROOM 3 \n", "48614 540469 22966 GINGERBREAD MAN COOKIE CUTTER 3 \n", "416153 572552 21770 OPEN CLOSED METAL SIGN 1 \n", "450594 575176 23377 PACK OF 12 DOLLY GIRL TISSUES 1 \n", "\n", " InvoiceDate UnitPrice CustomerID \n", "181401 05/07/2019 15:33 1.69 13141.0 \n", "134500 03/25/2019 12:06 1.65 14472.0 \n", "479735 11/16/2019 10:58 2.10 14849.0 \n", "104591 02/26/2019 15:19 1.65 14056.0 \n", "444255 11/04/2019 14:45 0.39 14502.0 \n", "33857 12/14/2018 17:31 1.95 NaN \n", "504418 11/25/2019 14:30 2.55 14954.0 \n", "85499 02/06/2019 15:09 2.95 14415.0 \n", "178184 05/04/2019 15:40 0.83 NaN \n", "335253 09/09/2019 14:15 1.25 12748.0 \n", "176220 05/03/2019 15:47 4.96 NaN \n", "453261 11/07/2019 16:14 5.79 NaN \n", "200014 05/20/2019 14:35 2.55 13468.0 \n", "63782 01/17/2019 15:08 2.46 NaN \n", "111502 03/05/2019 10:52 2.95 15039.0 \n", "238078 06/21/2019 14:22 2.95 17611.0 \n", "248548 07/02/2019 12:19 8.25 13373.0 \n", "476807 11/15/2019 13:16 1.06 12847.0 \n", "26521 12/10/2018 14:43 3.39 17937.0 \n", "313529 08/23/2019 14:42 1.25 14194.0 \n", "24054 12/08/2018 13:48 0.85 16727.0 \n", "77147 01/29/2019 13:19 4.95 17894.0 \n", "350402 09/19/2019 13:35 3.39 12939.0 \n", "234166 06/18/2019 15:32 2.46 NaN \n", "393211 10/10/2019 12:44 1.25 13704.0 \n", "300672 08/12/2019 12:23 1.25 13527.0 \n", "73068 01/25/2019 10:43 4.25 14911.0 \n", "432999 10/30/2019 14:51 3.75 17428.0 \n", "313205 08/23/2019 12:33 0.42 16722.0 \n", "161396 04/16/2019 13:58 0.42 NaN \n", "240463 06/24/2019 14:06 4.15 17372.0 \n", "328638 09/05/2019 10:07 2.08 14916.0 \n", "129783 03/20/2019 16:08 1.49 12352.0 \n", "509367 11/27/2019 11:23 6.63 NaN \n", "407579 10/17/2019 14:18 1.25 16533.0 \n", "252285 07/04/2019 11:22 6.25 15334.0 \n", "225804 06/12/2019 11:53 2.95 16919.0 \n", "42440 12/21/2018 16:06 1.25 18116.0 \n", "55036 01/10/2019 15:01 2.51 NaN \n", "506725 11/26/2019 13:26 2.89 12479.0 \n", "88392 02/11/2019 12:03 2.10 13742.0 \n", "111153 03/05/2019 10:12 2.46 NaN \n", "456092 11/08/2019 15:00 19.95 12417.0 \n", "535119 12/05/2019 16:47 0.83 17735.0 \n", "265599 07/13/2019 16:27 0.83 NaN \n", "192691 05/15/2019 11:07 1.65 16218.0 \n", "23307 12/08/2018 10:56 2.10 14419.0 \n", "48614 01/05/2019 14:04 1.25 12484.0 \n", "416153 10/22/2019 17:07 9.96 14096.0 \n", "450594 11/06/2019 18:29 0.83 NaN " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.sample(50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observations\n", "* This is our largest dataset in our practicum. \n", "* Column names are camelCased -- we'll convert to snake_case \n", "* We have negative quantities as well as negative price, some very extreme. so we need to find explanations for them as well.\n", "* We appear to be missing a LOT of CustomerID's\n", "* InvoiceNo is currently a string type, but perhaps can be an int type.\n", "* InvoiceDate is currently of type string, but should be datetime.\n", "* CustomerID is of type float, but should be an int.\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# Data Preprocessing\n", " * Rename variables to lower-cased with underscores between words\n", " * Feature engineering\n", " * Check for NULLS\n", " * Check for duplicates\n", " * Check for outliers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Rename variables\n", "We'll use my custom function to change the variables from camelCased to lowercased with underscores" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "df.columns = rename_variables(df.columns)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['invoice_no', 'stock_code', 'description', 'quantity', 'invoice_date',\n", " 'unit_price', 'customer_id'],\n", " dtype='object')" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "* We renamed the CamelCasedVariables into lower_cased_with_underscore_variable_names to make them more Pythonic and consistent with how I normally (so far) have worked with them\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Feature Engineering\n", "We will add a total_price column, as we're going to look at sales totals by item/customer/date" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "df['total_price'] = df['quantity'] * df['unit_price']" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "9747747.933999998" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['total_price'].sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Check for nulls" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# check if any null values exist\n", "df.isnull().values.any()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DataFrame: df\n", "Observations (rows): 541909\n", "\n", " Feature NaNs % total\n", "0 invoice_no 0 0.00\n", "1 stock_code 0 0.00\n", "2 description 1454 0.27\n", "3 quantity 0 0.00\n", "4 invoice_date 0 0.00\n", "5 unit_price 0 0.00\n", "6 customer_id 135080 24.93\n", "7 total_price 0 0.00\n", "\n" ] } ], "source": [ "show_info_on_nulls(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "* 1454 rows are missing descriptions. However, they make up less 0.3% of the data, we can safely drop them.\n", "* 135037 rows with emtpy customer_id -- we'll have to take a closer look as they comprise more than 25% of the data.\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Find and delete duplicate rows" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "There are:\n", "5268 duplicate rows, making up\n", "0.97% of the total 541909 rows.\n" ] } ], "source": [ "show_info_on_duplicates(df)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "df = df.drop_duplicates()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "Nearly 1% of the data are duplicates?\n", "\n", "**ACTION REQUIRED:** ask Data Engineering why there are so many duplicates. Is there some UX bug where a user inadvertantly places an order more than once? Or some other issue?\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Null customers\n", "Let's take a closer look as they comprise more than 25% of the data" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
7461454250437413NaN556801/26/2019 12:030.00NaN0.0
22084355623185123A?400006/07/2019 15:040.00NaN0.0
26388556004023343came coded as 20713310007/12/2019 14:280.00NaN0.0
11580754613984988?300003/07/2019 16:350.00NaN0.0
7461554250579063DNaN256001/26/2019 12:040.00NaN0.0
44703557494122197POPCORN HOLDER182011/05/2019 17:421.95NaN3549.0
16054155046047556Bdid a credit and did not tick ret130004/16/2019 13:180.00NaN0.0
20375155455047566Bincorrectly credited C550456 see 47130005/23/2019 09:570.00NaN0.0
8279554325884611BNaN128702/02/2019 16:060.00NaN0.0
46779657636522197POPCORN HOLDER113011/12/2019 17:551.95NaN2203.5
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "74614 542504 37413 NaN 5568 \n", "220843 556231 85123A ? 4000 \n", "263885 560040 23343 came coded as 20713 3100 \n", "115807 546139 84988 ? 3000 \n", "74615 542505 79063D NaN 2560 \n", "447035 574941 22197 POPCORN HOLDER 1820 \n", "160541 550460 47556B did a credit and did not tick ret 1300 \n", "203751 554550 47566B incorrectly credited C550456 see 47 1300 \n", "82795 543258 84611B NaN 1287 \n", "467796 576365 22197 POPCORN HOLDER 1130 \n", "\n", " invoice_date unit_price customer_id total_price \n", "74614 01/26/2019 12:03 0.00 NaN 0.0 \n", "220843 06/07/2019 15:04 0.00 NaN 0.0 \n", "263885 07/12/2019 14:28 0.00 NaN 0.0 \n", "115807 03/07/2019 16:35 0.00 NaN 0.0 \n", "74615 01/26/2019 12:04 0.00 NaN 0.0 \n", "447035 11/05/2019 17:42 1.95 NaN 3549.0 \n", "160541 04/16/2019 13:18 0.00 NaN 0.0 \n", "203751 05/23/2019 09:57 0.00 NaN 0.0 \n", "82795 02/02/2019 16:06 0.00 NaN 0.0 \n", "467796 11/12/2019 17:55 1.95 NaN 2203.5 " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Let's take a look at the extremes of the quantity feature with customer_id as null\n", "df[df['customer_id'].isnull()].sort_values(by = 'quantity', ascending = False).head(10)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
37542956946623270incorrect stock entry.-288010/02/2019 11:420.0NaN-0.0
11358054599084598check-300003/06/2019 13:070.0NaN-0.0
26388456003920713wrongly marked. 23343 in box-310007/12/2019 14:270.0NaN-0.0
32345856530416259NaN-316708/31/2019 12:180.0NaN-0.0
34160156676816045NaN-366709/12/2019 17:530.0NaN-0.0
43138157359679323WUnsaleable, destroyed.-483010/29/2019 15:170.0NaN-0.0
11581854615272140Fthrow away-536803/07/2019 17:250.0NaN-0.0
22552855668723003Printing smudges/thrown away-905806/12/2019 10:360.0NaN-0.0
22552955669023005printing smudges/thrown away-960006/12/2019 10:370.0NaN-0.0
22553055669123005printing smudges/thrown away-960006/12/2019 10:370.0NaN-0.0
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "375429 569466 23270 incorrect stock entry. -2880 \n", "113580 545990 84598 check -3000 \n", "263884 560039 20713 wrongly marked. 23343 in box -3100 \n", "323458 565304 16259 NaN -3167 \n", "341601 566768 16045 NaN -3667 \n", "431381 573596 79323W Unsaleable, destroyed. -4830 \n", "115818 546152 72140F throw away -5368 \n", "225528 556687 23003 Printing smudges/thrown away -9058 \n", "225529 556690 23005 printing smudges/thrown away -9600 \n", "225530 556691 23005 printing smudges/thrown away -9600 \n", "\n", " invoice_date unit_price customer_id total_price \n", "375429 10/02/2019 11:42 0.0 NaN -0.0 \n", "113580 03/06/2019 13:07 0.0 NaN -0.0 \n", "263884 07/12/2019 14:27 0.0 NaN -0.0 \n", "323458 08/31/2019 12:18 0.0 NaN -0.0 \n", "341601 09/12/2019 17:53 0.0 NaN -0.0 \n", "431381 10/29/2019 15:17 0.0 NaN -0.0 \n", "115818 03/07/2019 17:25 0.0 NaN -0.0 \n", "225528 06/12/2019 10:36 0.0 NaN -0.0 \n", "225529 06/12/2019 10:37 0.0 NaN -0.0 \n", "225530 06/12/2019 10:37 0.0 NaN -0.0 " ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['customer_id'].isnull()].sort_values(by = 'quantity', ascending = False).tail(10)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
8767054371321556CERAMIC STRAWBERRY MONEY BOX202/09/2019 11:464.13NaN8.26
50197857883323162REGENCY TEA STRAINER111/23/2019 15:237.46NaN7.46
14301054866321930JUMBO STORAGE BAG SKULLS203/30/2019 14:444.96NaN9.92
1592453764222357KINGS CHOICE BISCUIT TIN112/05/2018 15:338.47NaN8.47
29596256284390114SUMMER DAISIES BAG CHARM108/07/2019 17:372.46NaN2.46
35533556792121089damaged-709/20/2019 17:240.00NaN-0.00
13822254819185049DBRIGHT BLUES RIBBONS203/27/2019 15:202.46NaN4.92
15775955021182599FANNY'S REST STOPMETAL SIGN104/13/2019 10:414.13NaN4.13
481153C577343BANK CHARGESBank Charges-111/16/2019 15:1327.21NaN-27.21
8004154301320724RED RETROSPOT CHARLOTTE BAG101/31/2019 13:351.63NaN1.63
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "87670 543713 21556 CERAMIC STRAWBERRY MONEY BOX 2 \n", "501978 578833 23162 REGENCY TEA STRAINER 1 \n", "143010 548663 21930 JUMBO STORAGE BAG SKULLS 2 \n", "15924 537642 22357 KINGS CHOICE BISCUIT TIN 1 \n", "295962 562843 90114 SUMMER DAISIES BAG CHARM 1 \n", "355335 567921 21089 damaged -7 \n", "138222 548191 85049D BRIGHT BLUES RIBBONS 2 \n", "157759 550211 82599 FANNY'S REST STOPMETAL SIGN 1 \n", "481153 C577343 BANK CHARGES Bank Charges -1 \n", "80041 543013 20724 RED RETROSPOT CHARLOTTE BAG 1 \n", "\n", " invoice_date unit_price customer_id total_price \n", "87670 02/09/2019 11:46 4.13 NaN 8.26 \n", "501978 11/23/2019 15:23 7.46 NaN 7.46 \n", "143010 03/30/2019 14:44 4.96 NaN 9.92 \n", "15924 12/05/2018 15:33 8.47 NaN 8.47 \n", "295962 08/07/2019 17:37 2.46 NaN 2.46 \n", "355335 09/20/2019 17:24 0.00 NaN -0.00 \n", "138222 03/27/2019 15:20 2.46 NaN 4.92 \n", "157759 04/13/2019 10:41 4.13 NaN 4.13 \n", "481153 11/16/2019 15:13 27.21 NaN -27.21 \n", "80041 01/31/2019 13:35 1.63 NaN 1.63 " ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['customer_id'].isnull()].sample(10)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "invoice_no 2510\n", "stock_code 2510\n", "description 1056\n", "quantity 2510\n", "invoice_date 2510\n", "unit_price 2510\n", "customer_id 40\n", "total_price 2510\n", "dtype: int64" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['unit_price'] == 0].count()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "2510 records showing the unit_price of $0. Let's see how much of sales revenues that these unknown customers make up." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "# select the null customers\n", "df_null_customers = df[df['customer_id'].isnull()].reset_index()" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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indexinvoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
062253641422139NaN5611/29/2018 11:520.00NaN0.00
1144353654421773DECORATIVE ROSE BATHROOM BOTTLE111/29/2018 14:322.51NaN2.51
2144453654421774DECORATIVE CATS BATHROOM BOTTLE211/29/2018 14:322.51NaN5.02
3144553654421786POLKADOT RAIN HAT411/29/2018 14:320.85NaN3.40
4144653654421787RAIN PONCHO RETROSPOT211/29/2018 14:321.66NaN3.32
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" ], "text/plain": [ " index invoice_no stock_code description quantity \\\n", "0 622 536414 22139 NaN 56 \n", "1 1443 536544 21773 DECORATIVE ROSE BATHROOM BOTTLE 1 \n", "2 1444 536544 21774 DECORATIVE CATS BATHROOM BOTTLE 2 \n", "3 1445 536544 21786 POLKADOT RAIN HAT 4 \n", "4 1446 536544 21787 RAIN PONCHO RETROSPOT 2 \n", "\n", " invoice_date unit_price customer_id total_price \n", "0 11/29/2018 11:52 0.00 NaN 0.00 \n", "1 11/29/2018 14:32 2.51 NaN 2.51 \n", "2 11/29/2018 14:32 2.51 NaN 5.02 \n", "3 11/29/2018 14:32 0.85 NaN 3.40 \n", "4 11/29/2018 14:32 1.66 NaN 3.32 " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_null_customers.head()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Transactions from non-ID'ed customers totaled: 1447487.53\n", "out of ALL customers transactions totalling: 9726006.95\n", "which comes out to 14.88% of revenues.\n" ] } ], "source": [ "print(\"Transactions from non-ID'ed customers totaled: {:.2f}\".format(df_null_customers['total_price'].sum()))\n", "print(\"out of ALL customers transactions totalling: {:.2f}\".format(df['total_price'].sum()))\n", "print(\"which comes out to \"\n", " + str(round(df_null_customers['total_price'].sum()\n", " / df['total_price'].sum()\n", " * 100, 2))\n", " + \"% of revenues.\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "\\\\$1.4 million from unaccounted customers is quite significant. They make up 25% of the transactions 15% of revenues.\n", "\n", "We can assume that some were cash transactions, where we don't know who the customers are.\n", "\n", "However, there are transactions involving hundreds, even thousands of units. Some of these large transactions have no associated revenue (e.g. $0 unit price). It appears that large negative quantities sometimes were returned damaged product. Some large \"sales\" may have been gifts or donations.\n", "\n", "**ACTION REQUIRED:** There has to be a better way to reconcile these abnormal transactions so that we can properly track and attribute them to either a profit or loss. In our case, we're talking $1.4 million in sales that cannot be properly accounted.\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Delete Null Customers?\n", "Since we're talking about $1.4 million in transactions, we really cannot delete this information.\n", "\n", "However, if we do any type of analysis regarding the customers, we would have to take this lack of ID into account.\n", "\n", "We will fill the nulls with zeroes." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "# Do not delete null customers\n", "# df = df[df['customer_id'].notna()]" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "df['customer_id'].fillna(0, inplace=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Changing Data Types\n", "* We'll change all the invoice date to datetime\n", "* We'll change customer ID to int\n", "* We will change the text in description to lowercase" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "df['invoice_date'] = pd.to_datetime(df['invoice_date'])" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Timestamp('2018-11-29 08:26:00')" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['invoice_date'].min()" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Timestamp('2019-12-07 12:50:00')" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['invoice_date'].max()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "df['customer_id'] = df['customer_id'].astype(int)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
37861456965320717STRAWBERRY SHOPPER BAG202019-10-03 12:52:001.251245125.00
41408557233622738RIBBON REEL SNOWY VILLAGE102019-10-22 10:29:001.651352316.50
40258457150523197SKETCHBOOK MAGNETIC SHOPPING LIST242019-10-15 15:19:001.451724434.80
14339354869922479DAISY GARDEN MARKER32019-04-01 11:08:001.2503.75
3122753890722835HOT WATER BOTTLE I AM SO POORLY42018-12-13 10:40:004.651537318.60
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "378614 569653 20717 STRAWBERRY SHOPPER BAG 20 \n", "414085 572336 22738 RIBBON REEL SNOWY VILLAGE 10 \n", "402584 571505 23197 SKETCHBOOK MAGNETIC SHOPPING LIST 24 \n", "143393 548699 22479 DAISY GARDEN MARKER 3 \n", "31227 538907 22835 HOT WATER BOTTLE I AM SO POORLY 4 \n", "\n", " invoice_date unit_price customer_id total_price \n", "378614 2019-10-03 12:52:00 1.25 12451 25.00 \n", "414085 2019-10-22 10:29:00 1.65 13523 16.50 \n", "402584 2019-10-15 15:19:00 1.45 17244 34.80 \n", "143393 2019-04-01 11:08:00 1.25 0 3.75 \n", "31227 2018-12-13 10:40:00 4.65 15373 18.60 " ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.sample(5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Outliers - Negative quantities\n", "Let's check why there are negative quantities" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
540422C58148423843PAPER CRAFT , LITTLE BIRDIE-809952019-12-07 09:27:002.0816446-168469.6
61624C54143323166MEDIUM CERAMIC TOP STORAGE JAR-742152019-01-16 10:17:001.0412346-77183.6
22553055669123005printing smudges/thrown away-96002019-06-12 10:37:000.000-0.0
22552955669023005printing smudges/thrown away-96002019-06-12 10:37:000.000-0.0
4287C53675784347ROTATING SILVER ANGELS T-LIGHT HLDR-93602018-11-30 14:23:000.0315838-280.8
22552855668723003Printing smudges/thrown away-90582019-06-12 10:36:000.000-0.0
11581854615272140Fthrow away-53682019-03-07 17:25:000.000-0.0
43138157359679323WUnsaleable, destroyed.-48302019-10-29 15:17:000.000-0.0
34160156676816045NaN-36672019-09-12 17:53:000.000-0.0
32345856530416259NaN-31672019-08-31 12:18:000.000-0.0
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "540422 C581484 23843 PAPER CRAFT , LITTLE BIRDIE -80995 \n", "61624 C541433 23166 MEDIUM CERAMIC TOP STORAGE JAR -74215 \n", "225530 556691 23005 printing smudges/thrown away -9600 \n", "225529 556690 23005 printing smudges/thrown away -9600 \n", "4287 C536757 84347 ROTATING SILVER ANGELS T-LIGHT HLDR -9360 \n", "225528 556687 23003 Printing smudges/thrown away -9058 \n", "115818 546152 72140F throw away -5368 \n", "431381 573596 79323W Unsaleable, destroyed. -4830 \n", "341601 566768 16045 NaN -3667 \n", "323458 565304 16259 NaN -3167 \n", "\n", " invoice_date unit_price customer_id total_price \n", "540422 2019-12-07 09:27:00 2.08 16446 -168469.6 \n", "61624 2019-01-16 10:17:00 1.04 12346 -77183.6 \n", "225530 2019-06-12 10:37:00 0.00 0 -0.0 \n", "225529 2019-06-12 10:37:00 0.00 0 -0.0 \n", "4287 2018-11-30 14:23:00 0.03 15838 -280.8 \n", "225528 2019-06-12 10:36:00 0.00 0 -0.0 \n", "115818 2019-03-07 17:25:00 0.00 0 -0.0 \n", "431381 2019-10-29 15:17:00 0.00 0 -0.0 \n", "341601 2019-09-12 17:53:00 0.00 0 -0.0 \n", "323458 2019-08-31 12:18:00 0.00 0 -0.0 " ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['quantity'] < 0].sort_values(by = 'quantity').head(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "Two items have huge negative quantities. Are the returns? Combined, they make up over $200k in refunds. Let's look at the first entry, stock# 23843 returned by customer# 16446" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
54042158148323843PAPER CRAFT , LITTLE BIRDIE809952019-12-07 09:15:002.0816446168469.6
540422C58148423843PAPER CRAFT , LITTLE BIRDIE-809952019-12-07 09:27:002.0816446-168469.6
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "540421 581483 23843 PAPER CRAFT , LITTLE BIRDIE 80995 \n", "540422 C581484 23843 PAPER CRAFT , LITTLE BIRDIE -80995 \n", "\n", " invoice_date unit_price customer_id total_price \n", "540421 2019-12-07 09:15:00 2.08 16446 168469.6 \n", "540422 2019-12-07 09:27:00 2.08 16446 -168469.6 " ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['stock_code'] == '23843']" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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6161954143123166MEDIUM CERAMIC TOP STORAGE JAR742152019-01-16 10:01:001.041234677183.60
61624C54143323166MEDIUM CERAMIC TOP STORAGE JAR-742152019-01-16 10:17:001.0412346-77183.60
18677055288223166MEDIUM CERAMIC TOP STORAGE JAR962019-05-10 10:10:001.041464699.84
18719655295323166MEDIUM CERAMIC TOP STORAGE JAR42019-05-10 12:11:001.25167455.00
18771855300523166MEDIUM CERAMIC TOP STORAGE JAR52019-05-10 16:29:001.25146516.25
18786855300923166MEDIUM CERAMIC TOP STORAGE JAR32019-05-10 16:52:001.25136013.75
18864455305223166MEDIUM CERAMIC TOP STORAGE JAR482019-05-11 10:14:001.041525149.92
18939855314923166MEDIUM CERAMIC TOP STORAGE JAR122019-05-11 14:16:001.251422615.00
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19811555401323166MEDIUM CERAMIC TOP STORAGE JAR122019-05-18 13:13:001.251330815.00
19883955407023166MEDIUM CERAMIC TOP STORAGE JAR92019-05-20 11:06:001.251355511.25
19942755409823166MEDIUM CERAMIC TOP STORAGE JAR62019-05-20 13:01:001.25147697.50
19986855410423166MEDIUM CERAMIC TOP STORAGE JAR122019-05-20 14:03:001.251270515.00
20103055426123166MEDIUM CERAMIC TOP STORAGE JAR22019-05-21 12:32:001.25160332.50
20109955426823166MEDIUM CERAMIC TOP STORAGE JAR12019-05-21 12:59:001.25153111.25
20157055430723166MEDIUM CERAMIC TOP STORAGE JAR962019-05-21 14:59:001.041298999.84
20285555450423166MEDIUM CERAMIC TOP STORAGE JAR122019-05-22 15:13:001.251771915.00
20320755451223166MEDIUM CERAMIC TOP STORAGE JAR42019-05-22 15:54:002.4609.84
203625C55452723166MEDIUM CERAMIC TOP STORAGE JAR-92019-05-22 17:25:001.0415251-9.36
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "61619 541431 23166 MEDIUM CERAMIC TOP STORAGE JAR 74215 \n", "61624 C541433 23166 MEDIUM CERAMIC TOP STORAGE JAR -74215 \n", "186770 552882 23166 MEDIUM CERAMIC TOP STORAGE JAR 96 \n", "187196 552953 23166 MEDIUM CERAMIC TOP STORAGE JAR 4 \n", "187718 553005 23166 MEDIUM CERAMIC TOP STORAGE JAR 5 \n", "187868 553009 23166 MEDIUM CERAMIC TOP STORAGE JAR 3 \n", "188644 553052 23166 MEDIUM CERAMIC TOP STORAGE JAR 48 \n", "189398 553149 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "189452 553152 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "189591 553160 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "190854 553212 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "191128 553339 23166 MEDIUM CERAMIC TOP STORAGE JAR 48 \n", "191165 553341 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "191581 553377 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "192039 553389 23166 MEDIUM CERAMIC TOP STORAGE JAR 3 \n", "194462 553607 23166 MEDIUM CERAMIC TOP STORAGE JAR 240 \n", "194887 553678 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "195455 553718 23166 MEDIUM CERAMIC TOP STORAGE JAR 1 \n", "195725 553739 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "196707 553860 23166 MEDIUM CERAMIC TOP STORAGE JAR 2 \n", "198115 554013 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "198839 554070 23166 MEDIUM CERAMIC TOP STORAGE JAR 9 \n", "199427 554098 23166 MEDIUM CERAMIC TOP STORAGE JAR 6 \n", "199868 554104 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "201030 554261 23166 MEDIUM CERAMIC TOP STORAGE JAR 2 \n", "201099 554268 23166 MEDIUM CERAMIC TOP STORAGE JAR 1 \n", "201570 554307 23166 MEDIUM CERAMIC TOP STORAGE JAR 96 \n", "202855 554504 23166 MEDIUM CERAMIC TOP STORAGE JAR 12 \n", "203207 554512 23166 MEDIUM CERAMIC TOP STORAGE JAR 4 \n", "203625 C554527 23166 MEDIUM CERAMIC TOP STORAGE JAR -9 \n", "\n", " invoice_date unit_price customer_id total_price \n", "61619 2019-01-16 10:01:00 1.04 12346 77183.60 \n", "61624 2019-01-16 10:17:00 1.04 12346 -77183.60 \n", "186770 2019-05-10 10:10:00 1.04 14646 99.84 \n", "187196 2019-05-10 12:11:00 1.25 16745 5.00 \n", "187718 2019-05-10 16:29:00 1.25 14651 6.25 \n", "187868 2019-05-10 16:52:00 1.25 13601 3.75 \n", "188644 2019-05-11 10:14:00 1.04 15251 49.92 \n", "189398 2019-05-11 14:16:00 1.25 14226 15.00 \n", "189452 2019-05-11 14:55:00 1.25 13089 15.00 \n", "189591 2019-05-11 15:26:00 1.25 14194 15.00 \n", "190854 2019-05-14 09:42:00 1.25 15358 15.00 \n", "191128 2019-05-14 12:19:00 1.04 15125 49.92 \n", "191165 2019-05-14 12:25:00 1.25 16293 15.00 \n", "191581 2019-05-14 14:58:00 1.25 14888 15.00 \n", "192039 2019-05-14 16:37:00 2.46 0 7.38 \n", "194462 2019-05-16 10:47:00 1.04 16684 249.60 \n", "194887 2019-05-16 13:00:00 1.25 14009 15.00 \n", "195455 2019-05-16 16:14:00 2.46 0 2.46 \n", "195725 2019-05-17 09:23:00 1.25 14895 15.00 \n", "196707 2019-05-17 13:57:00 1.25 17841 2.50 \n", "198115 2019-05-18 13:13:00 1.25 13308 15.00 \n", "198839 2019-05-20 11:06:00 1.25 13555 11.25 \n", "199427 2019-05-20 13:01:00 1.25 14769 7.50 \n", "199868 2019-05-20 14:03:00 1.25 12705 15.00 \n", "201030 2019-05-21 12:32:00 1.25 16033 2.50 \n", "201099 2019-05-21 12:59:00 1.25 15311 1.25 \n", "201570 2019-05-21 14:59:00 1.04 12989 99.84 \n", "202855 2019-05-22 15:13:00 1.25 17719 15.00 \n", "203207 2019-05-22 15:54:00 2.46 0 9.84 \n", "203625 2019-05-22 17:25:00 1.04 15251 -9.36 " ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['stock_code'] == '23166'].head(30)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "Okay, so they ARE refunds. With those quanties, most likely they were erroneous entries that were corrected, as the transactions were also withing 15-20 minutes apart.\n", "\n", "We'll delete them as they cancelled out. That way, we can avoid skewing any visualizations we make." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Delete non-significant outliers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Who are the returns?" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 9251 entries, 141 to 541717\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 invoice_no 9251 non-null object \n", " 1 stock_code 9251 non-null object \n", " 2 description 9251 non-null object \n", " 3 quantity 9251 non-null int64 \n", " 4 invoice_date 9251 non-null datetime64[ns]\n", " 5 unit_price 9251 non-null float64 \n", " 6 customer_id 9251 non-null int64 \n", " 7 total_price 9251 non-null float64 \n", "dtypes: datetime64[ns](1), float64(2), int64(2), object(3)\n", "memory usage: 650.5+ KB\n" ] } ], "source": [ "df[df['invoice_no'].str.contains(pat = 'C[0-9]', regex = True)].info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### It looks like we have 9251 returns -- a return has invoice number prefix letter 'C'" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "rows_to_delete = [540421, 540422, 61619, 61624]" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": [ "df.drop(rows_to_delete, axis = 'index', inplace = True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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...........................
53698158123472817NaN272019-12-06 10:33:000.000.0
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2512 rows × 8 columns

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" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "622 536414 22139 NaN 56 \n", "1970 536545 21134 NaN 1 \n", "1971 536546 22145 NaN 1 \n", "1972 536547 37509 NaN 1 \n", "1987 536549 85226A NaN 1 \n", "... ... ... ... ... \n", "536981 581234 72817 NaN 27 \n", "538504 581406 46000M POLYESTER FILLER PAD 45x45cm 240 \n", "538505 581406 46000S POLYESTER FILLER PAD 40x40cm 300 \n", "538554 581408 85175 NaN 20 \n", "538919 581422 23169 smashed -235 \n", "\n", " invoice_date unit_price customer_id total_price \n", "622 2018-11-29 11:52:00 0.0 0 0.0 \n", "1970 2018-11-29 14:32:00 0.0 0 0.0 \n", "1971 2018-11-29 14:33:00 0.0 0 0.0 \n", "1972 2018-11-29 14:33:00 0.0 0 0.0 \n", "1987 2018-11-29 14:34:00 0.0 0 0.0 \n", "... ... ... ... ... \n", "536981 2019-12-06 10:33:00 0.0 0 0.0 \n", "538504 2019-12-06 13:58:00 0.0 0 0.0 \n", "538505 2019-12-06 13:58:00 0.0 0 0.0 \n", "538554 2019-12-06 14:06:00 0.0 0 0.0 \n", "538919 2019-12-06 15:24:00 0.0 0 -0.0 \n", "\n", "[2512 rows x 8 columns]" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['unit_price'] <= 0]" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
222681C556445MManual-12019-06-08 15:31:0038970.0015098-38970.00
524602C580605AMAZONFEEAMAZON FEE-12019-12-03 11:36:0017836.460-17836.46
43702C540117AMAZONFEEAMAZON FEE-12019-01-03 09:55:0016888.020-16888.02
43703C540118AMAZONFEEAMAZON FEE-12019-01-03 09:57:0016453.710-16453.71
15017537632AMAZONFEEAMAZON FEE12018-12-05 15:08:0013541.33013541.33
15016C537630AMAZONFEEAMAZON FEE-12018-12-05 15:04:0013541.330-13541.33
16356C537651AMAZONFEEAMAZON FEE-12018-12-05 15:49:0013541.330-13541.33
16232C537644AMAZONFEEAMAZON FEE-12018-12-05 15:34:0013474.790-13474.79
524601C580604AMAZONFEEAMAZON FEE-12019-12-03 11:35:0011586.500-11586.50
299982A563185BAdjust bad debt12019-08-10 14:50:0011062.06011062.06
446533C574902AMAZONFEEAMAZON FEE-12019-11-05 15:21:008286.220-8286.22
173277C551685POSTPOSTAGE-12019-05-01 12:51:008142.7516029-8142.75
173382551697POSTPOSTAGE12019-05-01 13:46:008142.75160298142.75
342635C566899AMAZONFEEAMAZON FEE-12019-09-13 13:53:007427.970-7427.97
191386C553355AMAZONFEEAMAZON FEE-12019-05-14 13:58:007006.830-7006.83
173391C551699MManual-12019-05-01 14:12:006930.0016029-6930.00
287150C562086AMAZONFEEAMAZON FEE-12019-07-31 12:27:006721.370-6721.37
16357C537652AMAZONFEEAMAZON FEE-12018-12-05 15:51:006706.710-6706.71
312246C564341AMAZONFEEAMAZON FEE-12019-08-22 14:53:006662.510-6662.51
262414C559917AMAZONFEEAMAZON FEE-12019-07-11 15:21:006497.470-6497.47
383495C570025AMAZONFEEAMAZON FEE-12019-10-05 10:29:005942.570-5942.57
429248C573549AMAZONFEEAMAZON FEE-12019-10-29 13:23:005942.570-5942.57
446434C574897AMAZONFEEAMAZON FEE-12019-11-05 15:03:005877.180-5877.18
191385C553354AMAZONFEEAMAZON FEE-12019-05-14 13:54:005876.400-5876.40
239250C558036AMAZONFEEAMAZON FEE-12019-06-22 12:31:005791.180-5791.18
124741C546987AMAZONFEEAMAZON FEE-12019-03-16 12:56:005693.050-5693.05
96844C544587AMAZONFEEAMAZON FEE-12019-02-19 15:07:005575.280-5575.28
342611C566889AMAZONFEEAMAZON FEE-12019-09-13 13:50:005522.140-5522.14
16313C537647AMAZONFEEAMAZON FEE-12018-12-05 15:41:005519.250-5519.25
96845C544589AMAZONFEEAMAZON FEE-12019-02-19 15:11:005258.770-5258.77
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity invoice_date \\\n", "222681 C556445 M Manual -1 2019-06-08 15:31:00 \n", "524602 C580605 AMAZONFEE AMAZON FEE -1 2019-12-03 11:36:00 \n", "43702 C540117 AMAZONFEE AMAZON FEE -1 2019-01-03 09:55:00 \n", "43703 C540118 AMAZONFEE AMAZON FEE -1 2019-01-03 09:57:00 \n", "15017 537632 AMAZONFEE AMAZON FEE 1 2018-12-05 15:08:00 \n", "15016 C537630 AMAZONFEE AMAZON FEE -1 2018-12-05 15:04:00 \n", "16356 C537651 AMAZONFEE AMAZON FEE -1 2018-12-05 15:49:00 \n", "16232 C537644 AMAZONFEE AMAZON FEE -1 2018-12-05 15:34:00 \n", "524601 C580604 AMAZONFEE AMAZON FEE -1 2019-12-03 11:35:00 \n", "299982 A563185 B Adjust bad debt 1 2019-08-10 14:50:00 \n", "446533 C574902 AMAZONFEE AMAZON FEE -1 2019-11-05 15:21:00 \n", "173277 C551685 POST POSTAGE -1 2019-05-01 12:51:00 \n", "173382 551697 POST POSTAGE 1 2019-05-01 13:46:00 \n", "342635 C566899 AMAZONFEE AMAZON FEE -1 2019-09-13 13:53:00 \n", "191386 C553355 AMAZONFEE AMAZON FEE -1 2019-05-14 13:58:00 \n", "173391 C551699 M Manual -1 2019-05-01 14:12:00 \n", "287150 C562086 AMAZONFEE AMAZON FEE -1 2019-07-31 12:27:00 \n", "16357 C537652 AMAZONFEE AMAZON FEE -1 2018-12-05 15:51:00 \n", "312246 C564341 AMAZONFEE AMAZON FEE -1 2019-08-22 14:53:00 \n", "262414 C559917 AMAZONFEE AMAZON FEE -1 2019-07-11 15:21:00 \n", "383495 C570025 AMAZONFEE AMAZON FEE -1 2019-10-05 10:29:00 \n", "429248 C573549 AMAZONFEE AMAZON FEE -1 2019-10-29 13:23:00 \n", "446434 C574897 AMAZONFEE AMAZON FEE -1 2019-11-05 15:03:00 \n", "191385 C553354 AMAZONFEE AMAZON FEE -1 2019-05-14 13:54:00 \n", "239250 C558036 AMAZONFEE AMAZON FEE -1 2019-06-22 12:31:00 \n", "124741 C546987 AMAZONFEE AMAZON FEE -1 2019-03-16 12:56:00 \n", "96844 C544587 AMAZONFEE AMAZON FEE -1 2019-02-19 15:07:00 \n", "342611 C566889 AMAZONFEE AMAZON FEE -1 2019-09-13 13:50:00 \n", "16313 C537647 AMAZONFEE AMAZON FEE -1 2018-12-05 15:41:00 \n", "96845 C544589 AMAZONFEE AMAZON FEE -1 2019-02-19 15:11:00 \n", "\n", " unit_price customer_id total_price \n", "222681 38970.00 15098 -38970.00 \n", "524602 17836.46 0 -17836.46 \n", "43702 16888.02 0 -16888.02 \n", "43703 16453.71 0 -16453.71 \n", "15017 13541.33 0 13541.33 \n", "15016 13541.33 0 -13541.33 \n", "16356 13541.33 0 -13541.33 \n", "16232 13474.79 0 -13474.79 \n", "524601 11586.50 0 -11586.50 \n", "299982 11062.06 0 11062.06 \n", "446533 8286.22 0 -8286.22 \n", "173277 8142.75 16029 -8142.75 \n", "173382 8142.75 16029 8142.75 \n", "342635 7427.97 0 -7427.97 \n", "191386 7006.83 0 -7006.83 \n", "173391 6930.00 16029 -6930.00 \n", "287150 6721.37 0 -6721.37 \n", "16357 6706.71 0 -6706.71 \n", "312246 6662.51 0 -6662.51 \n", "262414 6497.47 0 -6497.47 \n", "383495 5942.57 0 -5942.57 \n", "429248 5942.57 0 -5942.57 \n", "446434 5877.18 0 -5877.18 \n", "191385 5876.40 0 -5876.40 \n", "239250 5791.18 0 -5791.18 \n", "124741 5693.05 0 -5693.05 \n", "96844 5575.28 0 -5575.28 \n", "342611 5522.14 0 -5522.14 \n", "16313 5519.25 0 -5519.25 \n", "96845 5258.77 0 -5258.77 " ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.sort_values(by = 'unit_price', ascending = False).head(30)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### A quantity of 1 with a unit price of \\$38970?\n", "Let's take a closer look at this customer" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
22267055644222502PICNIC BASKET WICKER SMALL602019-06-08 15:22:004.9515098297.0
22268055644422502PICNIC BASKET WICKER 60 PIECES602019-06-08 15:28:00649.501509838970.0
222681C556445MManual-12019-06-08 15:31:0038970.0015098-38970.0
22268255644622502PICNIC BASKET WICKER 60 PIECES12019-06-08 15:33:00649.5015098649.5
222692C55644822502PICNIC BASKET WICKER SMALL-602019-06-08 15:39:004.9515098-297.0
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "222670 556442 22502 PICNIC BASKET WICKER SMALL 60 \n", "222680 556444 22502 PICNIC BASKET WICKER 60 PIECES 60 \n", "222681 C556445 M Manual -1 \n", "222682 556446 22502 PICNIC BASKET WICKER 60 PIECES 1 \n", "222692 C556448 22502 PICNIC BASKET WICKER SMALL -60 \n", "\n", " invoice_date unit_price customer_id total_price \n", "222670 2019-06-08 15:22:00 4.95 15098 297.0 \n", "222680 2019-06-08 15:28:00 649.50 15098 38970.0 \n", "222681 2019-06-08 15:31:00 38970.00 15098 -38970.0 \n", "222682 2019-06-08 15:33:00 649.50 15098 649.5 \n", "222692 2019-06-08 15:39:00 4.95 15098 -297.0 " ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['customer_id'] == 15098]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "Another case of weird shenanigans. We can see that for this customer, a grand total of $649.50 was eventually netted after all the various purchase/refund transactions. Perhaps someone was new and didn't know how to operate the cash register?\n", "\n", "If this was online, then perhaps a customer service representative manually cancelled a mistakenly placed order.\n", "\n", "**ACTION REQUIRED:** What happened here bears investigation. Check with Product Manager, Customer Support, and back-end team to see if this process needs improvement\n", "\n", "Due to the fact that the sales total here was almost $40k, we're going to delete the transactions that cancel each other out in this instance.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Delete non-significant transactions" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "rows_to_delete = [222670,\n", " 222680,\n", " 222681,\n", " 222692]" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": [ "df.drop(rows_to_delete, axis = 'index', inplace = True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Zero priced items\n", "It doesn't make sense to analyze products with no price. Question: were these items given away?" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
62253641422139NaN562018-11-29 11:52:000.000.0
28287556166322501incorrectly put back into stock-1082019-07-26 16:40:000.00-0.0
28288256166522171?1422019-07-26 16:55:000.000.0
28288356166622502NaN302019-07-26 16:59:000.000.0
28290456166844091ANaN-22019-07-26 17:03:000.00-0.0
...........................
3357653926322580ADVENT CALENDAR GINGHAM SACK42018-12-14 14:36:000.0165600.0
27932456128422167OVAL WALL MIRROR DIAMANTE12019-07-24 12:24:000.0168180.0
8678954359984535BFAIRY CAKES NOTEBOOK A6 SIZE162019-02-08 13:08:000.0175600.0
18761355300047566PARTY BUNTING42019-05-10 15:21:000.0176670.0
42040457289321208PASTEL COLOUR HONEYCOMB FAN52019-10-24 14:36:000.0180590.0
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2510 rows × 8 columns

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" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "622 536414 22139 NaN 56 \n", "282875 561663 22501 incorrectly put back into stock -108 \n", "282882 561665 22171 ? 142 \n", "282883 561666 22502 NaN 30 \n", "282904 561668 44091A NaN -2 \n", "... ... ... ... ... \n", "33576 539263 22580 ADVENT CALENDAR GINGHAM SACK 4 \n", "279324 561284 22167 OVAL WALL MIRROR DIAMANTE 1 \n", "86789 543599 84535B FAIRY CAKES NOTEBOOK A6 SIZE 16 \n", "187613 553000 47566 PARTY BUNTING 4 \n", "420404 572893 21208 PASTEL COLOUR HONEYCOMB FAN 5 \n", "\n", " invoice_date unit_price customer_id total_price \n", "622 2018-11-29 11:52:00 0.0 0 0.0 \n", "282875 2019-07-26 16:40:00 0.0 0 -0.0 \n", "282882 2019-07-26 16:55:00 0.0 0 0.0 \n", "282883 2019-07-26 16:59:00 0.0 0 0.0 \n", "282904 2019-07-26 17:03:00 0.0 0 -0.0 \n", "... ... ... ... ... \n", "33576 2018-12-14 14:36:00 0.0 16560 0.0 \n", "279324 2019-07-24 12:24:00 0.0 16818 0.0 \n", "86789 2019-02-08 13:08:00 0.0 17560 0.0 \n", "187613 2019-05-10 15:21:00 0.0 17667 0.0 \n", "420404 2019-10-24 14:36:00 0.0 18059 0.0 \n", "\n", "[2510 rows x 8 columns]" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['unit_price'] == 0].sort_values('customer_id')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "Were these items given for free, perhaps as a promotion? How come several customers received more than one type of item?\n", "\n", "We will delete these, but this certainly brings up questions that should be answered." ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "df = df[df['unit_price'] != 0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data Preprocessing Conclusion\n", "* This is our largest dataset in our practicum. \n", "* We converted the original camelCased variables to lowercase with underscores\n", "* We converted description text to lowercase for consistency, to allow for efficient deletions\n", "* We investigated the large negative quantities and determined no-harm, no-foul for the largest outliers\n", "* We were missing a LOT of CustomerID's -- were these just cash transactions, or was there something more?\n", "* We converted invoice_no from type string to type int\n", "* We converted invoice_date from type string to type datetime\n", "* We converted customer_id from type float to type int\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "# Carry out EDA\n", "* Explore distributions and find out\n", " * What items sell the most?\n", " * Which items are returned the most?\n", " * How are buyers distributed? Do sales come from few buyers who make huge purchases, or a large number of buyers making small purchases?\n", " * Explore seasonality -- which items sell best at what times?\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Group by Item stock code" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 534123 entries, 0 to 541908\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 invoice_no 534123 non-null object \n", " 1 stock_code 534123 non-null object \n", " 2 description 534123 non-null object \n", " 3 quantity 534123 non-null int64 \n", " 4 invoice_date 534123 non-null datetime64[ns]\n", " 5 unit_price 534123 non-null float64 \n", " 6 customer_id 534123 non-null int64 \n", " 7 total_price 534123 non-null float64 \n", "dtypes: datetime64[ns](1), float64(2), int64(2), object(3)\n", "memory usage: 36.7+ MB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": [ "aggregations = {\n", " 'quantity': ('quantity','sum'),\n", " 'num_of_customers': ('customer_id','nunique'),\n", " 'sales_total': ('total_price','sum'),\n", " 'sales_average': ('total_price', 'mean')\n", "}\n", "\n", "grouped_items = df.groupby(['stock_code',\n", " 'description',\n", " 'unit_price']).agg(**aggregations).reset_index()" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionunit_pricequantitynum_of_customerssales_totalsales_average
010002INFLATABLE POLITICAL GLOBE0.8582441700.4014.008000
110002INFLATABLE POLITICAL GLOBE1.639114.672.095714
210002INFLATABLE POLITICAL GLOBE1.6627144.823.201429
310080GROOVY CACTUS INFLATABLE0.3930119117.395.590000
410080GROOVY CACTUS INFLATABLE0.85211.701.700000
510120DOGGY RUBBER0.211922540.321.390345
610123CHEARTS WRAPPING TAPE0.65533.251.083333
710124ASPOTS ON RED BOOKCOVER TAPE0.421656.721.344000
810124GARMY CAMO BOOKCOVER TAPE0.421747.141.785000
910125MINI FUNKY DESIGN TAPES0.4226010109.2010.920000
1010125MINI FUNKY DESIGN TAPES0.7924118.961.580000
1110125MINI FUNKY DESIGN TAPES0.8136129.162.916000
1210125MINI FUNKY DESIGN TAPES0.8596539820.2515.476415
1310125MINI FUNKY DESIGN TAPES1.63619.781.956000
1410125MINI FUNKY DESIGN TAPES1.66416.642.213333
1510133COLOURING PENCILS BROWN TUBE0.42203581854.709.092553
1610133COLOURING PENCILS BROWN TUBE0.7958145.826.545714
1710133COLOURING PENCILS BROWN TUBE0.8138130.782.798182
1810133COLOURING PENCILS BROWN TUBE0.833791314.576.291400
1910133COLOURING PENCILS BROWN TUBE0.8533125281.359.075806
2010133COLOURING PENCILS BROWN TUBE1.63416.522.173333
2110133COLOURING PENCILS BROWN TUBE1.66111.661.660000
2210135COLOURING PENCILS BROWN TUBE0.2546211.505.750000
2310135COLOURING PENCILS BROWN TUBE0.4274021310.8014.127273
2410135COLOURING PENCILS BROWN TUBE1.063002318.00159.000000
2510135COLOURING PENCILS BROWN TUBE1.25902691127.5011.505102
2610135COLOURING PENCILS BROWN TUBE1.281321168.9612.068571
2710135COLOURING PENCILS BROWN TUBE2.46842206.647.653333
2810135COLOURING PENCILS BROWN TUBE2.5124160.244.633846
2911001ASSTD DESIGN RACING CAR PEN0.832811233.2310.140435
3011001ASSTD DESIGN RACING CAR PEN1.272841360.68120.226667
3111001ASSTD DESIGN RACING CAR PEN1.69805441360.4520.305224
3211001ASSTD DESIGN RACING CAR PEN3.29512167.797.990000
3311001ASSTD DESIGN RACING CAR PEN3.369130.245.040000
3415030FAN BLACK FRAME0.291431141.473.190000
3515034PAPER POCKET TRAVELING FAN0.0716574115.9919.331667
3615034PAPER POCKET TRAVELING FAN0.14337767472.785.312135
3715034PAPER POCKET TRAVELING FAN0.831621134.463.361500
3815034PAPER POCKET TRAVELING FAN0.851018.501.214286
3915036ASSORTED COLOURS SILK FAN0.536001318.00318.000000
4015036ASSORTED COLOURS SILK FAN0.65420082730.00341.250000
4115036ASSORTED COLOURS SILK FAN0.728688126255.36390.960000
4215036ASSORTED COLOURS SILK FAN0.751407521055.2517.020161
4315036ASSORTED COLOURS SILK FAN0.8369991605809.1722.516163
4415036ASSORTED COLOURS SILK FAN1.2552165.006.500000
4515036ASSORTED COLOURS SILK FAN1.2858174.243.712000
4615036ASSORTED COLOURS SILK FAN1.63107811757.1411.872568
4715039SANDALWOOD FAN0.536003318.00106.000000
4815039SANDALWOOD FAN0.8596056816.0011.492958
4915039SANDALWOOD FAN1.634701766.1010.944286
\n", "
" ], "text/plain": [ " stock_code description unit_price quantity \\\n", "0 10002 INFLATABLE POLITICAL GLOBE 0.85 824 \n", "1 10002 INFLATABLE POLITICAL GLOBE 1.63 9 \n", "2 10002 INFLATABLE POLITICAL GLOBE 1.66 27 \n", "3 10080 GROOVY CACTUS INFLATABLE 0.39 301 \n", "4 10080 GROOVY CACTUS INFLATABLE 0.85 2 \n", "5 10120 DOGGY RUBBER 0.21 192 \n", "6 10123C HEARTS WRAPPING TAPE 0.65 5 \n", "7 10124A SPOTS ON RED BOOKCOVER TAPE 0.42 16 \n", "8 10124G ARMY CAMO BOOKCOVER TAPE 0.42 17 \n", "9 10125 MINI FUNKY DESIGN TAPES 0.42 260 \n", "10 10125 MINI FUNKY DESIGN TAPES 0.79 24 \n", "11 10125 MINI FUNKY DESIGN TAPES 0.81 36 \n", "12 10125 MINI FUNKY DESIGN TAPES 0.85 965 \n", "13 10125 MINI FUNKY DESIGN TAPES 1.63 6 \n", "14 10125 MINI FUNKY DESIGN TAPES 1.66 4 \n", "15 10133 COLOURING PENCILS BROWN TUBE 0.42 2035 \n", "16 10133 COLOURING PENCILS BROWN TUBE 0.79 58 \n", "17 10133 COLOURING PENCILS BROWN TUBE 0.81 38 \n", "18 10133 COLOURING PENCILS BROWN TUBE 0.83 379 \n", "19 10133 COLOURING PENCILS BROWN TUBE 0.85 331 \n", "20 10133 COLOURING PENCILS BROWN TUBE 1.63 4 \n", "21 10133 COLOURING PENCILS BROWN TUBE 1.66 1 \n", "22 10135 COLOURING PENCILS BROWN TUBE 0.25 46 \n", "23 10135 COLOURING PENCILS BROWN TUBE 0.42 740 \n", "24 10135 COLOURING PENCILS BROWN TUBE 1.06 300 \n", "25 10135 COLOURING PENCILS BROWN TUBE 1.25 902 \n", "26 10135 COLOURING PENCILS BROWN TUBE 1.28 132 \n", "27 10135 COLOURING PENCILS BROWN TUBE 2.46 84 \n", "28 10135 COLOURING PENCILS BROWN TUBE 2.51 24 \n", "29 11001 ASSTD DESIGN RACING CAR PEN 0.83 281 \n", "30 11001 ASSTD DESIGN RACING CAR PEN 1.27 284 \n", "31 11001 ASSTD DESIGN RACING CAR PEN 1.69 805 \n", "32 11001 ASSTD DESIGN RACING CAR PEN 3.29 51 \n", "33 11001 ASSTD DESIGN RACING CAR PEN 3.36 9 \n", "34 15030 FAN BLACK FRAME 0.29 143 \n", "35 15034 PAPER POCKET TRAVELING FAN 0.07 1657 \n", "36 15034 PAPER POCKET TRAVELING FAN 0.14 3377 \n", "37 15034 PAPER POCKET TRAVELING FAN 0.83 162 \n", "38 15034 PAPER POCKET TRAVELING FAN 0.85 10 \n", "39 15036 ASSORTED COLOURS SILK FAN 0.53 600 \n", "40 15036 ASSORTED COLOURS SILK FAN 0.65 4200 \n", "41 15036 ASSORTED COLOURS SILK FAN 0.72 8688 \n", "42 15036 ASSORTED COLOURS SILK FAN 0.75 1407 \n", "43 15036 ASSORTED COLOURS SILK FAN 0.83 6999 \n", "44 15036 ASSORTED COLOURS SILK FAN 1.25 52 \n", "45 15036 ASSORTED COLOURS SILK FAN 1.28 58 \n", "46 15036 ASSORTED COLOURS SILK FAN 1.63 1078 \n", "47 15039 SANDALWOOD FAN 0.53 600 \n", "48 15039 SANDALWOOD FAN 0.85 960 \n", "49 15039 SANDALWOOD FAN 1.63 470 \n", "\n", " num_of_customers sales_total sales_average \n", "0 41 700.40 14.008000 \n", "1 1 14.67 2.095714 \n", "2 1 44.82 3.201429 \n", "3 19 117.39 5.590000 \n", "4 1 1.70 1.700000 \n", "5 25 40.32 1.390345 \n", "6 3 3.25 1.083333 \n", "7 5 6.72 1.344000 \n", "8 4 7.14 1.785000 \n", "9 10 109.20 10.920000 \n", "10 1 18.96 1.580000 \n", "11 1 29.16 2.916000 \n", "12 39 820.25 15.476415 \n", "13 1 9.78 1.956000 \n", "14 1 6.64 2.213333 \n", "15 81 854.70 9.092553 \n", "16 1 45.82 6.545714 \n", "17 1 30.78 2.798182 \n", "18 1 314.57 6.291400 \n", "19 25 281.35 9.075806 \n", "20 1 6.52 2.173333 \n", "21 1 1.66 1.660000 \n", "22 2 11.50 5.750000 \n", "23 21 310.80 14.127273 \n", "24 2 318.00 159.000000 \n", "25 69 1127.50 11.505102 \n", "26 1 168.96 12.068571 \n", "27 2 206.64 7.653333 \n", "28 1 60.24 4.633846 \n", "29 1 233.23 10.140435 \n", "30 1 360.68 120.226667 \n", "31 44 1360.45 20.305224 \n", "32 2 167.79 7.990000 \n", "33 1 30.24 5.040000 \n", "34 11 41.47 3.190000 \n", "35 4 115.99 19.331667 \n", "36 67 472.78 5.312135 \n", "37 1 134.46 3.361500 \n", "38 1 8.50 1.214286 \n", "39 1 318.00 318.000000 \n", "40 8 2730.00 341.250000 \n", "41 12 6255.36 390.960000 \n", "42 52 1055.25 17.020161 \n", "43 160 5809.17 22.516163 \n", "44 1 65.00 6.500000 \n", "45 1 74.24 3.712000 \n", "46 1 1757.14 11.872568 \n", "47 3 318.00 106.000000 \n", "48 56 816.00 11.492958 \n", "49 1 766.10 10.944286 " ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items.head(50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "###### Observation\n", "There are some identically described items, but whose unit_price differs. Perhaps one is a discounted/bulk pricing? However, it seems that pricing is/can be arbitrarily set? Notice that item 10135 has pricing/quantity ratios that don't follow any rhyme or reason:\n", "* Quantity 8688 @ \\\\$0.72 each\n", "* Quantity 4200 @ \\\\$0.65 each\n", "* Quantity 600 @ \\\\$0.53 each" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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unit_pricequantitynum_of_customerssales_totalsales_average
count16281.00000016281.00000016281.00000016281.00000016281.000000
mean39.108888325.33646617.669246597.38388039.559728
std414.4889561009.53230549.2239731911.086232428.464352
min-11062.060000-9360.0000001.000000-22124.120000-17836.460000
25%1.4500006.0000001.00000025.5000004.960000
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75%5.950000192.0000006.000000435.00000025.270909
max17836.46000027636.000000814.00000085738.50000011062.060000
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" ], "text/plain": [ " unit_price quantity num_of_customers sales_total \\\n", "count 16281.000000 16281.000000 16281.000000 16281.000000 \n", "mean 39.108888 325.336466 17.669246 597.383880 \n", "std 414.488956 1009.532305 49.223973 1911.086232 \n", "min -11062.060000 -9360.000000 1.000000 -22124.120000 \n", "25% 1.450000 6.000000 1.000000 25.500000 \n", "50% 2.950000 34.000000 1.000000 115.460000 \n", "75% 5.950000 192.000000 6.000000 435.000000 \n", "max 17836.460000 27636.000000 814.000000 85738.500000 \n", "\n", " sales_average \n", "count 16281.000000 \n", "mean 39.559728 \n", "std 428.464352 \n", "min -17836.460000 \n", "25% 4.960000 \n", "50% 10.170000 \n", "75% 25.270909 \n", "max 11062.060000 " ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items.describe()" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": [ "grouped_items_by_description = grouped_stock = df.groupby(['stock_code','description']).agg(**aggregations).reset_index()" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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quantitynum_of_customerssales_totalsales_average
count4176.0000004176.0000004176.0000004176.000000
mean1268.39152365.3134582329.02465413.507847
std2885.71715688.3643887666.730254129.155911
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" ], "text/plain": [ " quantity num_of_customers sales_total sales_average\n", "count 4176.000000 4176.000000 4176.000000 4176.000000\n", "mean 1268.391523 65.313458 2329.024654 13.507847\n", "std 2885.717156 88.364388 7666.730254 129.155911\n", "min -1194.000000 1.000000 -221520.500000 -6515.308824\n", "25% 45.000000 7.000000 106.192500 6.069004\n", "50% 310.000000 31.000000 601.125000 10.732028\n", "75% 1271.000000 88.000000 2055.182500 17.334659\n", "max 53751.000000 888.000000 206245.480000 3022.500000" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_description.describe()" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionquantitynum_of_customerssales_totalsales_average
010002INFLATABLE POLITICAL GLOBE86041759.8910.702676
110080GROOVY CACTUS INFLATABLE30320119.095.413182
210120DOGGY RUBBER1922540.321.390345
310123CHEARTS WRAPPING TAPE533.251.083333
410124ASPOTS ON RED BOOKCOVER TAPE1656.721.344000
510124GARMY CAMO BOOKCOVER TAPE1747.141.785000
610125MINI FUNKY DESIGN TAPES129550993.9910.688065
710133COLOURING PENCILS BROWN TUBE28461021535.407.793909
810135COLOURING PENCILS BROWN TUBE2228932203.6412.380000
911001ASSTD DESIGN RACING CAR PEN1430462152.3917.936583
1015030FAN BLACK FRAME1431141.473.190000
1115034PAPER POCKET TRAVELING FAN520671731.735.153028
1215036ASSORTED COLOURS SILK FAN2308219518064.1634.539503
1315039SANDALWOOD FAN2064591956.5413.219865
1415044APINK PAPER PARASOL457541436.0713.942427
1515044BBLUE PAPER PARASOL32038943.8815.473443
1615044CPURPLE PAPER PARASOL310441014.9411.277111
1715044DRED PAPER PARASOL642551814.2621.096047
1815056BLEDWARDIAN PARASOL BLACK271414315176.3446.553190
1915056NEDWARDIAN PARASOL NATURAL389318521815.2446.914495
\n", "
" ], "text/plain": [ " stock_code description quantity num_of_customers \\\n", "0 10002 INFLATABLE POLITICAL GLOBE 860 41 \n", "1 10080 GROOVY CACTUS INFLATABLE 303 20 \n", "2 10120 DOGGY RUBBER 192 25 \n", "3 10123C HEARTS WRAPPING TAPE 5 3 \n", "4 10124A SPOTS ON RED BOOKCOVER TAPE 16 5 \n", "5 10124G ARMY CAMO BOOKCOVER TAPE 17 4 \n", "6 10125 MINI FUNKY DESIGN TAPES 1295 50 \n", "7 10133 COLOURING PENCILS BROWN TUBE 2846 102 \n", "8 10135 COLOURING PENCILS BROWN TUBE 2228 93 \n", "9 11001 ASSTD DESIGN RACING CAR PEN 1430 46 \n", "10 15030 FAN BLACK FRAME 143 11 \n", "11 15034 PAPER POCKET TRAVELING FAN 5206 71 \n", "12 15036 ASSORTED COLOURS SILK FAN 23082 195 \n", "13 15039 SANDALWOOD FAN 2064 59 \n", "14 15044A PINK PAPER PARASOL 457 54 \n", "15 15044B BLUE PAPER PARASOL 320 38 \n", "16 15044C PURPLE PAPER PARASOL 310 44 \n", "17 15044D RED PAPER PARASOL 642 55 \n", "18 15056BL EDWARDIAN PARASOL BLACK 2714 143 \n", "19 15056N EDWARDIAN PARASOL NATURAL 3893 185 \n", "\n", " sales_total sales_average \n", "0 759.89 10.702676 \n", "1 119.09 5.413182 \n", "2 40.32 1.390345 \n", "3 3.25 1.083333 \n", "4 6.72 1.344000 \n", "5 7.14 1.785000 \n", "6 993.99 10.688065 \n", "7 1535.40 7.793909 \n", "8 2203.64 12.380000 \n", "9 2152.39 17.936583 \n", "10 41.47 3.190000 \n", "11 731.73 5.153028 \n", "12 18064.16 34.539503 \n", "13 1956.54 13.219865 \n", "14 1436.07 13.942427 \n", "15 943.88 15.473443 \n", "16 1014.94 11.277111 \n", "17 1814.26 21.096047 \n", "18 15176.34 46.553190 \n", "19 21815.24 46.914495 " ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_description.head(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "If we omit unit pricing, we can see that there is a total of 4176 different items carried.\n", "\n", "---" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [], "source": [ "aggregations = {\n", " 'quantity': ('quantity','sum'),\n", " 'num_of_customers': ('customer_id','nunique'),\n", " 'sales_total': ('total_price','sum'),\n", " 'sales_average': ('total_price', 'mean')\n", "}" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'quantity': ('quantity', 'sum'),\n", " 'num_of_customers': ('customer_id', 'nunique'),\n", " 'sales_total': ('total_price', 'sum'),\n", " 'sales_average': ('total_price', 'mean')}" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "aggregations" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": [ "grouped_items_by_total_sales = df.groupby(['stock_code', 'description']).agg(\n", " **aggregations).sort_values(\n", " by = 'sales_total', \n", " ascending = False).reset_index()" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": [ "grouped_items_by_quantity_sold = df.groupby(['stock_code', 'description']).agg(\n", " **aggregations).sort_values(\n", " by = 'quantity', \n", " ascending = False).reset_index()" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": [ "grouped_items_by_unit_price = df.groupby(['stock_code', 'description', 'unit_price']).agg(\n", " **aggregations).sort_values(\n", " by = 'unit_price', \n", " ascending = False).reset_index()" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionquantitynum_of_customerssales_totalsales_average
0DOTDOTCOM POSTAGE7052206245.48291.719208
122423REGENCY CAKESTAND 3 TIER12996888164459.4975.198669
247566PARTY BUNTING1800670998243.8857.151763
385123AWHITE HANGING HEART T-LIGHT HOLDER3500285997659.9442.720884
485099BJUMBO BAG RED RETROSPOT4725663792175.7942.812722
523084RABBIT NIGHT LIGHT3063145166661.6364.594603
6POSTPOSTAGE300338066230.6452.899872
722086PAPER CHAIN KIT 50'S CHRISTMAS1887661663715.2453.362848
884879ASSORTED COLOUR BIRD ORNAMENT3628268058792.4239.511035
979321CHILLI LIGHTS1022220653746.6679.861308
1023298SPOTTY BUNTING821057242030.6736.046887
1122386JUMBO BAG PINK POLKADOT2099237341584.4333.401149
1221137BLACK RECORD COVER FRAME1163614140578.21106.504488
1322720SET OF 3 CAKE TINS PANTRY DESIGN732964137378.7925.514532
1423284DOORMAT KEEP CALM AND COME IN526237936532.3949.434899
1522960JAM MAKING SET WITH JARS844857536069.3429.565033
1682484WOOD BLACK BOARD ANT WHITE FINISH598828635795.9751.430991
1720725LUNCH BAG RED RETROSPOT1865853334717.6621.364714
1822197POPCORN HOLDER3632229733959.2639.441649
1922114HOT WATER BOTTLE TEA AND SYMPATHY565832632663.3450.174101
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" ], "text/plain": [ " stock_code description quantity num_of_customers \\\n", "0 DOT DOTCOM POSTAGE 705 2 \n", "1 22423 REGENCY CAKESTAND 3 TIER 12996 888 \n", "2 47566 PARTY BUNTING 18006 709 \n", "3 85123A WHITE HANGING HEART T-LIGHT HOLDER 35002 859 \n", "4 85099B JUMBO BAG RED RETROSPOT 47256 637 \n", "5 23084 RABBIT NIGHT LIGHT 30631 451 \n", "6 POST POSTAGE 3003 380 \n", "7 22086 PAPER CHAIN KIT 50'S CHRISTMAS 18876 616 \n", "8 84879 ASSORTED COLOUR BIRD ORNAMENT 36282 680 \n", "9 79321 CHILLI LIGHTS 10222 206 \n", "10 23298 SPOTTY BUNTING 8210 572 \n", "11 22386 JUMBO BAG PINK POLKADOT 20992 373 \n", "12 21137 BLACK RECORD COVER FRAME 11636 141 \n", "13 22720 SET OF 3 CAKE TINS PANTRY DESIGN 7329 641 \n", "14 23284 DOORMAT KEEP CALM AND COME IN 5262 379 \n", "15 22960 JAM MAKING SET WITH JARS 8448 575 \n", "16 82484 WOOD BLACK BOARD ANT WHITE FINISH 5988 286 \n", "17 20725 LUNCH BAG RED RETROSPOT 18658 533 \n", "18 22197 POPCORN HOLDER 36322 297 \n", "19 22114 HOT WATER BOTTLE TEA AND SYMPATHY 5658 326 \n", "\n", " sales_total sales_average \n", "0 206245.48 291.719208 \n", "1 164459.49 75.198669 \n", "2 98243.88 57.151763 \n", "3 97659.94 42.720884 \n", "4 92175.79 42.812722 \n", "5 66661.63 64.594603 \n", "6 66230.64 52.899872 \n", "7 63715.24 53.362848 \n", "8 58792.42 39.511035 \n", "9 53746.66 79.861308 \n", "10 42030.67 36.046887 \n", "11 41584.43 33.401149 \n", "12 40578.21 106.504488 \n", "13 37378.79 25.514532 \n", "14 36532.39 49.434899 \n", "15 36069.34 29.565033 \n", "16 35795.97 51.430991 \n", "17 34717.66 21.364714 \n", "18 33959.26 39.441649 \n", "19 32663.34 50.174101 " ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_total_sales.head(20)" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionquantitynum_of_customerssales_totalsales_average
084077WORLD WAR 2 GLIDERS ASSTD DESIGNS5375130813560.0925.064861
185099BJUMBO BAG RED RETROSPOT4725663792175.7942.812722
222197POPCORN HOLDER3632229733959.2639.441649
384879ASSORTED COLOUR BIRD ORNAMENT3628268058792.4239.511035
421212PACK OF 72 RETROSPOT CAKE CASES3601663721047.0715.396540
585123AWHITE HANGING HEART T-LIGHT HOLDER3500285997659.9442.720884
623084RABBIT NIGHT LIGHT3063145166661.6364.594603
722492MINI PAINT SET VINTAGE2643721416810.4243.103641
822616PACK OF 12 LONDON TISSUES260951967967.8215.176800
921977PACK OF 60 PINK PAISLEY CAKE CASES2471941212170.7713.736761
1022178VICTORIAN GLASS HANGING T-LIGHT2382540432508.4230.495704
1115036ASSORTED COLOURS SILK FAN2308219518064.1634.539503
1217003BROCADE RING PURSE230171375853.1523.988320
1321915RED HARMONICA IN BOX2183635126210.3338.945513
1422386JUMBO BAG PINK POLKADOT2099237341584.4333.401149
1522197SMALL POPCORN HOLDER2010522917008.6628.020857
1622086PAPER CHAIN KIT 50'S CHRISTMAS1887661663715.2453.362848
1720725LUNCH BAG RED RETROSPOT1865853334717.6621.364714
188499160 TEATIME FAIRY CAKE CASES180154169074.2710.650552
1947566PARTY BUNTING1800670998243.8857.151763
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" ], "text/plain": [ " stock_code description quantity num_of_customers \\\n", "0 84077 WORLD WAR 2 GLIDERS ASSTD DESIGNS 53751 308 \n", "1 85099B JUMBO BAG RED RETROSPOT 47256 637 \n", "2 22197 POPCORN HOLDER 36322 297 \n", "3 84879 ASSORTED COLOUR BIRD ORNAMENT 36282 680 \n", "4 21212 PACK OF 72 RETROSPOT CAKE CASES 36016 637 \n", "5 85123A WHITE HANGING HEART T-LIGHT HOLDER 35002 859 \n", "6 23084 RABBIT NIGHT LIGHT 30631 451 \n", "7 22492 MINI PAINT SET VINTAGE 26437 214 \n", "8 22616 PACK OF 12 LONDON TISSUES 26095 196 \n", "9 21977 PACK OF 60 PINK PAISLEY CAKE CASES 24719 412 \n", "10 22178 VICTORIAN GLASS HANGING T-LIGHT 23825 404 \n", "11 15036 ASSORTED COLOURS SILK FAN 23082 195 \n", "12 17003 BROCADE RING PURSE 23017 137 \n", "13 21915 RED HARMONICA IN BOX 21836 351 \n", "14 22386 JUMBO BAG PINK POLKADOT 20992 373 \n", "15 22197 SMALL POPCORN HOLDER 20105 229 \n", "16 22086 PAPER CHAIN KIT 50'S CHRISTMAS 18876 616 \n", "17 20725 LUNCH BAG RED RETROSPOT 18658 533 \n", "18 84991 60 TEATIME FAIRY CAKE CASES 18015 416 \n", "19 47566 PARTY BUNTING 18006 709 \n", "\n", " sales_total sales_average \n", "0 13560.09 25.064861 \n", "1 92175.79 42.812722 \n", "2 33959.26 39.441649 \n", "3 58792.42 39.511035 \n", "4 21047.07 15.396540 \n", "5 97659.94 42.720884 \n", "6 66661.63 64.594603 \n", "7 16810.42 43.103641 \n", "8 7967.82 15.176800 \n", "9 12170.77 13.736761 \n", "10 32508.42 30.495704 \n", "11 18064.16 34.539503 \n", "12 5853.15 23.988320 \n", "13 26210.33 38.945513 \n", "14 41584.43 33.401149 \n", "15 17008.66 28.020857 \n", "16 63715.24 53.362848 \n", "17 34717.66 21.364714 \n", "18 9074.27 10.650552 \n", "19 98243.88 57.151763 " ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_quantity_sold.head(20)" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionunit_pricequantitynum_of_customerssales_totalsales_average
0AMAZONFEEAMAZON FEE17836.46-11-17836.46-17836.460000
1AMAZONFEEAMAZON FEE16888.02-11-16888.02-16888.020000
2AMAZONFEEAMAZON FEE16453.71-11-16453.71-16453.710000
3AMAZONFEEAMAZON FEE13541.33-11-13541.33-4513.776667
4AMAZONFEEAMAZON FEE13474.79-11-13474.79-13474.790000
5AMAZONFEEAMAZON FEE11586.50-11-11586.50-11586.500000
6BAdjust bad debt11062.061111062.0611062.060000
7AMAZONFEEAMAZON FEE8286.22-11-8286.22-8286.220000
8POSTPOSTAGE8142.75010.000.000000
9AMAZONFEEAMAZON FEE7427.97-11-7427.97-7427.970000
10AMAZONFEEAMAZON FEE7006.83-11-7006.83-7006.830000
11MManual6930.00-11-6930.00-6930.000000
12AMAZONFEEAMAZON FEE6721.37-11-6721.37-6721.370000
13AMAZONFEEAMAZON FEE6706.71-11-6706.71-6706.710000
14AMAZONFEEAMAZON FEE6662.51-11-6662.51-6662.510000
15AMAZONFEEAMAZON FEE6497.47-11-6497.47-6497.470000
16AMAZONFEEAMAZON FEE5942.57-21-11885.14-5942.570000
17AMAZONFEEAMAZON FEE5877.18-11-5877.18-5877.180000
18AMAZONFEEAMAZON FEE5876.40-11-5876.40-5876.400000
19AMAZONFEEAMAZON FEE5791.18-11-5791.18-5791.180000
20AMAZONFEEAMAZON FEE5693.05-11-5693.05-5693.050000
21AMAZONFEEAMAZON FEE5575.28-11-5575.28-5575.280000
22AMAZONFEEAMAZON FEE5522.14-11-5522.14-5522.140000
23AMAZONFEEAMAZON FEE5519.25-11-5519.25-5519.250000
24AMAZONFEEAMAZON FEE5258.77-11-5258.77-5258.770000
25AMAZONFEEAMAZON FEE5225.03-11-5225.03-5225.030000
26AMAZONFEEAMAZON FEE4575.64-11-4575.64-4575.640000
27AMAZONFEEAMAZON FEE4534.24-11-4534.24-4534.240000
28AMAZONFEEAMAZON FEE4527.65-11-4527.65-4527.650000
29DOTDOTCOM POSTAGE4505.17114505.174505.170000
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" ], "text/plain": [ " stock_code description unit_price quantity num_of_customers \\\n", "0 AMAZONFEE AMAZON FEE 17836.46 -1 1 \n", "1 AMAZONFEE AMAZON FEE 16888.02 -1 1 \n", "2 AMAZONFEE AMAZON FEE 16453.71 -1 1 \n", "3 AMAZONFEE AMAZON FEE 13541.33 -1 1 \n", "4 AMAZONFEE AMAZON FEE 13474.79 -1 1 \n", "5 AMAZONFEE AMAZON FEE 11586.50 -1 1 \n", "6 B Adjust bad debt 11062.06 1 1 \n", "7 AMAZONFEE AMAZON FEE 8286.22 -1 1 \n", "8 POST POSTAGE 8142.75 0 1 \n", "9 AMAZONFEE AMAZON FEE 7427.97 -1 1 \n", "10 AMAZONFEE AMAZON FEE 7006.83 -1 1 \n", "11 M Manual 6930.00 -1 1 \n", "12 AMAZONFEE AMAZON FEE 6721.37 -1 1 \n", "13 AMAZONFEE AMAZON FEE 6706.71 -1 1 \n", "14 AMAZONFEE AMAZON FEE 6662.51 -1 1 \n", "15 AMAZONFEE AMAZON FEE 6497.47 -1 1 \n", "16 AMAZONFEE AMAZON FEE 5942.57 -2 1 \n", "17 AMAZONFEE AMAZON FEE 5877.18 -1 1 \n", "18 AMAZONFEE AMAZON FEE 5876.40 -1 1 \n", "19 AMAZONFEE AMAZON FEE 5791.18 -1 1 \n", "20 AMAZONFEE AMAZON FEE 5693.05 -1 1 \n", "21 AMAZONFEE AMAZON FEE 5575.28 -1 1 \n", "22 AMAZONFEE AMAZON FEE 5522.14 -1 1 \n", "23 AMAZONFEE AMAZON FEE 5519.25 -1 1 \n", "24 AMAZONFEE AMAZON FEE 5258.77 -1 1 \n", "25 AMAZONFEE AMAZON FEE 5225.03 -1 1 \n", "26 AMAZONFEE AMAZON FEE 4575.64 -1 1 \n", "27 AMAZONFEE AMAZON FEE 4534.24 -1 1 \n", "28 AMAZONFEE AMAZON FEE 4527.65 -1 1 \n", "29 DOT DOTCOM POSTAGE 4505.17 1 1 \n", "\n", " sales_total sales_average \n", "0 -17836.46 -17836.460000 \n", "1 -16888.02 -16888.020000 \n", "2 -16453.71 -16453.710000 \n", "3 -13541.33 -4513.776667 \n", "4 -13474.79 -13474.790000 \n", "5 -11586.50 -11586.500000 \n", "6 11062.06 11062.060000 \n", "7 -8286.22 -8286.220000 \n", "8 0.00 0.000000 \n", "9 -7427.97 -7427.970000 \n", "10 -7006.83 -7006.830000 \n", "11 -6930.00 -6930.000000 \n", "12 -6721.37 -6721.370000 \n", "13 -6706.71 -6706.710000 \n", "14 -6662.51 -6662.510000 \n", "15 -6497.47 -6497.470000 \n", "16 -11885.14 -5942.570000 \n", "17 -5877.18 -5877.180000 \n", "18 -5876.40 -5876.400000 \n", "19 -5791.18 -5791.180000 \n", "20 -5693.05 -5693.050000 \n", "21 -5575.28 -5575.280000 \n", "22 -5522.14 -5522.140000 \n", "23 -5519.25 -5519.250000 \n", "24 -5258.77 -5258.770000 \n", "25 -5225.03 -5225.030000 \n", "26 -4575.64 -4575.640000 \n", "27 -4534.24 -4534.240000 \n", "28 -4527.65 -4527.650000 \n", "29 4505.17 4505.170000 " ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_unit_price.head(30)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionunit_pricequantitynum_of_customerssales_totalsales_average
30AMAZONFEEAMAZON FEE4383.62-11-4383.62-4383.620000
16190MManual0.19-5509-104.50-10.450000
11MManual6930.00-11-6930.00-6930.000000
2522MManual9.36-11-9.36-9.360000
266MManual367.38-11-367.38-367.380000
54MManual1715.85-11-1715.85-1715.850000
15AMAZONFEEAMAZON FEE6497.47-11-6497.47-6497.470000
1863MManual12.75-13-12.75-2.550000
337MManual269.70-11-269.70-269.700000
904POSTPOSTAGE75.00-11-75.00-75.000000
2361DDiscount10.06-11-10.06-10.060000
4000SSAMPLES6.15-11-6.15-6.150000
1078POSTPOSTAGE30.53-11-30.53-30.530000
320185068CREAM SWEETHEART SHELF + HOOKS7.95-11-7.95-7.950000
12AMAZONFEEAMAZON FEE6721.37-11-6721.37-6721.370000
537979320FLAMINGO LIGHTS4.95-11-4.95-4.950000
908MManual71.46-11-71.46-71.460000
2181MManual10.95-42-43.80-14.600000
115MManual869.55-11-869.55-869.550000
279BANK CHARGESBank Charges326.68-11-326.68-326.680000
1673MManual14.95-13-14.95-4.983333
202MManual544.40-11-544.40-544.400000
4654MManual5.70-11-5.70-5.700000
26AMAZONFEEAMAZON FEE4575.64-11-4575.64-4575.640000
2368SSAMPLES10.00-11-10.00-10.000000
964SSAMPLES50.99-11-50.99-50.990000
1382MManual17.55-11-17.55-17.550000
4708SSAMPLES5.44-11-5.44-5.440000
845BANK CHARGESBank Charges95.38-11-95.38-95.380000
1297POSTPOSTAGE20.47-11-20.47-20.470000
1578CRUKCRUK Commission15.96-11-15.96-15.960000
876SSAMPLES83.06-11-83.06-83.060000
401MManual233.25-11-233.25-233.250000
686BANK CHARGESBank Charges149.16-11-149.16-149.160000
1AMAZONFEEAMAZON FEE16888.02-11-16888.02-16888.020000
5380POSTPOSTAGE4.90-11-4.90-4.900000
2170POSTPOSTAGE11.00-11-11.00-11.000000
3857SSAMPLES6.70-11-6.70-6.700000
16130DDiscount0.20-481-9.60-9.600000
961CRUKCRUK Commission52.24-11-52.24-52.240000
877BANK CHARGESBank Charges82.89-11-82.89-82.890000
998DDiscount42.50-11-42.50-42.500000
86922827RUSTIC SEVENTEEN DRAWER SIDEBOARD85.00-11-85.00-85.000000
949BANK CHARGESBank Charges56.93-11-56.93-56.930000
16277DDiscount0.01-7201-7.20-7.200000
6527POSTPOSTAGE3.95-12-3.95-1.316667
1639DDiscount15.07-11-15.07-15.070000
225BANK CHARGESBank Charges475.69-11-475.69-475.690000
753SSAMPLES128.56-11-128.56-128.560000
27AMAZONFEEAMAZON FEE4534.24-11-4534.24-4534.240000
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" ], "text/plain": [ " stock_code description unit_price quantity \\\n", "30 AMAZONFEE AMAZON FEE 4383.62 -1 \n", "16190 M Manual 0.19 -550 \n", "11 M Manual 6930.00 -1 \n", "2522 M Manual 9.36 -1 \n", "266 M Manual 367.38 -1 \n", "54 M Manual 1715.85 -1 \n", "15 AMAZONFEE AMAZON FEE 6497.47 -1 \n", "1863 M Manual 12.75 -1 \n", "337 M Manual 269.70 -1 \n", "904 POST POSTAGE 75.00 -1 \n", "2361 D Discount 10.06 -1 \n", "4000 S SAMPLES 6.15 -1 \n", "1078 POST POSTAGE 30.53 -1 \n", "3201 85068 CREAM SWEETHEART SHELF + HOOKS 7.95 -1 \n", "12 AMAZONFEE AMAZON FEE 6721.37 -1 \n", "5379 79320 FLAMINGO LIGHTS 4.95 -1 \n", "908 M Manual 71.46 -1 \n", "2181 M Manual 10.95 -4 \n", "115 M Manual 869.55 -1 \n", "279 BANK CHARGES Bank Charges 326.68 -1 \n", "1673 M Manual 14.95 -1 \n", "202 M Manual 544.40 -1 \n", "4654 M Manual 5.70 -1 \n", "26 AMAZONFEE AMAZON FEE 4575.64 -1 \n", "2368 S SAMPLES 10.00 -1 \n", "964 S SAMPLES 50.99 -1 \n", "1382 M Manual 17.55 -1 \n", "4708 S SAMPLES 5.44 -1 \n", "845 BANK CHARGES Bank Charges 95.38 -1 \n", "1297 POST POSTAGE 20.47 -1 \n", "1578 CRUK CRUK Commission 15.96 -1 \n", "876 S SAMPLES 83.06 -1 \n", "401 M Manual 233.25 -1 \n", "686 BANK CHARGES Bank Charges 149.16 -1 \n", "1 AMAZONFEE AMAZON FEE 16888.02 -1 \n", "5380 POST POSTAGE 4.90 -1 \n", "2170 POST POSTAGE 11.00 -1 \n", "3857 S SAMPLES 6.70 -1 \n", "16130 D Discount 0.20 -48 \n", "961 CRUK CRUK Commission 52.24 -1 \n", "877 BANK CHARGES Bank Charges 82.89 -1 \n", "998 D Discount 42.50 -1 \n", "869 22827 RUSTIC SEVENTEEN DRAWER SIDEBOARD 85.00 -1 \n", "949 BANK CHARGES Bank Charges 56.93 -1 \n", "16277 D Discount 0.01 -720 \n", "6527 POST POSTAGE 3.95 -1 \n", "1639 D Discount 15.07 -1 \n", "225 BANK CHARGES Bank Charges 475.69 -1 \n", "753 S SAMPLES 128.56 -1 \n", "27 AMAZONFEE AMAZON FEE 4534.24 -1 \n", "\n", " num_of_customers sales_total sales_average \n", "30 1 -4383.62 -4383.620000 \n", "16190 9 -104.50 -10.450000 \n", "11 1 -6930.00 -6930.000000 \n", "2522 1 -9.36 -9.360000 \n", "266 1 -367.38 -367.380000 \n", "54 1 -1715.85 -1715.850000 \n", "15 1 -6497.47 -6497.470000 \n", "1863 3 -12.75 -2.550000 \n", "337 1 -269.70 -269.700000 \n", "904 1 -75.00 -75.000000 \n", "2361 1 -10.06 -10.060000 \n", "4000 1 -6.15 -6.150000 \n", "1078 1 -30.53 -30.530000 \n", "3201 1 -7.95 -7.950000 \n", "12 1 -6721.37 -6721.370000 \n", "5379 1 -4.95 -4.950000 \n", "908 1 -71.46 -71.460000 \n", "2181 2 -43.80 -14.600000 \n", "115 1 -869.55 -869.550000 \n", "279 1 -326.68 -326.680000 \n", "1673 3 -14.95 -4.983333 \n", "202 1 -544.40 -544.400000 \n", "4654 1 -5.70 -5.700000 \n", "26 1 -4575.64 -4575.640000 \n", "2368 1 -10.00 -10.000000 \n", "964 1 -50.99 -50.990000 \n", "1382 1 -17.55 -17.550000 \n", "4708 1 -5.44 -5.440000 \n", "845 1 -95.38 -95.380000 \n", "1297 1 -20.47 -20.470000 \n", "1578 1 -15.96 -15.960000 \n", "876 1 -83.06 -83.060000 \n", "401 1 -233.25 -233.250000 \n", "686 1 -149.16 -149.160000 \n", "1 1 -16888.02 -16888.020000 \n", "5380 1 -4.90 -4.900000 \n", "2170 1 -11.00 -11.000000 \n", "3857 1 -6.70 -6.700000 \n", "16130 1 -9.60 -9.600000 \n", "961 1 -52.24 -52.240000 \n", "877 1 -82.89 -82.890000 \n", "998 1 -42.50 -42.500000 \n", "869 1 -85.00 -85.000000 \n", "949 1 -56.93 -56.930000 \n", "16277 1 -7.20 -7.200000 \n", "6527 2 -3.95 -1.316667 \n", "1639 1 -15.07 -15.070000 \n", "225 1 -475.69 -475.690000 \n", "753 1 -128.56 -128.560000 \n", "27 1 -4534.24 -4534.240000 " ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_unit_price[grouped_items_by_unit_price['sales_total'] < 0].sample(50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "\n", "It looks like we are being charged an Amazon fee (maybe we're selling on Amazon?) as well we are charging customers a shipping fee.\n", "\n", "There are a lot of \"manually\" made entries that do not indicate at all what item was returned. There are also a lot of discounts as well.\n", "\n", "And, what is a \"CRUK\" commission, a payout to a third party, perhaps?\n", "\n", "\n", "\n", "\n", "\n", "We can see there's an error with index 0 in the above group -- item 22502 is a Wicker Picknet Basket, with a unit price of \\\\$649.50. However, the description says there are 60 pieces. \n", "\n", "I think it might be safe to assume that this is not a designer picnic basket that costs \\\\$649.50. Therefore, someone entered the total sales price into the unit price, and used 1 in quantity. The correct entry should be 60 quantity, and a unit price of \\\\$10.82" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Separate out the fees paid and charged\n", "That way, we can more accurately gauge sales in terms of net profits" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": [ "df_amazon_fees = df[df['stock_code'] == 'AMAZONFEE']" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "df_shipping_charges = df[df['stock_code'] == 'DOT']" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "df_postage_charges = df[df['stock_code'] == 'POST']\n", "df_samples = df[df['stock_code'] == 'S']\n", "df_bad_debt = df[df['stock_code'] == 'B']" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [], "source": [ "df_bank_charges = df[df['stock_code'] == 'BANK CHARGES']" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [], "source": [ "df = df[~df['stock_code'].str.contains('AMAZONFEE')]\n", "df = df[~df['stock_code'].str.contains('DOT')]\n", "df = df[~df['stock_code'].str.contains('POST')]\n", "df = df[~df['stock_code'].str.contains('CRUK')]\n", "df = df[~df['stock_code'].str.contains('BANK CHARGES')]" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [], "source": [ "df = df[df['stock_code'] != 'M']\n", "df = df[df['stock_code'] != 'D']\n", "df = df[df['stock_code'] != 'B']\n", "df = df[df['stock_code'] != 'S']" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_price
22268255644622502PICNIC BASKET WICKER 60 PIECES12019-06-08 15:33:00649.5015098649.50
17064555133922502PICNIC BASKET WICKER SMALL12019-04-25 17:18:0010.79010.79
22431355651522502PICNIC BASKET WICKER SMALL12019-06-11 10:45:0010.79010.79
23424455750222502PICNIC BASKET WICKER SMALL22019-06-18 15:32:0010.79021.58
23256755732422502PICNIC BASKET WICKER SMALL22019-06-18 09:41:0010.79021.58
...........................
18271055256322502PICNIC BASKET WICKER SMALL162019-05-08 11:54:004.951759779.20
18245755254722502PICNIC BASKET WICKER SMALL162019-05-08 10:34:004.951309879.20
15229054958522502PICNIC BASKET WICKER SMALL322019-04-09 09:54:004.9514616158.40
18186255251422502PICNIC BASKET WICKER SMALL192019-05-07 16:30:004.95094.05
35947656818822502PICNIC BASKET WICKER SMALL12019-09-23 14:33:002.00160492.00
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472 rows × 8 columns

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" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "222682 556446 22502 PICNIC BASKET WICKER 60 PIECES 1 \n", "170645 551339 22502 PICNIC BASKET WICKER SMALL 1 \n", "224313 556515 22502 PICNIC BASKET WICKER SMALL 1 \n", "234244 557502 22502 PICNIC BASKET WICKER SMALL 2 \n", "232567 557324 22502 PICNIC BASKET WICKER SMALL 2 \n", "... ... ... ... ... \n", "182710 552563 22502 PICNIC BASKET WICKER SMALL 16 \n", "182457 552547 22502 PICNIC BASKET WICKER SMALL 16 \n", "152290 549585 22502 PICNIC BASKET WICKER SMALL 32 \n", "181862 552514 22502 PICNIC BASKET WICKER SMALL 19 \n", "359476 568188 22502 PICNIC BASKET WICKER SMALL 1 \n", "\n", " invoice_date unit_price customer_id total_price \n", "222682 2019-06-08 15:33:00 649.50 15098 649.50 \n", "170645 2019-04-25 17:18:00 10.79 0 10.79 \n", "224313 2019-06-11 10:45:00 10.79 0 10.79 \n", "234244 2019-06-18 15:32:00 10.79 0 21.58 \n", "232567 2019-06-18 09:41:00 10.79 0 21.58 \n", "... ... ... ... ... \n", "182710 2019-05-08 11:54:00 4.95 17597 79.20 \n", "182457 2019-05-08 10:34:00 4.95 13098 79.20 \n", "152290 2019-04-09 09:54:00 4.95 14616 158.40 \n", "181862 2019-05-07 16:30:00 4.95 0 94.05 \n", "359476 2019-09-23 14:33:00 2.00 16049 2.00 \n", "\n", "[472 rows x 8 columns]" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['stock_code'] == '22502'].sort_values(by = 'unit_price', ascending = False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Correct entry# 222682" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": [ "df.at[222682, 'description'] = 'picnic basket wicker small'" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [], "source": [ "df.at[222682, 'quantity'] = 60" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "df.at[222682, 'unit_price'] = 10.83" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Recalculate groups" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'quantity': ('quantity', 'sum'),\n", " 'num_of_customers': ('customer_id', 'nunique'),\n", " 'sales_total': ('total_price', 'sum'),\n", " 'sales_average': ('total_price', 'mean')}" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "aggregations" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": [ "grouped_items = df.groupby(['stock_code',\n", " 'description',\n", " 'unit_price']).agg(**aggregations).reset_index()" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": [ "grouped_items_by_total_sales = df.groupby(['stock_code', 'description']).agg(\n", " **aggregations).sort_values(\n", " by = 'sales_total', \n", " ascending = False).reset_index()" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [], "source": [ "grouped_items_by_quantity_sold = df.groupby(['stock_code', 'description']).agg(\n", " **aggregations).sort_values(\n", " by = 'quantity', \n", " ascending = False).reset_index()" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [], "source": [ "grouped_items_by_unit_price = df.groupby(['stock_code', 'description', 'unit_price']).agg(\n", " **aggregations).sort_values(\n", " by = 'unit_price', \n", " ascending = False).reset_index()" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionquantitynum_of_customerssales_totalsales_average
022423REGENCY CAKESTAND 3 TIER12996888164459.4975.198669
147566PARTY BUNTING1800670998243.8857.151763
285123AWHITE HANGING HEART T-LIGHT HOLDER3500285997659.9442.720884
385099BJUMBO BAG RED RETROSPOT4725663792175.7942.812722
423084RABBIT NIGHT LIGHT3063145166661.6364.594603
522086PAPER CHAIN KIT 50'S CHRISTMAS1887661663715.2453.362848
684879ASSORTED COLOUR BIRD ORNAMENT3628268058792.4239.511035
779321CHILLI LIGHTS1022220653746.6679.861308
823298SPOTTY BUNTING821057242030.6736.046887
922386JUMBO BAG PINK POLKADOT2099237341584.4333.401149
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" ], "text/plain": [ " stock_code description quantity num_of_customers \\\n", "0 22423 REGENCY CAKESTAND 3 TIER 12996 888 \n", "1 47566 PARTY BUNTING 18006 709 \n", "2 85123A WHITE HANGING HEART T-LIGHT HOLDER 35002 859 \n", "3 85099B JUMBO BAG RED RETROSPOT 47256 637 \n", "4 23084 RABBIT NIGHT LIGHT 30631 451 \n", "5 22086 PAPER CHAIN KIT 50'S CHRISTMAS 18876 616 \n", "6 84879 ASSORTED COLOUR BIRD ORNAMENT 36282 680 \n", "7 79321 CHILLI LIGHTS 10222 206 \n", "8 23298 SPOTTY BUNTING 8210 572 \n", "9 22386 JUMBO BAG PINK POLKADOT 20992 373 \n", "\n", " sales_total sales_average \n", "0 164459.49 75.198669 \n", "1 98243.88 57.151763 \n", "2 97659.94 42.720884 \n", "3 92175.79 42.812722 \n", "4 66661.63 64.594603 \n", "5 63715.24 53.362848 \n", "6 58792.42 39.511035 \n", "7 53746.66 79.861308 \n", "8 42030.67 36.046887 \n", "9 41584.43 33.401149 " ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_total_sales.head(10)" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionquantitynum_of_customerssales_totalsales_average
084077WORLD WAR 2 GLIDERS ASSTD DESIGNS5375130813560.0925.064861
185099BJUMBO BAG RED RETROSPOT4725663792175.7942.812722
222197POPCORN HOLDER3632229733959.2639.441649
384879ASSORTED COLOUR BIRD ORNAMENT3628268058792.4239.511035
421212PACK OF 72 RETROSPOT CAKE CASES3601663721047.0715.396540
585123AWHITE HANGING HEART T-LIGHT HOLDER3500285997659.9442.720884
623084RABBIT NIGHT LIGHT3063145166661.6364.594603
722492MINI PAINT SET VINTAGE2643721416810.4243.103641
822616PACK OF 12 LONDON TISSUES260951967967.8215.176800
921977PACK OF 60 PINK PAISLEY CAKE CASES2471941212170.7713.736761
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" ], "text/plain": [ " stock_code description quantity num_of_customers \\\n", "0 84077 WORLD WAR 2 GLIDERS ASSTD DESIGNS 53751 308 \n", "1 85099B JUMBO BAG RED RETROSPOT 47256 637 \n", "2 22197 POPCORN HOLDER 36322 297 \n", "3 84879 ASSORTED COLOUR BIRD ORNAMENT 36282 680 \n", "4 21212 PACK OF 72 RETROSPOT CAKE CASES 36016 637 \n", "5 85123A WHITE HANGING HEART T-LIGHT HOLDER 35002 859 \n", "6 23084 RABBIT NIGHT LIGHT 30631 451 \n", "7 22492 MINI PAINT SET VINTAGE 26437 214 \n", "8 22616 PACK OF 12 LONDON TISSUES 26095 196 \n", "9 21977 PACK OF 60 PINK PAISLEY CAKE CASES 24719 412 \n", "\n", " sales_total sales_average \n", "0 13560.09 25.064861 \n", "1 92175.79 42.812722 \n", "2 33959.26 39.441649 \n", "3 58792.42 39.511035 \n", "4 21047.07 15.396540 \n", "5 97659.94 42.720884 \n", "6 66661.63 64.594603 \n", "7 16810.42 43.103641 \n", "8 7967.82 15.176800 \n", "9 12170.77 13.736761 " ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_quantity_sold.head(10)" ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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stock_codedescriptionunit_pricequantitynum_of_customerssales_totalsales_average
022656VINTAGE BLUE KITCHEN CABINET295.032885.0295.000000
122655VINTAGE RED KITCHEN CABINET295.035885.0126.428571
222655VINTAGE RED KITCHEN CABINET265.5-11-265.5-265.500000
322826LOVE SEAT ANTIQUE WHITE METAL195.0891560.0130.000000
422826LOVE SEAT ANTIQUE WHITE METAL175.021350.0350.000000
522656VINTAGE BLUE KITCHEN CABINET175.0-11-175.0-175.000000
622827RUSTIC SEVENTEEN DRAWER SIDEBOARD165.015172475.0130.263158
722828REGENCY MIRROR WITH SHUTTERS165.044660.0165.000000
8C2CARRIAGE150.011150.0150.000000
922827RUSTIC SEVENTEEN DRAWER SIDEBOARD145.01862610.0290.000000
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" ], "text/plain": [ " stock_code description unit_price quantity \\\n", "0 22656 VINTAGE BLUE KITCHEN CABINET 295.0 3 \n", "1 22655 VINTAGE RED KITCHEN CABINET 295.0 3 \n", "2 22655 VINTAGE RED KITCHEN CABINET 265.5 -1 \n", "3 22826 LOVE SEAT ANTIQUE WHITE METAL 195.0 8 \n", "4 22826 LOVE SEAT ANTIQUE WHITE METAL 175.0 2 \n", "5 22656 VINTAGE BLUE KITCHEN CABINET 175.0 -1 \n", "6 22827 RUSTIC SEVENTEEN DRAWER SIDEBOARD 165.0 15 \n", "7 22828 REGENCY MIRROR WITH SHUTTERS 165.0 4 \n", "8 C2 CARRIAGE 150.0 1 \n", "9 22827 RUSTIC SEVENTEEN DRAWER SIDEBOARD 145.0 18 \n", "\n", " num_of_customers sales_total sales_average \n", "0 2 885.0 295.000000 \n", "1 5 885.0 126.428571 \n", "2 1 -265.5 -265.500000 \n", "3 9 1560.0 130.000000 \n", "4 1 350.0 350.000000 \n", "5 1 -175.0 -175.000000 \n", "6 17 2475.0 130.263158 \n", "7 4 660.0 165.000000 \n", "8 1 150.0 150.000000 \n", "9 6 2610.0 290.000000 " ] }, "execution_count": 82, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_items_by_unit_price.head(10)" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set(style = 'whitegrid')\n", "f, ax = plt.subplots(figsize = (12, 10))\n", "\n", "\n", "sns.barplot(\n", " x = 'sales_total',\n", " y = 'description',\n", " data = grouped_items_by_total_sales.head(25),\n", " color = 'b',\n", " alpha = 0.6).set_title(\"Top 25 Products sold sorted by Total Sales\", fontsize = 16)\n", "\n", "ax.set_xlabel('Sales')\n", "ax.set_ylabel('Item');" ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [ { "data": { "image/png": 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aFXn+W2+9xd27dwvdIfvhw4fcunVLed1Nq1at+OGHH1Cr1UqdP/74g0uXLinfp6dp5+T7779Xjt27d48zZ848d0xCiH+WbMQkhBBClFFWVlZ4e3uzZs0aDA0Nad26NT///DNr1qxhxIgRWFpaKnUPHjzI3LlzcXV1Zd++fezZs4clS5YU2XZoaChZWVkEBwdz/fp1rl+/rpTVrl0ba2tr/P39CQ4OJiQkBFdXV86ePUtUVBTe3t7P3QTo7+jXrx+ff/45Pj4+TJ48mYoVK7J+/XrS09Px9/cH4L333iMmJgYfHx/8/f25ceMGkZGROu106tSJefPmMXPmTLy8vEhOTubrr7/WqePv74+XlxcTJ05kwIAB3LhxgyVLljB06FAsLCyoVKkSAHv27KFDhw44OTlx+/ZtJk2axJAhQ9BoNKxYsYI6derQqFGjIsdkYGCAv78/EyZM4Pbt2yxcuBAXFxedoMna2hpnZ2cOHTpEWFhYsfdpzpw5jB49mkGDBjF8+HBlZ+ePPvqIJUuWULNmTZ1NhlxcXFi3bh0bNmygfv36bNq0iTt37vDaa68B0KhRIwwNDVm4cCGDBw8mMzOTtWvXkp6e/kJpuk+rVKkSSUlJ/Pzzzzg5ORVbrlKpMDExoWfPnsTExDBu3Ljntm9nZ8ewYcNYtWoVKSkp9OzZEysrK2WDMHNzc2VnbH9/fwYNGoSPjw/Dhw/nwYMHLFmyhNdff52+ffvqtf3mm2/Sp08fwsLCePLkCbVr12bVqlWFvnpICPG/I0GrEEIIUYYFBgZSpUoVYmJiiI6O5vXXX2fatGm89957OvVGjx7NhQsXGDt2LLa2tkREROht4KSl0Wg4cOAAubm5BAQE6JVPmzaNUaNGMXDgQIyNjVm3bh2bN2+mWrVqjB07Fl9f339krFCwIvjVV18xf/585s6dS25uLs2bN+err76icePGQMHziF9++SWhoaFMnjyZmjVr8tFHH+kEO3Z2doSEhLBixQp8fHxo1qwZS5cu1dlNuXnz5qxZs4aIiAjGjRtHtWrV8Pb2VoJjZ2dnOnbsyMcff8yAAQMIDg5m5cqVLF26lIkTJwIFq76LFi3Sed/ts1q3bk2LFi2YNm0aubm5uLu7M336dL16Li4unDhxgh49ehR7n6ysrPj666/ZsGEDCQkJREdHY2Jigr29PV26dGHjxo14eHjw8ccf4+zsjL+/P7dv3yYiIgIjIyP69OmDn5+fslpZr1495s+fT2RkJL6+vlSvXh0XFxf+/e9/M3fuXG7evPnCKd5+fn7Mnj2b0aNHs3v37mLLtSu7Li4uxMTE6OwuXZQPP/yQJk2asGXLFoKCgnj48CHVq1fnX//6F+PHj1fS1x0cHPj8889ZvHgxkyZNUnabDgwM1HtuVSs0NBQrKyuWLVuGRqPh3XffpUaNGkpqvBDif0+V/3eenBdCCCFEqbO3t1cCTfHq8vHxwdLSkkWLFv3tth49ekRMTAwtW7bUSSMvy+bMmcPFixfZuHFjaXdFCFHGyEqrEEIIIUQpWr9+PcnJyRw8eJDNmzeXSJtmZmbFvoqnrNiyZQsXLlxg8+bNLF68uLS7I4QogyRoFUIIIYQoRUeOHOHEiRNMnTr1lVkVLUnnzp0jLi6OoUOHFpnSLoT4v03Sg4UQQgghhBBClFnyyhshhBBCCCGEEGWWpAcLIYqUl5dHdnY2xsbGqFSq0u6OEEIIIYQop/Lz89FoNLz22mt673OWoFUIUaTs7GwuXbpU2t0QQgghhBD/RzRo0ICKFSvqHJOgVQhRJO17Bxs0aPDSL5cXZd+5c+dwcHAo7W6IEibzWn7J3JZfMrflk8zry1Gr1Vy6dKnQ915L0CqEKJI2JTjrUQ5GOZIeXN5UrlqL+w81pd0NUcJkXssvmdvyS+a2fHoV59XM1BgLc9NS7UNhj6RJ0CqEKNaeI5dQ55R2L0RJS7+dTrXq1Uq7G6KEybyWXzK35ZfMbfn0Ks6rp2uTUg9aCyO7BwshhBBCCCGEKLMkaBVCCCGEEEIIUWaVmfTgESNG4OXlxdtvvw3A/Pnz2bRpE8eOHVM2gOnYsSObNm2iTp06xMfHEx0dTW5uLgYGBri5ueHn54eRkRHHjh3D398fW1tb4M/Xdvj4+DB48GBiY2M5fvw44eHhOn14+rz8/HyePHlC586dmTRpEq+99ppO3e7du/Ppp5/SqFEjACZOnMjFixfZvXs3AA8fPqRDhw4cOXKEChUqkJiYyJgxY9i6davOA9murq5UqFBBeeD4wYMHODg4EB4ejrm5uc419+7dy7Jly8jPz6dOnTrMmzcPS0tLvXt55MgRoqKiuH37Nnl5eTRq1IgPP/yQmjVrcuzYMSIjI9mwYYPeefb29ly8eJHU1FTc3Nyws7MD4PHjx7Rs2ZKAgACqVaumV641YMAAvLy8ih1TcnIyYWFh3L17l9zcXJo3b87MmTP1xgtw6dIlPDw8WLp0KT169FCOX7t2jblz55KWlkZ+fj52dnYEBwdTtWpV8vPzWbZsGXv27EGlUmFiYsLEiRNxcXFhxYoVfPfddwAkJyfTsGFDANzc3GjZsuULz39x35Vnv4Na48ePp1u3bhw7dozFixfz6NEjcnNz6dy5MwEBARgaGrJs2TIAJkyYAMD58+eJiIjgv//9LwA2NjbMmDGD+vXrK/MWEhJC//79let4e3szfvx42rZt+9xrCSGEEEIIUdaVmZXWdu3acfLkSeXzTz/9RPPmzZVj//3vfzE3N6dOnTrExsby2WefERkZyY4dO9i4cSMXLlwgODhYOd/BwYG4uDji4uJISEggKiqKkJAQsrKyntsP7Xnx8fFs376dzMxM5syZU2h/T506BUBubi7Jycm89tprpKSkAHDmzBmaN29OhQoVAIiNjcXNzY2YmBi9tlavXq309bvvvuPatWts27ZNp05WVhZz5sxh9erVxMfHY29vrwQ3Tztx4gSBgYFMnTqV3bt3s2fPHtq2bcu4ceOeO+5nWVtb6/SpWrVqTJw4sdBy7T8vL68XGtOUKVOYMmUK8fHxJCQkYGRkxKefflpoP7Zu3VrofQsODqZ3794kJCSwfft2GjduzOzZswHYtWsXSUlJfPvtt8THx7Nw4UKmTZvGnTt3GDNmjNIvQPnfY8aMAV58/l+k7tPfQe2/bt26oVarCQgIYNGiRcTHx/Ptt99y+fJlvvrqK71rXLlyhZEjRzJ06FC+//57vv/+ewYPHoyvry9qtVqp98knn3D9+nW981/mWkIIIYQQQpRFZSZodXZ25vTp0wDcvHkTExMTevTowaFDh4CCYKxDhw4AREZGEhQUpKxiWVhYEBoayvbt20lLSyu0/bS0NMzMzF7qtR3GxsZMmzaNnTt3cv/+fZ2yp4PWX375hUaNGtGhQwcOHjyo19+MjAyOHj1KYGAgu3btem7g/ODBAx48eEDlypV1jms0GmbPnk2NGjWAgtW1woKU5cuXM2bMGJo3b64c8/Lywt3dXSfIeRkqlYoJEybw22+/kZyc/NLnPzum9PR0Hj9+DICBgQHjx4+nZ8+eeudpNBoSEhKYPHkySUlJXL16VSlLT0/n0aNHymcvLy8laL59+za5ubnKeOvVq8fSpUsxMnq5xILnzf/fqfvo0SOysrKU/puYmDBz5kzatGmjV3fNmjX069ePzp07K8fefvttfH19db5H7733HkFBQX/rWkIIIYQQQpRFZSZobdKkCVevXuXJkyccOnSIDh060KFDB72gNSMjg7S0NBwdHXXOt7S0pH79+iQlJQEF70Xy9PSke/futG3blvj4eNauXfvS75qsXr06lSpV4sqVKzrH27VrpwTZhw4domPHjjr9/fnnn5WgNT4+ng4dOlCnTh0cHByIj4/XacvX1xcPDw/at2+Pj48PQ4cO1QviqlSpQrdu3YCCdN3Vq1crqdRPO3PmDK1bt9Y7PmrUqL/1nk0TExPq1q3L5cuXAbh16xaenp46/y5evPhCY5oxYwZjxoyhe/fuzJo1i6SkJJ0gW2v//v3Url2bevXq8fbbb+ustr7//vssWrQIFxcXPvjgA/bv368EYn379iUrKwtnZ2dGjRrF6tWrqVevXqGp1MUpav5fpK72O/j0v8zMTCwtLfHz86Nfv354eHgQEhLCzZs3lVTlpxU1n4MGDcLKykr57OPjQ2ZmJt98841OvZe5lhBCCCGEEGVRmQlaDQ0NadasGWfPnlWCQBsbGx4/fsy9e/c4ffo07dq1U+rn5ubqtaHRaJT3+mhTM7dv3067du2oWLGiXqD7olQqFaamuls/W1lZYWFhwY0bN5T+tmzZknPnzqFWq0lLS1MCg2+//ZbevXsD4O7uzqZNm3TaWr16NQkJCcyePZvMzEzc3NwKfT8RFKxa+vr60rBhQ955550i+wsFqaHaYKlLly7KyvBfpVKplHTnwtKD7e3tX2hM/fr149ChQwQGBmJkZMT06dMJDQ3Vu97WrVt17ltsbKyyeuri4sKBAwcICQnBysqKhQsXKs+AWlpasmnTJjZv3kzHjh05ePAgvXv3VlK3/8q4n53/F6lbWHpwlSpVABgzZgwHDhzAz89Ped56/fr1RbapNXz4cDw9PXF1dWXnzp3KcSMjI8LDwwtNE36ZawkhhBBCCFHWlJmgFf5Muf3111+VlTdnZ2d++OEHqlSpgoWFBVZWVtja2iqrnFoZGRmkpKTQuHFjneMmJiaEhITw448/6vyR/6LS09N58OCB3oY62v7u37+fhw8fUqtWLUxMTLC3t2f79u20aNEClUpFUlISly5dIjQ0FFdXV6Kiovjtt984c+aMXns9evSgU6dOfPjhh4X25datWwwZMgR7e/tCgzyApk2bKsGpiYmJEizZ2Nig0fz1lxur1Wr+85//KJv/vKhnx3TlyhWioqKwsLCgW7duzJ49m40bN+qtEN65c4eDBw+ydu1aXF1dCQoK4v79++zZs4e7d+8SFhaGqampstKakJDA4cOHycjIYN26dSQnJ2Nvb8+IESPYsGEDHTt2VDbJehnPm/+/WvfMmTN89dVXWFlZ0bt3b+bNm0dkZKTePQDd+QRYv349cXFxtGnTRkmx1mrQoIFemvDLXEsIIYQQQoiyqEwFrc7OzsTFxdGgQQPl+cMOHTqwbt06JdUWYPLkyYSFhSkrZ9nZ2QQFBeHu7s7rr7+u127FihWZMGECCxYs0PtD/3nUajULFizgnXfewczMrND+fvHFFzorwNr+duzYESjYgGnAgAHs27ePxMRE9u/fj6enp95qq9akSZM4efIk+/bt0zmem5uLv78/PXv2ZObMmUWuxE6YMIGoqCh++eUX5VhycjIpKSl/ebfYvLw8li1bRrNmzV4oeHvW02OysrLiiy++4MiRI0r5hQsXlF2YteLi4mjXrh0HDhwgMTGRH3/8EX9/fzZt2kTFihVJTEzU2azq999/p2rVqlhaWvLgwQOWLFlCdnY2ULCJVUpKit41ilPc/P/VupaWlkRGRuo8H5yUlFRo/3x9fdm6dSv79+9XjqWkpJCcnIyBgf5/vto0Ye2POi9zLSGEEEIIIcqiMvPKGyhYKbp79y5DhgxRjrVr147JkyfTvn175VivXr0wNDRk0qRJqNVqcnNz6dWrF/7+/kW23b9/fzZs2MC6deuoUaMGCQkJOitvfn5+tGjRQnkOEQoCxXbt2jFt2rRC22zdujVXrlwhMDBQOdahQwfmzZtH+/btUavVbN++nS+++ELnvOHDhzNw4EBmzJih12bVqlXx8fFhwYIFdOzYUQneExMTOX/+PLm5uUq/HRwc9FZcnZyciIiIYMmSJaSnpyurwB988AFOTk4cO3aMEydO0KJFC+UcDw8P5s6dq9OO9plVQHltzuLFiwstf/p+FLYZ0NNjio+PZ/Xq1SxcuJCgoCCMjY2pV6+eTttQkFI9ZcoUnWNeXl5ER0dz5coVVq9eTXh4OJ9++ikVKlTA2tqalStXYmhoyNixY4mIiKBPnz6YmppiYGCAl5eXzg8fRXmZ+S+u7tPlWr169cLX15fw8HA+/PBDsrKyUKlUODo66ux+rfXGG2/w+eefs3jxYhYuXIhGo6FixYoMHjwYDw8Pvaepu94AACAASURBVPraNOF+/foBBZtQvei1hBBCCCGEKItU+fn5+aXdCSFE2fTkyRPOnTtHUmoO6pzS7o0oaem306lWvVppd0OUMJnX8kvmtvySuS2fXsV59XRtQvUqFqVybe3fnQ4ODnr7yZSp9GAhhBBCCCGEEOJpErQKIYQQQgghhCizJGgVQgghhBBCCFFmlamNmIQQZVM35wYYGRuXdjdECbt/7z6VLCuVdjdECZN5Lb9kbssvmdvy6VWcVzPTsvn3ngStQohiWVma6z0QL159Vy9fxO6N2qXdDVHCZF7LL5nb8kvmtnySeS05kh4shBBCCCGEEKLMkqBVCCGEEEIIIUSZJenBQohiZdx7iJGxprS7IUpY5aq1uJ2ZVdrdECVM5rX8krktv2Ru/xlmpsZYmMvjTeWBBK1CiGLtOXIJdU5p90KUtFfxpeeieDKv5ZfMbfklc/vP8HRtIkFrOSHpwUIIIYQQQgghyiwJWoUQQgghhBBClFmSHlzKYmNjOX78OOHh4UyfPp02bdrQr18/pXzZsmUATJgwAW9vb86fP8+RI0cwMTFR6nh6elKpUiU2bNjA9OnTOXr0KJaWluTl5VGhQgU+/vhjGjZsCEB2djaLFi3i0KFDmJmZYWFhwYQJE3B2dtbrm7e3Nzdu3MDc3Jy8vDyqVKlCeHg4tWv/uXV3YmIiY8aMYevWrTg4OOicv2vXLtasWUN2djYajYY2bdowY8YMKlasqFPv2LFj+Pv7Y2trC0BeXh7Z2dn4+PgwePBgvXKt8ePH061bN+zt7ZXxqdVq7OzsCAwMpG7dunpjerpufn4+Dx48oFOnTsyePRtDQ0Odcq0uXbrg5OTEokWLALh69SrVqlXD3NycOnXqEBUVVWy7Go2GyMhIdu3ahampKaampowcORJ3d3el3/PmzePnn39GpVJRqVIlPvjgAxwdHUlNTcXNzQ07OztUKhUajQZra2vmzZtHzZo1AYiPjyc6Oprc3FwMDAxwc3PDz88PIyMjxo0bR2pqKg8fPiQ9PV25j1OnTqVTp05690gIIYQQQoiyRILWV4yFhQWHDh3C1dUVgMuXL3Pr1i0qVfrzxcUTJ05UAt+9e/cSFBTEli1byM/Px9/fn0aNGrFjxw5MTEw4f/48vr6+fPLJJ7Rt21bveiEhIcrx9evXM3/+fD799FOlPDY2Fjc3N2JiYnSC1oSEBCIjI1m+fDl2dnbk5+ezcOFCZs6cydKlS/Wu4+DgwIYNG5TPFy5c4N1338XDw6PQ8mfFxcUp/3vjxo2MGjWKnTt36gT3hdXNysqid+/eHDp0iM6dO+uVP00b4Hl7ezN+/Hi9+/W8dmfNmsWTJ0+IjY3FwsKClJQUfHx8UKvV9O3bl/Xr15OXl0dCQgIqlYqTJ08yduxYfvzxRwCsra112g8PD2fBggUsXryY2NhY1q1bR1RUFLa2tmRlZTF9+nSCg4MJCwsjKioKKPhxIDIy8rn3UQghhBBCiLJG0oNfMd27d2f37t3K5507d9KjR48i6z948IBq1Qoe7D9+/DjXrl1jxowZSjDXuHFjxowZw/Lly4u9dlZWltIWQEZGBkePHiUwMJBdu3aRlfXnrneRkZF8+OGH2NnZAaBSqZgyZQpNmzZ9oXGmpaVhZmZWaNBZnMGDB2NqasrBgweLrZuZmcmjR4+oXLnyS1/nRdtNSUlh9+7dhIaGYmFhAYCNjQ0zZswgMjISgPT0dDQaDRpNwQ69rVq1IiwsjLy8vELbb9u2Lb/99htQcK+DgoKUFVQLCwtCQ0PZvn07aWlpJTouIYQQQggh/tdkpfUV4+LiQnBwMBqNBmNjY/bt28eECRP4448/lDpLly7l888/59GjR1y7do0VK1YAcPbsWRwcHFCpVDpttm7dmk8++aTQ6wUFBWFubs6DBw+4d++ezipdfHw8HTp0oE6dOjg4OBAfH8+QIUO4e/cuV65cwcnJSactY2NjfHx8Cr3OuXPn8PT05NGjR9y7d4+2bduydu1aJWjVlj9t/fr1VKlSpdD26tevz+XLl+natatemaenJzk5Ody5cwc7OzuCgoJo1qyZTvnTXjSNtqh2d+3ahZ2dHebm5jr1nZycSElJ4e7duwwbNgw/Pz+cnZ1p06YNzs7OvPPOO5ia6u94p9Fo2L17N82bNycjI4O0tDQcHR116lhaWlK/fn2SkpJ4/fXXi+27EEIIIYQQZZUErWXIs8EkFDwfaWDw54K4iYkJrVq14qeffqJWrVrY2NhQoUIFnXOeTg8+deoUo0ePJi4uDpVKRW5urt41NBpNodcG3fTg7777jhEjRvDDDz9gYWHBt99+y/jx4wFwd3fnyy+/ZMiQIXrjSU1NZdy4cUDB6uzmzZupVauWznW06b9qtZrAwEAsLCx0ArHi0oOfpVKp9O6LljbNdv369cTGxuoFtkWlBxenqHaLuu85OTlKeZ06ddi+fTtnz57lp59+Ytu2baxfv55t27YBcOvWLSWYVqvVODo6EhAQoKzEvuy8CiGEEEII8aqQ9OBScOLECW7evAkUBKWGhoZAwerY/fv3dereuXMHS0tLnWNubm7s3r2bXbt2KRv5FKVly5bY2tqSlJREs2bNOHfunJKCqnXmzBm9TZQK4+bmRl5eHv/5z39ISkri0qVLhIaG4urqSlRUFL/99htnzpyhcuXK2NjYcOrUKQDq1KlDXFwccXFxGBsbFxpgaZmYmBASEsKPP/7Izp07i+1TUS5evEj9+vWfW2f48OFUr16dBQsW/OXrvEi7jo6OXLlyhXv37unUO336NDY2NlhaWrJ48WJu3bqFo6Mj/v7+xMbGYm1tzeHDh4E/n2mNi4tj165dzJ8/n8qVK2NlZYWtrS2nT5/WaTsjI4OUlBQaN25comMTQgghhBDif02C1lKwdetW9u7dCxQEVzY2NgA4Ozuzc+dOHj58CMDt27fZt28f7dq10znfxcWFY8eOceDAAVxcXJ57rbS0NFJTU2nYsCFOTk7Ur1+fsLAwJXA9d+4cK1asYOzYscX2+9y5c+Tk5FCvXj1iY2MZMGAA+/btIzExkf379+Pp6cmmTZsAmDx5MiEhITppyydOnODu3btKkF6UihUrMmHCBBYsWMDjx4+L7dezvv76a1QqVaEbSz1r+vTpbNmyheTk5Je+zou2W7t2bTw8PJg5cybZ2dlAwQ7E8+bNU1aqb968SVRUFGq1GiiY+4yMDBo0aFDstSZPnkxYWBgpKSlAwQ7RQUFBuLu7S2qwEEIIIYR45Ul6cCnw9fVl2rRpfPnll9SsWZMlS5YA0LlzZ5KTkxkwYAAqlQoDAwMCAwN56623dM43MTGhZcuWAIU+86h9ptXQ0JAnT57wwQcf8MYbbwAFm/ZERETQu3dvDA0NsbS0ZOHChUUGeNpnWg0NDcnJyWHRokWYmJiwfft2vvjiC526w4cPZ+DAgcyYMYPevXtjbm5OUFAQ2dnZZGVlYWdnR2RkpF5qcGH69+/Phg0bWLduHS1btiz0mdZevXrh6+sL/Pkcal5eHjY2Nnz22Wc6adVFeeutt+jbty/z589n3bp1Om1p1a1bt9Adj1+m3dmzZ7Nq1SreffddDA0NMTExYdKkScpK+axZs5g/fz5ubm6YmZlhbGzM1KlTsbOzIzU19bnX6tWrF4aGhkyaNAm1Wk1ubi69evXC39//pfoshBBCCCFEWaTKz8/PL+1OCCHKpidPnnDu3DmSUnNQ55R2b0RJS7+dTrXq1YqvKF4pMq/ll8xt+SVz+8/wdG1C9SoWpXb9kydP0qpVq1K7/qtG+3eng4OD3sKcpAcLIYQQQgghhCizJGgVQgghhBBCCFFmyTOtQohidXNugJGxcWl3Q5Sw+/fuU8myUml3Q5QwmdfyS+a2/JK5/WeYmcrfLuWFBK1CiGJZWZoXuumXeLVdvXwRuzdql3Y3RAmTeS2/ZG7LL5lbIZ5P0oOFEEIIIYQQQpRZErQKIYQQQgghhCizJD1YCFGsjHsPMTLWlHY3RAmrXLUWtzOzSrsbooTJvJZfMrcvzszUGAtzeaxFiPJCglYhRLH2HLkk72kth+S9gOWTzGv5JXP74jxdm0jQKkQ5IunBQgghhBBCCCHKLAlahRBCCCGEEEKUWZIeLP4xqampuLm5YWdnh0qlQqPRYG1tzbx586hZsyYA8fHxREdHk5ubi4GBAW5ubvj5+WFkZMSxY8fw9/fH1tYWlUrF48ePadCgAWFhYVhYWJCfn8/69evZtm0bAAYGBowePZpevXopfVi/fj0xMTEYGhpiaGjIgAED8PLyAiA2Npbw8HBq1aoFQG5uLmq1mmnTpvH2228TGxvL/Pnz2bFjB9WqVVPGNGzYMBITE3XGGhsby/HjxwkPD1eOHTt2jMjISDZs2ADAr7/+yqJFi7h58yZGRkY4OjoSGBiIlZVVke0C2Nvb07BhQwDUajV2dnYEBgZSt25dvXKtLl26MGXKFLy9vblx4wbm5uYAZGVlYWNjw6JFi5QxCSGEEEIIUZZJ0Cr+UdbW1sTFxSmfw8PDWbBgAYsXLyY2NpZ169YRFRWFra0tWVlZTJ8+neDgYMLCwgBwcHBQgj6AiRMnsmrVKgICAoiIiOD8+fN8+eWXVKxYkRs3bjB06FCqVKlC+/btWbZsGT///DMbNmygWrVqZGRkMHbsWO7evcu4ceMAcHV11Qk09+7dS3BwMG+//TYA2dnZzJ49m6ioqL91H37//XfGjh3LggULaN++PXl5eURHRzNs2DC2bt1a7PlP38ONGzcyatQodu7ciYmJiV75s0JCQmjbti0AeXl5TJw4kXXr1hEYGPi3xiSEEEIIIcT/gqQHi/+ptm3b8ttvvwEQGRlJUFAQtra2AFhYWBAaGsr27dtJS0sr9Pw2bdrw22+/kZ2dzeeff86sWbOoWLEiADVr1mTx4sVUr16dR48esWbNGsLCwpQVRSsrK0JCQoiOjubRo0eFtp+WloalpaXyuUePHvz3v/8lISHhb407OjqagQMH0r59e6BgVdjX15cKFSqwa9eul2pr8ODBmJqacvDgwZfux8OHD8nMzNQZoxBCCCGEEGWZrLSK/xmNRsPu3btp3rw5GRkZpKWl4ejoqFPH0tKS+vXrk5SUpBdYPXz4kMTERNq0acPly5cxMjJSUmS1tO39+uuvmJmZUadOHZ3y+vXrY2JiwuXLlwFITEzE09OTrKwsHj9+TIcOHVi+fLlS39jYmHnz5uHv74+zs/Nzx6dt6+n+atOgz549S8+ePfXOad26NefOncPJyem5bT+rfv36XL58ma5duwLoXBdg6tSpdOrUCYCgoCDMzMzIyMjA0tISd3d3hg8f/lLXE0IIIYQQorRI0Cr+Ubdu3VICKrVajaOjIwEBAeTl5QEFz5E+S6PRoFKpADh37pxyfk5ODu3atWPEiBH8/vvvSmpsYVQqVaFta9vRtq9ND87KysLX15c33niDevXq6dRv2rQp//73v5k9ezYzZswo8prPphprn2nV9icnR/+dMRrNX3v3qUqlokKFCsrnF0kPPnXqFBMnTqRbt27PvXdCCCGEEEKUJRK0in/Us8+0Ps3W1pbTp08rK4IAGRkZpKSk0LhxY1JTU/WeadWys7Pj8ePHXLt2jdq1ayvHd+zYQXp6OgMGDECj0XD58mXefPNNpfy3334jLy+PevXqkZycrBy3sLBg/vz5eHh44OzsTIsWLXSuN378ePr168f27dv/0n1wdHTkzJkzysqo1unTp/H29n7p9i5evMjAgQNf6pyWLVvi7e1NQEAA3377LUZG8p+/EEIIIYQo++SZVlFqJk+eTFhYGCkpKUDBpkdBQUG4u7vz+uuvP/fcChUq4OXlxZw5c8jKygIKdvZdvHgxdnZ2mJmZMWbMGGbOnMmdO3cAuHPnDrNmzWL06NGYmZnptWljY8PQoUMJDQ0lPz9fp8zExIR58+axcuXKvzRWPz8/tm7dyuHDhwHIz89n+fLlPH78uNC04ef5+uuvUalUyuZKL2PEiBFkZ2cTExPz0ucKIYQQQghRGmSpRZSaXr16YWhoyKRJk1Cr1eTm5tKrVy/8/f1f6PwpU6YQFRXFgAEDMDIywtDQkICAADp27AiAr68vFStWZPjw4eTn56NSqRg0aJDyypvC+Pn5sWXLlkI3XmratCnvvffeX9qUqW7duqxZs4ZFixYREhJCbm4urVq1YsOGDZiamgJw7do1nRXeVq1aER0dDfz5zGpeXh42NjZ89tlnGBj8+ZvTs8+01q1bl6VLl+r1w8TERPmxoE+fPsomVkIIIYQQQpRVqvxnl5SEEOL/e/LkCefOnSMpNQe1/iO54hWXfjudatXlfb3ljcxr+SVz++I8XZtQvYpFaXfjhZ08eZJWrVqVdjdECZN5fTnavzsdHByURR0tSQ8WQgghhBBCCFFmSdAqhBBCCCGEEKLMkqBVCCGEEEIIIUSZJRsxCSGK1c25AUbGxqXdDVHC7t+7TyXLSqXdDVHCZF7LL5nbF2dmKv+fJUR5IkGrEKJYVpbmeg/Ei1ff1csXsXujdvEVxStF5rX8krkVQvxfJenBQgghhBBCCCHKLAlahRBCCCGEEEKUWZIeLIQoVsa9hxgZa0q7G6KEVa5ai9uZWaXdDVHCZF7LL5nbF2dmaoyFuTzWIkR5IUGrEKJYe45cQp1T2r0QJS39djrVqlcr7W6IEibzWn7J3L44T9cmErQKUY5IerAQQgghhBBCiDJLglYhhBBCCCGEEGVWuUwPvnTpEh4eHixdupQePXoAcO3aNebOnUtaWhr5+fnY2dkRHBxM1apVyc/PZ9myZezZsweVSoWJiQkTJ07ExcUFAI1GQ2RkJLt27cLU1BRTU1NGjhyJu7s7AMuWLWPTpk1Uq1aQsqNWqzEyMmLOnDk8fPiQRYsWAXD16lWqVauGubk5derUISoqCnt7exo2bKjT/y5dujBlyhS8vb25ceMG5ubm5ObmYmFhwcSJE2nfvn2h4962bRsbNmwgJyeHvLw8+vfvz7Bhw5Ty+Ph4oqOjyc3NxcDAADc3N/z8/DAyMiI2Npbjx48THh6u1256ejrh4eGcOXMGMzMzrK2tCQgIoHHjxgB4e3szfvx42rZtq5wzffp02rRpQ79+/XB1daVChQoY///3fD548AAHBwfCw8MxNzfXudbT90Oj0dCiRQuCg4MxNTXV6ePz7nmrVq10yvPz88nLy2PQoEEMHTq00Hv366+/smjRIm7evImRkRGOjo4EBgZiZWWl16/8/HwePHhAp06dmD17NoaGhtjb2xMSEkL//v2VNp+9L5mZmbi4uDBlyhRGjhypc6+2bdvG/v37qVGjhnJ87NixJCcnk5iYSGxsLOHh4dSqVUun33PnzqVq1ap07dqVtWvX0qFDB6XM1dWVL774gjVr1nDq1Ck0Gg1Xr17Fzs4OgGHDhvHvf/+70PshhBBCCCFEWVEug9atW7fi5uZGTEyMErQGBwfTt29fevfuDcCqVauYPXu2EowmJSXx7bffYmRkxH/+8x8GDx7Mjh07qFq1KrNmzeLJkyfExsZiYWFBSkoKPj4+qNVq+vbtC8CgQYOYMGGC0of169cTHh7ON998Q6dOnYDCgzuAuLi4IscSEhKi1D979iyjR4/mq6++on79+jr1YmJi2LRpE6tWrcLa2pr79+8zcuRIzMzM6N+/P7Gxsaxbt46oqChsbW3Jyspi+vTpBAcHExYWVuT1Hz9+rAQ3CxcuRKVScfjwYUaOHMnXX3/Nm2+++UJzsnr1aurUqQMUBJhDhgxh27ZtDBkyRK+u9n7k5+czYcIEtmzZgpeXl169593zZ8szMjJ47733MDU11QksAX7//XfGjh3LggULaN++PXl5eURHRzNs2DC2bt2qvJ/06XnKysqid+/eHDp0iM6dOwPwySef0LFjR73AUishIQFXV1diYmIYMWIEKpVKKatRowbff/893t7eSvvnz5/HwODPZAhXV9dCf1RITU3F2NiYWbNmER8fj4WFhU757NmzlXrDhg177vdNCCGEEEKIsqbcpQdrNBoSEhKYPHkySUlJXL16FShYLXz06JFSz8vLSwmEbt++TW5uLmq1GoB69eqxdOlSjIyMSElJYffu3YSGhirBgI2NDTNmzCAyMrLQPuTl5XHjxg0sLS1LdGxNmzalZ8+eSlD2tBUrVhAYGIi1tTUAlSpVYv78+TRo0ACAyMhIgoKCsLW1BcDCwoLQ0FC2b99OWlpakdfcuXMnVatWZdSoUUqQ1aFDB/r160d0dPRfGseDBw948OABlStXfm49jUbDo0ePlNXU5ynunltZWTFmzBi+/vprvbLo6GgGDhyorGAbGBjg6+tLhQoV2LVrV6HtZWZm8ujRI50xvPfeewQFBRXZx9jYWIYMGYKJiQlHjx7VKevevTu7d+9WPu/du5cuXboU2dazrK2tad++PfPnz3/hc4QQQgghhHgVlLuV1v3791O7dm3q1avH22+/TUxMDIGBgbz//vsEBgaybNkynJ2dcXFxwc3NDYC+ffuya9cunJ2dcXJyom3btrzzzjtYWlry008/YWdnp5fG6uTkREpKCnfv3gVg06ZN7N27l/v375OXl0eXLl2eu4L5NE9PT53PU6dOVVZnn/XWW2+xb98+nWMZGRlcv35dSdfV0qaBZmRkkJaWhqOjo065paUl9evXJykpqci+nT17lqZNm+odb926NYsXLy7yvGf5+vpiaGjInTt3qFmzJkOHDqVnz56F1tXejxs3blCjRg2cnZ0Lrfey97xBgwZcvnxZ7/jZs2cL7Uvr1q05d+6cspru6elJTk4Od+7cwc7OjqCgIJo1a6bU9/HxYc+ePXzzzTd6q7nJycmkp6fj5OREz549iYmJ0RlXo0aNOHToEOnp6VSrVo1du3YxcuRIDhw4oNRJTEzU+a6YmJjo/IAxffp0PDw8OHz4sE6asBBCCCGEEK+ycrfSunXrViUF2N3dndjYWNRqNS4uLhw4cICQkBCsrKxYuHChkjpqaWnJpk2b2Lx5Mx07duTgwYP07t2blJQUVCoVubm5etfJySl4/4d29XHQoEHExcWxefNmXnvtNZo3b66sehYnLi5O519RAav2ehUqVNA5pk0h1aaxFqWwcWg0Gp001cKuV9x5hZ2fn5+vk9q6evVqEhISmD17NpmZmbi5uRV5Xe19OHLkCG3atGHKlCmF1nvZe17YvdMe187ns2N8tl87duzA39+fBw8e0LVrV51yIyMjwsPD+eSTT7h+/bpO2ZYtW3Bzc8PQ0BB3d3f27t1Lenq6Tp3u3bvz/fffc+/ePbKysnj99dd1yl1dXXW+J8+uuFtYWPDxxx8za9YssrLkPX5CCCGEEKJ8KFdB6507dzh48CBr167F1dWVoKAg7t+/z+7duwkLC8PU1BQXFxc++OADEhISOHz4MBkZGaxbt47k5GTs7e0ZMWIEGzZsoGPHjuzevRtHR0euXLnCvXv3dK51+vRpbGxs9NJRq1evTkhICHPnziUlJaXEx3jx4kVlBVWrcuXK2NjYcO7cOZ3jx48fZ9GiRVhZWWFra8vp06d1yjMyMkhJSdFboX2ao6MjZ86c0Tt++vRpHBwcgIKg/8GDBzrld+7coVKlSnrn9ejRg06dOvHhhx8+f6AUBOPvvvsup06dem69F73nhd07eLExPm348OFUr16dBQsW6JU1aNBAL01YrVazfft2vvvuO1xdXZVNmGJjY3XO7dmzJ7t372bPnj1069at6AE/R8eOHSVNWAghhBBClCvlKmiNi4ujXbt2HDhwgMTERH788Uf8/f3ZuHEjiYmJbNu2Tan7+++/U7VqVSXgWrJkCdnZ2UDBJjgpKSk0atSI2rVr4+HhwcyZM5Xyq1evMm/ePMaPH19oP1q2bEmXLl1YuHBhiY7v119/Zffu3bz77rt6ZaNGjSI8PJzbt28DBQFpeHg4devWBWDy5MmEhYUpQV12djZBQUG4u7vrreg9zd3dnUePHrFq1Sry8/MBOHToELGxsYwaNQqAdu3asW3bNmW18vLlyyQlJdG8efNC25w0aRInT57US3MuzJEjR54bVGsVd89v3brFypUrC93Qyc/Pj61bt3L48GGgYJV4+fLlPH78uMgU5unTp7NlyxaSk5P1ynx8fMjMzFR+JPjxxx+pUqUKhw4dIjExkcTERObOnUtMTIxyTwEaNmxIeno6mzdvVlLX/4rp06dz6NAhbt269ZfbEEIIIYQQoqwoV8+0fvvtt3qppF5eXkRHRxMTE8PixYv59NNPqVChAtbW1qxcuRJDQ0PGjh1LREQEffr0wdTUFAMDA7y8vJTnAmfPns2qVat49913MTQ0xMTEhEmTJimvvCnM+++/j7u7OydOnMDJyem5/X72mda6deuydOlSAIKCgjA3N1dSWyMiIpRdeJ82ePBgcnJyGDlyJCqVivz8fAYOHKg8W9mrVy8MDQ2ZNGkSarWa3NxcevXqhb+/v9JGQkKCzmZAfn5++Pv78/nnn7NgwQIlpbd27dqsW7dOWbUcOHAgKSkpeHp6YmBggKmpqbLCW5iqVavi4+PDggUL6NixI0ZGul9D7f1QqVRUrFiRuXPnPvf+aT19z+HPZ16fvh+9evXSO69u3bqsWbOGRYsWERISQm5uLq1atWLDhg1Fply/9dZb9O3bl/nz57Nu3TqdMm2acL9+/YA/N2B6Wu/evVm8eDEHDx7UOd6tWzeOHz9OzZo1SU1N1Sl79plWgBEjRuh9v7RpwtofFYQQQgghhHiVqfKfXuoRQoinPHnyhHPnzpGUmoNa/7Ff8YpLv51OterF784tXi0yr+WXzO2L83RtQvUqFsVXLCNOnjxJq1atSrsbooTJvL4c7d+dDg4OegtH5So9WAghhBBCCCFE+SJBqxBCCCGEEEKIMqtcPV6m6wAAIABJREFUPdMqhPhndHNugJGxcWl3Q5Sw+/fuU8lSf5dv8WqTeS2/ZG5fnJmp/H+WEOWJBK1CiGJZWZoX+x5g8eq5evkidm/ULu1uiBIm81p+ydwKIf6vkvRgIYQQQgghhBBllgStQgghhBBCCCHKLEkPFkIUK+PeQ4yMNaXdDVHCKletxe3MrNLuhihhMq/ll8xt0cxMjbEwl8dYhCivJGgVQhRrz5FL8p7Wckje+Vg+ybyWXzK3RfN0bSJBqxDlmKQHCyGEEEIIIYQosyRoFUIIIYQQQghRZpWL9ODU1FTc3Nyws7NDpVKh0WiwtrZm3rx51KxZE4AJEyZw5coVEhISdM69desWCxYs4MKFCxgaGlKrVi2CgoKwsbEhNjaW48ePEx4eDsDNmzcZNmwYXl5e/4+9Ow+rqtofP/4+jA5ccQDLKccrmuSsiEPdAAVROCqaU6BoGhpqGSik5pAi4KwIqWlkV0ONE4hjKWpopoVaomiZmWKpIOSs5wDn9wc/9vV4GJNvIH1ez+PzsPdee+3PWutYflhr7YOPj49BPTqdjoiICHbv3o2lpSWWlpaMGTMGd3d3AFatWkVMTAw2Nv9b1vPiiy+ycOFC5Tg1NZWgoCDlODMzE2tra3bs2EFycjILFy5Ep9NRs2ZNQkJCaNCggUEMQUFBfPvtt1hbWwPw4MEDatasycKFC2nevLnR9XwajYZhw4ah1Wq5desW9+/fp169egCEh4fz8ccfF1kvQFJSEitXruTu3buYmJjQo0cP3nnnHapWrQrAnj17WLt2LdnZ2ej1etRqNW+88QYA3t7eXLt2jWrVqqHX69Hr9UyYMEHpu0uXLhEWFsaFCxewtLSkadOmTJs2jUaNGhEbG8vGjRsB+OWXX3jhhRcwNzenY8eOzJ4926CdFy9eJDw8nKtXrwLQsmVLZsyYQe3atZUyn376KWFhYRw4cABbW1vl8+Xj40NiYqIy1lOmTMHCwoLFixfj6+urxJ/PxsaG9evX86RTp06xbNkysrKyyM3NpXPnzgQFBVGlShWlTGhoKHFxcXz99ddYWFgo50vah0/GoNVqWbhwId999x0qlYoaNWowffp02rZtaxSfEEIIIYQQFU2lSFoB6tatS3x8vHIcGhpKeHg4S5cuJTMzk7Nnz2Jra8uJEyfo2LEjAPfv38fb25sxY8awaNEiVCoV27dvx9fXl927dxvUn56ezujRo5Wk9UmzZs3i0aNHaDQarKysuHLlCuPGjUOr1TJgwAAAhg0bxqRJkwptQ+vWrZU2PHjwgCFDhjBnzhwAAgMDiYyMpFWrVnz++efMnz+fqKgoozomT57MoEGDlOMFCxawatUqli9fXuD1fNu2bQMwStRLUu/Ro0eZPXs2q1atok2bNmi1WkJDQ5k4cSIbNmzgxo0bhIWFodFoqFWrFvfu3cPb25umTZvi7OwMwPz583FwcADg/PnzDB48mF69evHo0SN8fHwICAjA09MTgPj4eIYPH8727dvx8vLCy8sLACcnJ9auXUvDhg2N2pf/C4d58+bh5OSEXq9nzZo1+Pv7s3nzZqWcRqPB2dmZ2NhY/Pz8jOrJzs5m6tSpVK1alfDwcExNTY3iL8y5c+fw9/dn9erVtGvXjuzsbD744ANmzZrFokWLlPp3795Nhw4d2Lt3Lx4eHkr8penDx0VHR5Obm0tCQgIqlYrk5GQmTpzIgQMHMDeXL18XQgghhBAVW6VdHuzg4MDPP/8MQEJCAl26dKFPnz7ExMQoZXbu3Ent2rUZOnQoKpUKAE9PTwICAtBqtUq5mzdv4uvri6+vb4EJ65UrV9i7dy8LFizAysoKgEaNGhEcHExERMRfin/NmjV06dKFzp07o9VqmTJlCq1atQLAzs6OP/74o9g6tFot6enpRjOrT+vJeiMjI/H396dNmzYAWFhYEBwczIULF0hOTiYrKwudTsfDhw8BqF69OqGhobRo0aLA+u3s7KhWrRq//fYbn332Gd27d1cSVgC1Wk2nTp347LPPShzzZ599Rrdu3XBycgJApVIxbtw4RowYQXZ23huGzp07x61btxg3bhxbt24lNzfXoI6cnBwCAgKoVq0aixYtUhLWklq/fj1eXl60a9cOADMzMwIDA3FxcVHKHDx4kBdeeIEBAwYYfFZL24ePy8jIQKfTodPlvf23U6dOhISEGLVPCCGEEEKIiqjSzLQ+TqfTsXfvXtq3bw/kzZ5NnTqVli1bsmLFCt577z1q1qxJamqqkmg9zs3NTfk5MzOT0aNHo9PplBnTJ6WkpNC8eXODpZkAnTt35sqVK/z5558AxMTEsG/fPuX6smXLaNasmVF9d+7cYevWrcpSZgsLC9RqNQC5ublEREQYJDqPW7lyJdHR0fz5559YWlri4uLCW2+9ZXD9k08+UY4LWkZb2npPnz5tVIe5uTkdOnTg9OnT+Pr64uzsjIuLC61bt8bBwQEPDw8aN25c4LOSkpIAaNq0KStXruSVV14xKtOlSxcOHz5cbNz5UlNT6datm8E5U1NT+vfvrxzHxsbi5uaGvb09ZmZmJCUlKc/Oyclh2rRpfPXVV+zcuRMTE8Pf98ycOdNg/N3c3JgwYYJRDL179zY4Z2Vlhaurq3Ks0Whwc3PjlVdeURL/Fi1a0KpVq2L7sLAYfHx8ePPNN3F0dKRr1644OjoycOBALC3lLYtCCCGEEKLiqzRJ640bN5TETqvV0rZtW959911SU1O5du0a3bt3x9zcnNatWxMXF8fo0aMxMTEx2DNYkKSkJEJCQti1axdLliwhODjYqIxKpSInJ8fofP4MXv4sbnHLg/Nt374dFxcX6tSpY3Beq9USFBREdnY2b775ZoH35i/jvXjxImPGjKFXr17K7O/j10urqHpVKpXS1ifjzW/73LlzmThxIocPH+bw4cO89tprLF68mD59+gD/S7hycnKwtrZm+fLlVK9evdC+1el0St0loVKpihxrnU5HQkICGzZsAKBv377ExMQoSWv+ftEpU6YQGBjI5s2bDZbWlmR5sEqlKjJRvHnzJkeOHGH+/PlUqVKFV199lZiYGGbOnAkU34eFxdCwYUN27NjB6dOn+eabb4iLiyM6Opq4uDhq1KhRZMxCCCGEEEKUt0qzPDh/T2t8fDy7d+8mLCyMmjVrEhsbi1arxdXVFScnJ3799Vdl2aW9vT0pKSlGdc2YMUNZWuzu7s7AgQMJCQlh+/btHDp0yKh827ZtuXTpErdu3TI4f/LkSRo1alTq5bn79u1TXkKU7969e7zxxhtkZ2cTFRVV7F7EZs2aERAQwLRp07hz506pnl/aetu2bcupU6cMymm1Ws6ePYu9vT0HDx5k165dPPfcc3h5ebFs2TJmzpzJ559/rpSfP38+8fHx7Nixg02bNuHo6Fho3ZDXt/b29iWOu6Cxzs3Nxd/fn4yMDA4cOMCdO3fw9/fHyckJjUbDoUOHuHbtGpD3+Zo3bx5vvPEGFhYWrFixosTPfjyG06dPG5y7e/cufn5+aLVatm/fjl6vZ/DgwTg5OXH06FHi4+N5+PBhifqwMEuXLuXGjRu0bdsWPz8/NBoNdevW5ciRI6VugxBCCCGEEH+3SpO0FkSr1ZKQkEB0dDSJiYkkJiayf/9+0tPTOXbsGG5ubly9elV5CRHkLRE9fvy4suwyPzm0tbVlzpw5BAcHk5GRYfCc+vXr4+HhwYwZM7h37x4Aly9fZuHChfj7+5cqZr1ez5kzZ+jQoYPB+cDAQBo3bszy5cuLnR3O179/fxo0aEBkZGSpYihtvZMmTSIqKoozZ84AebOW8+fPp1mzZnTq1IkqVaqwZMkS0tLSgLw2pqam0rp162KfNWLECJKTkw1eshUXF8eJEycYPnx4iWMeOnQohw4dUn7poNfriYyM5ObNm9jY2KDRaJgyZYryOUlKSqJTp07KZ8Pc3ByVSoWJiQlhYWHExMRw9OjREj8fYPTo0Xz22Wf8+OOPQF4/hYaGYmVlhYWFBRqNhtDQUCWGw4cPY21tza5du56qD69fv87q1auVfdrp6elkZmbSsmXLUsUvhBBCCCFEeag0y4MLkpiYSIMGDZQX30DeHsIhQ4YQExODg4MD0dHRhISEEB0djUqlomHDhmzYsKHAxNDV1ZXExESmT5/ORx99ZLA8dfbs2axZs4bBgwdjamqKhYUFU6ZMMZoxLU5mZibm5uYGy0jPnj3L/v37adGiBQMHDgTyZv7WrVtXbH3Tpk1j9OjRjBgxAjDe0wqwZMmSEr3Qp7B6O3fuTFhYGAsWLODWrVtkZ2fz8ssvExkZiUqlolu3bvj7++Pn56e8DKhXr14Ge20LU6tWLTZt2kR4eDhRUVHo9Xr+/e9/89lnnxl8VU1xbG1tWbduHeHh4SxevJicnBxefPFFVq9eTUZGBseOHSMkJMTgHl9fX+bMmaMsO8/XsGFDgoODCQwMZPv27YDxflLI+/qcx5ff2tnZsWjRIhYsWMCDBw/Q6XR0796dmTNncvr0abKysgz2vJqYmDBq1ChiYmLYunVrsX1YWAyzZs0iLCwMNzc3qlatirm5OQEBAcrXFQkhhBBCCFGRqfR6vb68gxBCVEyPHj0iJSWFM2nZaI23LYtnXEZ6Bja2NsUXFM8UGdfKS8a2cGqnNtjWsiq+YAWVnJxMp06dyjsMUcZkXEsn/9+d9vb2Ru+BqdTLg4UQQgghhBBCPNskaRVCCCGEEEIIUWFJ0iqEEEIIIYQQosKq1C9iEkKUjd6OLTEr5muWxLPn9q3b1LCW7+qtbGRcKy8Z28JVtZT/RwlRmUnSKoQoVm3rakYb4sWz7/LF8zRvUr+8wxBlTMa18pKxFUL8U8nyYCGEEEIIIYQQFZYkrUIIIYQQQgghKixZHiyEKFbmrfuYmevKOwxRxmrWqUd61t3yDkOUMRnXyuufNLZVLc2xqibbUoQQeSRpFUIU66ujP6HNLu8oRFnLSM/AxtamvMMQZUzGtfL6J42t2qmNJK1CCIUsDxZCCCGEEEIIUWFJ0iqEEEIIIYQQosKqEEmrr68v+/btU47DwsLo0KEDWq1WOdezZ0/S0tLw9vbm2LFjBvcHBQWh0WgAlOuxsbGo1WrUajX29va4u7ujVquZO3cuaWlp2NvbK9fz/2zatMkoNicnJ9LS0gzOPRlDVlYWL730Ehs2bDCKa+TIkej1euWcRqMhKChIOT579izjxo2jT58+9OnTh7Fjx3LhwoUCn29nZ8e2bduKjGXz5s14enri7u5O7969CQ0NNejHwuIAOHbsGN7e3gCsWrWKHj16GPXRH3/8oZRPTEzEzs6OlJQUoz7L72+1Wo2TkxOTJ0/m/v37zJ07F7Vajbu7u8EYxMbGKvcXNXaPS0tLw8nJyahtT/Zbcf1SVF9kZWUpsfTo0cOgT7KysgzusbOzKzKOe/fuMXfuXHr37o2npycjRozg6NGjStmCPtuQ9zn6z3/+g1qtxsPDg4EDB7Jr164Crz/+JycnB41GQ9euXZVz/fv3p0+fPgZ/34QQQgghhKjIKsSe1m7dupGcnIyLiwsA33zzDe3btyc5ORlHR0d+++03qlWrRsOGDUtcp5eXF15eXkBe4rB27Vrl/rS0NOrWrUt8fHyZxJ+QkICTkxNbtmzB19cXlUqlXPvhhx/YuHEjo0aNMrrv0qVLjBkzhrCwMF555RUA9u3bx/jx49mzZw8WFhZG9yxZsoSePXtSr149o2sffvghBw4cYN26dTz33HNotVqCg4NZtmwZ06dPL3W7hg0bxqRJkwq9rtFocHNzY8uWLdjb2xtce7y/tVotI0aMIC4ujtmzZwN5Y+Dj41PgGBQ1dn/F0/RLrVq1lBhXrVoFUGSfFEav1+Pn50fr1q3ZuXMnFhYWnD17lvHjx7NkyRIcHByKvH/y5MkMGjQIgCtXrjBixAhq1qxJ9+7dja4/ycnJidDQUOV43759vP/++8rfNyGEEEIIISqyCjHT6ujoyMmTJwG4fv06FhYWuLq6cvjwYQC+//57evToUZ4hFkmj0TBixAgsLCz49ttvDa6NHTuWqKgofvvtN6P71q9fz6BBg5SEFcDFxYXx48dz927BbwccNWoUM2fONDr/6NEj1q1bx4IFC3juuecAsLCwYMaMGTRp0uQpWlewzMxMvv32WwIDA9m9e3eh8QLcuXOHO3fuULNmzTKPozh/d78U5vjx4/z+++8EBwcrv4x48cUXmTBhApGRkaWqq1GjRvj4+LB58+a/FMvVq1extrb+S/cKIYQQQgjxd6sQM61t2rTh8uXLPHr0iMOHDyvLMP39/QkMDOT777/H2dlZKT9z5kyqVaumHP/xxx907dq1VM+8ceMGarXa4Fx4eHiBSzzHjx+Pubm5cnz58mXl53PnzpGRkUHnzp3p27cvW7ZswdHRUbneuHFj/Pz8eO+99/jvf/9rUO+pU6eYOnWq0fOGDRtWaNzjxo3jq6++Ytu2bQwZMkQ5f+HCBczMzGjRooVB+dq1azN06NAC60pMTDTog/v37/P8888rxzExMQbLSBs2bMjq1asB2L59Oz169KBhw4bY29uzfft2RowYoZQdP348pqam3Lx5k+eff57XX3+dvn37Ftqu/ysl7Zfi+qKknvxM3bhxA4DTp09jb29vMAsP0KVLF5YsWVLq57Rs2ZIvvvhCOV65ciWffPKJctyxY0dlVju/bXfv3uXhw4f06NGj1ImyEEIIIYQQ5aVCJK2mpqa0a9eO06dPc/jwYUaOHEmjRo14+PAht27d4uTJk8yYMUMpP3/+fIPllE/uRyyJ0iwPfnJ5av6+T4DPP/8cNzc3TE1NcXd3JzIykoyMDGxs/vdKeh8fH7788ks2btzIv/71L4O6H09iRo8eTVZWFnfu3CEgIAB3d3ejWMzMzAgNDcXHx4eePXsWWteJEyeUPaAZGRkcOXLEqK4nl40eO3aMiIgI5bio5cFffPEF/v7+ALi7u/Pf//7XIGnN77O9e/cSGhqKm5ubUcL2dylJvxTXFyX15Gcqf8+tSqUiJyfHqLxOp/vL/VKlShXl55IsD7579y7jx4+nSZMmNG3a9C89UwghhBBCiL9bhVgeDHn7Wk+cOMGPP/5I+/btgbxlw/v376dWrVpYWVmVc4TGtFotO3bsYM+ePTg5OTFmzBgA5aVQ+UxMTAgJCTFaJvzSSy9x4sQJ5Tg6Opr4+Hi6du3Kw4cPC31uy5YtjZYJN2vWDK1Wy6+//grkzbTFx8cTHx9PRkZGmbQ335kzZ/jpp59YsGABTk5OrF69mp9//plTp04ZlXV1daVXr1689957T/3c06dPKy8UevyXGEX5O/ulKO3atSMlJQWdTmdw/tSpU0b7gUvi/PnzNG/evFT3WFlZERYWxtq1a5Xl+EIIIYQQQlR0FSZpdXR0JD4+npYtW2JmljcB3KNHDz7++OMKu5/1wIED1KpVi8OHD5OYmEhiYiLz5s1jy5YtBm8MBmjSpAl+fn6sX79eOTd+/HhiY2M5dOiQcu7KlSucO3cOE5Oih2bcuHFkZWUpyUfVqlXx8/MjODiY69evA5Cbm8v+/fuLrau0NBoNr732GgcPHiQxMZFDhw6hVquJiYkpsPyUKVNITk7m4MGDT/Xcl156SUk4FyxYUKJ7/s5+KUrnzp1p0aIFISEhSuKakpJCVFQUEydOLFVdly5dYvPmzQwfPrzUcTRq1IjXX3+dBQsWGH1GhRBCCCGEqIgqxPJgyJs9/PPPPw2WmHbr1o23335beUNqWSpoT2uXLl0KfMlRYfJfwPS4/v37s3TpUpKSkozK5y8TztekSRM++eQTli5dyqJFi9DpdPzrX/9i+PDheHh4FPns/GXCjy8JHT9+PHXq1GHixIlkZ2dz584d7O3t2bp1a4nb9Lgn97QCBAYGsmPHDjZu3GhwfvTo0QwdOpTg4GCjeurUqcO4ceMIDw+nZ8+eyi8lysLvv/9Ohw4dlONOnTrx0UcfGZQp6375qyIiIli2bBn9+/fH1NQUa2trFi1aZLDUfdy4cZiamirHO3fuBP63Z1WlUmFqasr06dPp2LGjUu7JPa1AoXtl33zzTT7//HMSEhLw9PQsyyYKIYQQQghR5lR6mW4RQhTi0aNHpKSkcCYtG212eUcjylpGegY2tjbFFxTPFBnXyuufNLZqpzbY1qp4W8P+ryQnJ9OpU6fyDkOUMRnX0sn/d6e9vT2WlpYG1yrM8mAhhBBCCCGEEOJJkrQKIYQQQgghhKiwKsyeViFExdXbsSVmj31Xsagcbt+6TQ3rGuUdhihjMq6V1z9pbKtayv9zhBD/I0mrEKJYta2rGe0tEM++yxfP07xJ/fIOQ5QxGdfKS8ZWCPFPJcuDhRBCCCGEEEJUWJK0CiGEEEIIIYSosGR5sBCiWJm37mNmrivvMEQZq1mnHulZd8s7DFHGZFwrr6LGtqqlOVbVZBuHEKJykqRVCFGsr47+JN/TWgn9k77z8Z9ExrXyKmps1U5tJGkVQlRasjxYCCGEEEIIIUSFJUmrEEIIIYQQQogKS5YHi6eSlpaGm5sbzZs3ByA3N5d79+4xYMAAJk+erJT76aef8PDwYOXKlbi6uirnnZycqFKlCubm5mRnZ9O0aVMWLFiAtbU1q1atIiYmBhsbG/R6PXq9nhkzZtCtWzfl3o0bN5KQkMCePXsAOHfuHK1atQLAzc2NCRMmKM9atWoVO3bsID4+nipVqgBw7NgxIiIi+PTTT9FoNBw/fpzQ0FAArly5wuLFizlz5gympqbUrl2bgIAAOnXqZPD8hg0bKs/w9vbG39+fEydOlCimoKAgunbtyqBBgwz6tTxiEUIIIYQQoiKSpFU8tbp16xIfH68cX79+HVdXV/r166cks7Gxsbi5ubFlyxaDpBVg7dq1SrK1YMEC1qxZw7Rp0wAYNmwYkyZNAiA1NZWxY8fyzTffGNw/YcIEJfmys7MziOVJV69eZenSpbz33ntFtikrK4sRI0YwefJkVqxYAcDJkyeZNGkScXFx2NgUvV+sNDEVpyLFIoQQQgghxN9NlgeLMpeeno5er6d69eoA6HQ6EhISePvttzlz5gyXL18u8L78WdrCkrA7d+5Qp06dp4pt6NCh7Nq1i++//77Iclu2bKFjx44MGTJEOdehQweCgoJ48ODBU8VQWhUpFiGEEEIIIf5uMtMqntqNGzdQq9U8evSIrKwsXnrpJSIiInj++ecBOHToEPXr16dp06a4uLiwZcsWAgMDlfvHjx+Pubk5N2/exNTUFH9/f+VaTEwM+/btQ6vV8ttvvzFv3rynirVmzZrMmTOHGTNmFDnjeOrUKXr27Gl0vn///gbH+bHnKywhfxoVKRYhhBBCCCH+bpK0iqeWvzw4NzeX0NBQfvnlF3r06KFcj42NVRIsd3d3AgICmDJlChYWFoDh8uANGzYwduxYdu3aBRguD7548SIjR46kadOmyl7Ov8LFxYXdu3ezdOlSnJ2dCy2nUqmUn6dNm8b58+e5f/8+w4YNY+zYsUaxQ94+0v8LFSkWIYQQQggh/k6yPFiUGRMTE6ZNm8b169dZv349ADdv3iQpKYkNGzbg5OTEzJkzuX37Nl999VWBdQwZMoSLFy+SlZVldK1Zs2Z07NiRU6dOPXWsM2fOZNeuXSQnJxd4/aWXXuLEiRPKcXh4OPHx8Xh6enL//v2nfn5pVKRYhBBCCCGE+LtJ0irKlJmZGdOmTSMyMpL09HTi4+Pp1q0bX3/9NYmJiRw4cAA/Pz9iYmIKvP/o0aPUq1eP2rVrG127ffs2Z8+e5cUXX3zqOGvVqsWcOXOIjIws8Prw4cNJTk5Go9Gg1+sByMjI4NSpU5iY/L1/bSpSLEIIIYQQQvzdZHmwKHMvv/wyHTp0YMWKFfzwww+88847BtdHjhzJRx99xC+//AL8by+miYkJpqamLF26VCmbv6fVxMSER48eMWTIEBwdHcskThcXF1xdXblx44bRtdq1axMTE8OSJUtYv349OTk5mJub4+npiY+PT5k8P9/s2bP54IMPlON169aVWyxCCCGEEEJUNCp9/tSNEEI84dGjR6SkpHAmLRttdnlHI8paRnoGNrZFf2WSePbIuFZeRY2t2qkNtrWs/uaIRFlJTk5+qvd1iIpJxrV08v/daW9vj6WlpcE1WVsohBBCCCGEEKLCkqRVCCGEEEIIIUSFJUmrEEIIIYQQQogKS17EJIQoVm/HlpiZm5d3GKKM3b51mxrWNco7DFHGZFwrr6LGtqql/DdaCFF5SdIqhChWbetqRhvixbPv8sXzNG9Sv7zDEGVMxrXykrEVQvxTyfJgIYQQQgghhBAVliStQgghhBBCCCEqLFkeLIQoVuat+5iZ68o7DFHGatapR3rW3fIOQ5QxGdfSq2ppjlU12QIhhBAVlSStQohifXX0J7TZ5R2FKGsZ6RnY2NqUdxiijMm4lp7aqY0krUIIUYHJ8mAhhBBCCCGEEBWWJK1CCCGEEEIIISosSVorubS0NOzs7Hj//fcNzqempmJnZ4dGowHA29ubY8eOAeDk5MSyZcsMygcFBRVY9nFOTk64u7ujVqvx9PRk0KBBfPvtt8r1Tz/9FHt7e9LT043uS0tLA8DOzo5t27YZXM9/XlRUFGq1GrVajZ2dnfJzVFSUQXmtVsvcuXPp378/Hh4ejBw5kh9//FHpD3t7e+Xe/D+bNm0iNjZWOba3t1faMnfuXKXuu3fv0qFDB65fv27wzOPHjzNw4MAybc9PP/2EnZ0de/fuNerro0eP8vrrr+Pq6krv3r2ZPHky165dK7aNQgghhBBCPGtkT+s/QM2aNUlKSiInJwdTU1MAdu3aRe3atQu955NPPqF3797Y29uX6llr166lYcOGACQmJhIQEMDhw4cB0Gg0ODs7Exsbi5+fX6F1LFmyhJ49e1KvXj2D8xMmTGANeG6xAAAgAElEQVTChAlAXjIYHx9f4P3R0dHk5uaSkJCASqUiOTmZiRMncuDAAQDq1q1b6L1eXl5AXuL5eFvyWVlZ0bt3b3bu3MmYMWOU83FxcQwePLhM2xMbG4ubmxtbtmzB1dVVOf/9998TGBhIREQE7du3B2DTpk289dZbxMbGFttGIYQQQgghniUy0/oPUL16dVq3bs13332nnDty5Ajdu3cv9J4333yT4OBgtFrtX36ug4MD6enpZGVlce7cOW7dusW4cePYunUrubm5hd43atQoZs6c+Zefm5GRgU6nQ6fLe9ttp06dCAkJKfKZpTFo0CB27NihHD969IiDBw/Sv3//Asv/lfbodDoSEhJ4++23OXPmDJcvX1auRUZGMmHCBCVhBRg5ciTu7u5PNV5CCCGEEEJURJK0/kP07dtXWWb6448/Ymdnh7m5eaHlPTw8aNSoEatXr/7Lz9yxYwdNmjShVq1ayqyhvb09ZmZmJCUlFXrfuHHjyMrKMlpWW1I+Pj788MMPODo6MmHCBDZu3EiHDh2wtMx7M+SNGzeMls6eP3++xPU7ODhw+/ZtLl68CMC+fftwdHTE2tq6zNpz6NAh6tevT9OmTXFxcWHLli3KtVOnTtGlSxeje8aOHYuFhUWZtFEIIYQQQoiKQpYH/0M4OTmxfPlycnNz2b17N3379mXXrl1F3jN37lzUajW9e/cu8XPGjx+Pubk5Op2OevXqsXz5cmXWcMOGDUBeAh0TE8Mrr7xSYB1mZmaEhobi4+NDz549S97I/69hw4bs2LGD06dP88033xAXF0d0dDRxcXHA0y+dValUDBgwgB07djB58mTi4+MZPXp0oeX/SntiY2OVmVt3d3cCAgKYMmWKkpSqVCogb//ukCFDALh16xZLly6lbt26sjxYCCGEEEJUGpK0/kNUr16dVq1akZyczLfffsu7775bbNJqa2tLUFAQwcHBtGzZskTPKWgf6JdffsmdO3fw9/cH8pa+3rx5k2vXrvH8888XWE/Lli3/8jLhpUuXMnLkSNq2bUvbtm3x8/Nj2LBhHDlyhJdeeqnU9RVk0KBBjBkzhhEjRnDp0iUcHR2LLF+a9ty8eZOkpCTOnDnDxo0b0ev13L59m6+++op+/frx0ksvceLECf79739jYWGhJKfe3t7KkmghhBBCCCEqC1ke/A/St29flixZoizRLQlPT08aNWpU4BtsS0qj0TBlyhQSExNJTEwkKSmJTp06FbtcNn9Z7cmTJ0v1vOvXr7N69Wplf2d6ejqZmZklTrxLon79+tSrV4+VK1fi6empzHwWpaTtiY+Pp1u3bnz99dckJiZy4MAB/Pz8iImJAWDSpEmsXr2aH374Qbnn3LlzXLlyRXnRlhBCCCGEEJWFJK3/IK+++iqpqam4u7uX6r65c+dSvXr1v/TMjIwMjh07ZvRmXV9fX7Zt20ZOTk6h9+Yvqy2tWbNmodfrcXNzo1+/fowbN46AgACaN28OFLzfc/78+aV+jpeXF59//rnyVTfFKWl7vvjiC0aMGGFwLv9re3755Rc6d+7MsmXLWL58OR4eHjg7OzN//nymT59O586dy7SNQgghhBBClDeVXq/Xl3cQQoiK6dGjR6SkpHAmLRttdnlHI8paRnoGNrY25R2GKGMyrqWndmqDbS2r8g6jWMnJyXTq1Km8wxD/B2RsKycZ19LJ/3envb298gLVfDLTKoQQQgghhBCiwpKkVQghhBBCCCFEhSVJqxBCCCGEEEKICku+8kYIUazeji0xMzcv7zBEGbt96zY1rGuUdxiijMm4ll5VS/nvmxBCVGSStAohilXbuprRhnjx7Lt88TzNm9Qv7zBEGZNxFUIIUdnI8mAhhBBCCCGEEBWWJK1CCCGEEEIIISosWR4shChW5q37mJnryjsMUcZq1qlHetbd8g5DlDEZ1+JVtTTHqppseRBCiGeFJK1CiGJ9dfQntNnlHYUoaxnpGdjY2pR3GKKMybgWT+3URpJWIYR4hsjyYCGEEEIIIYQQFZYkrUIIIYQQQgghKixZHvw3SUtLw83NjebNm6NSqdDpdNStW5eFCxfy/PPPAzBp0iQuXbpEQkKCwb03btwgPDyc1NRUTE1NqVevHjNnzqRRo0ZoNBqOHz9OaGgoANevX8fHx4eRI0fi4+NjUI9OpyMiIoLdu3djaWmJpaUlY8aMwd3dHYBVq1YRExODjc3/lpW9+OKLLFy4sMA2TZs2jW7dujFo0CAAkpOTWbhwITqdjpo1axISEkKDBg0M7vH29sbf3x8HBwej+pKSkli5ciV3797FxMSEHj168M4771C1alXS0tJwdnZmw4YN9OjRQ7nHycmJjRs3Aij9C/Dw4UM6duzIu+++q7Tn3r17LF68mMOHD1O1alWsrKyYNGkSjo6OAAQFBXHlyhX++9//olKpAIz6FyA2NlZ55i+//MILL7yAubk5HTt2ZPbs2djZ2XH+/HkA9uzZw9q1a8nOzkav16NWq3njjTcA+P3335k3bx5Xr15Fr9fTvHlz3n//ferUqVPgc48dO0ZERASffvppgWMF8OGHH1KvXj02bdrE1q1b0ev1qFQqfH19GTBgQIHjKIQQQgghREUmSevfqG7dusTHxyvHoaGhhIeHs3TpUjIzMzl79iy2tracOHGCjh07AnD//n28vb0ZM2YMixYtQqVSsX37dnx9fdm9e7dB/enp6YwePVpJWp80a9YsHj16hEajwcrKiitXrjBu3Di0Wq2S0AwbNoxJkyYV2Y7r168ze/Zsjh49Srdu3ZTzgYGBREZG0qpVKz7//HPmz59PVFRUifrm6NGjzJ49m1WrVtGmTRu0Wi2hoaFMnDiRDRs2AGBubs6sWbPYvn07VlZWRfavXq9n6dKlTJ48mc2bN6PX6/Hz86N169bs3LkTCwsLzp49y/jx41myZImSRP/www9s3LiRUaNGFRqrl5cXXl5eQF7SvHbtWho2bFhgP4WFhaHRaKhVqxb37t3D29ubpk2b4uzszPvvv8+AAQPo378/AGvWrGH27NlERESUqM8KG6sffviBbdu2sWXLFqpUqcLNmzfx8vKiVatWtGrVqkR1CyGEEEIIUVHI8uBy5ODgwM8//wxAQkICXbp0oU+fPsTExChldu7cSe3atRk6dKgy++fp6UlAQABarVYpd/PmTXx9ffH19S0wYb1y5Qp79+5lwYIFSsLXqFEjgoODS5wk5UtISMDZ2Zm+ffsq57RaLVOmTFGSIjs7O/74448S1xkZGYm/vz9t2rQBwMLCguDgYC5cuEBycjKQl5R2796dsLCwYutTqVRMmjSJn3/+mXPnznH8+HF+//13goODsbCwAPJmkSdMmEBkZKRy39ixY4mKiuK3334rceyFycrKQqfT8fDhQwCqV69OaGgoLVq0ACAjI4MHDx4o5UeOHFng2JVWeno6er1eqbtOnTqsXLmSWrVqPXXdQgghhBBC/N0kaS0nOp2OvXv30r59eyBvGWrfvn3p27cve/fu5c8//wQgNTVVSeQe5+bmRvXq1QHIzMxk9OjR6HS6QpeApqSk0Lx5c6pVq2ZwvnPnzly5ckV5XkxMDGq1Wvlz8eJFo7reeOMNhgwZYnDOwsICtVoNQG5uLhEREbi4uJS4P06fPk3btm0Nzpmbm9OhQwdOnz6tnAsKCuLw4cMcOXKk2DotLCxo3LgxFy9e5PTp09jb2yuJf74uXboY1N+4cWP8/Px477330Ov1JY6/IK1atcLZ2RkXFxcGDx7MokWLyM3NpXHjxgBMnTqVxYsX8/LLLzN9+nQOHTpE165dS1z/k2P11ltvAfDyyy/ToEEDevXqxeuvv86qVauoWbMmzz333FO1RwghhBBCiPIgSevf6MaNG0qC4enpiV6v59133yU1NZVr167RvXt36tWrR+vWrYmLiwPAxMREmRksTFJSEmPGjOGFF15gyZIlBZZRqVTk5OQYnc/OzlauQ96S0/j4eOVPs2bNStVGrVZLQEAA2dnZvPnmmyW+T6VSKbE8Wd/jiaaVlRUffPABs2bN4u7d4r+HUKVSUaVKlULbr9PpjBJZHx8f9Hq9sm/1acydO5fExESGDx/O77//zmuvvcaXX34J5CWXX3/9NfPnz6d27dosWrRIWe5rYmL8VzN/f2q+J8dq9erVQF6yHhkZyc6dO+nbty9nzpzB09OTU6dOPXV7hBBCCCGE+LtJ0vo3yt9zGR8fz+7duwkLC6NmzZrExsai1WpxdXXFycmJX3/9VVkibG9vT0pKilFdM2bMUJYWu7u7M3DgQEJCQti+fTuHDh0yKt+2bVsuXbrErVu3DM6fPHmSRo0aYW1t/dTtu3fvHm+88QbZ2dlERUVhbm5e4nvbtm1rlFRptVrOnj2Lvb29wfmePXuWaJmwVqvl119/pUWLFrRr146UlBR0Op1BmVOnThnVb2JiQkhIyFMvEz548CC7du3iueeew8vLi2XLljFz5kw+//xz/vzzT0JCQrC0tFRmWhMSEjhy5AiZmZnUqFGD27dvG9SXmZlZonGKi4vj6NGjNG7cmJEjR/Lhhx8yatQog/3UQgghhBBCPCskaS1nWq2WhIQEoqOjSUxMJDExkf3795Oens6xY8dwc3Pj6tWrbNu2TbknNjaW48ePK8tM85NDW1tb5syZQ3BwMBkZGQbPqV+/Ph4eHsyYMYN79+4BcPnyZRYuXIi/v3+ZtCUwMJDGjRuzfPnyYmeHnzRp0iSioqI4c+YMkDcDOn/+fJo1a0anTp2MyucvE75x40aB9eXm5rJq1SratWvHCy+8QOfOnWnRogUhISFK4pqSkkJUVBQTJ040ur9Jkyb4+fmxfv36UrXjcVWqVGHJkiWkpaUBeTOlqamptG7dmn/9618kJiYqM+oAFy5coE6dOlhbW9O+fXt+/PFHLl++DOR9Tr744gvlTcdFycnJYcmSJWRmZir3/vzzz7z44ot/uS1CCCGEEEKUF3l7cDlLTEykQYMGtGvXTjlnZWXFkCFDiImJwcHBgejoaEJCQoiOjkalUtGwYUM2bNhQYGLo6upKYmIi06dP56OPPjJYTjp79mzWrFnD4MGDMTU1xcLCgilTpihfefM0zp49y/79+2nRogUDBw4E8maW161bZ1R23LhxmJqaKsc7d+6kc+fOhIWFsWDBAm7dukV2djYvv/wykZGRRst38/vogw8+YOzYscq5/OXXkJe0tm7dmqVLlyrXIyIiWLZsGf3798fU1BRra2sWLVpU4NfvQN4y4fylvH9Ft27d8Pf3x8/PT0mUe/XqxVtvvYWpqSlr164lNDSUFStWUKVKFerWrcuHH36IqakptWvX5oMPPuDtt98mJycHrVZLnz59GDp0qFJ/TEwM+/btM3jm9OnT8fLyIisri+HDhyvLjPv168fgwYP/cluEEEIIIYQoLyr9075tRghRaT169IiUlBTOpGWjNd5yLJ5xGekZ2NjaFF9QPFNkXIundmqDbS3jr06r6JKTkwtcfSSefTK2lZOMa+nk/7vT3t4eS0tLg2uyPFgIIYQQQgghRIUlSasQQgghhBBCiApL9rQKIYrV27ElZqV4G7R4Nty+dZsa1jXKOwxRxmRci1fVUv57JoQQzxJJWoUQxaptXc1ob4F49l2+eJ7mTeqXdxiijMm4CiGEqGxkebAQQgghhBBCiApLklYhhBBCCCGEEBWWLA8WQhQr89Z9zMx15R2GKGM169QjPetueYchylhlH9eqluZYVZPtCkII8U8iSasQolhfHf1Jvqe1EpLv86ycKvu4qp3aSNIqhBD/MLI8WAghhBBCCCFEhSVJqxBCCCGEEEKICuuZWx6clpaGm5sbzZs3R6VSodPpqFu3LgsXLuT5558HYNKkSVy6dImEhASDe2/cuEF4eDipqamYmppSr149Zs6cSaNGjdBoNBw/fpzQ0FAArl+/jo+PDyNHjsTHx8egHp1OR0REBLt378bS0hJLS0vGjBmDu7s7AKtWrSImJgYbm/8tz3rxxRdZuHChQT0XL15k9uzZ3Lp1C1tbW5YuXYq1tTW///47gYGB3Lx5k6ZNm7J48WKqV69ucG9QUBDffvst1tbWAGi1WkaOHMnrr79OWloaPj4+JCYmcuzYMcaOHcsXX3zBv//9b+V+Ozs7zp8/X6p229nZ0apVK1QqFTk5OVSvXp25c+diZ2cHQGhoKHFxcXz99ddYWFgYPQtgz549rF27luzsbPR6PWq1mjfeeAMAJycnNm7cSMOGDQ2e6+3tzbVr16hWrZpyzsbGhuXLl9OvXz/mzp3Lq6++qlybOnUqzz33HNOnTzfq7/DwcK5evQpAy5YtmTFjBrVr11bKfPrpp4SFhXHgwAFsbW0BDPozf/ynTJmChYUFixcvxtfXt8D41q9fz5NOnTrFsmXLyMrKIjc3l86dOxMUFESVKlWUMoX1Y1F9V1gfrV+/Hq1Wy8KFC/nuu+9QqVTUqFGD6dOn07ZtW6P4hBBCCCGEqGieuaQVoG7dusTHxyvHoaGhhIeHs3TpUjIzMzl79iy2tracOHGCjh07AnD//n28vb0ZM2YMixYtQqVSsX37dnx9fdm9e7dB/enp6YwePVpJ3p40a9YsHj16hEajwcrKiitXrjBu3Di0Wi0DBgwAYNiwYUyaNKnQNuj1eiZMmMCMGTN4+eWXWbx4MWvXriUwMJC5c+cyYsQI+vXrx+rVq4mMjCQwMNCojsmTJzNo0CAAMjIy6N27N46OjgV+n2ZQUBBbt27F1NS00JiKazdg0O+ffvop77//Plu2bCE7O5vdu3fToUMH9u7di4eHh9G9169fJywsDI1GQ61atbh37x7e3t40bdoUZ2fnQuMCmD9/Pg4ODkbn582bx9y5c+natSvVq1fn0KFDnDt3zugXBPnJ+Lx583ByckKv17NmzRr8/f3ZvHmzUk6j0eDs7ExsbCx+fn5Gz8vOzmbq1KlUrVqV8PBwpT8Li+9x586dw9/fn9WrV9OuXTuys7P54IMPmDVrFosWLVLqL6gfS9J3hcUQHR1Nbm4uCQkJqFQqkpOTmThxIgcOHMDc3LzImIUQQgghhChvlWJ5sIODAz///DMACQkJdOnShT59+hATE6OU2blzJ7Vr12bo0KGoVCoAPD09CQgIQKvVKuVu3ryJr68vvr6+BSZuV65cYe/evSxYsAArKysAGjVqRHBwMBERESWO+cyZM1SrVo2XX34ZAD8/P0aOHIlOp+O7777D1dUVgEGDBrFnz55i67OxsaFp06ZcuHDB6FqHDh2wtrZm3bp1hd5fXLsL4uDgwE8//QTAwYMHeeGFFxgwYIBBvz8uKysLnU7Hw4cPAahevTqhoaG0aNGiRM8ryH/+8x86d+7MypUruX//Ph988AFhYWFGiftnn31Gt27dcHJyAkClUjFu3DhGjBhBdnbeG4bOnTvHrVu3GDduHFu3biU3N9egjpycHAICAqhWrRqLFi0q8hcABVm/fj1eXl60a9cOADMzMwIDA3FxcVHKFNaPT9N3GRkZ6HQ6dLq8t/926tSJkJAQo/YJIYQQQghRET2TM62P0+l07N27l/bt2wN5M2VTp06lZcuWrFixgvfee4+aNWuSmppKmzZtjO53c3NTfs7MzGT06NHodDplxvRJKSkpNG/e3GAZJkDnzp25cuUKf/75JwAxMTHs27dPub5s2TKaNWumHF++fBkbGxvee+89UlNTadasGbNmzSIrKwsrKyvMzPKGxtbWluvXrxfbD+fOnePy5csFthHyZuEGDRqEs7OzwTLhkrb7SXq9np07d9KhQwcgr9/d3Nx45ZVXCA4O5sKFC0YJVatWrXB2dsbFxYXWrVvj4OCAh4cHjRs3LvZ5M2fONOhzNzc3JkyYAMCMGTPw9PTk2rVreHp68tJLLxndn5qaSrdu3QzOmZqa0r9/f+U4NjYWNzc37O3tMTMzIykpiVdeeQXIS1inTZvGV199xc6dOzExMfx9T1HxPR5D7969Dc5ZWVkpv6CAwvuxJH1XWAw+Pj68+eabODo60rVrVxwdHRk4cGCBM/JCCCGEEEJUNM/kTOuNGzdQq9Wo1Wo8PT3R6/W8++67pKamcu3aNbp37069evVo3bo1cXFxAJiYmBjsDyxIUlISY8aM4YUXXmDJkiUFlsnfz/mk/Nm6/FncYcOGER8fr/x5PGHNL3/8+HGGDx/OF198QaNGjQgNDUWv1yt1PP7MgqxcuRK1Wo2HhwezZs1i3rx5RvtB89WvX5933nmHoKAgo/hL0u58+f3u7u7OL7/8wrx587h58yZHjhyhb9++VKlShVdffbXQ2da5c+eSmJjI8OHD+f3333nttdf48ssvi3wm5CXdj/fn4wlhzZo1eeedd0hNTTVKFPOpVKoix1+n05GQkKAksX379jVoQ/5+0SlTphAYGKjMWpYkvsdjKCpRLK4fi+u7wmJo2LAhO3bs4OOPP6Zdu3bExcWhVqu5fft2obEIIYQQQghRUTyTM61P7mnNFxERgVarVWau7t27R0xMDKNHj8be3h6NRmN0z4wZMxg9ejQA7u7uDBw4kJ49e+Lp6Un37t2VmbZ8bdu25dKlS9y6dUt5CRLAyZMnadSokcG5otja2tK4cWNlVrB///5MnjyZ2rVrc+fOHXJycjA1NSU9PZ26desWWMfje1pLYujQoezdu9domXBJ2p2voH7/+OOP0ev1DB48GICHDx+i0+kICAgweMHQwYMHuX//Pu7u7nh5eeHl5cXWrVv5/PPP6dOnT4nbUZD69evz3HPPFbpH097enpSUFINzubm5TJ48mTlz5nDixAnu3LmDv78/kJfE3rx5k2vXrgF5n7l58+ah1+s5dOgQK1asICAgoFQx2tvbc/r0aYO+vXv3LgEBAaxcuZLt27cX2o/ffvvtX+67pUuXMnLkSNq2bUvbtm3x8/Nj2LBhSoIshBBCCCFERfZMzrQWRKvVkpCQQHR0NImJiSQmJrJ//37S09M5duwYbm5uXL16lW3btin3xMbGcvz4cWWJZX7CY2try5w5cwgODiYjI8PgOfXr18fDw4MZM2Zw7949IG+p78KFC5WEpyQ6dOhAZmYm586dAyAxMZE2bdpgbm5O586d2bVrFwBxcXHKvteyMH/+fKKjow3OlaTdRdFoNISGhir9fvjwYaytrZU25KtSpQpLliwhLS0NyFtinJqaSuvWrZ+uUSUwdOhQDh06xKFDh5RnR0ZGcvPmTWxsbNBoNEyZMkVpQ1JSEp06dVI+L+bm5qhUKkxMTAgLCyMmJoajR4+WKobRo0fz2Wef8eOPPwJ5iXFoaChWVlZYWFgU2Y9P03fXr19n9erVyt7t9PR0MjMzadmyZaniF0IIIYQQojw8kzOtBUlMTKRBgwbKS24gb7/gkCFDiImJwcHBgejoaEJCQoiOjkalUtGwYUM2bNhQ4LJRV1dXEhMTmT59Oh999JHBEt3Zs2ezZs0aBg8ejKmpKRYWFkyZMkX5ypuSqFKlCqtXr2bmzJk8ePCA559/nvDwcKX+oKAgoqKiqFevHkuXLn2KnjFUv359pk6dyqxZswq8XlS7C3L69GmysrIM9mqamJgwatQoYmJiDGaCu3Xrhr+/P35+fsry2l69evHWW28pZfr372/wzJMnTwLG+zUh7+3FNWrUKFG7bW1tWbduHeHh4SxevJicnBxefPFFVq9eTUZGBseOHSMkJMTgHl9fX+bMmYNarTY437BhQ4KDgwkMDGT79u0ljs/Ozo5FixaxYMECHjx4gE6no3v37sycObPYfty6dWuxfVdYDLNmzSIsLAw3NzeqVq2Kubk5AQEBNG/evER9J4QQQgghRHlS6fV6fXkHIYSomB49ekRKSgpn0rLRZpd3NKKsZaRnYGNrU3xB8Uyp7OOqdmqDbS2r8g6jXCQnJ9OpU6fyDkP8H5CxrZxkXEsn/9+d9vb2Ru+BqTTLg4UQQgghhBBCVD6StAohhBBCCCGEqLAkaRVCCCGEEEIIUWFVmhcxCSH+7/R2bIlZIV8nJJ5dt2/dpoZ1yV5mJp4dlX1cq1rKf4uEEOKfRpJWIUSxaltXM9oQL559ly+ep3mT+uUdhihjMq5CCCEqG1keLIQQQgghhBCiwpKkVQghhBBCCCFEhSXLg4UQxcq8dR8zc115hyHKWM069UjPulveYYgy9qyOa1VLc6yqyTYEIYQQxiRpFUIU66ujP6HNLu8oRFnLSM/AxtamvMMQZexZHVe1UxtJWoUQQhRIlgcLIYQQQgghhKiwJGkVQgghhBBCCFFh/SOS1uHDh7Nz506Dc/fv38fBwYHMzEyCgoLQaDTKtbi4OLy8vFCr1Xh4eLBx40YAkpKSUKvVqNVqOnToQO/evVGr1bz11lsAZGRkEBAQgIuLCx4eHowdO5azZ88q9Xp7eyv3qNVqnJ2dGT16NBkZGQBGcQAMGjQIPz8/g3MajQYHBwflPoC0tDScnJwKbH9mZiYzZsygd+/e9O3bl4EDB7J//37lupOTE2lpaYX2X0Ex6PV6Vq5ciYeHB56engwePJivv/5auX7s2DGGDh2Kp6cn/fr1Izw8nJycHKO6C2rzqlWrWLVqVZn0Q3Ftf/z53t7eBAQEFBnL0aNHef3113F1daV3795MnjyZa9euGbVryJAhqNVq/vOf/9C1a1dlzM+fP19s+/PbFhQUpBxfuXKFKVOm4OLigqurK8OHDyc5OVm5XtAYent7c+zYMaKiopTn29nZKT9HRUUZPVcIIYQQQoiK5h+xp9XLy4uEhAT69eunnPvyyy9xcHCgdu3aBmW3bNlCTEwMa9asoW7duty+fZsxY8ZQtWpVhgwZQq9evYC8hMDf3x8HBwcAHj58iI+PD15eXixatAiVSsWRI0cYM2YMmzdvplmzZgDMnz9fuSc3N5fJkyfz8ccfExgYaBT3uegAet4AACAASURBVHPnsLCw4Ny5c/zxxx/Uq1dPuXbv3j1mz57N6tWri2y7Vqtl1KhRuLq6smfPHkxNTbl48SJjx46lQYMGtGrVqsj7C4th9+7dnDlzhi+++AIzMzN+/fVX5ZcD//rXv3j33Xf57LPPaNSoEVqtlsmTJ7Np0yZ8fHyKfF5pYiiuH/5K2/fs2YObmxsuLi5G177//nsCAwOJiIigffv2AGzatIm33nqL2NhYg7Lbtm0D8pLP48ePExoaWup258vKymLEiBFMnjyZFStWAHDy5EkmTZpEXFwcNjZF712bMGECEyZMAMDOzo74+Pi/HIsQQgghhBB/t3/ETGvfvn05ceIEf/75p3Ju+/bteHl5GZWNiooiMDCQunXrAlCjRg3CwsJo2bJlkc/YtWsXderUYezYsahUKgB69OjBoEGD+Oijjwq85/79+2RlZWFtbV3gdY1GQ48ePXB2dmbr1q0G11xdXfntt99ISEgoMq69e/diaWmJv78/pqamADRr1ow5c+YUOPNZ0hjS09PJyclBq9UC0LRpU1auXImZmRkPHjzg7t27/4+9O4+rqlofP/45zBCKA+KQaISFA+IskopeFEVEDmGpZTjghBM5X0zUNEQcUhO09Ks5oFfQ61FARW5eQsMcbg5dUXGISjRNECdwYDq/P/ixL0dGTQPteb9evnLvtfbaz9775IuH9ax9ePjwIQBGRkbMmjWLjh07lnu+p4kByr4Pz3LtY8eOZd68eTqflUKrV69m7NixSsIKMHjwYNzd3ZX78CJERkbStm1b3n//fWVfmzZtCAgIUO6xEEIIIYQQr6q/xEzra6+9Ro8ePdi/fz+DBg3i999/5+eff6ZLly46/TIyMrh+/TrNmzfX2W9ra1vuOc6cOUPLli2L7e/QoQPLli1TtgMDAzE1NSUjIwMLCwvc3d0ZNmxYseNycnKIiYkhPDycO3fuMHnyZMaPH4+BQcEjMzQ0ZOHChfj5+eHk5FRqXD/++CMdOnQotr9bt27lXlNZMXh5eREbG4uTkxPt27fH0dGRd999V0nAx4wZg7e3NzY2Njg6OuLm5kb79u1LPM/KlSvZtGmTsp2ens6gQYP+8H14lmtv3749d+7cISgoiKVLl+q0nT59Wqdkt9CIESNKHe95OH36dLHPKoCHh4fO9ujRozE0NFS2r1y58kLjEkIIIYQQ4s/wl5hphYI1kXv27AEgJiYGT09PZfatkJ5ewe0wNn76V+6rVKoSZ+9ycnKUmVcoKA+Ojo5m5cqV3L17F1dXV4yMjIodl5CQQJ06dWjSpAnt2rVDT0+Pb7/9VqdPy5Yt6d+/P3Pnzq1wnEuXLkWtVtO7d2+CgoLK7FtWDBYWFkRERLB9+3a6dOnCd999h4eHB6mpqUDBjOWhQ4cYM2YMWVlZjBo1io0bN5Z4Hn9/f6KiopQ/hQnr874PFb32KVOm8N///pcDBw4Uayt8ltnZ2cra0O7du3Py5Mkyz/1HFf0MzZgxA7VajaurK+vXr1f2r127Vuc+2tvbv9CYhBBCCCGE+DP8ZZLWDh06kJaWxvXr10stDa5RowbW1tYkJSXp7D9+/HixWbcnOTg4cPr06WL7T506VWLy0LZtW3x8fJg6dSq5ucW/AHPnzp1cv34dFxcXevToQWZmJhEREcX6TZgwgV9//VVJyJ9kb2/PqVOnlO1p06YRFRXFmDFjyMws+8vny4phw4YNJCcnY2dnx/DhwwkPD6dLly7ExcVx+vRptm7dSq1atfDw8GDhwoWEhYUp6zyfxh+5D8967aampgQHBzNv3jzu3r2r7G/ZsqWSnBoZGSnJobW1NTk5ORW6nlmzZinJ7pkzZyp0TNHzAixevJioqCg8PT158OBBhcYQQgghhBDiZfWXSVoBvLy8+PLLL7GwsKBRo0Yl9hkxYgQhISGkpaUBBSXDISEhNG7cuMyx3d3defjwIWvWrEGr1QKQmJiIRqMptXx0+PDhZGVlERkZqbM/PT2d77//nj179hAfH098fDy7d+/m6NGjykxmISMjIxYuXMhXX31VZlxffvmlkljdv3+fY8eOKTPLJSkvhvv377NixQqysrIAyMzMJDU1lWbNmmFhYUFYWBjJycnKeGfPnqVZs2Zl3sOnjaG8+/Cs1w4FZcJubm46CfLEiRNZtWoVP/74o7IvOTmZ1NTUYrP2pVmwYIGS7JZUTl6SwjcFazQa5bOVnp7O6dOny70OIYQQQgghXnZ/iTWthby9vXFxcWHBggWl9vnggw/Izc3F19cXlUqFVqtl4MCBOi/BKYmRkRGbNm1i8eLFuLm5oVKpaNCgARs2bCh1TayRkRGTJk0iODgYT09PZX9UVBTdunWjbt26yj5ra2tcXFyIjIxU3kRcqGXLlgwdOrTElxEZGRmxefNmVqxYgZeXFwB5eXn07t2bkSNHKv08PDx0SlAnTJhQZgyTJk1i+fLleHp6YmxsjJ6eHoMHD6Zz584AhISE8Mknn5CZmYlKpcLBwYE5c+aUeQ+f9EfvQ0WvvTRTpkzh4MGDynb79u1Zvnw5K1asID09nQcPHlC/fn3+/ve/l7petyLmzp3LZ599pmz/3//9n057rVq1iIiI4PPPP2f9+vXk5eVhaGiIp6fnM72NWQghhBBCiJeJSls4dSOEEE94/PgxSUlJnL2aS3bxKnbxkktPS8eyTtlfmSRePi/rc1W7tKBOTfPKDqNKO3HiBO3atavsMMQLIM/21STP9ekU/txpb29f7B1DUlsohBBCCCGEEKLKkqRVCCGEEEIIIUSV9Zda0yqEeDauTm9jUOQ7YMWr4d7de1S3qF7ZYYjn7GV9rqbG8m+MEEKIkknSKoQoVy0Ls2f6/mJRtV1JuYDtGw0qOwzxnMlzFUII8aqR8mAhhBBCCCGEEFWWJK1CCCGEEEIIIaosKQ8WQpQr4+4DDAxzKjsM8ZzVqF2ftNuZlR2GeM6q4nM1NTbE3EyWGAghhHg2krQKIcr1zZGL8j2tr6CX9fs8Rdmq4nNVu7SQpFUIIcQzk/JgIYQQQgghhBBVliStQgghhBBCCCGqLCkP/pNcvHiRfv36sXLlSnr37g3Ab7/9xvz587l27RparRZbW1vmzJlD7dq10Wq1hIaG8s0336BSqTAyMsLf3x9nZ2cAcnJyCAsLIzY2FmNjY4yNjfH19cXd3R2A0NBQIiIisLQsKBHLzs7GwMCATz/9lAcPHrB06VIArly5gqWlJWZmZjRs2JBVq1ZhZ2dH06ZNdeLv3r07kydPxsfHhxs3bmBmZkZeXh7m5ub4+/vzzjvvlHjdu3fvJjw8nNzcXPLz83n//fcZMmSI0h4dHc26devIy8tDT08PNzc3xowZg4GBARqNhuPHjxMSElJs3PT0dEJCQjh9+jSmpqZYWVkxdepUmjdvDoCPjw8TJkzA0dFROSYgIICOHTvi7e2Ni4sLJiYmGP7/7x69f/8+9vb2hISEYGZmRnJyMsHBwdy5c4e8vDxat27NrFmzMDMz04kjOzubhQsX8p///AeVSkX16tX5+9//joODAwB2dnZcuHCBY8eOERYWRnh4uM7xT+7PzMzE19eXtm3bEhAQoNP3yZgBJkyYgKurK7m5uXTv3p3evXsze/ZspT00NJQ9e/YQFRWFiYlJiecUQgghhBCiKpOk9U+yc+dO3NzciIyMVJLWOXPm4OXlhYeHBwBr1qxh7ty5SjJ69uxZdu3ahYGBAT///DMffPABe/fupXbt2syePZvHjx+j0WgwNzcnNTWVUaNGkZ2djZeXFwCDBg1i4sSJSgwbN24kJCSEHTt20LVrV6Dk5A4gKiqq1GsJCgpS+p85c4aRI0eydetWmjRpotMvMjKSiIgI1qxZg5WVFffu3cPX1xdTU1Pef/99NBoNGzZsYNWqVTRq1IjMzEwCAgKYM2cOwcHBpZ7/0aNHDBkyhP79+7NkyRJUKhWHDx/G19eXf/zjH7z55psVeiZr166lYcOGQEHy+eGHH7J7924+/PBDJk+eTHBwMG3atCE/P5958+bxxRdfMHPmTJ0xNm7cSH5+PjExMahUKk6cOMG4ceP49ttvdZLLisjKymLkyJF07NiRadOmlRtzUQcPHqRly5bExsYybdo0TE1NlbZr166xbNkyPvnkk6eKRwghhBBCiKpAyoP/BDk5OcTExDBp0iTOnj3LlStXgILZwocPHyr9Bg8ezODBgwFIS0sjLy+P7OxsAGxsbFi5ciUGBgakpqYSFxfHggULMDc3B8Da2pqZM2cSFhZWYgz5+fncuHEDCwuL53ptLVu2pE+fPuzYsaNY25dffsn06dOxsrICoHr16ixatIi3334bgLCwMAIDA2nUqBEA5ubmLFiwgD179nDt2rVSz7lv3z5q167NiBEjUKlUAHTu3Blvb2/WrVv3TNdx//597t+/T40aNYCCZ/Po0SMA9PT0mDBhAn369Cl2XHp6Ojk5OeTkFLxZt127dgQHB5Ofn/9U53/w4AGjR4+mU6dOpSasZdFoNLi6uuLg4MDevXt12gYOHMi+ffv44YcfnnpcIYQQQgghKpvMtP4JDh48SIMGDbCxsaFnz55ERkYyffp0pkyZwvTp0wkNDcXJyQlnZ2fc3NwA8PLyIjY2FicnJ9q3b4+joyPvvvsuFhYWfP/999ja2hYrVW3fvj2pqancuXMHgIiICA4cOMC9e/fIz8+ne/fuZc5gFqVWq3W2p02bpszOPumtt94iISFBZ19GRgbXr19XynUL2draKu3Xrl1TymgLWVhY0KRJE86ePVtqbGfOnKFly5bF9nfo0IFly5aVetyTRo8ejb6+Prdu3aJevXp89NFHSmI6c+ZMxo4di5WVFY6OjvTo0YPu3bsXG2PIkCGMGTMGJycnOnbsiJOTE++++y7GxhV/S+bDhw8ZM2YMFy9eZNWqVeXGXDiDa2Njw4oVK8jIyOD7778nODgYfX19tmzZwnvvvaccU6NGDT799FNmzZpV5gy6EEIIIYQQVZHMtP4Jdu7cqZQAu7u7o9FoyM7OxtnZmUOHDhEUFEStWrVYsmSJUs5rYWFBREQE27dvp0uXLnz33Xd4eHiQmpqKSqUiLy+v2Hlycwu+k6Rw9nHQoEFERUWxfft2XnvtNVq3bq3MepYnKipK509pCWvh+QrXSxbS0yv4aJWXvJV0HTk5Oco1lHa+8o4r6XitVqvEBQWltjExMcydO5fbt2/j5uamHOft7U1iYiLTp0/HwMCAgIAAFixYUGzMhg0bsmfPHjZs2ECrVq3YvXs3arWae/fulXndRZ05cwYnJyfc3d0JDAwss+/atWuVZ7JixQqgYF1wp06dsLCwoEePHly4cIFz587pHNezZ0/s7e2fKqkXQgghhBCiKpCk9QW7desW3333HV9//TUuLi4EBgZy79494uLiCA4OxtjYGGdnZ/7+978TExPD4cOHycjIYMOGDSQnJ2NnZ8fw4cMJDw+nS5cuxMXF4eDgwC+//MLdu3d1znXq1Cmsra2LlQDXqVOHoKAg5s+fT2pq6nO/xgsXLigzqIVq1KiBtbU1SUlJOvuPHz/O0qVLqVWrFo0aNeLUqVM67RkZGaSmphaboS3KwcGB06dPF9t/6tQp7O3tgYKk//79+zrtt27donr16sWO6927N127dlXWfP7yyy+sWrUKc3NzXF1dmTt3Ltu2bSuxBHrZsmXcvHkTBwcH/Pz80Gg0WFlZcfjw4VLjf1KbNm0YN24cAQEBXLp0iW3btlX4WCgoDT516hQuLi54enqip6dHREREsX6BgYHs27ePEydOPNX4QgghhBBCVCZJWl+wqKgoOnXqxKFDh4iPj+fbb7/Fz8+Pbdu2ER8fz+7du5W+ly9fpnbt2krCtWLFCrKysoCCt8qmpqbSrFkzGjRoQL9+/Zg1a5bSfuXKFRYuXMiECRNKjKNt27Z0796dJUuWPNfr++9//0tcXJxOOWqhESNGEBISQlpaGlCQkIaEhNC4cWMAJk2aRHBwsJJIZ2VlERgYiLu7O6+//nqp53R3d+fhw4esWbMGrVYLQGJiIhqNhhEjRgDQqVMndu/ercw+p6SkcPbsWVq3bl3imB9//DEnTpwgISGBWrVqsXnzZo4cOaK0nz9/nmbNmhU77vfff2fVqlXK2uO0tDQyMjKUdbsVUVjua2pqyuLFi1myZAmXL1+u0LFJSUncuHGDhIQE4uPjiY+PZ82aNcTExJCZmanTt2bNmnz66aesXr26wrEJIYQQQghR2WRN6wu2a9cuJk+erLNv8ODBrFu3jsjISJYtW8YXX3yBiYkJVlZWfPXVV+jr6zNu3DiWL1+Op6cnxsbG6OnpMXjwYDp37gzA3LlzWbNmDe+99x76+voYGRnx8ccfK195U5IpU6bg7u7ODz/8QPv27cuM+8k1rY0bN2blypVAwYydmZmZUha8fPnyEt9o+8EHH5Cbm4uvry8qlQqtVsvAgQN5//33Aejbty/6+vp8/PHHZGdnk5eXR9++ffHz81PGiImJIS4uTtkeM2YMfn5+bNq0icWLFyslvQ0aNGDDhg3KjO/AgQNJTU1FrVajp6eHsbGxMsNbktq1azNq1CgWL15MdHQ0a9euZcmSJQQGBmJoaIiNjU2JpbWzZ89m0aJFuLm5YWpqiqGhIdOmTSs28wzwww8/0KZNG2W7X79+9O3bV6dPq1atGDZsGJMnT+af//xnueXVGo0Gb29vnfJsR0dHbGxsiImJKda/Z8+e9O7dm5s3b5Y5rhBCCCGEEFWFSls4VSWEEE94/PgxSUlJnL2aS3ZuZUcjnrf0tHQs61hWdhjiOauKz1Xt0oI6Nc0rO4yX3okTJ2jXrl1lhyFeAHm2ryZ5rk+n8OdOe3v7YhM3Uh4shBBCCCGEEKLKkqRVCCGEEEIIIUSVJUmrEEIIIYQQQogqS17EJIQol6vT2xj8/7cci1fHvbv3qG5R/GugxMutKj5XU2P590MIIcSzk6RVCFGuWhZm5b7JWLx8rqRcwPaNBpUdhnjO5LkKIYR41Uh5sBBCCCGEEEKIKkuSViGEEEIIIYQQVVaFyoPT0tLYtWsXd+7c0dk/Y8aMFxKUEKJqybj7AAPDnMoOQzxnNWrXJ+12ZmWHIZ6zqvZcTY0NMTeT5QVCCCGeXYWS1rFjx1KvXj2sra1fdDxCiCromyMXyc6t7CjE85aelo5lHcvKDkM8Z1XtuapdWkjSKoQQ4g+pUNKak5NDWFjYi45FCCGEEEIIIYTQUaE1rS1atODixYsvOhYhhBBCCCGEEEJHhWZa27Zti5eXF3Xq1MHA4H+H/Pvf/35hgYkX79ixY/j5+dGoUSO0Wi05OTkMGjSIoUOHAuDj48ONGzcwMzMDIDMzE2tra5YuXYqlZUHpWXR0NOvWrSMvLw89PT3c3NwYM2aM8jm5efMmixcv5vz58+jr61O/fn0CAwN1Ss3j4+MZO3YsO3fuxN7eXtnv4uKCiYkJhoaG5OTkULduXaZOnar0KdpeqHnz5ixcuFDnOgMCAjh69CgWFhYAPHz4kBo1arBw4UJsbW0JDQ0FYOLEiQQEBJCamsqWLVtQqVQAaDQajh8/TkhICADnzp1j+fLl/PrrrwBYW1szc+ZMmjRpUuwe29nZ0bRpU1QqFXl5ebz22mvMmzcPOzs7AgIC6NixI97e3kr/orGUd/9/++035s+fz7Vr19Bqtdja2jJnzhxq166NRqMhJCSE+vXr68Qzf/58WrVqVebnQgghhBBCiKqkQknr+vXrWbp0KY0aNXrR8Yg/mb29PeHh4UBBUtS3b186d+6sJGBBQUE4OjoCkJ+fj7+/Pxs2bGD69OloNBo2bNjAqlWraNSoEZmZmQQEBDBnzhyCg4N58OABPj4++Pr6smTJElQqFdHR0QwfPpzY2Fgl2dRoNLi5uREZGamTtAKsXbuWhg0bApCQkMCIESOIjY2lVq1axdrL4u/vr5McLliwgNDQUFasWFGs748//sjmzZuV5L2oX375BV9fXxYtWkS3bt0AOHDgAKNHj2b//v0YGRkVOyYqKkr5e3h4OHPmzCEyMrLcmKHs+z9nzhy8vLzw8PAAYM2aNcydO1cp5XdxcVESbSGEEEIIIV5WFSoPrl69Ou7u7tjb2+v8Ea+Wx48fo6+vT7Vq1Upsf/DgAbdv31ZmLMPCwggMDFR+mWFubs6CBQvYs2cP165dY+/evdSqVYuBAwcqs5aenp5MmzaN7OxsADIyMjh69CjTp08nNjaWzMzS33jZvXt3HBwc2LNnzx+6zuzsbNLS0pTreNKIESP48ssvlZnUotavX4+3t7eSsAL07NmT0aNHlxl7IUdHx2cutX/y/qenp/Pw4UOlffDgwQwePPiZxhZCCCGEEKKqqtBMa6dOnVi0aBG9evXSmUlq0aLFCwtM/DmSkpJQq9Xk5+dz5coV+vTpg5WVldIeGBiIqakpGRkZWFhY4O7uzrBhw8jIyODatWs4ODjojGdhYUGTJk04e/Ys58+fL/Ez4ubmpvw9Ojqazp0707BhQ+zt7YmOjubDDz8sNd633nqLlJQUZXv06NE65cFDhgyhf//+xY5buXIlGzdu5M6dOxgbG9OzZ0/Gjx9f4jkaN26Mn58fn3zyCVu2bNFpO336NFOmTCl2zKBBg0qNuZBWq2Xv3r20adOm3L6FSrv/AFOmTGH69OmEhobi5OSEs7Ozzr2Nj49HrVYr20ZGRuzYsaPC5xZCCCGEEKIqqFDSGhMTA0BcXJyyT6VSyZrWV8CT5cEjR45k7dq1jBkzBvhfeerJkyfx9/fH1dVV5xcXeXl5xcbMyclBpVKhp6dXYrlsUbt27WLChAkAuLu7s2XLljKTVpVKhYmJibL9tOXBKSkp+Pr60rVrV8zNzUvtP2TIEP71r3+xefPmYjPPhbPGAMOGDeP27dvcv3+fadOm4e7uXmyswsQxOzsbW1tb5s+fX2ycQlqtFj29/xVAlHX/nZ2dOXToEMeOHePIkSMsWbKEvXv3snr1akDKg4UQQgghxKuhQklrfHz8i45DVAHm5ub06dOH77//vlhb27Zt8fHxYerUqezatYtatWrRqFEjTp06RdeuXZV+GRkZpKam0rx5c7KystBoNMXGmjVrFsOGDSM7O5uLFy+yYMECFi5cSF5eHjdv3uT06dO0bt26xBgvXLhA7969n/ka33zzTaZNm8aMGTOIjY0ttRRaT0+P4OBgBg0axMCBA5X9LVu25OTJk3Tv3h2AjRs3AgUve3r06FGJYxVd01qUhYUF9+7d09l369atEl/o9OT9z8zMZPXq1XzyySc4Ozvj7OzMuHHj6NKlCxkZGeXdBiGEEEIIIV4aFVrTmpWVxfz58xk6dCh37txhzpw5ZGVlvejYxJ8sLy+P48eP07x58xLbhw8fTlZWlvISoUmTJhEcHExqaipQ8DkJDAzE3d2d119/HTc3N65du6ZTkrpz506OHz9O48aN0Wg0DBgwgISEBOLj4zl48CBqtZqIiIgSzx8fH8/58+fp06fPH7pODw8PXn/9dWVGsjRvvPEGfn5+rF+/Xtk3evRodu7cycGDB5V9qampJCcn68yQVoSTkxP79u3jwYMHAKSlpZGQkECnTp1K7F/0/lerVo34+Hh2796ttF++fJnatWuXulZXCCGEEEKIl1GFZlqDgoKwsrLi1q1bGBsbk5mZyZw5c/j8889fdHziBStc06pSqcjNzcXOzo5Ro0aV2NfIyEhJVD09Penbty/6+vp8/PHHZGdnk5eXR9++ffHz8wPAxMSEjRs3EhwczMaNG1GpVDRs2JCvv/4agD179rB582adcwwbNoyBAwcyc+ZMQHfNas2aNVm/fr1OWe+Ta1pNTU1LTXqLmjFjBsOGDSuzFBn+VyZc6I033mDTpk0sW7aMJUuWkJOTQ7Vq1fjggw/o169fuectqlu3biQnJzNgwAClnHr69Om89dZbJfZ/8v6vXbuWkJAQvvjiC0xMTLCysuKrr75CX18fKL6mFQoSXy8vr6eKUwghhBBCiMqk0mq12vI6eXl5sXv3buW/+fn5eHh4sG/fvj8jRiFEJXn8+DFJSUmcvZpLdm5lRyOet/S0dCzrWFZ2GOI5q2rPVe3Sgjo1S3+HgKi4EydO0K5du8oOQ7wA8mxfTfJcn07hz5329vYYGxvrtFWonvHJsse8vLynLoUUQgghhBBCCCGeVoXKgzt06MCSJUt49OgR3333HVu3bqVjx44vOjYhhBBCCCGEEH9xFUpap02bxtq1a6lWrRrLly+na9eupX7HpRDi1ePq9DYGRdYOi1fDvbv3qG5RvbLDEM9ZVXuupsbyb4cQQog/pkJJ68GDBxk/frxOolq4xlUI8eqrZWFWbG2BePldSbmA7RsNKjsM8ZzJcxVCCPGqKTNpjY+PJzc3l8WLF6PVail8Z1Nubi6hoaGStAohhBBCCCGEeKHKTFrPnz/P0aNHuXXrls5XkxgYGDBs2LAXHZsQQgghhBBCiL+4MpPW7t27061bNw4ePEj37t3/pJCEEFVNxt0HGBjmVHYY4jmrUbs+abczKzsM8Zy9qOdqamyIuZksExBCCPHnKzNpnThxIiqVCq1Wi0ajUfZrtVpUKhX//ve/X3iAQojK982Ri/I9ra+gqvZ9nuL5eFHPVe3SQpJWIYQQlaLcNa1CCCGEEEIIIURl0avsAIQQQgghhBBCiNJI0vqKuXr1Kvb29qjVatRqNf369cPFxYWVK1eW2F74Z+vWrQC4uLjg7u6OWq3G3d2d4cOHk5SUVO55XVxcuHr1qs4+Hx8fjh07pmzfvn2bli1b8vXXX+v0CwgIoHv37kosvXr1YsCAAfz0009Ke9OmTfn99991jhs3bhwuLi7K9i+//MLYsWNxdXXFw8ODiRMnkpqaqhPj8uXLi527sPS9aLxarZYNGzYoMb377rvs3btXX5FZkQAAIABJREFU59jc3Fy6dOnCZ599Vup9sbOzAwruu52dHYcPHy73vh07dow2bdqgVqvx9PSkT58+bNq0SadPdHQ0np6e9O3bl379+rFq1Spycwvqd3ft2kWfPn149OiR0n/evHmEhISUGqcQQgghhBBVVYW+p1W8XKysrIiKilK2f//9d3r37k3fvn0xNjYu1v6ktWvX0rBhQwASEhIYMWIEsbGx1KpV6w/FFRMTg4uLC5GRkQwfPhyVSqW0+fv74+3trWwvWLCA0NBQVqxYAUDdunX517/+hY+PDwCZmZmcO3cOPb2C37ukp6czZMgQpk2bhqenJwBRUVF88MEHREdHK7Fv2rQJV1dX7O3ty4x1+fLlnDt3ji1btlCtWjVu3LjBRx99RM2aNXnnnXeAgu8vbtmyJbGxsUybNg1TU9MyxzQ0NGT27NlER0djbm5eZl97e3vCw8OVa+3bty+dO3emSZMmaDQaNmzYwKpVq2jUqBGZmZkEBAQwZ84cgoODeffdd0lISGDp0qUEBgayf/9+/vvf/7Jt27YyzymEEEIIIURVJDOtfwFpaWlotVpee+21pz62e/fuODg4sGfPnj8ch0aj4cMPP8TIyIijR4+W2i87O5u0tDQsLCyUfb169SIuLk7ZPnDggM4brbdt28Y777yjJKwAarWadu3a6SRrY8aMYebMmWRnZ5d6/qysLDZt2sTs2bOpVq0aAPXq1WPZsmXUqVNH53pcXV1xcHAoNgtbEisrK9555x0WLVpUbt+iHj9+jL6+vhJLWFgYgYGBNGrUCABzc3MWLFjAnj17uHbtGlAws/rNN9+wa9cuQkJCWL58OUZGRk91XiGEEEIIIaoCmWl9Bd28eRO1Ws3jx4+VktywsDDq1avH1atXlfaiFi9erJSyPumtt94iJSWl3POOHj0aQ0NDZfvKlSvK35OTk0lPT6d9+/b06dOHyMhInJyclPaVK1eyceNG7ty5g7GxMT179mT8+PFKe7NmzUhMTCQ9PR1LS0tiY2Px9fXl0KFDAJw5c4Zu3boVi6lDhw4kJiYq2/369ePMmTOsWrWKyZMnl3gdKSkpGBgY0LhxY539Dg4Oyt8zMjL4/vvvCQ4ORl9fny1btvDee++Ve48CAgLo168fhw8fpnPnzqX2S0pKQq1Wk5+fz5UrV+jTpw9WVlZkZGRw7do1nVgALCwsaNKkCWfPnuX111+nRo0afPbZZ4waNYqgoCAlwRVCCCGEEOJlIzOtr6DC8t99+/ahVqvRarU6CVJhe9E/pSWsACqVChMTk3LPu3btWp0xi5bg/vOf/8TNzQ19fX3c3d05cOAA6enpSru/vz/R0dFs3LiRnJwcunbtWqyEtlevXvzrX//i7t27ZGZm8vrrr+vEmJeXVyymnJwcnTJkKJiF3LFjR6lrdfX09MqdlYyOjqZTp05YWFjQo0cPLly4wLlz58o8BgpmRT/77DNmz55NZmbp36Nob29PVFQUMTExHD58mF9++YW1a9cq7RW51h9++AFLS0u+++67cuMSQgghhBCiqpKk9RWmp6fHjBkz+P3331m/fv0zj3PhwgVsbW2f+fjs7Gz27NnD/v37cXFxwdfXF0Dnu38Lvfnmm0ybNo0ZM2Zw//59nbY+ffoQFxfHN998g6urq06bg4MDp0+fLjbeqVOniq1frVOnDgEBAcycOZOcnJxix9ja2vLo0SN+++03nf179+5VXoik0Wg4deoULi4ueHp6oqenR0RERAXuBnTp0uWpyoTNzc3p06cPJ0+epFatWjRq1IhTp07p9MnIyCA1NZXmzZsDcOTIEfbs2YNGo+HixYsl3mshhBBCCCFeBpK0vuIMDAyYMWMGq1evJi0t7amPj4+P5/z58/Tp0+eZY/j222+pWbMmiYmJxMfHEx8fz/z584mMjESr1Rbr7+Hhweuvv87q1at19jdt2pT09HS2b9+Om5ubTtuHH37IiRMndF4wtXv3bk6ePMkHH3xQ7Byenp5YW1vrrJMtZGJiwuDBg/n000+V2dCrV6+ybNkybG1tSUpK4saNGyQkJCjXs2bNGmJiYsqcPS0qICCAxMREbt68WW7fvLw8jh8/riSkkyZNIjg4WHkzclZWFoGBgbi7u/P666+TkZFBQEAAISEh1K1bl8WLFxMSEqLzJmUhhBBCCCFeFrKm9S/A2dmZNm3a8MUXX+Dn51fimtYOHToQGBgI6K5NrVmzJuvXry/3bbdlKXwBU1EeHh4sW7as1NLVGTNmMGzYsGLHubq6cvz4cWV9bqGaNWuydetWFi9ezJdffolWq+Wtt95i27Ztpb71eN68eXh4eJTYNnnyZFatWsWAAQMwMDBAX1+fqVOn0qVLF+bPn4+3t7dOybSjoyM2NjbExMSUmCQ/qbBMeMSIESW2F65pValU5ObmYmdnx6hRowDo27cv+vr6fPzxx2RnZ5OXl0ffvn3x8/NDq9USEBCAWq2mY8eOQMEs9NChQ5k+fTpbt25FX1+/3PiEEEIIIYSoKlTakqa6hBCCgjcXJyUlcfZqLtm5lR2NeN7S09KxrGNZ2WGI5+xFPVe1Swvq1Hz2X2CKP+7EiRO0a9eussMQL4A821eTPNenU/hzp729PcbGxjptUh4shBBCCCGEEKLKkqRVCCGEEEIIIUSVJUmrEEIIIYQQQogqS17EJIQol6vT2xj8/5dziVfHvbv3qG5RvbLDEM/Zi3qupsbyb4AQQojKIUmrEKJctSzMii2IFy+/KykXsH2jQWWHIZ4zea5CCCFeNVIeLIQQQgghhBCiypKkVQghhBBCCCFElSXlwUKIcmXcfYCBYU5lhyGesxq165N2O7OywxDP2dM+V1NjQ8zNpPxfCCFE1SVJqxCiXN8cuUh2bmVHIZ639LR0LOtYVnYY4jl72ueqdmkhSasQQogqTcqDhRBCCCGEEEJUWZK0CiGEEEIIIYSosiRpraI0Gg0BAQEABAQEoNFodNpDQ0MJDQ0FwMfHh3bt2pGdna3TR61W4+Pjo4zRvXt31Go1/fr14/333yc5OVnpm5WVxbx583B1dcXT05MPP/yQI0eOlBibj48Prq6uylhDhgzht99+0+kTHx+PnZ0dSUlJxY6PjY3lvffeo0+fPvTs2ZNPPvmE+/fvF+t37Ngx2rRpg1qtxsvLCzc3N/z9/cnMzFTiOHbsGAAuLi4sX75c5/ii983Ozk6nbd68eXz00UdkZWUVO6bwPqnVavr06cOWLVuU9vT0dKZNm0bPnj3p168fI0aM4Ny5c0q7i4sLV69eLXYtT+5ft24dffv2JT09XdkXEhJCp06ddJ7j1atXsbe3V+Lp3bs3M2fO1DmurGd34cIF5diOHTsq1/b+++8Xi1EIIYQQQoiqSJLWV4S5uTmJiYnKdkpKCjdv3tTp4+/vT1RUFDExMYwZM4bAwEAAtFotfn5+GBoasnfvXqKjowkMDGT69OlKUvikoKAgZSwXFxcWLVqk067RaHBzcyMyMlJnf0xMDCtWrGDRokXExsbyzTffUKNGDWbNmlXieezt7YmKimL37t3s378fgDVr1pTYd9OmTSUmySXFnpKSwv/93//x2muvFWsvvE9RUVGEh4fz+eef89NPP/Ho0SOGDBlCs2bN+Oabb4iJicHX1xdfX19SUlLKPW+hjRs3EhUVxebNm7G0LFh3lpubS2xsLG3atCEuLk6nv5WVlRLP/v37sbS0xN/fHyj/2dnZ2SnHuri4KNe2Y8eOCscrhBBCCCFEZZKk9RXRq1cvnWRn37599O7du9T+9+/fVxKm48eP89tvvzFz5kyMjIwAaN68OWPHjmX16tXlnjszM1MZCyAjI4OjR48yffp0YmNjlZlRgLCwMD755BNsbW0BUKlUTJ48mZYtW1boOjt27MilS5dKbBszZgwzZ84sNuNcVEhICCkpKaxZswZTU9Nyz2dpaYmNjQ2XL19m37591K5dmxEjRqBSqQDo3Lkz3t7erFu3rkLxb968md27d7Np0yZq166t7E9ISKBRo0Z4eXkRERFR6vEqlYqJEydy6dIlkpOT//CzE0IIIYQQoqqTpPUV4ezszPHjx8nJKfhakoSEBP72t7/p9Fm5ciVqtZpevXoxe/ZsBg8eDMCZM2ewt7dXErFCHTp04MyZMyWeLzAwELVajYuLCxs2bKB///5KW3R0NJ07d6Zhw4bY29sTHR0NwJ07d/jll19o3769zliGhoaMGjWq3Gt88OAB8fHxtG7dusT2fv36YW1tzapVq0psX7JkCRs2bGD06NGYmJiUez6A5ORkrly5QosWLThz5kyJyXVZ96mof/zjHwQHB+Pj40OtWrV02gpnprt168b58+e5fPlyqeMYGRnRuHFjUlJSnunZCSGEEEII8TKRr7x5CTyZkEBBWaie3v9+52BkZES7du34/vvvqV+/PtbW1sUSM39/f7y9vQE4efIkI0eOJCoqCpVKRV5eXrFz5OTklHhuKCixdXR0BGD//v0MHz6cf//735ibm7Nr1y4mTJgAgLu7O1u2bOHDDz8sdj1Xr15l/PjxQMHs7Pbt26lfv77OeZKSklCr1UBBCW2nTp0YPnx4qfdq3rx5qNVqXF1di7VdvnyZRYsW8cknnxAVFUW1atVKHGPlypVs2rSJ/Px8TExMmD9/Pg0bNnym+1TUsWPHWLNmDTNmzMDJyYkGDRoAcOvWLQ4fPkxQUBAmJib87W9/IyIiQinfLolKpcLExOQPxySEEEIIIURVJ0lrFfLDDz9gbW1N3bp10Wq16OvrA2BhYcG9e/d0+t66dYsmTZro7HNzcyMuLo66devi7u5e5rnatm1Lo0aNOHv2LK1atSI8PJycnBwMDQ2VPqdPn8be3r7cuN3c3Jg9ezY///wzenp6XLx4kQULFrBw4ULy8vK4efMmp0+fpnXr1lhbW3Py5Em6dOlCw4YNiYqKAgpeVFRS8mVvb094eHi5MRSqU6cOAQEBzJw5k7ffflunLTQ0FCMjI7777jvmzp3LsmXLShyjaHJflIODA9u2bSu2/9SpUxW6T0uXLsXGxoZBgwYxdepUtmzZgr6+PtHR0Wi1Wt577z0AHj16RE5ODtOmTStxnOzsbH7++WeaNGlC9erV/9CzE0IIIYQQoqqT8uAqZOfOnRw4cAAoeOurtbU1AE5OTuzbt48HDx4AkJaWRkJCAp06ddI53tnZmWPHjnHo0CGcnZ3LPNe1a9e4evUqTZs2pX379jRp0oTg4GClvDgpKYkvv/yScePGlRt3UlISubm52NjYoNFoGDBgAAkJCcTHx3Pw4EHUarWyTnPSpEkEBQXx008/Kcf/8MMP3LlzR0nS/yhPT0+sra2LvdCocM3n3LlzOXnyJDt37nyqcd3d3Xn48CFr1qxBq9UCkJiYiEajYcSIEeUeX5hUTpgwgcePHytlzBqNhpCQEOLj44mPjycxMRELCwv27dtXbIz8/HxCQ0Np1aoVjRo1+sPPTgghhBBCiKpOZlqrkNGjRzNjxgy2bNlCvXr1WLFiBQDdunUjOTmZAQMGoFKp0NPTY/r06bz11ls6xxsZGdG2bVsAjI2Ni41fWPaqr6/P48eP+fvf/84bb7wBFLwgafny5Xh4eKCvr4+FhQVLlixRSoCfFBgYiJmZGfr6+uTm5rJ06VKMjIzYs2cPmzdv1uk7bNgwBg4cyMyZM/Hw8MDMzIzAwECysrLIzMzE1taWsLCwYqXBf8S8efPw8PAosa169eosXLiQ8ePH07ZtW2xsbCo0ppGREZs2bWLx4sW4ubmhUqlo0KABGzZsUF4sBeDh4aFTmnvq1CmdcQwNDVmyZAnvvfceTk5O3L59W6ecWU9Pj6FDhxIREUHHjh25efOmUiKdn59Ps2bNdGaJn/bZCSGEEEII8TJRaQunjIQQ4gmPHz8mKSmJs1dzyc6t7GjE85aelo5lHcvyO4qXytM+V7VLC+rUNH+BEYnn5cSJE7Rr166ywxAvgDzbV5M816dT+HOnvb19sQk4KQ8WQgghhBBCCFFlSdIqhBBCCCGEEKLKkqRVCCGEEEIIIUSVJS9iEkKUy9XpbQyKfKWOeDXcu3uP6hbVKzsM8Zw97XM1NZb/t4UQQlRtkrQKIcpVy8KsxDdSi5fblZQL2L7RoLLDEM+ZPFchhBCvGikPFkIIIYQQQghRZUnSKoQQQgghhBCiypLyYCFEuTLuPsDAMKeywxDPWY3a9Um7nVnZYYjnrPC5mhobYm4mZf1CCCFefpK0CiHK9c2Ri2TnVnYU4nlLT0vHso5lZYchnrPC56p2aSFJqxBCiFeClAcLIYQQQgghhKiyJGkVQgghhBBCCFFlSXnwK2L//v2sXbuW3NxctFotarWakSNHAuDj48O5c+c4cuQIRkZGyjFqtZrq1asTHh6u7AsJCWH37t0cOnRI6Xvs2DHCwsJ0+pW1v6jQ0FAiIiKwtCwoQXz06BFubm5MnjwZgKysLJYuXUpiYiKmpqaYm5szceJEnJycAAgICODo0aNYWFgAkJ2dzeDBg/noo48AuHnzJosXL+b8+fPo6+tTv359AgMDsba2BiA9PZ2QkBBOnz6NqakpVlZWTJ06lebNmyv35saNG5iZmQGQmZmJtbU1S5cuxdLSEh8fH+rWrcvSpUt1rglg4sSJOtfq4+PDhAkTcHR0VPYFBATQsWNHvL29Adi4cSORkZHo6+ujr6/PgAEDGDx4cJnjajQaQkJCqF+/PlqtluzsbDw8PBg7diz6+vo67UXNnz+f2rVr4+bmhq2tLQD5+flkZWXh5eWFv79/qc9NCCGEEEKIqkKS1lfA77//zqJFi9BoNNSsWZOsrCx8fHywsbGhR48eAJibm5OYmIiLiwsAKSkp3Lx5k+rV//cF9Lm5ucTGxtKmTRvi4uLo16/fc4lv0KBBSiL24MED3N3dad++PV26dMHPz49mzZqxd+9ejIyMOHfuHKNHj+bzzz9Xkj9/f38l6UtPT8fV1RUnJyfq16+Pj48Pvr6+LFmyBJVKRXR0NMOHDyc2Npa8vDyGDBlC//79lfbDhw/j6+vLP/7xD958800AgoKClHPl5+fj7+/Phg0bmD59OlDwCwE3Nzd69uz5h+5DaGgo//nPfwgPD8fS0pKMjAzGjRvHnTt3GD9+fJnHuri4EBISotzDcePGERoayqRJk4q1F3X16lWsrKyIiopS9v3+++/07t2bvn37KsmsEEIIIYQQVZWUB78Cbt++TU5ODo8ePQLgtddeIyQkhCZNmih9evXqRVxcnLK9b98+evfurTNOQkICjRo1wsvLi4iIiBcSq5mZGQ4ODly6dInjx4/z22+/MXPmTGVWt3nz5owdO5bVq1eXeLylpSU2NjZcvnyZvXv3UqtWLQYOHIhKpQLA09OTadOmkZ2dzb59+6hduzYjRoxQ2jt37oy3tzfr1q0rcfwHDx5w+/ZtZWYXYOzYscybN487d+4883U/fPiQ9evXExwcrMw616pVi6CgINatW8fDhw8rPJaZmRlTpkxh27ZtaLXap44lLS0NrVbLa6+99tTHCiGEEEII8WeTmdZXQNOmTenRowc9e/akWbNmODo60q9fPxo3bqz0cXZ2Zs6cOeTk5GBoaEhCQgITJ07kp59+UvpoNBrc3Nzo1q0bM2fO5PLlyzqJ7/Nw7do1Tp48ydChQzl16hT29vZKQlmoQ4cOfP755yUen5yczJUrV2jRogVff/01LVq0KNbHzc0NgDNnztCyZcti7R06dGDZsmXKdmBgIKampmRkZGBhYYG7uzvDhg1T2tu3b8+dO3cICgrSKRMuSWBgoFJqDHD9+nU6duzIpUuXMDU1pWHDhjr9mzRpgpGRESkpKWWO+6S33nqLO3fukJGRAUB8fDxqtVppNzIyYseOHUBBCbVarebx48fcvn2bli1bEhYWRr169Z7qnEIIIYQQQlQGSVpfEfPmzWPcuHEkJiaSmJjIgAEDWLp0Kb169QIKkph27drx/fffU79+faytrTExMVGOv3XrFocPHyYoKAgTExP+9re/ERERQWBg4B+OLSIiggMHDpCfn4++vj5+fn60a9eO06dPk5eXV6x/Tk6OTiK7cuVKNm3aRH5+PiYmJsyfP5+GDRuip6ens0b3SSqVqkLjF5YHnzx5En9/f1xdXYuNO2XKFNRqNQcOHCjzWouWGkPBmtayYoGCsuwnE/fyFPY3Ni74OovSyoMBpTw4Pz+fkJAQfvrpJzp37vxU5xNCCCGEEKKySNL6CkhISFDWivbv35/+/fuzfft2/vnPfypJKxTMQMbFxVG3bl3c3d11xoiOjkar1fLee+8BBS9MysnJYdq0aX84vqJrWotq1aoV4eHhyuxvodOnT2Nvb69sF13TWpS9vT0ajabY/lmzZjFs2DAcHBzYtm1bsfbCGd4ntW3bFh8fH6ZOncquXbswMPjf/x6mpqYEBwczefJkevfurVM+XBFNmjQhJyeHlJQUZS0twKVLl8jPz8fGxuapxrtw4QL16tXD3Ny8wsfo6ekxY8YMvLy8WL9+PaNGjXqqcwohhBBCCFEZZE3rK8DExITPP/+cq1evAqDVajl//jzNmjXT6efs7MyxY8c4dOgQzs7OOm2Fb6CNj48nPj6exMRELCws2Ldv3wuLu3379jRp0oTg4GBycnIASEpK4ssvv2TcuHHlHu/m5sa1a9eUMliAnTt3cvz4cRo3boy7uzsPHz5kzZo1ytrPxMRENBoNI0aMKHHM4cOHk5WVRWRkZInxurm5PdN6X1NTU8aOHcusWbO4desWUDC7PXv2bEaOHImpqWmFx7p//z5ffPGF8tbhp2FgYMCMGTNYvXo1aWlpT328EEIIIYQQfzaZaX0FdOrUiQkTJuDn56ckf127di32RlojIyPatm0L/K+sFArWft6+fRtXV1dln56eHkOHDiUiIoKpU6fyww8/0KZNG6W9X79+9O3bt8T98+fPr3DsYWFhLF++HA8PD/T19bGwsGDJkiU6JbalMTExYePGjQQHB7Nx40ZUKhUNGzbk66+/Vsp7N23axOLFi3Fzc0OlUtGgQQM2bNhQ6ltzjYyMmDRpEsHBwXh6ehZrnzJlCgcPHqzw9RU1evRoqlWrxrBhw9BqtahUKgYNGqSTfK5Zs4avv/5a2Z43bx7wvzWrhWXGvXr10pkpfXJNKxQk4O3bty8Wh7OzM23atOGLL74gKCjoma5FCCGEEEKIP4tK+yyvHxVC/CU8fvyYpKQkzl7NJTu3sqMRz1t6WjqWdSwrOwzxnBU+V7VLC+rUrPgSAlH1nThxgnbt2lV2GOIFkGf7apLn+nQKf+60t7fXmWADKQ8WQgghhBBCCFGFSdIqhBBCCCGEEKLKkjWtQohyuTq9jUGRNzyLV8O9u/eoblG9ssMQz1nhczU1lv9nhRBCvBokaRVClKuWhVmxtQXi5Xcl5QK2bzSo7DDEcybPVQghxKtGyoOFEEIIIYQQQlRZkrQKIYQQQgghhKiypDxYCFGujLsPMDDMqewwxHNWo3Z90m5nVnYYogymxoaYm0lpvhBCiL82SVqFEOX65shF+Z7WV5B8T2vVp3ZpIUmrEEKIvzwpDxZCCCGEEEIIUWVJ0iqEEEIIIYQQosqS8uD/7+rVq7i5uWFra4tKpSInJwcrKysWLlxIvXr1AJg4cSK//PILMTExynHHjh3Dz8+PRo0aoVKpePToEW+//TbBwcGYm5vj4uKCiYkJhkW+47J58+YsXLiQgIAAjh49ioWFBQAPHz6kRo0aLFy4EFtb22IxJiQk8NVXX/HgwQPy8/Pp2bMn/v7+6OnpERAQQMeOHfH29lb6h4aGKnEX8vb2xsrKiq+++krnGsLCwggPD0ej0bBo0SL27t2LpaWlcm+GDBlCfHy8TjxPjn/p0iV8fX2ZPXs2vXr1ws7OjgsXLjBv3jxOnjxJTk4OV65cUa5tyJAh9O/fXxnv+PHjTJw4UbnfhfcpOzubWbNmkZSUhImJCUuXLsXW1hYfHx/effddvL292bp1K9u3b0er1aJSqRg+fDheXl7F7qFWq2Xjxo3s3r0bAD09PUaOHEnfvn0BcHFxYfPmzTRs2FA5xsfHhwkTJuDo6IidnR1NmzZVxrp//z5du3Zl7ty56Ovr6xx/7Ngxli1bxsOHD8nLy6Nbt25MnTqVy5cvM2PGDACuX7+OmZkZFhYWGBkZsWPHDlxcXDA0NCQuLk6JITc3ly5dutC9e3dCQkKU/SV9JoEK3w8hhBBCCCGqOklai7CysiIqKkrZDgkJYfHixSxbtoyMjAzOnTtHnTp1OHnyJG3btlX62dvbEx4ermz7+/uzZs0apk6dCsDatWt1kqCi/P39dRLNBQsWEBoayooVK3T6HTp0iPnz57N+/XpsbGx49OgRkyZNYuXKlUyaNKlC15ecnIyRkRHJyclcv36d+vXrl9gvKyuLuXPnsmrVqgqNC/DTTz8xatQo5s6dS8+ePXXa5s6dC/wv+S16j4tKSkrC19eXMWPG6OwPDw/H1NSU2NhY/vOf/zBz5ky2b9+OsbExJiYm/Pjjj+zYsYPIyEhMTEy4desW/fv3p2nTpkqCWWj58uWcO3eOLVu2UK1aNW7cuMFHH31EzZo1eeeddyp0rUXjz8zMxMPDg8TERLp166bsz87OZurUqWzbtg1ra2uys7Px9/dn69atOvegpF82ADx69IgLFy5gZ2cHwJEjR1CpVDp9SvtMPs39EEIIIYQQoqqT8uAyODo6cunSJQBiYmLo0KEDvXr1IiIioszjOnbsqBz3NLKzs0lLS1NmXov66quvGDt2LDY2NgCYmJjw6aef0rFjxwqPr9Fo6Ny5Mz169GD79u2l9uvduze//vprsdm70vz888+MGjWKTz/9tFjC+jTOnDlDYmIi/fr1w8/Pj+vXrwMFM8yenp4AdOjQgYyMDH777TdatWoGxwWCAAAgAElEQVSFnZ0daWlpaLVaHj58CEDt2rVZuXIlNWvW1Bk/KyuLTZs2MXv2bKpVqwZAvXr1WLZsGXXq1HmmmG/fvq3MkBf18OFDMjMzlZiMjIyYNWtWhZ9Xr169dGZa9+3bR+/evXX6lPaZrOj9EEIIIYQQ4mUgM62lyMnJIS4ujtatWwMFCd+UKVN4++23+eKLL/jkk0+KJSoADx48ID4+Xic5GT16tE55cNGy2JUrV7Jx40bu3LmDsbExPXv2ZPz48cXGPX/+PLNmzdLZV69ePaWUtnCsTZs2Kdvp6ekMGjRIuZ6YmBjCw8O5c+cOkydPZvz48RgYFP8IGBoasnDhQvz8/HBycirzPv36668MHTqUxo0b07179zL7lqdatWr06dOHXr16sW3bNiZPnkxERAQ3b97USSrr1KnDjRs3lLJka2trNBoNXbt2pXXr1jg6OqJWq6lbt67O+CkpKRgYGNC4cWOd/Q4ODjrbTz6vK1eu6LSr1Wpyc3O5desWtra2BAYG0qpVK50+FhYWjBkzBm9vb2xsbHB0dMTNzY327dtX6F64ubnx6aef4u/vT3Z2NsnJyfj4+HD8+HGlT2mfSWdn5wrdDyGEEEIIIV4GkrQWcfPmTdRqNVAw6+ng4MDUqVM5f/48N27c4J133sHQ0JBmzZr9P/buPL6mc9/j+GdnTm6IELNQDaWEUio0hp7QI8Y4dDBU0JprqBbH1FI1JMYiQp2mQuoQJE0MDVcbdTmmlmoFUTUVl0rEkJgy7fuHk3VtOzK02oTzff9lr/WsZ/2eteT1yi/P73k2MTEx9O3bF7hX1ppzXWZmJk2bNqVfv35GvwUpDz516hRvvvkmLVq0wNXV1aqdyWTC0THvrz14sNQ4Z80p3JutLFu2LDVq1MBsNmNjY8P27dt5+eWXc+2rXr16dOvWjcmTJzN+/PiH3nPbtm0sWLCA+fPns3LlSgIDA/OMMS9Tp041/t2jRw/mzp1LamqqsS4zR078ORwcHAgNDeXs2bPs2rWLnTt3EhYWRnh4uPFHB7i3ftXBwSHfOB58X71797Y4n1PaGx4eTnR0NK1bt861nyFDhvD666+ze/du/vWvfzFgwABGjhxp/L/JS/ny5XF1deXkyZP88ssv+Pr6WpzP6/9kQZ+HiIiIiMjjQOXB98lZ0xobG0tcXBzBwcGUKlWKqKgo0tPTadu2LX5+fpw+fdqiHNPb29u4bvPmzbz//vv5JpgPevrppxk9ejRjx44lNTXV6ry3tzcJCQkWx06fPm1s6JOfqKgoLl68iJ+fH61btyYtLS3fMudhw4Zx9uxZNm3a9NA2ffr04aWXXmL27NksXLiQxMTEAsXzoOzsbJYsWUJWVpbFcVtbW8qXL8/ly5eNY8nJyZQrV874HBMTw549e6hWrRq9evVi6dKl9OnTx2rtrJeXF3fu3OF///d/LY5v3rzZYoa6oPr27UvZsmWZNWuW1blDhw6xatUqSpcuTceOHZk5cyYhISGsW7euwP37+/uzZcsW4uLiaN++vcW5vP5PFvR5iIiIiIg8DpS05iM9PZ2NGzcSHh5OfHw88fHxfP311yQlJbFv375Heq+OHTtSuXJlQkNDrc7179+fkJAQzpw5A9xbnxkUFPTQzZTul5yczO7du9m0aZMxhpiYGPbu3cu5c+ceep2DgwMzZ8602Gn4QTlltM888wxDhw5l1KhRxlrKwrCxsWHbtm3GOs6YmBiee+45XFxcaNWqlZFwfffddzg6OlKpUiXj2qysLObOnUtKSgpw752dOHGCOnXqWNzDycmJXr16MWXKFNLS0oB7m0PNmzcv192aC2LcuHGsX7/eKll3c3MjJCTE4viRI0d49tlnC9x3TtJ68uRJi7Hk93+yoM9DRERERORxoPLgfMTHx1O5cmWLNYuurq68+uqrrFmzxlgzmpcH10g6Ozs/dJZz7Nix9O3bl549e+Lp6Wkcb9myJaNGjWLUqFFkZWWRmZmJv78/w4YNy/f+sbGxtGrVymJNo6enJ35+fkRGRtKiRYuHXluvXj369OlToE2Z+vXrx/bt25k+fTrTpk3Lt/2DgoODef/991m8eDGlS5c2ZjB79+7NBx98QIcOHXBwcLCa2ezWrRtXr16lR48eRtlwhw4deOWVV6zuMWrUKBYvXsxrr72GnZ0dtra2vPfeezRv3rzQ8QLUrFmTLl26EBwczPLly43j1atXJygoiAkTJpCWlobJZKJ+/fp88MEHBe67fPnylChRwmrzpvz+T86fP7/Az0NEREREpLgzmc1mc1EHISLF0927d0lISODI+UzSM4s6GnnUkpOS8SjrUdRhSB4C/OpS1t16n4O8HDhwgEaNGv1BEUlR0rt9cundPpn0Xgsn5/dOb29vq6WWKg8WERERERGRYktJq4iIiIiIiBRbSlpFRERERESk2NJGTCKSr5ebPYPdfZuJyZPhxvUblHQrWdRhSB6cHfVzJyIioqRVRPJV2s2l0N89LMXfL6eO4/VUpfwbioiIiBQhlQeLiIiIiIhIsaWkVURERERERIotlQeLSL5Srt/Czj6jqMOQR6xUmYokXU0r6jDkAc6O9ri6qBxfREQkh5JWEcnXtj0/kZ5Z1FHIo5aclIxHWY+iDkMeEOBXV0mriIjIfVQeLCIiIiIiIsWWklYREREREREptlQeXET27dtHSEgIERERFsfPnz9PYGAg8fHxFsdr1arF8ePH2bdvH2+99RZffPEFNWvWtDoPcPnyZWbNmsWxY8ewtbWlYsWKTJo0CU9Pz1zv+7B7Llq0iDVr1uDh4YHZbMZsNjNx4kSaNm1qtLl69SotW7Zk1KhRvPnmmxbXHz16lPnz53P27FkAPD09GT9+PDVq1LB6HrVq1aJ27doAmM1mUlNTadGiBZMnT8bW1tbifI6XXnqJUaNG0bt3by5duoSLiwtZWVm4uroyYsQIXnzxRav73N8WIC0tDU9PT+bMmYOHh4fVeQAPDw/mzJlD3759AUhOTjaOA4SHhzNixIg8+wXYsGEDn376KVlZWdjY2ODv78+gQYOws7v3Y7hq1SrWrl2L2WzGZDLRr18/unTpAoCfnx9OTk7Y29tjNpuxs7Nj7Nixxrv48ccfmTNnDr/++it2dnbUr1+fMWPGULp0aZYsWcKWLVsASExMNJ6jv78/Q4YMsXpGIiIiIiLFiZLWx9S4ceNYu3Yttra2Fsdv3bpF7969efPNN5k9ezYmk4kNGzbQr18/4uLiCn2f7t27M3z4cACOHTvGW2+9xe7du43zGzduxM/Pj8jISPr164fJZALgzJkzvPnmmwQHB9OqVSsAvvrqKwYOHMiWLVtwcHCwuldsbKzx77S0NDp27MiuXbuM6+8//6Bp06bh4+MDwOHDh+nfvz+rVq3KNUG+v212djYjRoxg+fLljBkzxup8bvEtWrQIwHguBek3Ojqa5cuXs3jxYqpWrUpaWhrjxo3jgw8+YMaMGfzwww+sW7eOyMhInJycuHLlCt26daN27dpGkrls2TKqVKkCQHx8PKNHj2bXrl38/PPPDB06lFmzZvHiiy+SnZ3Np59+SmBgIFFRUQwZMsRITmvVqpXncxQRERERKW5UHvwYatiwIW5ubvzjH/+wOrd582ZKly7N66+/biSQnTt3ZvTo0aSnp/+u+6amplKmTBmLY9HR0fTs2RMHBwf27t1rHA8LC6Nr165GwgnQpk0bBg4cSFpa/ruVXr16ldu3b1OqVKlCx1mvXj3atWvHunXr8m1769Ytrl69ipubW6HvU5h+Q0JCmDRpElWrVgXA1dWV6dOns2nTJi5cuEBSUhJms5nbt28DUKZMGRYuXIi7u3uu/fv4+JCUlMTVq1f59NNPef31142ZZRsbGwYOHIiTk9Nv+kOFiIiIiEhxopnWx9S0adPo2rUrrVu3tigTPnbsGHXr1rVq7+/vb/w7ISGBgIAA43NGxsO/ymTNmjV89dVXpKenc/bsWaZOnWqcS0xMJDk5mcaNG9OuXTsiIyNp1qwZAIcOHeLdd9+16q979+4PvVdAQACZmZlcuXIFLy8vJk2axHPPPWdx/n6jR4+mRYsWufZVs2ZNvvnmm1zPTZo0CWdnZ1JSUnBzc6N9+/ZG6W/O+fvLgwtaRvuwflNSUrhw4QL169e3aO/m5kaNGjU4cuQIL730EtHR0bRo0YIGDRrg4+NDQEAA5cuXz/VemzZt4qmnnsLd3Z3Dhw/Trl07qzYvvPACCQkJRomxiIiIiMjjSElrMWNjYz35nbPG8X6VKlVi1KhRRpnw/dfnVnp7P29v71zXtObm/vLgU6dO0atXL6pXr06jRo1Yv349/v7+2Nra0r59e0JDQ0lOTjbWcN4fc9++fbl69SqpqamMHj2a9u3bW90rp2w1PDyc6OhoWrdunev5gjCZTDg5OeV6LqeM9+DBg4wYMYKXX37Z4pk9rDw4P/n1m5WVZXVNRkYGJpMJBwcHQkNDOXv2LLt27WLnzp2EhYURHh5OgwYNABg4cCD29vZkZGRQsWJFPv74Y2OsmZnW30eT1x8jREREREQeFyoPLmZKlixJamqqxbErV67kWr76+uuvW5UJe3t7k5CQYNV24sSJnDhx4nfF9vTTT/P8889z6NAh0tPT2bRpE1u2bMHPz8/YhCk6Ohq4V6J78OBB49rw8HBiY2Np0qQJd+7cyfM+ffv2pWzZssyaNes3x3r8+HG8vLzybPP888/Tu3dv3nvvvVyTvt/qwX5Lly5N1apV+f777y3apaSkcO7cOerUqUNMTAx79uyhWrVq9OrVi6VLl9KnTx+LRH3ZsmXExsby5ZdfEhYWxrPPPgtA/fr1OXTokFUc33//Pd7e3o9sXCIiIiIiRUFJazHj6upKtWrV2Lp1q3Hs/rLbB02bNo3w8HDjs7+/PxcuXLBYzxkVFcX+/fupVq3a74rtxo0bHD16lDp16rB9+3bc3d3ZtWsX8fHxxMfHM3XqVCIjIzGbzQwcOJCoqCh27NhhXH/u3DkSExNznU1+0Lhx41i/fj2JiYmFjvPHH39k69atvPLKK/m27devHzdv3iQyMrLQ9ylMv++88w4zZszg3LlzANy8eZNJkybRvn17KleuTFZWFnPnziUlJQWA9PR0Tpw4QZ06dfK916BBg4iKiuJf//oXcG9mPjQ0lDt37uRaNiwiIiIi8jhReXAR+u6772jYsKHxuVOnTkydOpXZs2czZcoUFi9eTEZGBrVq1eKDDz7ItY9KlSrx7rvv8v777wPg5OREeHg4M2bMIDw8HJPJRJUqVfjss8/yLRvOTc6aVhsbG+7evcurr75Ks2bNGDRoED179rRo27FjR+bNm8fOnTtp2bIlK1asYN68ecyePZuMjAxKlChBjx496NSpU773rVmzJl26dCE4OJjly5cD1mtaq1WrxsKFC4H/X4eaUxY8f/58Y6fdvDg4OBgJZefOnS36ul9ERAQlS5bMt7+H9duhQwdsbW0ZOXIk6enpZGVl0aFDBwYPHgxAt27duHr1Kj169DCS+g4dOhQo8a5WrRphYWHMmTOHadOmkZWVRaNGjYiIiMDR0bHAMYuIiIiIFEcms9lsLuogRKR4unv3LgkJCRw5n0n6o6uglmIiOSkZj7IeRR2GPCDAry5l3V1/8/UHDhygUaNGjzAiKS70bp9cerdPJr3Xwsn5vdPb29tq4kXlwSIiIiIiIlJsKWkVERERERGRYktrWkUkXy83ewY7e/uiDkMesRvXb1DSreBrteXP4eyonzUREZH7KWkVkXyVdnPRpk5PoF9OHcfrqUpFHYaIiIhInlQeLCIiIiIiIsWWklYREREREREptlQeLCL5Srl+Czv7jKIOQx6xUmUqknQ1rajD+I/k7GiPq4tK7kVERApCSauI5Gvbnp/0Pa1PIH1Pa9EJ8KurpFVERKSAVB4sIiIiIiIixZaSVhERERERESm2VB78B4qPjyckJITbt2/j6+vLpEmTANi9ezczZ87k7t27tGvXjlGjRllc9+GHH3Lw4EEyMjL45Zdf8PLyAiAwMBCTyURQUBAVK1a0uGbq1Kk899xzAPz000906tSJhQsX0rZtW44fP87YsWMBuHjxIi4uLri5ueHg4MC6devo3bs3w4YNw8fHBz8/P+zt7dm6davRd2ZmJs2bN+ell14iKCiIcePGsXfvXtzc3CxiiI6OxtbW1uLzg7F6eHgQFhYGQEREBMHBwWzfvp2yZcsabfz8/Fi5ciVVqlShVq1a1K5dGwCz2UxqaiotWrRg8uTJDB06lKeffpq///3vxrVr1qwhOjqa1atXW8SSlpbG3Llz+fbbb7G1taVkyZKMGzeOunXrGm0efG65xQPw6aef8sUXX7BixQpWr17NmjVr8PCwLLFcunSp1Tu6fPkys2bN4tixY9ja2lKxYkUmTZqEp6en0SY+Pp4hQ4YQFRWFt7e3cTwxMZEZM2Zw7do1srKyaNCgARMnTsTFxYVFixblGcOqVatYu3YtZrMZk8lEv3796NKlCyIiIiIijwMlrX+Qc+fOMXnyZNatW0eZMmXo06cPO3bswMfHhwkTJhAREUHFihUZNGgQO3bsoFWrVsa1kydPBuD8+fMEBgYSGxtrnIuOjsbPz4+goKCH3jsqKgp/f38iIyNp27YttWrVMvoYN24cTZo0oWvXrg+9/s6dOxw/fpxatWoBsGfPHkwmk0WbESNG5NlHjrxijY6OpnXr1kRFRTF48OCH9nH/+NPS0ujYsSO7du1i6tSpdO7cmU6dOlGnTh1+/fVXQkJCWLlypUXCmp2dzYABA/Dx8SEmJgY7Ozv27t3LgAED2Lx5M+7u7oD1c8tNeHg4sbGxrFy5kjJlygDQvXt3hg8fnudzuHXrFr179+bNN99k9uzZmEwmNmzYQL9+/YiLi8Pe3t54Jjkx3J+0jho1ihkzZtCwYUOys7P58MMPWbBgAePHj88zhh9++IF169YRGRmJk5MTV65coVu3btSuXdv4Y4CIiIiISHGm8uA/yLZt22jfvj0VKlTA3t6e+fPn89xzz/Hjjz9SrVo1PD09sbOzo1OnTmzZsuWR3TcjI4ONGzfyzjvvcOTIEX755ZdC9/HXv/7VYqb1yy+/fGgS91slJiZy/fp1BgwYwNq1a8nOzi7QdVevXuX27duUKlWK8uXLM3r0aCZNmkR2djbTpk1jwIABPP300xbX7Nu3j4sXLzJixAjs7O79naZp06bMnDnTuG9BntvKlSuJiYlhxYoVRsJaUJs3b6Z06dK8/vrrxh8AOnfuzOjRo0lPTwcgJSWFvXv3MmbMGOLi4khL+/9dXZOTk7lz5w4ANjY2DBs2jHbt2uV736SkJMxmM7dv3wagTJkyLFy40EjURURERESKO820/kHOnj2Lvb09gwcP5uLFi7z00ku88847XL582aIUtly5cvz666+F6js+Pp6AgADjc06ZL8COHTuoVKkS1atXp02bNkRGRjJmzJhC9e/v78+UKVMYMWIE6enpJCYm0rt3b/bv32+0WbhwIStWrDA+P//888YMcV6xjh8/nqZNmxqzmt7e3tjZ2bFz506L2eb7BQQEkJmZyZUrV/Dy8mLSpElGKfSrr75KXFwcY8aM4dq1awQGBlpdf/ToUWrXro2NjeXfaO6/X37P7Z///CefffYZ06dPp3Tp0hb9rFmzhq+++sr4XKVKFRYvXmzR5tixYxalyDn8/f2Nf2/YsAFfX1+qVKmCt7c3GzZsoGfPnsZzGzJkCOXKlcPHx4fWrVvz0ksv5RtDy5YtiY6OpkWLFjRo0AAfHx8CAgIoX7689YMWERERESmGlLT+QbKysvjuu++IiIjAxcWFIUOG8MUXX2BnZ2dRapuzzrAw8iq5jYqKomPHjgC0b9+e0aNHM3LkSBwcHArcf/ny5XF1deXkyZP88ssv+Pr6WrX5PeXBObOan332GQDt2rVjzZo1D01ac8qDw8PDjZLi+3300Uf4+fnx9ddf5/osbWxscHTM+6sl8ntu+/bt45NPPmHs2LE0a9aMSpUqGdcWpDzYxsYm33fwxRdfMGzYMCOGzz//3Ehau3btyl//+lf27NnD7t27GTduHJ06dWLixIl5xuDg4EBoaChnz55l165d7Ny5k7CwMMLDw2nQoEGe8YiIiIiIFAcqD/6DeHh40KxZM0qXLo2TkxNt2rThxx9/pEKFCiQlJRntkpKSKFeu3CO555UrV9i5cyefffYZfn5+TJo0iRs3brBt27ZC9+Xv78+WLVuIi4ujffv2jyS+HNu3byc1NZVhw4bh5+dHdHQ0O3bs4NKlS3le17dvX8qWLcusWbMsjleuXBnA2CjpQd7e3hw9ehSz2WxxfN68eezdu7dAz23OnDm0atWK7t27895775GVlVWoMXt7e5OQkGB1fOLEiZw4cYIjR47w008/MX36dPz8/Fi8eDEnTpzg0KFDnDlzhsWLF+Pq6srLL7/M5MmTWb16tTG7npeYmBj27NlDtWrV6NWrF0uXLqVPnz4W64RFRERERIozJa1/kL/85S/s2rWLGzdukJWVxc6dO6lbty7PPfccp0+f5uzZs2RlZbFp0yZatmz5SO4ZGxtL06ZN+Z//+R/i4+PZvn07gwcPZs2aNYXuKydpPXnyJHXq1Hkk8eWIjo5m5MiRxMfHEx8fz86dO2nUqFGBkrBx48axfv16EhMTC3y/xo0bU6ZMGUJCQoxkc+fOnURHR1OjRo0CPbecjZKGDRvG3bt3rcp/8+Pv78+FCxcsxhgVFcX+/fupVq0a0dHRvPbaa3zzzTfEx8ezY8cOAgICWLNmDaVLl2blypXs2bPHuPbYsWM8++yz+d43KyuLuXPnkpKSAkB6ejonTpx45O9UREREROSPovLgP8hzzz1H//796dmzJxkZGfj6+tKtWzdsbGwICgpi+PDh3L17l1atWlmsayyIB9eJAvTr148vvvjC6utzevXqxaeffsrJkyeNr84piPLly1OiRAmaNGmS6/kH17QCzJ07lxo1auTZb3JyMvv27WPGjBlW8U+ZMoWhQ4fmeX3NmjXp0qULwcHBLF++vAAjAZPJRGhoKDNnzqRjx47Y2dnh7u7OsmXL8PDwyPe53c/e3p7Zs2fzyiuv0KxZM8B6PSnA3//+d1588UXjs5OTE+Hh4cyYMYPw8HBMJhNVqlQxSqQ3bdrEypUrLfro27cvr7/+OuPHj2fZsmXMnj2bSZMmYW9vT/Xq1Zk3b57R9mExdOvWjatXr9KjRw9jTW+HDh145ZVXCvTsRERERESKmsn8YM2kiMi/3b17l4SEBI6czyQ9s6ijkUctOSkZj7Ie+TeURy7Ary5l3V3/kL4PHDhAo0aN/pC+pWjp3T659G6fTHqvhZPze6e3t7fVfjQqDxYREREREZFiS0mriIiIiIiIFFtKWkVERERERKTY0kZMIpKvl5s9g92/d1CWJ8eN6zco6VayqMP4j+TsqJ8nERGRglLSKiL5Ku3mYrUgXh5/v5w6jtdTlYo6DBEREZE8qTxYREREREREii0lrSIiIiIiIlJsqTxYRPKVcv0WdvYZRR2GPGKlylQk6WpaUYfxH8nZ0R5XF5Xci4iIFISSVhHJ17Y9P5GeWdRRyKOWnJSMR1mPog7jP1KAX10lrSIiIgWk8mAREREREREptpS0ioiIiIiISLGl8mApts6fP4+/vz9eXl6YTCYyMjIoV64cM2fOpEKFCgAMHz6cM2fOsHHjRuO6ffv2MXjwYKpWrQpAdnY2N2/eZMCAAfj7+9O3b18AkpOTAfDwuFceOXXqVAYMGMDGjRspX748AHfu3KFTp05MmDCBv/zlL8Y9evfuzaVLl3BxcSE7Oxt3d3eCgoKoVKkS+/btIyQkhIiICIuxBAYGEh8fT3R0NMHBwWzevNm49/3nX331VdLT07l+/Tq3bt2iYsWKAMyaNYv//u//NsY9btw4zp07x+eff47JZAIgOjqa/fv3ExQUBMDRo0eZP38+Z8+eBcDT05Px48dTo0aNR/WaRERERET+UEpapVgrV64csbGxxuegoCBmzZrFvHnzSElJ4ejRo5QtW5aDBw/y/PPPG+28vb0tksZjx47xyiuv0KlTJ6O/RYsWAfcSwBzdunXjo48+IiQkBIAFCxbQuHFji4Q1x7Rp0/Dx8QEgPDyc4OBgFixYUKBx3bx5k8mTJ7N48WKrc+vWrQOsE1DASFpz/PDDD6xcuZI+ffpY9XPmzBnefPNNgoODadWqFQBfffUVAwcOZMuWLTg4OBQoVhERERGRoqTyYHms+Pj4cOLECQA2btzICy+8wF//+lfWrFmT53UXLlzA2dk530Rt5MiRnDhxgq+//ppjx46xbds2Jk6cmG9caWlpxqxpQbRt25azZ89azBD/Fm+99RZLliwxZlLvFxYWRteuXY2EFaBNmzYMHDiQtDTtGCsiIiIijwfNtMpjIyMjg61bt9KgQQPg3kzku+++yzPPPMOCBQuYMGECpUqVAiAhIYGAgABu377N9evX8fHx4bPPPss3aXVycmL69OmMHz+eMmXK8NFHH+Hq6ppr20mTJuHi4kJqairXr1+3mNnNj729PTNnzmTw4ME0a9aswNc9qFq1agwePJgJEybw+eefW5w7dOgQ7777rtU13bt3/833ExERERH5s2mmVYq1y5cvExAQQEBAAJ07d8ZsNvPee+9x7NgxLl26xIsvvkjFihV59tlniYmJMa7z9vYmNjaWTZs20bRpU0qUKEH9+vULdM/GjRvTuHFjnnrqqTwTymnTphEbG0t8fDzTp0+nX79+pKWlYWNj/WNlNpuNdac56tWrR7du3Zg8eXIBn0buAgMDMZvNrFy50urc/ffs27cvAQEB+Pn58eWXX/6ue4qIiIiI/FmUtEqxlrOmNTY2lri4OIKDgylVqhRRUVGkp6fTtm1b/CT1+nAAACAASURBVPz8OH36dK4lwg4ODkybNo3t27cXKlGrVKkSlStXLnB7f39/srOzOX36NCVLluTGjRsW51NSUnBzc7O6btiwYZw9e5ZNmzYV+F4PsrGxYcaMGVZlwvXq1ePgwYPG5/DwcGJjY2nSpAl37tz5zfcTEREREfkzKWmVx056ejobN24kPDyc+Ph44uPj+frrr0lKSmLfvn1W7UuUKMHw4cOZNWvWH5asJSQkkJmZSfXq1alRowbXr1/nhx9+AO7tXrxu3bpcZ20dHByYOXMmS5cu/V33f+qppxg8eDBhYWHGsYEDBxIVFcWOHTuMY+fOnSMxMTHX2WARERERkeJIa1rlsRMfH0/lypV57rnnjGOurq68+uqrrFmzJtc1m6+++ioREREsX76cIUOGPJI4cta02trakpmZyZw5c4z1rx9//DEzZszgzp073Llzh6ZNmzJs2LBc+6lXrx59+vT53ZsyBQYGWuwu/NRTT7FixQrmzZvH7NmzycjIoESJEvTo0YNOnTr9rnuJiIiIiPxZTGaz2VzUQYhI8XT37l0SEhI4cj6T9MyijkYeteSkZDzKFnzXa3l0AvzqUtY9903efq8DBw7QqFGjP6RvKVp6t08uvdsnk95r4eT83unt7Y2jo6PFOdUIioiIiIiISLGlpFVERERERESKLa1pFZF8vdzsGezs7Ys6DHnEbly/QUm3kkUdxn8kZ0f9PImIiBSUklYRyVdpNxertQXy+Pvl1HG8nqpU1GGIiIiI5EnlwSIiIiIiIlJsKWkVERERERGRYkvlwSKSr5Trt7CzzyjqMOQRK1WmIklX04o6jP84zo72uLqo3F5ERKSglLSKSL627flJ39P6BNL3tBaNAL+6SlpFREQKQeXBIiIiIiIiUmwpaRUREREREZFiS+XBf5K0tDTmzp3Lt99+i62tLSVLlmTcuHHUrVuX8+fPExgYSHx8vMU1tWrV4vjx48bn+Ph4hgwZQlRUFN7e3sZxPz8/nJycsP/392impqbi7e1NUFAQLi4uVv3cLzw8nMjISGxtbbG1teW1116jV69eALz66qukp6dz/fp1bt26RcWKFQGYNWsWY8eOBeDixYu4uLjg5uaGg4MD69ats4oHoE6dOsycOdPi3r179+bSpUu4uLiQnZ2Nu7s7QUFBVKr0/1/B8bAxA8TFxREWFsbNmzfJyMigSZMmjB8/nhIlSliNc9WqVaxduxaz2YzJZKJfv3506dLFeH4rV66kSpUqFrENGzaMypUrW7ybjIwMRo4ciYODA3PmzGHSpEk0adKErl27PnRsWVlZuLq6MmLECF588UWr8zk8PDwICwsjPT2dmTNn8u2332IymShZsiR///vfqV+/PmD5/yIzM5N//OMfbNiwAZPJRFZWFn/7298YNGgQJpOJRYsWsWnTJmJjY3FycgJg3759hISEEBERkev/CRERERGR4kRJ658gOzubAQMG4OPjQ0xMDHZ2duzdu5cBAwawefPmAvcTHR2Nv78/kZGRVgncsmXLjKQrPT2dnj17EhMTQ8+ePR/a36JFi/j222+JiIjAw8ODlJQUhg4dyrVr13j77bdZt26dcd/9+/cTFBRkXBsbGwvAuHHjck3a7o8nL9OmTcPHxwe4l0AHBwezYMGCfMe8ceNGQkJCCA0NxcvLC7PZzOzZs5k4cSILFy60uMcPP/zAunXriIyMxMnJiStXrtCtWzdq165N7dq1840xR2ZmJu+++y7Ozs7MmjULW1vbAo/t8OHD9O/fn1WrVlGjRg2r8/cLDw8nOzubjRs3YjKZOHDgAEOHDmX79u0WfwgA+PDDD0lOTiYyMpKSJUuSlpbG22+/TYkSJYw/Ply4cIF58+YxYcKEAo9VRERERKS4UHnwn2Dfvn1cvHiRESNGYGd37+8ETZs2ZebMmWRnZxeoj5SUFPbu3cuYMWOIi4sjLe3hO36mpqaSmppKqVKlHtrm9u3bhIWFMWPGDDw87m3EUrp0aaZNm8ann37K7du3CzHCRyMtLc2IBfIec0hICBMmTMDLywsAk8nEqFGjqFevnlW/SUlJmM1mY0xlypRh4cKFuLu7Fzi2rKwsRo8ejYuLC7Nnz843YX1QvXr1aNeunfGHgLwkJyeTkZFBRsa93XobNWrEjBkzrP6vXLp0iQ0bNhAUFETJkiUBcHV15YMPPrB4jq+//jpffvkl3333XaFiFhEREREpDjTT+ic4evQotWvXxsbG8m8ErVq1AuD8+fNcvnyZgICAh/axYcMGfH19qVKlCt7e3mzYsMFiFnXgwIHY2tpy5coVKlSowBtvvEG7du0e2t+JEydwdna2mg2tUaMGDg4OnDp1irp16/6W4Rrx3D8rGBgYSLdu3azaTZo0CRcXF1JTU7l+/bpFyerDxnzt2jXOnDlD48aNLfqyt7dnwIABVvdo2bIl0dHRtGjRggYNGuDj40NAQADly5cv0FiysrIYO3Ys27ZtY/PmzVbvsaBq1qzJN998YzX2HP7+/gwZMoTAwEAGDRpEs2bNaNKkCc2aNeNvf/sbjo6Wu43++OOPeHl54ebmZnHcy8vLSOYBSpUqxZQpU5g4caIxQy4iIiIi8rhQ0vonsLGxsUo4HlSuXDmrhKJWrVrGv7/44guGDRsGQPv27fn8888tktacctytW7cSFBSEv78/JpPpoffLWf+Ym8zMzDyvLYjfUh68ZcsW+vXrx9dff42rq2u+Y86J8fz587z99tvAvdnZtWvXGutvARwcHAgNDeXs2bPs2rWLnTt3EhYWRnh4OA0aNMh1rGaz2UhOc9aejhw5kjFjxvDPf/7Tqky3IEwmk7Gu9MGx369KlSps2rSJw4cPs3v3bmJiYggPDycmJsaYUX3wGeQ8vyVLlpCdnY2DgwNRUVHGuTZt2hAXF8e8efNo3bp1oWMXERERESkqKg/+E3h7e3P06FHMZrPF8Xnz5rF37958rz9y5Ag//fQT06dPx8/Pj8WLF3PixAkOHTpk1bZt27a0aNEi3/WLNWrUICMjg1OnTlkcP3HiBNnZ2VSvXr0AI3u0/P39yc7O5vTp03mOuVSpUnh6enLw4EHgXpIXGxtLbGws9vb2Vsl4TEwMe/bsoVq1avTq1YulS5fSp08f448Ebm5upKamWlxz5coVI0EsV64cU6dOpX///jg4OFisuS2M48ePW8yAPsy8efO4fPky9evXZ/DgwURHR1OuXDn+9a9/WbTz9vbm5MmTRtm0v78/sbGxLFmyhKtXr1r1O2nSJL788ksOHDjwm+IXERERESkKSlr/BI0bN6ZMmTKEhIQYCdXOnTuJjo42NuXJS3R0NK+99hrffPMN8fHx7Nixg4CAANasWZNr+5EjR3LgwAGLUtQHOTs7M2TIECZOnMiVK1eAe4na+++/T//+/XF2di78QH+nhIQEMjMzqV69er5jfuedd5g2bRonT540rv/uu++4du2a1XrTrKws5s6dS0pKCnBvo6oTJ05Qp04d4N764qioKOOPCvv37+fWrVtGgmlvb4/JZMLGxobg4GDWrFnDnj17CjW2H3/8ka1bt/LKK6/k2/bXX39l8eLFpKenA/fW5KakpPDMM89YtKtUqRKdO3fm73//Ozdu3ADuzZJ/8803uZYwu7u7M2XKFEJDQwsVu4iIiIhIUVJ58J/AZDIRGhrKzJkz6dixI3Z2dri7u7Ns2TI8PDw4f/78Q69NT09n06ZNrFy50uJ43759ef311xk/frzVNWXKlGHAgAHMmjWL5s2bA9CwYUPjfKVKldi8eTMDBw6kRIkS9O3b1/gqmO7duxu7zv4eD65pdXZ2zjXJzlnXaWtrS2ZmJnPmzMHBwSHfMXfs2BEXFxcmTZrEzZs3SUtLw8vLi5CQEIvSYIBu3bpx9epVevToYSRzHTp0MBLIoUOHMn36dDp27IjJZMLNzY3Q0FBj06z7ValShfHjxzNmzBg2bNiQ5zPIGVtOWfD8+fMtSqYfXNMKEBERwfvvv09wcDD+/v44Oztjb2/P6NGjc52lnTJlCsuXLycwMJCsrCxu3ryJj48P//jHP3KNqU2bNrRt25bLly/nGbuIiIiISHFhMj9Ysyoi8m93794lISGBI+czSc8s6mjkUUtOSsajrEf+DeWRCvCrS1l31z+s/wMHDtCoUaM/rH8pOnq3Ty692yeT3mvh5Pze6e3tbbUfkMqDRUREREREpNhS0ioiIiIiIiLFlpJWERERERERKba0EZOI5OvlZs9g9xu+m1aKtxvXb1DSrWT+DeWRcnbUz5KIiEhhKGkVkXyVdnOxWhAvj79fTh3H66lKRR2GiIiISJ5UHiwiIiIiIiLFlpJWERERERERKbZUHiwi+Uq5fgs7+4yiDkMesVJlKpJ0Na2ow/iP4uxoj6uLSu1FREQKQ0mriORr256fSM8s6ijkUUtOSsajrEdRh/EfJcCvrpJWERGRQlJ5sIiIiIiIiBRbSlpFRERERESk2FJ58BPk/PnzBAYGEh8fb3G8Vq1aHD9+nH379jF48GCqVq1qcX7YsGG8/PLLAFy9epWWLVsyatQo3nzzTaPNuHHj2Lt3L25ubgDcvn2bUqVKMXPmTA4dOsTKlSsBOHnyJFWrVsXe3p7nn3+eyZMnW9zrzJkzBAcH8/PPP+Po6Ej16tUZO3Ysnp6eAPj5+eHk5IT9fd8Jen98AH/9619ZsGABzz77LAAjRozg+PHjbN26FYBbt27h6+vLnj17GDBgAMOGDcPHxwez2Ux4eDgxMTEA2NjY0L9/fzp06GDxnHJ8+OGHnDhxgk8++YSPPvrIYvw5oqOjiY2NJSgoiIoVKwKQlZVFeno6Y8eOpU2bNhbtzWYzixYtYtu2bZhMJhwcHBgxYgQtW7Y0YmjevDlhYWHGNSkpKbRo0YLBgwczfPhw43jXrl0pV64cS5cuNY4tWrQIwKJdXsdFRERERIo7Ja3/Yby9vYmIiHjo+Y0bN+Ln50dkZCT9+vXDZDIZ50aMGEHXrl2Nz9OnT2fRokV8/PHHdOvWDbiXdC5btowqVapY9Z2cnExgYCCjR4+mc+fOAMTGxtKjRw82bNhA6dKlAR56fY6mTZty8OBBnn32WbKyskhMTMTV1ZVz587h6enJoUOHaNCgAU5OThbXzZ8/n6NHj/L5559TokQJLl26xBtvvIG7uzsvvviiRdtp06Zx6tQp/vGPf+Ds7Jzr+O/n5+dHUFCQ8fmrr77igw8+sEpa4+LiOHLkCF988QV2dnacPn2aHj16sHnzZsqUKQPA6dOnuXbtGqVKlQLgv//7vylZsqRFP4mJiTg4OJCYmMjFixeNhFlERERE5Emj8mCxEB0dTc+ePXFwcGDv3r0PbZeenk5SUpLVzGNeVq9ezYsvvmgkrAABAQE0atSI1atXF7ifnKQV4IcffuDZZ5/F19eXnTt3AvDdd9/h6+trcc3NmzdZsWIF77//PiVKlACgQoUKzJs3j7Jly1q0DQoK4tSpU3zyySdGwlpYFy5cyPXZJCUlGTOxANWrV2fhwoXY2f3/349at27N119/bXzesmWLxUwz3HtPvr6+tG7dmrVr1/6mGEVEREREHgeaaX3CXL58mYCAgIeeT0hIsDofHh6Ou7s7iYmJJCcn07hxY9q1a0dkZCTNmjUz2i1cuJDw8HCuXbuGo6Mjbdq04e233y5wbIcPH6ZVq1ZWx1944QV27dplfB44cKBRHly9enU+/vhji/ZNmzZlzpw5AOzatYvmzZvj6enJypUr6dmzJ99++y0TJkywuObUqVPY2dlRrVo1i+P169e3+Dx79myWL1/OihUrrGZqFy5cyIoVK4zP95c/x8fHExAQQFpaGnfu3MHX15fQ0FCrsXbp0oW4uDiaNWtG48aN8fHx4W9/+5tFgtuuXTuWLl1Kt27dSE5OBrBIrDMyMti4cSMRERFcu3aNUaNG8fbbb1skviIiIiIiTwr9lvuEKVeuHLGxsRbHatWqZfw7r/Lg9evX4+/vj62tLe3btyc0NJTk5GQ8PO59JUZOeeypU6d48803adGiBa6urgWOzWQykZWVZXU8IyPDogw5v/Lg0qVL4+rqyqVLl9i1axcLFiygTJkyjB07lvT0dC5cuEDt2rUtrrGxscHBwSHfGH/++WeCg4OZMGECsbGxxqwsFKw8OC0tjYEDB/LUU09RvXp1q3Zubm6sWbOG48ePs3v3buLj4wkLC2P9+vXGut6GDRty+vRpUlNT2bJlC23btjWSV4BvvvmGsmXLUqNGDcxmMzY2Nmzfvt1qNlZERERE5Emg8mAB7pX7btq0iS1btuDn52dswhQdHW3V9umnn2b06NGMHTuW1NTUAt+jfv36HDp0yOr4999/j7e3d6Hibdq0KTt27ODWrVtUrFgRBwcHatWqxaZNm2jYsKFFEgzg5eXFnTt3+N///V+L45s3b7aYPV20aBFdunShYcOGVptIFYSrqyvBwcEsW7aM77//3ur88uXLSUxMpFatWvTr14+IiAiaN29ubCIF95L7v/zlL3z99dds3bqVtm3bWvQRFRXFxYsX8fPzo3Xr1qSlpbFmzZpCxyoiIiIi8jhQ0ioAbN++HXd3d3bt2kV8fDzx8fFMnTqVyMhIzGazVfuOHTtSuXLlXEtgH6Znz54cOHDAYiY4JiaGgwcP0qNHj0LF26xZM1auXEnTpk2NY76+vixfvpzmzZtbtXdycqJXr15MmTKFtLQ04N5uy/PmzcPLy8tolzMbO3nyZA4ePEhUVFSh4gLw9PTkjTfeYPr06VbPLjU1lY8//pibN28CkJaWxrlz54ydkHO0a9eOf/7znzg4OBgbVMG9zax2797Npk2bjPcUExPD3r17OXfuXKFjFREREREp7lQe/B8mtzWtHTp04MCBA/Ts2dPieMeOHZk3b56xwdGDxo4dS9++fenZs6dR2poXd3d3Vq1axaxZs1iyZAlms5maNWuyevVqi8SsIF544QXOnDnDmDFjjGO+vr7MnDnTaifgHKNGjWLx4sW89tpr2NnZYWtry3vvvZdrkluyZElmzpzJ22+/zfPPPw9Yr2kFmDt3bq73GjRoEOvXr2fjxo0WG08NHTqU+fPn07lzZxwdHbGxsaFXr15WG0c1aNCApKQkXn31VYvjsbGxtGrVivLlyxvHPD09jR2fHR0d+eSTT/jss8+M8x9++CFArsfvj01EREREpDgymXObRhMRAe7evUtCQgJHzmeSnlnU0cijlpyUjEdZj6IO4z9KgF9dyroXfC+A3+LAgQM0atToD72HFA292yeX3u2TSe+1cHJ+7/T29sbR0dHinMqDRUREREREpNhS0ioiIiIiIiLFlpJWERERERERKba0EZOI5OvlZs9gZ29f1GHII3bj+g1KupUs6jD+ozg76udIRESksJS0iki+Sru5WC2Il8ffL6eO4/VUpaIOQ0RERCRPKg8WERERERGRYktJq4iIiIiIiBRbKg8WkXylXL+FnX1GUYchj1ipMhVJuppW1GE80Zwd7XF1UWm9iIjI76GkVUTytW3PT6RnFnUU8qglJyXjUdajqMN4ogX41VXSKiIi8jupPFhERERERESKLSWtIiIiIiIiUmypPBg4f/48/v7+eHl5AZCdnc3Nmzfp0qULI0aMsDqf47XXXqNXr174+fnh5OSEvb09GRkZlC9fnvfeew9vb2+re93fFiA1NRVvb2+CgoJwcXGxOg9Qp04d+vbty9ixYwG4ePEiLi4uuLm54eDgwLp16/LtFyA8PJzIyEhsbW2xtbU14gcwm80sWrSIbdu2YTKZcHBwYMSIEbRs2RKAWrVqUbt2bUwmE1lZWfzXf/0XH374IbVq1QJg586dLFy4kLS0NGxsbPD19WXUqFE4Ozvz4YcfcvDgQTIyMvjll1+M5xgYGEi3bt0sns8333zD0qVLuXXrFtnZ2bRp04YRI0ZgY2PDuHHjaNKkCV27djXaL1q0CIDhw4cbx7p27Uq5cuVYunSpcSw6OpqgoCAqVqwIQFZWFunp6YwdO5Y2bdrk2k+OM2fOEBwczM8//4yjoyPVq1dn7NixeHp6EhUVxcqVKwE4efIkVatWxd7enueffx7goeM2mUwW8eSYOnUqzz33nPF53759DB48mKpVq2I2m8nIyKB79+706dPH4rrcxgyQkpLC3Llz2b9/P3Z2djg5OTFs2DBat25tNU4RERERkeJISeu/lStXjtjYWOPzr7/+Stu2benQoQOOjo5W5x+0bNkyqlSpAtxLvN566y3i4uIoXbp0nm3T09Pp2bMnMTEx9OzZ0+r8/XLun1vyll+/ixYt4ttvvyUiIgIPDw9SUlIYOnQo165d4+233yYuLo4jR47wxRdfYGdnx+nTp+nRowebN2+mTJkyFvcHiIiI4IMPPiAyMpI9e/YwefJkFi1aRN26dUlPTycoKIihQ4fy2WefMXnyZODeHwcCAwMf+hz/53/+h6lTpxIWFkb16tW5c+cO77zzDgsXLuSdd9556LO/X2JiIg4ODiQmJnLx4kWLpNDPz4+goCDj81dffcUHH3xAmzZtHtpfcnIygYGBjB49ms6dOxvPoUePHmzYsIFu3boZibefn1+u7y63cUdHR1vF8zDe3t5EREQAkJaWRocOHfD19aVGjRp5jjk9PZ0+ffrQtm1btmzZgq2tLadOneKtt96icuXK1K5dO997i4iIiIgUNZUHP0RSUhJms5n/+q//KvS1L730EvXr12fTpk35tk1NTSU1NZVSpUr9ljAL1O/t27cJCwtjxowZeHjc23SldOnSTJs2jU8//ZTbt2+TlJRkzD4CVK9enYULF2Jnl/vfNXx8fPjpp58ACA0NZdiwYdStWxcABwcHxo8fz88//8yBAwcKHPPSpUsZMmQI1atXB8DJyYkpU6bQpEmTAvcRHR2Nr68vrVu3Zu3atXm2vXDhAm5ubnm2Wb16NS+++KKRsAIEBATQqFEjVq9eXeC4HpW7d+9ia2tLiRIljGMPG/PWrVtxdHRk2LBh2NraAvD0008zZcoUsrKy/vTYRURERER+C820/tvly5cJCAjg7t27XL16lXr16hESEkKFChU4f/68cf5+s2bNMspjH1SzZk1OnTqV67mBAwdia2vLlStXqFChAm+88Qbt2rWzOH9/eXBuZbSF6ffw4cM4OztbzQDWqFEDBwcHTp06RZcuXYiLi6NZs2Y0btwYHx8f/va3v+Wa1JnNZjZv3kzDhg0BOHz4sDGbmsPe3p6GDRty+PBhGjdunG/sAMeOHWPixIkWxypUqECFChWMzwsXLmTFihXG5+TkZLp37w5ARkYGGzduJCIigmvXrjFq1CjefvttI/GOj48nICCAtLQ07ty5g6+vL6GhoXnGdPjwYVq1amV1/IUXXmDXrl0FGtfD5MSTI6fU+0EJCQkEBASQnZ3NL7/8Qrt27ShXrhyQ95h/+OEHXnjhBav+chuPiIiIiEhxpaT133LKf7OzswkKCuLkyZP4+vpanS8ok8mEk5NTrudySki3bt1KUFAQ/v7+mEwmq/OF9bB+c9ah5iYzMxOTyYSbmxtr1qzh+PHj7N69m/j4eMLCwli/fj2enp4ARoKVnp6Ol5cXU6dONcaamWn9fSjp6ekW48qPyWTC0THvr4YYMWJErmta4V5ZdtmyZalRowZmsxkbGxu2b9/Oyy+/DPx/eXBaWhoDBw7kqaeeMmZ184opt2eXkZFRqLHl5reWB/fv359ly5YxaNCgfMd8vzlz5rBz507u3LlDixYtmDRp0u+KX0RERETkz6Dy4AfY2NgwduxYfv31V8LCwn5zP8ePH7fauOlBbdu2pUWLFkyYMOE336cg/daoUYOMjAyrmd8TJ06QnZ1N9erVWb58OYmJidSqVYt+/foRERFB8+bN2bp1q9E+NjaW2NhY4uLiCAkJMRLr+vXrc+jQIYu+09PTOXr0aK6bUT2Mt7c3CQkJFsdOnz5tbECVn6ioKC5evIifnx+tW7cmLS2NNWvWWLVzdXUlODiYZcuW8f333+fZZ25jA/j+++8LNbZHxdXVlXbt2nHw4EEg7zF7e3tbjG/06NHExsYyaNAg0tLS/vTYRURERER+CyWtubCzs2Ps2LGEhoaSlJRU6Ovj4+M5duyYRcnvw4wcOZIDBw7wzTff/IZIC9avs7MzQ4YMYeLEiVy5cgWAK1eu8P7779O/f3+cnZ1JTU3l448/5ubNm8C9Gb1z587x7LPP5nuv4cOHs2TJEo4cOQLcm4WcNm0aTz/9NI0aNSpwzP379yckJIQzZ84AcPPmzVx32M1NcnIyu3fvZtOmTcTHxxMfH09MTAx79+7l3LlzVu09PT154403mD59Omaz+aH99uzZkwMHDljMssfExHDw4EF69OhR4LE9KllZWezfv586derkO+b27dtz+/ZtlixZQkZGBnBvrfO+ffuwsdGPvoiIiIg8HlQe/BAtW7akYcOGLFiwgMGDB+e6pvWFF14wSizvX4fq7u5OWFgYrq6u+d6nTJkyDBgwgFmzZtG8eXOrvgCcnZ1znTEsTL8DBw6kRIkS9O3bF7PZjMlkonv37sZX3gwdOpT58+fTuXNnHB0dsbGxoVevXhYl0g/TuHFjgoODmT59OtevXyczM5OWLVsSGhpaqBLali1bMmrUKEaNGkVWVhaZmZn4+/szbNiwfK+NjY2lVatWlC9f3jjm6emJn58fkZGRPP3001bXDBo0iPXr17Nx40YAPvnkEz777DPj/Icffkjnzp1ZtWoVs2bNYsmSJZjNZmrWrMnq1atz3Rm6MB5c0wrQr18/unTpYnEsZ01rThl2rVq1GDBgAKtXr85zzKNHj2blypV8/PHHRp9ZWVm0bduW/v37/67YRURERET+LCZzXtNMIvIf7e7duyQkJHDkfCbp1suW5TGXnJSMR1mPog7jiRbgV5ey7vn/GSHXxQAAIABJREFUAfNROnDgQKGqXOTxoXf75NK7fTLpvRZOzu+d3t7eVvvcqEZQREREREREii0lrSIiIiIiIlJsaU2riOTr5WbPYHffOmt5Mty4foOSbiWLOownmrOjfm5ERER+LyWtIpKv0m4u+X6Hrjx+fjl1HK+nKhV1GCIiIiJ5UnmwiIiIiIiIFFtKWkVERERERKTYUnmwiOQr5fot7OwzijoMecRKlalI0tW0og7jieDsaI+ri0roRURE/ghKWkUkX9v2/KTvaX0C6XtaH50Av7pKWkVERP4gKg8WERERERGRYktJq4iIiIiIiBRbKg9+AkRHR7N//36CgoIYN24cTZo0oWvXrsb5RYsWATB8+HB69+7N0aNH2bNnDw4ODkabgIAASpYsSUREBOPGjWPv3r24ubmRnZ2Nk5MTH330EbVr1wbg5s2bzJkzh127duHs7IyrqyvDhw+nWbNmVrH17t2bS5cu4eLiQnZ2Nu7u7gQFBVGp0v9/zUZ8fDxDhgwhKioKb29vi+vj4uIICwvj5s2bZGRk0KRJE8aPH0+JEiWs7rVq1SrWrl2L2WzGZDLRr18/unTpQlRUFCtXrgTg5MmTVK1aFXt7e55//nneeust/P398fLyAiA7O5ubN2/SpUsXRowYYfT9008/0alTJxYuXMj/tXfn8Tmd+f/HX5HcsYVYaiuZtqhaYg8Ra5siSMi3lkENukwUE9s8xpLKCFP7WkSozqhBp5ZvQsTallIqqLViaQ21BCUkQiJy30nO74/8cr5uiYTOkEjfz8ejj8ec6zrnOp9zrlsmn1zL7ePjA8C7775Lv379aN++PQAzZsxg9erVHDhwwHy3rVu3ZvXq1QwYMIBixYphsVhIS0vjlVdeYcqUKbi6uhIREcH06dOpUqWK3fP87W9/o3z58rnGFxsb+8j6oUOH0rNnT3r27Mkf/vAHs905c+Zw8eJFFixYkO0dioiIiIgUNEpaf4NcXFzYu3cv3t7eAJw/f54bN25QunRp85zhw4ebie/XX39NcHAw//u//4thGAwePJg6deqwefNmnJ2dOXXqFIMGDWLOnDl4enpmu9/kyZPN8uXLlzNjxgzmz59v1kdERNCpUyfWrFljl7RGRUURGhpKWFgYNWrUwDAMZs2axfjx47MlXMePH2fdunWsWbOGYsWKcevWLXr06EHt2rXp0aMHPXr0AMDb25ulS5dSrVo1AGJjY6lYsSKRkZFmW9evX8fHxwdfX18zGQwPDzdjzEpaW7RoweHDh82kdd++fTRq1IjDhw/j5eXFxYsXKVGihHmvB+87ZcoUPvnkE8aMGWPGNX369GzvLq/4ihYtmmv9tGnTeOedd2jfvj2VK1fmzJkzREZGsmHDhmz3EhEREREpiDQ9+DeoY8eObN++3TzesmWLmYjl5O7du7zwQuZmLQcPHuTq1asEBQWZo4l169ZlyJAhhIWF5XnvpKQksy2A+Ph49u/fz+jRo9m6dStJSf+3k2loaCgffvihmTg6ODgwatQo6tevn63duLg4DMMgJSUFgPLly7NgwQLKli2bZ0yPaqtkyZIA2Gw2oqKiGDlyJCdPnuTSpUsAeHl5cfToUSAzUXR2dsbHx4e9e/cCcOjQIVq1apWt/azR0Affw38SX271derUoW/fvkyePJmMjAyCg4OZMGEC5cqV+1X3FhERERF51jTS+hvUtm1bJkyYgM1mw2KxsGvXLoYNG8a5c+fMcxYsWMA///lPUlJSuHr1KosXLwbgxIkTuLu74+DgYNdms2bNmDNnTo73Cw4OpkSJEty9e5fExERWrlxp1m3cuJFWrVpRrVo13N3d2bhxI2+//Ta3b9/mwoULeHh42LVlsVgICAjI8ZkiIiJo06YNjRo1wtPTE39/fypVqpTn+7hx4wb+/v6kpqaSkJBA/fr1CQ0NpXLlygDs3r2bF198kVdeeYX27duzZs0aRo8eTb169bh06RKpqans3buXVq1a0apVKwIDAxk9ejSHDh3izTffNO8zaNAgLBYLt27dwtHRkcDAQLNu586d+Pv7m8fOzs6sW7cuz/hiY2PzjH/o0KF0796d0aNHU6NGDXNkWERERETkeaCR1kLm4WQSMNd4ZnF2dqZp06bs27ePn376CTc3N4oVK2Z3zfDhw4mMjOTLL79kxYoVjBgxgsuXL+Pg4EB6enq2e9hsthzvDZnTgyMjI9m5cydTpkzh3XffNUdU169fj5+fHwBdunRh9erVOT5PbGws/v7++Pv706ZNG65du2Z3nrOzM2FhYWzevJnOnTtz8uRJunXrxrFjx/J6Zeb02i1btuDv749hGHYjpOHh4XYxRkREYLVacXR0pGHDhpw4cYK9e/fSunVr3NzcuH//PomJiRw9epQWLVqY7SxdupTIyEj27t3LwIEDef/99zEMA8icHhwZGWn+l5WwPk58edU7OzszYcIEdu/eTXBwcJ7vQ0RERESkIFHS+pw6dOgQ169fBzKTUkdHRwBcXV25c+eO3bm3bt3C1dXVrqxTp05s376drVu30qVLl1zv1aRJE373u99x8uRJGjZsSExMDDabze6cY8eOZdtEKSedOnUiIyODn3/+mZMnT/LTTz8xZcoUvL29WbRoEWfPnuXYsWOUKVMGNzc3jhw5AkC1atXMhM5isWRLnDds2EB0dDQvvfQS/fr1Y8mSJQwcONBurWdeihQpwpgxY7h+/Tr/+Mc/gMx3t2fPHpYtW4a3tzfBwcHcuXOHr776Cshc13rkyBF++OEHGjVqBGROG96xYwdly5bFxcUlx3v16tWL8+fPk5CQ8B/F97j1L774IqVLl85xAysRERERkYJMSetzKjw8nK+//hqAH3/8ETc3NyAzYdqyZQv37t0DMtc37tq1y27EDzKn0x44cIBvv/2Wtm3b5nqvK1euEBsbS+3atfHw8KBmzZpMnTrVTFxjYmJYvHgxQ4cOzTPumJgYc/fciIgIfv/737Nr1y527tzJ7t278ff3N0dbR44cyeTJk+2mLR86dIjbt2+bSXqW9PR05syZQ3x8PABWq5WzZ89St27dPGN6kJOTE2PGjCEsLIy4uDgiIyNp0aIF3377LTt37uSbb75h8ODBZoxeXl5ERkZSq1YtnJwyZ9u3atWKzz77LMf1rFmio6OpUqXKE68tfTi+J60XEREREXneaE3rc2rQoEGMGTOGVatWUblyZT7++GMA2rVrx5kzZ/j973+Pg4MDRYoUYfTo0bz66qt21zs7O9OkSRMAihYtmq39rDWtjo6OpKamMnbsWF5++WUgc4OkefPm4efnh6OjI66ursyaNSvHnYPh/9a0Ojo6kpaWxuzZs3F2dmbTpk3mV9Fkeeedd+jduzdBQUH4+flRokQJgoODSU5OJikpiRo1ahAaGprt62F69OhBQkICffv2pUiRzL/F+Pr60rNnzyd+t23btqVx48bMnz+f48ePM2rUKLv6fv368fe//51z585Rq1Ytbt++zdtvv23Wt2jRgpEjR9KyZUu767LWtBYpUgRHR0fmzp1r1j28phUyv1Ln4TW9D8c3ePDgXOsnT578xM8vIiIiIlKQOBhZi+pERB6SmppKTEwMJ2PTsKbldzTy33Yz7iYvVPh1u1iLPX/velQom/NygGft8OHDNG3aNL/DkKdAfVt4qW8LJ/Xrk8n6vdPd3T3boJqmB4uIiIiIiEiBpaRVRERERERECiwlrSIiIiIiIlJgaSMmEclTB69aOFks+R2G/JfdSbxDadfS+R1GoVC8qP59iIiIPC1KWkUkT+VcS+S4y7Q83y6d/5EaL7+Y32GIiIiI5ErTg0VERERERKTAUtIqIiIiIiIiBZamB4tInuIT7+FkseV3GPJfVqZ8FeISkvI7jOdC8aIWXEpoiryIiEh+UNIqInn6KvonrGn5HYX8t92Mu8kLFV7I7zCeC/7e9ZS0ioiI5BNNDxYREREREZECS0mriIiIiIiIFFhPLWlNSkpi0qRJ+Pn54e/vT//+/Tl58qRZn5yczKRJk+jQoQPdunXj7bffJjo62qzv378/Bw4cyLHtPXv20KtXLzp37oyvry9Tp04lJSUFgNjYWLy9vbNd89prrwFw4MABGjdujL+/P/7+/nTt2hVvb2+++OKLHO917949ZsyYQceOHenSpQu+vr6sW7fuseIEGDZsGF27ds1W/vnnn+Pv70+3bt3w9/dnw4YNZt2ZM2cYMGAA3bp1w9fXl/Hjx3Pv3r1s7yDrGRo3bkyHDh3w9/fnT3/60yOf/WEPx75161Z69uxJ586dad++PR9++CF3794131v//v3trn/wXffq1Qt/f39ef/11mjdvbsb2448/2l3j7e1NbGzsI+Ow2WzMmzePjh070rVrV3r27MmWLVvMc8eNG0dERES2Z1m4cCGtWrUy36mfnx+rVq3Ksf7B/65du/ZEn4m83kOWlStX4u7uTlxcnF35a6+9Zvf5efj5Af71r3/RrVs3unTpQocOHZg+fTpWqzXb/SMiIvD09OTmzZuPjCU+Pp7x48fToUMHOnfuzFtvvcWOHTuyPZeIiIiISEH1VNa0ZmRkEBAQgKenJxs2bMDJyYn9+/cTEBDA5s2bKVOmDIMHD6ZOnTps3rwZZ2dnTp06xaBBg5gzZw6enp6PbDs6OpqQkBAWLlxIvXr1sFqtTJ8+naFDh7Js2bLHis/d3Z2VK1eax6dPn6Znz5507doVFxcXu3OHDRtG1apViYqKomjRoty4cYP333+fChUq8Prrr+d6n/j4eE6dOkWFChU4cuQITZo0AeD48eOsW7eONWvWUKxYMW7dukWPHj2oXbs2tWvXZtSoUUydOpXGjRuTkZHBpEmTmD9/PkFBQWbbbdq0oU2bNkBm0hMYGJjre8tLVFQUoaGhhIWFUaNGDQzDYNasWYwfP54FCxbkeX1WIhYREcHBgweZPn36r4rjr3/9K6mpqURERODi4sLly5cJCAjAarXyP//zP7le26dPH4YNGwZkvvuBAwdStGhRevXqla3+QZcuXXqiz8TjiIiI4M033yQ8PJzBgwfb1c2ZM4fWrVtTpUqVbNctWbKEb775hk8//ZRKlSphtVoJCgpi3rx5jB07Ntv5ycnJhISEsGjRomx1VquVgQMH4uPjw7Zt23B0dOT8+fO8//77VK1aldq1az/xc4mIiIiIPGtPZaT1wIEDXLt2jeHDh+PklJkXt2jRgmnTppGRkcHBgwe5evUqQUFBODs7A1C3bl2GDBlCWFhYrm2HhYURGBhIvXr1AHB2diYoKIh///vfHD58+FfFe+XKFYoXL27GkuXIkSOcPXuWv/71rxQtmrkBR8WKFfnb3/5mHucmKiqKZs2a0bFjR1avXm2Wx8XFYRiGOTpcvnx5FixYQNmyZQG4efMm9+/fB6BIkSIEBgbSuXPnX/Vsjys0NJQPP/yQGjVqAODg4MCoUaOoX7/+U73vgy5fvsz27duZMmWKmSi6ubkRFBREaGjoE7VVrlw5hgwZwr/+9a9fFcujPhOP48yZMyQmJhIQEMDatWvJyMiwqx84cCDBwcHZrktNTeXTTz9lypQpVKpUCcj8fI8fP56XX345x3v5+Phw8eJFoqKistVt376dokWLEhgYiKOjIwDVq1dn4sSJpKenP/FziYiIiIjkh6cy0nrq1Clq165NkSL2OXG7du0AWL9+Pe7u7jg4ONjVN2vWjDlz5uTa9okTJwgJCbErs1gsNG7cmBMnTlC5cuU844uJicHf35+UlBQSExPx9PRk2bJl2RKU48eP06hRIywWi11548aN87wHZI62/fnPf6ZWrVrMnz+fDz/8kDJlytC2bVsiIiJo06YNjRo1wtPTE39/fzNRCQoKYsiQIVSsWBFPT0/efPPNPEd1/xO3b9/mwoULeHh42JVbLBYCAgLM46z3lsVm+3VfgTJo0CC7d3rp0iWz/Ro1alCiRAm78z08PLh8+TK3b99+ovvUqlWL8+fPm8erV6/m66+/No+rVatmjlA+7mfiwXOzPPwewsPD6dSpE+7u7jg5ObFnzx7zsw8QEBDAV199xbp168xRYIB///vfODk5UbNmTbv2ypUrR+/evXN8RovFwrRp0xg8eDBeXl52dcePH6dZs2bZrnkwFhERERGRgu6pJK1FihTJdSTSwcEhx5Eem82WLZHN6dq0tOzfvWG1WnFwcMiWKAMYhmHXbtZUUKvVyujRo3FxcaFBgwa53hdgxYoVhIeHY7PZqF69eq6jf6dPn+aXX36hZcuWWCwW6tSpw4YNG3jnnXdwdnYmLCyMixcvsnfvXvbs2cM//vEPli9fTqNGjejevTsdO3YkOjqaffv2MW7cOLp27cr48ePzjPE/kfWOYmNjzbWx8fHxrF27Fsg+rTo2NpYBAwY88X2WLl1KtWrVzOOsNZqP+lxk9Xden42HOTg4UKxYMfP4UdOD4ck+E7m9B5vNRlRUlDlVvXPnzqxevdouUXRycmL69OkMGDCA1q1bZ4s5y5EjR5g0aRKQOfr+3Xff5RhP/fr16dGjByEhIXZTyB82e/Zs9uzZw/3792nTpk2Oo70iIiIiIgXNU5ke7O7uzqlTpzAMw6587ty57N+/n4YNGxITE5NthOrYsWO4u7vn2naDBg04duyYXZnVauXUqVO4u7tTunRpc/OgLLdu3cLV1TVbW87OzkyePJlvvvnGbrOfLPXr1+eHH34wE6kBAwYQGRlJSEgIiYmJucYZHh6O1WrFx8cHb29vfv75Z3OK8IYNG4iOjuall16iX79+LFmyhIEDBxIZGcmFCxdYtGgRLi4udOjQgZCQEL744otsm/c8yvXr180NhR4cJc1NmTJlcHNz48iRI0DmCGRkZCSRkZFYLJZnNpW0QYMGXLhwIdu7PXr0KG5ubjn2YW5+/PFHc7rz48rrM5GXb775hrt37xIYGIi3tzcRERHs3r2bX375xe68WrVqZZsmXL16daxWKz///DMATZo0Mfvhwc2WchIYGMjFixfZtGmTWebu7s7Ro0fN47/85S9ERkbywQcfkJSU9MTPJiIiIiKSH55K0urh4UH58uUJDQ01E549e/YQERFBzZo18fDwoGbNmkydOtVMXGNiYli8eDFDhw7Nte1hw4axePFicydim83G5MmTqV69Ok2bNsXFxYWXXnqJ7du3m9esWbMm29TJLKVKlWLYsGHMnDnTXEeapWnTptSsWZOPPvrIrLt//z579uzJcUQ3i9VqJSoqiuXLl7Nz50527tzJjh07iIuL48CBA6SnpzNnzhzi4+PN88+ePUvdunUpV64cK1assNtJ+fTp09SpUyfX95KlUqVKZqLz6aefPtY1ACNHjmTy5MmcO3fOLDt06BC3b98210M+bS+++KI5opycnAxkTh2eNm0agYGBT9TWjRs3WLJkCf369XviOHL7TOQlIiKCESNGmP2+Z88emjZtmuMfHQICAkhISDATy+LFizN48GCCgoK4fv06kLmp2Y4dO3L9vEFmsj1t2jSWLFlilnXp0oWUlBQWL15s/ju7e/cuBw4cyLM9EREREZGC4qlMD3ZwcCAsLIxp06bh5+eHk5MTZcuWZenSpbzwwgtA5sY/8+bNw8/PD0dHR1xdXZk1a5bdDrgBAQF2CdPmzZvx8PBgxowZTJkyhcTERNLS0mjbti1hYWHm1MpZs2YxceJEFi1ahM1m47XXXmPChAmPjLdXr16sXLmSzz77jCFDhtg9x6JFiwgLCzPXHt6/f5927doxa9asR8YZEhJC1apVadiwoVnm4uJCr169WL16NfPmzSMhIYG+ffuayYOvry89e/bEwcGBpUuXMmvWLIKDg7FYLLzyyivMnTv3V/VFlgfX4b744ots3rzZrt7Pz48SJUoQHBxMcnIySUlJ1KhRg9DQUKpUqWKuO33aQkJC+OSTT+jZsyeOjo44OzszYsQIunTpYnfORx99ZB5nJedZa1YdHBwwDIPevXvj6+trnvfwmlaAsWPH5piUP+ozkZubN29y4MABpk6dalf+7rvvMnHixGx/kMmaJty9e3ezbNCgQZQvX56hQ4eSlpbG3bt3cXd3N6do56Z+/foMHDjQ3JTJ2dmZFStW8PHHH5s7L6enp+Pj48Mf//jHx3omEREREZH85mA8PIdXROT/S01NJSYmhpOxaVizLyWX59zNuJu8UOGF/A7jueDvXY8KZZ/866/yw+HDh2natGl+hyFPgfq28FLfFk7q1yeT9Xunu7t7tv2RNEdQRERERERECiwlrSIiIiIiIlJgPZU1rSJSuHTwqoXTQ99XLM+/O4l3KO1aOr/DeC4UL6rPv4iISH5R0ioij5S15N2luBPOzvqlvbC5dP4a1aqUz+8wnhupqan5HcJje55ilSejvi281LeFk/r18VmtVoBsX5sK2ohJRHJx9+5dfvrpp/wOQ0RERER+I2rVqkWpUqXsypS0isgjZWRkkJycjMViMb9SSkRERETkv80wDGw2GyVLljS/FjSLklYREREREREpsLR7sIiIiIiIiBRYSlpFRERERESkwFLSKiIiIiIiIgWWklYREREREREpsJS0ioiIiIiISIGlpFVEREREREQKLCWtIiIiIiIiUmApaRWRR4qKiqJLly507NiRzz//PL/DkVwkJSXh5+dHbGwsAPv27aNr16507NiRefPmmeedPn2a7t274+Pjw/jx40lLSwPg6tWr9OvXj06dOjFkyBCSk5MBuHPnDoMGDaJz587069ePuLi4Z/9wv1GhoaH4+vri6+vLzJkzAfVrYTF//ny6dOmCr68vn332GaC+LWxmzJjBuHHjAPVtYdC/f398fX3x9/fH39+f48ePq1+fNUNEJAe//PKL8cYbbxgJCQlGcnKy0bVrV+Ps2bP5HZbk4NixY4afn59Rr1494/Lly0ZKSorRrl0749KlS4bNZjPee+89Y9euXYZhGIavr69x9OhRwzAMIygoyPj8888NwzCMQYMGGZs2bTIMwzBCQ0ONmTNnGoZhGJMmTTI++eQTwzAMY/369caIESOe9eP9Jn333XdG7969jdTUVMNqtRoDBgwwoqKi1K+FwIEDB4w+ffoYNpvNSElJMd544w3j9OnT6ttCZN++fYanp6cxduxY/TwuBDIyMozWrVsbNpvNLFO/PnsaaRWRHO3bt48WLVpQpkwZSpQogY+PD9u2bcvvsCQHa9euJSQkhIoVKwLwww8/8NJLL+Hm5oaTkxNdu3Zl27ZtXLlyhfv379OoUSMAunfvzrZt27DZbHz//ff4+PjYlQPs2rWLrl27AuDn58e3336LzWbLh6f8balQoQLjxo3D2dkZi8VCjRo1uHDhgvq1EGjevDkrVqzAycmJW7dukZ6ezp07d9S3hcTt27eZN28egwcPBvTzuDA4f/48AO+99x7dunVj1apV6td8oKRVRHJ048YNKlSoYB5XrFiR69ev52NE8ihTpkzBw8PDPH5U3z1cXqFCBa5fv05CQgIuLi44OTnZlT/clpOTEy4uLsTHxz+Lx/pNe/XVV81fei5cuMDWrVtxcHBQvxYSFouFBQsW4Ovri5eXl/7NFiITJkxg1KhRlC5dGtDP48Lgzp07eHl5sWjRIpYvX87q1au5evWq+vUZU9IqIjnKyMjAwcHBPDYMw+5YCq5H9d2jynPq20f1tWEYFCmi/+t4Vs6ePct7773HmDFjcHNzU78WIsOHDyc6Oppr165x4cIF9W0hsG7dOqpUqYKXl5dZpp/Hz7/GjRszc+ZMSpUqRbly5ejZsycLFixQvz5jTvkdgIgUTJUrV+bQoUPmcVxcnDn9VAq2ypUr223kkNV3D5ffvHmTihUrUq5cOe7evUt6ejqOjo52fV2xYkVu3rxJ5cqVSUtLIzk5mTJlyjzzZ/otOnz4MMOHD+fDDz/E19eXgwcPql8LgXPnzmG1WqlTpw7FixenY8eObNu2DUdHR/Mc9e3zacuWLcTFxeHv709iYiL37t3jypUr6tvn3KFDh7DZbOYfIwzDoGrVqvp5/IwpjReRHLVs2ZLo6Gji4+NJSUnhyy+/pG3btvkdljyGhg0b8vPPP3Px4kXS09PZtGkTbdu2pWrVqhQtWpTDhw8DEBkZSdu2bbFYLHh4eLBlyxYANmzYYPZ1u3bt2LBhA5D5C5mHhwcWiyV/Huw35Nq1a/zpT39i9uzZ+Pr6AurXwiI2Npbg4GCsVitWq5UdO3bQp08f9W0h8Nlnn7Fp0yYiIyMZPnw43t7e/P3vf1ffPufu3r3LzJkzSU1NJSkpifXr1/PnP/9Z/fqMORiGYeR3ECJSMEVFRfHJJ59gs9no2bMnAQEB+R2S5MLb25sVK1ZQrVo1oqOjmTZtGqmpqbRr146goCAcHBw4c+YMwcHBJCUlUa9ePaZNm4azszNXrlxh3Lhx3Lp1iypVqjB37lxcXV25ffs248aN4/Lly5QqVYrZs2dTrVq1/H7UQm/y5MmEh4fzu9/9zizr06cPL7/8svq1EFi4cCFbt27F0dGRjh07MmzYMP2bLWQiIiI4ePAg06dPV98WAh9//DHbt28nIyODt99+m4EDB6pfnzElrSIiIiIiIlJgaXqwiIiIiIiIFFhKWkVERERERKTAUtIqIiIiIiIiBZaSVhERERERESmwlLSKiIiIiIhIgeWU3wGIiIiI/DekpaWxbNkyoqKiAMjIyKB58+YMHz6csmXLPpV7rlu3DqvVSr9+/fjiiy+4e/cugwYNsit/XOfOnWPGjBlcu3YNAFdXV0aOHImHh0eu1y1cuJCEhAQmTJiQra5x48ZERUXpKzRE5LmmpFVEREQKhdGjR5ORkcGqVatwdXXFZrOxfPly+vTpQ3h4OC4uLv/1ex4+fJhXX30VgL59++ZY/riGDx/OyJEj6dChAwDff/89H3zwATt27KBMmTL/vaBFRJ4zSlpFREQaDZ7UAAAEnklEQVTkuffDDz/w/fff89VXX1G8eHEALBYLAQEBHDlyhC+++IKAgAC8vb2ZP38+9evXB7A7XrJkCTt27OD+/fukpKQwduxYOnTowMKFC7ly5QpxcXFcuXKFSpUqMWvWLI4fP87OnTv57rvvKFasGPHx8SQkJODl5WVXvmLFCiZMmECrVq0AGD9+PLVq1WLgwIF2zxAXF8e9e/fM42bNmvHxxx/j6OgIwNdff01oaCgZGRmULFmSoKAgGjRoYNfGoUOH+Oijj3BwcKB+/fpkZGQ8tXcuIvKsaE2riIiIPPeOHDmCu7u7mbA+qFWrVhw5ciTX669cucK+fftYuXIlUVFRjBo1igULFpj1hw4dYv78+Wzbto3ixYuzevVqOnTogLe3N++8847dNOCHy/v27cvatWsBSEpKYufOnbz11lvZYpgwYQKTJ0+mdevWjBgxglWrVlG/fn1KlSrFuXPnCAkJYeHChWzcuJHhw4czdOhQkpKSzOutVisjRoxg3LhxbNiwAU9PT+7fv//E71JEpKBR0ioiIiKFnmEYudZXrVqVmTNnEhUVxezZs1m9ejXJyclmffPmzc3pxXXr1iUxMfGx7929e3f27dtHfHw8Gzdu5PXXX6d06dLZzvPz82Pv3r3MnDmT6tWrEx4ejq+vL7Gxsezfv58WLVrg5uYGgJeXF+XKlSMmJsa8/qeffsLJyQkvLy+zvZIlSz52nCIiBZWSVhEREXnuNWnShBMnTpCSkgJkjjomJCQAsH//fho2bGie+2ACa7VaATh58iS9e/cmKSmJVq1a8cc//tGu/WLFipn/28HBIc8k+EGlS5emU6dObNy4kfDwcLu1r1nOnTvH7NmzKVq0KC1btmTEiBGsX7+eV199le3bt5ORkYGDg4PdNYZhkJaWlq3sQU5OWgkmIs8/Ja0iIiLy3GvQoAGenp6MGzeOxMRELl++TL9+/Rg2bBg//vijOX33wdHJAwcOEBcXB2RueuTu7s67775L8+bN2bFjB+np6Xne19HRMVvimFN5v379WLFiBYZhZFuHCvDCCy+wdu1atm3bZpbdvn2b69evU7duXby8vNi7dy+XL18GIDo6mmvXrtkl46+99hqGYbB7924AduzY8UQjwiIiBZX+/CYiIiKFwqxZs1i2bBl/+MMfALDZbDg6OlKyZEl27NjBW2+9xV/+8hcmTpzImjVrqFevHvXq1QMyp9J++eWXdO7cmYyMDN544w0SExPt1ozmpG3btkyfPj3X8g8++IDatWvj6upKnz59cmzH1dWVf/7zn8yZM4eZM2dSvHhxnJ2d+eCDD8zpviEhIQQGBpKenk6xYsVYsmQJpUqVMtuwWCwsWrSIiRMnMnfuXOrUqUP58uWf/EWKiBQwDsaTzG8RERERec7cuXOHmJgYWrZsmW8xXLp0if79+5sbOYmIyONT0ioiIiLyFM2fP5+1a9cyadIk2rdvn9/hiIg8d5S0ioiIiIiISIGljZhERERERESkwFLSKiIiIiIiIgWWklYREREREREpsJS0ioiIiIiISIGlpFVEREREREQKLCWtIiIiIiIiUmD9Pxi66JNr4qS9AAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set(style = 'whitegrid')\n", "f, ax = plt.subplots(figsize = (12, 9))\n", "\n", "\n", "sns.barplot(\n", " x = 'quantity',\n", " y = 'description',\n", " data = grouped_items_by_quantity_sold.head(25),\n", " color = 'b',\n", " alpha = 0.6).set_title(\"Top 25 Products by Quantity Sold\", fontsize = 16)\n", "\n", "ax.set_xlabel('Quantity Sold')\n", "ax.set_ylabel('Item');" ] }, { "cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set(style = 'whitegrid')\n", "f, ax = plt.subplots(figsize = (12, 9))\n", "\n", "\n", "sns.barplot(\n", " x = 'unit_price',\n", " y = 'description',\n", " data = grouped_items_by_unit_price.head(48),\n", " color = 'b',\n", " alpha = 0.6).set_title(\"Top 25 Products sold by Unit Price\", fontsize = 16)\n", "\n", "ax.set_xlabel('Sales')\n", "ax.set_ylabel('Item');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observations\n", "* Both the charts of top products sold by revenue generated and by quantities sold show a skewed chart. A small number of products bring in high revenue, and then a much larger group bring in less.\n", "* Likewise, a small number of products get purchased more, and a much larger group have less sales.\n", "\n", "Like the \"elbow method\" in determining clusters, we can pick some numbers to see which group brought in more total profits." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Find the \"elbow\"" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [], "source": [ "product_sales_total = 20000" ] }, { "cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [], "source": [ "sales_above_20k = grouped_items[grouped_items['quantity'] >= product_sales_total]['sales_total'].sum()" ] }, { "cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [], "source": [ "sales_below_20k = grouped_items[grouped_items['quantity'] < product_sales_total]['sales_total'].sum()" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Products bringing in sales of $20000 or above totaled: $66941.98 or 0.69% of total sales.\n", "Products that brought in under $20000 totaled: $9673080.54 or 99.31% of total sales.\n" ] } ], "source": [ "print(\"Products bringing in sales of $\" \n", " + str(product_sales_total) \n", " + \" or above totaled: $\" \n", " + str(round(sales_above_20k, 2))\n", " + \" or {:.2f}% of total sales.\".format(\n", " sales_above_20k / grouped_items['sales_total'].sum() * 100))\n", "print(\"Products that brought in under $\"\n", " + str(product_sales_total) \n", " + \" totaled: $\" \n", " + str(round(sales_below_20k,2))\n", " + \" or {:.2f}% of total sales.\".format(\n", " sales_below_20k / grouped_items['sales_total'].sum() * 100))" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [], "source": [ "# we can do a more detailed breakdown. First, a list of dollar amounts for possible \"elbow\" locations\n", "product_sales_list = [20000, 10000, 7500, 5000, 4500, 4000, 3000, 2000, 1000]\n", "product_quantities_list = [20000, 10000, 7500, 5000, 4000, 3000, 1500]\n", "unit_price_list = [500, 250, 100, 50, 25, 10, 5, 3, 2, 1, 0.75, 0.5, 0.25]" ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [], "source": [ "def revenues_percentage_above_below_x_feature(grouped_df, feature_name, list_of_units):\n", " '''This function takes a grouped by item dataframe, and a list of feature quantities and compares sales\n", " between products selling more than a given feature quantity versus products selling less than the feature quantity.\n", " \n", " PURPOSE: give the analyst a better idea of whether more profits came from fewer high priced items, or \n", " from a lot of lower priced items\n", " \n", " RETURNS: a DataFrame with the percentages broken down by list_of_units\n", " '''\n", " columns = [feature_name, \n", " 'sales_above', \n", " 'sales_below', \n", " 'percent_above', \n", " 'percent_below']\n", " new_df = pd.DataFrame(columns = columns)\n", " total_sales = grouped_df['sales_total'].sum()\n", " \n", " for units in list_of_units:\n", " sales_at_above_feature_units = grouped_df[grouped_df[feature_name] >= units]['sales_total'].sum()\n", " sales_below_feature_units = grouped_df[grouped_df[feature_name] < units]['sales_total'].sum()\n", " \n", " new_df = new_df.append({feature_name : units,\n", " 'sales_above' : round(sales_at_above_feature_units, 2),\n", " 'sales_below' : round(sales_below_feature_units,2),\n", " 'percent_above' : round(sales_at_above_feature_units / total_sales * 100, 2),\n", " 'percent_below' : round(sales_below_feature_units / total_sales * 100, 2) },\n", " ignore_index = True)\n", " return new_df" ] }, { "cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [], "source": [ "df_revenue_percentages_above_below_sales_totals = revenues_percentage_above_below_x_feature(grouped_items, \"sales_total\", product_sales_list)" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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sales_totalsales_abovesales_belowpercent_abovepercent_below
020000.0537442.069202580.465.5294.48
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81000.07520351.092219671.4377.2122.79
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" ], "text/plain": [ " sales_total sales_above sales_below percent_above percent_below\n", "0 20000.0 537442.06 9202580.46 5.52 94.48\n", "1 10000.0 1467462.59 8272559.93 15.07 84.93\n", "2 7500.0 2068389.18 7671633.34 21.24 78.76\n", "3 5000.0 3395942.69 6344079.83 34.87 65.13\n", "4 4500.0 3712038.28 6027984.24 38.11 61.89\n", "5 4000.0 4076211.92 5663810.60 41.85 58.15\n", "6 3000.0 4972323.63 4767698.89 51.05 48.95\n", "7 2000.0 6035255.75 3704766.77 61.96 38.04\n", "8 1000.0 7520351.09 2219671.43 77.21 22.79" ] }, "execution_count": 93, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_revenue_percentages_above_below_sales_totals" ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "9202580.46" ] }, "execution_count": 94, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_revenue_percentages_above_below_sales_totals.iloc[0][2]" ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", "def show_pie(percentage_df, unit_name, title_name):\n", " # Pie chart\n", " labels = ['Equal to or above ' + str(percentage_df[0]) + ' ' + unit_name,\n", " '< ' + str(percentage_df[0]) + ' ' + unit_name]\n", " sizes = [percentage_df[1], percentage_df[2]]\n", "\n", " #colors\n", " colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99']\n", "\n", " # figure size\n", " plt.figure(figsize = (8,8))\n", " \n", " # font size\n", " plt.rcParams['font.size'] = 18\n", " \n", " plt.pie(sizes,\n", " colors = colors,\n", " labels = labels,\n", " autopct = '%1.1f%%',\n", " startangle = 90,\n", " pctdistance = 0.85)\n", "\n", " #draw circle\n", " centre_circle = plt.Circle((0,0),\n", " 0.6,\n", " fc = 'white')\n", "\n", " fig = plt.gcf()\n", " fig.gca().add_artist(centre_circle)\n", "\n", " plt.title(title_name, fontsize = 18)\n", " plt.tight_layout()\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [ { "data": { "image/png": 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JtmNERETECoUQERERsUIhRERERKxQCBERERErFEJERETECoUQERERsUIhRERERKxQCBERERErFEJERETECoUQERERsUIhRERERKxQCBERERErFEJERETECoUQERERsUIhRERERKxQCBERERErFEJERETECoUQERERsUIhRERERKxQCBERERErFEJERETECoUQERERsUIhRERERKxQCBERERErFEJERETECoUQERERsUIhRERERKxQCBERERErFEJERETECoUQERERsUIhRERERKxQCBERERErFEJERETEiv8PR2vEK1y/VWgAAAAASUVORK5CYII=\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_pie(df_revenue_percentages_above_below_sales_totals.iloc[0], 'dollars','Revenue Percentage of Products Sales above or below $20k each')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "We can see that the majority of sales are products that total less than \\\\$20,000 in sales.\n", "Some of the extreme numbers we see make up just 5.5% of total sales." ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [], "source": [ "df_revenue_percentages_above_below_quantities_sold = revenues_percentage_above_below_x_feature(grouped_items, \"quantity\", product_quantities_list)" ] }, { "cell_type": "code", "execution_count": 98, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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quantitysales_abovesales_belowpercent_abovepercent_below
020000.066941.989673080.540.6999.31
110000.0392919.729347102.804.0395.97
27500.0704203.029035819.507.2392.77
35000.01372403.858367618.6714.0985.91
44000.01854922.017885100.5119.0480.96
53000.02480569.527259453.0025.4774.53
61500.04168348.605571673.9242.8057.20
\n", "
" ], "text/plain": [ " quantity sales_above sales_below percent_above percent_below\n", "0 20000.0 66941.98 9673080.54 0.69 99.31\n", "1 10000.0 392919.72 9347102.80 4.03 95.97\n", "2 7500.0 704203.02 9035819.50 7.23 92.77\n", "3 5000.0 1372403.85 8367618.67 14.09 85.91\n", "4 4000.0 1854922.01 7885100.51 19.04 80.96\n", "5 3000.0 2480569.52 7259453.00 25.47 74.53\n", "6 1500.0 4168348.60 5571673.92 42.80 57.20" ] }, "execution_count": 98, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_revenue_percentages_above_below_quantities_sold" ] }, { "cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_pie(df_revenue_percentages_above_below_quantities_sold.iloc[0], 'units sold', 'Revenue Percentage of Products Sales above or below 20k units sold each')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "Likewise, over 99% of total sales are from products selling less than 20,000 units." ] }, { "cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [], "source": [ "df_revenue_percentages_above_below_unit_prices = revenues_percentage_above_below_x_feature(grouped_items, \"unit_price\", unit_price_list)" ] }, { "cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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unit_pricesales_abovesales_belowpercent_abovepercent_below
0500.000.009740022.520.00100.00
1250.001504.509738518.020.0299.98
2100.0020599.509719423.020.2199.79
350.0037119.529702903.000.3899.62
425.0086589.579653432.950.8999.11
510.00797854.358942168.178.1991.81
65.002259786.117480236.4123.2076.80
73.004305784.645434237.8844.2155.79
82.006103645.453636377.0762.6737.33
91.008659263.901080758.6288.9011.10
100.759057681.00682341.5292.997.01
110.509346640.70393381.8295.964.04
120.259703772.5336249.9999.630.37
\n", "
" ], "text/plain": [ " unit_price sales_above sales_below percent_above percent_below\n", "0 500.00 0.00 9740022.52 0.00 100.00\n", "1 250.00 1504.50 9738518.02 0.02 99.98\n", "2 100.00 20599.50 9719423.02 0.21 99.79\n", "3 50.00 37119.52 9702903.00 0.38 99.62\n", "4 25.00 86589.57 9653432.95 0.89 99.11\n", "5 10.00 797854.35 8942168.17 8.19 91.81\n", "6 5.00 2259786.11 7480236.41 23.20 76.80\n", "7 3.00 4305784.64 5434237.88 44.21 55.79\n", "8 2.00 6103645.45 3636377.07 62.67 37.33\n", "9 1.00 8659263.90 1080758.62 88.90 11.10\n", "10 0.75 9057681.00 682341.52 92.99 7.01\n", "11 0.50 9346640.70 393381.82 95.96 4.04\n", "12 0.25 9703772.53 36249.99 99.63 0.37" ] }, "execution_count": 101, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_revenue_percentages_above_below_unit_prices" ] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_pie(df_revenue_percentages_above_below_unit_prices.iloc[5], 'dollars', 'Revenue Percentage of Sales of Producst selling above or below unit price of $10')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "This appears to be a \"\\\\$10 Store\", since the majority of sales comes from products selling for \\\\$10 or less.\n", "\n", "More likely, though, this is a wholesaler, judging by the variety of prices and discounts, as well as some of the quantities sold.\n", "\n", "In any case:\n", "* We found that the top products sold by revenue generated and by quantities sold show skewed charts: \n", " * Products that brought in sales of \\\\$20k only make up 5.5% of total revenues\n", " * More than 75% of revenues were from products that generated sales of \\\\$7500 or less each\n", "* Likewise, nearly 80% of revenues were from products that sold 4000 or less units\n", "* And finally, more than 80% of revenues came from products whose unit pricing was \\\\$5 or less\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Group by Customer" ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": [ "aggregations = {\n", " 'orders': ('invoice_no', 'nunique'),\n", " 'sales_total': ('total_price','sum'),\n", " 'sales_average': ('total_price', 'mean')\n", "}\n", "\n", "grouped_customers = df.groupby(['customer_id']).agg(\n", " **aggregations).sort_values(\n", " by = 'sales_total', ascending = False).reset_index()" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [], "source": [ "top_20_customers = grouped_customers.head(20).sort_values(by = 'sales_total', ascending = False)" ] }, { "cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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customer_idorderssales_totalsales_average
0014101506879.5911.451323
11464673278778.02135.197876
21810260259657.30602.453132
31745049189575.53559.219853
414911243132893.2422.558690
51241524123638.18159.739251
61415665114335.7780.859809
7175114588138.2082.065363
8166843065920.12235.429000
9136945762961.54108.367539
10160296660369.93232.192038
111531111859284.1923.924209
121308911857322.1330.934771
13150615454250.34132.641418
14140961753258.4310.453078
15179494953215.74700.207105
16157692951823.72352.542313
17142984550862.4431.013683
18140881450415.4985.449983
191784116939861.495.110447
\n", "
" ], "text/plain": [ " customer_id orders sales_total sales_average\n", "0 0 1410 1506879.59 11.451323\n", "1 14646 73 278778.02 135.197876\n", "2 18102 60 259657.30 602.453132\n", "3 17450 49 189575.53 559.219853\n", "4 14911 243 132893.24 22.558690\n", "5 12415 24 123638.18 159.739251\n", "6 14156 65 114335.77 80.859809\n", "7 17511 45 88138.20 82.065363\n", "8 16684 30 65920.12 235.429000\n", "9 13694 57 62961.54 108.367539\n", "10 16029 66 60369.93 232.192038\n", "11 15311 118 59284.19 23.924209\n", "12 13089 118 57322.13 30.934771\n", "13 15061 54 54250.34 132.641418\n", "14 14096 17 53258.43 10.453078\n", "15 17949 49 53215.74 700.207105\n", "16 15769 29 51823.72 352.542313\n", "17 14298 45 50862.44 31.013683\n", "18 14088 14 50415.49 85.449983\n", "19 17841 169 39861.49 5.110447" ] }, "execution_count": 105, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top_20_customers" ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [], "source": [ "def plot_cust_sales_history(grouped_df, group_name = \"\"):\n", " num_of_customers = len(grouped_df)\n", " print(\"Sales history of the \" + group_name + \" customers\")\n", " for i in range(0, num_of_customers):\n", " plt.figure(figsize = (15, 6))\n", " df[df['customer_id'] == grouped_df['customer_id'][i]]['total_price'].hist(bins = 100)\n", " plt.title('Customer:' + str(grouped_df['customer_id'][i]))\n", " plt.xlabel('Orders')\n", " plt.ylabel('Invoice totals')\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 107, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sales history of the top 20 customers\n" ] }, { "data": { "image/png": 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\n", 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\n", 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\n"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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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Xxmuhb9euXSovL1dISIikc0GuXbt2KikpcW9TUlIih8OhwMDA88aPHz8uh8NRo/cLCgqSv7//lSm+gcvNzfX4ywUaH/pqLnprppr2la+BxoHvVzPRVzPR1584nc5fXATz2uWd33//vWbPni2n06nS0lKtW7dOzz//vA4cOKCDBw+qsrJSmZmZCg0NVbt27eTv7+9O6hkZGQoNDfVWaQAAAADQZHhtpa9Pnz76/PPPNXjwYFVVVenRRx9Vr169lJKSori4ODmdToWFhSkyMlKSlJqaqqSkJJWWlqp79+4aOXKkt0oDAAAAgCbDqw/Ce+655/Tcc8+dNxYSEqL169dfsG23bt20evVqb5YDAAAAAE2O1y7vBAAAAADUP0IfAAAAABiM0AcAAAAABiP0AQAAAIDBCH0AAAAAYDBCHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwCAl7nKK2s1DwBAbdjruwAAAEzn5+uj6IkZ1c5vmDOoDqsBADQ1rPQBAAAAgMEIfQAAAABgMEIfAAAAABiM0AcAAAAABiP0AQAAAIDBCH0AAAAAYDBCHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMEIfAAAAABiM0AcAAAAABiP0AQAAAIDBCH0AAAAAYDBCHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMEIfAAAAABjskkJfaWmpJGnv3r165513VF5efslvMGvWLE2aNEmSlJOTo+joaIWHhystLc29TX5+vmJiYhQREaHExERVVFTU5BwAAAAAANXwGPrmzZunyZMn65tvvtETTzyhtWvXasqUKZd08O3bt2vdunWSpLKyMiUkJGjhwoXauHGj8vLylJ2dLUmKj49XcnKyNm3aJMuylJ6efvlnBAAAAABw8xj6srOzNX36dG3evFlRUVFasmSJ9u3b5/HA3333ndLS0jRmzBhJ0u7du9WpUyd16NBBdrtd0dHRysrKUmFhocrKyhQcHCxJiomJUVZWVi1PCwAAAAAgXeLlnS1atFBOTo7uueceSZLL5fK4T3JysiZMmKBrrrlGklRcXKyAgAD3vMPhUFFR0QXjAQEBKioqqtFJAAAAAAAuzu5pgzZt2mjKlCnKy8vTvHnzlJqaKofD8Yv7rFq1SjfccINCQkK0du1aSVJVVZVsNpt7G8uyZLPZqh2vqby8vBrv05jl5ubWdwnwAvpqLnprpp/3tXfv3lfsWKhf9MJM9NVM9PXSeAx9s2bNUnp6uhYvXqwWLVrIZrNp1qxZv7jPxo0bVVJSokGDBunUqVM6e/asCgsL5ePj496mpKREDodDgYGBKikpcY8fP37cY6i8mKCgIPn7+9d4v8YoNze31r9coOGhr+ait2a60n3la6Rh4PvVTPTVTPT1J06n8xcXwaoNfd999925Dex2Pfroo+6xxx9/3OObvvnmm+4/r127Vjt37tTUqVMVHh6ugwcPqn379srMzNTDDz+sdu3ayd/f3920jIwMhYaGXvIJAgAAAACqV23ou+eee2Sz2dyXW1qW5Z6z2WzKz8+v0Rv5+/srJSVFcXFxcjqdCgsLU2RkpCQpNTVVSUlJKi0tVffu3TVy5MjLPB0AAAAAwM9VG/ou5RM6L0VMTIxiYmIkSSEhIVq/fv0F23Tr1k2rV6++Iu8HAAAAAPiJx3v6XC6XsrOzdebMGUlSZWWlDh06pAkTJni9OAAAAABA7XgMfRMmTNDhw4dVUlKi22+/XZ9//rl+/etf10VtAAAAAIBa8vicvvz8fK1du1b//u//roSEBK1YsUKnTp2qi9oAAAAAALXkMfQ5HA7Z7XbddNNN2r9/vzp37qzvv/++LmoDAAAAANSSx9DXsmVLbdiwQd26ddO7776rL774QmfPnq2L2gAAAAAAteQx9CUnJys/P1/33XefmjVrphEjRlzSs/oAAAAAAPXPY+j7v//7P73wwguy2WyaO3eudu7cqRYtWtRFbQAAAACAWqr20zu3bt2qiooKzZ49W5ZluR/OXlFRofnz52vw4MF1ViQAAAAA4PJUG/ry8/O1Y8cOnThxQkuWLPlpB7tdo0eProvaAAAAAAC1VG3oGzdunMaNG6dly5Zp+PDhdVkTAAAAAOAK8fhw9tjYWP3tb3/Thx9+qIqKCt13330aM2aM7HaPuwIAAAAA6pnHD3JJS0vTjh07NGrUKP3hD3/QZ599ptmzZ9dFbQAAAACAWvK4XPfhhx9qzZo18vX1lSQ98MADevDBB5WQkOD14gAAAAAAteNxpc+yLHfgkyQ/P7/zXgMAAAAAGi6Poa9bt26aMWOGDh06pMOHD2vmzJnq0qVLXdQGAAAAAKglj6Fv8uTJOn36tGJjYzV06FCdPHlSycnJdVEbAAAAAKCWPN7Tt2PHDqWkpJw39s477/BwdgAAAABoBKoNfVu3blVFRYVmz54ty7JkWZYkqaKiQvPnzyf0AQAAAEAjUG3oy8/P144dO3TixAktWbLkpx3sdo0ePbouagMAAAAA1FK1oW/cuHEaN26cli1bpuHDh9dlTQAAAACAK8TjB7kQ+AAAAACg8fIY+gAAAAAAjRehDwAAAAAMdkmh79ixY8rOzlZlZaW++eYbb9cEAAAAALhCPIa+bdu2KTY2VlOnTtWJEycUFRWl999/vy5qAwAAAADUksfQt2DBAqWnp+uaa66Rw+HQ8uXL9eqrr9ZFbQAAAACAWvIY+iorK+VwONyvb7vtNtlsNq8WBQAAAAC4MjyGvhYtWuibb75xB71du3bJ39/f64UBAAAAAGqv2oez/2jixIl67LHHVFJSokceeUQFBQWaP39+XdQGAAAAAKglj6HvzjvvVHp6uj777DNVVVUpODhYbdq0qYvaAAAAAAC15PHyzn379ulPf/qTwsLCdOONN2r06NH6+uuv66I2AAAAAEAteQx9U6ZM0dChQyVJXbt2VVxcnCZPnuz1wgAAAAAAtecx9P3www/63e9+537dr18/lZaWerUoAAAAAMCV4TH02Ww27du3z/36q6++UrNmHncDAAAAADQAHj/I5dlnn9WIESPUpUsXSdLXX3+t1NRUrxcGAAAAAKg9j6GvT58+ysrK0qeffiofHx/17NlT1157bV3UBgAAAACopWqv09y+fbskafPmzcrNzZVlWaqoqFBubq42b95cZwUCAAAAAC5ftSt9//M//6OQkBAtXbr0gjmbzabw8HCvFgYAAAAAqL1qQ9/06dMlyR36KioqZFmWfH1966YyAAAAAECtefwYzhMnTujJJ59UcHCwevTooZEjR6qoqOiSDj5v3jwNGDBAUVFRevPNNyVJOTk5io6OVnh4uNLS0tzb5ufnKyYmRhEREUpMTFRFRcVlnhIAAAAA4EceQ9+0adPUs2dP5eTkKCcnR3fddZemTJni8cA7d+7Ujh07tH79eq1Zs0ZLly7Vvn37lJCQoIULF2rjxo3Ky8tTdna2JCk+Pl7JycnatGmTLMtSenp6rU8OAAAAAJo6j6GvoKBAzzzzjK655hq1adNG48eP16FDhzwe+Ne//rWWLFkiu92uEydOqLKyUqdPn1anTp3UoUMH2e12RUdHKysrS4WFhSorK1NwcLAkKSYmRllZWbU/OwAAAABo4jyGvoqKCjmdTvfrH374QTab7ZIO7uvrq1dffVVRUVEKCQlRcXGxAgIC3PMOh0NFRUUXjAcEBFzyJaQAAAAAgOp5fE7fgAEDNHr0aMXExMhms2nNmjWKiIi45DcYP368nnzySY0ZM0YFBQXnBUbLsmSz2VRVVXXR8ZrIy8ur0faNXW5ubn2XAC+gr+ait2b6eV979+59xY6F+kUvzERfzURfL43H0Ddu3DgFBgbqo48+UlVVlWJiYjRkyBCPB/7qq6/kcrl02223qUWLFgoPD1dWVpZ8fHzc25SUlMjhcCgwMFAlJSXu8ePHj8vhcNToRIKCguTv71+jfRqr3NzcWv9ygYaHvpqL3prpSveVr5GGge9XM9FXM9HXnzidzl9cBPN4eeecOXN09913a+7cuXr11Vc1dOjQS1qFO3LkiJKSkuRyueRyubRlyxbFxsbqwIEDOnjwoCorK5WZmanQ0FC1a9dO/v7+7qSekZGh0NDQGpwmAAAAAOBiPK70VVVV6T/+4z/0b//2bxo6dKjCw8Pl5+fn8cBhYWHavXu3Bg8eLB8fH4WHhysqKkpt27ZVXFycnE6nwsLCFBkZKUlKTU1VUlKSSktL1b17d40cObL2ZwcAAAAATZzH0BcfH6+JEyfqo48+0tq1azV79mxFRkYqISHB48Hj4uIUFxd33lhISIjWr19/wbbdunXT6tWra1A6AAAAAMATj6FPkpo1a6agoCAdOHBABQUF2rVrl7frAgAAAABcAR5D33vvvac1a9bon//8pyIjIzVjxgx17969LmoDAAAAANSSx9D3xhtv6Pe//73mzp2r5s2b10VNAAAAAIArxGPoW7lypVwul3744QeVlZW5x1u3bu3VwgAAAAAAtXdJoW/GjBkqLy+XZVmSJJvNpvz8fK8XBwAAAACoHY+h7/XXX9eKFSu4jw8AAAAAGiGPD2e/7rrrCHwAAAAA0Eh5DH3333+/li9frqKiIn333Xfu/wAAAAAADZ/Hyzv/+te/yuVyadq0ae4x7ukDAAAAgMbBY+jbvXt3XdQBAAAAAPCCakPfnj17fnFH7vMDAAAAgIav2tAXFxdX7U42m01btmzxSkEAAAAAgCun2tC3devWuqwDAAAAAOAFHj+9EwAAAADQeBH6AAAAAMBghD4AAAAAMBihDwAAAAAMRugDAAAAAIMR+gAAAADAYIQ+AAAAADAYoQ8AAAAADEboAwAAAACDEfoAAAAAwGCEPgAAAAAwGKEPAAAAAAxG6AMAAAAAgxH6AAAAAMBghD4AAAAAMBihDwAAAAAMRugDAAAAAIMR+gAAAADAYIQ+AADqmau88rLmAAC4FPb6LgAAgKbOz9dH0RMzLjq3Yc6gOq4GAGAaVvoAAAAAwGCEPgAAAAAwGKEPAAAAAAxG6AMAAAAAgxH6AAAAAMBghD4AAAAAMBihDwAAAAAM5tXQ99prrykqKkpRUVGaPXu2JCknJ0fR0dEKDw9XWlqae9v8/HzFxMQoIiJCiYmJqqio8GZpAAAAANAkeC305eTk6OOPP9a6dev0zjvvaM+ePcrMzFRCQoIWLlyojRs3Ki8vT9nZ2ZKk+Ph4JScna9OmTbIsS+np6d4qDQAAAACaDK+FvoCAAE2aNEl+fn7y9fXVLbfcooKCAnXq1EkdOnSQ3W5XdHS0srKyVFhYqLKyMgUHB0uSYmJilJWV5a3SAAAAAKDJ8Fro69y5szvEFRQU6N1335XNZlNAQIB7G4fDoaKiIhUXF583HhAQoKKiIm+VBgAAAABNht3bb/Dll1/q6aef1gsvvCAfHx8VFBS45yzLks1mU1VVlWw22wXjNZGXl3elSm4UcnNz67sEeAF9NRe9NdPP+9q7d+86eR94H3/fZqKvZqKvl8aroS83N1fjx49XQkKCoqKitHPnTpWUlLjnS0pK5HA4FBgYeN748ePH5XA4avReQUFB8vf3v2K1N2S5uble/eUC9YO+movemqku+8rXT93h+9VM9NVM9PUnTqfzFxfBvHZ559GjRzVu3DilpqYqKipKktSzZ08dOHBABw8eVGVlpTIzMxUaGqp27drJ39/fndQzMjIUGhrqrdIAAAAAoMnw2krfG2+8IafTqZSUFPdYbGysUlJSFBcXJ6fTqbCwMEVGRkqSUlNTlZSUpNLSUnXv3l0jR470VmkAAAAA0GR4LfQlJSUpKSnponPr16+/YKxbt25avXq1t8oBAAAAgCbJqw9nBwAAAADUL0IfAAAAABiM0AcAAAAABiP0AQAAAIDBCH0AAAAAYDBCHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMEIfAAAAAFolBasAABC1SURBVBiM0AcAAAAABiP0AQAAAIDBCH0AAAAAYDBCHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMEIfAAAAABiM0AcAAAAABiP0AQAAAIDBCH0AAAAAYDBCHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMEIfAAAAABiM0AcAAAAABvNq6CstLdXAgQN15MgRSVJOTo6io6MVHh6utLQ093b5+fmKiYlRRESEEhMTVVFR4c2yAAAAAKDJ8Fro+/zzzzVs2DAVFBRIksrKypSQkKCFCxdq48aNysvLU3Z2tiQpPj5eycnJ2rRpkyzLUnp6urfKAgAAAIAmxWuhLz09XZMnT5bD4ZAk7d69W506dVKHDh1kt9sVHR2trKwsFRYWqqysTMHBwZKkmJgYZWVleassAAAaFVd5Za3mAQCwe+vAf/7zn897XVxcrICAAPdrh8OhoqKiC8YDAgJUVFTkrbIAAGhU/Hx9FD0xo9r5DXMG1WE1AIDGyGuh719VVVXJZrO5X1uWJZvNVu14TeXl5V2ROhuL3Nzc+i4BXkBfzUVvzfTzvvbu3btB1IHa4+/TTPTVTPT10tRZ6AsMDFRJSYn7dUlJiRwOxwXjx48fd18SWhNBQUHy9/e/IrU2dLm5ufX6ywW8g76ai96aqSH1taHUYYKG1FdcOfTVTPT1J06n8xcXwerskQ09e/bUgQMHdPDgQVVWViozM1OhoaFq166d/P393Sk9IyNDoaGhdVUWAAAAABitzlb6/P39lZKSori4ODmdToWFhSkyMlKSlJqaqqSkJJWWlqp79+4aOXJkXZUFAAAAAEbzeujbunWr+88hISFav379Bdt069ZNq1ev9nYpAAAAANDk1NnlnQAAAACAukfoAwAAAACDEfoAAAAAwGCEPgAAAAAwGKEPAAAAAAxG6AMAAAAAgxH6AAAAAMBghD4AAAAAMBihDwAAAAAMRugDAAAAAIMR+gAAAADAYIQ+AAAAADAYoQ8AgEbMVV5Zq3kAgPns9V0AAAC4fH6+PoqemFHt/IY5g+qwGgBAQ8RKHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMEIfAAAAABiM0AcAgMFc5ZWXNQcAMIe9vgsAAADe4+fro+iJGRed2zBnUB1XAwCoD6z0AQAAAIDBCH0AAAAAYDBCHwAAAAAYjNAHAAAAAAYj9AEAAACAwQh9AAAAAGAwQh8AAAAAGIzQBwAALooHuwOAGXg4OwAAuCge7A4AZmClDwAAAAAMRugDAAAAAIMR+gAAuAT/eg9b796966mSK4f78gCgaeCePgAALsEv3d8mNc573Ew8JwDAhVjpAwAANeZplZBVRABoOBrUSt+GDRu0aNEiVVRUaNSoURo+fHh9lwQAAC6CVUIAaDwaTOgrKipSWlqa1q5dKz8/P8XGxuo3v/mNbr311vouDQAANBKu8kr5+fpc9jwAmKjBhL6cnBzdc889at26tSQpIiJCWVlZeuaZZ+q5MgAAUFO1CV+e9nWWV8q/mnlWIAHgQg0m9BUXFysgIMD92uFwaPfu3R73syxLkuRyubxWW0PkdDrruwR4AX01F71t+MorKuVr/+UVoNZX/UIQcTqrnf+lOW/uW591WVUVGpH8brXzryf+Tk5nRbXznvatbv71xN95PCdP+H41E301E30958cs9GM2+lc2q7qZOrZo0SI5nU4999xzkqT09HTl5eVp2rRpv7jf999/r/3799dFiQAAAADQYHXp0kVXX331BeMNZqUvMDBQu3btcr8uKSmRw+HwuN9VV12lLl26yNfXVzabzZslAgAAAECDY1mWysvLddVVV110vsGEvnvvvVfz58/XyZMn1aJFC23evFmvvPKKx/2aNWt20TQLAAAAAE1F8+bNq51rMKHv+uuv14QJEzRy5EiVl5dryJAh6tGjR32XBQAAAACNWoO5pw8AAAAAcOU1q+8CAAAAAADeQ+gDAAAAAIMR+gAAAADAYIQ+AAAAADAYoQ8AAAAADEboa+CKi4v11FNPafDgwYqNjdWRI0ckSadPn9ZTTz2l/v37a/jw4SopKZEkuVwuxcfHq3///nrooYf01Vdf1Wf58GDv3r0KCgpyv6avjVtubq6GDBmiQYMGadSoUSosLJREX02zYcMGDRgwQOHh4Vq2bFl9l4Maeu211xQVFaWoqCjNnj1bkpSTk6Po6GiFh4crLS3NvW1+fr5iYmIUERGhxMREVVRU1FfZuESzZs3SpEmTJNFXU2zdulUxMTHq37+/pk+fLoneXhYLDdqoUaOs5cuXW5ZlWcuXL7eeffZZy7Isa+rUqdbixYsty7KsdevWucdff/116+WXX7Ysy7J27txpDR06tB6qxqU4e/asFRsba3Xp0sU9Rl8btz59+lj5+fmWZVnWqlWrrDFjxliWRV9NcuzYMatPnz7Wt99+a505c8aKjo62vvzyy/ouC5fok08+sR555BHL6XRaLpfLGjlypLVhwwYrLCzMOnTokFVeXm499thj1rZt2yzLsqyoqCjrs88+syzLsl566SVr2bJl9Vk+PMjJybF+85vfWC+++KL1ww8/0FcDHDp0yLr//vuto0ePWi6Xyxo2bJi1bds2ensZWOlrwE6ePKl9+/YpNjZWkvTwww/rueeekyRt27ZN0dHRkqSBAwfqww8/VHl5ubZt26YHH3xQknT33Xfr5MmT+uabb+rnBPCLUlJSNGrUqPPG6Gvj5XK59Oyzz6pbt26SpK5du+ro0aOS6KtJcnJydM8996h169Zq2bKlIiIilJWVVd9l4RIFBARo0qRJ8vPzk6+vr2655RYVFBSoU6dO6tChg+x2u6Kjo5WVlaXCwkKVlZUpODhYkhQTE0OvG7DvvvtOaWlpGjNmjCRp9+7d9NUA7733ngYMGKDAwED5+voqLS1NLVq0oLeXgdDXgB0+fFg33nijUlJS9PDDD2v8+PHy9fWVdO6yz4CAAEmS3W5Xq1atdPLkyfPGpXM/4I4dO1Yv9aN6W7ZsUVlZmSIjI88bp6+Nl5+fnwYNGiRJqqqq0muvvaZ+/fpJoq8m+deeORwOFRUV1WNFqInOnTu7fyEsKCjQu+++K5vNdtGeXuz7k143XMnJyZowYYKuueYaSdV/r9LXxuXgwYOqrKzUmDFjNGjQIC1fvpzeXiZ7fReAc959913NnDnzvLFOnTpp7969iouL00svvaRVq1Zp0qRJWrp06QX7W5alZs2aybIs2Wy2C8ZRPy7W15tvvlmlpaV66623PO5PXxum6vr61ltvyeVyadKkSaqoqNDTTz990f3pa+NVVVV1Qc9+/hqNw5dffqmnn35aL7zwgnx8fFRQUOCe+7Gn9LrxWLVqlW644QaFhIRo7dq1kqr/XqWvjUtlZaV27dqlpUuXqmXLlho7dqyaN29Oby8Doa+B6N+/v/r373/e2KFDh/TQQw+pT58+ks5dFvbjDawOh0PHjx9XYGCgKioqdObMGbVu3VrXX3+9iouL1bFjR0nS8ePH5XA46vZk4Haxvq5atUqLFy/W8OHD3WODBg3SsmXL6GsjcbG+StKZM2c0duxYtW7dWosWLXKvzNNXcwQGBmrXrl3u1yUlJfSskcnNzdX48eOVkJCgqKgo7dy50/3hStJPPQ0MDDxvnO/Phmvjxo0qKSnRoEGDdOrUKZ09e1aFhYXy8fFxb0NfG6frrrtOISEhatu2rSSpX79+ysrKoreXgf+l3IB17NhRgYGBys7OliR98MEH6t69uyQpLCxM77zzjqRz/9jddddd8vX1VVhYmDIyMiRJu3btkr+/v2688cb6OQFc1NChQ/X+++8rIyPD3auMjAy1atWKvjZy8fHx6tSpk+bOnSs/Pz/3OH01x7333qvt27fr5MmT+uGHH7R582aFhobWd1m4REePHtW4ceOUmpqqqKgoSVLPnj114MAB92VkmZmZCg0NVbt27eTv76/c3FxJ5/6dptcN05tvvqnMzExlZGRo/Pjx6tu3r15//XX6aoA+ffro448/1unTp1VZWamPPvpIkZGR9PYy2CzLsuq7CFTv66+/1uTJk/Xtt9+qVatWSklJ0U033aTvvvtOkyZN0uHDh3X11VcrNTVV7du3l9PpVHJysvLy8uTn56fp06e7gyIapq5du+qLL76QJPraiO3du1cPPfSQbr31Vtnt5y6icDgc+tvf/kZfDbNhwwYtXrxY5eXlGjJkiJ588sn6LgmXaPr06VqzZo17dV2SYmNjddNNN2nmzJlyOp0KCwvTSy+9JJvNpn379ikpKUmlpaXq3r27Zs6ced7/0EHDs3btWu3cuVMpKSnavn07fTXA6tWr9dZbb6m8vFz33XefkpKS9Pe//53e1hChDwAAAAAMxuWdAAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMB7ODgCApBUrVmjFihWqqKiQzWbT7bffrgkTJlzSsxN79eqlDRs2qH379nVQKQAANUPoAwA0ebNmzdK+ffu0ePFi3XDDDaqqqtL69ev1yCOPaNWqVQoMDKzvEgEAuGyEPgBAk3bs2DGtXLlS27Zt069+9StJUrNmzTR48GDl5eVp8eLFys7OVo8ePfTFF1/o+eefV5s2bfTKK6/IZrPpjjvuUFVVlft4W7du1aJFi1ReXq7mzZvrxRdfVK9evTR//nz985//VHFxsbp27aqxY8cqMTFRLpdLlmVpyJAhGj58eH39NQAADEboAwA0aZ9//rluvvlmd+D7uXvvvVdz586VJHXu3Flz586Vy+VSnz59lJqaqpCQEGVmZio9PV2SVFBQoLS0NC1ZskRt2rTRl19+qT/84Q/avHmzJKmwsFCZmZmy2+1KSEhQ37599dRTT6mkpEQzZszQsGHD1KwZt9sDAK4sQh8AoMmrqKi46LjL5ZLNZpMk3XXXXZKk/fv3y263KyQkRJI0cOBAJScnS5I++eQTFRcXa/To0e5j2Gw2HTp0SJIUHBwsu/3cj97f/e53evHFF7V7926FhIQoKSmJwAcA8Ap+ugAAmrTg4GAdPHhQJSUlF8z9/e9/V69evSRJLVu2dI9blnXedj8GuaqqKoWEhCgjI8P9X3p6ujp37nzBMfr06aNNmzapf//+ys/PV3R0tI4dO3bFzw8AAEIfAKBJu/766zVixAg9//zzKioqco+vWbNGmzdv1pNPPnne9l27dpVlWcrOzpYkbdmyRadOnZIkhYSE6JNPPtFXX30lScrOztaDDz6osrKyC9534sSJ2rhxo6KiojR58mS1atXKvSIIAMCVxOWdAIAmb+LEiVq1apXGjh0rl8sll8ulO+64QytXrlS7du3O29bX11cLFizQlClT9Je//EW33Xabrr32WknSrbfeqmnTpun555+XZVmy2+1atGiRrrrqqgve849//KMSExP13//93/Lx8VG/fv10991318n5AgCaFpv1r9eoAAAAAACMweWdAAAAAGAwQh8AAAAAGIzQBwAAAAAGI/QBAAAAgMEIfQAAAABgMEIfAAAAABiM0AcAAAAABiP0AQAAAIDB/h/1aVdyjvMQxwAAAABJRU5ErkJggg==\n", 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\n", 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6dFF1dbV3/ODBg7Lb7ercubOOHTum+vp6hYWFebf/OaKjoxUeHn7e51NaWnpWoQTBQW8Ch7kQGuhD8NGD0EAfQgN9CD56EBpCrQ9Op/OMF8f8dpvo3r17lZWVJZfLJZfLpfXr1ystLU27d+/WN998o/r6eq1atUrx8fGKjIxUeHi4N0UXFhYqPj5eNptNsbGxKioqkiQVFBQoPj7eXyUDAAAAgGn47cpgQkKCtm/friFDhigsLEyJiYlyOBzq3Lmzxo0bJ6fTqYSEBA0cOFCSlJubq6ysLNXU1KhXr14aOXKkJCk7O1uTJ0/WwoUL1bVrV82aNctfJQMAAACAafj1M4Pjxo3TuHHjGo3FxcVpxYoVp2wbFRWl/Pz8U8YjIyO1ePFiv9UIAAAAAGbk16eJAgAAAABCE2EQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEzI6s+Dv/zyy1q9erUkKSEhQZMmTdJTTz2l0tJStW3bVpL08MMPa8CAASovL1dmZqZqa2sVGxuradOmyWq1qrKyUhMnTtShQ4d0xRVXKDc3V+3atfNn2QAAAADQ4vntymBJSYk+/PBDLV++XAUFBfriiy+0bt06lZWV6Y033lBhYaEKCws1YMAASdLEiRM1ZcoUrVmzRoZhKC8vT5I0bdo0DR8+XMXFxYqOjtaCBQv8VTIAAAAAmIbfwmBERIQmT56s1q1by2azqXv37qqsrFRlZaUyMjKUkpKiuXPnqqGhQfv27VNdXZ1iYmIkSampqSouLpbb7daWLVuUlJTUaBwAAAAAcH78dptojx49vH9XVFRo9erVWrJkiT755BNlZ2erQ4cOevDBB5Wfn68ePXooIiLCu31ERISqqqp0+PBhtW/fXlartdE4AAAAAOD8+PUzg5L01Vdf6cEHH9SkSZN05ZVXav78+d51I0aMUEFBgbp37y6LxeIdNwxDFovF+/tEJy/7UlZWdn4ncILS0tJmOxbOXt++fX1uQ28Ci/c7NNCH4KMHoYE+hAb6EHz0IDRcSH3waxgsLS3VI488ooyMDDkcDu3cuVMVFRXe2z4Nw5DValWXLl1UXV3t3e/gwYOy2+3q3Lmzjh07pvr6eoWFham6ulp2u/1n1RAdHa3w8PBmOZezCSUIDnoTOMyF0EAfgo8ehAb6EBroQ/DRg9AQan1wOp1nvDjmt88M7t+/X2PHjlVubq4cDoekH8PfjBkzdOTIEbndbr399tsaMGCAIiMjFR4e7k3RhYWFio+Pl81mU2xsrIqKiiRJBQUFio+P91fJAAAAAGAafrsy+Oqrr8rpdConJ8c7lpaWpgceeEDDhg2Tx+NRYmKikpOTJUm5ubnKyspSTU2NevXqpZEjR0qSsrOzNXnyZC1cuFBdu3bVrFmz/FUyLlAud71a28LOeT0AAABgRn4Lg1lZWcrKyjrtuvT09FPGoqKilJ+ff8p4ZGSkFi9e3Oz1oeVobQtTyoTCJtevfHFwAKsBAAAALgx+u00UAAAAABC6CIMAAAAAYEKEQQAAAAAwIcIgAAAAAJgQYRAAAAAATIgwCAAAAAAmRBgEAAAAABMiDAIAAACACREGAQAAAMCEzioM1tTUSJL+8Y9/qKCgQG63269FAQAAAAD8y+prgzlz5mjPnj2aMGGC7rvvPl111VXasmWLnn322UDUBwAAAADwA59XBjdu3KhnnnlGa9eulcPh0KJFi7Rjx45A1AYAAAAA8JOzuk20bdu2KikpUb9+/SRJLpfLr0UBAAAAAPzLZxjs1KmTpk6dqrKyMt14443Kzc2V3W4PRG0AAAAAAD/xGQaff/552e12vfLKK2rbtq0sFouef/75QNQGAAAAAPCTJh8g889//vPHDaxWDR8+3Dt27733BqYyAAAAAIDfNBkG+/XrJ4vFIsMwvL9/YrFYVF5eHpACAQAAAADNr8kwyBNDAQAAAKDl8vk9gy6XSxs3blRtba0kqb6+Xnv27NH48eP9XhwAAAAAwD98hsHx48fr22+/VXV1ta699lpt27ZNN9xwQyBqAwAAAAD4ic+niZaXl+svf/mLfve73ykjI0NvvfWWjhw5EojaAAAAAAB+4jMM2u12Wa1W/frXv9aXX36pHj166NixY4GoDQAAAADgJz7D4EUXXaSVK1cqKipKq1ev1s6dO/XDDz8EojYAAAAAgJ/4DINTpkxReXm5brrpJrVq1UojRozguwYBAAAA4ALnMwz+7//+ryZNmiSLxaKXXnpJn3zyidq2bRuI2gAAAAAAftLk00Q3bNggj8ejmTNnyjAM75fOezwezZs3T0OGDAlYkQAAAACA5tVkGCwvL9fmzZt16NAhLVq06P92sFo1atSoQNQGAAAAAPCTJsPg2LFjNXbsWC1ZskTp6emBrAkAAAAA4Gc+v3Q+LS1N//3f/633339fHo9HN910kx566CFZrT53BQAAAACEKJ8PkJk9e7Y2b96se+65R7///e/12WefaebMmYGoDQAAAADgJz4v773//vtatmyZbDabJOnf//3fdfvttysjI8PvxQEAAAAA/MPnlUHDMLxBUJJat27daBkAAAAAcOHxGQajoqI0Y8YM7dmzR99++62ee+45XX311YGoDQAAAADgJz7DYHZ2to4ePaq0tDTdcccd+v777zVlypSzOvjLL78sh8Mhh8Ph/ZxhSUmJUlJSlJiYqNmzZ3u3LS8vV2pqqpKSkpSZmSmPxyNJqqysVHp6ugYOHKgxY8aotrb2XM4TAAAAAHACn2Fw8+bNysnJUUlJiTZv3qwXXnhB7777rs8Dl5SU6MMPP9Ty5ctVUFCgL774QqtWrVJGRoYWLFigoqIilZWVaePGjZKkiRMnasqUKVqzZo0Mw1BeXp4kadq0aRo+fLiKi4sVHR2tBQsWnOcpAwAAAACaDIMbNmzQ2rVrlZOTo3Xr1mnt2rVau3atioqKNG/ePJ8HjoiI0OTJk72fMezevbsqKip0+eWXq1u3brJarUpJSVFxcbH27dunuro6xcTESJJSU1NVXFwst9utLVu2KCkpqdE4AAAAAOD8NPk00fLycm3evFmHDh3SokWL/m8Hq1WjRo3yeeAePXp4/66oqNDq1at19913KyIiwjtut9tVVVWlAwcONBqPiIhQVVWVDh8+rPbt23u/0/CncQAAAADA+WkyDI4dO1Zjx47VkiVLlJ6efs4v8NVXX+nBBx/UpEmTFBYWpoqKCu86wzBksVjU0NAgi8VyyvhPv0908rIvZWVl51z7yUpLS5vtWDh7ffv2Pe9j0LvmxfsZGuhD8NGD0EAfQgN9CD56EBoupD74/J7B8wmCpaWleuSRR5SRkSGHw6FPPvlE1dXV3vXV1dWy2+3q0qVLo/GDBw/Kbrerc+fOOnbsmOrr6xUWFubd/ueIjo5WeHj4OZ/DiefSHKEEwUHvmg9zITTQh+CjB6GBPoQG+hB89CA0hFofnE7nGS+O+XyAzLnav3+/xo4dq9zcXDkcDknSddddp927d+ubb75RfX29Vq1apfj4eEVGRio8PNybogsLCxUfHy+bzabY2FgVFRVJkgoKChQfH++vkgEAAADANHxeGTxXr776qpxOp3JycrxjaWlpysnJ0bhx4+R0OpWQkKCBAwdKknJzc5WVlaWamhr16tVLI0eOlPTjV1tMnjxZCxcuVNeuXTVr1ix/lQwAAAAApnFWYfC7777Tzp07dfPNN6uqqkqXXnqpz32ysrKUlZV12nUrVqw4ZSwqKkr5+fmnjEdGRmrx4sVnUyYAAAAA4Cz5vE30vffeU1pamqZNm6ZDhw7J4XDob3/7WyBqAwAAAAD4ic8wOH/+fOXl5ekXv/iF7Ha73nzzTc2dOzcQtQEAAAAA/MRnGKyvr2/0BM9rrrnmZ3+9AwAAAAAgtPgMg23btlVlZaU3AG7durVZvqoBAAAAABA8Ph8gM2HCBI0ePVrV1dW66667VFFRoXnz5gWiNgAAAACAn/gMg//6r/+qvLw8ffbZZ2poaFBMTIw6deoUiNoAAAAAAH7i8zbRHTt26IknnlBCQoIuvfRSjRo1Sl9//XUgagMAAAAA+InPMDh16lTdcccdkqSePXtq3Lhxys7O9nthAAAAAAD/8RkGjx8/rgEDBniXb731VtXU1Pi1KAAAAACAf/kMgxaLRTt27PAu79q1S61a+dwNAAAAABDCfD5A5tFHH9WIESN09dVXS5K+/vpr5ebm+r0wAAAAAID/+AyD/fv3V3FxsT799FOFhYXpuuuu08UXXxyI2gAAAAAAftLk/Z6bNm2SJK1du1alpaUyDEMej0elpaVau3ZtwAoEAAAAADS/Jq8M/vWvf1VcXJwWL158yjqLxaLExES/FgYAAAAA8J8mw+AzzzwjSd4w6PF4ZBiGbDZbYCoDAAAAAPiNz8eCHjp0SPfff79iYmLUu3dvjRw5UlVVVYGoDQAAAADgJz7D4PTp03XdddeppKREJSUlio2N1dSpUwNQGgAAAADAX3yGwYqKCj388MP6xS9+oU6dOumRRx7Rnj17AlEbAAAAAMBPfIZBj8cjp9PpXT5+/LgsFotfiwIAAAAA+JfP7xkcNGiQRo0apdTUVFksFi1btkxJSUmBqA0AAAAA4Cc+w+DYsWPVpUsXffDBB2poaFBqaqqGDh0aiNoAAAAAAH7iMwy++OKLuuOOO/Sf//mfgagHAAAAABAAPj8z2NDQoLvvvlv33HOPVq1aJZfLFYi6AAAAAAB+5DMMTpw4Ue+9955Gjx6tdevW6dZbb9WMGTMCURsAAAAAwE983iYqSa1atVJ0dLR2796tiooKbd261d91AQAAAAD8yGcYXLdunZYtW6bPP/9cAwcO1IwZM9SrV69A1AYAAAAA8BOfYfDVV1/VnXfeqZdeeklt2rQJRE0AAAAAAD/zGQaXLl0ql8ul48ePq66uzjvesWNHvxYGAAAAAPCfswqDM2bMkNvtlmEYkiSLxaLy8nK/FwcAAAAA8A+fYfDPf/6z3nrrLT4nCAAAAAAtiM+vlvjlL39JEAQAAACAFsZnGLz55pv15ptvqqqqSv/85z+9PwAAAACAC5fP20T/9Kc/yeVyafr06d4xPjMIAAAAABc2n2Fw+/bt53zwmpoapaWl6b/+67902WWX6amnnlJpaanatm0rSXr44Yc1YMAAlZeXKzMzU7W1tYqNjdW0adNktVpVWVmpiRMn6tChQ7riiiuUm5urdu3anXM9AAAAAIAfNRkGv/jiizPu6OtzhNu2bVNWVpYqKiq8Y2VlZXrjjTdkt9sbbTtx4kQ988wziomJUUZGhvLy8jR8+HBNmzZNw4cPl8Ph0Pz587VgwQJNnDjxLE4LAAAAAHAmTYbBcePGNbmTxWLR+vXrz3jgvLw8ZWdna9KkSZKk48ePq7KyUhkZGaqqqtKAAQP08MMPa//+/aqrq1NMTIwkKTU1VXPnztUdd9yhLVu2aP78+d7xu+++mzAIAAAAAM2gyTC4YcOG8zrws88+22j54MGD6tevn7Kzs9WhQwc9+OCDys/PV48ePRQREeHdLiIiQlVVVTp8+LDat28vq9XaaBwAAAAAcP58fmawuXTr1s17lU+SRowYoYKCAnXv3l0Wi8U7bhiGLBaL9/eJTl4+G2VlZede9ElKS0ub7Vg4e3379j3vY9C75sX7GRroQ/DRg9BAH0IDfQg+ehAaLqQ+BCwM7ty5UxUVFUpKSpL0Y+izWq3q0qWLqqurvdsdPHhQdrtdnTt31rFjx1RfX6+wsDBVV1ef8lnDsxEdHa3w8PDzrr+0tLRZQgmCg941H+ZCaKAPwfxxrpsAABUxSURBVEcPQgN9CA30IfjoQWgItT44nc4zXhzz+T2DzcUwDM2YMUNHjhyR2+3W22+/rQEDBigyMlLh4eHeBF1YWKj4+HjZbDbFxsaqqKhIklRQUKD4+PhAlQsAAAAALVrArgxGRUXpgQce0LBhw+TxeJSYmKjk5GRJUm5urrKyslRTU6NevXpp5MiRkqTs7GxNnjxZCxcuVNeuXTVr1qxAlQsAAAAALZrfw+CJD6JJT09Xenr6KdtERUUpPz//lPHIyEgtXrzYr/UBAAAAgBkF7DZRAAAAAEDoIAwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAkRBgEAAADAhAiDAAAAAGBChEEAAAAAMCHCIAAAAACYEGEQAAAAAEyIMAgAAAAAJkQYBAAAAAATIgwCAAAAgAn5NQzW1NQoOTlZe/fulSSVlJQoJSVFiYmJmj17tne78vJypaamKikpSZmZmfJ4PJKkyspKpaena+DAgRozZoxqa2v9WS4AAAAAmIbfwuC2bds0bNgwVVRUSJLq6uqUkZGhBQsWqKioSGVlZdq4caMkaeLEiZoyZYrWrFkjwzCUl5cnSZo2bZqGDx+u4uJiRUdHa8GCBf4qFwAAAABMxW9hMC8vT9nZ2bLb7ZKk7du36/LLL1e3bt1ktVqVkpKi4uJi7du3T3V1dYqJiZEkpaamqri4WG63W1u2bFFSUlKjcQAAAADA+bP668DPPvtso+UDBw4oIiLCu2y321VVVXXKeEREhKqqqnT48GG1b99eVqu10TgAAAAA4Pz5LQyerKGhQRaLxbtsGIYsFkuT4z/9PtHJy2ejrKzs3Is+SWlpabMdC2evb9++530Mete8eD9DA30IPnoQGuhDaKAPwUcPQsOF1IeAhcEuXbqourrau1xdXS273X7K+MGDB2W329W5c2cdO3ZM9fX1CgsL827/c0VHRys8PPy86y8tLW2WUILgoHfNh7kQGuhD8NGD0EAfQgN9CD56EBpCrQ9Op/OMF8cC9tUS1113nXbv3q1vvvlG9fX1WrVqleLj4xUZGanw8HBvgi4sLFR8fLxsNptiY2NVVFQkSSooKFB8fHygygUAAACAFi1gVwbDw8OVk5OjcePGyel0KiEhQQMHDpQk5ebmKisrSzU1NerVq5dGjhwpScrOztbkyZO1cOFCde3aVbNmzQpUuQAAAADQovk9DG7YsMH7d1xcnFasWHHKNlFRUcrPzz9lPDIyUosXL/ZrfQAAAABgRgG7TRQAAAAAEDoIgwAAAABgQoRBAAAAADAhwiAAAAAAmBBhEAAAAABMiDAIAAAAACZEGAQAAAAAEyIMAgAAAIAJEQYBAAAAwIQIgwAAAABgQoRBtHgud/05rQMAAABaMmuwCwD8rbUtTCkTCk+7buWLgwNcDQAAABAauDIIAAAAACZEGAQAAAAAEyIMAgAAAIAJEQYBAAAAwIQIgwAAAABgQoRBAAAAADAhwiAAAAAAmBBhEAAAAABMiDAIAAAAACZEGAQAAAAAEyIMAgAAAIAJEQYBAAAAwIQIgwAAAABgQoRBAAAAADAhwiAAAAAAmBBhEAAAAABMiDAIAAAAACZEGAQAAAAAEyIMAgAAAIAJEQYBAAAAwIQIgwAAAABgQtZgvOiIESP0/fffy2r98eWnT5+u2tpaPffcc3I6nbrttts0fvx4SVJ5ebkyMzNVW1ur2NhYTZs2zbsfAAAAAODcBDxVGYahiooKvfvuu95QV1dXp4EDB2rx4sXq2rWrHnzwQW3cuFEJCQmaOHGinnnmGcXExCgjI0N5eXkaPnx4oMsGAAAAgBYl4LeJfv3115Kk0aNH6/bbb9cbb7yh7du36/LLL1e3bt1ktVqVkpKi4uJi7du3T3V1dYqJiZEkpaamqri4ONAlAwAAAECLE/AwePToUcXFxWn+/Pl6/fXXtXTpUlVWVioiIsK7jd1uV1VVlQ4cONBoPCIiQlVVVYEuGQAAAABanIDfJtqnTx/16dPHuzx06FDNnTtXffv29Y4ZhiGLxaKGhgZZLJZTxn+OsrKy8y/6/ystLW22Y+Hsnfjfhj/Q15+P9yw00IfgowehgT6EBvoQfPQgNFxIfQh4GNy6davcbrfi4uIk/RjwIiMjVV1d7d2murpadrtdXbp0aTR+8OBB2e32n/V60dHRCg8PP++6S0tL/R5KEBz09edhLoQG+hB89CA00IfQQB+Cjx6EhlDrg9PpPOPFsYDfJnrs2DHNnDlTTqdTNTU1Wr58uR5//HHt3r1b33zzjerr67Vq1SrFx8crMjJS4eHh3nRdWFio+Pj4QJcMAAAAAC1OwK8M9u/fX9u2bdOQIUPU0NCg4cOHq0+fPsrJydG4cePkdDqVkJCggQMHSpJyc3OVlZWlmpoa9erVSyNHjgx0yQAAAADQ4gTlC/see+wxPfbYY43G4uLitGLFilO2jYqKUn5+fqBKAwAAAABTCPhtogAAAACA4CMMAgAAAIAJEQYBAAAAwIQIgwAAAABgQoRBAAAAADAhwiAAAAAAmBBhEAAAAABMiDAIAAAAACZEGAQAAAAAEyIMAgAAAIAJEQYBAAAAwIQIgwAAAABgQoRBAAAAADAhwiAAAAAAmBBhEAAAAABMiDAIAAAAACZEGAQAAAAAEyIMwtRc7vrzWg8AAABcqKzBLgAIpta2MKVMKGxy/coXBwewGgAAACBwuDIInMGZrgxy1RAAAAAXMq4MAmdwpiuHXDUEAADAhYwrgwAAAABgQoRBAAAAADAhwiAAAAAAmBBhEAAAAABMiDAIAAAAACZEGAQAAAAAEyIMAgAAAIAJEQYBAAAAwIQIgwAAAABgQoRBhASXuz7YJQAAAACmYg12AYAktbaFKWVC4WnXrXxxcICrOTsud71a28LOeT0AAAAQTIRB4BydKcBK0rKc5DPuT1gEAABAMF0QYXDlypVauHChPB6P7rnnHqWnpwe7JMAnX2ExVK94AgAAwBxCPgxWVVVp9uzZ+stf/qLWrVsrLS1N//Zv/6arrroq2KUBAAAAwAUr5B8gU1JSon79+qljx4666KKLlJSUpOLi4mCXBZy3Mz00hwfqAAAAwN9C/srggQMHFBER4V222+3avn27z/0Mw5AkuVyuZqvF6XQ227HMxu2pl8165s/HdWx3+vVOp7PJdee7Plj7SpLR4NGIKatPu27hk7fIaDjDw2k89WrdxPt5pnXS2fXCF+ZCaKAPwUcPQgN9CA30IfjoQWgIpT78lIV+ykYnsxhNrQkRCxculNPp1GOPPSZJysvLU1lZmaZPn37G/Y4dO6Yvv/wyECUCAAAAQMi6+uqr1aFDh1PGQ/7KYJcuXbR161bvcnV1tex2u8/92rVrp6uvvlo2m00Wi8WfJQIAAABAyDEMQ263W+3atTvt+pAPgzfeeKPmzZun77//Xm3bttXatWv19NNP+9yvVatWp02/AAAAAGAWbdq0aXJdyIfBSy65ROPHj9fIkSPldrs1dOhQ9e7dO9hlAQAAAMAFLeQ/MwgAAAAAaH4h/9USAAAAAIDmRxgEAAAAABMiDAIAAACACREGAQAAAMCECIMAAAAAYEKEwTNYvny5br75Zg0ePFiDBw/W7NmzJUlHjx7VAw88oNtuu03p6emqrq4OcqUt38qVKzVo0CAlJiZqyZIlwS7HNEaMGCGHw+GdA9u2bVNJSYlSUlKUmJjonRPwj5qaGiUnJ2vv3r2S1OR7X15ertTUVCUlJSkzM1MejydYJbc4J/fgqaeeUmJiondOrFu3ThI98KeXX35ZDodDDodDM2fOlMRcCIbT9YH5EHhz5szRoEGD5HA49Nprr0liPgTa6XpwQc8FA02aPn26sXLlylPGp02bZrzyyiuGYRjG8uXLjUcffTTQpZnKd999Z/Tv3984fPiwUVtba6SkpBhfffVVsMtq8RoaGoybb77ZcLvd3rHjx48bCQkJxp49ewy3222MHj3aeO+994JYZcv1+eefG8nJyUavXr2Mb7/99ozvvcPhMD777DPDMAzjqaeeMpYsWRLM0luMk3tgGIaRnJxsVFVVnbItPfCPjz76yLjrrrsMp9NpuFwuY+TIkcbKlSuZCwF2uj6sXbuW+RBgH3/8sZGWlma43W7j+PHjRv/+/Y3y8nLmQwCdrge7du26oOcCVwbP4O9//7uWL1+ulJQUPfHEEzpy5Igk6b333lNKSookKTk5We+//77cbncwS23RSkpK1K9fP3Xs2FEXXXSRkpKSVFxcHOyyWryvv/5akjR69GjdfvvteuONN7R9+3Zdfvnl6tatm6xWq1JSUuiFn+Tl5Sk7O1t2u12Smnzv9+3bp7q6OsXExEiSUlNT6UkzObkHx48fV2VlpTIyMpSSkqK5c+eqoaGBHvhRRESEJk+erNatW8tms6l79+6qqKhgLgTY6fpQWVnJfAiwG264QYsWLZLVatWhQ4dUX1+vo0ePMh8C6HQ9aNOmzQU9FwiDZxAREaE//OEPWrFihbp27arp06dLkg4cOKCIiAhJktVqVfv27fX9998Hs9QW7cT3W5LsdruqqqqCWJE5HD16VHFxcZo/f75ef/11LV26VJWVlfQiQJ599lnFxsZ6l5uaByePR0RE0JNmcnIPDh48qH79+mnGjBnKy8vT1q1blZ+fTw/8qEePHt7/IVVRUaHVq1fLYrEwFwLsdH347W9/y3wIApvNprlz58rhcCguLo5/G4Lg5B54PJ4Lei4QBiWtXr1a8fHxjX5GjRql+fPnq2/fvrJYLLrvvvv0wQcfnHZ/wzDUqhVvpb80NDTIYrF4lw3DaLQM/+jTp49mzpypDh06qHPnzho6dKjmzp1LL4KkqXnA/Aicbt26af78+bLb7Wrbtq1GjBihjRs30oMA+OqrrzR69GhNmjRJ3bp1Yy4EyYl9uPLKK5kPQfLII49o06ZN2r9/vyoqKpgPQXBiDzZt2nRBzwUSjKTbbrtN77//fqOfefPm6fXXX/duYxiGwsLCJP34/7ocPHhQkuTxeFRbW6uOHTsGo3RT6NKlS6OH9FRXV3tv24L/bN26VZs2bfIuG4ahyMhIehEkTc2Dk8cPHjxIT/xk586dWrNmjXfZMAxZrVZ64GelpaUaNWqUJkyYoP/4j/9gLgTJyX1gPgTerl27VF5eLklq27atEhMT9fHHHzMfAuh0PSgqKrqg5wJhsAkXXXSR/vznP2vbtm2SpDfeeEMDBgyQJCUkJKigoECSVFRUpNjYWNlstqDV2tLdeOON2rRpk77//nsdP35ca9euVXx8fLDLavGOHTummTNnyul0qqamRsuXL9fjjz+u3bt365tvvlF9fb1WrVpFLwLkuuuuO+17HxkZqfDwcJWWlkqSCgsL6YmfGIahGTNm6MiRI3K73Xr77bc1YMAAeuBH+/fv19ixY5WbmyuHwyGJuRAMp+sD8yHw9u7dq6ysLLlcLrlcLq1fv15paWnMhwA6XQ+uv/76C3ouWINdQKgKCwvTSy+9pKlTp6qurk6//vWvvY9SfvTRRzV58mQ5HA516NBBubm5Qa62Zbvkkks0fvx4jRw5Um63W0OHDlXv3r2DXVaL179/f23btk1DhgxRQ0ODhg8frj59+ignJ0fjxo2T0+lUQkKCBg4cGOxSTSE8PLzJ9z43N1dZWVmqqalRr169NHLkyCBX2zJFRUXpgQce0LBhw+TxeJSYmKjk5GRJ9MBfXn31VTmdTuXk5HjH0tLSmAsB1lQfmA+BlZCQoO3bt2vIkCEKCwtTYmKiHA6HOnfuzHwIkNP14OGHH1anTp0u2LlgMQzDCHYRAAAAAIDA4jZRAAAAADAhwiAAAAAAmBBhEAAAAABMiDAIAAAAACZEGAQAAAAAE+KrJQAAOIO33npLb731ljwejywWi6699lqNHz9el156qc99+/Tpo5UrV+qyyy4LQKUAAPw8hEEAAJrw/PPPa8eOHXrllVfUtWtXNTQ0aMWKFbrrrrv0zjvvqEuXLsEuEQCAc0YYBADgNL777jstXbpU7733nv7lX/5FktSqVSsNGTJEZWVleuWVV7Rx40b17t1bO3fu1OOPP65OnTrp6aeflsVi0W9+8xs1NDR4j7dhwwYtXLhQbrdbbdq00ZNPPqk+ffpo3rx5+vzzz3XgwAH17NlTY8aMUWZmplwulwzD0NChQ5Wenh6stwEA0IIRBgEAOI1t27bpyiuv9AbBE91444166aWXJEk9evTQSy+9JJfLpf79+ys3N1dxcXFatWqV8vLyJEkVFRWaPXu2Fi1apE6dOumrr77S73//e61du1aStG/fPq1atUpWq1UZGRm65ZZb9MADD6i6ulozZszQsGHD1KoVH/MHADQvwiAAAE3weDynHXe5XLJYLJKk2NhYSdKXX34pq9WquLg4SVJycrKmTJkiSfroo4904MABjRo1ynsMi8WiPXv2SJJiYmJktf74T/KAAQP05JNPavv27YqLi1NWVhZBEADgF/zrAgDAacTExOibb75RdXX1Kes+/vhj9enTR5J00UUXeccNw2i03U8Br6GhQXFxcSosLPT+5OXlqUePHqcco3///lqzZo1uu+02lZeXKyUlRd99912znx8AAIRBAABO45JLLtGIESP0+OOPq6qqyju+bNkyrV27Vvfff3+j7Xv27CnDMLRx40ZJ0vr163XkyBFJUlxcnD766CPt2rVLkrRx40bdfvvtqqurO+V1J0yYoKKiIjkcDmVnZ6t9+/beK4gAADQnbhMFAKAJEyZM0DvvvKMxY8bI5XLJ5XLpN7/5jZYuXarIyMhG29psNs2fP19Tp07VrFmzdM011+jiiy+WJF111VWaPn26Hn/8cRmGIavVqoULF6pdu3anvOYf/vAHZWZm6u2331ZYWJhuvfVWXX/99QE5XwCAuViMk+9pAQAAAAC0eNwmCgAAAAAmRBgEAAAAABMiDAIAAACACREGAQAAAMCECIMAAAAAYEKEQQAAAAAwIcIgAAAAAJgQYRAAAAAATOj/AZ8iBWw7cntLAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_cust_sales_history(top_20_customers, 'top 20')" ] }, { "cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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customer_idorderssales_totalsales_average
0014101506879.5911.451323
414911243132893.2422.558690
191784116939861.495.110447
111531111859284.1923.924209
121308911857322.1330.934771
11464673278778.02135.197876
10160296660369.93232.192038
61415665114335.7780.859809
21810260259657.30602.453132
9136945762961.54108.367539
13150615454250.34132.641418
15179494953215.74700.207105
31745049189575.53559.219853
7175114588138.2082.065363
17142984550862.4431.013683
8166843065920.12235.429000
16157692951823.72352.542313
51241524123638.18159.739251
14140961753258.4310.453078
18140881450415.4985.449983
\n", "
" ], "text/plain": [ " customer_id orders sales_total sales_average\n", "0 0 1410 1506879.59 11.451323\n", "4 14911 243 132893.24 22.558690\n", "19 17841 169 39861.49 5.110447\n", "11 15311 118 59284.19 23.924209\n", "12 13089 118 57322.13 30.934771\n", "1 14646 73 278778.02 135.197876\n", "10 16029 66 60369.93 232.192038\n", "6 14156 65 114335.77 80.859809\n", "2 18102 60 259657.30 602.453132\n", "9 13694 57 62961.54 108.367539\n", "13 15061 54 54250.34 132.641418\n", "15 17949 49 53215.74 700.207105\n", "3 17450 49 189575.53 559.219853\n", "7 17511 45 88138.20 82.065363\n", "17 14298 45 50862.44 31.013683\n", "8 16684 30 65920.12 235.429000\n", "16 15769 29 51823.72 352.542313\n", "5 12415 24 123638.18 159.739251\n", "14 14096 17 53258.43 10.453078\n", "18 14088 14 50415.49 85.449983" ] }, "execution_count": 108, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top_20_customers.sort_values(by = 'orders', ascending = False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "Of the Top 20 customers, 90% made for than 24 orders (we are disregarding customer_id of \"zero\", since these were the unknown customers)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cohort Analysis" ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [], "source": [ "first_order_date_by_customers = df.groupby('customer_id')['invoice_date'].min()" ] }, { "cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [], "source": [ "first_order_date_by_customers.name = 'first_order_date'" ] }, { "cell_type": "code", "execution_count": 111, "metadata": {}, "outputs": [], "source": [ "df = df.join(first_order_date_by_customers, on = 'customer_id')" ] }, { "cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_pricefirst_order_date
053636585123AWHITE HANGING HEART T-LIGHT HOLDER62018-11-29 08:26:002.551785015.302018-11-29 08:26:00
153636571053WHITE METAL LANTERN62018-11-29 08:26:003.391785020.342018-11-29 08:26:00
253636584406BCREAM CUPID HEARTS COAT HANGER82018-11-29 08:26:002.751785022.002018-11-29 08:26:00
353636584029GKNITTED UNION FLAG HOT WATER BOTTLE62018-11-29 08:26:003.391785020.342018-11-29 08:26:00
453636584029ERED WOOLLY HOTTIE WHITE HEART.62018-11-29 08:26:003.391785020.342018-11-29 08:26:00
\n", "
" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "0 536365 85123A WHITE HANGING HEART T-LIGHT HOLDER 6 \n", "1 536365 71053 WHITE METAL LANTERN 6 \n", "2 536365 84406B CREAM CUPID HEARTS COAT HANGER 8 \n", "3 536365 84029G KNITTED UNION FLAG HOT WATER BOTTLE 6 \n", "4 536365 84029E RED WOOLLY HOTTIE WHITE HEART. 6 \n", "\n", " invoice_date unit_price customer_id total_price \\\n", "0 2018-11-29 08:26:00 2.55 17850 15.30 \n", "1 2018-11-29 08:26:00 3.39 17850 20.34 \n", "2 2018-11-29 08:26:00 2.75 17850 22.00 \n", "3 2018-11-29 08:26:00 3.39 17850 20.34 \n", "4 2018-11-29 08:26:00 3.39 17850 20.34 \n", "\n", " first_order_date \n", "0 2018-11-29 08:26:00 \n", "1 2018-11-29 08:26:00 \n", "2 2018-11-29 08:26:00 \n", "3 2018-11-29 08:26:00 \n", "4 2018-11-29 08:26:00 " ] }, "execution_count": 112, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [], "source": [ "df['first_order_month'] = df['first_order_date'].astype('datetime64[M]')" ] }, { "cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [], "source": [ "df['order_month'] = df['invoice_date'].astype('datetime64[M]')" ] }, { "cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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invoice_nostock_codedescriptionquantityinvoice_dateunit_pricecustomer_idtotal_pricefirst_order_datefirst_order_monthorder_month
52982158075421670BLUE SPOT CERAMIC DRAWER KNOB62019-12-04 10:05:003.29019.742018-11-29 14:32:002018-11-012019-12-01
22615555678122846BREAD BIN DINER STYLE RED12019-06-12 12:47:0016.951338416.952019-06-12 12:47:002019-06-012019-06-01
50849957919621080SET/20 RED RETROSPOT PAPER NAPKINS42019-11-26 15:54:000.83140963.322019-08-28 10:49:002019-08-012019-11-01
4862354046921289LARGE STRIPES CHOCOLATE GIFT BAG162019-01-05 14:04:001.251248420.002019-01-05 14:04:002019-01-012019-01-01
47701557704622754SMALL RED BABUSHKA NOTEBOOK122019-11-15 13:46:000.851244910.202019-06-03 15:37:002019-06-012019-11-01
51907358013616169EWRAP 50'S CHRISTMAS12019-11-29 19:42:000.42178410.422018-11-29 14:30:002018-11-012019-11-01
23315155744284931BBLUE SCOTTIE DOG W FLOWER PATTERN22019-06-18 12:53:002.55148085.102019-06-18 12:53:002019-06-012019-06-01
35601656798121243PINK POLKADOT PLATE22019-09-21 11:22:003.2906.582018-11-29 14:32:002018-11-012019-09-01
10800554547521094SET/6 RED SPOTTY PAPER PLATES962019-03-01 10:59:000.641241561.442019-01-04 11:12:002019-01-012019-03-01
16957355119321746SMALL RED RETROSPOT WINDMILL42019-04-25 11:05:001.25179545.002018-12-01 14:18:002018-12-012019-04-01
38169856988723356LOVE HOT WATER BOTTLE32019-10-04 15:28:005.951388217.852019-10-04 15:28:002019-10-012019-10-01
34505756714022429ENAMEL MEASURING JUG CREAM82019-09-14 14:47:004.251541034.002019-03-21 10:15:002019-03-012019-09-01
7495954253620677PINK POLKADOT BOWL22019-01-26 13:37:002.4604.922018-11-29 14:32:002018-11-012019-01-01
32419556539622111SCOTTIE DOG HOT WATER BOTTLE12019-08-31 16:39:0010.79010.792018-11-29 14:32:002018-11-012019-08-01
34458456708520750RED RETROSPOT MINI CASES22019-09-14 12:38:007.951243415.902018-12-12 11:12:002018-12-012019-09-01
7093854210722720SET OF 3 CAKE TINS PANTRY DESIGN12019-01-23 13:38:004.95162224.952019-01-23 13:38:002019-01-012019-01-01
49770357846323368SET 12 COLOUR PENCILS DOLLY GIRL162019-11-22 12:30:000.651275710.402019-05-10 19:01:002019-05-012019-11-01
15517254997520702PINK PADDED MOBILE32019-04-11 14:38:004.251617512.752019-04-11 14:38:002019-04-012019-04-01
6605054171121976PACK OF 60 MUSHROOM CAKE CASES1202019-01-19 11:18:000.421464650.402018-12-18 10:09:002018-12-012019-01-01
49658757834720782CAMOUFLAGE EAR MUFF HEADPHONES12019-11-22 09:26:0010.79010.792018-11-29 14:32:002018-11-012019-11-01
42217357306822728ALARM CLOCK BAKELIKE PINK22019-10-25 13:56:003.75175457.502019-10-25 13:48:002019-10-012019-10-01
43320457390523254CHILDRENS CUTLERY DOLLY GIRL12019-10-30 15:06:004.15169714.152019-10-30 15:06:002019-10-012019-10-01
18825155301720676RED RETROSPOT BOWL52019-05-10 19:01:001.25127576.252019-05-10 19:01:002019-05-012019-05-01
35914156817723366SET 12 COLOURING PENCILS DOILY162019-09-23 13:30:000.651353610.402019-09-23 13:30:002019-09-012019-09-01
10945754563821430SET/3 RED GINGHAM ROSE STORAGE BOX242019-03-02 12:26:003.391311381.362018-12-06 13:07:002018-12-012019-03-01
22858755693221422PORCELAIN ROSE SMALL12019-06-13 15:41:001.6301.632018-11-29 14:32:002018-11-012019-06-01
38783357038822045SPACEBOY GIFT WRAP252019-10-08 12:37:000.421491110.502018-11-29 14:05:002018-11-012019-10-01
50077157880821775DECORATIVE FLORE BATHROOM BOTTLE32019-11-23 13:23:001.25163273.752018-12-03 12:43:002018-12-012019-11-01
12872654735821086SET/6 RED SPOTTY PAPER CUPS42019-03-20 12:25:000.65159982.602018-12-10 13:32:002018-12-012019-03-01
18234655253921175GIN + TONIC DIET METAL SIGN122019-05-08 10:17:002.55030.602018-11-29 14:32:002018-11-012019-05-01
34866156746121239PINK POLKADOT CUP32019-09-18 12:31:001.6304.892018-11-29 14:32:002018-11-012019-09-01
6642154179422327ROUND SNACK BOXES SET OF 4 SKULLS12019-01-19 13:21:002.95172382.952018-12-01 15:05:002018-12-012019-01-01
50569157909422326ROUND SNACK BOXES SET OF4 WOODLAND62019-11-26 10:56:002.951266817.702018-12-17 12:46:002018-12-012019-11-01
50716457916723333IVORY WICKER HEART MEDIUM62019-11-26 14:06:001.25168007.502019-11-26 14:06:002019-11-012019-11-01
1989553790085172HYACINTH BULB T-LIGHT CANDLES322018-12-07 10:45:000.421598313.442018-11-29 12:15:002018-11-012018-12-01
22765755689021929JUMBO BAG PINK VINTAGE PAISLEY202019-06-13 12:48:002.081758141.602018-11-30 14:47:002018-11-012019-06-01
42153657299721803CHRISTMAS TREE STAR DECORATION362019-10-25 11:24:000.421787815.122019-10-25 11:24:002019-10-012019-10-01
49391057825521985PACK OF 12 HEARTS DESIGN TISSUES52019-11-21 12:58:000.39146751.952019-11-21 12:58:002019-11-012019-11-01
38816757042082580BATHROOM METAL SIGN12019-10-08 13:33:000.55178410.552018-11-29 14:30:002018-11-012019-10-01
6933554196922169FAMILY ALBUM WHITE PICTURE FRAME12019-01-22 13:46:0016.63016.632018-11-29 14:32:002018-11-012019-01-01
16159655047722378WALL TIDY RETROSPOT32019-04-16 14:01:002.10173386.302018-12-11 12:57:002018-12-012019-04-01
38076456983422554PLASTERS IN TIN WOODLAND ANIMALS122019-10-04 13:00:001.651438319.802019-06-27 10:18:002019-06-012019-10-01
46069957593021174POTTERING IN THE SHED METAL SIGN12019-11-09 17:58:004.1304.132018-11-29 14:32:002018-11-012019-11-01
44311857469022664TOY TIDY DOLLY GIRL DESIGN52019-11-04 13:11:002.101263810.502019-11-04 13:11:002019-11-012019-11-01
12093054668421535RED RETROSPOT SMALL MILK JUG242019-03-14 09:47:002.551615261.202019-03-14 09:47:002019-03-012019-03-01
16068755046822549PICTURE DOMINOES122019-04-16 13:43:001.451670017.402018-12-06 16:34:002018-12-012019-04-01
40663657182423494VINTAGE DOILY DELUXE SEWING KIT32019-10-17 11:49:005.951247217.852018-11-29 14:33:002018-11-012019-10-01
53993658145022720SET OF 3 CAKE TINS PANTRY DESIGN32019-12-06 17:54:004.951679414.852019-06-10 14:15:002019-06-012019-12-01
51654657992722984CARD GINGHAM ROSE122019-11-29 09:20:000.42125725.042019-10-17 08:20:002019-10-012019-11-01
12321954689222241GARLAND WOODEN HAPPY EASTER12019-03-15 18:20:002.4602.462018-11-29 14:32:002018-11-012019-03-01
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" ], "text/plain": [ " invoice_no stock_code description quantity \\\n", "529821 580754 21670 BLUE SPOT CERAMIC DRAWER KNOB 6 \n", "226155 556781 22846 BREAD BIN DINER STYLE RED 1 \n", "508499 579196 21080 SET/20 RED RETROSPOT PAPER NAPKINS 4 \n", "48623 540469 21289 LARGE STRIPES CHOCOLATE GIFT BAG 16 \n", "477015 577046 22754 SMALL RED BABUSHKA NOTEBOOK 12 \n", "519073 580136 16169E WRAP 50'S CHRISTMAS 1 \n", "233151 557442 84931B BLUE SCOTTIE DOG W FLOWER PATTERN 2 \n", "356016 567981 21243 PINK POLKADOT PLATE 2 \n", "108005 545475 21094 SET/6 RED SPOTTY PAPER PLATES 96 \n", "169573 551193 21746 SMALL RED RETROSPOT WINDMILL 4 \n", "381698 569887 23356 LOVE HOT WATER BOTTLE 3 \n", "345057 567140 22429 ENAMEL MEASURING JUG CREAM 8 \n", "74959 542536 20677 PINK POLKADOT BOWL 2 \n", "324195 565396 22111 SCOTTIE DOG HOT WATER BOTTLE 1 \n", "344584 567085 20750 RED RETROSPOT MINI CASES 2 \n", "70938 542107 22720 SET OF 3 CAKE TINS PANTRY DESIGN 1 \n", "497703 578463 23368 SET 12 COLOUR PENCILS DOLLY GIRL 16 \n", "155172 549975 20702 PINK PADDED MOBILE 3 \n", "66050 541711 21976 PACK OF 60 MUSHROOM CAKE CASES 120 \n", "496587 578347 20782 CAMOUFLAGE EAR MUFF HEADPHONES 1 \n", "422173 573068 22728 ALARM CLOCK BAKELIKE PINK 2 \n", "433204 573905 23254 CHILDRENS CUTLERY DOLLY GIRL 1 \n", "188251 553017 20676 RED RETROSPOT BOWL 5 \n", "359141 568177 23366 SET 12 COLOURING PENCILS DOILY 16 \n", "109457 545638 21430 SET/3 RED GINGHAM ROSE STORAGE BOX 24 \n", "228587 556932 21422 PORCELAIN ROSE SMALL 1 \n", "387833 570388 22045 SPACEBOY GIFT WRAP 25 \n", "500771 578808 21775 DECORATIVE FLORE BATHROOM BOTTLE 3 \n", "128726 547358 21086 SET/6 RED SPOTTY PAPER CUPS 4 \n", "182346 552539 21175 GIN + TONIC DIET METAL SIGN 12 \n", "348661 567461 21239 PINK POLKADOT CUP 3 \n", "66421 541794 22327 ROUND SNACK BOXES SET OF 4 SKULLS 1 \n", "505691 579094 22326 ROUND SNACK BOXES SET OF4 WOODLAND 6 \n", "507164 579167 23333 IVORY WICKER HEART MEDIUM 6 \n", "19895 537900 85172 HYACINTH BULB T-LIGHT CANDLES 32 \n", "227657 556890 21929 JUMBO BAG PINK VINTAGE PAISLEY 20 \n", "421536 572997 21803 CHRISTMAS TREE STAR DECORATION 36 \n", "493910 578255 21985 PACK OF 12 HEARTS DESIGN TISSUES 5 \n", "388167 570420 82580 BATHROOM METAL SIGN 1 \n", "69335 541969 22169 FAMILY ALBUM WHITE PICTURE FRAME 1 \n", "161596 550477 22378 WALL TIDY RETROSPOT 3 \n", "380764 569834 22554 PLASTERS IN TIN WOODLAND ANIMALS 12 \n", "460699 575930 21174 POTTERING IN THE SHED METAL SIGN 1 \n", "443118 574690 22664 TOY TIDY DOLLY GIRL DESIGN 5 \n", "120930 546684 21535 RED RETROSPOT SMALL MILK JUG 24 \n", "160687 550468 22549 PICTURE DOMINOES 12 \n", "406636 571824 23494 VINTAGE DOILY DELUXE SEWING KIT 3 \n", "539936 581450 22720 SET OF 3 CAKE TINS PANTRY DESIGN 3 \n", "516546 579927 22984 CARD GINGHAM ROSE 12 \n", "123219 546892 22241 GARLAND WOODEN HAPPY EASTER 1 \n", "\n", " invoice_date unit_price customer_id total_price \\\n", "529821 2019-12-04 10:05:00 3.29 0 19.74 \n", "226155 2019-06-12 12:47:00 16.95 13384 16.95 \n", "508499 2019-11-26 15:54:00 0.83 14096 3.32 \n", "48623 2019-01-05 14:04:00 1.25 12484 20.00 \n", "477015 2019-11-15 13:46:00 0.85 12449 10.20 \n", "519073 2019-11-29 19:42:00 0.42 17841 0.42 \n", "233151 2019-06-18 12:53:00 2.55 14808 5.10 \n", "356016 2019-09-21 11:22:00 3.29 0 6.58 \n", "108005 2019-03-01 10:59:00 0.64 12415 61.44 \n", "169573 2019-04-25 11:05:00 1.25 17954 5.00 \n", "381698 2019-10-04 15:28:00 5.95 13882 17.85 \n", "345057 2019-09-14 14:47:00 4.25 15410 34.00 \n", "74959 2019-01-26 13:37:00 2.46 0 4.92 \n", "324195 2019-08-31 16:39:00 10.79 0 10.79 \n", "344584 2019-09-14 12:38:00 7.95 12434 15.90 \n", "70938 2019-01-23 13:38:00 4.95 16222 4.95 \n", "497703 2019-11-22 12:30:00 0.65 12757 10.40 \n", "155172 2019-04-11 14:38:00 4.25 16175 12.75 \n", "66050 2019-01-19 11:18:00 0.42 14646 50.40 \n", "496587 2019-11-22 09:26:00 10.79 0 10.79 \n", "422173 2019-10-25 13:56:00 3.75 17545 7.50 \n", "433204 2019-10-30 15:06:00 4.15 16971 4.15 \n", "188251 2019-05-10 19:01:00 1.25 12757 6.25 \n", "359141 2019-09-23 13:30:00 0.65 13536 10.40 \n", "109457 2019-03-02 12:26:00 3.39 13113 81.36 \n", "228587 2019-06-13 15:41:00 1.63 0 1.63 \n", "387833 2019-10-08 12:37:00 0.42 14911 10.50 \n", "500771 2019-11-23 13:23:00 1.25 16327 3.75 \n", "128726 2019-03-20 12:25:00 0.65 15998 2.60 \n", "182346 2019-05-08 10:17:00 2.55 0 30.60 \n", "348661 2019-09-18 12:31:00 1.63 0 4.89 \n", "66421 2019-01-19 13:21:00 2.95 17238 2.95 \n", "505691 2019-11-26 10:56:00 2.95 12668 17.70 \n", "507164 2019-11-26 14:06:00 1.25 16800 7.50 \n", "19895 2018-12-07 10:45:00 0.42 15983 13.44 \n", "227657 2019-06-13 12:48:00 2.08 17581 41.60 \n", "421536 2019-10-25 11:24:00 0.42 17878 15.12 \n", "493910 2019-11-21 12:58:00 0.39 14675 1.95 \n", "388167 2019-10-08 13:33:00 0.55 17841 0.55 \n", "69335 2019-01-22 13:46:00 16.63 0 16.63 \n", "161596 2019-04-16 14:01:00 2.10 17338 6.30 \n", "380764 2019-10-04 13:00:00 1.65 14383 19.80 \n", "460699 2019-11-09 17:58:00 4.13 0 4.13 \n", "443118 2019-11-04 13:11:00 2.10 12638 10.50 \n", "120930 2019-03-14 09:47:00 2.55 16152 61.20 \n", "160687 2019-04-16 13:43:00 1.45 16700 17.40 \n", "406636 2019-10-17 11:49:00 5.95 12472 17.85 \n", "539936 2019-12-06 17:54:00 4.95 16794 14.85 \n", "516546 2019-11-29 09:20:00 0.42 12572 5.04 \n", "123219 2019-03-15 18:20:00 2.46 0 2.46 \n", "\n", " first_order_date first_order_month order_month \n", "529821 2018-11-29 14:32:00 2018-11-01 2019-12-01 \n", "226155 2019-06-12 12:47:00 2019-06-01 2019-06-01 \n", "508499 2019-08-28 10:49:00 2019-08-01 2019-11-01 \n", "48623 2019-01-05 14:04:00 2019-01-01 2019-01-01 \n", "477015 2019-06-03 15:37:00 2019-06-01 2019-11-01 \n", "519073 2018-11-29 14:30:00 2018-11-01 2019-11-01 \n", "233151 2019-06-18 12:53:00 2019-06-01 2019-06-01 \n", "356016 2018-11-29 14:32:00 2018-11-01 2019-09-01 \n", "108005 2019-01-04 11:12:00 2019-01-01 2019-03-01 \n", "169573 2018-12-01 14:18:00 2018-12-01 2019-04-01 \n", "381698 2019-10-04 15:28:00 2019-10-01 2019-10-01 \n", "345057 2019-03-21 10:15:00 2019-03-01 2019-09-01 \n", "74959 2018-11-29 14:32:00 2018-11-01 2019-01-01 \n", "324195 2018-11-29 14:32:00 2018-11-01 2019-08-01 \n", "344584 2018-12-12 11:12:00 2018-12-01 2019-09-01 \n", "70938 2019-01-23 13:38:00 2019-01-01 2019-01-01 \n", "497703 2019-05-10 19:01:00 2019-05-01 2019-11-01 \n", "155172 2019-04-11 14:38:00 2019-04-01 2019-04-01 \n", "66050 2018-12-18 10:09:00 2018-12-01 2019-01-01 \n", "496587 2018-11-29 14:32:00 2018-11-01 2019-11-01 \n", "422173 2019-10-25 13:48:00 2019-10-01 2019-10-01 \n", "433204 2019-10-30 15:06:00 2019-10-01 2019-10-01 \n", "188251 2019-05-10 19:01:00 2019-05-01 2019-05-01 \n", "359141 2019-09-23 13:30:00 2019-09-01 2019-09-01 \n", "109457 2018-12-06 13:07:00 2018-12-01 2019-03-01 \n", "228587 2018-11-29 14:32:00 2018-11-01 2019-06-01 \n", "387833 2018-11-29 14:05:00 2018-11-01 2019-10-01 \n", "500771 2018-12-03 12:43:00 2018-12-01 2019-11-01 \n", "128726 2018-12-10 13:32:00 2018-12-01 2019-03-01 \n", "182346 2018-11-29 14:32:00 2018-11-01 2019-05-01 \n", "348661 2018-11-29 14:32:00 2018-11-01 2019-09-01 \n", "66421 2018-12-01 15:05:00 2018-12-01 2019-01-01 \n", "505691 2018-12-17 12:46:00 2018-12-01 2019-11-01 \n", "507164 2019-11-26 14:06:00 2019-11-01 2019-11-01 \n", "19895 2018-11-29 12:15:00 2018-11-01 2018-12-01 \n", "227657 2018-11-30 14:47:00 2018-11-01 2019-06-01 \n", "421536 2019-10-25 11:24:00 2019-10-01 2019-10-01 \n", "493910 2019-11-21 12:58:00 2019-11-01 2019-11-01 \n", "388167 2018-11-29 14:30:00 2018-11-01 2019-10-01 \n", "69335 2018-11-29 14:32:00 2018-11-01 2019-01-01 \n", "161596 2018-12-11 12:57:00 2018-12-01 2019-04-01 \n", "380764 2019-06-27 10:18:00 2019-06-01 2019-10-01 \n", "460699 2018-11-29 14:32:00 2018-11-01 2019-11-01 \n", "443118 2019-11-04 13:11:00 2019-11-01 2019-11-01 \n", "120930 2019-03-14 09:47:00 2019-03-01 2019-03-01 \n", "160687 2018-12-06 16:34:00 2018-12-01 2019-04-01 \n", "406636 2018-11-29 14:33:00 2018-11-01 2019-10-01 \n", "539936 2019-06-10 14:15:00 2019-06-01 2019-12-01 \n", "516546 2019-10-17 08:20:00 2019-10-01 2019-11-01 \n", "123219 2018-11-29 14:32:00 2018-11-01 2019-03-01 " ] }, "execution_count": 115, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.sample(50)" ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [], "source": [ "aggregations = {\n", " 'num_of_orders': ('invoice_no', 'nunique'),\n", " 'num_of_customers' : ('customer_id', 'nunique'),\n", " 'sales_total': ('total_price','sum')\n", "}\n", "\n", "\n", "cohort_grouped = df.groupby('first_order_month').agg(**aggregations)" ] }, { "cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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num_of_ordersnum_of_customerssales_total
first_order_month
2018-11-0145332052.791599e+06
2018-12-0170127433.109304e+06
2019-01-0128214731.075818e+06
2019-02-0116923655.095876e+05
2019-03-0117354145.661178e+05
2019-04-019892852.895956e+05
2019-05-019362912.784896e+05
2019-06-017032252.063646e+05
2019-07-015302011.591624e+05
2019-08-013921621.625227e+05
2019-09-016752892.186757e+05
2019-10-017073762.162994e+05
2019-11-014323021.319079e+05
2019-12-0134312.457762e+04
\n", "
" ], "text/plain": [ " num_of_orders num_of_customers sales_total\n", "first_order_month \n", "2018-11-01 4533 205 2.791599e+06\n", "2018-12-01 7012 743 3.109304e+06\n", "2019-01-01 2821 473 1.075818e+06\n", "2019-02-01 1692 365 5.095876e+05\n", "2019-03-01 1735 414 5.661178e+05\n", "2019-04-01 989 285 2.895956e+05\n", "2019-05-01 936 291 2.784896e+05\n", "2019-06-01 703 225 2.063646e+05\n", "2019-07-01 530 201 1.591624e+05\n", "2019-08-01 392 162 1.625227e+05\n", "2019-09-01 675 289 2.186757e+05\n", "2019-10-01 707 376 2.162994e+05\n", "2019-11-01 432 302 1.319079e+05\n", "2019-12-01 34 31 2.457762e+04" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cohort_grouped" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "We would expect that revenue from every cohort be lower than that of the previous one since customers from older cohorts would have had more time to place orders. However, there was a huge (more than 2x) spike in the second cohort (December, 2018), which could possibly be attributed to the Christmas holiday.\n", "\n", "Additionally, the March 2019 cohort was also (albeit slightly) higher than the February 2019 cohort, as well as May compared to April, September to August, and October to September.\n", "\n", "December 2019 cohort was very small, due to the fact the data collected ends on 2019-12-07." ] }, { "cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Timestamp('2019-12-07 12:50:00')" ] }, "execution_count": 118, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['invoice_date'].max()" ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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order_month2018-11-012018-12-012019-01-012019-02-012019-03-012019-04-012019-05-012019-06-012019-07-012019-08-012019-09-012019-10-012019-11-012019-12-01
first_order_month
2018-11-01205.093.080.070.077.079.083.081.072.076.081.080.099.039.0
2018-12-01NaN743.0295.0236.0289.0250.0298.0264.0263.0261.0280.0296.0387.0161.0
2019-01-01NaNNaN473.0110.0130.0113.0157.0134.0127.0126.0141.0158.0177.045.0
2019-02-01NaNNaNNaN365.090.066.0103.099.086.085.0100.099.0110.024.0
2019-03-01NaNNaNNaNNaN414.077.0110.083.0103.078.0102.0107.0113.032.0
2019-04-01NaNNaNNaNNaNNaN285.065.061.062.058.066.066.078.017.0
2019-05-01NaNNaNNaNNaNNaNNaN291.067.049.049.062.072.084.015.0
2019-06-01NaNNaNNaNNaNNaNNaNNaN225.050.043.058.060.072.014.0
2019-07-01NaNNaNNaNNaNNaNNaNNaNNaN201.045.040.047.055.019.0
2019-08-01NaNNaNNaNNaNNaNNaNNaNNaNNaN162.034.043.047.016.0
2019-09-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN289.088.097.031.0
2019-10-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN376.0104.037.0
2019-11-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN302.023.0
2019-12-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN31.0
\n", "
" ], "text/plain": [ "order_month 2018-11-01 2018-12-01 2019-01-01 2019-02-01 2019-03-01 \\\n", "first_order_month \n", "2018-11-01 205.0 93.0 80.0 70.0 77.0 \n", "2018-12-01 NaN 743.0 295.0 236.0 289.0 \n", "2019-01-01 NaN NaN 473.0 110.0 130.0 \n", "2019-02-01 NaN NaN NaN 365.0 90.0 \n", "2019-03-01 NaN NaN NaN NaN 414.0 \n", "2019-04-01 NaN NaN NaN NaN NaN \n", "2019-05-01 NaN NaN NaN NaN NaN \n", "2019-06-01 NaN NaN NaN NaN NaN \n", "2019-07-01 NaN NaN NaN NaN NaN \n", "2019-08-01 NaN NaN NaN NaN NaN \n", "2019-09-01 NaN NaN NaN NaN NaN \n", "2019-10-01 NaN NaN NaN NaN NaN \n", "2019-11-01 NaN NaN NaN NaN NaN \n", "2019-12-01 NaN NaN NaN NaN NaN \n", "\n", "order_month 2019-04-01 2019-05-01 2019-06-01 2019-07-01 2019-08-01 \\\n", "first_order_month \n", "2018-11-01 79.0 83.0 81.0 72.0 76.0 \n", "2018-12-01 250.0 298.0 264.0 263.0 261.0 \n", "2019-01-01 113.0 157.0 134.0 127.0 126.0 \n", "2019-02-01 66.0 103.0 99.0 86.0 85.0 \n", "2019-03-01 77.0 110.0 83.0 103.0 78.0 \n", "2019-04-01 285.0 65.0 61.0 62.0 58.0 \n", "2019-05-01 NaN 291.0 67.0 49.0 49.0 \n", "2019-06-01 NaN NaN 225.0 50.0 43.0 \n", "2019-07-01 NaN NaN NaN 201.0 45.0 \n", "2019-08-01 NaN NaN NaN NaN 162.0 \n", "2019-09-01 NaN NaN NaN NaN NaN \n", "2019-10-01 NaN NaN NaN NaN NaN \n", "2019-11-01 NaN NaN NaN NaN NaN \n", "2019-12-01 NaN NaN NaN NaN NaN \n", "\n", "order_month 2019-09-01 2019-10-01 2019-11-01 2019-12-01 \n", "first_order_month \n", "2018-11-01 81.0 80.0 99.0 39.0 \n", "2018-12-01 280.0 296.0 387.0 161.0 \n", "2019-01-01 141.0 158.0 177.0 45.0 \n", "2019-02-01 100.0 99.0 110.0 24.0 \n", "2019-03-01 102.0 107.0 113.0 32.0 \n", "2019-04-01 66.0 66.0 78.0 17.0 \n", "2019-05-01 62.0 72.0 84.0 15.0 \n", "2019-06-01 58.0 60.0 72.0 14.0 \n", "2019-07-01 40.0 47.0 55.0 19.0 \n", "2019-08-01 34.0 43.0 47.0 16.0 \n", "2019-09-01 289.0 88.0 97.0 31.0 \n", "2019-10-01 NaN 376.0 104.0 37.0 \n", "2019-11-01 NaN NaN 302.0 23.0 \n", "2019-12-01 NaN NaN NaN 31.0 " ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Assess changes in absolute values by month\n", "\n", "df.pivot_table(index = 'first_order_month',\n", " columns = 'order_month',\n", " values = 'customer_id',\n", " aggfunc = 'nunique')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observations\n", "* The number of active customers decreases after the first month\n", "* It seems like the first 4-5 cohorts, after the initial month, settles into a somewhat consistent level of orders. However, around mid-year, the average orders seem lower. Perhaps this is due to seasonality.\n", "* The users of the December 2018 cohort still account for the greatest share of active customers even a year later.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Assess changes in relative values by lifetime" ] }, { "cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [], "source": [ "\n", "aggregations = {'revenue': ('total_price', 'sum'),\n", " 'num_of_customers' : ('customer_id','nunique')}\n", "\n", "orders_grouped_by_cohorts = df.groupby(['first_order_month',\n", " 'order_month']).agg(**aggregations)" ] }, { "cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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revenuenum_of_customers
first_order_monthorder_month
2018-11-012018-11-01103249.92205
2018-12-01288927.8993
2019-01-01201104.9880
2019-02-01122481.6770
2019-03-01188820.3677
2019-04-01110959.4379
2019-05-01181814.9283
2019-06-01159306.7681
2019-07-01198619.9272
2019-08-01185200.4376
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" ], "text/plain": [ " revenue num_of_customers\n", "first_order_month order_month \n", "2018-11-01 2018-11-01 103249.92 205\n", " 2018-12-01 288927.89 93\n", " 2019-01-01 201104.98 80\n", " 2019-02-01 122481.67 70\n", " 2019-03-01 188820.36 77\n", " 2019-04-01 110959.43 79\n", " 2019-05-01 181814.92 83\n", " 2019-06-01 159306.76 81\n", " 2019-07-01 198619.92 72\n", " 2019-08-01 185200.43 76" ] }, "execution_count": 121, "metadata": {}, "output_type": "execute_result" } ], "source": [ "orders_grouped_by_cohorts.head(10)" ] }, { "cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [], "source": [ "orders_grouped_by_cohorts['revenue_per_customer'] = orders_grouped_by_cohorts[\n", " 'revenue'] / orders_grouped_by_cohorts['num_of_customers']" ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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revenuenum_of_customersrevenue_per_customer
first_order_monthorder_month
2018-11-012018-11-01103249.92205503.658146
2018-12-01288927.89933106.751505
2019-01-01201104.98802513.812250
2019-02-01122481.67701749.738143
2019-03-01188820.36772452.212468
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" ], "text/plain": [ " revenue num_of_customers \\\n", "first_order_month order_month \n", "2018-11-01 2018-11-01 103249.92 205 \n", " 2018-12-01 288927.89 93 \n", " 2019-01-01 201104.98 80 \n", " 2019-02-01 122481.67 70 \n", " 2019-03-01 188820.36 77 \n", "\n", " revenue_per_customer \n", "first_order_month order_month \n", "2018-11-01 2018-11-01 503.658146 \n", " 2018-12-01 3106.751505 \n", " 2019-01-01 2513.812250 \n", " 2019-02-01 1749.738143 \n", " 2019-03-01 2452.212468 " ] }, "execution_count": 123, "metadata": {}, "output_type": "execute_result" } ], "source": [ "orders_grouped_by_cohorts.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Revenue per customer for cohorts changing over time" ] }, { "cell_type": "code", "execution_count": 124, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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order_month2018-11-012018-12-012019-01-012019-02-012019-03-012019-04-012019-05-012019-06-012019-07-012019-08-012019-09-012019-10-012019-11-012019-12-01
first_order_month
2018-11-01503.6581463106.7515052513.8122501749.7381432452.2124681404.5497472190.5412051966.7501232758.6100002436.8477632428.3641982969.2891254946.2005053261.504359
2018-12-01NaN493.394118691.084339696.352712723.754533567.085600841.306879815.689356803.970722970.5781231109.9742141124.566791914.069871592.175280
2019-01-01NaNNaN469.320825514.782636502.203846419.405398617.751720585.060448603.758898684.126746535.173830746.551392745.179718465.561333
2019-02-01NaNNaNNaN413.594548280.583778460.032727425.118544322.990606374.810000453.589647494.392500468.381010508.164182197.993333
2019-03-01NaNNaNNaNNaN416.745749301.293117523.536818430.806145480.659709541.381282532.999216600.243271523.734690235.308125
2019-04-01NaNNaNNaNNaNNaN393.485758380.790769363.614590331.168387368.477759392.663030416.196667400.702436233.914118
2019-05-01NaNNaNNaNNaNNaNNaN412.786632268.635224401.065714346.586327443.159839472.353750443.804524331.350000
2019-06-01NaNNaNNaNNaNNaNNaNNaN382.773289285.003400284.189070475.182931425.922500506.441667299.322857
2019-07-01NaNNaNNaNNaNNaNNaNNaNNaN440.266323241.316444406.657250399.262766364.312182249.515789
2019-08-01NaNNaNNaNNaNNaNNaNNaNNaNNaN399.519630458.548235740.920000838.770000683.005000
2019-09-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN511.196647301.554659347.474021345.099677
2019-10-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN426.481170442.203942269.008378
2019-11-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN418.951126234.117391
2019-12-01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN792.826452
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" ], "text/plain": [ "order_month 2018-11-01 2018-12-01 2019-01-01 2019-02-01 \\\n", "first_order_month \n", "2018-11-01 503.658146 3106.751505 2513.812250 1749.738143 \n", "2018-12-01 NaN 493.394118 691.084339 696.352712 \n", "2019-01-01 NaN NaN 469.320825 514.782636 \n", "2019-02-01 NaN NaN NaN 413.594548 \n", "2019-03-01 NaN NaN NaN NaN \n", "2019-04-01 NaN NaN NaN NaN \n", "2019-05-01 NaN NaN NaN NaN \n", "2019-06-01 NaN NaN NaN NaN \n", "2019-07-01 NaN NaN NaN NaN \n", "2019-08-01 NaN NaN NaN NaN \n", "2019-09-01 NaN NaN NaN NaN \n", "2019-10-01 NaN NaN NaN NaN \n", "2019-11-01 NaN NaN NaN NaN \n", "2019-12-01 NaN NaN NaN NaN \n", "\n", "order_month 2019-03-01 2019-04-01 2019-05-01 2019-06-01 \\\n", "first_order_month \n", "2018-11-01 2452.212468 1404.549747 2190.541205 1966.750123 \n", "2018-12-01 723.754533 567.085600 841.306879 815.689356 \n", "2019-01-01 502.203846 419.405398 617.751720 585.060448 \n", "2019-02-01 280.583778 460.032727 425.118544 322.990606 \n", "2019-03-01 416.745749 301.293117 523.536818 430.806145 \n", "2019-04-01 NaN 393.485758 380.790769 363.614590 \n", "2019-05-01 NaN NaN 412.786632 268.635224 \n", "2019-06-01 NaN NaN NaN 382.773289 \n", "2019-07-01 NaN NaN NaN NaN \n", "2019-08-01 NaN NaN NaN NaN \n", "2019-09-01 NaN NaN NaN NaN \n", "2019-10-01 NaN NaN NaN NaN \n", "2019-11-01 NaN NaN NaN NaN \n", "2019-12-01 NaN NaN NaN NaN \n", "\n", "order_month 2019-07-01 2019-08-01 2019-09-01 2019-10-01 \\\n", "first_order_month \n", "2018-11-01 2758.610000 2436.847763 2428.364198 2969.289125 \n", "2018-12-01 803.970722 970.578123 1109.974214 1124.566791 \n", "2019-01-01 603.758898 684.126746 535.173830 746.551392 \n", "2019-02-01 374.810000 453.589647 494.392500 468.381010 \n", "2019-03-01 480.659709 541.381282 532.999216 600.243271 \n", "2019-04-01 331.168387 368.477759 392.663030 416.196667 \n", "2019-05-01 401.065714 346.586327 443.159839 472.353750 \n", "2019-06-01 285.003400 284.189070 475.182931 425.922500 \n", "2019-07-01 440.266323 241.316444 406.657250 399.262766 \n", "2019-08-01 NaN 399.519630 458.548235 740.920000 \n", "2019-09-01 NaN NaN 511.196647 301.554659 \n", "2019-10-01 NaN NaN NaN 426.481170 \n", "2019-11-01 NaN NaN NaN NaN \n", "2019-12-01 NaN NaN NaN NaN \n", "\n", "order_month 2019-11-01 2019-12-01 \n", "first_order_month \n", "2018-11-01 4946.200505 3261.504359 \n", "2018-12-01 914.069871 592.175280 \n", "2019-01-01 745.179718 465.561333 \n", "2019-02-01 508.164182 197.993333 \n", "2019-03-01 523.734690 235.308125 \n", "2019-04-01 400.702436 233.914118 \n", "2019-05-01 443.804524 331.350000 \n", "2019-06-01 506.441667 299.322857 \n", "2019-07-01 364.312182 249.515789 \n", "2019-08-01 838.770000 683.005000 \n", "2019-09-01 347.474021 345.099677 \n", "2019-10-01 442.203942 269.008378 \n", "2019-11-01 418.951126 234.117391 \n", "2019-12-01 NaN 792.826452 " ] }, "execution_count": 124, "metadata": {}, "output_type": "execute_result" } ], "source": [ "orders_grouped_by_cohorts.pivot_table(index = 'first_order_month',\n", " columns = 'order_month',\n", " values = 'revenue_per_customer',\n", " aggfunc = 'mean')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Finding cohort lifetime" ] }, { "cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [], "source": [ "orders_grouped_by_cohorts = orders_grouped_by_cohorts.reset_index()\n", "orders_grouped_by_cohorts['cohort_lifetime'] = orders_grouped_by_cohorts[\n", " 'order_month'] - orders_grouped_by_cohorts['first_order_month']" ] }, { "cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [], "source": [ "# convert lifetime to months\n", "orders_grouped_by_cohorts['cohort_lifetime'] = orders_grouped_by_cohorts['cohort_lifetime'] / np.timedelta64(1,'M')" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [], "source": [ "# round to nearest month\n", "orders_grouped_by_cohorts['cohort_lifetime'] = orders_grouped_by_cohorts['cohort_lifetime'].round().astype('int')" ] }, { "cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [], "source": [ "# change first_order_month to year and month only\n", "orders_grouped_by_cohorts['first_order_month'] = orders_grouped_by_cohorts['first_order_month'].dt.strftime('%Y-%m')" ] }, { "cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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first_order_monthorder_monthrevenuenum_of_customersrevenue_per_customercohort_lifetime
02018-112018-11-01103249.92205503.6581460
12018-112018-12-01288927.89933106.7515051
22018-112019-01-01201104.98802513.8122502
32018-112019-02-01122481.67701749.7381433
42018-112019-03-01188820.36772452.2124684
.....................
1002019-102019-11-0145989.21104442.2039421
1012019-102019-12-019953.3137269.0083782
1022019-112019-11-01126523.24302418.9511260
1032019-112019-12-015384.7023234.1173911
1042019-122019-12-0124577.6231792.8264520
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105 rows × 6 columns

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" ], "text/plain": [ " first_order_month order_month revenue num_of_customers \\\n", "0 2018-11 2018-11-01 103249.92 205 \n", "1 2018-11 2018-12-01 288927.89 93 \n", "2 2018-11 2019-01-01 201104.98 80 \n", "3 2018-11 2019-02-01 122481.67 70 \n", "4 2018-11 2019-03-01 188820.36 77 \n", ".. ... ... ... ... \n", "100 2019-10 2019-11-01 45989.21 104 \n", "101 2019-10 2019-12-01 9953.31 37 \n", "102 2019-11 2019-11-01 126523.24 302 \n", "103 2019-11 2019-12-01 5384.70 23 \n", "104 2019-12 2019-12-01 24577.62 31 \n", "\n", " revenue_per_customer cohort_lifetime \n", "0 503.658146 0 \n", "1 3106.751505 1 \n", "2 2513.812250 2 \n", "3 1749.738143 3 \n", "4 2452.212468 4 \n", ".. ... ... \n", "100 442.203942 1 \n", "101 269.008378 2 \n", "102 418.951126 0 \n", "103 234.117391 1 \n", "104 792.826452 0 \n", "\n", "[105 rows x 6 columns]" ] }, "execution_count": 129, "metadata": {}, "output_type": "execute_result" } ], "source": [ "orders_grouped_by_cohorts" ] }, { "cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [], "source": [ "# pivot table of changes in average revenue per customer whose columns will contain the lifetime and whose rows will be cohorts\n", "avg_revenue_per_customer_pivot = orders_grouped_by_cohorts.pivot_table(index = 'first_order_month',\n", " columns = 'cohort_lifetime',\n", " values = 'revenue_per_customer',\n", " aggfunc = 'mean')" ] }, { "cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# let's visualize revenue_per_customer_pivot\n", "plt.figure(figsize = (20, 9))\n", "plt.title('Average customer purchase size')\n", "sns.heatmap(avg_revenue_per_customer_pivot,\n", " annot = True, \n", " fmt='.1f',\n", " linewidth = 1,\n", " linecolor = 'gray');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Observation\n", "* We can see that the Nov 2018 cohort looks like the \"winner\" in terms of higher sales throughout their lifetime\n", "* The final cohort Dec 2019 has the highest initial purchases. Perhaps the result of a good marketing campaign?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# Testing Hypothesis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "After analyzing the data, the question comes to mind whether the average unit price paid by the top buyers was different than the rest. Did the top buyers get discounted pricing, and \"made up\" for it with the sheer volume they ordered?\n", "\n", "Null hypothesis: The average price paid by the Top 25% of customers is the same as the rest, suggesting that the only difference in top customers is the volume of items they purchase.\n", "\n", "Alternative hypothesis: The average price by the Top 25% of customers is not the same as the rest, suggesting that they get special pricing discounts, but make up for it by the sheer volume they purchase." ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [], "source": [ "# We will group the customers and then sort by total revenues" ] }, { "cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [], "source": [ "grouped_customer = df.groupby('customer_id').agg({'invoice_no':'nunique',\n", " 'unit_price': 'mean',\n", " 'total_price': 'sum'}).reset_index()" ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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customer_idinvoice_nounit_pricetotal_price
0014104.4686381506879.59
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" ], "text/plain": [ " customer_id invoice_no unit_price total_price\n", "0 0 1410 4.468638 1506879.59\n", "1 12347 7 2.644011 4310.00\n", "2 12348 4 0.692963 1437.24\n", "3 12349 1 4.237500 1457.55\n", "4 12350 1 1.581250 294.40" ] }, "execution_count": 134, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_customer.head()" ] }, { "cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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customer_idinvoice_nounit_pricetotal_price
count4362.000004362.0000004362.0000004.362000e+03
mean15297.411055.3165983.4066772.232926e+03
std1736.7114723.1343835.9739472.423915e+04
min0.000001.0000000.122500-1.192200e+03
25%13814.250001.0000002.1714362.930250e+02
50%15299.500003.0000002.8452516.432150e+02
75%16777.750005.0000003.7404641.584745e+03
max18287.000001410.000000295.0000001.506880e+06
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" ], "text/plain": [ " customer_id invoice_no unit_price total_price\n", "count 4362.00000 4362.000000 4362.000000 4.362000e+03\n", "mean 15297.41105 5.316598 3.406677 2.232926e+03\n", "std 1736.71147 23.134383 5.973947 2.423915e+04\n", "min 0.00000 1.000000 0.122500 -1.192200e+03\n", "25% 13814.25000 1.000000 2.171436 2.930250e+02\n", "50% 15299.50000 3.000000 2.845251 6.432150e+02\n", "75% 16777.75000 5.000000 3.740464 1.584745e+03\n", "max 18287.00000 1410.000000 295.000000 1.506880e+06" ] }, "execution_count": 135, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grouped_customer.describe()" ] }, { "cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [], "source": [ "# For the top 25%, they spent $1582.60 or more" ] }, { "cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [], "source": [ "grouped_customers_sorted_total_price = grouped_customer.sort_values(by = 'total_price', ascending = False)" ] }, { "cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [], "source": [ "top_25_percent = grouped_customers_sorted_total_price[\n", " grouped_customers_sorted_total_price['total_price'] >= grouped_customers_sorted_total_price['total_price'].quantile(0.75)]['unit_price']" ] }, { "cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [], "source": [ "other_75_percent = grouped_customers_sorted_total_price[\n", " grouped_customers_sorted_total_price['total_price'] < grouped_customers_sorted_total_price['total_price'].quantile(0.75)]['unit_price']" ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [], "source": [ "from scipy import stats as st\n" ] }, { "cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [], "source": [ "# significance level. Not a life or death situation, so we choose 0.5\n", "alpha = 0.05" ] }, { "cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [], "source": [ "top_25 = top_25_percent.to_list()\n", "other_75 = other_75_percent.to_list()" ] }, { "cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [], "source": [ "results = st.ttest_ind(top_25_percent, other_75_percent)" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Result of t-test pvalue is: 0.01107778774627851\n", "Rejecting the null hypothesis: there is a significant difference between the samples tested\n" ] } ], "source": [ "print(\"Result of t-test pvalue is:\", str(results.pvalue))\n", "if (results.pvalue < alpha):\n", " print(\"Rejecting the null hypothesis: there is a significant difference between the samples tested\")\n", "else:\n", " print(\"Failed to reject the null hypothesis: there is no reason to consider the samples different\")\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# Conclusion\n", "\n", "### Dataset\n", "* This was our largest dataset in our practicum. \n", "* Column names are camelbacked -- we converted to lowercase\n", "* There were also negative quantities and prices, some very extreme. So we investigated them as well.\n", "* We were missing a LOT of CustomerID's\n", "* We converted data types - InvoiceNo into int type, InvoiceDate into datetime, CustomerID into int.\n", "\n", "### Duplicates\n", "* We deleted 5268 duplicate rows, which was 0.97% of the data\n", "\n", "ACTION REQUIRED: Why was nearly 1% of the data duplicates? Need to ask Data Engineering about data logging, or UX about data entry. Is there a bug in the backend, or is this a front-end issue (or user error)?\n", "\n", "### Missing Data (Nulls/Nans)\n", "\n", "* 1454 rows are missing descriptions. There are some descriptions, \"damaged, manual, postage, check, discount, samples, bank fee\", etc., that we can exclude from our analysis. There were also things like, \"oops ! adjustment, crushed ctn, etc. \" In the end, however, they make up less 0.3% of the data, so we dropped them.\n", "* 135037 rows with emtpy customer_id which comprises 25% of the transactions involved unknown customers. These transactions total \\\\$1.4 million, so a significant amount.\n", "Some can perhaps be attributed to cash transactions, but the sheer number of their existence suggests a systemic problem that should be discussed with PdM, UX, Data/Engineering.\n", "\n", "There were transactions involving hundreds, even thousands of units. Some of these large transactions have no associated revenue (e.g. \\\\$0 unit price). It appears that large negative quantities sometimes were returned damaged product. Some large \"sales\" may have been gifts or donations.\n", "In any case, since we cannot correlate these transactions with actual customers, we deleted these transactions as well.\n", "\n", "ACTION REQUIRED: There has to be a better way to reconcile these abnormal transactions so that we can properly track and attribute them to either a profit or loss. In our case, we're talking \\\\$1.4 million in sales that cannot be properly accounted.\n", "\n", "### Outliers\n", "\n", "* We deleted a couple of notable \"erroneous\" transactions -- two orders that had 80k+ and 74k+ units ordered, and then cancelled/returned within minutes.\n", "* Another pair of transactions that started off with 60 units ordered @ $649.50, totally \\\\$38970, and then refunded 3 minutes later as a single item with a unit_price of \\\\$38970. This also presented an opportunity to correct another transaction's unit pricing.\n", "\n", "ACTION REQUIRED: Some items are obvious returns, but others have no customers associated, and some descriptions look very arbitrary. There should be a more consistent system, because some of the quantities and dollar amounts are very large (in the negative).\n", "\n", "* There were also 37 transactions where zero dollars were charged -- I'm assuming the items in these transactions were given to the customer for free. We deleted these as well, since we would not be able to take action on any particular customer.\n", "\n", "ACTION REQUIRED: Why were also several dozen items are listed with unit_price of \\\\$0?\n", "\n", "* Of the top 20 customers, 90% made 24 or more orders.\n", "\n", "### EDA\n", "\n", "* Some transactions for the same item have different prices that seem to have been arbitrarily set, e.g. not related to units purchased.\n", "* We found that the top products sold by revenue generated and by quantities sold show skewed charts: \n", "\t* Products that brought in sales of \\\\$20k only make up 5.5% of total revenues\n", "\t* More than 75% of revenues were from products that generated sales of \\\\$7500 or less each\n", "* Likewise, nearly 80% of revenues were from products that sold 4000 or less units\n", "* And finally, more than 80% of revenues came from products whose unit pricing was \\\\$10 or less\n", "* 90% of The Top 20 customers (in terms of sales) made 24 or more orders\n", "\n", "### Cohort Analysis\n", "* The number of active customers decreases after the first month\n", "* It seems like the first 4-5 cohorts, after the initial month, settles into a somewhat consistent level of orders. However, around mid-year, the average orders seem lower. Perhaps this is due to seasonality.\n", "* The users of the December 2018 cohort still account for the greatest share of active customers even a year later (It was also the largest cohort, nearly twice the size of the next two largest -- could be attributed to Christmas holiday, but again, consistently outpurchased the other cohorts in the dataset).\n", "* In terms of revenue, the November 2018 cohort produced the most revenue consistently throughout the study.\n", "* The December 2019 cohort (only one month) had the highest initial revenue, perhaps the result of a good holiday marketing campaign?\n", "\n", "\n", "### Hypothesis Testing\n", "* We hypothesized that the top 25% customers may be getting special pricing, such as discounts, and making up the difference by sheer volume.\n", "**RESULT**: We reject the null hypothesis. The top 25% customers do appear to be getting a different pricing.\n", "\n", "Although we've seen pricing that seems arbritrary, our testing do show that the top 25% of customers on average have different pricing. Perhaps they were getting free samples, which might explain the \\\\$0 unit pricing on some items. In addition to questions about the entire ordering system that we posed above, we should also ask about customer service/support -- they being the face or \"voice\" of the company, they can constitute a large part of whether there is repeat business by current customers.\n", "\n", "In short, there appears to be many areas that can be shored up, in order to continuing generating more accurate and complete data that will help the business make more accurate assessments and decisions." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[back to top](#toc)" ] } ], "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": "3.8.3" } }, "nbformat": 4, "nbformat_minor": 4 }