diff --git a/Copy_of_DS_Unit_1_Sprint_Challenge_2.ipynb b/Copy_of_DS_Unit_1_Sprint_Challenge_2.ipynb new file mode 100644 index 0000000..e1c255f --- /dev/null +++ b/Copy_of_DS_Unit_1_Sprint_Challenge_2.ipynb @@ -0,0 +1,2277 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Copy of DS_Unit_1_Sprint_Challenge_2.ipynb", + "version": "0.3.2", + "provenance": [], + "collapsed_sections": [], + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "metadata": { + "id": "i-n_5en3ER1o", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Data Science Unit 1 Sprint Challenge 2\n", + "\n", + "# Storytelling with Data\n", + "\n", + "In this sprint challenge you'll work with a dataset from **FiveThirtyEight's article, [Every Guest Jon Stewart Ever Had On ‘The Daily Show’](https://fivethirtyeight.com/features/every-guest-jon-stewart-ever-had-on-the-daily-show/)**!" + ] + }, + { + "metadata": { + "id": "Thm2n5FF2Fnp", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 0 — Run this starter code\n", + "\n", + "You don't need to add or change anything here. Just run this cell and it loads the data for you, into a dataframe named `df`.\n", + "\n", + "(You can explore the data if you want, but it's not required to pass the Sprint Challenge.)" + ] + }, + { + "metadata": { + "id": "0rTHgzJIuRS7", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "\n", + "df = pd.read_csv('https://raw.githubusercontent.com/fivethirtyeight/data/master/daily-show-guests/daily_show_guests.csv')\n", + "df.rename(columns={'YEAR': 'Year', 'Raw_Guest_List': 'Guest'}, inplace=True)\n", + "\n", + "def get_occupation(group):\n", + " if group in ['Acting', 'Comedy', 'Musician']:\n", + " return 'Acting, Comedy & Music'\n", + " elif group in ['Media', 'media']:\n", + " return 'Media'\n", + " elif group in ['Government', 'Politician', 'Political Aide']:\n", + " return 'Government and Politics'\n", + " else:\n", + " return 'Other'\n", + " \n", + "df['Occupation'] = df['Group'].apply(get_occupation)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "akuLkbkxSzdg", + "colab_type": "code", + "outputId": "04064ac6-f8ff-48cb-db63-28914ae49a76", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "cell_type": "code", + "source": [ + "df.shape" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(2693, 6)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 3 + } + ] + }, + { + "metadata": { + "id": "P3sn8b6hS2Bo", + "colab_type": "code", + "outputId": "1532331a-e37d-42d6-f27a-505f5f7dc861", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 297 + } + }, + "cell_type": "code", + "source": [ + "df.describe()" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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YearGoogleKnowlege_OccupationShowGroupGuestOccupation
01999actor1/11/99ActingMichael J. FoxActing, Comedy & Music
11999Comedian1/12/99ComedySandra BernhardActing, Comedy & Music
21999television actress1/13/99ActingTracey UllmanActing, Comedy & Music
31999film actress1/14/99ActingGillian AndersonActing, Comedy & Music
41999actor1/18/99ActingDavid Alan GrierActing, Comedy & Music
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" + ], + "text/plain": [ + " Year GoogleKnowlege_Occupation Show Group Guest \\\n", + "0 1999 actor 1/11/99 Acting Michael J. Fox \n", + "1 1999 Comedian 1/12/99 Comedy Sandra Bernhard \n", + "2 1999 television actress 1/13/99 Acting Tracey Ullman \n", + "3 1999 film actress 1/14/99 Acting Gillian Anderson \n", + "4 1999 actor 1/18/99 Acting David Alan Grier \n", + "\n", + " Occupation \n", + "0 Acting, Comedy & Music \n", + "1 Acting, Comedy & Music \n", + "2 Acting, Comedy & Music \n", + "3 Acting, Comedy & Music \n", + "4 Acting, Comedy & Music " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 5 + } + ] + }, + { + "metadata": { + "id": "OS0nW1vz1itX", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 1 — What's the breakdown of guests’ occupations per year?\n", + "\n", + "For example, in 1999, what percentage of guests were actors, comedians, or musicians? What percentage were in the media? What percentage were in politics? What percentage were from another occupation?\n", + "\n", + "Then, what about in 2000? In 2001? And so on, up through 2015.\n", + "\n", + "So, **for each year of _The Daily Show_, calculate the percentage of guests from each occupation:**\n", + "- Acting, Comedy & Music\n", + "- Government and Politics\n", + "- Media\n", + "- Other\n", + "\n", + "#### Hints:\n", + "1. Use pandas to make a **crosstab** of **`Year`** & **`Occupation`**. ([This documentation](http://pandas.pydata.org/pandas-docs/stable/reshaping.html#cross-tabulations) has examples and explanation.)\n", + "2. To get percentages instead of counts, use crosstab's **`normalize`** parameter to normalize over each _row._ ([This documentation](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.crosstab.html) describes the parameter and its options.)\n", + "3. You'll know you've calculated the crosstab correctly when the percentage of \"Acting, Comedy & Music\" guests is 90.36% in 1999, and 45% in 2015." + ] + }, + { + "metadata": { + "id": "sRMc0H_5z6ff", + "colab_type": "code", + "outputId": "5c1b9a6d-7a76-475a-c911-958042e767ce", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 607 + } + }, + "cell_type": "code", + "source": [ + "ct = pd.crosstab(df['Year'], df['Occupation'], normalize = 'index')\n", + "ct" + ], + "execution_count": 6, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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19990.9036140.0120480.0662650.018072
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20010.7261150.0382170.1974520.038217
20020.6226420.0691820.2641510.044025
20030.5602410.1024100.2469880.090361
20040.3841460.2256100.2743900.115854
20050.3703700.1604940.3333330.135802
20060.3602480.1925470.2919250.155280
20070.2553190.1702130.3333330.241135
20080.2073170.2012200.4695120.121951
20090.2085890.2085890.3619630.220859
20100.3515150.1818180.3030300.163636
20110.3374230.1656440.3128830.184049
20120.2682930.2012200.3170730.213415
20130.4277110.1265060.3072290.138554
20140.3926380.1288340.3251530.153374
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" + ], + "text/plain": [ + "Occupation Acting, Comedy & Music Government and Politics Media \\\n", + "Year \n", + "1999 0.903614 0.012048 0.066265 \n", + "2000 0.739645 0.082840 0.124260 \n", + "2001 0.726115 0.038217 0.197452 \n", + "2002 0.622642 0.069182 0.264151 \n", + "2003 0.560241 0.102410 0.246988 \n", + "2004 0.384146 0.225610 0.274390 \n", + "2005 0.370370 0.160494 0.333333 \n", + "2006 0.360248 0.192547 0.291925 \n", + "2007 0.255319 0.170213 0.333333 \n", + "2008 0.207317 0.201220 0.469512 \n", + "2009 0.208589 0.208589 0.361963 \n", + "2010 0.351515 0.181818 0.303030 \n", + "2011 0.337423 0.165644 0.312883 \n", + "2012 0.268293 0.201220 0.317073 \n", + "2013 0.427711 0.126506 0.307229 \n", + "2014 0.392638 0.128834 0.325153 \n", + "2015 0.450000 0.170000 0.240000 \n", + "\n", + "Occupation Other \n", + "Year \n", + "1999 0.018072 \n", + "2000 0.053254 \n", + "2001 0.038217 \n", + "2002 0.044025 \n", + "2003 0.090361 \n", + "2004 0.115854 \n", + "2005 0.135802 \n", + "2006 0.155280 \n", + "2007 0.241135 \n", + "2008 0.121951 \n", + "2009 0.220859 \n", + "2010 0.163636 \n", + "2011 0.184049 \n", + "2012 0.213415 \n", + "2013 0.138554 \n", + "2014 0.153374 \n", + "2015 0.140000 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 6 + } + ] + }, + { + "metadata": { + "id": "Nqf9oJJDDu-d", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 2 — Recreate this explanatory visualization:" + ] + }, + { + "metadata": { + "id": "scozkHQc0_eD", + "colab_type": "code", + "outputId": "22262c66-c740-4b68-cf21-d4dd0f6515c0", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 406 + } + }, + "cell_type": "code", + "source": [ + "from IPython.display import display, Image\n", + "url = 'https://fivethirtyeight.com/wp-content/uploads/2015/08/hickey-datalab-dailyshow.png'\n", + "example = Image(url, width=500)\n", + "display(example)" + ], + "execution_count": 7, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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ZBtnkfptMLmk+J6HR1RolfR2cZ4kCMURmERt2i1wRFHvq1F3TaMmmGBsU6Ssc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\n4JhflzBydcIRb30AAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [], + "image/png": { + "width": 500 + } + } + } + ] + }, + { + "metadata": { + "id": "W7lw3JzAE6BJ", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "**Hint:** use the crosstab you calculated in part 1!\n", + "\n", + "**Expectations:** Your plot should include:\n", + "- 3 lines visualizing \"occupation of guests, by year.\" The shapes of the lines should look roughly identical to 538's example. Each line should be a different color. (But you don't need to use the _same_ colors as 538.)\n", + "- Legend or labels for the lines. (But you don't need each label positioned next to its line or colored like 538.)\n", + "- Title in the upper left: _\"Who Got To Be On 'The Daily Show'?\"_ with more visual emphasis than the subtitle. (Bolder and/or larger font.)\n", + "- Subtitle underneath the title: _\"Occupation of guests, by year\"_\n", + "\n", + "Any visual element not specifically mentioned in the expectations is an optional bonus, but it's _not_ required to pass the Sprint Challenge.\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "metadata": { + "id": "V6VPpdNmXgcP", + "colab_type": "code", + "outputId": "fb30d562-159e-4b37-bf7f-0c046aac435e", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 207 + } + }, + "cell_type": "code", + "source": [ + "!pip install seaborn --upgrade" + ], + "execution_count": 8, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Requirement already up-to-date: seaborn in /usr/local/lib/python3.6/dist-packages (0.9.0)\n", + "Requirement already satisfied, skipping upgrade: pandas>=0.15.2 in /usr/local/lib/python3.6/dist-packages (from seaborn) (0.22.0)\n", + "Requirement already satisfied, skipping upgrade: matplotlib>=1.4.3 in /usr/local/lib/python3.6/dist-packages (from seaborn) (2.1.2)\n", + "Requirement already satisfied, skipping upgrade: scipy>=0.14.0 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.1.0)\n", + "Requirement already satisfied, skipping upgrade: numpy>=1.9.3 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.14.6)\n", + "Requirement already satisfied, skipping upgrade: pytz>=2011k in /usr/local/lib/python3.6/dist-packages (from pandas>=0.15.2->seaborn) (2018.7)\n", + "Requirement already satisfied, skipping upgrade: python-dateutil>=2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.15.2->seaborn) (2.5.3)\n", + "Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (0.10.0)\n", + "Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (2.3.0)\n", + "Requirement already satisfied, skipping upgrade: six>=1.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (1.11.0)\n" + ], + "name": "stdout" + } + ] + }, + { + "metadata": { + "id": "BQP4iX30Xmau", + "colab_type": "code", + "outputId": "8002a020-74f1-4bea-80c9-7bd1be1ffc0a", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "cell_type": "code", + "source": [ + "import seaborn as sns\n", + "sns.__version__" + ], + "execution_count": 9, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "'0.9.0'" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 9 + } + ] + }, + { + "metadata": { + "id": "k1KD5v4KYVxU", + "colab_type": "code", + "outputId": "22f1f05c-293b-480f-a727-b65038518650", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 51 + } + }, + "cell_type": "code", + "source": [ + "ct.index.values" + ], + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009,\n", + " 2010, 2011, 2012, 2013, 2014, 2015])" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 10 + } + ] + }, + { + "metadata": { + "id": "_df5th0JYVu1", + "colab_type": "code", + "outputId": "9c45a9e8-7dd1-40b8-b8f8-82feacf17be6", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 111 + } + }, + "cell_type": "code", + "source": [ + "ct.head(1)" + ], + "execution_count": 11, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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OccupationActing, Comedy & MusicGovernment and PoliticsMediaOther
Year
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" + ], + "text/plain": [ + "Occupation Acting, Comedy & Music Government and Politics Media \\\n", + "Year \n", + "1999 0.903614 0.012048 0.066265 \n", + "\n", + "Occupation Other \n", + "Year \n", + "1999 0.018072 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 11 + } + ] + }, + { + "metadata": { + "id": "anXbIeyxgwXs", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1088 + }, + "outputId": "77e2dbd0-da48-4666-9d7e-8060835addfc" + }, + "cell_type": "code", + "source": [ + "ct_unstacked = ct.unstack()\n", + "ct_unstacked" + ], + "execution_count": 28, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Occupation Year\n", + "Acting, Comedy & Music 1999 0.903614\n", + " 2000 0.739645\n", + " 2001 0.726115\n", + " 2002 0.622642\n", + " 2003 0.560241\n", + " 2004 0.384146\n", + " 2005 0.370370\n", + " 2006 0.360248\n", + " 2007 0.255319\n", + " 2008 0.207317\n", + " 2009 0.208589\n", + " 2010 0.351515\n", + " 2011 0.337423\n", + " 2012 0.268293\n", + " 2013 0.427711\n", + " 2014 0.392638\n", + " 2015 0.450000\n", + "Government and Politics 1999 0.012048\n", + " 2000 0.082840\n", + " 2001 0.038217\n", + " 2002 0.069182\n", + " 2003 0.102410\n", + " 2004 0.225610\n", + " 2005 0.160494\n", + " 2006 0.192547\n", + " 2007 0.170213\n", + " 2008 0.201220\n", + " 2009 0.208589\n", + " 2010 0.181818\n", + " 2011 0.165644\n", + " ... \n", + "Media 2003 0.246988\n", + " 2004 0.274390\n", + " 2005 0.333333\n", + " 2006 0.291925\n", + " 2007 0.333333\n", + " 2008 0.469512\n", + " 2009 0.361963\n", + " 2010 0.303030\n", + " 2011 0.312883\n", + " 2012 0.317073\n", + " 2013 0.307229\n", + " 2014 0.325153\n", + " 2015 0.240000\n", + "Other 1999 0.018072\n", + " 2000 0.053254\n", + " 2001 0.038217\n", + " 2002 0.044025\n", + " 2003 0.090361\n", + " 2004 0.115854\n", + " 2005 0.135802\n", + " 2006 0.155280\n", + " 2007 0.241135\n", + " 2008 0.121951\n", + " 2009 0.220859\n", + " 2010 0.163636\n", + " 2011 0.184049\n", + " 2012 0.213415\n", + " 2013 0.138554\n", + " 2014 0.153374\n", + " 2015 0.140000\n", + "Length: 68, dtype: float64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 28 + } + ] + }, + { + "metadata": { + "id": "zf06zdz6j6J4", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "479598a9-bdd9-4486-f1e1-c2b357844558" + }, + "cell_type": "code", + "source": [ + "list(ct_unstacked.index.levels[0])" + ], + "execution_count": 30, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "['Acting, Comedy & Music', 'Government and Politics', 'Media', 'Other']" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 30 + } + ] + }, + { + "metadata": { + "id": "hShEyq9uiAYK", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 88 + }, + "outputId": "d96376d6-cd5a-4f60-8099-6e15ea3e52dc" + }, + "cell_type": "code", + "source": [ + "ct_unstacked.index" + ], + "execution_count": 31, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "MultiIndex(levels=[['Acting, Comedy & Music', 'Government and Politics', 'Media', 'Other'], [1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015]],\n", + " labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]],\n", + " names=['Occupation', 'Year'])" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 31 + } + ] + }, + { + "metadata": { + "id": "HzJliVUFi70Y", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 340 + }, + "outputId": "8aa8cdc0-120d-4406-f0ac-fd842baca1e4" + }, + "cell_type": "code", + "source": [ + "ct_unstacked['Acting, Comedy & Music']" + ], + "execution_count": 58, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year\n", + "1999 0.903614\n", + "2000 0.739645\n", + "2001 0.726115\n", + "2002 0.622642\n", + "2003 0.560241\n", + "2004 0.384146\n", + "2005 0.370370\n", + "2006 0.360248\n", + "2007 0.255319\n", + "2008 0.207317\n", + "2009 0.208589\n", + "2010 0.351515\n", + "2011 0.337423\n", + "2012 0.268293\n", + "2013 0.427711\n", + "2014 0.392638\n", + "2015 0.450000\n", + "dtype: float64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 58 + } + ] + }, + { + "metadata": { + "id": "_QRV28uxlyM9", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "b3b9a502-3a4e-43a9-90b0-fa32d8d09857" + }, + "cell_type": "code", + "source": [ + "len(ct_unstacked['Acting, Comedy & Music'])" + ], + "execution_count": 36, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "17" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 36 + } + ] + }, + { + "metadata": { + "id": "miMexkI8oXG9", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 681 + }, + "outputId": "d71bdfdb-fb2a-4a88-f994-c96782140020" + }, + "cell_type": "code", + "source": [ + "first_col = ['Acting, Comedy & Music'] * len(ct_unstacked['Acting, Comedy & Music'])\n", + "years_col = range(1999, 2016)\n", + "first_col_df = pd.DataFrame([years_col, first_col, ct.loc[:, 'Acting, Comedy & Music']])\n", + "first_col = first_col_df.T.rename(str, {0: 'Year', 1: 'Guest type', 2: 'Percentages'})\n", + "first_col" + ], + "execution_count": 61, + "outputs": [ + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:4: FutureWarning: Intepreting call\n", + "\t'.rename(a, b)' as \n", + "\t'.rename(index=a, columns=b)'.\n", + "Use named arguments to remove any ambiguity. In the future, using positional arguments for 'index' or 'columns' will raise a 'TypeError'.\n", + " after removing the cwd from sys.path.\n" + ], + "name": "stderr" + }, + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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YearGuest typePercentages
01999Acting, Comedy & Music0.903614
12000Acting, Comedy & Music0.739645
22001Acting, Comedy & Music0.726115
32002Acting, Comedy & Music0.622642
42003Acting, Comedy & Music0.560241
52004Acting, Comedy & Music0.384146
62005Acting, Comedy & Music0.37037
72006Acting, Comedy & Music0.360248
82007Acting, Comedy & Music0.255319
92008Acting, Comedy & Music0.207317
102009Acting, Comedy & Music0.208589
112010Acting, Comedy & Music0.351515
122011Acting, Comedy & Music0.337423
132012Acting, Comedy & Music0.268293
142013Acting, Comedy & Music0.427711
152014Acting, Comedy & Music0.392638
162015Acting, Comedy & Music0.45
\n", + "
" + ], + "text/plain": [ + " Year Guest type Percentages\n", + "0 1999 Acting, Comedy & Music 0.903614\n", + "1 2000 Acting, Comedy & Music 0.739645\n", + "2 2001 Acting, Comedy & Music 0.726115\n", + "3 2002 Acting, Comedy & Music 0.622642\n", + "4 2003 Acting, Comedy & Music 0.560241\n", + "5 2004 Acting, Comedy & Music 0.384146\n", + "6 2005 Acting, Comedy & Music 0.37037\n", + "7 2006 Acting, Comedy & Music 0.360248\n", + "8 2007 Acting, Comedy & Music 0.255319\n", + "9 2008 Acting, Comedy & Music 0.207317\n", + "10 2009 Acting, Comedy & Music 0.208589\n", + "11 2010 Acting, Comedy & Music 0.351515\n", + "12 2011 Acting, Comedy & Music 0.337423\n", + "13 2012 Acting, Comedy & Music 0.268293\n", + "14 2013 Acting, Comedy & Music 0.427711\n", + "15 2014 Acting, Comedy & Music 0.392638\n", + "16 2015 Acting, Comedy & Music 0.45" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 61 + } + ] + }, + { + "metadata": { + "id": "3jb7HA4ylZpk", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 851 + }, + "outputId": "dc51e511-615c-415c-bb46-1b08aa2ab792" + }, + "cell_type": "code", + "source": [ + "second_col = ['Government and Politics'] * len(ct_unstacked['Government and Politics'])\n", + "second_col_df = pd.DataFrame([years_col, second_col, ct.loc[:, 'Government and Politics']])\n", + "second_col = second_col_df.T.rename(str, {0: 'Year', 1: 'Guest type', 2: 'Percentages'})\n", + "second_col\n", + "\n", + "third_col = ['Media'] * len(ct_unstacked['Media'])\n", + "third_col_df = pd.DataFrame([years_col, third_col, ct.loc[:, 'Media']])\n", + "third_col = third_col_df.T.rename(str, {0: 'Year', 1: 'Guest type', 2: 'Percentages'})\n", + "third_col\n", + "\n", + "fourth_col = ['Other'] * len(ct_unstacked['Other'])\n", + "fourth_col_df = pd.DataFrame([years_col, fourth_col, ct.loc[:, 'Other']])\n", + "fourth_col = fourth_col_df.T.rename(str, {0: 'Year', 1: 'Guest type', 2: 'Percentages'})\n", + "fourth_col" + ], + "execution_count": 63, + "outputs": [ + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: FutureWarning: Intepreting call\n", + "\t'.rename(a, b)' as \n", + "\t'.rename(index=a, columns=b)'.\n", + "Use named arguments to remove any ambiguity. In the future, using positional arguments for 'index' or 'columns' will raise a 'TypeError'.\n", + " This is separate from the ipykernel package so we can avoid doing imports until\n", + "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:8: FutureWarning: Intepreting call\n", + "\t'.rename(a, b)' as \n", + "\t'.rename(index=a, columns=b)'.\n", + "Use named arguments to remove any ambiguity. In the future, using positional arguments for 'index' or 'columns' will raise a 'TypeError'.\n", + " \n", + "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:13: FutureWarning: Intepreting call\n", + "\t'.rename(a, b)' as \n", + "\t'.rename(index=a, columns=b)'.\n", + "Use named arguments to remove any ambiguity. In the future, using positional arguments for 'index' or 'columns' will raise a 'TypeError'.\n", + " del sys.path[0]\n" + ], + "name": "stderr" + }, + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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YearGuest typePercentages
01999Other0.0180723
12000Other0.0532544
22001Other0.0382166
32002Other0.0440252
42003Other0.0903614
52004Other0.115854
62005Other0.135802
72006Other0.15528
82007Other0.241135
92008Other0.121951
102009Other0.220859
112010Other0.163636
122011Other0.184049
132012Other0.213415
142013Other0.138554
152014Other0.153374
162015Other0.14
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" + ], + "text/plain": [ + " Year Guest type Percentages\n", + "0 1999 Other 0.0180723\n", + "1 2000 Other 0.0532544\n", + "2 2001 Other 0.0382166\n", + "3 2002 Other 0.0440252\n", + "4 2003 Other 0.0903614\n", + "5 2004 Other 0.115854\n", + "6 2005 Other 0.135802\n", + "7 2006 Other 0.15528\n", + "8 2007 Other 0.241135\n", + "9 2008 Other 0.121951\n", + "10 2009 Other 0.220859\n", + "11 2010 Other 0.163636\n", + "12 2011 Other 0.184049\n", + "13 2012 Other 0.213415\n", + "14 2013 Other 0.138554\n", + "15 2014 Other 0.153374\n", + "16 2015 Other 0.14" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 63 + } + ] + }, + { + "metadata": { + "id": "rnftH0-SpGyO", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1969 + }, + "outputId": "23e5e11f-76a5-44bc-c79b-4eaeca89b46d" + }, + "cell_type": "code", + "source": [ + "merged_df = first_col.append(second_col).append(third_col).append(fourth_col)\n", + "merged_df" + ], + "execution_count": 64, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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YearGuest typePercentages
01999Acting, Comedy & Music0.903614
12000Acting, Comedy & Music0.739645
22001Acting, Comedy & Music0.726115
32002Acting, Comedy & Music0.622642
42003Acting, Comedy & Music0.560241
52004Acting, Comedy & Music0.384146
62005Acting, Comedy & Music0.37037
72006Acting, Comedy & Music0.360248
82007Acting, Comedy & Music0.255319
92008Acting, Comedy & Music0.207317
102009Acting, Comedy & Music0.208589
112010Acting, Comedy & Music0.351515
122011Acting, Comedy & Music0.337423
132012Acting, Comedy & Music0.268293
142013Acting, Comedy & Music0.427711
152014Acting, Comedy & Music0.392638
162015Acting, Comedy & Music0.45
01999Government and Politics0.0120482
12000Government and Politics0.0828402
22001Government and Politics0.0382166
32002Government and Politics0.0691824
42003Government and Politics0.10241
52004Government and Politics0.22561
62005Government and Politics0.160494
72006Government and Politics0.192547
82007Government and Politics0.170213
92008Government and Politics0.20122
102009Government and Politics0.208589
112010Government and Politics0.181818
122011Government and Politics0.165644
............
42003Media0.246988
52004Media0.27439
62005Media0.333333
72006Media0.291925
82007Media0.333333
92008Media0.469512
102009Media0.361963
112010Media0.30303
122011Media0.312883
132012Media0.317073
142013Media0.307229
152014Media0.325153
162015Media0.24
01999Other0.0180723
12000Other0.0532544
22001Other0.0382166
32002Other0.0440252
42003Other0.0903614
52004Other0.115854
62005Other0.135802
72006Other0.15528
82007Other0.241135
92008Other0.121951
102009Other0.220859
112010Other0.163636
122011Other0.184049
132012Other0.213415
142013Other0.138554
152014Other0.153374
162015Other0.14
\n", + "

68 rows × 3 columns

\n", + "
" + ], + "text/plain": [ + " Year Guest type Percentages\n", + "0 1999 Acting, Comedy & Music 0.903614\n", + "1 2000 Acting, Comedy & Music 0.739645\n", + "2 2001 Acting, Comedy & Music 0.726115\n", + "3 2002 Acting, Comedy & Music 0.622642\n", + "4 2003 Acting, Comedy & Music 0.560241\n", + "5 2004 Acting, Comedy & Music 0.384146\n", + "6 2005 Acting, Comedy & Music 0.37037\n", + "7 2006 Acting, Comedy & Music 0.360248\n", + "8 2007 Acting, Comedy & Music 0.255319\n", + "9 2008 Acting, Comedy & Music 0.207317\n", + "10 2009 Acting, Comedy & Music 0.208589\n", + "11 2010 Acting, Comedy & Music 0.351515\n", + "12 2011 Acting, Comedy & Music 0.337423\n", + "13 2012 Acting, Comedy & Music 0.268293\n", + "14 2013 Acting, Comedy & Music 0.427711\n", + "15 2014 Acting, Comedy & Music 0.392638\n", + "16 2015 Acting, Comedy & Music 0.45\n", + "0 1999 Government and Politics 0.0120482\n", + "1 2000 Government and Politics 0.0828402\n", + "2 2001 Government and Politics 0.0382166\n", + "3 2002 Government and Politics 0.0691824\n", + "4 2003 Government and Politics 0.10241\n", + "5 2004 Government and Politics 0.22561\n", + "6 2005 Government and Politics 0.160494\n", + "7 2006 Government and Politics 0.192547\n", + "8 2007 Government and Politics 0.170213\n", + "9 2008 Government and Politics 0.20122\n", + "10 2009 Government and Politics 0.208589\n", + "11 2010 Government and Politics 0.181818\n", + "12 2011 Government and Politics 0.165644\n", + ".. ... ... ...\n", + "4 2003 Media 0.246988\n", + "5 2004 Media 0.27439\n", + "6 2005 Media 0.333333\n", + "7 2006 Media 0.291925\n", + "8 2007 Media 0.333333\n", + "9 2008 Media 0.469512\n", + "10 2009 Media 0.361963\n", + "11 2010 Media 0.30303\n", + "12 2011 Media 0.312883\n", + "13 2012 Media 0.317073\n", + "14 2013 Media 0.307229\n", + "15 2014 Media 0.325153\n", + "16 2015 Media 0.24\n", + "0 1999 Other 0.0180723\n", + "1 2000 Other 0.0532544\n", + "2 2001 Other 0.0382166\n", + "3 2002 Other 0.0440252\n", + "4 2003 Other 0.0903614\n", + "5 2004 Other 0.115854\n", + "6 2005 Other 0.135802\n", + "7 2006 Other 0.15528\n", + "8 2007 Other 0.241135\n", + "9 2008 Other 0.121951\n", + "10 2009 Other 0.220859\n", + "11 2010 Other 0.163636\n", + "12 2011 Other 0.184049\n", + "13 2012 Other 0.213415\n", + "14 2013 Other 0.138554\n", + "15 2014 Other 0.153374\n", + "16 2015 Other 0.14\n", + "\n", + "[68 rows x 3 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 64 + } + ] + }, + { + "metadata": { + "id": "RkEqpku3s6ho", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "df2a565c-d31f-401d-d0da-67b42ddc2b16" + }, + "cell_type": "code", + "source": [ + "type(merged_df.iloc[0, 0]), type(merged_df.iloc[0, 1]), type(merged_df.iloc[0, 2])" + ], + "execution_count": 74, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(int, str, float)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 74 + } + ] + }, + { + "metadata": { + "id": "F1eEgi83vjY4", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 85 + }, + "outputId": "6f586d3b-98fc-4a1a-82a2-ab8436003725" + }, + "cell_type": "code", + "source": [ + "merged_df.dtypes" + ], + "execution_count": 78, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Year object\n", + "Guest type object\n", + "Percentages object\n", + "dtype: object" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 78 + } + ] + }, + { + "metadata": { + "id": "E8XBAr8rz_Na", + "colab_type": "code", + "outputId": "a7183199-3f34-479b-c0d1-d3ceaa41f85a", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 491 + } + }, + "cell_type": "code", + "source": [ + "import matplotlib.ticker as ticker\n", + "\n", + "plt.figure(figsize = (10, 7))\n", + "ax = sns.lineplot(x = pd.to_numeric(merged_df['Year']),\n", + " y = pd.to_numeric(merged_df['Percentages']),\n", + " hue = merged_df['Guest type']\n", + " );\n", + "plt.title(s = \"Who got to be on 'The Daily Show'?\",\n", + " x = 0,\n", + " y = 1.11,\n", + " fontsize = 20,\n", + " ha = 'left')\n", + "plt.suptitle(t = 'Occupation of Guests, by year',\n", + " x = 0.13,\n", + " y = 0.95,\n", + " fontsize = 16,\n", + " fontweight = 'ultralight',\n", + " ha = 'left')\n", + "ax.set(xlabel = '',\n", + " ylabel = '',\n", + " xticks = range(2000, 2013, 4)\n", + " );\n", + "\n", + "xlabels = ['2000', \"'04\", \"'08\", \"'12\"]\n", + "@ticker.FuncFormatter\n", + "def major_formatter(x, pos):\n", + " return xlabels[pos]\n", + " \n", + "for tick in ax.xaxis.get_major_ticks():\n", + " tick.label1.set_horizontalalignment('center')\n", + "ax.xaxis.set_major_formatter(major_formatter)\n", + "\n" + ], + "execution_count": 126, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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BA1SpUkVJlRw3ZkaVKlWOqZVUiZWIiBRaSqrkeDvWY06JlYiIiEiYKLESERHJ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\nV+A8ZxFdp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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "LuacMjSf2ses", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 3 — Who were the top 10 guests on _The Daily Show_?\n", + "\n", + "**Make a plot** that shows their names and number of appearances.\n", + "\n", + "**Hint:** you can use the pandas `value_counts` method.\n", + "\n", + "**Expectations:** This can be a simple, quick plot: exploratory, not explanatory. \n", + "\n", + "If you want, you can add titles and change aesthetics, but it's _not_ required to pass the Sprint Challenge." + ] + }, + { + "metadata": { + "id": "tbwfBN3HsFlh", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 359 + }, + "outputId": "9ef66423-cba4-46fa-c238-d16bc36dbf0f" + }, + "cell_type": "code", + "source": [ + "top_guests = df['Guest'].value_counts()[:10].to_frame()\n", + "top_guests" + ], + "execution_count": 117, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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Guest
Fareed Zakaria19
Denis Leary17
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Ricky Gervais13
Paul Rudd13
Tom Brokaw12
Will Ferrell10
Reza Aslan10
Richard Lewis10
Bill O'Reilly10
\n", + "
" + ], + "text/plain": [ + " Guest\n", + "Fareed Zakaria 19\n", + "Denis Leary 17\n", + "Brian Williams 16\n", + "Ricky Gervais 13\n", + "Paul Rudd 13\n", + "Tom Brokaw 12\n", + "Will Ferrell 10\n", + "Reza Aslan 10\n", + "Richard Lewis 10\n", + "Bill O'Reilly 10" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 117 + } + ] + }, + { + "metadata": { + "id": "5-4Q3Qh81RH6", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 432 + }, + "outputId": "3db82ed3-c41b-4be7-e1f5-98a64eb2be47" + }, + "cell_type": "code", + "source": [ + "plt.figure(figsize = (15, 7))\n", + "sns.barplot(x = top_guests.index,\n", + " y = top_guests.Guest);" + ], + "execution_count": 124, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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BEAAAoDOCIAAAQGcEQQAAgM4IggAAAJ0RBAEAADqz5kGwqm5RVWdM/H2/qp66aJgDq+qS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\nyQdrcFQNV63+Nck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"provenance": [], + "collapsed_sections": [], + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "metadata": { + "id": "i-n_5en3ER1o", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Data Science Unit 1 Sprint Challenge 2\n", + "\n", + "# Storytelling with Data\n", + "\n", + "In this sprint challenge you'll work with a dataset from **FiveThirtyEight's article, [Every Guest Jon Stewart Ever Had On ‘The Daily Show’](https://fivethirtyeight.com/features/every-guest-jon-stewart-ever-had-on-the-daily-show/)**!" + ] + }, + { + "metadata": { + "id": "Thm2n5FF2Fnp", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 0 — Run this starter code\n", + "\n", + "You don't need to add or change anything here. Just run this cell and it loads the data for you, into a dataframe named `df`.\n", + "\n", + "(You can explore the data if you want, but it's not required to pass the Sprint Challenge.)" + ] + }, + { + "metadata": { + "id": "0rTHgzJIuRS7", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "\n", + "df = pd.read_csv('https://raw.githubusercontent.com/fivethirtyeight/data/master/daily-show-guests/daily_show_guests.csv')\n", + "df.rename(columns={'YEAR': 'Year', 'Raw_Guest_List': 'Guest'}, inplace=True)\n", + "\n", + "def get_occupation(group):\n", + " if group in ['Acting', 'Comedy', 'Musician']:\n", + " return 'Acting, Comedy & Music'\n", + " elif group in ['Media', 'media']:\n", + " return 'Media'\n", + " elif group in ['Government', 'Politician', 'Political Aide']:\n", + " return 'Government and Politics'\n", + " else:\n", + " return 'Other'\n", + " \n", + "df['Occupation'] = df['Group'].apply(get_occupation)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "OS0nW1vz1itX", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 1 — What's the breakdown of guests’ occupations per year?\n", + "\n", + "For example, in 1999, what percentage of guests were actors, comedians, or musicians? What percentage were in the media? What percentage were in politics? What percentage were from another occupation?\n", + "\n", + "Then, what about in 2000? In 2001? And so on, up through 2015.\n", + "\n", + "So, **for each year of _The Daily Show_, calculate the percentage of guests from each occupation:**\n", + "- Acting, Comedy & Music\n", + "- Government and Politics\n", + "- Media\n", + "- Other\n", + "\n", + "#### Hints:\n", + "1. Use pandas to make a **crosstab** of **`Year`** & **`Occupation`**. ([This documentation](http://pandas.pydata.org/pandas-docs/stable/reshaping.html#cross-tabulations) has examples and explanation.)\n", + "2. To get percentages instead of counts, use crosstab's **`normalize`** parameter to normalize over each _row._ ([This documentation](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.crosstab.html) describes the parameter and its options.)\n", + "3. You'll know you've calculated the crosstab correctly when the percentage of \"Acting, Comedy & Music\" guests is 90.36% in 1999, and 45% in 2015." + ] + }, + { + "metadata": { + "id": "sRMc0H_5z6ff", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "Nqf9oJJDDu-d", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 2 — Recreate this explanatory visualization:" + ] + }, + { + "metadata": { + "id": "scozkHQc0_eD", + "colab_type": "code", + "outputId": "64a105e6-8fa5-45e5-c78e-d29fcd19b3f2", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 406 + } + }, + "cell_type": "code", + "source": [ + "from IPython.display import display, Image\n", + "url = 'https://fivethirtyeight.com/wp-content/uploads/2015/08/hickey-datalab-dailyshow.png'\n", + "example = Image(url, width=500)\n", + "display(example)" + ], + "execution_count": 0, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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ZBtnkfptMLmk+J6HR1RolfR2cZ4kCMURmERt2i1wRFHvq1F3TaMmmGBsU6Ssc\nYr2i+Kd1Os1Vn5ZmVpiCJuZck3x6EGKy1fOa2ZVUchW77IdW6HRkFDF2VUh2WXSvXZPWkfVK4jva\nbpaM+oe2aylETa9BQoMCP+TJNUXbkF1mSTbbJAKRLcSGg6ZzxlWFLui2e3pSMscpM49oj05Oyt+d\nJLOW0hugLesJvUYFgFEtaq9AXYqY5NMDEZOtnuf01Jo+rL2qTwrGfiiZE1VfQwYxZ1XoYvvVgsdk\nr1Y6RKZ6Je9oulkyi7g0e35Zbs/3/J6cJ84pTja5SKfEtWZsrPas7waIIbKOmHHStIxu566kAdOT\nT5IvzB1vTCfP/5VNTL9tTRLI/KnebnX+yHFU06RP6A6cpl4SxmT47WjTZnEnuMe8/saq8Is1ZrYX\np7E3toO8Ysxy3+0x9LQ9d74403/P72ktVRdHxirz0/T3mf3ZwwQ8iBwglnxoUR/9M80oTuCJwRXP\nTi5JNHyemzfAnDoIIAbEhAeSTIKFKDPhDIqetWV40BsCiAExM9r0CR5acQLPCx5ESfbqPhPz9yaR\nNiIQQCz9zUmj77ts9AQaP4z/ccEDTQv3GfVmo+RV5K93y1ULSMQQQAyImaowD1krp6iPyW/6HquG\no4geMQQQm0D0KpW0Jwztqj2tYapaZyaqHmvUNMtTYBgCiCGYRl7q1knzKQ/payiXQAAxBAKBAGII\nBAIBxBAIBAKIIRAIIIZAIBBADIFAIIAYAoFAADEEAgHEEAgEAoghEAgEEEMgEEAMgUAggBgCgUAA\nMQQCgQBiCAQCiCEQCAQQQyAQCCCGQCAQQAyBQAAxBAKBAGIIBAIBxBAIBAKIIRAIIIZAIBBADIFA\nIIAYAoEAYggEAgHEEAgEAoiNFl98kcNv8csvvszhVv/wix/lb6N/9MUPoRYQA2JADIgBMSAGxIAY\nEANiQAyIATEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAM\niAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAMiAExIIYAYkAMiAExIAbEgBgQ\nA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyI\nATEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsQQ0RDTtL7wyqDbbGri\nXzWb3QHz716z1QdiQAyIAbEpI9aoFAuFQpF/sWm8Vij1mJe6JeOlYtt5oW78uwHEgBgQA2JTRUwr\nWMHDZr9YpIp17ZcKRLFWodRtFwsaEANiQAyITROxfqFSbZZ4xDQj4xr0dcpKpPk40FOzZn/Q0v9j\nw1YpdPWMrdAEYkAMiAGxqTYnLZA4xKoFK8FqsHmXxZWekNXJezQgBsSAGBBLJWLFQtnO0ohYhmtW\nUlYqlIAYEANiQCzdiBUKFeEH+hfMD0AMiAExIKYwYtVCy7hDCcSAGBADYmoipvf+16uFolUp1q0C\nMSAGxICYWoiZhWNmJVm/URRKNIAYEANiQCz9iOl1F0Zff1t/pdQaADEgBsSAmHKI6SOP6noSVp9o\nwSsQA2JADIglhNigXfZPwn74BQKBQATGlBDTgpMwIIZAIFKLGEnCBrplpS6ak2hOojmJ5qRizcmi\nnYSVC6UKHZ0ExIAYEANiSnXs62Mp9THiGhmKBMSAGBADYoohZo07mmCZGBADYkAMiAUiVrTtGnAD\nwIek+QjEgBgQA2LpRqxqTxrWLBjjI81o2T/qg42qQAyIATEglh7EBpoe+q1G4z9kxnxjUkTNhKvI\nToqoK6YVC/xcri0jVxsAMSAGxIDYtBBrFmiQDjBr+nwjaO1Em7zEz6qvTznW1uqFyY3/BmJADIgB\nsWDE7En2i2z9V9t8dohr6h0Tt9IEn3oExIAYEANiruakHQxF/Vaz2eYHFA3aTdkz2vquPwRiQAyI\nAbHJIaZcADEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAM\niAExIAbEgBgCiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAMiAExIAbEgBgQ\nA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyI\nATEgBsSAGBBDADEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBAD\nYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQCx3iO12doAYEANiQExZxNZnZmaWgBgQA2JATFHE\ndmeMqAExIAbEgJiaiK2biM3uAjEgBsSAmJKIdUzEZhaAGBADYkBMScSG85Zim0AMiAExIKYkYnYq\nNncAxIAYEANiKiI2XLYUWwZiQAyIATElETuYtRSLVy0GxIAYEANi0w7rBuXMPBADYkAMiCmJ2HDB\nUmwViAExIAbElETMKniNVywGxIAYEANi04+apdgiEANiQAyIKYnYcC52sRgQA2JADIilIOIXiwEx\nIAbEgFgaYilusRgQA2JADIilIWIXiwExIAbEgFgqIm6xGBADYkAMiKUjYhaLATEgBsSAWDoiZrEY\nEANiQAyIpSTiFYsBMSAGxIBYWiJWsRgQA2JADIilJWIViwExIAbEgFhqwi4Wi/TUECAGxIAYEEtN\nxCkWA2JADIgBsfTEevSnhgAxIAbEgFiKInqxGBADYkAMiKUoduxisfB9+0AMiAExIJamiFwsBsSA\nGBADYmmKA7tYrAPEgBgQA2IqIha5WAyIATEgBsTSFYvRisWAGBADYkAsZQ3KaMViQAyIATEglrJY\njVQsBsSAGBADYmmLSMViQAyIATEglraIVCwGxIAYEANiqYsoxWJADIgBMSCWuohSLAbEgBgQA2Lp\niwjFYkBMuAB09Ah3Z3ens6vUVgMxhEKIRSgWi4HYas2I8MMzdxb0WE5iszo1Y1ELtc0Rl+ODWCfk\nnd31eavJLsl2d2tW7Ii7rLY+hX0GxKCWmoiRYrHgVCE6YvYTScKfkJ2o0wN5uWG3ko0cc32kJY2M\n2MGCsyqrXnnwzJK4yyLshKT2GRADYqoiFr5YLDpiy1GfcJnMCXmwOMPG0lQRW2DWZNMLsVnx2wBi\nQAyIRYiFkPlSdMRIPrQb+PkLCZ6QB/MzM4kpNipim+Yf7Q47szLNOy7e5oEYEANikSNssVhkxHa8\n21EeiCXSv2Plf7N6R9NObTZiezZxxMyHGRh71pxK1xOxJaE1GUEl9IkBMSBGWn1BCUtkxIzlzhvZ\n2FxYxJIIC4ZZq698x1RsbnqIORvX8UVs5oC2JmfHkFoBMSCWbcRCFotFRsxY7PJi4BDzuWTP2UVu\nW2qRn4eSPGJmK3Kd6/piFzHPJIvGz4tADIgBsaixad/ISxYx8wzdNJtRXGtnd10vIVglynRMZub1\nkqtdtvRqx/jJ+K9ecrDJNHQPNvXyg136e1fs8kMQDrj2rPHuWs15n/lxxseuWwu1/2KVMe/LH/wT\n3FvIBujrRBDbsZdi/or5mWa5u/aFYkm6i5bpCpsrv+4gZi75wL1gcyvIXuHL1fidC8SAWF4QC1cs\nFhUxszvIOi/n2C4cUvuwSjKVGefTaXJjvu78MVmxA7vlu2z/XhLrwn3ARaPLyMpzDpbIzcAaY0ht\naPecLekqrFs/LhA2D/42bm2Zpcyuk5VdZTKnZbELzv4j82aDu9fRWoF5pz1pLGpO2AkdmlFaq22v\nLrk0sAmhsHOBGBDLD2K7YYrFoiI2ayUY81xLdV24a+iL2M4s87she99xyROxZbaLiQu6ND3zO6CG\nENr0la05v3e/ZUl8adle2V3mE+dcH25eHxbnaDedG7FVRz5j+5YDEFuiq7QgILaeVGEJEEMoh1io\nYrGIiG3ap+Yqe0rZPdkLsySV8EWM/nJ2KKRts16ILczIOp8o1HNzVKkO/yEzq/RH0xSrEHje6tez\n2qQHc3z5xgJxynzDjns0vfMGiWE2Ys67TA53/BEzoZpdsPbgOoeYa+cCMSCWI8RIfdJ6coiR4oJd\nVpU50m5btTO/nc4q0ycmnL8z85udDu2otxKNxd3hgZ0xeSK24NVkntclMUu2TBDss77W6ZAUTP9x\nlXaqmZvwd5L0y2wNWn+oj6TaXXAQW3fesOreh6QNO79LerZciDn5m9maHPojNm+PdDVxnOcQc+1c\nIAbE8oRYiGKxaIgdzJIze452Uq3TweYL7kzChZj1l3Pk/GVu2y17IuaVUe7Sm5brhNUOzbCWaKuV\nNBOtt/zYl86vV8nKLNMUa4E0nGfIWvNZ4M482yBeFNp5NmKkJ23e/LU/YjTvMnr32X0m27lADIjl\nB7EQxWLREFt3zqNlutxF2s6pcemQHLFV+iZy/toa7kZGbJV2dR0Qzzo0SdykHVsdsmzzLb/wpfPr\nRWL9Ll3igkPcpr3gJY9+uHX795tuxOz25K7162DEuJZph2vVCjsXiAGxHCEWXCwWDbFF52zfoT7M\nSkYQ+iDGn787LFyRm5PMKW79DdcFZ1dsDTnEzLf8wp8xmoCr9j3WdabXX+iMWrJ/uyn2w81uLtuK\nrYp1LDZidnvSLiXzR8zu0ltwyj6cP5+VDs8EYkAsN4gFF4tFQsxMOuY6Zjh90EMZk6ER67BwLfgi\nNuPxes0fsQUesQVhDOaMvS7ugZ5zFj9LYmuSdPlbjdXOvJgfEcRM5TbtxqY/YjXm5sYqtxrRHoUM\nxIBY9hALLBaLhNi6CMDihBBbEjq1SSnqWBGrWWs7K7QmD5y8bdG5o3ogQ8xMMkmj1B8xbnj7MhAD\nYkBMbPv43NWKhNiiCIC52OQQm/MvdqWd2uRWZFzEfu7vrTnhiZjZm7W8I+3ysu4CzEvLtzp8I5G5\n3eBX7DrH7VQgBsSAmBMBxWJRENt1GUbv7VmnuTNaJjRiQ2YY5IFnn9guP4XZDrkbsMQQMm+vTwBi\nS7Rjn9tF8259zSGSNbE12aGfSRTblSO2zBgn7IR1V2tYr9RYrS3MiBsh27lADIjlCzFSLLY5OmLm\nyb5IMpgFcuozveurIe5Oyvq0lxhvh96dYqtcRkhqp+YYAXcCETPf8jNfutSxm4TscCOrVEzMtDpM\nJ6NVOCs8y8BBbIeZV0zYCTWaedZcu7gmvzu5iruTQCyniPkXi0VBbJ7LOpzChHW6eL5OzP7IMH3a\nq7THzVn2rMsZO4FZdfIbpk6sRmwJQMx6y190kHLabCYPTJ2YTdSseAHYZTy1iy3md6WI2e3JWX5V\naGHcKvncVecq0xERk+1cIAbEcobYcHnGZ8RKBMR2hVmp57hkan5zuLPonHGWcHPLxrMxAvq07YFD\nC3Mzs06fmHuWDDIptp4C2jSYcJiNw9lNAsJ6MGLWW+Y7ZFz4OnlpZvWAVLGStveSOM80kxUubXY2\nl7jhVW7ElmmPGV0VS+2FdfJucgvAGPl5sOhKJyU7F4gBsbwhRp4a0hkRsVVhPtdlLvcRnpwx5zl2\nUuzTpqWj687dyZq7p0mcnrrD9UrNyLiQI3Ywy75lXujsYzMxUqAi1Arzm2vdnpQjtjPDp1gLsg+r\nOS4u0EFPrrGToabTBWJALKOIkXNxfkTE5gRZNp0++fVZV0qyGRoxMtXM7DotsZDNC7vMyUFE3pkX\n53gIQkwy8QWtHZnd4e6CzEm7E9lKk9mdnVlPxEipGb8qzoYsSUsszFViZ7GYleZ7QAyI5Qmx4YL3\nKRAesR0XhLNOo2+XNKzocxg782ER09++aU0H6AxXnJX1/nSc1tss89TLAzIT1/zmMBxi+nxi37Yz\noZqwtnM7Qw6xZXmlsDPDl7kiB8tzXogty2i15w7T5z+jO+FgaZbbNPbPJTsXiAGxvCFmF4vN7o6U\niflHZ7223uF6bA6E+VBD7F2bjF2PiXeGHeMptOtimcGOMSlrlE/68os/Y8wtuyMsZHVH2oKWdSYe\ndEaaa3VHMoOtsW1eS3TvXCAGxPKFGBnWsjBGxOIGnbfLaqaRoqrlMX6mzxz7PFVzo83ln64AYgiV\nEfMuFps6Yuvk/uKB1fnTsc3dHeNnhkGsQ+6DLmTl2AViCKUR63gVi00dMWFWVXM0Zm1hYWmcnxkG\nMWdMdlYSMSCGUBsxz2KxqSM23GEVWzyYxEdGQWw9M8cuEEOojZhXsdj0EdPvLxLG5ickRnjE5jaz\nc+wCMYTaiHkVi6UAsaE9TX3nYFIfFwYx18MmgRgQA2JTDnmxWDoQm3CEvTuZrQBiCNURkxeLATEg\nBsSAmCohLRYDYkAMiAExZUJWLAbEgBgQA2LKhF0sxs3hB8SAGBADYuqEpFgMiAExIAbE1AlSLLYD\nxIAYEANiSsa6q1gMiAExIAbEVIoFcYJQIAbEgBgQUynsuZFpsRgQA2JADIgpFTVmsgggBsSAGBBT\nL+b4YjEgBsSAGBBTK4RiMSAGxIAYEFMslrhiMSAGxIAYEFMs+GIxIAbEgBgQUy24YjEgBsSAGBBT\nLthiMSAGxIAYEFMu2GIxIAbEgBgQUy+YYjEgBsSAGBBTMGixGBADYkAMiCkYtFgMiAExIAbEVIwl\n8tQQIAbEgBgQUzGcYjEgBsSAGBALioFGokdfdF6b0obYxWILQAyIATEgFhSVghMt8lrL/dKEwy4W\n+yUgBsSAGBALj1iTvNZ0vzThsIvFvv0DIAbEgBgQ8w+taUWdR6xuvtgaTGtT7GKxnwFiQAyIAbFw\noTchNSY7G0x5Uw7sYrEOEANiQAyIhYoqA5eO2NS3hRSLbR4AMSAGxIBYcAwKhfKQIlac/sYsztix\nUMtXOgbEgBgQixNt9k5koVCZ/saQYjFzNPji6g4QA2JADIj5tyb7DGLlRqVSaU23Y2x1hovZpfVd\nIAbEgBgQC9GaHJICi2JvqpuzMCPG3HIOusiAGBADYqO2JjUDsEqlqCvWn+bm7M7PSGJ+OeNdZEAM\niAGxGFFmW5P9UqGs/2ugl47Vp7tBf/qXFmdlkC1kuYsMiAExIBY9+lxrcjjsWb1hJabU4ssvphS/\n9Qs/JXPs2z/zK7/9BQKBUC3GhFhLPkqyyRTAfjnFrf7Bn/zjf4MMsh/7uV/5AY4JBAKICa1JOWJT\nCWaDD9aX5uRdZJtoTqI5ieZk3puTA6E1mUbEzJ7+VY8uslqWusiAGBADYpGjWyg0VEDMiJ3VBZlj\nGSqHBWJADIhFjgaPVZHclEwjYkZ0lqXFF3PZKIcFYkAMiEWOMj/gu0gal3V5V9nUEdPjYNOzi0z1\nclggBsSAWOQQxkpW7QRsUCyUprtB/ncydteXpF1k82qPGAdiQAyIRY2+UNSqV+wX2/p/ytOb2TUU\nYkbsrC7KHJtRuIsMiAExIBY1NBGrOhk8Oe3JLMI9KKRTk/f1L60DMSAGxPKJ2LBZNA1rTHuDQj/t\n6GBT2tc/r2L/GBADYkAsumKaOOnOoK1PsN+f+gZFemTbrqQcVkXFgBgQA2LZicjPndwRy2EVVAyI\nATEglmPETMi4LjL1FANiQAyI5RwxI5guMuUUA2JADIgBMSMO5hVVDIgBMSAGxJRWDIgBMSAGxOxY\nUlIxIAbEgBgQU1oxIAbEgBgQU1oxIAbEgBgQcys2q85QSiAGxIAYEFNaMSAGxIAYEFNaMSAGxIAY\nEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNa\nMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEJPHshqKATEgBsSAmEesK6EYEANiQAyIKa0YEANiQAyI\nBSvWAWJADIgBMQURcxSbWQdiQAyIATEFEVNAMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAG\nxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAYEFNaMSAGxIAY\nEFNaMSAGxIAYEAsXm7OpVAyIATEgBsRCxk4qFQNiQAyIATGlFQNiQAyIAbHoitWAGBADYkBMQcSo\nYktADIgBMSCmIGIpVAyIATEgBsSUVgyIATEgBsSUVgyIATEgBsSUVgyIATEgBsSUVgyIATEgBsSU\nVgyIATEgBsSUVgyIATEgBsSUVgyIATEgBsSUVgyIATEgBsSUVgyIATEgBsSUVgyIATEgBsTixe58\nKhQDYkAMiAGxmHGQCsWAGBADYkBMacWAGBADYkBsdMUWD4AYEANiQEw9xKhi81NTDIgBMSAGxJRW\nDIgBMSAGxJJRbEoT7wMxIAbEgFgyis3MLu8CMSAGxICYaogxiukd/JtADIgBMSCmGGKcYjNztQmn\nY0AMiAExIJaoYpNOx4AYEANiQGx0xZZnOcYmmY4BMSAGxIBYEoyt89nY5NIxIAbEgBgQSyZ2lsR0\nbCKlY0AMiAExIJZYOrY6x6djSx0gBsSAGBBTBzE9Oks8Y3Or407HgBgQA2JATOl0DIgBMSAGxJRO\nx4AYEANiQEzpdAyIATEgBsQmko7Nr48nHQNiQAyIAbExxW6NT8dml3aAGBADYkBMHcT02FwcezoG\nxIAYEANiSqdjQAyIATEgpnQ6BsSAGBADYlNIx5IbIA7EgBgQA2KTiPUFPh1bSGo2ayAGxIAYEJtQ\nOibM15PQbNZADIgBMSCmdDoGxIAYEANiSqdjQAyIATEgpnQ6BsSAGBADYlNPx0aZzRqIATEgBsQm\nH67ZrONnY0AMiAExIDaV4Gezno1d/wrEgBgQA2JpSMeWgRgQA2JATDHE+HQsbrcYEANiQAyIpSId\nWwJiQAyIAbEvlFzthZFSMSAGxIAYEJtydEZKxYAYEANiQEzpVAyIATEgBsSUTsWAGBADYkBM6VQM\niAExIAbEph47I6RiQAyIATEgNv1Yip+KATEx9vf0OARiQAyITTJ246diWUTs7bYV+/Sll9Yrr0Ig\ntrGix56h2YYez4EYEANi6U7FsojY3ooVW5Q1+5WNKIjtse8AYkAMiE0iFVsAYixiazQRA2JADIip\nkYp1gBiD2Mpr8soTIAbEgFhWU7FMI7YltCajIYY+MSAGxFRIxTKN2MohbU2uRUYsawHEgFg2U7HM\nIma2IF/R1uRTIAbEgFgmU7HMIvbc+L+ntDX5ikfsPzCKLl695d62vf1yn0Hs0CgYI2Uah3tGicbr\nt0AMiAGxlKVimUVs+4nTnjRak4+5bvp/49fs9uZTR6XXj61es0NZx/7h8zXSq7YPxIAYEEtVKpZd\nxF467UmDs+csYltOp9nK2r7w0hMJYodP3G8AYkAMiCUdB7NxUrHsIrZP2pNma3KfQWzbxOjpczP3\neuwka2zwiFnCbWysKF10AcSAWOqjFicVyy5iw8d2e9JsTTIkmaitvSU4bRupltlafKLT9XLNjdhb\nkoHtm79UtV8MiAGxbKZiGUbsud2efGJWjAl51SvKmf7DK8c1OyfjELNuFBi/fM6V0AIxIAbEUpCK\nZRgxuz351oKHImamU1aJhdnXpadYT5nS2DWfiv1tkroBMSAGxMaYis0DMYsaqz35ysq2HJJM237t\nLxn1E3ukmOwxk2F5DDvSCy5eb28AMSAGxCaRiq0DMZMaq/H31Eqy+MYhG/pfrjAFrjLE9rfWuL8H\nYkAMiI01FZsDYiY1Zs61ZSdZoyD2XPx7IAbEgFhqUrEsI2a1Eu2+ex6xX/tXtp3YC0LslVVA9vzl\n3hYQA2JALG2pWKYRe87MZsEXTKzwYyfXfPvEHju3M9GxD8SAWOpSsUwjts/MKybcnfxPuHdsOEUU\nsruT5jLM3yETA2JALHWpWKYRs9uTa8Ohq/7eqqd4bINl1fAztftuxA4dFIEYEANiaUrFso3Yczo3\nolCxv7J9OHxrloc9dl56sj88fCkZdmTmZluHw9fWLcq1V0AMiAGxMaZic9FSsWwjtk9nqRbHTq5w\nc1gzQ8IfuxCjv1xTefQkEANiisR6tFQs24iZ7cW1oYAYS5Y9byKdp2Jr24WY88u1/Q0gBsSA2Ngj\nWiqWccSeO91f/Hxiv07mE3MmPbRnDHs+3JZMxbNttSjfDg+NqlcgBsSAWIpSsbw+Afw/e63P48o9\n6NuYu/W155O/3+7tq77RQAyIKZaKzR4AMR/EfpS/jQZiQEy1VKwGxIAYEANi2U/FgBgQA2JATOlU\nDIgBMSAGxJROxYAYEANiQEzpVAyIATEgFi0Gmh099lWt2ewOgNg0UjEgBsSAWLSoFkhQxbol49/F\nNhCbQioGxIAYEIsWFQcxzTGMvDJtxTKE2HAhbCoGxIAYEIuMWNMMR6xBUX+pP2gV2eQMiI0YnbCp\nGBADYkAsWhQKZeGVlm6YnZDVgdjEUzEgBsSAWFTEKsIrei+Z1adfKpSA2MRTMSAGxIBYVMSq7gam\n8AMQSzAV2wViQAyIJYmYZrcdgdikUrElIAbEgFjCiFXrlUq1DcQmlIrN7AIxIAbEkkXMivIAiKUi\nFQNiQAyIRYqmUdVaMYrFykAsFakYEANiQCxSdIuFup6D9cu0tBWITTUVA2JADIhFbVCa/9+npRZS\nxL78AjF6/JSl2G9jTyByG+NATKQLiI0vfstC7OewJxBAbOKIoTmZSCwF94qhOYnmJJqTQCy9sRvc\nKwbEgBgQA2JKp2JADIgBsSjRc25KArGUpGJADIgBsYiINayf6GjvKrGrjAHgY0vFOkAMiAGxZJqT\nxULRLNXX6Lw7+lQ8LfulKhAbUyq2AMSAGBBLBjG9Yr+sV4q1i3RmV2NSRF0xjXkJiE0uFQNiQAyI\nRYpBmQyepJNZtMlLjSlvUCYRC0rFgBgQA2IRFasXXE8FMfKygnuOHiA2iVQMiAExIBY1+i19gn3+\n+WyDdrPZ6k99g7KJWEAqlkvE9v7p3/zXgBgCD8/NRiqWR8Rer+ixBcQQQCwTqVgOETtcMxBbeQ7E\nEEBMkaj5pWI5RGxjxYpXQAyIATE14mDWJxXLH2IvV0i8BmJADIipn4rlDrF9x7CVtX0gBsSAmPKp\nWN4QO3yyklfFgBgQUz8VWwdiw+crbDw5BGJADIgplIrNAbHXtl7fy6FiQAyIZTMVyxdidnXFyve+\n+PO2YjkqFwNiQCybqVi+ELOrKzb0YUdbuVMMiAGxbKZiuULMrq5Ye2uMndzKW7kYEANi2UzF8oTY\nvlMfZiDm3KfMi2JADIhlMxXLEWJErS17Fgvy77wUWgAxIJbNVCxHiNnVFY8PyVQ8+2u5UgyIATHF\nY12eiuUHMVJdYYhlzydGFMtHoQUQA2Kqx5w0FcsNYqS6YntIEXNgy4ViQAyIZTMVyw1ipLpiyCI2\nfGUr9hSIpTZqCwurQAyIeadieUHMqa7gEXOGIeWgXExNxDbNw7YGxIAYk4rV8ojYPj/7DjPHPikX\newnEUhidBeugnQViQIxJxWYP8ofY4eMVbjZX9kEhuSkXUw+xXXtqdT2AGBDzTMXygdiW0H/PIuYU\nvWa90EI1xA5qs45hC0AMiHmmYrlA7LXIFPfItrc5KRdTDLF1StjM/C4QA2KeqVgeECNK0W4v/rmT\npFzscbYLLZRCrDNHCZtdH9vHALEspGJ5QIyrrpAglpNyMYUQ212ghM3UDsb3QUAsC6lYDhDbtluL\nh56I5aNcTBnEDpYYwpZ2x/lRQCwLqVj2EduXPNtIRIxAl+lyMVUQY/rzZxY64/0sIKZgdMRULPOI\nidUVcsSccrFtIDblxgLTGTa3Pu5PA2IqxoKQimUesS1Zd5cbsRw8UlcFxDpMZ9hsbfyfB8SykIpl\nHbHX0iIwCWJOudgeEJPEztJCbXfca7i7yHSGLR9MYJ8AsSykYhlHzF1d4YWYM81FZsvFRkFsxyrX\nWh8nLAc1hrCF3YnsEyCmciq2lA/E3NUVnojRORIzWmgxCmLzBJfFzXGt3ipb3NqZ0D4BYiqnYjO7\neUBs24MlKWLDvWyXi42AGJsjzS7tjOPaOpniViCWxVQs04jJqit8EHPKxTaAmKQxydw1TLp7bIfr\nzz+Y3D4BYllIxbKMmLS6wg8xMutYNsvF4iM2P+OKJLvHdidX3ArEspiKZRmxLc/WoRdiTrnYcyAm\nb0wykVD32AFX3Loz2X0CxLKQimUYsdfeU+x4IjZ8mt1ysbiIkcbkzuaiwFgS3WNccevmpPcJEMtC\nKpZdxDyqKwIQc8rFXgMx/ppnlBYerM8n2z3WYZY3uzr5fQLEspCKZRexDZ9Oem/EnI607JWLxURs\n1e4Es/+5W5tLrHts8sWtQCwzsUtTscwitu1X9OWDGC0XewvEjGPF7rFiGo47S7NJdI8dLLNL2J3K\nPgFi6saSk4plFbF931ahH2LOW7NWLhYPsQXZ42WGCXSPTaW4FYhlMRXLKGLe1RXBiDnlYk+AGGlM\nzrnzqNG6xzYnOlkFEMtwKraTVcS2/JMpf8QyWi4WBzHSmJRmSu7usYWQ3WOdaRW3ArHspWILGUXs\ndcADjAIQy2a5WBzEbGyWvX7v7h5bCu4e44tbD6a5T4BYBlKxTiYR86uuCIWYo1iWysViIEYak37Q\nuLvHln27x6Za3ArEspiKZRKxjaAhkIGIHWbwkbrREfNtTDIsrbq6x1Y9u8fYJ7HNdaa9T4BYFlKx\nfy6DiG0HTqkTiJijWIbKxaIjthjQmGS4Ww7XPTbt4lYglsVU7Keyh9h+cM19MGK0XCwzikVGbDNE\nY5LxKbh7bGJPYgNi+UrFfitriAVUV4RFzFEsM+ViURE7CNeYZJuKvt1jB9ObrAKIZTwVyxpiWyHs\nCYMYLRfLiGJREQvfmGSg8u4em+ST2IBYXsIe9fEvZGurgqorwiPmKJaRcrGIiNmNydmorT5599h6\nOopbgVjGwm4uLGRqowKrKyIg5hRaZEOxaIiRxmScUZHu7rH5yT6JDYjlJmpR+zwUCPum4tNhEohl\nq1wsGmJ2Y3Ix5oe5usfSUdwKxDKais0trWbGse1wDywKi1imysUiIRa3MckcXauSWa0XdtO1T4BY\nVlIxM9/PhGR7IR+AGxaxTJWLRUFslMYkDbF7bD51hxgQy0oqRq+Ty+s7Km9PmOqKaIg5fWwZUCwK\nYsujNSZpMN1js+vp2ydALFOpGCPZ5q6im/M07BQ64RFzysUeK19oEQGxzsiNSSas7rHZ2kEK9wkQ\ny14q5lw0F2oKSvYqdNIUATGnZkP5crHwiB3MJdGYZJa3ulRL5+EExDIQu3/zt2e8Ynax1jlQaFvC\nVVdERswpF3uaG8QSa0ymPoBYFuLLL/6tzdrCrKdkc+pI9iS8NZEQGz7PRrlYaMRIY3I3+4c/EMsG\nYuawo9315QVPyNS4dRmyuiIGYk652Eulv+qwiJHG5GoODn8gliHEzNgJkCzVty7DVlfEQWyYiXKx\nsIgtz2RwJAcQywliVltidWneW7LUFmGErq6IhZhT9KpyoUVIxHLUmARiGUWMSDbnI1kKb10+jfSA\noqiIZaJcLCRiOWpMArEsI2Z2jXRqi96SpawI41U0YyIjloVysXCI1XLUmARiWUfMkizo1uVqp9OZ\nPmYRqitiIub0ualbLhYKsZ08NSaBWC4QM2PXVzL7yr2wsFir1TZ106awFU8iVnLFQMwpF9vINGLz\neWpMArH8IGZdon1vXYopmm7acm1iaVqU6orYiJFPUbZcLAxi+WpMArGcIUYkm5+JHvNWmrY+pjQt\nUnVFfMSccrHtzCJmNyZndvJy+AOx/CFmhn8RRnDMWmlaLaksLVp1xQiIkedZKlouFgIx+3ut5ebw\nB2I5RcyWzOfWZehI5GyJVl0xCmJOudieil91MGJ2Y3I+P4c/EMszYkboRRi1JT2tGkGxBDqQX8Wo\n4IqJ2PDQvgu68lzBe5SBiOWuMQnEgBjnWaezqjcRddKiJWgjT5QXtbpiJMSccrGVNfXGUQYitpC3\nxiQQA2I+1/ROZ7MWLk0bVbEncebJiY2YcxNBL3t9nTHEVnPXmARiQCyZNG00xSJXV4yImFMuZlSM\nqdU1FoDY7mzuGpNADIiNmKbNJqDYXrye9hEQYxVb2Xob9d3rCwtLtemMcQhALIeNSSAGxEbFbHTF\nYlRXjIzYcH+DKra2HS0FdB5qMAXK/BGzG5Nz+Tr8gRgQS0ix2C2YGNUVoyOm53+PGcaiFI3tiIO1\nJkmZL2KkMdnJ1+EPxIDYiLFJyl9jKvYq7vw4IyI2HL5co4w9Cd2WPZDfuZ0QZb6I2Y3J5Zwd/kAM\niI0a6yMpFqu6IhnEhofbTNfYRsiusWXfIfTjpswPMdKYPMjZ4Q/EgNh0FXsS+ylEoyOmE7rF9vCH\n6RrbDFE3N0bKfBDLaWMSiAGxKSsWr7oiMcT0rjGuhz+4MWlLsbQ4PxXKfBBbzGdjEogBsekqtjfC\nOMZkENM75Zge/sdBPfyLzDQ3O5u1cJQl2L7zRmwzp41JIAbEklUs4ikUt7oiUcT0dHAtbPHrqnvO\n1DCUzS4sryZDmSdiB3ltTAIxIJZQkO7u+UinatzqioQRGx5uhSt+Jd1Om67fTIoyT8Ry25gEYkAs\nqViKoRiprngb6xMTREzv4We6xlY8i19tpha9lhKSss3kEbMbk7MHOTz8gRgQm5pie2sjTU+YKGL6\n2jxhevjlBR+1cG3mYMrmYzf6PBA78EwRgRgQywFih2+TWYtoih2+JP3pT2N+XsKI6Ykh0zX2WNI1\nRkr1wwnkT9lSzJTJA7HFgBQRiAGxDCNmlBg8fpmIYxEU26edULEfApk4YnrxK9vDLw4hIKX6kbqd\nPCmbjTeVpByxPDcmgVjeEXv7lKRDSUysRRQLSgheMS23+LNEJ4+Yf/HrcvypugzKXKOVFuLUBksR\ny3VjEojlGzHulF17Pno6RnKOJb8Pfc6kO6M8dWgciInFr4eubGeEqbo66zV+Lrbl6JmTFLHlPDcm\ngVieEeMIs0odXo046/xBoGKvN/iPfB7/w8aDmL6K0uJXku2M/ECBTo0+w3g2cu4kQ6yT68YkEMsv\nYofPVySxtjXaRKf+ir3dfsx92uPtUdAcF2Ly4tfF5J5Iu7vItCkjDkz6S3/u3xT3GemrG3djcn9v\nP52HPxDLJ2JcFzYfo/Xy+yi2J2R+o3bDjQ8xXvinxv6QlOqPEJtMq7IWJoF6u/d6+/mG3ZW4trG1\nvfd2co3Jw71X2xvm5edpKp8PBcTyiBhP2NZrsV05Ci8eih2+4pOwBHrgxogYc8fDerbbbsJd5wc1\nqticT8nG3t7L7acbj6VXmydPt1/v0cbkOKbNeLun08keK0/epvDwB2I5RIwnzDgsD18+WUnKGEcx\npvdof2tN6HxLYKvHiphQ/PpHE892dplHSC3uShOvjZUQ8fjv+8M//ePfSuThn1zb8bWOp6y/YR+I\nAbGpI8alRHQmQNGZ+L38u+K0+682hH63ZE6EMSPG76lf/InEZ4jYZDr4a6TbyTvx8o/v6C3MRHbr\nob4KvmvwCogBsekixhPG9+K/eppMLz/38JC3Qu/b45dJ9auMHTG+2f2dP5D0DBEHZNT8t378J/7u\n7XCJl3/oLcxXse/M6G3HrY214A95DsSA2BQR8yPMPI6F24f6/cO3Iyn2WnBxK8GnPI4fMaEM5e9J\nukNo/5//m372j3znF6Mw9Q//5q8F/s3axvOXe1HWVW+8Pn0Sfh3S1r0PxHKEGFvH6flkjD1XL/+r\nuIp966d/MQERp4rYaM9282yxvd6OmnhtbDzXu/HfmnViex79VeJbtrZf74/YdrS/uI3tl3uHw+cp\n7d4HYrlBjCPMbwbTw1euXv79GIr9gT8inFNJd6ZMBrHh8B//xZjPduPbanqdgtFZH82utY2n29t7\nzPWGFrsadw7/gV8OA9CrvcO4bUf7DihJ5NPZvQ/EcoJYaMKs9OP5iL38h//U35V0RcW0ENNL9X/6\nl+M82+1wz8i49JQrTEeTiIeeeL2SNQn5iv15vTvtD/7sd/6hMC1MUloWru0o1KKRo2gtjd37QCwX\niHFVT49DHYBiL3+U7ixheOTow5mmiZhRXv+tnw35bLc9o7BLb+zFusO4svLL3/ljfweXePkjVnNG\nEegVEVthWpjh244eV7cnKezeB2I5QIwf5x26XyduL79QUbHyj+yNZ6sng5hdqv/X88Wv7HlNGopP\nRrir+I/+4Z/9gz/+14UYiMQitiMOSX+79/J5jLRP3nb0SC83Ij3gDogBsSQQi0mYlVhE7uUX5fvF\nn/7W7I7CiNFSfX56i9gNRb7NtmH0eBlfSSfkQCQWMbuquOb61l5Futno1Xb0COeQeHIIxIDYJBDj\nRgHGuLsWrZdfRO+P/UT8R4OnA7F5ZgzVq8crycQTHY1XYm0qOxBpMwxiNf/5zfb3QrQwPbr9/TPt\ntHXvA7FMIyYMkox36Qzby08nnCbc/WOjPBo8FYgJs+pvr42QdOlZl95c8854fAciuRHbCTW/2aHR\nwpThq9/2fB0TIad7f+0VEANi40Xs0D1IMmaE6OUXhy2ZFRUxH0eZGsRcs+ofbkVKuPR7gnqmE3o8\nEDO5xWwtCDGvxqTcHXpLkrlRGTdo9/42EANi40TsZVKEmX1dL317+b2GR8Z7HGVaECMzdbFQvN3w\nb54ZhV0v9/bi3cxwBiJ5Tm7hILYaY7JsvVhtL5ly3VR17wOxrCLmMc57hNgTh4iT8lWxouIx09xc\nGp9i40dsSQrF3mOPhmIS5/MO26Y88EaM3HDYmdIhl6bufSCWTcSCBknGvAC7evn1jCtgeOT4FBs7\nYptePXqvNkhDcQzjb9Zn/Z6IRBBbiNKYHEekqHsfiGURsddjIUyada2sBZWSjU2xcSOW2Kz6UT93\nyecpuzZidmNybooH3evUdO8Dsewhxo8wSr7SVEy9GC9f+zTKElds3IgtJDerfsTozHs+EclCjDQm\nO9M86vYfp6R7H4hlDbFogyRjpmMvJTftvYdHhn0cZboQW53mM4RWmTbluhuxhRiP8U0+Dp3OhS0g\nBsQSQ2wShFkftBVheGSYx1GmDbGd6T6Qlnsi0o6A2OoYC1ciRTq694FYlhDjRxiNuauC7eUPmHD6\nYCyKjRex+XG4G6lNKR2IZCCWisakFS+dC+YUu/eBWHYQG2WQZMxmpdnLH2LC6bEoNlbEailIdpin\n7DoDkQzE0tGYtIJ277+e2joAsawgNnnCrIN4O9Sdg3EoNk7EOjNpSHbYgUj25BY6YptpaUyaQbv3\nXwIxIDYKYv/R9lQICx9jUGyMiMlK9acSroFIP/ri30lPY9LqVph69z4Qy0L8F9/71QRHGI1ZscTK\nrsaI2FKMMT1j2m3CU3Z/9MXPpKgxacW0u/eBmPKxt82N5ksnYUPJ4yjTi9jmOCffiBrcQKTdH/3J\naVZ+eMSUu/eBWJYASzFhQ+FxlGlGbFql+l7BDkT6B7891coPj3g11e59IJYdwPSK+f1Ur3HCio0N\nsemV6nupykxuMZa64ZFjf5pPEAFiKsahBLCkB0mmX7FxIbaawgYbOxApbetmHZJT7N4HYsoB9vq5\ndP709BOWtGJjQmzKpfqetM4yiG2m8Lh0uvc3Jt29D8SyANjKyj+7p8YWOIol0Gc+JsSmXqrv1aZc\nTG1j0gqnyufJhHs1gJj6gG1s/9thngCejthMbtr98SBWS1UpKd+mnEtrY9IK2r0/2UsqEEsund6w\nHsA1hmW/9QHM+Lwv1UHMmXZ/dMXGglg6SvU9hZ1NaWPSiil178dFTGs2uwPuBRI5RYyds3jDeIZy\nUin121dbj/0AGyqGWHKKjQOx1JTqe8Tu3/7tv3Ezvd/tdLr34yHWLRX0KLboK60CiVYeEeOe7kgn\nX386ImaegK09fckuVynEElNsHIilp1TfI9iH56ZRsWl078dCrE3AajgvNR3EmjlEbO+x/xNwjEel\nRq1CDQuYeoglpdgYEEtVqb6KiE2lez8OYj2DqsGgXSwUNAaxetOI1iB3iEnTMClmz/Vn4oS5QO1H\nAExBxBJ6HGXyiKWtVF9FxJgniEyqez8OYlW7zagVClXyWqVQGKRiF04esf0nkR9i/9yn/3//5dO1\nKICpiFgyj6NMHrHUleqriNjku/fjIFYslKwfyoUig1g69uDEEaNz4Ky9fLW9tfE4NGbum5megD3e\neuXXHFUOsUQeHpI4YqvprmBQBbHhW+ey/jy1iJVIXxgjV4V6livEmDTMeUDt/t7L7acba2Ets/v/\n4wKmJmKOYnPxa/eTRiylpfrqITY8dJ6H9XQS3fsj1YmVqFyFQiWPiLFpmBu4ve3tjY2VUSIEYIoi\n5ig2M7caM/NJGrG0luqrh9hw6HQTP5nAtCqjIKbfpKxTxMqNSqXSmnrH2CQRk6VhktgzMHsSGbAn\n4QBTFTGqmD5n6W4KEEtxqb56iE30AeEjIDZg706SAotiLz+IvaTNvzDTix/uvd5+HhKzJ89fR8nD\nlUSMUUxPf2Iwlixi6S7VVw6xSXbvx0dsUGbqxDQDsEpFZ63Yzwlib2lDMVpFzNs9//7/iICpi9iQ\nm15mIbIeiSKW9lJ95RCbYPd+bMT6umFlp/HYLxXKul6DOtPCzDZiTBoW8yHubyX9/zEAUxgx9plk\nMfr4E0Us9aX6yiE2ue79uIj1iqxhxgvWP0pMqcWXX2Q2fuc3HXd+/S+MuKy/8Of+xe/9k/ryfvNP\n/dl/94ucxQ9+5cdYxn7sF34wpRWxZ67/9p/+ApFc/CnnJPmd0RY0FsSMgUd1WSd+k+knyy5if5Y+\nXOh7OFRHi1/5KZaxb//x354KpvbM9b+E7yPR+JfJafKro13qx4FY23OMJItYVpuTNE1eeZyOuQhV\nbU7aXeqL3NTLS2EHLibYnFSgVF+95qQRe5Po3o+FWFc3rD3MK2KvaTfW85Q8pFZtxPQJZpZmY/Tx\nJ4eYCqX6aiLGlCFtj+0z4iBm1FZ4GJZ9xNKXhmUAMeMZsdH7+BNDTIlSfUURGx46d/G3xnXJj4NY\nk52Dx4oiuSmZdcRSmIZlAjE91ue45/nUAtOixBBTolRfVcSYB4SPa6LEkQaAsy+VrR/0GovpFoqN\nFTFm0p21ND2ZIxOI6bN5LXCMBRXAJoWYGqX66iJGq/fTg1jPnYgZs/NodkuzNN0dNk7EmLkPnx6m\n6SjJCGJ6H/8S38ffmQBineSevwTEPE6ctbQhplfn18mE+j36WlHvJtPKGZ7ZlU3DXqfrIMkMYu4+\n/s1xI6ZKqb7KiNnd+ylqTmoFJsiLdfLCtCezGBtiqU3DsoWY0cc/F66PPxnEVCnVVxoxc+79pynq\n2JciNmwWhVn3M4bYdmrTsOHw5P9+//+eDTMU4fr4E0GMzKq/q8iuURSxsUacjn2NBjNnxaCtT7Df\nn/oGjQexkJPuTMmw+/d63Bxn6bjsLPCdY7tjQkyBWfWB2DgQS3WMBTHfuQ+nHUd37824v8rUF7nD\n9/EvdsaCmG3lojK7BYgBscylYcPhzXsSd6eZ+ip3l/k+/vXkEVOoVB+IAbGMpmHD4eV7Ji6PMvVl\nuvr4D5JFbGdGnVJ9IAbE4gY792EK07Dh+Xsu7s8z9n2uz3v28Y+OmL3sZYX2BxADYlFj9LkPxxtW\npz4bt8cZ+0Y9+/hHRmxZpVJ9IAbERk7D9tO4tUe2YX/tv7+jjF1l7Tvd5fv4ySQXoyKmVqk+EANi\nWUzDhkObrt//D78cXtGc7N1p1r7VXX6Si/n1BBBTrFQfiAGx6MFMupPONGw4vLbV+u+Miv3jW5qM\n3Rxl7Xs9WOX7+PWHVUZA7OjUjIsrI65vzfgvf+Pnf1KhUn0gBsQiRzon3eHiwibrwh52dPaOdvBf\nZO9YFfv4/1UXYicmVWcmVVcWVe/e+8b3f+M/ViptPf4//vf/9XiIAGLR0rDHeynd1FP7RLx2xk4e\nMfUWdyfZO1q5iaz/0M//e3/VSavejxJ31xdKSHZ2+S6Td6CB2FgQUyANc25M3rEDwE/uMls0ZobZ\nx/+Tf+uf+Jf+6/cJR8olO76gRc36ZQsBxNRPw+hooyN+FosLpoP/LGvf7tHp1f/w/ffji7vrq9MU\n0m+nYMx6Hg0RQMwnmEl3tg5Tu6H2hfneaDVyU/Ec3WSyaOz0/Or2/v0k4t1NmiTjUjDa53kKu4CY\ndxr2PMWT7tAgvV9m/4gwn9gp08GfgaKx47Orm7sRYfr3v2/EP/MnzPhDZvz8b3w/7ZIduVIwGhfA\nC4gFp2FP05uGOaONLocSxIZHV+8zMSr86PTiOkqf/f9mUvV9i6qfN6n6yRnvmDs4Ob+8DZBsarns\nyYVs1f6/33c6xtCkBGIKp2FOp/7NUIoYXzSm5NF+Eth6vP+//spfvfrP//W/34y/ZUGP2ZloYZfq\nn5z5ftT97dXZpCU7OruWpWA3F8c/+t2/luX7z0BsZMSYSXfSnIY5o41I/65seurz+wmMCj86v9Hr\nGy6vri70+qyEzvTj08DW463Z/+5f7NphYrPGxNKCFYs7Qps1LZLJU7B3l+ZtGr3Y9dpZqTMABsSE\nSPmkO5QOcmOSnFbSOfbZorGxdPDrgrl5ub290QtNz3TTYrUeL28DO93PSAKS3BPA0yOZdwpm/4FR\nsU+vT5cQDIix8Tbdcx8yQS7FjhMeDwo5ZUeFH41fMDc5odM0o/XoX1x/f3spFHIlj5iTCfqtyu3l\n+Zjacb4pGIPY8MRZv1t0jAExGnS0d7rTMDraiDYSPZ92NKZR4ccXse4W3llp2jmXpulmXN8FV29J\nEBwTYnZSGCCZviGnSXb6B6ZgLGLDI0e7d+gYA2J2MPWtKU/Dhmfusm3vR7Yd3yQ+KjymYJLU6vb2\nOqDz/t0tbT1OFLFQklkbYTSeR9QsTArGIaZfnpw/wyAkIGbGHh1mlPI0jB1tFAKxpEeFJyVYcLha\nj5NHjEh2HWabjYbz+Wn0vChsCiYgNjy7xyAkIMbE89RPukOPefuEencUErEER4WfXLrP5ptzc9aI\n61EHYbOtx5DVWZNBzO5evLi+C91ovjZ6AZNOwUTEmGGyd8dALO+IMYUVz1O/fbfMaKNwiOmH+20C\no8JPJMXjN+dHYtpiTdoVPAeOV+sxQqf5JBGLKpm1NWbH2VEyKZgLseHRNQYhATErXiow2tuJS2lH\nSABi3KjwWMVFEsHur4MXdHIaOk0zWo8RfZ04YkSy2+i9f2LHWfQUzI0YvcWT80FIuUfscEON+lYr\nzuXT6AciNtKo8LN4gkl6l6Rpmt56jFd9NR3EbJ0vdJrvYtzLMDrOYqVgMsSGp/fZncsXiIUNOnHY\n2qv0b9zJe260UQTEYo8KP7u+T0QwjzTtfISG0BQRYzbi/Opy9O7AECmYFDGnizTXg5DyjdjhljKF\nFeYRe+8xm1QYxNi78mGLxiSCvbtMTf9LGhBjNDszcsw4kwWFS8HkiNHK5xwPQso1YvuP0/40o6Hs\nqnvvOubDIRZtVPiRVLA0Xe5ThRjdyaenV1c3Ye9rhE/BvBBTZBDS+e3N2JDNM2J0qOTjfRU2zTXa\nKCpibHGR/6hw2aCidAmWWsToPjwN6jiLlIJ5IqbAIKQja+TIuOa2yy9izFDJrUMVtuzCu0I7NGL8\nqPCT8ILdXaSvyyXliNE4lXScRU7BvBFL+yCkY3L1vQdiySL2ak2JicOYJMqnPjs8YoGjwo+lgqWy\nmlIZxGjOpGtm3Jy9ib9D5c+dTPEgpFMGbyCWJGLsUMlDNY5/yWijWIjxjxLhm6ayQUUpFUxJxBII\nj4fnpnUQ0jnbN3gLxBJEjJmD+qUamyUdbRQTMX5U+LGfYDcXKR7RAsTYi1wKByEdXXG3hsbW1s0l\nYgoNlSQhHW0UFzHJqHCpYOfpLqAEYpwYaRuE5HSF2YSNr6GbQ8SUGippx6V/j0dkxPhHiZyFGRYJ\nxNKNWMoGIZ3x9zFuxwlr/hBjJj/cU2WjPEYbjYAYPypcLMlXQDAg5o7UDEI6OuevitfjbeHmDTG1\nhkoSbzxGG42EGNfBn/ygIiA2ecRSMgjpWOgKuxq3qDlDTK2hkuSguA96dn08xJhuFPUEA2LSmP4g\npBP+oLqbQM1HrhBjnir55K0yW+Q92mhUxLhR4YoJBsQ8eh6mOwhJ6Aq7mcg9hjwhpthQSfHi6tNA\niI0YLZNM3aAiIBYLsWkOQhK6wu6vJ1TskSPEVBsqKSjjl5aPgJg5KlxBwYCYJyVTGoQ08a6w/CH2\ndkOxoZIkPw9TiD0KYvpRr+gU7UAs4Lo3yUFIU+gKyx1ir1UbKkmOjfswIzZGQ0zVAGKeV75JD0Ka\nSldYzhBT6KmSQpL0zm+0ERADYh5Nu0kOQjq6mE5XWL4QU2+oJAn/0UZADIh5wTKxQUjHl3xX2MXk\n62zzgNi2ekMl7SBHYlDpAxADYmJMZhDSKd8VdjuVmYCyjxg7VPJQrW0JGm0ExICYd5yMfxDSOd8V\ndj2lkeeZR0zFoZLkKAzdOQvEgJikSTneQUhiV9jl1G5yZxwxpkf/qWJpWIjRRkAMiPnG5fgGIaWg\nKywniDGFFS9V25AQo42AGBALaO+NaRBSKrrCcoGYmkMlSYQYbQTEgFhQl8Q4BiGlpCssD4gxPfrb\n6m3HVZSaayAGxLwS+puEByEdXaWlKywHiDFDJffU24yzSBXXQAyIBV4OExmEdHydnq6wzCP2dkPd\nHv1h2NFGQAyIhbkgJjYI6ZR/nN9tSqZuyihiqg6VJCl7uNFGQAyIhUqfog9COj5l4soO/lky16mZ\n+SSTiB1uKTpUkkTI0UZADIiFuygyE75eXDFxy8Td+whxf5WiqU+yiNjeY5V79IfhRxsBMSAWMi7e\nJxnv0vUgmQwipu5QSTtCjzYCYkAsbJzcJ0bYbdpmMc8cYr/z68oOlbTjNHovLBADYoFNyrtkCLtO\n3yTAWUPs5a8q3aM/jDTaCIgBsQhxObpgqeoKyyhi+2oXVrAXzPsovQ5ADIiF6acI36S8Z7v8r8l9\ngLN0PlM5S4gxNyXVGypJ4ibCaCMgBsSiZfmXt7c37N3JM7aSQtl9kiHE6KQ7qvboDyOONgJiQAyR\nIcT26EjJlefKbsV5vDkHgBgQA2Kqx1vaklRyqKQdEUcbATEghsgKYtu0JbnyvUNlN4OMNrqL2n8K\nxIAYEFO7JUkr9Fc2fucLdTfkLuJoIyAGxBBZQOztU64l+YW6iEUebQTEgBhCfcQO6SCjlTVjpKS6\niJ3Hf8IWEANiQEzVeM20JJ+aE1Yoi9jpCHM+ATEgBsQUbUnSAv2VJ/Y9SVURizPaCIgBMYTSiDHP\nAWEq9BVFLNZoIyAGxBAqI/aKKavYomUVaiJ2dhtntBEQA2IIdRFjhnqvbLDVrQoidkKfQxrzUQ5A\nDIgBMdVakkyB/tor7leqIXZ8yTwBK+4TToEYEANiagUz1Ns186FSiB1fcDPV3cZdDhADYvI4Mqan\niNVHcWK880iJfaIgYuxQ7w3XdBXqIHZ0zj8AK96NSSAWIs4ujWmxbq5O1N/oiIidihfHY2YeHt8J\nDs1eWmN6nnNj37n7OcyZxoBYrOCGeksmb1UFsbMbcR66m/iXPSDmF1d0LsB3p6pv9KiInXIP/Lg6\nCkbsSv68B3MBQCxOsEO9t2VDvZVA7PRanGPz7mKUeX+BmE+ziJ9b/lLxjU4UMZ2xEyA26ZYkO9Rb\n/kTJ9CN2wnblW0fS5YgzlwMx770tXi6uVNm8U6LIOBF7f38cAbErBi4gFq8l+TTEpGEpR+z4QhTs\n/nL0nhog5hV2EbHxiJ4ju1l5rMjmjRMxo9P+4tb3bpKsT4xFDH1iMcI11Fs9xI4uxMdm3V8n8gw/\nIOYVl2z53UnswalZQ4zdOccBiDFxlZ7sS0nE2KHeW2+H6iHmuhmpd+Un9SBlIOaV+PL9YOZZe6/I\n5p2PHbHhO59ZU2SIXQOxEWJfMtRbKcTO3F35CT4KHoh5xBWfa5zy/zw6MyoN7BOVq6hiiqS4P7J/\nY71sv+fY+psL8t5j+73HF84zzo7Pr67O2YznRP8dfUW2mOMzM2u/EJ9C9D/93v/IVUeQtT5lV9L+\nSP3T/RG7YTsJT/mHsjmIHdtrNzyxHvlGPpB9QJK9k47YfpMrZp8AMY+h3vJ85/d+L30FeicJ34wE\nYmERu/Pp9Tm6dp4I6yRtJEszvq933B+9u2DObatswxbhitRw3J1QOE/tN5rLvhRujJ6RftGbYwoL\nvxi2/51dZ2eE2q3tg7WB9hLvz/htuz/3R4ztsycLvj4SECN/dMVXZTPLoXvy0n7zyW3g3c+cIeYx\n1Fua8Nwbx02qGDuW3IxM+psFYh5O+dyPZG9bmmXGd3RW3TNiDvtH1wxid9YZbOlz7fRwHjkynDm9\nnxfDW6G845rpEz2hiHGLkSN2dCe+1ULs3Hn1VNi2y3CZmGTB4RFz7UnulVMgppdVbPgV6PPHLHlQ\n+3Va7kAdS7ryx/CtAjGfHiH5dN/2/G3vrCvMnf7KBZXq2p5Q5Mj8o7vLGzrlrnluX71nELulX+6F\ngxh98Z45+Y+d39/fWNe2d0dD6WLkiFnO3bK3Fc0VpGbcmOeBcNn07xM7J4C/v79jqi5CI3ZkJ5B0\nT1rLvbs1F/cOiPkM9XZfWxkwrlNQmn10fit25SdzMxKIRUJMeijckJbb6b19kh7RU+7ePhuvuYzM\nTLTMr/SeRUx/8+mp1V10S/vh9JbcqX0nx/jx2kHu2HHimuRBksXo3WTuPjHzrb//l0mmc0wQ0+06\nPbVzP7oGeoPk+NYXsWsi6wVpix7T9rcLMb1v7D3TJ+Ysx1zK3THZk+d2IntBrgtneUfMb6i3GBfC\n5WfKjI3xZiQQC4nYFYMYn0cc09+ck86wGzKh24l9Eh5T1q7JeXlrd/6cGbic0vzrXCDkxMlIrE+5\nI2JdOzUfTi+cdDGS24Pm3/2VH5JetjNns26G3Ca9c9quVk4mrxM7p8K9c1rdx87Ky4pd30uKXek7\nrL+8Jr2C5ivC7YYcIsYN9X4bkPa4sp73786ntuZn4+7KB2KjIXbhNH3sjrNTG5BLQgRJUK5oL9mN\nk4mdMCJYNwNOeMRMVqwF3dFVubWzPBuCO/v0ly5GWuNASiwoLMxUmvf2G06Ye7AXYSr2rTccDTls\nwyLG7ElyF+FqwuV4KUaMK9B/HdRwuH8viXcX0+jjl4wruhpvJx0QC25O8ojdMB3tt6Q9Se5JvmP/\n6MqsJbggSdkte5+RvffHI8YM07nkEDuxxqGbcWcnZdLFeCH2u//t6dnVLY/YkHvDOWUl3NhJxiGK\nbVjEbtwjUq108v72mq8rySFigUO92bh0vpX/87/iUrKJ36o8vhr/zUggFgkxKyE3h8nccafoFY8Y\n6c8/IW9yJfciLaEQu+JwEDMh49fhEeOKdbwQu2IWF2oWC/YNkRG7dd8APmJW8vY4v4jtuZ7F5pf6\n0B79K73Y9fia70yf3K3KsY0rAmKxEDsWSyxOfRE7s+u1SOMqdYhduoeyx0PMnE/MKUVNGrHheZgR\n5llHjH0W2+O9oL++uGeSY7Ni//iSa13eTKSPXzquaDL7C4h5xD3TUOK6iKSI2Xcl70iflvmLazqL\n4FVSiL1jlnkaHjHLhv/n8uL0ekTEJF2HSSI2PLkR6+vyhljIod7EDrq/jGJje9jR0RXH2O3Z5AW7\nPZ9YSxaIecS1MMT5lpyi18zpdefcG7R69J07f9eS83NUxI4liIRFzOyo+G8kHfv8ql0E94lJEqd3\nTLJ3EwGxa6ZPjB2KpPfcXb+bzFjVFCIWdqi3va8crKwxF3Ts5Pm7Sd2qdJe0jvdmJBALi9gprUCg\n/3TuTlrn7RG9wXdCitzvad52kyxiVnJ4Egsx83fm3UnfTOyUudl4EQYx9nbmHVdLEu3u5In4YVaF\nRw4R2wo71JseG+9Jud2QHwDOF5u+G08f/8mlS7AJdOUDsXBT8dyyLRr7gifUiV0xecg7rgl0TE/u\nc1crKy5iTA74jlVHjtiVC7Hf/SFRxwuxIf2tV52YsJdonRgdIu+J2Cm/ouKevKa1ws5I07whth92\nqLd5lN25JuzkZ7E4FW5VJp0enbqqKfSu/Mk/jgKIeV5iyAVMr5K4sWvtb52mopG8X7Azjl3xA/6s\nYnSjauGeu2M5CmLHTjn9DdFTjpjVP3Fzdc338P0v/6k5QtgcCeCBmD084Ijc8QpE7Jy8wWL+euiB\n2L11gJudg3zF/v350bFTlXdDdtapJJXNA2IvQw71Nvf9vfsBEOJUPGO8VemuaJ3QzUggFhox7kaZ\nMQySnNNHXP5MoDi2DyfSHOK+4LtEmpPsGES7802O2Llr7CQ9lO9lk0nQyXOYRkEoxIbX7qduyRC7\n9hk7yQzetD7j3e27CY0AT2smFjDU29x5N7IHBbnnExvLrUq9I99dXntzPqX5M4BYmCudcff6yjmn\nuZG2zl/f8ZPmuCdoGB0xToxz7z6x4Z2ImAPv/cmtH2LUv/uTcIgx5xJ5cqAMMXvUvDiLxTvxkV3n\n4hbmsU8saKi3+W04u+6e3U+ySRGTvlV57L4VaeRg05sBCIj5fVvXzFRZFDF6VNwxx8PFe77f/Yi8\n+d2VKEVsxIbOPD03J0MfxMjkYa4DWW9OmOvlidjQGgxglByFQ4zeBiPbKX/akdUEds0n5uxJciY6\nWziREcwpvDv5avtlcEvS3aPvg9gwyVuVkluR799NpxUJxMJ2XV4I846SROs86BGy9pvPEu7nPDbm\ncA3xfO0TcWLX4f/8e3851CfomxZxXlVjnc6D3yJ/ovjJmb49x8LSgvdtZhELtcNvvR4k6Dk9dSK3\nKt3DIqdwLxKIRUUsQxFxjv1chJqIndHiMDFd9Zljf9RblWcSwSZbDwbEgBgQywRiR9eyHv1gxEa6\nVSm5Ffn+5iIlM8gCMSAGxFQKejPkXvK0qYCnHcW6VSkZUzTFW5FADIgh1EaM6dGX9UUFPrIt6q3K\n44vb9ykpBwNiQAyIqY/YkWePfljEhlFuVZ7IbkVenqVtrwAxIAbEVIkzYbh3PMRC3qqU3Yq8m/6t\nSCAGxBDKInZEJ4W79eqQCvsE8KBblWfXab0VCcSAGEJVxJiBIheefxQWMb9blUfSW5Hnx6ndM0AM\niAExFeLCv0c/MmIetypltyLv03QrEogBMYSSiLE9+n6gREFMcqtS0pGftluRQAyIIVRELLhHPxZi\nQ/FWpftW5KkCeweIATEglva4DP0IqMiIibcq2Y78qxM1dg8QA2JALN1x4p7ANUnExFuVKb8VCcSA\nGEI1xLhHso0FMdetypR35AMxIIZQCDHhkWxjQoy5VXl/rZZgQAyIAbFUx2nYHv1RETNuVb6b+vSG\nQAyIAbGMIXbpMYHrOBBTN4AYEANiKY3jCD36QAyIATEglraQPZINiAExIIZQBDH5I9mAGBADYgg1\nEPN4JBsQA2JADKEEYldRe/SBGBADYkAsPcH06F9GeycQA2JADIjFDK3Z7A6SWZTPI9mAGBADYoix\nINYtFfQothNYlO8j2YAYEANiiHEg1i3YMbpi/o9kA2JADIghxoDYoFgoNPuDlv6f3oiLOg81gSsQ\nA2JADJEkYi3dMDshq4+2pOO4PfpADIgBMSAWP6qFgtWnXyqUkknE7mMOxAZiQAyIAbEYUSkUhB/i\nxmnAI9mAGBADYohUIza8838kGxADYkAMkW7Eji5vr0eY2h6IATEgBsSmi9iIAcSAGBADYkAMiAEx\nIAbEgBgQA2JATHXEmgUEAoEYOYAYAoEAYmhOojmJ5iSak+gTA2JADIgBMSAGxIAYEEMAMSAGxIAY\nEOOjSuwqjzoAHIgBMSAGxKaAmD4VT8v4r1YoVIEYEANiQEw5xIxJEXXFNP0/GhADYkAMiCmH2LBN\nKjoaU94gIAbEgBgQi6dY0TSsOe0NAmJADIgBsZgtynaz2epPfYOAGBADYkBM6QBiQAyIATEgBsSA\nGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAMiAExBBADYkAMiAEx\nIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAY\nEANiQAyIATEgBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEghgBiQAyIATEg\nBsSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEghkAgEEAMgUAAMQQCgQBiCAQC\nAcQQCAQCiCEQCCCWjtCqxUKp3g94qV8vFYpVjX1p0CwXCpW2sl9Vu1LhNlG2jUZ0xb9TOQbVSlPc\nDYVCuTngtrhaEL9/taNXqXS5A7zdrFaqg8AdAcTUiHrBjGLb/VKP+YKtlwrMX/WK1kt1Vb8q/Zjl\njljJNpqnvQ56do5PrVBocFtXtja6PHB9/4V2Zra6WSiwiJWs7dNkO6LUA2KqIdYwGDJSqoLz5bX0\nf1SNl4rOtbhnHOZN/fpMj4WBfiSUGvWicFIoFMVClbtau7eR7I5mdo7PFvNFG6Fvb7He0L/LMnvG\nW99/ITPnc7VQZP9ZkCBmHO8NY0eUkIsphphmJ1x6FlKhmYf5kn4sV5mkpW3/NXOoGzlYv6TqsT4Q\nUg3JNtqX7WKGDusGn1ZqVg420C1r0f1Cvv9KVra6zLcX2l3N2DyNz9XMZLSeqUtWPhBrkDOZtq26\n5GvUr030uK6QP9ec48I6t7uqfusa35qUbaPdyMzSUV3hE2eysQMqVtv9/SsfYnZtqaXxiVjfvoSX\ngZhqx3RB/E6dn+hLGjmuNXpGO0e9qhfsFt+alG2j3X+SoR5uvQ3dk37/zg/c95+R9mRPSK4liDlH\ncSU7dOemOdns5hWxBt+a9ECsrfCdC2kbujSMgJiWja3uSr5DYevazR4QUxQxNuEY5AuxvjYMgVgl\nW4nYUOuHQMy6sNWFu7cK060NghBzjooCmpOqItaivfh5QUw8u6WIaQW+0Zm1kCDWszc5W6UlYRFj\n7nAAMcU6DYq0/wOIMYhVzH2gaVm97S5BzOjjrvaG3XK279PJEWujxEJVxAzDmkMg5kKsZ26clt2r\nswwxUsWc7XaVFLF2ITP9gHlDrF1ke6+BGEWsbvYPadnNSWSIkdr1TN3RCIVYI1PDFHKFmFGh3RgC\nMfc26r28pWHuEKsYtetNY+xRlnuH3IgZFb9FGKYkYnXh8gPEnG2sO0X8OULMLuI3mtLFDHcPuRAz\nEtAiBk4qiVhd/OqAGNlGOxHLGWJ18rU3Mt0/1JQMAC+jT19JxFquyw8QI9vYMkaE66Gf1pWMTtEi\nQcz5Scv07UkRsSoMUxWxQdE1tgSIkW1sFpjIZlICxOjXj9oKRRFruntvgRiTiTmR0d4SIEa3Gv1h\niiJWdg+N7TITW5B8jdxub7KzWJQydajLtnGY+bO5QSdvqNCXsjZ2MhixQcZHZmQaMUkaReYTY6YY\nI3Nt6WWQzg0rez4xoz80G4e6ZBuzj5jmnkbLuTtZlMz9kFXENEwjpjJixQqJPv167TqhHvMd6/O/\nNopM49PoTas0m6XMXMIk25iDI1ynu9RsVtgeoWrW68T6xtFuTGar/6fqfMUlch4gJVMOMUnXtWSO\n9ba7iJuMTsnMPZ22V6F6lhEj5flMn1/mK/Y19qj3fAmIqRLVSsWViemns3EYV7mOTs2YfL7MzY/Z\nNybYL2Xo9JZsI7lyZ7dzaGAk08U6dyVqmd9/Zre5zxz0Vc+XgBgCgUAAMQQCgQBiCAQCAcQQCAQQ\nQyAQCCCGQCAQQAyBQCCAGAKBAGIIBAIBxBAIBAKIIRAIBBBDIBBADIFAIIAYAoFAADEEAgHEEAgE\nAoghEAgEEEMgEAgghkAggBgCgUAAMQQCgQBiCAQCAcQQCAQQQyAQCCCGQCAQCSL2EQKBQCgcQAyB\nQAAxBAKBAGIIBAIBxBAIBBBDIBAIIIZAIBBADIFAIIAYAoEAYggEAgHEEAgEAoghEAgEEEMgEEAM\ngUAggBgCgUCMHbFnnz8QXnnhegWBQCBSi9ibD1/xZn324cMj7DUEAqEOYrxiumFADIFAKIUYq5hh\nGBBDIBBqIUYVMw0DYggEQinEvnH6xT778M3XQAyBQKiF2IsHOl6mYrphH3/06TcsYh+/seKF/vOn\nbz41X3lhvfGN9f9WMD8aP7948/FH9D/Wn74wfvf5J+xS9UU9fPPGBPTBmzcP+Y8jH/TgmQ7r59Y6\nWatg/4f9QERO49HnekPiU+YfXz97wByf5Igxj5PPPrb/7tOvPnx4Q44oKz4VlmsfuvRH+3C0X3/2\n5hnzG/OQfSCeL/brDz9i18dclReyLTFWytmSh5998+Gbzx4G/YpZS/fJYP/8+ZtPzHV5wK4Fs8SP\n6erw2+i7OdxqyHYi9wl0B/F7gN91L4TViYDYI5Ovrx5YhpFXyGHxwQpj2599eGa+Yu2HDx+s/7eC\n+fEDXYb9H+tP31i/fcEs1VjUG3Op+sLfCB9nf9CDr6yXPv3IWQX7P+wHIvIZn1pHwGfsP6xmhX1Y\n2EeMfaR8wnSakCPKimfS84L50T4cyT++ecj8wwzzFf4AZj6HrM9HH3scsZ+xW/LxN9YiPw74FbOW\n7pPB+vnZh6+sdfkusxbsEskJLW7jR76bw62GZCfyn0B3EL8H+F33RlidiIgZin3m3jHGIr96ZMTH\nnoiZvza/y0ePPvvwmfWzHLHvPnqkb66+qAf6X31l/PNj83jQD7oH39jHA/04+4Ne6C999OC7Hz48\nFBFjPxCRy3ion5sPPvqudWY9/OaDnoXpB9YLGWL6cfL5h2+Mnz/58M2nen5PjqjPzCPuYRTEHnxt\nkfCGHrSffPXhc9cB/JV5iH74mEXsxYfPvrIxZcNcqY8++cYyQl/Yw48efm76Y/9KbyF9Qn/12Yev\nXYg5ZyKL2MfWx+tafE3XgluiP2Jem8OthnsncpvD7iB+D/C7blTEDDlt9wXE6CLliLELe0YsliNm\n5XzPhKPETMWeubfA/vkboux3RcTYHxC5jO9al/oX5lnwXXIMfSNDzPj/r81j6XPrJe6I8jwvpIi9\nsA9T9jcPzI+QHMCfWetIzpSvPjyy15oLe6U+NbfkY/PCblzZP6a/esb+St+Uj0XExEWar3xlvfmR\n3dVt/RW3RH/EPDaHXw33TuQ2x3rnQ8kekOy6URD76LOvP/5oAog9cyFmpGJ2IibbafYnPHz0EIgh\nhLC//4eP2FOJOzI5xKxjzj7yuCMqEmKfkJYR9xsvxITjWCf2oZW/yD7vAdsI4df3EdvJ8tHHjx6E\nQeyFlcwZJ5npCbsfhCWGREy2Gs+8WuPc5kj2gGTXjYSY/JUJIGakYnYi5oMY9wFADGH3gn39wHX0\nhUTMfQS94X72REy/4n73o7iImTmIlb8En3U+iLneJUXskd34M972tdF8Thoxr9NQtjmSPZAdxPSr\nBLkjCsQQUUL35KuPJ43Y585BGgOxN0Zv0Av3YTsWxPS+u2fOEs0tTQFi7B5IDLGvPn/mfODDT569\n+Vp2d5L687GVCT4kPQ/sbQlGKOZ93J574UbM+Os37o+TI+bxgYh8hnGTjFQiBCP2lQwxelPvY6Zn\n2vyjh8+euRF74dxmkyLmOoC541jv/nlgnENfjQEx8QahXgngfI7+tgfGieuJ2KcGAp53Jx8FISbe\nGZVszgPJHpDtuhiIff5BvzlAvpbPjTuoX3146IeY3tP+0EzkP4uD2KNvyJ0ZZjMffaD9Y3LEnunx\nCIghXPHwM+doCETsu+b5440YG+bF9oXZGvvGfJdzgr+hArGIfWpe3IMQs3q67XPIhdin+mH+aQjE\nHhrnw8NgxN58eME48pl+6kkQM3HR/+9zYwe9iIKYsxoeiHGb8+Aza79xe0C262Ig9uzDpw/eEER0\nzT7hUx93c9K+q/O5dS84UnOSW0X2UHKW4tWcJF8PmpMIVzL2xi5H8keMnuKezUn+UH5hZG7GsW4t\niWYpX5MuMVo09uaN9aeBzUmrJujRmw+fyhB7w5dIeiL2iMAS0Jx8SLrEzLcZ/5MgZjQ79XsVRsvq\nmbiD/JuTj4T0xntzmIyG2wOSXRenOfmJ8Z7PCGJGxT6X6koQM9/xkXVRi46YM1lZJMSePXsDxBCe\n3fvcqeSN2LOPQiNmHH0PPhi1G/zJpb/5kdOe5Ipdn/3/7Z27maMwFEbLISEmIlROA4QugNAdEFOA\naqABOlAN9LJXb11LgPDau7P7/SfyDAZLsnRGjytNUyExuZ8F147TXCUx6gJtNRJzka7+tm3vShLT\nPz0pq/1Ls72UWEjGdJWdZEs2K4FC0b0jMcqZjntzocGtniodzyXWWnOvzRsT+4/4uFsS84+GxEAB\nG7t0NZxc7klMkRwHuVNVX15a/OzDNpNgV9E2dRJb9Uab7WgmXFRJrLRGUQ6x8L1GcxuNFssSezTb\nKihJ697fnNiXZxJjb1ZBYkkJFIruLYmFVVgDbfKRzbnEzEhydoVzU2JtnAyAxMBv43b5iWRb3LHE\nhAtO8g1sEmc1iO6Yd9opIibWUXC1eMgn9islJprKVv8Rifleo52WUhQGkEuMEtPR4FnJuH74BYlN\nLr6VlcBxcd2TGP29UX3iMH7Qa0liemrOR7rcDbGYQ7ByvcS6MNEKiYGXtjLEGQ7XTDovsc520uLE\n/mYHGW5CitWoHOo5bCutok1P+/Z05W5w8epVErNx8dcSG2NOvG79mNGeesAurXUS85sLbFrm3aci\neaIeHlGfk/omLbf8WXZ4Mi6zI83X0n1PYonFMocVJUbRFb2POb4rsc59/fUSW8w0Wq/S/Q2QGGhs\n+9uoZXSraTK9mXZpFysNW29EunMxNFp9k1DZjpk0xEIPsvTcvlrzCSQTaFErMb/nsSAxu7SX5oQa\n4MMa1ApWJZnc0kujvXQtsTbdINk7ifEnCr1vujWDTXkpMZ8dloy8GbLseINOX5SYtdhjanOHFSWm\nF2382i0LpagJdpU82jmTWFysdR9N23qVXsB4NpAYeEEfcSL1Cet2cEkvpHIDKFZvQoN2m5d3fWW2\nNSgumsvXYxgGG3XUZRLrVNIR4i0xrcDp6RMFibGT+1hOaLFwo2kjN2o9viTjxDhvifETba/RpXF1\nLY09sdvNqz4kNT71ODssGVMeHJF+gh9Uqm9KTFtMH8uUO6wssSkcanJfYoPvw9VKzCyh74qFAkFi\nwFnMHPkyu2o76fNh/GFYab1xNexpW6C96dmcSkxfaE1s2d5kEtM9jUqJ+XPAriTGczLow0m34epS\nhcRIw3NI4+h+x5/oCkPF5dtjiYVjzdJkFCSWfkIw6PhNifGTmH4cHU7bAYca86tbtiWkI8LjesNv\n+nuD4ZNE9aKvuvSRYnuLi2R8sozr/nnu+IMdBsB/ybKgDD4pMW0xOAyAP4gcUAYflVgzzHAYAOAf\nlhgAAEBiAAAAiQEAACQGAIDEAAAAEgMAAEgMAACJAQAAJAYAAJAYAABAYgAASAwAACAxAACAxAAA\n4JhflzBydcIRb30AAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [], + "image/png": { + "width": 500 + } + } + } + ] + }, + { + "metadata": { + "id": "W7lw3JzAE6BJ", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "**Hint:** use the crosstab you calculated in part 1!\n", + "\n", + "**Expectations:** Your plot should include:\n", + "- 3 lines visualizing \"occupation of guests, by year.\" The shapes of the lines should look roughly identical to 538's example. Each line should be a different color. (But you don't need to use the _same_ colors as 538.)\n", + "- Legend or labels for the lines. (But you don't need each label positioned next to its line or colored like 538.)\n", + "- Title in the upper left: _\"Who Got To Be On 'The Daily Show'?\"_ with more visual emphasis than the subtitle. (Bolder and/or larger font.)\n", + "- Subtitle underneath the title: _\"Occupation of guests, by year\"_\n", + "\n", + "Any visual element not specifically mentioned in the expectations is an optional bonus, but it's _not_ required to pass the Sprint Challenge.\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "metadata": { + "id": "E8XBAr8rz_Na", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "LuacMjSf2ses", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Part 3 — Who were the top 10 guests on _The Daily Show_?\n", + "\n", + "**Make a plot** that shows their names and number of appearances.\n", + "\n", + "**Hint:** you can use the pandas `value_counts` method.\n", + "\n", + "**Expectations:** This can be a simple, quick plot: exploratory, not explanatory. \n", + "\n", + "If you want, you can add titles and change aesthetics, but it's _not_ required to pass the Sprint Challenge." + ] + }, + { + "metadata": { + "id": "tbwfBN3HsFlh", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + } + ] +} \ No newline at end of file diff --git a/module2-choose-appropriate-visualizations/LS_DS_122_Choose_appropriate_visualizations.ipynb b/module2-choose-appropriate-visualizations/LS_DS_122_Choose_appropriate_visualizations.ipynb index 964e477..b1422bf 100644 --- a/module2-choose-appropriate-visualizations/LS_DS_122_Choose_appropriate_visualizations.ipynb +++ b/module2-choose-appropriate-visualizations/LS_DS_122_Choose_appropriate_visualizations.ipynb @@ -1,652 +1,4101 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "_Lambda School Data Science_\n", - "# Choose appropriate visualizations" - ] + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "LS_DS_122_Choose_appropriate_visualizations.ipynb", + "version": "0.3.2", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + } }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Upgrade Seaborn\n", - "\n", - "Make sure you have at least version 0.9.0" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pip install --upgrade seaborn" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import seaborn as sns\n", - "sns.__version__" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Fix misleading visualizations" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!wget https://raw.githubusercontent.com/LambdaSchool/DS-Sprint-02-Storytelling-With-Data/master/module2-choose-appropriate-visualizations/misleading.py\n", - " \n", - "import misleading" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Fix misleading plot #1" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "misleading.plot1()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Fix misleading plot #2" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "misleading.plot2()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Fix misleading plot #3" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "misleading.plot3()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Fix misleading plot #4" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "_If you're on Jupyter (not Colab) then uncomment and run this cell below:_" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# import altair as alt\n", - "# alt.renderers.enable('notebook')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "misleading.plot4()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Links\n", - "- [How to Spot Visualization Lies](https://flowingdata.com/2017/02/09/how-to-spot-visualization-lies/)\n", - "- [Where to Start and End Your Y-Axis Scale](http://stephanieevergreen.com/y-axis/)\n", - "- [xkcd heatmap](https://xkcd.com/1138/)\n", - "- [Surprise Maps: Showing the Unexpected](https://medium.com/@uwdata/surprise-maps-showing-the-unexpected-e92b67398865)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Use Seaborn to visualize distributions and relationships with continuous and discrete variables\n", - "\n", - "#### Links\n", - "- [Seaborn tutorial](https://seaborn.pydata.org/tutorial.html)\n", - "- [Seaborn example gallery](https://seaborn.pydata.org/examples/index.html)\n", - "- [Chart Chooser](https://extremepresentation.typepad.com/files/choosing-a-good-chart-09.pdf)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Anscombe dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Load dataset" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "df = sns.load_dataset('anscombe')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### See the data's shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### See the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### [Group by](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html) `'dataset'`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### [Describe](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.describe.html) the groups" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Get the [count](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.count.html), for each column in each group" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Get the [mean](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.mean.html) ..." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Get the [standard deviation](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.std.html) ..." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Get the [correlation](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.corr.html) ..." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Use pandas to [plot](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.plot.html) the groups, as scatter plots" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Use Seaborn to make [relational plots](http://seaborn.pydata.org/generated/seaborn.relplot.html)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Use Seaborn to make [linear model plots](http://seaborn.pydata.org/generated/seaborn.lmplot.html)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Links\n", - "- [Seaborn examples: Anscombe's quartet](http://seaborn.pydata.org/examples/anscombes_quartet.html)\n", - "- [Wikipedia: Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet)\n", - "- [The Datasaurus Dozen](https://www.autodeskresearch.com/publications/samestats)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Tips dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Load dataset" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "tips = sns.load_dataset('tips')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### See the data's shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### See the first 5 rows" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Describe the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Make univariate [distribution plots](https://seaborn.pydata.org/generated/seaborn.distplot.html)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Make bivariate [relational plots](https://seaborn.pydata.org/generated/seaborn.relplot.html)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Make univariate [categorical plots](https://seaborn.pydata.org/generated/seaborn.catplot.html)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Make bivariate [categorical plots](https://seaborn.pydata.org/generated/seaborn.catplot.html)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Flights" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Load dataset" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "flights = sns.load_dataset('flights')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### See the data's shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### See the first 5 rows" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Describe the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot year & passengers" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot month & passengers" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create a [pivot table](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.pivot_table.html) of passengers by month and year" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot the pivot table as a [heat map](https://seaborn.pydata.org/generated/seaborn.heatmap.html)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.5" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} + "cells": [ + { + "metadata": { + "id": "thzC-vUkBYoj", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "_Lambda School Data Science_\n", + "# Choose appropriate visualizations" + ] + }, + { + "metadata": { + "id": "SnrHVS0iBYom", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Upgrade Seaborn\n", + "\n", + "Make sure you have at least version 0.9.0" + ] + }, + { + "metadata": { + "id": "TCiDuv8tBYom", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 326 + }, + "outputId": "af6f25d2-0e9d-46dc-f865-79d2bf95a6f4" + }, + "cell_type": "code", + "source": [ + "!pip install --upgrade seaborn" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Collecting seaborn\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/a8/76/220ba4420459d9c4c9c9587c6ce607bf56c25b3d3d2de62056efe482dadc/seaborn-0.9.0-py3-none-any.whl (208kB)\n", + "\u001b[K 100% |████████████████████████████████| 215kB 25.4MB/s \n", + "\u001b[?25hRequirement already satisfied, skipping upgrade: pandas>=0.15.2 in /usr/local/lib/python3.6/dist-packages (from seaborn) (0.22.0)\n", + "Requirement already satisfied, skipping upgrade: scipy>=0.14.0 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.1.0)\n", + "Requirement already satisfied, skipping upgrade: matplotlib>=1.4.3 in /usr/local/lib/python3.6/dist-packages (from seaborn) (2.1.2)\n", + "Requirement already satisfied, skipping upgrade: numpy>=1.9.3 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.14.6)\n", + "Requirement already satisfied, skipping upgrade: python-dateutil>=2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.15.2->seaborn) (2.5.3)\n", + "Requirement already satisfied, skipping upgrade: pytz>=2011k in /usr/local/lib/python3.6/dist-packages (from pandas>=0.15.2->seaborn) (2018.7)\n", + "Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (2.3.0)\n", + "Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (0.10.0)\n", + "Requirement already satisfied, skipping upgrade: six>=1.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (1.11.0)\n", + "Installing collected packages: seaborn\n", + " Found existing installation: seaborn 0.7.1\n", + " Uninstalling seaborn-0.7.1:\n", + " Successfully uninstalled seaborn-0.7.1\n", + "Successfully installed seaborn-0.9.0\n" + ], + "name": "stdout" + } + ] + }, + { + "metadata": { + "id": "ZmOAobKIBYox", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "dcb32b71-7426-4863-deaf-d7274a0d0591" + }, + "cell_type": "code", + "source": [ + "import seaborn as sns\n", + "sns.__version__" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "'0.9.0'" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 1 + } + ] + }, + { + "metadata": { + "id": "4lAhJOM3BYoz", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Fix misleading visualizations" + ] + }, + { + "metadata": { + "id": "nxVowJrkBYo0", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "3NxNs-35BYo3", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 224 + }, + "outputId": "2c738f29-685e-4239-c9f1-61761d521a39" + }, + "cell_type": "code", + "source": [ + "!wget https://raw.githubusercontent.com/LambdaSchool/DS-Sprint-02-Storytelling-With-Data/master/module2-choose-appropriate-visualizations/misleading.py\n", + " \n", + "import misleading" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "stream", + "text": [ + "--2018-11-13 21:42:08-- https://raw.githubusercontent.com/LambdaSchool/DS-Sprint-02-Storytelling-With-Data/master/module2-choose-appropriate-visualizations/misleading.py\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.0.133, 151.101.64.133, 151.101.128.133, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.0.133|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 1641 (1.6K) [text/plain]\n", + "Saving to: ‘misleading.py’\n", + "\n", + "\rmisleading.py 0%[ ] 0 --.-KB/s \rmisleading.py 100%[===================>] 1.60K --.-KB/s in 0s \n", + "\n", + "2018-11-13 21:42:08 (153 MB/s) - ‘misleading.py’ saved [1641/1641]\n", + "\n" + ], + "name": "stdout" + } + ] + }, + { + "metadata": { + "id": "8s1O2FZVBYo5", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Fix misleading plot #1" + ] + }, + { + "metadata": { + "id": "_XO5A2kjBYo6", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 331 + }, + "outputId": "64f35e62-3191-4736-a00d-ba6a568ddade" + }, + "cell_type": "code", + "source": [ + "misleading.plot1()" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + }, + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "gskhx_4PBYo9", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "misleading??" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "MQYSjJQYB7C5", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 314 + }, + "outputId": "5597be1b-4c96-44c7-e58b-d44ac9303878" + }, + "cell_type": "code", + "source": [ + "insurance = pd.DataFrame(\n", + " index=['State Farm', 'GEICO'], \n", + " data={'Market Share %': [18.07, 12.79]})\n", + "\n", + "insurance.plot.bar();" + ], + "execution_count": 6, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "aHTsEy_qBYo_", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Fix misleading plot #2" + ] + }, + { + "metadata": { + "id": "T98CC2fVBYpA", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 310 + }, + "outputId": "068cafed-aeb7-4d3b-d890-c48577ffd5c7" + }, + "cell_type": "code", + "source": [ + "misleading.plot2();" + ], + "execution_count": 7, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "HJlC-Nj_BYpG", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Fix misleading plot #3" + ] + }, + { + "metadata": { + "id": "n0Ql9AS7BYpI", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 336 + }, + "outputId": "087ff328-e5f5-4643-93bc-d9a4789b6d3c" + }, + "cell_type": "code", + "source": [ + "misleading.plot3();" + ], + "execution_count": 8, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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3Ed8l0o0M+ktRC7USeG5d5pbzjTCqYlWX+XJ8dyz1yb9FB5iausw/ij93LcyB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\nJGlGLFaSJEkz8v8B7VusKzwbg08AAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "4oJslQPfBYpP", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Fix misleading plot #4" + ] + }, + { + "metadata": { + "id": "fIjMoUpFBYpQ", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "_If you're on Jupyter (not Colab) then uncomment and run this cell below:_" + ] + }, + { + "metadata": { + "id": "kuhwq9roBYpR", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# import altair as alt\n", + "# alt.renderers.enable('notebook')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "mRBfpfauBYpU", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 348 + }, + "outputId": "3a24c952-0e50-4c8e-c285-d75271ce32ec" + }, + "cell_type": "code", + "source": [ + "misleading.plot4()" + ], + "execution_count": 13, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Chart({\n", + " data: UrlData({\n", + " format: TopoDataFormat({\n", + " feature: 'states',\n", + " type: 'topojson'\n", + " }),\n", + " url: 'https://vega.github.io/vega-datasets/data/us-10m.json'\n", + " }),\n", + " encoding: EncodingWithFacet({\n", + " color: Color({\n", + " shorthand: 'State Farm policy premiums',\n", + " type: 'quantitative'\n", + " })\n", + " }),\n", + " height: 300,\n", + " mark: 'geoshape',\n", + " projection: Projection({\n", + " type: 'albersUsa'\n", + " }),\n", + " transform: [LookupTransform({\n", + " from: LookupData({\n", + " data: state id State Farm policy premiums \\\n", + " 0 Alabama 1 768213 \n", + " 1 Alaska 2 128613 \n", + " 2 Arizona 4 760003 \n", + " 3 Arkansas 5 454931 \n", + " 4 California 6 3655463 \n", + " 5 Colorado 8 827143 \n", + " 6 Connecticut 9 169773 \n", + " 7 Delaware 10 191319 \n", + " 8 District of Columbia 11 67231 \n", + " 9 Florida 12 2806322 \n", + " 10 Georgia 13 1761224 \n", + " 11 Hawaii 15 133498 \n", + " 12 Idaho 16 130613 \n", + " 13 Illinois 17 2256543 \n", + " 14 Indiana 18 861382 \n", + " 15 Iowa 19 368898 \n", + " 16 Kansas 20 351343 \n", + " 17 Kentucky 21 680433 \n", + " 18 Louisiana 22 1415980 \n", + " 19 Maine 23 101111 \n", + " 20 Maryland 24 883401 \n", + " 21 Massachusetts 25 0 \n", + " 22 Michigan 26 1580398 \n", + " 23 Minnesota 27 851940 \n", + " 24 Mississippi 28 467887 \n", + " 25 Missouri 29 883774 \n", + " 26 Montana 30 156816 \n", + " 27 Nebraska 31 273727 \n", + " 28 Nevada 32 404688 \n", + " 29 New Hampshire 33 103340 \n", + " 30 New Jersey 34 619623 \n", + " 31 New Mexico 35 261922 \n", + " 32 New York 36 1666653 \n", + " 33 North Carolina 37 842368 \n", + " 34 North Dakota 38 67282 \n", + " 35 Ohio 39 1240075 \n", + " 36 Oklahoma 40 636063 \n", + " 37 Oregon 41 564416 \n", + " 38 Pennsylvania 42 1654528 \n", + " 39 Rhode Island 44 0 \n", + " 40 South Carolina 45 874436 \n", + " 41 South Dakota 46 101912 \n", + " 42 Tennessee 47 889329 \n", + " 43 Texas 48 3395165 \n", + " 44 Utah 49 300403 \n", + " 45 Vermont 50 30003 \n", + " 46 Virginia 51 878312 \n", + " 47 Washington 53 794882 \n", + " 48 West Virginia 54 323608 \n", + " 49 Wisconsin 55 443680 \n", + " 50 Wyoming 56 90412 \n", + " 51 Puerto Rico 72 0 \n", + " \n", + " BERKSHIRE HATHAWAY GRP STATE TOTAL \n", + " 0 282947 3025561 \n", + " 1 81366 454623 \n", + " 2 604049 4373055 \n", + " 3 96908 1777917 \n", + " 4 2091720 25255501 \n", + " 5 365797 4057463 \n", + " 6 486498 2795415 \n", + " 7 129033 802005 \n", + " 8 115149 325239 \n", + " 9 3952147 17333354 \n", + " 10 821326 7571988 \n", + " 11 184743 722550 \n", + " 12 87222 863636 \n", + " 13 412978 7028885 \n", + " 14 201200 3506499 \n", + " 15 58105 1650388 \n", + " 16 76533 1725608 \n", + " 17 186915 2805864 \n", + " 18 369492 4136224 \n", + " 19 68109 699558 \n", + " 20 1059508 4554586 \n", + " 21 473913 4924736 \n", + " 22 0 8462142 \n", + " 23 108942 3412460 \n", + " 24 100827 1760180 \n", + " 25 214191 3606590 \n", + " 26 33538 668513 \n", + " 27 61046 1167135 \n", + " 28 262815 2129828 \n", + " 29 103403 806545 \n", + " 30 1441019 7375823 \n", + " 31 174865 1284430 \n", + " 32 3926684 12633982 \n", + " 33 560700 5543700 \n", + " 34 15516 454376 \n", + " 35 405652 6303148 \n", + " 36 151388 2515842 \n", + " 37 223187 2647434 \n", + " 38 602848 8270326 \n", + " 39 97597 867558 \n", + " 40 426033 3583918 \n", + " 41 15682 508569 \n", + " 42 292357 3769652 \n", + " 43 2127633 19180816 \n", + " 44 139315 1723931 \n", + " 45 52939 359996 \n", + " 46 884489 5105360 \n", + " 47 478922 4780616 \n", + " 48 110806 1209872 \n", + " 49 131845 2950711 \n", + " 50 30187 374169 \n", + " 51 0 444480 ,\n", + " fields: ['State Farm policy premiums'],\n", + " key: 'id'\n", + " }),\n", + " lookup: 'id'\n", + " })],\n", + " width: 500\n", + "})" + ], + "text/html": [ + "\n", + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", + " \n", + "\n", + "\n" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 13 + } + ] + }, + { + "metadata": { + "id": "lRQFKQwaBYpW", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "ZMOZSoQnBYpa", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Links\n", + "- [How to Spot Visualization Lies](https://flowingdata.com/2017/02/09/how-to-spot-visualization-lies/)\n", + "- [Where to Start and End Your Y-Axis Scale](http://stephanieevergreen.com/y-axis/)\n", + "- [xkcd heatmap](https://xkcd.com/1138/)\n", + "- [Surprise Maps: Showing the Unexpected](https://medium.com/@uwdata/surprise-maps-showing-the-unexpected-e92b67398865)" + ] + }, + { + "metadata": { + "id": "mrprFCkRBYpb", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Use Seaborn to visualize distributions and relationships with continuous and discrete variables\n", + "\n", + "#### Links\n", + "- [Seaborn tutorial](https://seaborn.pydata.org/tutorial.html)\n", + "- [Seaborn example gallery](https://seaborn.pydata.org/examples/index.html)\n", + "- [Chart Chooser](https://extremepresentation.typepad.com/files/choosing-a-good-chart-09.pdf)" + ] + }, + { + "metadata": { + "id": "mLvAclpKBYpd", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## 1. Anscombe dataset" + ] + }, + { + "metadata": { + "id": "1ChbwtW8BYpf", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Load dataset" + ] + }, + { + "metadata": { + "id": "aqJ4fdPdBYpg", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "df = sns.load_dataset('anscombe')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "OuvaJ73XBYpj", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### See the data's shape" + ] + }, + { + "metadata": { + "id": "9DpDI6BJBYpl", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "b8baff7a-3f15-468f-a740-37bbea06f394" + }, + "cell_type": "code", + "source": [ + "df.shape" + ], + "execution_count": 15, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(44, 3)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 15 + } + ] + }, + { + "metadata": { + "id": "cZo1WD4tBYpp", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### See the data" + ] + }, + { + "metadata": { + "id": "AIbDoy4mBYpp", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1413 + }, + "outputId": "095b6783-e86b-48ca-8a3d-090bf7af4c73" + }, + "cell_type": "code", + "source": [ + "df" + ], + "execution_count": 16, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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datasetxy
0I10.08.04
1I8.06.95
2I13.07.58
3I9.08.81
4I11.08.33
5I14.09.96
6I6.07.24
7I4.04.26
8I12.010.84
9I7.04.82
10I5.05.68
11II10.09.14
12II8.08.14
13II13.08.74
14II9.08.77
15II11.09.26
16II14.08.10
17II6.06.13
18II4.03.10
19II12.09.13
20II7.07.26
21II5.04.74
22III10.07.46
23III8.06.77
24III13.012.74
25III9.07.11
26III11.07.81
27III14.08.84
28III6.06.08
29III4.05.39
30III12.08.15
31III7.06.42
32III5.05.73
33IV8.06.58
34IV8.05.76
35IV8.07.71
36IV8.08.84
37IV8.08.47
38IV8.07.04
39IV8.05.25
40IV19.012.50
41IV8.05.56
42IV8.07.91
43IV8.06.89
\n", + "
" + ], + "text/plain": [ + " dataset x y\n", + "0 I 10.0 8.04\n", + "1 I 8.0 6.95\n", + "2 I 13.0 7.58\n", + "3 I 9.0 8.81\n", + "4 I 11.0 8.33\n", + "5 I 14.0 9.96\n", + "6 I 6.0 7.24\n", + "7 I 4.0 4.26\n", + "8 I 12.0 10.84\n", + "9 I 7.0 4.82\n", + "10 I 5.0 5.68\n", + "11 II 10.0 9.14\n", + "12 II 8.0 8.14\n", + "13 II 13.0 8.74\n", + "14 II 9.0 8.77\n", + "15 II 11.0 9.26\n", + "16 II 14.0 8.10\n", + "17 II 6.0 6.13\n", + "18 II 4.0 3.10\n", + "19 II 12.0 9.13\n", + "20 II 7.0 7.26\n", + "21 II 5.0 4.74\n", + "22 III 10.0 7.46\n", + "23 III 8.0 6.77\n", + "24 III 13.0 12.74\n", + "25 III 9.0 7.11\n", + "26 III 11.0 7.81\n", + "27 III 14.0 8.84\n", + "28 III 6.0 6.08\n", + "29 III 4.0 5.39\n", + "30 III 12.0 8.15\n", + "31 III 7.0 6.42\n", + "32 III 5.0 5.73\n", + "33 IV 8.0 6.58\n", + "34 IV 8.0 5.76\n", + "35 IV 8.0 7.71\n", + "36 IV 8.0 8.84\n", + "37 IV 8.0 8.47\n", + "38 IV 8.0 7.04\n", + "39 IV 8.0 5.25\n", + "40 IV 19.0 12.50\n", + "41 IV 8.0 5.56\n", + "42 IV 8.0 7.91\n", + "43 IV 8.0 6.89" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 16 + } + ] + }, + { + "metadata": { + "id": "EZIARb4aBYps", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### [Group by](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html) `'dataset'`" + ] + }, + { + "metadata": { + "id": "nsX7pDtcBYpt", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "groups = df.groupby('dataset')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "UKAuwBQcBYpv", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### [Describe](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.describe.html) the groups" + ] + }, + { + "metadata": { + "id": "XiN2Fqf_BYpx", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 235 + }, + "outputId": "14610598-fa3c-461d-ef86-73fbd75ff466" + }, + "cell_type": "code", + "source": [ + "groups.describe()" + ], + "execution_count": 19, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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xy
countmeanstdmin25%50%75%maxcountmeanstdmin25%50%75%max
dataset
I11.09.03.3166254.06.59.011.514.011.07.5009092.0315684.266.3157.588.5710.84
II11.09.03.3166254.06.59.011.514.011.07.5009092.0316573.106.6958.148.959.26
III11.09.03.3166254.06.59.011.514.011.07.5000002.0304245.396.2507.117.9812.74
IV11.09.03.3166258.08.08.08.019.011.07.5009092.0305795.256.1707.048.1912.50
\n", + "
" + ], + "text/plain": [ + " x y \\\n", + " count mean std min 25% 50% 75% max count mean \n", + "dataset \n", + "I 11.0 9.0 3.316625 4.0 6.5 9.0 11.5 14.0 11.0 7.500909 \n", + "II 11.0 9.0 3.316625 4.0 6.5 9.0 11.5 14.0 11.0 7.500909 \n", + "III 11.0 9.0 3.316625 4.0 6.5 9.0 11.5 14.0 11.0 7.500000 \n", + "IV 11.0 9.0 3.316625 8.0 8.0 8.0 8.0 19.0 11.0 7.500909 \n", + "\n", + " \n", + " std min 25% 50% 75% max \n", + "dataset \n", + "I 2.031568 4.26 6.315 7.58 8.57 10.84 \n", + "II 2.031657 3.10 6.695 8.14 8.95 9.26 \n", + "III 2.030424 5.39 6.250 7.11 7.98 12.74 \n", + "IV 2.030579 5.25 6.170 7.04 8.19 12.50 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 19 + } + ] + }, + { + "metadata": { + "id": "vS2ltNU5BYp0", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Get the [count](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.count.html), for each column in each group" + ] + }, + { + "metadata": { + "id": "HCja94yeBYp1", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "outputId": "bde7a814-5cad-43a9-fede-843c4c82f1d5" + }, + "cell_type": "code", + "source": [ + "groups.count()" + ], + "execution_count": 20, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
xy
dataset
I1111
II1111
III1111
IV1111
\n", + "
" + ], + "text/plain": [ + " x y\n", + "dataset \n", + "I 11 11\n", + "II 11 11\n", + "III 11 11\n", + "IV 11 11" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 20 + } + ] + }, + { + "metadata": { + "id": "3c08P4xGBYp4", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Get the [mean](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.mean.html) ..." + ] + }, + { + "metadata": { + "id": "YHzNozUEBYp4", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "outputId": "d660921a-2b70-42c4-f957-73511a4e3964" + }, + "cell_type": "code", + "source": [ + "groups.mean()" + ], + "execution_count": 21, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
xy
dataset
I9.07.500909
II9.07.500909
III9.07.500000
IV9.07.500909
\n", + "
" + ], + "text/plain": [ + " x y\n", + "dataset \n", + "I 9.0 7.500909\n", + "II 9.0 7.500909\n", + "III 9.0 7.500000\n", + "IV 9.0 7.500909" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 21 + } + ] + }, + { + "metadata": { + "id": "MzXS-MIlBYp7", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Get the [standard deviation](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.std.html) ..." + ] + }, + { + "metadata": { + "id": "fhsCRfdOBYp8", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "outputId": "5ae76b01-0884-4229-e18e-a00a6e68632e" + }, + "cell_type": "code", + "source": [ + "groups.std()" + ], + "execution_count": 22, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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xy
dataset
I3.3166252.031568
II3.3166252.031657
III3.3166252.030424
IV3.3166252.030579
\n", + "
" + ], + "text/plain": [ + " x y\n", + "dataset \n", + "I 3.316625 2.031568\n", + "II 3.316625 2.031657\n", + "III 3.316625 2.030424\n", + "IV 3.316625 2.030579" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 22 + } + ] + }, + { + "metadata": { + "id": "PkBPfSCrBYp_", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Get the [correlation](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.corr.html) ..." + ] + }, + { + "metadata": { + "id": "u-29guDhBYqB", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 328 + }, + "outputId": "a774b8e3-66dc-4c3c-81fa-23b6186ff97f" + }, + "cell_type": "code", + "source": [ + "groups.corr()" + ], + "execution_count": 23, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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xy
dataset
Ix1.0000000.816421
y0.8164211.000000
IIx1.0000000.816237
y0.8162371.000000
IIIx1.0000000.816287
y0.8162871.000000
IVx1.0000000.816521
y0.8165211.000000
\n", + "
" + ], + "text/plain": [ + " x y\n", + "dataset \n", + "I x 1.000000 0.816421\n", + " y 0.816421 1.000000\n", + "II x 1.000000 0.816237\n", + " y 0.816237 1.000000\n", + "III x 1.000000 0.816287\n", + " y 0.816287 1.000000\n", + "IV x 1.000000 0.816521\n", + " y 0.816521 1.000000" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 23 + } + ] + }, + { + "metadata": { + "id": "NR94sqlmBYqG", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Use pandas to [plot](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.plot.html) the groups, as scatter plots" + ] + }, + { + "metadata": { + "id": "uXwO2h1YBYqG", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1081 + }, + "outputId": "f9df39e9-8ba1-44c8-e045-add9870a3003" + }, + "cell_type": "code", + "source": [ + "groups.plot(x = 'x', y = 'y', kind = 'scatter');" + ], + "execution_count": 25, + "outputs": [ + { + "output_type": "display_data", + 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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "BR8h5Ol-BYqO", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Use Seaborn to make [relational plots](http://seaborn.pydata.org/generated/seaborn.relplot.html)" + ] + }, + { + "metadata": { + "id": "808v1qy_BYqQ", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 729 + }, + "outputId": "50d7600c-d82d-4551-9f6d-cbe35f1a17c9" + }, + "cell_type": "code", + "source": [ + "import seaborn as sns\n", + "\n", + "sns.relplot('x', 'y', col = 'dataset',\n", + " col_wrap = 2, hue = 'dataset', data = df);" + ], + "execution_count": 26, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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KKdeUUv65lDJcSnl0kqcmeUsp5epSyon72q7z/c8spVzbGb+sM9ZXSnlLZ/tv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\nFokkWfngymetYg0A23r6jh0vB1x/yy1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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "OapOkuWIBYqS", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Use Seaborn to make [linear model plots](http://seaborn.pydata.org/generated/seaborn.lmplot.html)" + ] + }, + { + "metadata": { + "id": "JKXQ8eYtBYqS", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 729 + }, + "outputId": "da0d8cec-8d02-48da-e0ab-15a5d678552d" + }, + "cell_type": "code", + "source": [ + "sns.lmplot('x', 'y', col = 'dataset',\n", + " col_wrap = 2, # 2 columns per row.\n", + " hue = 'dataset', # Color point based on dataset col values.\n", + " ci = None, # Don't show confidence interval\n", + " data = df\n", + " );" + ], + "execution_count": 28, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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ySU5s6Ty3dHkN5Du3fD6eff64kLfoCXOuhG8+cJ7TfSz85lHwqa5I5dJXnMgJ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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "I8F0krOABYqU", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Links\n", + "- [Seaborn examples: Anscombe's quartet](http://seaborn.pydata.org/examples/anscombes_quartet.html)\n", + "- [Wikipedia: Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet)\n", + "- [The Datasaurus Dozen](https://www.autodeskresearch.com/publications/samestats)" + ] + }, + { + "metadata": { + "id": "BgCcJmTqBYqV", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## 2. Tips dataset" + ] + }, + { + "metadata": { + "id": "0zx1PbkoBYqV", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Load dataset" + ] + }, + { + "metadata": { + "id": "LMR1m4muBYqW", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "tips = sns.load_dataset('tips')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "vBAYZGB-BYqY", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### See the data's shape" + ] + }, + { + "metadata": { + "id": "sIb4SCRBBYqY", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "b0120736-e91b-4841-a7f3-bc13ea4b749f" + }, + "cell_type": "code", + "source": [ + "tips.shape" + ], + "execution_count": 30, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(244, 7)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 30 + } + ] + }, + { + "metadata": { + "id": "wK_PqB05BYqb", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### See the first 5 rows" + ] + }, + { + "metadata": { + "id": "KRGMEPu8BYqc", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "outputId": "91924154-24a4-43b8-8893-b0a07b5c51ae" + }, + "cell_type": "code", + "source": [ + "tips.head()" + ], + "execution_count": 31, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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total_billtipsexsmokerdaytimesize
016.991.01FemaleNoSunDinner2
110.341.66MaleNoSunDinner3
221.013.50MaleNoSunDinner3
323.683.31MaleNoSunDinner2
424.593.61FemaleNoSunDinner4
\n", + "
" + ], + "text/plain": [ + " total_bill tip sex smoker day time size\n", + "0 16.99 1.01 Female No Sun Dinner 2\n", + "1 10.34 1.66 Male No Sun Dinner 3\n", + "2 21.01 3.50 Male No Sun Dinner 3\n", + "3 23.68 3.31 Male No Sun Dinner 2\n", + "4 24.59 3.61 Female No Sun Dinner 4" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 31 + } + ] + }, + { + "metadata": { + "id": "ypWwzUSABYqf", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Describe the data" + ] + }, + { + "metadata": { + "id": "XIYunRRzBYqg", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 173 + }, + "outputId": "b6d960b1-78b8-4115-f175-11f8b468c393" + }, + "cell_type": "code", + "source": [ + "# tips.describe(include = 'all') # show discriptions for all columns\n", + "tips.describe(exclude = [np.number])" + ], + "execution_count": 32, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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sexsmokerdaytime
count244244244244
unique2242
topMaleNoSatDinner
freq15715187176
\n", + "
" + ], + "text/plain": [ + " sex smoker day time\n", + "count 244 244 244 244\n", + "unique 2 2 4 2\n", + "top Male No Sat Dinner\n", + "freq 157 151 87 176" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 32 + } + ] + }, + { + "metadata": { + "id": "RD5-BxX3BYqi", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Make univariate [distribution plots](https://seaborn.pydata.org/generated/seaborn.distplot.html)" + ] + }, + { + "metadata": { + "id": "cWeX6pRsBYqj", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 283 + }, + "outputId": "c4a09d1b-db67-4ce7-b873-e433f76f5dab" + }, + "cell_type": "code", + "source": [ + "sns.distplot(tips.tip); # showing histogram with\n", + " # Kernel Density Estimate (KDE) as a smooth cure" + ], + "execution_count": 33, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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UDPv8vHykmY8um2NTNaPEk9vrp/ycjSuL6ewb5qtP7aV/aMTW6jHTEkxPfx1Q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\na5mGy1V1DYFh2C+LyBVjHwz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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "NENRY-zTESvH", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 283 + }, + "outputId": "766759b2-cf61-45b2-e2a2-807bb7586350" + }, + "cell_type": "code", + "source": [ + "tips['percent'] = tips['tip'] / tips['total_bill']\n", + "sns.distplot(tips.percent);" + ], + "execution_count": 36, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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oDR0DXOga4FhLH88dbWX8KlNuzRL99MwDt8/7KIHNdWlTM/socLdz7jPJrz8J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\nTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "Ogbd3xKDBYql", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Make bivariate [relational plots](https://seaborn.pydata.org/generated/seaborn.relplot.html)" + ] + }, + { + "metadata": { + "id": "xbT2gOzJBYqq", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + }, + "outputId": "fe83ad66-4069-4014-e9b5-1088960f5d9e" + }, + "cell_type": "code", + "source": [ + "sns.relplot('tip', 'total_bill', data = tips, alpha = 0.5);" + ], + "execution_count": 37, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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9weJQQazpE0MFS68ryVrOFugKuPn8Q0e2PQm53iVdMkEmRG0a3SW5H/gs8KpS\n6pXSx/5nisH7lFLqc8A7wGMNbkfN9tIbtGtiKB71c3q4C0MZKAVag6Ut4tEA8Yhv283g99Jj3exu\nQSbIhNheo6sgXgQ2e9U90shr12ptgKSye+sN1jIxVO89DPrDXk4O9/DVn77DfDpHT9DD79x3G/1h\nb03t2W2Pdbu7BZkgE2JrHT0ot9kx8lsdcNmIa+61RGtm2eTSVJLbYiEGzAJ+r4tLU0lODXfXNIa7\n2x6rLAcWYm86OoA3CpDz4wul3uBcQ8Yvtwqt/ohvVz3jZCbP+HyauVQOy9IYKwozX1i3nHmrx96q\nx2pZFldm0yykTLpDXg71BTEMY1d7CQshbunoAN7sbLWugJdP3jPUkPHLrSa8ihvb7KYUTJPOFlha\nMbF0cVWc321Qru7brte9VThblsX3LyYqR9dH/G4eOzPMB4/HCfvdzKdNxhKpStndaDy05V7CQohb\nDLsbYKfy5FO18nBDPOrnSDxc2UqxVlprEksZ3k4sk1jKoPXqetjNroliw57xdDLLdqyCxemRHiYX\nM1ycXGIhneMDR/tZTOdILGVIbNLrnk5mK+H89LkJvn3+Bk+fm+DlawuVdl+ZTVfCF4pvIE+dHefK\nbBoDze3xSOX78bkVB/tCLKSyG37vQojVOrqrspvJp616i7WM71Yv351L5TAU3HuoHwN2PfmXyll8\n/+JNPnB7jGjAw0DEz9d+do3bB8KM9IY4NdxNJlcgba4fKoCNg788jruQMlcdWQ/FEF5ImaC9rJgF\nPnZiEG1plrM5zr0zT8jrZjZlyv68QmyjowN4p5NP2wVsLZNSSilODXcBulKfe2lqmYDHhc+tVq0g\n6wl6QLHtQZuGUnhcCkp79L6VSJLJ5VEUdyW7ubTCwsrGQwXb1QB3h7xESp9XFvG7ix/3uclbmuvz\nK6SyeV6fXMLnNlCGkgk5IWrQ0QEMO9tPYLuArXVBw8yyWZnkK7swscjJ4W4uTS0T9LkJug28HhfP\nvjqJWdh6Q5uBqI/3HYnxV+eu88ZkkusLaR69ez8hb/FgoWuzae4+0M343Apps4DPbXB7PIKBLg2J\nKOZSuQ1X7x3qC/LYmeF1Y8CH+oIopSp3EPOp4hvSg0f7i73jTb53IcQtHR/AO7FdwNa6oGGjx5lP\n5xjqLh4B9MKb04z0hfjh+ev0hnyM9ofY1xVgdjnLL67NM9QTJF499IHi+sIKXQEPIZ8Lr8vglWvz\nfOo9w1yfz5A2C3jdRmWooLw38FKmwKFYkNF4ZF0NcSzsBcAwDD54PM6ReHhdFQRQuYOYWspwKbHM\nTDJLqrQkWpYfC7E1x746GnFmmqJ1AAAbMUlEQVRg43YBW+uY8maPk9dwfnyRgNeNxyju5+tz5wn7\n3FxKLPPdX94k5HNz14Eonzg1VOkNL2fydAe8HN8fxcwV6Ap6mV7KoK3i4957qJ9LU8sb1jZPL5uc\nH5/n7qHuyiq68+PznBzuZqA0dGAYBkf6w9C//jkp30H0R3zkCpqbi5nK48vyYyG25sgAbtSBjdsF\nbK1jyps9DvrWRFx5399DsRA3FjN87/UpUmaBoNfNWCLFcxenKkMfYb+7aozXwmUoDsbCHBsMs68r\nSH/YS8Dj3rDdr11f5OXxBVZMqzI+HPAafHQpUwng7Z7r8hvdgZ4An7rnAEuZgiw/FqIGjgzgRq3Q\nqiVgaxlT3uxxppPZSs94IWXy4NF+lrN5MmaBlFkg6nfjdRcPzExm8pWhj3I52PhcmqmlPJaGe27z\ncn0+Q8FSxCO+ddeLhb1MJ7OYeYtc3mIulSVvaZRSDEZ9uIztg1NOJhZibxwZwI08sHG7gK116GOj\nx6nuGadK47bvP9LHG5NJbusNkrcsQOEyFBG/uzL0sZQpsGIWeOT4PqaTWQqWxaWpJEPdAa7OzjLc\n40ejVoXvK+OL/PTyLANRHydHevjJ2AxLpW0r33ckRsDr2va52OoIJql8EGJ7jgxgu/ajLfcIn7s4\nVQm7R44PrOsRbhTSADPJDH6PwXsP9xLyuugLeekL+3AbioLWPP9GgmzeYjQe4pHjA5Wvi/iL5WBv\n3Uzy5lQSgKDXhTIUbkPxy8kkr99YWrXfxaWpZbJ5i8uJZXoCbt4/GqMr4KFgFQ/TLG8iv9UbylZH\nMG303NR7TF6IdufIALZrP9pEMstzF29iKIPuoAet4bmLNznQE6iMp2522+53w+uTSa4vrGBpRW/I\nw+nhbmIRPyeGuhns8nPPbT0ULF3sOVcFWPn7fe7iFC5DrSoHi0V8/PzKHG5XsWohm7d44c1pRgci\nzKdzZAuaq5NJDsVCHIyFSJsF0tk8IZ972yGG7Y5gKpOhCiE25sgAtms/2rnlDC7D4G/HplnOFIj4\nXTx0NM7c8goDUT9aay7PpHj2tUksDSFf8XDN5y5O8d5Dvbwzt8J3f3mT5WyeiN9DwdIMdvnpjwYq\nvzb7fk8Nd9EV9PDew72Yec3NxTRpS7Mv6ued2dSqz7f0rTXoIZ+LkM/NGzeTjPSFmElmK29W246l\n13gEk+yaJsTGHBnAYM+BjQULfnRpmktTy2RyheLQgQX3j/ZhWRavjC/y5s0lfnp5Dp/b4FB/iMGu\n4gKOgtaV8AVIZnJ875dTxTDcJHjLtNaVMd1svkC+oHnPoV7uGoywmC2OD5cDH4q968P9IRLJLNm8\nxcG+IB8/tZ/9XQFCvltvVrXUPddyBFMjx+SFaGeODeC92O145UqugEspLK3RgFGqJFhayXNlNs1f\nvzJBl99LNl9gLm2SLRSI+ouBpfXqvSCUUuQtTcHafkObjSbDrs4sE/W7uTCxyP7uAC+OzdAb8nKw\nL8h9h2OcGu7a80kZtR7BJGfECbExeQWssZfxSkMpAh6D37n3NjxuRS6veWV8DhRML2UYS6SI+rM8\nfCzO828kmEvlKFgWjxwfxG1o7twf5fUbS+QtTW/Iw/H9kZpu0VPZPAGPweRCmoIFLgP6wz5uzK8w\nn84R8hZPUTaA07f1cDgWqstJGXute5ZFGqLTSQCvsXq8UjOXMvnOa5P4vQY+l2vLHnEs4uWR4/t4\n8m/fZjppEgt7+a8/cAi/2yDoK/YC59M5mEnxoTsHipNld8Q5caALrTWfee8I3784xYpp0Rvy8sjx\nAeK1hJSC6wsZ/ubVSZYyeaJ+Nx+5ax+DpaXNKbNAylwB4PRIT81j4Y2ue5YJONHpJIDXuDVeqZlc\nzDC1VFxaG7mY4NpcunILv1GP2O928ebNJYZ6ggxE/RhK8dr1Je492MP+qK/S851P5/jljSUePhZn\nMFoMIqUU7zsSYzQe2fnQh1ngR5emmVnOUrA0Zr7Aj8dmePdIz6rP281tf73G0uWMOCHWkwBeozxe\nOZcymZhfIeh1cXMxQyZXYGJ+hajfs+kM/nK2uAR3tD9MNm/hcSm8rmK49oZ9nBzqIuRzk8tbeNwG\no/0hYpFbj7HbkFrJFYr7QQS9aF1czZbO5vG6VWXsVW77hWg9EsBrlMcrn31tkoKlCXhcfOD2GGOJ\n5VLv0tpwBl9rzeKKyZXZNJlcAY/LYDaVpS/k5VIiRa4Ap4a72NdV/9vwkNfFwViIl6/Nk8kVqxHe\nPdJNPOyrHK2EKpaeTSezcvsvRIuQAF6jPF7ZFfRwdGCeSMDDs69OMp/O4TIUXrex4a18sRJhkQdG\nY5x7Z55Xry/i97i4f7SfmWSWpZUcXUEPaOo+BurzuDg93MWKWSBl5vG7DY4PRsnmLWJh767PmhNC\nNJYE8AaUUhyOhVhM57gwscDJ4W6S2WIZV2/Is+GtfDKTZz6dY6THx6fvHWE2beIxFJMLaczS5/zl\nz64R8LrrH4IaeoJeju2LYqFRQMBjcG02Tag0ZCKLIIRoPRLAm6ieuU9l88XltVv0XiN+N/u7fJgF\n+GffeYPLMym6A16e+JXDDHZ7+fq5CQ72hYDNQ3C39cchn5uZ5SwBr4FRqkMeS6TojwZYSJkNXQQh\nezwIsXsSwFsoT4rVoj/i4/aBCP/4b17H4zK4szQE8I1fjPP7H7yD3pC3tBKtaG0Iaq15dWKBsenU\nqkm6E0Pb95L7Iz7uOdjLn/34KsnSjmYPHu0nnc3THfI2bBGE7PEgxN5IANdJOXACXg9XppfJWxqP\ny+C2viAel+JgX3DVgZtrQ3AmmeH8xCLPv5Go7Cz28LF4ZS+I7a5936FeAh4XM8ksfq+bVDbHQNTP\nwd5AwxZByB4PQuyNBHAd+b0uVsxi8Cml0FqTyeWJBj3bLtmdXjYr4QvFncWefyPBPbf11LQXxPmJ\nJX7y9ixvTy+TSGZ56I54qYZZlZYd17/6QvZ4EGJvJIDrKOQx+I2TB3jyhbeZXjbpD3t54sEjhDwG\nx/dFtwzBgqU3DLNa94L46eVZ5tM5bi4VF2P8eGyGj50YXNUjrXcoyh4PQuyNvFK2UD3BFPa7MdBb\nnneWylm88s48Tzx4BIVCo3nlnXnec6h320UW8aif0XiodK6bJhb2cu+hXgASS5kte63lnqhZFdhp\ns4Auhfp2PdLdTqTJHg9C7I0E8CZWTzAVmE+b3B6PsGIWyFt6w8mmfN5isCfIv/rBGAvpHN1BD5+8\nZ5j8mp7tRuIRH5989xCvTy6hLU3Y7+GNm0t8/+IUPreLB0b7GOgKsLxBSJZ7ol63gcsonhlXPhFj\nux7pXibSZI8HIfZGAngT1RNMqWyBsUSK8bkVPnZikOulhQ3rJpuU4oU3E3QFPET9HpSCF95M8NG7\n9tV0zbwF43MrzKdNrs+v8KvH4pil8D4/scD4hUkyOWvdUUe3eqIzDPUEmEuZPDAaI53Nb9sj3etE\nmuzxIMTuOT6Ad3t7XT3BVL6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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "wjMRLafUEdq9", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + }, + "outputId": "30fb997f-0517-4a01-e02f-109c838220a7" + }, + "cell_type": "code", + "source": [ + "sns.relplot('total_bill', 'percent', data = tips, alpha = 0.5);" + ], + "execution_count": 38, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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/foyR6XhhpMKDg+2FjsH8qmady6xadri/hfM3w4VZcyZrSGUN/qJt4adjSV66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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "tPjV_m-6Ehg-", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + }, + "outputId": "9f1f1f5a-3f5e-4deb-c363-e19db935ce78" + }, + "cell_type": "code", + "source": [ + "sns.lmplot('total_bill', 'percent', data = tips);" + ], + "execution_count": 39, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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DkApmW37bS8/4F5iHf/bNdbMq7vnb75ZTy+rRnrDZ2J2qync9cHiQex95jkyx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\n6/WXldeYd/xsi7CUup5x1UhQrJK3v2a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E9NnUSriIEJHPAXvxW+FdAH4X+CLw98BW/Jab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\nrkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "Viax4yP_BYqs", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Make univariate [categorical plots](https://seaborn.pydata.org/generated/seaborn.catplot.html)" + ] + }, + { + "metadata": { + "id": "XIIicmMKBYqt", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 68 + }, + "outputId": "454a2522-854f-41ed-9db6-c2987bab0b7c" + }, + "cell_type": "code", + "source": [ + "tips.sex.value_counts()" + ], + "execution_count": 40, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Male 157\n", + "Female 87\n", + "Name: sex, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 40 + } + ] + }, + { + "metadata": { + "id": "URNntXr8EtGc", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + }, + "outputId": "df1b99f9-d62a-4429-cd14-aa4686e5b987" + }, + "cell_type": "code", + "source": [ + "tips.sex.value_counts().plot.bar();" + ], + "execution_count": 41, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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gAbiGHLk2txh8wYz/BryexR5tRzSwoopFLOzjM48PVA07pPIlLkyaSbai7SyW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\ncU1bINZvlpn1P770OrsM574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E4uTbTLrIj85O0hrxc2I0gdaglOKZwVa+f3qCbNEmU7Bx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\nTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "prTdt4SYFGWd", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + }, + "outputId": "9cd62edd-6537-4cfa-f652-2f5afe9679fa" + }, + "cell_type": "code", + "source": [ + "sns.catplot('sex', 'tip', data = tips, kind = 'swarm', alpha = 0.5);" + ], + "execution_count": 47, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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Svs9dD/5GfW3sHZh8V/eM63sGGrfr8pSjb+mz8N2PQfthiA7rGXgho2fhvU/q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\n+evTYyRzxcpYPrGvlZ9fmzEd/lje+ra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02u0KUgCPcbGC7HmUZzu6eXLb4YE5uPMnl7Fx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\nAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "kbQ3biwSBYqv", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Make bivariate [categorical plots](https://seaborn.pydata.org/generated/seaborn.catplot.html)" + ] + }, + { + "metadata": { + "id": "JFWSBWsOBYqv", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + }, + "outputId": "cf0a3d41-622f-41be-9918-a1606a221c51" + }, + "cell_type": "code", + "source": [ + "sns.catplot('sex', 'tip', data=tips, kind = 'bar');" + ], + "execution_count": 48, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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Flights" + ] + }, + { + "metadata": { + "id": "OPhXK_T5BYqx", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Load dataset" + ] + }, + { + "metadata": { + "id": "bOR9xfOsBYqy", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "flights = sns.load_dataset('flights')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "R8tvR9mVBYq1", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### See the data's shape" + ] + }, + { + "metadata": { + "id": "sIAYHZRiBYq2", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "d652cec4-9883-4814-b3da-bb435747f07a" + }, + "cell_type": "code", + "source": [ + "flights.shape" + ], + "execution_count": 52, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(144, 3)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 52 + } + ] + }, + { + "metadata": { + "id": "rkQJWUVsBYq3", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### See the first 5 rows" + ] + }, + { + "metadata": { + "id": "xw-hTsH9BYq4", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "outputId": "743b975e-24ee-49f2-e3c9-1e52e64fdc53" + }, + "cell_type": "code", + "source": [ + "flights.head()" + ], + "execution_count": 53, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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11949February118
21949March132
31949April129
41949May121
\n", + "
" + ], + "text/plain": [ + " year month passengers\n", + "0 1949 January 112\n", + "1 1949 February 118\n", + "2 1949 March 132\n", + "3 1949 April 129\n", + "4 1949 May 121" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 53 + } + ] + }, + { + "metadata": { + "id": "cHv-789-BYq6", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Describe the data" + ] + }, + { + "metadata": { + "id": "u0fqkyswBYq7", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 297 + }, + "outputId": "14cccba0-e2a6-4d22-aa00-d266f18387c8" + }, + "cell_type": "code", + "source": [ + "flights.describe()" + ], + "execution_count": 54, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearpassengers
count144.000000144.000000
mean1954.500000280.298611
std3.464102119.966317
min1949.000000104.000000
25%1951.750000180.000000
50%1954.500000265.500000
75%1957.250000360.500000
max1960.000000622.000000
\n", + "
" + ], + "text/plain": [ + " year passengers\n", + "count 144.000000 144.000000\n", + "mean 1954.500000 280.298611\n", + "std 3.464102 119.966317\n", + "min 1949.000000 104.000000\n", + "25% 1951.750000 180.000000\n", + "50% 1954.500000 265.500000\n", + "75% 1957.250000 360.500000\n", + "max 1960.000000 622.000000" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 54 + } + ] + }, + { + "metadata": { + "id": "EOPPb02nBYq-", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Plot year & passengers" + ] + }, + { + "metadata": { + "id": "0cmcgBMPBYrA", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "03b12c97-e3e1-41a3-df9b-1ea73cea011e" + }, + "cell_type": "code", + "source": [ + "print('number of NAs in database:', flights.isna().sum().sum())" + ], + "execution_count": 55, + "outputs": [ + { + "output_type": "stream", + "text": [ + "number of NAs in database: 0\n" + ], + "name": "stdout" + } + ] + }, + { + "metadata": { + "id": "PxSmPPhZFnRB", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + }, + "outputId": "3320d557-5ddd-417f-cf54-0d4580496efc" + }, + "cell_type": "code", + "source": [ + "sns.relplot('year', 'passengers', data = flights, alpha = 0.5);" + ], + "execution_count": 77, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "WbIRd3r6BYrE", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Plot month & passengers" + ] + }, + { + "metadata": { + "id": "IBI9ZrYkBYrE", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1969 + }, + "outputId": "d8ee1509-e7f3-4bd9-b6bc-338a56dc4c05" + }, + "cell_type": "code", + "source": [ + "# create dataframe without year\n", + "month_passengers = flights[['month', 'passengers']]\n", + "month_passengers.head(114) # make sure we have only month and passengers" + ], + "execution_count": 58, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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monthpassengers
0January112
1February118
2March132
3April129
4May121
5June135
6July148
7August148
8September136
9October119
10November104
11December118
12January115
13February126
14March141
15April135
16May125
17June149
18July170
19August170
20September158
21October133
22November114
23December140
24January145
25February150
26March178
27April163
28May172
29June178
.........
84January284
85February277
86March317
87April313
88May318
89June374
90July413
91August405
92September355
93October306
94November271
95December306
96January315
97February301
98March356
99April348
100May355
101June422
102July465
103August467
104September404
105October347
106November305
107December336
108January340
109February318
110March362
111April348
112May363
113June435
\n", + "

114 rows × 2 columns

\n", + "
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passengers
month
January2901
February2820
March3242
April3205
May3262
June3740
July4216
August4213
September3629
October3199
November2794
December3142
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" + ], + "text/plain": [ + " passengers\n", + "month \n", + "January 2901\n", + "February 2820\n", + "March 3242\n", + "April 3205\n", + "May 3262\n", + "June 3740\n", + "July 4216\n", + "August 4213\n", + "September 3629\n", + "October 3199\n", + "November 2794\n", + "December 3142" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 59 + } + ] + }, + { + "metadata": { + "id": "Ba2QaVicGeYB", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 345 + }, + "outputId": "17dc72e9-5edf-47d3-8d31-87f667c46f39" + }, + "cell_type": "code", + "source": [ + "passengers_by_month.plot(kind = 'bar');" + ], + "execution_count": 75, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + }, + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "p_g5ZCyRBYrG", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Create a [pivot table](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.pivot_table.html) of passengers by month and year" + ] + }, + { + "metadata": { + "id": "UWCDm-VGBYrH", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2000 + }, + "outputId": "e336bf3d-bfad-491e-d3d5-6cc3307a72be" + }, + "cell_type": "code", + "source": [ + "table = flights.pivot_table(values = 'passengers',\n", + " index = ['year', 'month']);\n", + "table" + ], + "execution_count": 63, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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passengers
yearmonth
1949January112
February118
March132
April129
May121
June135
July148
August148
September136
October119
November104
December118
1950January115
February126
March141
April135
May125
June149
July170
August170
September158
October133
November114
December140
1951January145
February150
March178
April163
May172
June178
.........
1958July491
August505
September404
October359
November310
December337
1959January360
February342
March406
April396
May420
June472
July548
August559
September463
October407
November362
December405
1960January417
February391
March419
April461
May472
June535
July622
August606
September508
October461
November390
December432
\n", + "

144 rows × 1 columns

\n", + "
" + ], + "text/plain": [ + " passengers\n", + "year month \n", + "1949 January 112\n", + " February 118\n", + " March 132\n", + " April 129\n", + " May 121\n", + " June 135\n", + " July 148\n", + " August 148\n", + " September 136\n", + " October 119\n", + " November 104\n", + " December 118\n", + "1950 January 115\n", + " February 126\n", + " March 141\n", + " April 135\n", + " May 125\n", + " June 149\n", + " July 170\n", + " August 170\n", + " September 158\n", + " October 133\n", + " November 114\n", + " December 140\n", + "1951 January 145\n", + " February 150\n", + " March 178\n", + " April 163\n", + " May 172\n", + " June 178\n", + "... ...\n", + "1958 July 491\n", + " August 505\n", + " September 404\n", + " October 359\n", + " November 310\n", + " December 337\n", + "1959 January 360\n", + " February 342\n", + " March 406\n", + " April 396\n", + " May 420\n", + " June 472\n", + " July 548\n", + " August 559\n", + " September 463\n", + " October 407\n", + " November 362\n", + " December 405\n", + "1960 January 417\n", + " February 391\n", + " March 419\n", + " April 461\n", + " May 472\n", + " June 535\n", + " July 622\n", + " August 606\n", + " September 508\n", + " October 461\n", + " November 390\n", + " December 432\n", + "\n", + "[144 rows x 1 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 63 + } + ] + }, + { + "metadata": { + "id": "gd_cK8jUBYrK", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Plot the pivot table as a [heat map](https://seaborn.pydata.org/generated/seaborn.heatmap.html)" + ] + }, + { + "metadata": { + "id": "_CtiI2_EHNfO", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 609 + }, + "outputId": "aec9c4eb-ebf2-45df-f4da-4246b63edb4c" + }, + "cell_type": "code", + "source": [ + "plt.figure(figsize = (15, 10))\n", + "sns.heatmap(flights.pivot_table('passengers', 'month', 'year'));" + ], + "execution_count": 73, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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NQ/2+MHS/JsnxS06/+9C2X4YCAgAAc62qjqiqO+zdTvK9SS5LclaSJw/dnpzk7cP2WUme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\nAMZu2u+x6u5dSXYdqE9VbU/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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + } + ] +} \ No newline at end of file diff --git a/module3-make-explanatory-visualizations/LS_DS_123_Make_explanatory_visualizations_LESSON.ipynb b/module3-make-explanatory-visualizations/LS_DS_123_Make_explanatory_visualizations_LESSON.ipynb new file mode 100644 index 0000000..bce03a0 --- /dev/null +++ b/module3-make-explanatory-visualizations/LS_DS_123_Make_explanatory_visualizations_LESSON.ipynb @@ -0,0 +1,4212 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "LS_DS_123_Make_explanatory_visualizations_LESSON.ipynb", + "version": "0.3.2", + "provenance": [], + "collapsed_sections": [ + "-8-trVo__vRE" + ], + "include_colab_link": true + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "metadata": { + "id": "-8-trVo__vRE", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "_Lambda School Data Science_\n", + "\n", + "# Choose appropriate visualizations\n", + "\n", + "\n", + "Recreate this [example by FiveThirtyEight:](https://fivethirtyeight.com/features/al-gores-new-movie-exposes-the-big-flaw-in-online-movie-ratings/)" + ] + }, + { + "metadata": { + "id": "ya_w5WORGs-n", + "colab_type": "code", + "outputId": "dd786c8e-26f2-47ed-d2f7-fdee9b012452", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 375 + } + }, + "cell_type": "code", + "source": [ + "from IPython.display import display, Image\n", + "\n", + "url = 'https://fivethirtyeight.com/wp-content/uploads/2017/09/mehtahickey-inconvenient-0830-1.png'\n", + "example = Image(url=url, width=400)\n", + "\n", + "display(example)" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "HioPkYtUG03B", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Using this data:\n", + "\n", + "https://github.com/fivethirtyeight/data/tree/master/inconvenient-sequel\n", + "\n", + "### Stretch goals\n", + "\n", + "Recreate more examples from [FiveThityEight's shared data repository](https://data.fivethirtyeight.com/).\n", + "\n", + "For example:\n", + "- [thanksgiving-2015](https://fivethirtyeight.com/features/heres-what-your-part-of-america-eats-on-thanksgiving/) ([`altair`](https://altair-viz.github.io/gallery/index.html#maps))\n", + "- [candy-power-ranking](https://fivethirtyeight.com/features/the-ultimate-halloween-candy-power-ranking/) ([`statsmodels`](https://www.statsmodels.org/stable/index.html))" + ] + }, + { + "metadata": { + "id": "N89pO3kX_-7p", + "colab_type": "code", + "outputId": "f4d2cc5a-4382-4eba-f203-55342b5c5ef8", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 375 + } + }, + "cell_type": "code", + "source": [ + "display(example)" + ], + "execution_count": 2, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "5uz0eEaEN-GO", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "\n", + "\n", + "fake = pd.Series([38, 3, 2, 1, 2, 4, 6, 5, 5, 33], \n", + " index=range(1,11))" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "lSspPjoUOsNk", + "colab_type": "code", + "outputId": "c82937b5-9b37-40bf-ffbc-5b77331493f2", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 224 + } + }, + "cell_type": "code", + "source": [ + "fake" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1 38\n", + "2 3\n", + "3 2\n", + "4 1\n", + "5 2\n", + "6 4\n", + "7 6\n", + "8 5\n", + "9 5\n", + "10 33\n", + "dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + } + ] + }, + { + "metadata": { + "id": "HNX09eJOOtes", + "colab_type": "code", + "outputId": "d5d9febf-8627-42e5-8fae-aa5a9f8c5d18", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 375 + } + }, + "cell_type": "code", + "source": [ + "display(example)" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "KZ0VLOV8OyRr", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 462 + }, + "outputId": "1dc43dad-6036-4763-fbe7-31f70d2e9279" + }, + "cell_type": "code", + "source": [ + "plt.style.available" + ], + "execution_count": 6, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "['seaborn-pastel',\n", + " 'classic',\n", + " 'seaborn-ticks',\n", + " 'ggplot',\n", + " 'seaborn-poster',\n", + " 'seaborn-notebook',\n", + " 'Solarize_Light2',\n", + " 'seaborn-muted',\n", + " 'seaborn-white',\n", + " 'seaborn-whitegrid',\n", + " 'seaborn-bright',\n", + " 'seaborn-colorblind',\n", + " 'seaborn-dark-palette',\n", + " 'fivethirtyeight',\n", + " 'seaborn-dark',\n", + " 'seaborn',\n", + " 'seaborn-deep',\n", + " 'bmh',\n", + " 'fast',\n", + " '_classic_test',\n", + " 'seaborn-talk',\n", + " 'seaborn-paper',\n", + " 'seaborn-darkgrid',\n", + " 'grayscale',\n", + " 'dark_background']" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 6 + } + ] + }, + { + "metadata": { + "id": "Bg7e_dWmPsEe", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "plt.style.use('fivethirtyeight')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "NcpQRIsVPsGr", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 390 + }, + "outputId": "9938e570-9a83-454f-d566-c14385b720c0" + }, + "cell_type": "code", + "source": [ + "ax = fake.plot.bar(color = '#EC713B', width = 0.9);\n", + "\n", + "# We can do this, but their title has a subtitle,\n", + "# so we can do something else.\n", + "# ax.set(title = \"'An inconvenient sequel: Truth to Power' is divisive\",\n", + "# xlabel = 'Rating',\n", + "# ylabel = 'Percent of total votes')\n", + "\n", + "ax.set(xlabel = 'Rating',\n", + " ylabel = 'Percent of total votes',\n", + " yticks = range(0, 50, 10))\n", + "ax.text(x = -2, y = 50, s = \"'An inconvenient sequel: Truth to Power' is divisive\",\n", + " fontsize = 16, fontweight = 'bold')\n", + "ax.text(x = -2, y = 46, s = \"IMDb ratings for the film as of Aug. 29\")\n", + "\n", + "ax.tick_params(labelrotation = 0)" + ], + "execution_count": 8, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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44OfnZ/7sEhMTAXB2dgagRo0arFu3jipVqtzTzo4dO0hKSiIoKAgnJydKlixJ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\ni01ku1KoiaRQRkYGdrvdbNvtdqqqqhgYGMDhcFB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"cfe70992-c92a-4d8d-f6b3-4e7b94ad7e6f" + }, + "cell_type": "code", + "source": [ + "# pd.options.display.max_columns = None # To get all columns\n", + "print(df.head())\n", + "\n", + "df.sample(1).T # Transpose a sample to see all rows" + ], + "execution_count": 11, + "outputs": [ + { + "output_type": "stream", + "text": [ + " timestamp respondents category \\\n", + "0 2017-07-17 12:28:32.785639 402 Males \n", + "1 2017-07-17 12:28:33.025600 78 Females \n", + "2 2017-07-17 12:28:33.273919 4 Aged under 18 \n", + "3 2017-07-17 12:28:33.495325 4 Males under 18 \n", + "4 2017-07-17 12:28:33.722849 130 Aged 18-29 \n", + "\n", + " link average mean median \\\n", + "0 http://www.imdb.com/title/tt6322922/ratings-male 4.6 5.0 2 \n", + "1 http://www.imdb.com/title/tt6322922/ratings-fe... 6.9 7.7 10 \n", + "2 http://www.imdb.com/title/tt6322922/ratings-age_1 4.2 4.2 3 \n", + "3 http://www.imdb.com/title/tt6322922/ratings-ma... 4.2 4.2 3 \n", + "4 http://www.imdb.com/title/tt6322922/ratings-age_2 6.3 6.5 9 \n", + "\n", + " 1_votes 2_votes 3_votes ... 1_pct 2_pct 3_pct 4_pct 5_pct \\\n", + "0 197 7 7 ... 49.0 1.7 1.7 0.7 1.7 \n", + "1 16 1 0 ... 20.5 1.3 0.0 1.3 1.3 \n", + "2 2 0 0 ... 50.0 0.0 0.0 0.0 25.0 \n", + "3 2 0 0 ... 50.0 0.0 0.0 0.0 25.0 \n", + "4 41 0 3 ... 31.5 0.0 2.3 0.8 1.5 \n", + "\n", + " 6_pct 7_pct 8_pct 9_pct 10_pct \n", + "0 1.7 2.7 2.0 5.0 33.6 \n", + "1 0.0 3.8 5.1 3.8 62.8 \n", + "2 0.0 0.0 0.0 0.0 25.0 \n", + "3 0.0 0.0 0.0 0.0 25.0 \n", + "4 2.3 4.6 3.1 4.6 49.2 \n", + "\n", + "[5 rows x 27 columns]\n" + ], + "name": "stdout" + }, + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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timestamp2017-08-05 20:30:04.165089
respondents309
categoryAged 45+
linkhttp://www.imdb.com/title/tt6322922/ratings-age_4
average4
mean4.6
median1
1_votes158
2_votes14
3_votes4
4_votes0
5_votes1
6_votes6
7_votes7
8_votes15
9_votes17
10_votes87
1_pct51.1
2_pct4.5
3_pct1.3
4_pct0
5_pct0.3
6_pct1.9
7_pct2.3
8_pct4.9
9_pct5.5
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" + ], + "text/plain": [ + " 14134\n", + "timestamp 2017-08-05 20:30:04.165089\n", + "respondents 309\n", + "category Aged 45+\n", + "link http://www.imdb.com/title/tt6322922/ratings-age_4\n", + "average 4\n", + "mean 4.6\n", + "median 1\n", + "1_votes 158\n", + "2_votes 14\n", + "3_votes 4\n", + "4_votes 0\n", + "5_votes 1\n", + "6_votes 6\n", + "7_votes 7\n", + "8_votes 15\n", + "9_votes 17\n", + "10_votes 87\n", + "1_pct 51.1\n", + "2_pct 4.5\n", + "3_pct 1.3\n", + "4_pct 0\n", + "5_pct 0.3\n", + "6_pct 1.9\n", + "7_pct 2.3\n", + "8_pct 4.9\n", + "9_pct 5.5\n", + "10_pct 28.2" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 11 + } + ] + }, + { + "metadata": { + "id": "VpCWap5HagKX", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 122 + }, + "outputId": "3c6c7c39-589a-4e0e-cf0f-1d759de643d0" + }, + "cell_type": "code", + "source": [ + "# features = [d + '_votes' for d in range(11)]\n", + "# features\n", + "df.timestamp.describe()" + ], + "execution_count": 12, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "count 80053\n", + "unique 80053\n", + "top 2017-08-15 12:10:06.137174\n", + "freq 1\n", + "Name: timestamp, dtype: object" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 12 + } + ] + }, + { + "metadata": { + "id": "o3Om1JREbASK", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 156 + }, + "outputId": "2f55d5a7-4235-4424-fb06-ac055826af85" + }, + "cell_type": "code", + "source": [ + "df.timestamp = pd.to_datetime(df.timestamp)\n", + "df.timestamp.describe()" + ], + "execution_count": 13, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "count 80053\n", + "unique 80053\n", + "top 2017-07-24 23:00:02.760781\n", + "freq 1\n", + "first 2017-07-17 12:28:32.785639\n", + "last 2017-08-29 23:10:06.218251\n", + "Name: timestamp, dtype: object" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 13 + } + ] + }, + { + "metadata": { + "id": "vDxgVcnIcxIL", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "df.set_index('timestamp', inplace = True)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "BXUkxv3qdMfR", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 437 + }, + "outputId": "dccf4567-2660-46b8-946e-e2c395fd0b5a" + }, + "cell_type": "code", + "source": [ + "df.head()" + ], + "execution_count": 15, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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respondentscategorylinkaveragemeanmedian1_votes2_votes3_votes4_votes...1_pct2_pct3_pct4_pct5_pct6_pct7_pct8_pct9_pct10_pct
timestamp
2017-07-17 12:28:32.785639402Maleshttp://www.imdb.com/title/tt6322922/ratings-male4.65.02197773...49.01.71.70.71.71.72.72.05.033.6
2017-07-17 12:28:33.02560078Femaleshttp://www.imdb.com/title/tt6322922/ratings-fe...6.97.71016101...20.51.30.01.31.30.03.85.13.862.8
2017-07-17 12:28:33.2739194Aged under 18http://www.imdb.com/title/tt6322922/ratings-age_14.24.232000...50.00.00.00.025.00.00.00.00.025.0
2017-07-17 12:28:33.4953254Males under 18http://www.imdb.com/title/tt6322922/ratings-ma...4.24.232000...50.00.00.00.025.00.00.00.00.025.0
2017-07-17 12:28:33.722849130Aged 18-29http://www.imdb.com/title/tt6322922/ratings-age_26.36.5941031...31.50.02.30.81.52.34.63.14.649.2
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respondentscategorylinkaveragemeanmedian1_votes2_votes3_votes4_votes...1_pct2_pct3_pct4_pct5_pct6_pct7_pct8_pct9_pct10_pct
timestamp
2017-08-29 00:00:02.2488821682Maleshttp://www.imdb.com/title/tt6322922/ratings-male5.35.36671502912...39.93.01.70.72.54.76.45.44.930.9
2017-08-29 00:00:02.499363257Femaleshttp://www.imdb.com/title/tt6322922/ratings-fe...6.97.31053344...20.61.21.61.61.61.95.45.110.151.0
2017-08-29 00:00:02.72720415Aged under 18http://www.imdb.com/title/tt6322922/ratings-age_14.55.357000...46.70.00.00.06.70.06.70.00.040.0
2017-08-29 00:00:03.02427013Males under 18http://www.imdb.com/title/tt6322922/ratings-ma...5.35.975000...38.50.00.00.07.70.07.70.00.046.2
2017-08-29 00:00:03.2482072Females under 18http://www.imdb.com/title/tt6322922/ratings-fe...1.01.012000...100.00.00.00.00.00.00.00.00.00.0
2017-08-29 00:00:03.441529450Aged 18-29http://www.imdb.com/title/tt6322922/ratings-age_26.46.68117367...26.00.71.31.63.85.37.86.25.142.2
2017-08-29 00:00:03.636825402Males Aged 18-29http://www.imdb.com/title/tt6322922/ratings-ma...6.36.58112346...27.90.71.01.53.75.08.26.25.240.5
2017-08-29 00:00:03.83944641Females Aged 18-29http://www.imdb.com/title/tt6322922/ratings-fe...7.17.9104021...9.80.04.92.44.94.94.97.34.956.1
2017-08-29 00:00:04.030663771Aged 30-44http://www.imdb.com/title/tt6322922/ratings-age_35.65.6728721124...37.22.71.60.52.74.76.94.96.432.4
2017-08-29 00:00:04.225962679Males Aged 30-44http://www.imdb.com/title/tt6322922/ratings-ma...5.55.3627020102...39.82.91.50.32.94.97.55.05.729.5
2017-08-29 00:00:04.53931276Females Aged 30-44http://www.imdb.com/title/tt6322922/ratings-fe...7.58.01011022...14.50.02.62.60.02.61.32.611.861.8
2017-08-29 00:00:04.776104539Aged 45+http://www.imdb.com/title/tt6322922/ratings-age_44.44.8224528133...45.55.22.40.61.53.54.55.96.524.5
2017-08-29 00:00:04.973766421Males Aged 45+http://www.imdb.com/title/tt6322922/ratings-ma...4.04.3220925133...49.65.93.10.71.44.33.85.94.820.4
2017-08-29 00:00:05.176998109Females Aged 45+http://www.imdb.com/title/tt6322922/ratings-fe...6.76.7931300...28.42.80.00.01.80.07.35.513.840.4
2017-08-29 00:00:05.3665548IMDb staffhttp://www.imdb.com/title/tt6322922/ratings-im...8.47.281000...12.50.00.00.00.012.512.525.025.012.5
2017-08-29 00:00:05.55659841Top 1000 votershttp://www.imdb.com/title/tt6322922/ratings-to...4.64.7511422...26.89.84.94.912.29.812.22.42.414.6
2017-08-29 00:00:05.767397922US usershttp://www.imdb.com/title/tt6322922/ratings-usa4.85.0440533208...43.93.62.20.91.03.35.95.06.328.1
2017-08-29 00:00:05.964362556Non-US usershttp://www.imdb.com/title/tt6322922/ratings-in...6.46.5712911108...23.22.01.81.45.87.99.06.36.336.3
2017-08-29 00:00:06.2884862646IMDb usershttp://www.imdb.com/title/tt6322922/ratings5.45.671020673924...38.52.51.50.92.14.05.75.55.433.7
2017-08-29 00:10:02.4376551682Maleshttp://www.imdb.com/title/tt6322922/ratings-male5.35.36671502912...39.93.01.70.72.54.76.45.44.930.9
2017-08-29 00:10:02.715850257Femaleshttp://www.imdb.com/title/tt6322922/ratings-fe...6.97.31053344...20.61.21.61.61.61.95.45.110.151.0
2017-08-29 00:10:02.97431715Aged under 18http://www.imdb.com/title/tt6322922/ratings-age_14.55.357000...46.70.00.00.06.70.06.70.00.040.0
2017-08-29 00:10:03.24279613Males under 18http://www.imdb.com/title/tt6322922/ratings-ma...5.35.975000...38.50.00.00.07.70.07.70.00.046.2
2017-08-29 00:10:03.4719742Females under 18http://www.imdb.com/title/tt6322922/ratings-fe...1.01.012000...100.00.00.00.00.00.00.00.00.00.0
2017-08-29 00:10:03.701915450Aged 18-29http://www.imdb.com/title/tt6322922/ratings-age_26.46.68117367...26.00.71.31.63.85.37.86.25.142.2
2017-08-29 00:10:03.922894402Males Aged 18-29http://www.imdb.com/title/tt6322922/ratings-ma...6.36.58112346...27.90.71.01.53.75.08.26.25.240.5
2017-08-29 00:10:04.16858441Females Aged 18-29http://www.imdb.com/title/tt6322922/ratings-fe...7.17.9104021...9.80.04.92.44.94.94.97.34.956.1
2017-08-29 00:10:04.391835771Aged 30-44http://www.imdb.com/title/tt6322922/ratings-age_35.65.6728721124...37.22.71.60.52.74.76.94.96.432.4
2017-08-29 00:10:04.630956679Males Aged 30-44http://www.imdb.com/title/tt6322922/ratings-ma...5.55.3627020102...39.82.91.50.32.94.97.55.05.729.5
2017-08-29 00:10:04.81999176Females Aged 30-44http://www.imdb.com/title/tt6322922/ratings-fe...7.58.01011022...14.50.02.62.60.02.61.32.611.861.8
..................................................................
2017-08-29 23:00:03.683160775Aged 30-44http://www.imdb.com/title/tt6322922/ratings-age_35.75.6728721124...37.02.71.50.52.74.96.85.06.532.3
2017-08-29 23:00:03.924760682Males Aged 30-44http://www.imdb.com/title/tt6322922/ratings-ma...5.55.3627020102...39.62.91.50.32.95.17.55.15.729.3
2017-08-29 23:00:04.18903477Females Aged 30-44http://www.imdb.com/title/tt6322922/ratings-fe...7.68.11011022...14.30.02.62.60.02.61.32.613.061.0
2017-08-29 23:00:04.381826544Aged 45+http://www.imdb.com/title/tt6322922/ratings-age_44.44.8224629133...45.25.32.40.61.53.54.65.96.624.4
2017-08-29 23:00:04.619175424Males Aged 45+http://www.imdb.com/title/tt6322922/ratings-ma...4.04.3220926133...49.36.13.10.71.44.24.05.94.720.5
2017-08-29 23:00:04.820031111Females Aged 45+http://www.imdb.com/title/tt6322922/ratings-fe...6.66.6932300...28.82.70.00.01.80.07.25.414.439.6
2017-08-29 23:00:05.0288728IMDb staffhttp://www.imdb.com/title/tt6322922/ratings-im...8.47.281000...12.50.00.00.00.012.512.525.025.012.5
2017-08-29 23:00:05.23167441Top 1000 votershttp://www.imdb.com/title/tt6322922/ratings-to...4.64.7511422...26.89.84.94.912.29.812.22.42.414.6
2017-08-29 23:00:05.442596925US usershttp://www.imdb.com/title/tt6322922/ratings-usa4.85.0440534208...43.83.72.20.91.03.25.85.06.528.0
2017-08-29 23:00:05.634805565Non-US usershttp://www.imdb.com/title/tt6322922/ratings-in...6.46.5712911108...22.81.91.81.45.78.39.26.56.236.1
2017-08-29 23:00:05.8295582662IMDb usershttp://www.imdb.com/title/tt6322922/ratings5.45.671021693825...38.42.61.40.92.14.15.85.55.533.7
2017-08-29 23:10:02.2077061693Maleshttp://www.imdb.com/title/tt6322922/ratings-male5.35.46671512913...39.63.01.70.82.54.86.45.44.930.8
2017-08-29 23:10:02.398710261Femaleshttp://www.imdb.com/title/tt6322922/ratings-fe...7.07.31054344...20.71.11.51.51.51.95.45.410.750.2
2017-08-29 23:10:02.62201915Aged under 18http://www.imdb.com/title/tt6322922/ratings-age_14.55.357000...46.70.00.00.06.70.06.70.00.040.0
2017-08-29 23:10:02.90885713Males under 18http://www.imdb.com/title/tt6322922/ratings-ma...5.35.975000...38.50.00.00.07.70.07.70.00.046.2
2017-08-29 23:10:03.0886352Females under 18http://www.imdb.com/title/tt6322922/ratings-fe...1.01.012000...100.00.00.00.00.00.00.00.00.00.0
2017-08-29 23:10:03.288272455Aged 18-29http://www.imdb.com/title/tt6322922/ratings-age_26.46.68117368...25.70.71.31.83.75.57.96.45.142.0
2017-08-29 23:10:03.501039406Males Aged 18-29http://www.imdb.com/title/tt6322922/ratings-ma...6.36.58112347...27.60.71.01.73.75.28.46.25.240.4
2017-08-29 23:10:03.72596042Females Aged 18-29http://www.imdb.com/title/tt6322922/ratings-fe...7.17.9104021...9.50.04.82.44.84.84.89.54.854.8
2017-08-29 23:10:03.942442775Aged 30-44http://www.imdb.com/title/tt6322922/ratings-age_35.75.6728721124...37.02.71.50.52.74.96.85.06.532.3
2017-08-29 23:10:04.147698682Males Aged 30-44http://www.imdb.com/title/tt6322922/ratings-ma...5.55.3627020102...39.62.91.50.32.95.17.55.15.729.3
2017-08-29 23:10:04.40675977Females Aged 30-44http://www.imdb.com/title/tt6322922/ratings-fe...7.68.11011022...14.30.02.62.60.02.61.32.613.061.0
2017-08-29 23:10:04.603751544Aged 45+http://www.imdb.com/title/tt6322922/ratings-age_44.44.8224629133...45.25.32.40.61.53.54.65.96.624.4
2017-08-29 23:10:04.905270424Males Aged 45+http://www.imdb.com/title/tt6322922/ratings-ma...4.04.3220926133...49.36.13.10.71.44.24.05.94.720.5
2017-08-29 23:10:05.172451111Females Aged 45+http://www.imdb.com/title/tt6322922/ratings-fe...6.66.6932300...28.82.70.00.01.80.07.25.414.439.6
2017-08-29 23:10:05.3695108IMDb staffhttp://www.imdb.com/title/tt6322922/ratings-im...8.47.281000...12.50.00.00.00.012.512.525.025.012.5
2017-08-29 23:10:05.59833141Top 1000 votershttp://www.imdb.com/title/tt6322922/ratings-to...4.64.7511422...26.89.84.94.912.29.812.22.42.414.6
2017-08-29 23:10:05.794141925US usershttp://www.imdb.com/title/tt6322922/ratings-usa4.85.0440534208...43.83.72.20.91.03.25.85.06.528.0
2017-08-29 23:10:06.022268565Non-US usershttp://www.imdb.com/title/tt6322922/ratings-in...6.46.5712911108...22.81.91.81.45.78.39.26.56.236.1
2017-08-29 23:10:06.2182512662IMDb usershttp://www.imdb.com/title/tt6322922/ratings5.45.671021693825...38.42.61.40.92.14.15.85.55.533.7
\n", + "

2660 rows × 26 columns

\n", + "
" + ], + "text/plain": [ + " respondents category \\\n", + "timestamp \n", + "2017-08-29 00:00:02.248882 1682 Males \n", + "2017-08-29 00:00:02.499363 257 Females \n", + "2017-08-29 00:00:02.727204 15 Aged under 18 \n", + "2017-08-29 00:00:03.024270 13 Males under 18 \n", + "2017-08-29 00:00:03.248207 2 Females under 18 \n", + "2017-08-29 00:00:03.441529 450 Aged 18-29 \n", + "2017-08-29 00:00:03.636825 402 Males Aged 18-29 \n", + "2017-08-29 00:00:03.839446 41 Females Aged 18-29 \n", + "2017-08-29 00:00:04.030663 771 Aged 30-44 \n", + "2017-08-29 00:00:04.225962 679 Males Aged 30-44 \n", + "2017-08-29 00:00:04.539312 76 Females Aged 30-44 \n", + "2017-08-29 00:00:04.776104 539 Aged 45+ \n", + "2017-08-29 00:00:04.973766 421 Males Aged 45+ \n", + "2017-08-29 00:00:05.176998 109 Females Aged 45+ \n", + "2017-08-29 00:00:05.366554 8 IMDb staff \n", + "2017-08-29 00:00:05.556598 41 Top 1000 voters \n", + "2017-08-29 00:00:05.767397 922 US users \n", + "2017-08-29 00:00:05.964362 556 Non-US users \n", + "2017-08-29 00:00:06.288486 2646 IMDb users \n", + "2017-08-29 00:10:02.437655 1682 Males \n", + "2017-08-29 00:10:02.715850 257 Females \n", + "2017-08-29 00:10:02.974317 15 Aged under 18 \n", + "2017-08-29 00:10:03.242796 13 Males under 18 \n", + "2017-08-29 00:10:03.471974 2 Females under 18 \n", + "2017-08-29 00:10:03.701915 450 Aged 18-29 \n", + "2017-08-29 00:10:03.922894 402 Males Aged 18-29 \n", + "2017-08-29 00:10:04.168584 41 Females Aged 18-29 \n", + "2017-08-29 00:10:04.391835 771 Aged 30-44 \n", + "2017-08-29 00:10:04.630956 679 Males Aged 30-44 \n", + "2017-08-29 00:10:04.819991 76 Females Aged 30-44 \n", + "... ... ... \n", + "2017-08-29 23:00:03.683160 775 Aged 30-44 \n", + "2017-08-29 23:00:03.924760 682 Males Aged 30-44 \n", + "2017-08-29 23:00:04.189034 77 Females Aged 30-44 \n", + "2017-08-29 23:00:04.381826 544 Aged 45+ \n", + "2017-08-29 23:00:04.619175 424 Males Aged 45+ \n", + "2017-08-29 23:00:04.820031 111 Females Aged 45+ \n", + "2017-08-29 23:00:05.028872 8 IMDb staff \n", + "2017-08-29 23:00:05.231674 41 Top 1000 voters \n", + "2017-08-29 23:00:05.442596 925 US users \n", + "2017-08-29 23:00:05.634805 565 Non-US users \n", + "2017-08-29 23:00:05.829558 2662 IMDb users \n", + "2017-08-29 23:10:02.207706 1693 Males \n", + "2017-08-29 23:10:02.398710 261 Females \n", + "2017-08-29 23:10:02.622019 15 Aged under 18 \n", + "2017-08-29 23:10:02.908857 13 Males under 18 \n", + "2017-08-29 23:10:03.088635 2 Females under 18 \n", + "2017-08-29 23:10:03.288272 455 Aged 18-29 \n", + "2017-08-29 23:10:03.501039 406 Males Aged 18-29 \n", + "2017-08-29 23:10:03.725960 42 Females Aged 18-29 \n", + "2017-08-29 23:10:03.942442 775 Aged 30-44 \n", + "2017-08-29 23:10:04.147698 682 Males Aged 30-44 \n", + "2017-08-29 23:10:04.406759 77 Females Aged 30-44 \n", + "2017-08-29 23:10:04.603751 544 Aged 45+ \n", + "2017-08-29 23:10:04.905270 424 Males Aged 45+ \n", + "2017-08-29 23:10:05.172451 111 Females Aged 45+ \n", + "2017-08-29 23:10:05.369510 8 IMDb staff \n", + "2017-08-29 23:10:05.598331 41 Top 1000 voters \n", + "2017-08-29 23:10:05.794141 925 US users \n", + "2017-08-29 23:10:06.022268 565 Non-US users \n", + "2017-08-29 23:10:06.218251 2662 IMDb users \n", + "\n", + " link \\\n", + "timestamp \n", + "2017-08-29 00:00:02.248882 http://www.imdb.com/title/tt6322922/ratings-male \n", + "2017-08-29 00:00:02.499363 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 00:00:02.727204 http://www.imdb.com/title/tt6322922/ratings-age_1 \n", + "2017-08-29 00:00:03.024270 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 00:00:03.248207 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 00:00:03.441529 http://www.imdb.com/title/tt6322922/ratings-age_2 \n", + "2017-08-29 00:00:03.636825 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 00:00:03.839446 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 00:00:04.030663 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00:10:02.715850 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 00:10:02.974317 http://www.imdb.com/title/tt6322922/ratings-age_1 \n", + "2017-08-29 00:10:03.242796 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 00:10:03.471974 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 00:10:03.701915 http://www.imdb.com/title/tt6322922/ratings-age_2 \n", + "2017-08-29 00:10:03.922894 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 00:10:04.168584 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 00:10:04.391835 http://www.imdb.com/title/tt6322922/ratings-age_3 \n", + "2017-08-29 00:10:04.630956 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 00:10:04.819991 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "... ... \n", + "2017-08-29 23:00:03.683160 http://www.imdb.com/title/tt6322922/ratings-age_3 \n", + "2017-08-29 23:00:03.924760 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 23:00:04.189034 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 23:00:04.381826 http://www.imdb.com/title/tt6322922/ratings-age_4 \n", + "2017-08-29 23:00:04.619175 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 23:00:04.820031 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 23:00:05.028872 http://www.imdb.com/title/tt6322922/ratings-im... \n", + "2017-08-29 23:00:05.231674 http://www.imdb.com/title/tt6322922/ratings-to... \n", + "2017-08-29 23:00:05.442596 http://www.imdb.com/title/tt6322922/ratings-usa \n", + "2017-08-29 23:00:05.634805 http://www.imdb.com/title/tt6322922/ratings-in... \n", + "2017-08-29 23:00:05.829558 http://www.imdb.com/title/tt6322922/ratings \n", + "2017-08-29 23:10:02.207706 http://www.imdb.com/title/tt6322922/ratings-male \n", + "2017-08-29 23:10:02.398710 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 23:10:02.622019 http://www.imdb.com/title/tt6322922/ratings-age_1 \n", + "2017-08-29 23:10:02.908857 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 23:10:03.088635 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 23:10:03.288272 http://www.imdb.com/title/tt6322922/ratings-age_2 \n", + "2017-08-29 23:10:03.501039 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 23:10:03.725960 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 23:10:03.942442 http://www.imdb.com/title/tt6322922/ratings-age_3 \n", + "2017-08-29 23:10:04.147698 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 23:10:04.406759 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 23:10:04.603751 http://www.imdb.com/title/tt6322922/ratings-age_4 \n", + "2017-08-29 23:10:04.905270 http://www.imdb.com/title/tt6322922/ratings-ma... \n", + "2017-08-29 23:10:05.172451 http://www.imdb.com/title/tt6322922/ratings-fe... \n", + "2017-08-29 23:10:05.369510 http://www.imdb.com/title/tt6322922/ratings-im... \n", + "2017-08-29 23:10:05.598331 http://www.imdb.com/title/tt6322922/ratings-to... \n", + "2017-08-29 23:10:05.794141 http://www.imdb.com/title/tt6322922/ratings-usa \n", + "2017-08-29 23:10:06.022268 http://www.imdb.com/title/tt6322922/ratings-in... \n", + "2017-08-29 23:10:06.218251 http://www.imdb.com/title/tt6322922/ratings \n", + "\n", + " average mean median 1_votes 2_votes 3_votes \\\n", + "timestamp \n", + "2017-08-29 00:00:02.248882 5.3 5.3 6 671 50 29 \n", + "2017-08-29 00:00:02.499363 6.9 7.3 10 53 3 4 \n", + "2017-08-29 00:00:02.727204 4.5 5.3 5 7 0 0 \n", + "2017-08-29 00:00:03.024270 5.3 5.9 7 5 0 0 \n", + "2017-08-29 00:00:03.248207 1.0 1.0 1 2 0 0 \n", + "2017-08-29 00:00:03.441529 6.4 6.6 8 117 3 6 \n", + "2017-08-29 00:00:03.636825 6.3 6.5 8 112 3 4 \n", + "2017-08-29 00:00:03.839446 7.1 7.9 10 4 0 2 \n", + "2017-08-29 00:00:04.030663 5.6 5.6 7 287 21 12 \n", + "2017-08-29 00:00:04.225962 5.5 5.3 6 270 20 10 \n", + "2017-08-29 00:00:04.539312 7.5 8.0 10 11 0 2 \n", + "2017-08-29 00:00:04.776104 4.4 4.8 2 245 28 13 \n", + "2017-08-29 00:00:04.973766 4.0 4.3 2 209 25 13 \n", + "2017-08-29 00:00:05.176998 6.7 6.7 9 31 3 0 \n", + "2017-08-29 00:00:05.366554 8.4 7.2 8 1 0 0 \n", + "2017-08-29 00:00:05.556598 4.6 4.7 5 11 4 2 \n", + "2017-08-29 00:00:05.767397 4.8 5.0 4 405 33 20 \n", + "2017-08-29 00:00:05.964362 6.4 6.5 7 129 11 10 \n", + "2017-08-29 00:00:06.288486 5.4 5.6 7 1020 67 39 \n", + "2017-08-29 00:10:02.437655 5.3 5.3 6 671 50 29 \n", + "2017-08-29 00:10:02.715850 6.9 7.3 10 53 3 4 \n", + "2017-08-29 00:10:02.974317 4.5 5.3 5 7 0 0 \n", + "2017-08-29 00:10:03.242796 5.3 5.9 7 5 0 0 \n", + "2017-08-29 00:10:03.471974 1.0 1.0 1 2 0 0 \n", + "2017-08-29 00:10:03.701915 6.4 6.6 8 117 3 6 \n", + "2017-08-29 00:10:03.922894 6.3 6.5 8 112 3 4 \n", + "2017-08-29 00:10:04.168584 7.1 7.9 10 4 0 2 \n", + "2017-08-29 00:10:04.391835 5.6 5.6 7 287 21 12 \n", + "2017-08-29 00:10:04.630956 5.5 5.3 6 270 20 10 \n", + "2017-08-29 00:10:04.819991 7.5 8.0 10 11 0 2 \n", + "... ... ... ... ... ... ... \n", + "2017-08-29 23:00:03.683160 5.7 5.6 7 287 21 12 \n", + "2017-08-29 23:00:03.924760 5.5 5.3 6 270 20 10 \n", + "2017-08-29 23:00:04.189034 7.6 8.1 10 11 0 2 \n", + "2017-08-29 23:00:04.381826 4.4 4.8 2 246 29 13 \n", + "2017-08-29 23:00:04.619175 4.0 4.3 2 209 26 13 \n", + "2017-08-29 23:00:04.820031 6.6 6.6 9 32 3 0 \n", + "2017-08-29 23:00:05.028872 8.4 7.2 8 1 0 0 \n", + "2017-08-29 23:00:05.231674 4.6 4.7 5 11 4 2 \n", + "2017-08-29 23:00:05.442596 4.8 5.0 4 405 34 20 \n", + "2017-08-29 23:00:05.634805 6.4 6.5 7 129 11 10 \n", + "2017-08-29 23:00:05.829558 5.4 5.6 7 1021 69 38 \n", + "2017-08-29 23:10:02.207706 5.3 5.4 6 671 51 29 \n", + "2017-08-29 23:10:02.398710 7.0 7.3 10 54 3 4 \n", + "2017-08-29 23:10:02.622019 4.5 5.3 5 7 0 0 \n", + "2017-08-29 23:10:02.908857 5.3 5.9 7 5 0 0 \n", + "2017-08-29 23:10:03.088635 1.0 1.0 1 2 0 0 \n", + "2017-08-29 23:10:03.288272 6.4 6.6 8 117 3 6 \n", + "2017-08-29 23:10:03.501039 6.3 6.5 8 112 3 4 \n", + "2017-08-29 23:10:03.725960 7.1 7.9 10 4 0 2 \n", + "2017-08-29 23:10:03.942442 5.7 5.6 7 287 21 12 \n", + "2017-08-29 23:10:04.147698 5.5 5.3 6 270 20 10 \n", + "2017-08-29 23:10:04.406759 7.6 8.1 10 11 0 2 \n", + "2017-08-29 23:10:04.603751 4.4 4.8 2 246 29 13 \n", + "2017-08-29 23:10:04.905270 4.0 4.3 2 209 26 13 \n", + "2017-08-29 23:10:05.172451 6.6 6.6 9 32 3 0 \n", + "2017-08-29 23:10:05.369510 8.4 7.2 8 1 0 0 \n", + "2017-08-29 23:10:05.598331 4.6 4.7 5 11 4 2 \n", + "2017-08-29 23:10:05.794141 4.8 5.0 4 405 34 20 \n", + "2017-08-29 23:10:06.022268 6.4 6.5 7 129 11 10 \n", + "2017-08-29 23:10:06.218251 5.4 5.6 7 1021 69 38 \n", + "\n", + " 4_votes ... 1_pct 2_pct 3_pct 4_pct \\\n", + "timestamp ... \n", + "2017-08-29 00:00:02.248882 12 ... 39.9 3.0 1.7 0.7 \n", + "2017-08-29 00:00:02.499363 4 ... 20.6 1.2 1.6 1.6 \n", + "2017-08-29 00:00:02.727204 0 ... 46.7 0.0 0.0 0.0 \n", + "2017-08-29 00:00:03.024270 0 ... 38.5 0.0 0.0 0.0 \n", + "2017-08-29 00:00:03.248207 0 ... 100.0 0.0 0.0 0.0 \n", + "2017-08-29 00:00:03.441529 7 ... 26.0 0.7 1.3 1.6 \n", + "2017-08-29 00:00:03.636825 6 ... 27.9 0.7 1.0 1.5 \n", + "2017-08-29 00:00:03.839446 1 ... 9.8 0.0 4.9 2.4 \n", + "2017-08-29 00:00:04.030663 4 ... 37.2 2.7 1.6 0.5 \n", + "2017-08-29 00:00:04.225962 2 ... 39.8 2.9 1.5 0.3 \n", + "2017-08-29 00:00:04.539312 2 ... 14.5 0.0 2.6 2.6 \n", + "2017-08-29 00:00:04.776104 3 ... 45.5 5.2 2.4 0.6 \n", + "2017-08-29 00:00:04.973766 3 ... 49.6 5.9 3.1 0.7 \n", + "2017-08-29 00:00:05.176998 0 ... 28.4 2.8 0.0 0.0 \n", + "2017-08-29 00:00:05.366554 0 ... 12.5 0.0 0.0 0.0 \n", + "2017-08-29 00:00:05.556598 2 ... 26.8 9.8 4.9 4.9 \n", + "2017-08-29 00:00:05.767397 8 ... 43.9 3.6 2.2 0.9 \n", + "2017-08-29 00:00:05.964362 8 ... 23.2 2.0 1.8 1.4 \n", + "2017-08-29 00:00:06.288486 24 ... 38.5 2.5 1.5 0.9 \n", + "2017-08-29 00:10:02.437655 12 ... 39.9 3.0 1.7 0.7 \n", + "2017-08-29 00:10:02.715850 4 ... 20.6 1.2 1.6 1.6 \n", + "2017-08-29 00:10:02.974317 0 ... 46.7 0.0 0.0 0.0 \n", + "2017-08-29 00:10:03.242796 0 ... 38.5 0.0 0.0 0.0 \n", + "2017-08-29 00:10:03.471974 0 ... 100.0 0.0 0.0 0.0 \n", + "2017-08-29 00:10:03.701915 7 ... 26.0 0.7 1.3 1.6 \n", + "2017-08-29 00:10:03.922894 6 ... 27.9 0.7 1.0 1.5 \n", + "2017-08-29 00:10:04.168584 1 ... 9.8 0.0 4.9 2.4 \n", + "2017-08-29 00:10:04.391835 4 ... 37.2 2.7 1.6 0.5 \n", + "2017-08-29 00:10:04.630956 2 ... 39.8 2.9 1.5 0.3 \n", + "2017-08-29 00:10:04.819991 2 ... 14.5 0.0 2.6 2.6 \n", + "... ... ... ... ... ... ... \n", + "2017-08-29 23:00:03.683160 4 ... 37.0 2.7 1.5 0.5 \n", + "2017-08-29 23:00:03.924760 2 ... 39.6 2.9 1.5 0.3 \n", + "2017-08-29 23:00:04.189034 2 ... 14.3 0.0 2.6 2.6 \n", + "2017-08-29 23:00:04.381826 3 ... 45.2 5.3 2.4 0.6 \n", + "2017-08-29 23:00:04.619175 3 ... 49.3 6.1 3.1 0.7 \n", + "2017-08-29 23:00:04.820031 0 ... 28.8 2.7 0.0 0.0 \n", + "2017-08-29 23:00:05.028872 0 ... 12.5 0.0 0.0 0.0 \n", + "2017-08-29 23:00:05.231674 2 ... 26.8 9.8 4.9 4.9 \n", + "2017-08-29 23:00:05.442596 8 ... 43.8 3.7 2.2 0.9 \n", + "2017-08-29 23:00:05.634805 8 ... 22.8 1.9 1.8 1.4 \n", + "2017-08-29 23:00:05.829558 25 ... 38.4 2.6 1.4 0.9 \n", + "2017-08-29 23:10:02.207706 13 ... 39.6 3.0 1.7 0.8 \n", + "2017-08-29 23:10:02.398710 4 ... 20.7 1.1 1.5 1.5 \n", + "2017-08-29 23:10:02.622019 0 ... 46.7 0.0 0.0 0.0 \n", + "2017-08-29 23:10:02.908857 0 ... 38.5 0.0 0.0 0.0 \n", + "2017-08-29 23:10:03.088635 0 ... 100.0 0.0 0.0 0.0 \n", + "2017-08-29 23:10:03.288272 8 ... 25.7 0.7 1.3 1.8 \n", + "2017-08-29 23:10:03.501039 7 ... 27.6 0.7 1.0 1.7 \n", + "2017-08-29 23:10:03.725960 1 ... 9.5 0.0 4.8 2.4 \n", + "2017-08-29 23:10:03.942442 4 ... 37.0 2.7 1.5 0.5 \n", + "2017-08-29 23:10:04.147698 2 ... 39.6 2.9 1.5 0.3 \n", + "2017-08-29 23:10:04.406759 2 ... 14.3 0.0 2.6 2.6 \n", + "2017-08-29 23:10:04.603751 3 ... 45.2 5.3 2.4 0.6 \n", + "2017-08-29 23:10:04.905270 3 ... 49.3 6.1 3.1 0.7 \n", + "2017-08-29 23:10:05.172451 0 ... 28.8 2.7 0.0 0.0 \n", + "2017-08-29 23:10:05.369510 0 ... 12.5 0.0 0.0 0.0 \n", + "2017-08-29 23:10:05.598331 2 ... 26.8 9.8 4.9 4.9 \n", + "2017-08-29 23:10:05.794141 8 ... 43.8 3.7 2.2 0.9 \n", + "2017-08-29 23:10:06.022268 8 ... 22.8 1.9 1.8 1.4 \n", + "2017-08-29 23:10:06.218251 25 ... 38.4 2.6 1.4 0.9 \n", + "\n", + " 5_pct 6_pct 7_pct 8_pct 9_pct 10_pct \n", + "timestamp \n", + "2017-08-29 00:00:02.248882 2.5 4.7 6.4 5.4 4.9 30.9 \n", + "2017-08-29 00:00:02.499363 1.6 1.9 5.4 5.1 10.1 51.0 \n", + "2017-08-29 00:00:02.727204 6.7 0.0 6.7 0.0 0.0 40.0 \n", + "2017-08-29 00:00:03.024270 7.7 0.0 7.7 0.0 0.0 46.2 \n", + "2017-08-29 00:00:03.248207 0.0 0.0 0.0 0.0 0.0 0.0 \n", + "2017-08-29 00:00:03.441529 3.8 5.3 7.8 6.2 5.1 42.2 \n", + "2017-08-29 00:00:03.636825 3.7 5.0 8.2 6.2 5.2 40.5 \n", + "2017-08-29 00:00:03.839446 4.9 4.9 4.9 7.3 4.9 56.1 \n", + "2017-08-29 00:00:04.030663 2.7 4.7 6.9 4.9 6.4 32.4 \n", + "2017-08-29 00:00:04.225962 2.9 4.9 7.5 5.0 5.7 29.5 \n", + "2017-08-29 00:00:04.539312 0.0 2.6 1.3 2.6 11.8 61.8 \n", + "2017-08-29 00:00:04.776104 1.5 3.5 4.5 5.9 6.5 24.5 \n", + "2017-08-29 00:00:04.973766 1.4 4.3 3.8 5.9 4.8 20.4 \n", + "2017-08-29 00:00:05.176998 1.8 0.0 7.3 5.5 13.8 40.4 \n", + "2017-08-29 00:00:05.366554 0.0 12.5 12.5 25.0 25.0 12.5 \n", + "2017-08-29 00:00:05.556598 12.2 9.8 12.2 2.4 2.4 14.6 \n", + "2017-08-29 00:00:05.767397 1.0 3.3 5.9 5.0 6.3 28.1 \n", + "2017-08-29 00:00:05.964362 5.8 7.9 9.0 6.3 6.3 36.3 \n", + "2017-08-29 00:00:06.288486 2.1 4.0 5.7 5.5 5.4 33.7 \n", + "2017-08-29 00:10:02.437655 2.5 4.7 6.4 5.4 4.9 30.9 \n", + "2017-08-29 00:10:02.715850 1.6 1.9 5.4 5.1 10.1 51.0 \n", + "2017-08-29 00:10:02.974317 6.7 0.0 6.7 0.0 0.0 40.0 \n", + "2017-08-29 00:10:03.242796 7.7 0.0 7.7 0.0 0.0 46.2 \n", + "2017-08-29 00:10:03.471974 0.0 0.0 0.0 0.0 0.0 0.0 \n", + "2017-08-29 00:10:03.701915 3.8 5.3 7.8 6.2 5.1 42.2 \n", + "2017-08-29 00:10:03.922894 3.7 5.0 8.2 6.2 5.2 40.5 \n", + "2017-08-29 00:10:04.168584 4.9 4.9 4.9 7.3 4.9 56.1 \n", + "2017-08-29 00:10:04.391835 2.7 4.7 6.9 4.9 6.4 32.4 \n", + "2017-08-29 00:10:04.630956 2.9 4.9 7.5 5.0 5.7 29.5 \n", + "2017-08-29 00:10:04.819991 0.0 2.6 1.3 2.6 11.8 61.8 \n", + "... ... ... ... ... ... ... \n", + "2017-08-29 23:00:03.683160 2.7 4.9 6.8 5.0 6.5 32.3 \n", + "2017-08-29 23:00:03.924760 2.9 5.1 7.5 5.1 5.7 29.3 \n", + "2017-08-29 23:00:04.189034 0.0 2.6 1.3 2.6 13.0 61.0 \n", + "2017-08-29 23:00:04.381826 1.5 3.5 4.6 5.9 6.6 24.4 \n", + "2017-08-29 23:00:04.619175 1.4 4.2 4.0 5.9 4.7 20.5 \n", + "2017-08-29 23:00:04.820031 1.8 0.0 7.2 5.4 14.4 39.6 \n", + "2017-08-29 23:00:05.028872 0.0 12.5 12.5 25.0 25.0 12.5 \n", + "2017-08-29 23:00:05.231674 12.2 9.8 12.2 2.4 2.4 14.6 \n", + "2017-08-29 23:00:05.442596 1.0 3.2 5.8 5.0 6.5 28.0 \n", + "2017-08-29 23:00:05.634805 5.7 8.3 9.2 6.5 6.2 36.1 \n", + "2017-08-29 23:00:05.829558 2.1 4.1 5.8 5.5 5.5 33.7 \n", + "2017-08-29 23:10:02.207706 2.5 4.8 6.4 5.4 4.9 30.8 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"4_pct float64\n", + "5_pct float64\n", + "6_pct float64\n", + "7_pct float64\n", + "8_pct float64\n", + "9_pct float64\n", + "10_pct float64\n", + "dtype: object" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 17 + } + ] + }, + { + "metadata": { + "id": "WIQRDwA6d00Q", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 377 + }, + "outputId": "08f7de42-360a-426c-ce03-9567f95c576f" + }, + "cell_type": "code", + "source": [ + "df.category.value_counts()" + ], + "execution_count": 18, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Non-US users 4216\n", + "Top 1000 voters 4216\n", + "Aged 18-29 4216\n", + "Aged 45+ 4216\n", + "Females 4216\n", + "Females Aged 18-29 4216\n", + "IMDb staff 4216\n", + "Males 4216\n", + "US users 4216\n", + "Aged under 18 4216\n", + "Females Aged 45+ 4216\n", + "Males Aged 45+ 4216\n", + "Males Aged 30-44 4216\n", + "Males Aged 18-29 4216\n", + "Males under 18 4216\n", + "Females Aged 30-44 4216\n", + "Aged 30-44 4216\n", + "IMDb users 4216\n", + "Females under 18 4165\n", + "Name: category, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 18 + } + ] + }, + { + "metadata": { + "id": "Gi_eWwQDd8RA", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 377 + }, + "outputId": "4ddb255e-1ae8-48c7-e338-91473c692f3e" + }, + "cell_type": "code", + "source": [ + "df.link.value_counts()" + ], + "execution_count": 19, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "http://www.imdb.com/title/tt6322922/ratings-female_age_3 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-female_age_4 4216\n", + "http://www.imdb.com/title/tt6322922/ratings 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-male 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-age_3 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-age_1 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-male_age_3 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-age_4 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-male_age_1 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-imdb_staff 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-age_2 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-female 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-female_age_2 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-usa 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-international 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-male_age_4 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-male_age_2 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-top_1000 4216\n", + "http://www.imdb.com/title/tt6322922/ratings-female_age_1 4165\n", + "Name: link, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 19 + } + ] + }, + { + "metadata": { + "id": "980vLd3PeHlU", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "final = df[df.category == 'IMDb users']" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "u6ey9VuEeUzE", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 301 + }, + "outputId": "30905e0c-5fef-4594-c210-902934f0f4a5" + }, + "cell_type": "code", + "source": [ + "lastday = df['2017-08-29']\n", + "lastday[lastday.category == 'IMDb users'].respondents.plot();" + ], + "execution_count": 21, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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respondentscategorylinkaveragemeanmedian1_votes2_votes3_votes4_votes...1_pct2_pct3_pct4_pct5_pct6_pct7_pct8_pct9_pct10_pct
timestamp
2017-08-29 23:10:06.2182512662IMDb usershttp://www.imdb.com/title/tt6322922/ratings5.45.671021693825...38.42.61.40.92.14.15.85.55.533.7
\n", + "

1 rows × 26 columns

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" + ], + "text/plain": [ + " respondents category \\\n", + "timestamp \n", + "2017-08-29 23:10:06.218251 2662 IMDb users \n", + "\n", + " link \\\n", + "timestamp \n", + "2017-08-29 23:10:06.218251 http://www.imdb.com/title/tt6322922/ratings \n", + "\n", + " average mean median 1_votes 2_votes 3_votes \\\n", + "timestamp \n", + "2017-08-29 23:10:06.218251 5.4 5.6 7 1021 69 38 \n", + "\n", + " 4_votes ... 1_pct 2_pct 3_pct 4_pct \\\n", + "timestamp ... \n", + "2017-08-29 23:10:06.218251 25 ... 38.4 2.6 1.4 0.9 \n", + "\n", + " 5_pct 6_pct 7_pct 8_pct 9_pct 10_pct \n", + "timestamp \n", + "2017-08-29 23:10:06.218251 2.1 4.1 5.8 5.5 5.5 33.7 \n", + "\n", + "[1 rows x 26 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 22 + } + ] + }, + { + "metadata": { + "id": "KGrgtyXQfzt6", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "columns = [str(d) + '_pct' for d in range(1, 11)]" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "xwI1SznWgE_2", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 224 + }, + "outputId": "827a792c-763b-4ed5-9581-51d47c779817" + }, + "cell_type": "code", + "source": [ + "data = final[columns].T['2017-08-29 23:10:06.218251']\n", + "# data.describe()\n", + "data.head(10)" + ], + "execution_count": 24, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1_pct 38.4\n", + "2_pct 2.6\n", + "3_pct 1.4\n", + "4_pct 0.9\n", + "5_pct 2.1\n", + "6_pct 4.1\n", + "7_pct 5.8\n", + "8_pct 5.5\n", + "9_pct 5.5\n", + "10_pct 33.7\n", + "Name: 2017-08-29 23:10:06.218251, dtype: float64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 24 + } + ] + }, + { + "metadata": { + "id": "bOfXSu9FgLHa", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 388 + }, + "outputId": "d2b81c6a-45a3-40af-a54c-cddf3e9a7d59" + }, + "cell_type": "code", + "source": [ + "# plt.figure(figsize = (15, 10))\n", + "plt.style.use('fivethirtyeight')\n", + "ax = data.plot.bar(color = '#EC713B', width = 0.9);\n", + "\n", + "# We can do this, but their title has a subtitle,\n", + "# so we can do something else.\n", + "# ax.set(title = \"'An inconvenient sequel: Truth to Power' is divisive\",\n", + "# xlabel = 'Rating',\n", + "# ylabel = 'Percent of total votes')\n", + "\n", + "ax.set(xlabel = 'Rating',\n", + " ylabel = 'Percent of total votes',\n", + " yticks = range(0, 50, 10))\n", + "ax.text(x = -2, y = 50, s = \"'An inconvenient sequel: Truth to Power' is divisive\",\n", + " fontsize = 16, fontweight = 'bold')\n", + "ax.text(x = -2, y = 46, s = \"IMDb ratings for the film as of Aug. 29\")\n", + "\n", + "ax.tick_params(labelrotation = 0)" + ], + "execution_count": 25, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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NgqypskcmmZmZ0NHRAVDyI5NKpdDU1BQ29JcvXyI/Px/KysoAICQyBQUFaGlplRtYUhUb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\njahJ7dWrV0hISBClrLt372Ls2LH4/ff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respondentsaveragemeanmedian1_votes2_votes3_votes4_votes5_votes6_votes7_votes8_votes9_votes10_votes1_pct2_pct3_pct4_pct5_pct6_pct7_pct8_pct9_pct10_pct
count80053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.00000080053.000000
mean403.3908045.3314785.6769546.023047159.45507411.5621036.9965903.2117227.79768413.44162018.83244917.95325622.565713141.57459437.3449192.2309011.7269361.0315193.1696893.5045944.7801994.8008595.97812735.431905
std544.9774001.6732791.6026803.131885227.15495116.1208698.9644254.26711810.63364819.32653726.79940925.39881828.591822187.95467320.0800972.4442951.6202331.4389293.9033914.1373293.7987145.2248085.75952015.814088
min1.0000001.0000001.0000001.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
25%34.0000004.3000004.8000003.0000006.0000000.0000000.0000000.0000001.0000001.0000001.0000002.0000002.0000006.00000025.0000000.0000000.0000000.0000000.8000001.2000002.2000002.6000003.60000026.300000
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75%518.0000006.5000006.6000009.000000227.00000020.00000010.0000005.00000010.00000019.00000026.00000024.00000032.000000188.00000046.0000003.2000002.2000001.4000003.6000004.3000006.8000005.3000006.40000045.100000
max2662.0000008.5000008.60000010.0000001021.00000069.00000040.00000025.00000055.000000110.000000154.000000147.000000146.000000897.000000100.00000010.3000009.1000008.60000025.00000050.00000025.00000028.60000033.30000082.800000
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timestamprespondentscategorylinkaveragemeanmedian1_votes2_votes3_votes4_votes5_votes6_votes7_votes8_votes9_votes10_votes1_pct2_pct3_pct4_pct5_pct6_pct7_pct8_pct9_pct10_pct
02017-07-17 12:28:32.785639402Maleshttp://www.imdb.com/title/tt6322922/ratings-male4.65.02197773771182013549.01.71.70.71.71.72.72.05.033.6
12017-07-17 12:28:33.02560078Femaleshttp://www.imdb.com/title/tt6322922/ratings-fe...6.97.71016101103434920.51.30.01.31.30.03.85.13.862.8
22017-07-17 12:28:33.2739194Aged under 18http://www.imdb.com/title/tt6322922/ratings-age_14.24.23200010000150.00.00.00.025.00.00.00.00.025.0
32017-07-17 12:28:33.4953254Males under 18http://www.imdb.com/title/tt6322922/ratings-ma...4.24.23200010000150.00.00.00.025.00.00.00.00.025.0
42017-07-17 12:28:33.722849130Aged 18-29http://www.imdb.com/title/tt6322922/ratings-age_26.36.5941031236466431.50.02.30.81.52.34.63.14.649.2
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" + ], + "text/plain": [ + " timestamp respondents category \\\n", + "0 2017-07-17 12:28:32.785639 402 Males \n", + "1 2017-07-17 12:28:33.025600 78 Females \n", + "2 2017-07-17 12:28:33.273919 4 Aged under 18 \n", + "3 2017-07-17 12:28:33.495325 4 Males under 18 \n", + "4 2017-07-17 12:28:33.722849 130 Aged 18-29 \n", + "\n", + " link average mean median \\\n", + "0 http://www.imdb.com/title/tt6322922/ratings-male 4.6 5.0 2 \n", + "1 http://www.imdb.com/title/tt6322922/ratings-fe... 6.9 7.7 10 \n", + "2 http://www.imdb.com/title/tt6322922/ratings-age_1 4.2 4.2 3 \n", + "3 http://www.imdb.com/title/tt6322922/ratings-ma... 4.2 4.2 3 \n", + "4 http://www.imdb.com/title/tt6322922/ratings-age_2 6.3 6.5 9 \n", + "\n", + " 1_votes 2_votes 3_votes 4_votes 5_votes 6_votes 7_votes 8_votes \\\n", + "0 197 7 7 3 7 7 11 8 \n", + "1 16 1 0 1 1 0 3 4 \n", + "2 2 0 0 0 1 0 0 0 \n", + "3 2 0 0 0 1 0 0 0 \n", + "4 41 0 3 1 2 3 6 4 \n", + "\n", + " 9_votes 10_votes 1_pct 2_pct 3_pct 4_pct 5_pct 6_pct 7_pct 8_pct \\\n", + "0 20 135 49.0 1.7 1.7 0.7 1.7 1.7 2.7 2.0 \n", + "1 3 49 20.5 1.3 0.0 1.3 1.3 0.0 3.8 5.1 \n", + "2 0 1 50.0 0.0 0.0 0.0 25.0 0.0 0.0 0.0 \n", + "3 0 1 50.0 0.0 0.0 0.0 25.0 0.0 0.0 0.0 \n", + "4 6 64 31.5 0.0 2.3 0.8 1.5 2.3 4.6 3.1 \n", + "\n", + " 9_pct 10_pct \n", + "0 5.0 33.6 \n", + "1 3.8 62.8 \n", + "2 0.0 25.0 \n", + "3 0.0 25.0 \n", + "4 4.6 49.2 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 40 + } + ] + }, + { + "metadata": { + "id": "_M_uJw8Ixb2m", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 493 + }, + "outputId": "b21d679e-0cef-4f3e-b6a3-8db6f5feb054" + }, + "cell_type": "code", + "source": [ + "df.dtypes" + ], + "execution_count": 41, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "timestamp object\n", + "respondents int64\n", + "category object\n", + "link object\n", + "average float64\n", + "mean float64\n", + "median int64\n", + "1_votes int64\n", + "2_votes int64\n", + "3_votes int64\n", + "4_votes int64\n", + "5_votes int64\n", + "6_votes int64\n", + "7_votes int64\n", + "8_votes int64\n", + "9_votes int64\n", + "10_votes int64\n", + "1_pct float64\n", + "2_pct float64\n", + "3_pct float64\n", + "4_pct float64\n", + "5_pct float64\n", + "6_pct float64\n", + "7_pct float64\n", + "8_pct float64\n", + "9_pct float64\n", + "10_pct float64\n", + "dtype: object" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 41 + } + ] + }, + { + "metadata": { + "id": "OyE9eF65xBVC", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "df.timestamp = pd.to_datetime(df.timestamp)\n", + "df.set_index('timestamp', inplace = True)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "RH5ocPi_xZu2", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 136 + }, + "outputId": "41524201-c7eb-4b14-8414-b67884cf1673" + }, + "cell_type": "code", + "source": [ + "final = df[df.category == 'IMDb users']['respondents']\n", + "final.head()" + ], + "execution_count": 43, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "timestamp\n", + "2017-07-17 12:28:36.697246 678\n", + "2017-07-17 12:34:21.250099 678\n", + "2017-07-17 13:00:06.506688 678\n", + "2017-07-17 14:00:06.727742 679\n", + "2017-07-17 15:00:06.055125 679\n", + "Name: respondents, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 43 + } + ] + }, + { + "metadata": { + "id": "-K7wEGHrzQZr", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 136 + }, + "outputId": "49310bb5-ca35-4450-aaa7-ee889c9e75bd" + }, + "cell_type": "code", + "source": [ + "total_respondents = final.iloc[-1]\n", + "final = final * 100 / total_respondents\n", + "final.head()" + ], + "execution_count": 44, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "timestamp\n", + "2017-07-17 12:28:36.697246 25.469572\n", + "2017-07-17 12:34:21.250099 25.469572\n", + "2017-07-17 13:00:06.506688 25.469572\n", + "2017-07-17 14:00:06.727742 25.507137\n", + "2017-07-17 15:00:06.055125 25.507137\n", + "Name: respondents, dtype: float64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 44 + } + ] + }, + { + "metadata": { + "id": "hPW6KVlTytw8", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 449 + }, + "outputId": "0c7efb08-7144-4647-b15a-107f574f42d2" + }, + "cell_type": "code", + "source": [ + "import matplotlib.ticker as ticker\n", + "\n", + "plt.figure(figsize = (10, 7))\n", + "plt.title(s = \"'An Inconvenient Sequel' was doomed before its release\",\n", + " x = 0,\n", + " y = 1.11,\n", + " ha = 'left')\n", + "plt.suptitle(t = 'Share of tickets sold and IMDb reviews for \"An Inconvenient Sequel\"\\nposted through Aug. 27, by day',\n", + " x = 0.09,\n", + " y = 0.95,\n", + " fontsize = 16,\n", + " fontweight = 'ultralight',\n", + " ha = 'left')\n", + "plt.style.use('fivethirtyeight')\n", + "ax = final.plot.line(color = '#47C0C7');\n", + "\n", + "ax.set(xlabel = '',\n", + " ylabel = '',\n", + " yticks = range(0, 101, 20))\n", + "# ax.set_xlim(final.index[0]) # Gives error: 'Too many values to unpack'\n", + "# ax.set_xlim(auto = True)\n", + "ax.annotate('Share of IMDb\\nreviews posted',\n", + " (pd.to_datetime('2017-08-03'), 80),\n", + " (pd.to_datetime('2017-08-03'), 80),\n", + " fontweight = 'bold',\n", + " color = '#47C0C7')\n", + "\n", + "ax.annotate('60% of the reviews were already in\\nby the wide release date',\n", + " (pd.to_datetime('2017-08-05'), 61),\n", + " (pd.to_datetime('2017-08-08'), 50),\n", + " fontweight = 'ultralight',\n", + " arrowprops=dict(facecolor='black', shrink=0.05))\n", + "\n", + "# Change axis colors\n", + "ax.set_facecolor('w')\n", + "\n", + "# dt.strftime(\"%A, %d. %B %Y %I:%M%p\")\n", + "\n", + "xlabels = ['', 'JULY 23, 2017', 'JULY 30', 'AUG. 6', 'AUG. 13', 'AUG. 20', 'AUG. 27']\n", + "@ticker.FuncFormatter\n", + "def major_formatter(x, pos):\n", + " return xlabels[pos]\n", + " \n", + "for tick in ax.xaxis.get_major_ticks():\n", + " tick.label1.set_horizontalalignment('center')\n", + "ax.xaxis.set_major_formatter(major_formatter)\n", + "\n", + "# ax.get_xaxis().get_major_formatter().set_useOffset(False)\n", + "\n", + "ax.tick_params(labelrotation = 0)\n", + "plt.show()" + ], + "execution_count": 64, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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tb2/PoEGDWLNmDZ07dy6y769YsQI9PT3++OMPGW9cx44dmThxIlu3bmXhwoXApwcrqVJf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\n1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"cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "metadata": { + "id": "JbDHnhet8CWy", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "_Lambda School Data Science_\n", + "\n", + "# Sequence your narrative\n", + "\n", + "Create a sequence of visualizations inspired by [Hans Rosling's 200 Countries, 200 Years, 4 Minutes](https://www.youtube.com/watch?v=jbkSRLYSojo).\n", + "\n", + "Using this [data from Gapminder](https://github.com/open-numbers/ddf--gapminder--systema_globalis/):\n", + "- https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--income_per_person_gdppercapita_ppp_inflation_adjusted--by--geo--time.csv\n", + "- https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--life_expectancy_years--by--geo--time.csv\n", + "- https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--population_total--by--geo--time.csv\n", + "- https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--entities--geo--country.csv\n", + "- https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--concepts.csv" + ] + }, + { + "metadata": { + "id": "SxTJBgRAW3jD", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Variables --> Visual Encodings\n", + "- Income --> x\n", + "- Lifespan --> y\n", + "- Region --> color\n", + "- Population --> size\n", + "- Year --> animation frame (alternative: small multiple)\n", + "- Country --> annotation\n", + "\n", + "Qualitative --> Verbal\n", + "- Editorial / contextual explanation --> audio narration (alternative: text)\n", + "\n", + "\n", + "| Year | Country | Region | Income | Lifespan | Population |\n", + "|------|---------|----------|--------|----------|------------|\n", + "| 1818 | USA | Americas | ### | ## | # |\n", + "| 1918 | USA | Americas | #### | ### | ## |\n", + "| 2018 | USA | Americas | ##### | ### | ### |\n", + "| 1818 | China | Asia | # | # | # |\n", + "| 1918 | China | Asia | ## | ## | ### |\n", + "| 2018 | China | Asia | ### | ### | ##### |\n" + ] + }, + { + "metadata": { + "id": "3ebEjShbWsIy", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Upgrade Seaborn\n", + "\n", + "Make sure you have at least version 0.9.0.\n", + "\n", + "In Colab, go to **Restart runtime** after you run the `pip` command." + ] + }, + { + "metadata": { + "id": "4RSxbu7rWr1p", + "colab_type": "code", + "outputId": "517d410a-a383-4dcd-bdee-93e5a0a245d9", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 326 + } + }, + "cell_type": "code", + "source": [ + "!pip install --upgrade seaborn" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Collecting seaborn\n", + "\u001b[?25l Downloading https://files.pythonhosted.org/packages/a8/76/220ba4420459d9c4c9c9587c6ce607bf56c25b3d3d2de62056efe482dadc/seaborn-0.9.0-py3-none-any.whl (208kB)\n", + "\u001b[K 100% |████████████████████████████████| 215kB 25.8MB/s \n", + "\u001b[?25hRequirement already satisfied, skipping upgrade: matplotlib>=1.4.3 in /usr/local/lib/python3.6/dist-packages (from seaborn) (2.1.2)\n", + "Requirement already satisfied, skipping upgrade: scipy>=0.14.0 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.1.0)\n", + "Requirement already satisfied, skipping upgrade: numpy>=1.9.3 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.14.6)\n", + "Requirement already satisfied, skipping upgrade: pandas>=0.15.2 in /usr/local/lib/python3.6/dist-packages (from seaborn) (0.22.0)\n", + "Requirement already satisfied, skipping upgrade: pytz in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (2018.7)\n", + "Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (2.5.3)\n", + "Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (0.10.0)\n", + "Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (2.3.0)\n", + "Requirement already satisfied, skipping upgrade: six>=1.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=1.4.3->seaborn) (1.11.0)\n", + "Installing collected packages: seaborn\n", + " Found existing installation: seaborn 0.7.1\n", + " Uninstalling seaborn-0.7.1:\n", + " Successfully uninstalled seaborn-0.7.1\n", + "Successfully installed seaborn-0.9.0\n" + ], + "name": "stdout" + } + ] + }, + { + "metadata": { + "id": "5sQ0-7JUWyN4", + "colab_type": "code", + "outputId": "faeabcaa-6dcb-418d-f7e5-dc3d7cdcb37f", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "cell_type": "code", + "source": [ + "import seaborn as sns\n", + "sns.__version__" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "'0.9.0'" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 1 + } + ] + }, + { + "metadata": { + "id": "S2dXWRTFTsgd", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## More imports" + ] + }, + { + "metadata": { + "id": "y-TgL_mA8OkF", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "CZGG5prcTxrQ", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Load & look at data" + ] + }, + { + "metadata": { + "id": "-uE25LHD8CW0", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "income = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--income_per_person_gdppercapita_ppp_inflation_adjusted--by--geo--time.csv')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "gg_pJslMY2bq", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "lifespan = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--life_expectancy_years--by--geo--time.csv')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "F6knDUevY-xR", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "population = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--population_total--by--geo--time.csv')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "hX6abI-iZGLl", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "entities = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--entities--geo--country.csv')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "AI-zcaDkZHXm", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "concepts = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--concepts.csv')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "EgFw-g0nZLJy", + "colab_type": "code", + "outputId": "b8afa1dd-2c31-4a95-9bd0-a707e15c1c1a", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "cell_type": "code", + "source": [ + "income.shape, lifespan.shape, population.shape, entities.shape, concepts.shape" + ], + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "((44268, 3), (44370, 3), (51939, 3), (273, 33), (590, 16))" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 10 + } + ] + }, + { + "metadata": { + "id": "I-T62v7FZQu5", + "colab_type": "code", + "outputId": "462b2972-7cf4-456a-9384-da6f695e82a3", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + } + }, + "cell_type": "code", + "source": [ + "income.head()" + ], + "execution_count": 11, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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3aged_15_24_unemployment_rate_percentNaNmeasurePercentage of total population, age group 15-2...NaNNaNNaNNaNAged 15-24 unemployment rate (%)Aged 15-24Unemployment rate (%)[\"linear\", \"log\"]NaNNaNhttp://ilo.org/legacy/english/global-reports/k...unemployment
4aged_15_64_labour_force_participation_rate_per...NaNmeasureFor age group 15-64, percentage of all labour ...NaNNaNNaNNaNAged 15-64 labour force participation rate (%)Aged 15-64Labour force participation rate (%)[\"linear\", \"log\"]NaNNaNhttp://ilo.org/legacy/english/global-reports/k...labour_force_participation
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geotimeincome_per_person_gdppercapita_ppp_inflation_adjustedlife_expectancy_years
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" + ], + "text/plain": [ + " geo time income_per_person_gdppercapita_ppp_inflation_adjusted \\\n", + "0 abw 1800 833 \n", + "1 abw 1801 833 \n", + "2 abw 1802 833 \n", + "3 abw 1803 833 \n", + "4 abw 1804 833 \n", + "\n", + " life_expectancy_years \n", + "0 34.42 \n", + "1 34.42 \n", + "2 34.42 \n", + "3 34.42 \n", + "4 34.42 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 24 + } + ] + }, + { + "metadata": { + "id": "ycidawqpeR93", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "df = pd.merge(df, population)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "BF62lbePdI_p", + "colab_type": "code", + "outputId": "6fafbf33-d424-4bb5-e37b-8a1b84b16506", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + } + }, + "cell_type": "code", + "source": [ + "# Preview\n", + "pd.merge(df, entities[variables], \n", + " how='inner', left_on='geo', right_on='country').head()" + ], + "execution_count": 26, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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1abw180183334.4219286abwArubaamerica
2abw180283334.4219286abwArubaamerica
3abw180383334.4219286abwArubaamerica
4abw180483334.4219286abwArubaamerica
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" + ], + "text/plain": [ + " geo time income_per_person_gdppercapita_ppp_inflation_adjusted \\\n", + "0 abw 1800 833 \n", + "1 abw 1801 833 \n", + "2 abw 1802 833 \n", + "3 abw 1803 833 \n", + "4 abw 1804 833 \n", + "\n", + " life_expectancy_years population_total country name world_6region \n", + "0 34.42 19286 abw Aruba america \n", + "1 34.42 19286 abw Aruba america \n", + "2 34.42 19286 abw Aruba america \n", + "3 34.42 19286 abw Aruba america \n", + "4 34.42 19286 abw Aruba america " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 26 + } + ] + }, + { + "metadata": { + "id": "xisnv1LPdtjB", + "colab_type": "code", + "outputId": "a4e19042-c8be-4430-87a9-f81ed3852a70", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "cell_type": "code", + "source": [ + "df = pd.merge(df, entities[variables], \n", + " how='inner', left_on='geo', right_on='country')\n", + "\n", + "df.drop(columns=['geo', 'country'], inplace=True)\n", + "\n", + "df.rename(columns={\n", + " 'time': 'year', \n", + " 'income_per_person_gdppercapita_ppp_inflation_adjusted': 'income', \n", + " 'life_expectancy_years': 'lifespan', \n", + " 'population_total': 'population', \n", + " 'name': 'country', \n", + " 'world_6region': 'region'\n", + "}, inplace=True)\n", + "\n", + "df.shape" + ], + "execution_count": 27, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(41790, 6)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 27 + } + ] + }, + { + "metadata": { + "id": "gFj-L4S_ehK_", + "colab_type": "code", + "outputId": "dfc27842-b470-411f-b7e0-3b7b36e895ac", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + } + }, + "cell_type": "code", + "source": [ + "df.head()" + ], + "execution_count": 28, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearincomelifespanpopulationcountryregion
0180083334.4219286Arubaamerica
1180183334.4219286Arubaamerica
2180283334.4219286Arubaamerica
3180383334.4219286Arubaamerica
4180483334.4219286Arubaamerica
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" + ], + "text/plain": [ + " year income lifespan population country region\n", + "0 1800 833 34.42 19286 Aruba america\n", + "1 1801 833 34.42 19286 Aruba america\n", + "2 1802 833 34.42 19286 Aruba america\n", + "3 1803 833 34.42 19286 Aruba america\n", + "4 1804 833 34.42 19286 Aruba america" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 28 + } + ] + }, + { + "metadata": { + "id": "4OdEr5IFVdF5", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Explore data" + ] + }, + { + "metadata": { + "id": "QXrJmqdaVTAz", + "colab_type": "code", + "outputId": "403ac295-f772-47b6-e5e7-eed3900dd901", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 297 + } + }, + "cell_type": "code", + "source": [ + "df.describe()" + ], + "execution_count": 29, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearincomelifespanpopulation
count41790.00000041790.00000041790.0000004.179000e+04
mean1909.3574064778.59368343.2671811.332550e+07
std63.32296910502.60258016.3942406.502349e+07
min1800.000000247.0000001.0000002.128000e+03
25%1854.000000884.00000031.2000003.760282e+05
50%1909.0000001449.00000035.5000001.915244e+06
75%1964.0000003536.75000056.3400006.260147e+06
max2018.000000177522.00000084.1700001.415046e+09
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" + ], + "text/plain": [ + " year income lifespan population\n", + "count 41790.000000 41790.000000 41790.000000 4.179000e+04\n", + "mean 1909.357406 4778.593683 43.267181 1.332550e+07\n", + "std 63.322969 10502.602580 16.394240 6.502349e+07\n", + "min 1800.000000 247.000000 1.000000 2.128000e+03\n", + "25% 1854.000000 884.000000 31.200000 3.760282e+05\n", + "50% 1909.000000 1449.000000 35.500000 1.915244e+06\n", + "75% 1964.000000 3536.750000 56.340000 6.260147e+06\n", + "max 2018.000000 177522.000000 84.170000 1.415046e+09" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 29 + } + ] + }, + { + "metadata": { + "id": "zQ7rfRBse8CG", + "colab_type": "code", + "outputId": "05b8c675-4d91-4833-dbbf-1aca1dcceb61", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 173 + } + }, + "cell_type": "code", + "source": [ + "df.describe(exclude=[np.number])" + ], + "execution_count": 30, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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countryregion
count4179041790
unique1946
topCroatiaeurope_central_asia
freq21910991
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" + ], + "text/plain": [ + " country region\n", + "count 41790 41790\n", + "unique 194 6\n", + "top Croatia europe_central_asia\n", + "freq 219 10991" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 30 + } + ] + }, + { + "metadata": { + "id": "cMWm0QYZfTFi", + "colab_type": "code", + "outputId": "ba8513e5-503f-4051-e7e8-a4b0467dceb6", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 697 + } + }, + "cell_type": "code", + "source": [ + "df.country.unique()" + ], + "execution_count": 31, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array(['Aruba', 'Afghanistan', 'Angola', 'Albania', 'Andorra',\n", + " 'United Arab Emirates', 'Argentina', 'Armenia',\n", + " 'Antigua and Barbuda', 'Australia', 'Austria', 'Azerbaijan',\n", + " 'Burundi', 'Belgium', 'Benin', 'Burkina Faso', 'Bangladesh',\n", + " 'Bulgaria', 'Bahrain', 'Bahamas', 'Bosnia and Herzegovina',\n", + " 'Belarus', 'Belize', 'Bermuda', 'Bolivia', 'Brazil', 'Barbados',\n", + " 'Brunei', 'Bhutan', 'Botswana', 'Central African Republic',\n", + " 'Canada', 'Switzerland', 'Chile', 'China', \"Cote d'Ivoire\",\n", + " 'Cameroon', 'Congo, Dem. Rep.', 'Congo, Rep.', 'Colombia',\n", + " 'Comoros', 'Cape Verde', 'Costa Rica', 'Cuba', 'Cyprus',\n", + " 'Czech Republic', 'Germany', 'Djibouti', 'Dominica', 'Denmark',\n", + " 'Dominican Republic', 'Algeria', 'Ecuador', 'Egypt', 'Eritrea',\n", + " 'Spain', 'Estonia', 'Ethiopia', 'Finland', 'Fiji', 'France',\n", + " 'Micronesia, Fed. Sts.', 'Gabon', 'United Kingdom', 'Georgia',\n", + " 'Ghana', 'Guinea', 'Gambia', 'Guinea-Bissau', 'Equatorial Guinea',\n", + " 'Greece', 'Grenada', 'Greenland', 'Guatemala', 'Guyana',\n", + " 'Hong Kong, China', 'Honduras', 'Croatia', 'Haiti', 'Hungary',\n", + " 'Indonesia', 'India', 'Ireland', 'Iran', 'Iraq', 'Iceland',\n", + " 'Israel', 'Italy', 'Jamaica', 'Jordan', 'Japan', 'Kazakhstan',\n", + " 'Kenya', 'Kyrgyz Republic', 'Cambodia', 'Kiribati', 'South Korea',\n", + " 'Kuwait', 'Lao', 'Lebanon', 'Liberia', 'Libya', 'St. Lucia',\n", + " 'Sri Lanka', 'Lesotho', 'Lithuania', 'Luxembourg', 'Latvia',\n", + " 'Macao, China', 'Morocco', 'Moldova', 'Madagascar', 'Maldives',\n", + " 'Mexico', 'Marshall Islands', 'Macedonia, FYR', 'Mali', 'Malta',\n", + " 'Myanmar', 'Montenegro', 'Mongolia', 'Mozambique', 'Mauritania',\n", + " 'Mauritius', 'Malawi', 'Malaysia', 'Namibia', 'Niger', 'Nigeria',\n", + " 'Nicaragua', 'Netherlands', 'Norway', 'Nepal', 'New Zealand',\n", + " 'Oman', 'Pakistan', 'Panama', 'Peru', 'Philippines',\n", + " 'Papua New Guinea', 'Poland', 'Puerto Rico', 'North Korea',\n", + " 'Portugal', 'Paraguay', 'Palestine', 'Qatar', 'Romania', 'Russia',\n", + " 'Rwanda', 'Saudi Arabia', 'Sudan', 'Senegal', 'Singapore',\n", + " 'Solomon Islands', 'Sierra Leone', 'El Salvador', 'Somalia',\n", + " 'Serbia', 'South Sudan', 'Sao Tome and Principe', 'Suriname',\n", + " 'Slovak Republic', 'Slovenia', 'Sweden', 'Swaziland', 'Seychelles',\n", + " 'Syria', 'Chad', 'Togo', 'Thailand', 'Tajikistan', 'Turkmenistan',\n", + " 'Timor-Leste', 'Tonga', 'Trinidad and Tobago', 'Tunisia', 'Turkey',\n", + " 'Taiwan', 'Tanzania', 'Uganda', 'Ukraine', 'Uruguay',\n", + " 'United States', 'Uzbekistan', 'St. Vincent and the Grenadines',\n", + " 'Venezuela', 'Vietnam', 'Vanuatu', 'Samoa', 'Yemen',\n", + " 'South Africa', 'Zambia', 'Zimbabwe'], dtype=object)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 31 + } + ] + }, + { + "metadata": { + "id": "hpeAXP8sfYur", + "colab_type": "code", + "outputId": "7679c50c-5ab8-47a8-d443-724dc72ae61f", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 142 + } + }, + "cell_type": "code", + "source": [ + "usa = df[df.country=='United States']\n", + "usa[usa.year.isin([1818, 1918, 2018])]" + ], + "execution_count": 32, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearincomelifespanpopulationcountryregion
393991818225839.419879049United Statesamerica
394991918937147.18106721812United Statesamerica
3959920185489879.14326766748United Statesamerica
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" + ], + "text/plain": [ + " year income lifespan population country region\n", + "39399 1818 2258 39.41 9879049 United States america\n", + "39499 1918 9371 47.18 106721812 United States america\n", + "39599 2018 54898 79.14 326766748 United States america" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 32 + } + ] + }, + { + "metadata": { + "id": "VPL8CJWdf6sO", + "colab_type": "code", + "outputId": "48189b43-3ed4-4ae3-b767-f36f2b60ac57", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 142 + } + }, + "cell_type": "code", + "source": [ + "china = df[df.country=='China']\n", + "china[china.year.isin([1818, 1918, 2018])]" + ], + "execution_count": 33, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearincomelifespanpopulationcountryregion
7120181898532.00374161494Chinaeast_asia_pacific
7220191898922.13462444535Chinaeast_asia_pacific
732020181601876.921415045928Chinaeast_asia_pacific
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" + ], + "text/plain": [ + " year income lifespan population country region\n", + "7120 1818 985 32.00 374161494 China east_asia_pacific\n", + "7220 1918 989 22.13 462444535 China east_asia_pacific\n", + "7320 2018 16018 76.92 1415045928 China east_asia_pacific" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 33 + } + ] + }, + { + "metadata": { + "id": "hecscpimY6Oz", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Plot visualization" + ] + }, + { + "metadata": { + "id": "gtxPFc_rWnKn", + "colab_type": "code", + "outputId": "0f9a6714-608b-420c-e870-d1b892c6def3", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 376 + } + }, + "cell_type": "code", + "source": [ + "now = df[df.year==2018]\n", + "print(now.shape)\n", + "now.sample(10)" + ], + "execution_count": 34, + "outputs": [ + { + "output_type": "stream", + "text": [ + "(188, 6)\n" + ], + "name": "stdout" + }, + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearincomelifespanpopulationcountryregion
1043320184658381.105754356Denmarkeurope_central_asia
321552018193268.3312501156Rwandasub_saharan_africa
1787320181740276.4782011735Iranmiddle_east_north_africa
139372018437566.6229463643Ghanasub_saharan_africa
622520181646766.922333201Botswanasub_saharan_africa
2930820182337479.404162618Panamaamerica
86342018143968.00832347Comorossub_saharan_africa
406942018289664.30282117Vanuatueast_asia_pacific
260232018119661.0730528673Mozambiquesub_saharan_africa
33907201862958.0315181925Somaliasub_saharan_africa
\n", + "
" + ], + "text/plain": [ + " year income lifespan population country \\\n", + "10433 2018 46583 81.10 5754356 Denmark \n", + "32155 2018 1932 68.33 12501156 Rwanda \n", + "17873 2018 17402 76.47 82011735 Iran \n", + "13937 2018 4375 66.62 29463643 Ghana \n", + "6225 2018 16467 66.92 2333201 Botswana \n", + "29308 2018 23374 79.40 4162618 Panama \n", + "8634 2018 1439 68.00 832347 Comoros \n", + "40694 2018 2896 64.30 282117 Vanuatu \n", + "26023 2018 1196 61.07 30528673 Mozambique \n", + "33907 2018 629 58.03 15181925 Somalia \n", + "\n", + " region \n", + "10433 europe_central_asia \n", + "32155 sub_saharan_africa \n", + "17873 middle_east_north_africa \n", + "13937 sub_saharan_africa \n", + "6225 sub_saharan_africa \n", + "29308 america \n", + "8634 sub_saharan_africa \n", + "40694 east_asia_pacific \n", + "26023 sub_saharan_africa \n", + "33907 sub_saharan_africa " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 34 + } + ] + }, + { + "metadata": { + "id": "CtwGDDeRgYy1", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "sns.relplot?" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "C0dJa6FVgd7r", + "colab_type": "code", + "outputId": "da88e191-7255-478d-de7e-af2eca709dfe", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + } + }, + "cell_type": "code", + "source": [ + "sns.relplot(x='income', y='lifespan', hue='region', size='population', data=now);" + ], + "execution_count": 36, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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DCrjv1PE7pEs1iQTx8nJMLIZxuQibBJblY+bvF5Cd76a2OorP7+K4H4/D7W2/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\ns9gdLfTjgHnGmC37l5aISN8GXe6bd3J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Fmb3eRD0jiQL+O1FPNXnAf5pp057AfkRZOQGy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\nHwNPE6Vkbc2RRFf1uPvrQD8zaxjzfMndq0IK02XAoHa0RVo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yearincomelifespanpopulationcountryregion
2291020189903482.39590321Luxembourgeurope_central_asia
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31498201812103380.712694849Qatarmiddle_east_north_africa
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" + ], + "text/plain": [ + " year income lifespan population country \\\n", + "22910 2018 99034 82.39 590321 Luxembourg \n", + "23348 2018 97057 83.24 632418 Macao, China \n", + "31498 2018 121033 80.71 2694849 Qatar \n", + "33031 2018 83888 84.03 5791901 Singapore \n", + "\n", + " region \n", + "22910 europe_central_asia \n", + "23348 east_asia_pacific \n", + "31498 middle_east_north_africa \n", + "33031 east_asia_pacific " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 37 + } + ] + }, + { + "metadata": { + "id": "5fEMqwO8m0hm", + "colab_type": "code", + "outputId": "944c48ef-28b0-42ec-e530-3f945316da18", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1072 + } + }, + "cell_type": "code", + "source": [ + "entities[entities.name=='Macao, China'].T" + ], + "execution_count": 38, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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145
countrymac
alt_5MACAU SPECIAL ADMINISTRATIVE REGION OF CHINA
alternative_1Macau
alternative_2Macao
alternative_3China, Macao SAR
alternative_4_cdiacMacau
arb1Macao SAR, China
arb2NaN
arb3NaN
arb4NaN
arb5NaN
arb6NaN
g77_and_oecd_countriesothers
gapminder_listMacao, China
god_idMO
gwidi130
income_groupshigh_income
is--countryTrue
iso3166_1_alpha2MO
iso3166_1_alpha3MAC
iso3166_1_numeric446
iso3166_2NaN
landlockedcoastline
latitude22.2006
longitude113.546
main_religion_2008eastern_religions
nameMacao, China
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unicode_region_subtagMO
upper_case_nameMACAU
world_4regionasia
world_6regioneast_asia_pacific
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}, + { + "metadata": { + "id": "E17uZnqmnoU3", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "qatar = now[now.country=='Qatar']\n", + "qatar_income = qatar.income.values[0]\n", + "qatar_lifespan = qatar.lifespan.values[0]" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "r7-yw9gNoHgB", + "colab_type": "code", + "outputId": "7cc8ef7b-1b6e-4ba9-8846-0770af139523", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 382 + } + }, + "cell_type": "code", + "source": [ + "sns.relplot(x='income', y='lifespan', hue='region', size='population', data=now)\n", + "\n", + "plt.text(x=qatar_income-5000, y=qatar_lifespan+1, s='Qatar')\n", + "\n", + "plt.title('Qatar has the highest incomes in 2018');" + ], + "execution_count": 40, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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Kq5a/5YeVzLrvTmLRKJOu/B0jjp2MQ9/f7lAqSooJBfw43Yl4Ovmz/o3QMe5HaV2WbqF3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\nVFJS0hDpMVW1HrgaeAuYDbyoqrOi0FyzHYvLgJ4SSCE3JZe6hjrGfjW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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "DNTMMBkVhrGk", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Plot multiple years" + ] + }, + { + "metadata": { + "id": "9BHzjgAopQmi", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# now = df[df.year==2018]\n", + "\n", + "years = [1818, 1918, 2018]\n", + "\n", + "centuries = df[df.year.isin(years)]" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "bklabbB1pfho", + "colab_type": "code", + "outputId": "6a09c31d-69c6-46ad-cd0a-37b7d4ebfbe2", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 373 + } + }, + "cell_type": "code", + "source": [ + "sns.relplot(x='income', y='lifespan', hue='region', size='population', \n", + " col='year', data=centuries)\n", + "\n", + "plt.xscale('log');" + ], + "execution_count": 42, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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KAL12ruDwW98ha+Hf0+bzwpk7UXvA0QTv/Ncag2jb9i3gzXP3JJLMUJbvJeDt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\nERERERERkS4oiSYiIiIiIiIiItKF/w+tFVXXduBccQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "woaEesN0rWfc", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Consistent countries per year?" + ] + }, + { + "metadata": { + "id": "IOUy6604psot", + "colab_type": "code", + "outputId": "99b3caa7-a287-415d-c6da-abf87317658b", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 102 + } + }, + "cell_type": "code", + "source": [ + "centuries.groupby('year').country.count()" + ], + "execution_count": 43, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "year\n", + "1818 190\n", + "1918 190\n", + "2018 188\n", + "Name: country, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 43 + } + ] + }, + { + "metadata": { + "id": "9xpyMoYHrisS", + "colab_type": "code", + "outputId": "6b3aebc4-8b7c-44c7-f2af-48c076f53ab9", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 85 + } + }, + "cell_type": "code", + "source": [ + "years_per_country = centuries.groupby('country').year.count()\n", + "years_per_country[years_per_country < 3]" + ], + "execution_count": 44, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "country\n", + "Greenland 2\n", + "Taiwan 2\n", + "Name: year, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 44 + } + ] + }, + { + "metadata": { + "id": "BB1Ki0v6hxCA", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Point out a story" + ] + }, + { + "metadata": { + "id": "P-Z_7vjBr-7m", + "colab_type": "code", + "outputId": "a3337db2-d4a7-43e3-d825-5e2e035440eb", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2173 + } + }, + "cell_type": "code", + "source": [ + "years = [1918, 1938, 1958, 1978, 1998, 2018]\n", + "\n", + "subset = df[df.year.isin(years)]\n", + "\n", + "sns.relplot(x='income', y='lifespan', hue='region', size='population', \n", + " row='year', data=subset)\n", + "\n", + "plt.xscale('log')\n", + "plt.xlim((150, 150000));" + ], + "execution_count": 45, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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Ba+Ag3rvwOkpyfeR7AmR2UdaN+T0uxg8qYNyAfBwd3BYQEekpFOhZLNqc4I0H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\n+UCPNjex+qv51FWuZo+DDt9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t4USYHE8O0WS0fQa3tE3jdDi5+/C7WVy/mD989geG5g1l\nWeMyKlsqeX3567y36j0G5AzgwWMewD9+PE2rW6dvdey9Jy8ufpGLx1zcfh2nz8NhP/gfigcMxjgc\njDnyWDx+/w7/fGLJGLXRWta2rGVg7kAKfYWdOi4waT9wOiGVInjwwTg8nh2uRUQkGynQu8jw/OHc\ncdgdBNwB5tfMJ5He/KNn1ZFqzn/tfFY1rcLv8vPSqS9RGizd7P6V4Ur+543/YUnDEspzynnw2AcZ\nXTSa6/a7DoCmeBN/+u+fiCQjTDluCgX+Aj5Z/QnlOeW8t6r1GfOVTStZ2rSMsb+4BvfJx5IuyOGF\nxg8YkjuaWEsC4zDEHVE+qPiAl5a8xIUHXcioolH43Tse5gBrwms47cXTSKaT7Fe2H7ceeisFvoKt\nHucdMoRhr79Osr4ed98ynHmbHx8gItKbKdC7QCQR4YOKD7h39r0A3HnYnZsMTKuOVBNOhAm6g6TS\nKVY1rWo9NhlhXcu6zQZ6Mp2kJlLDkoYlAKxqWkVdrI4/HfInrn7var6s+ZKgO8h9x9zHBa9eQEuy\nhT6OPowpGcOKphWMKhzFl7VfkufNI9+bzz+XP8V3J3yXRfWLOKjsGIrSpbzw55kUDwgx4eSBXPv+\ntaRtmvdWvcfU06d2WaDPq51HMp0EYNraaSRtslPHOfx+HP39uPv32/rOIiK9mAK9C0RSEd6veL99\n+52V77Bf3/2Ip+JEkhHcDjc/eutHfFX3FYNyB3H/Mfdz6tBTeX7x84wqGkW/UMdh1RhrpCnRhMvh\nYkTBCL6q+4ohuUNwGAdVkSq+rPkSgHAiTGW4kov2vIhifzF10Toe/GIylw45lbsP/zO1sXpSNsVv\nP/ktM6tmcsyQY9iv7360NMZ45PpPSERTVK1oYuCeheyWtxuL6hdhuvgJnX367EPfYF/WhNdw4Z4X\n4nNq2VURka6kQN8G9dF6Plj9AaubV3PasNPalyQNuUN8f/T3ue796/A6vZwy7BSqI9W8sewN/jLz\nLzxy/CN8VfcVAMsblxNOhLls78v40d4/wuvybvZ+8meVn3H1e1fzj6P+wR8P/iOJdIICXwHXvHsN\nJw49kROGnMArS19hYM5AhuYP5e3lb1MbrSXoDjKxeAyFr/yMVE4/EsffwmkvfptoKorB4HP6qGqp\nwpXy4fW7SERTAPiCbq7Z9xoen/84pw47dYuPv22r0mApj534GMl0koArQI5H08uKiHQlBfo2+GD1\nB1z3fut968/WfMZth91Gvjcfj9PDpL6TePHUF6mN1jLlyynMqprFHw/5IwDhZLi9hT04dzBN8SYe\nm/8Y/5+9+w6Ts6rbOP4909v2lmTTExIIIYSQ0JFeXkCagEFRpIigCEpRUV8RC+EFEaUKCkhTkN4E\npEoPSWghDdLb9r47fea8f8yySUibsDWT+3Nde2XKU36b3eSe55zznFMZquTEMSdu8lzWWt5e+zbJ\ndJLzXzyfk3c6mf0r9+fvn/ydaw+6lpqOGg4aehAX7H4BKZvih6/8kBWtK5jfNJ+L9riIgrxKOnY6\nkqTTyaOfPcafD/0z/1n+Hw6oPACv08tpz5xGub+c6y+8kSWvN1MxKp/SyjwqA/swuXwyPqevx1d9\nK/VrFjoRkd6iQN8Ga9vXdj2uCdd09QkDlPhL+KT+Ey585UIA/C5/V7P1HR/dwa2H3UosFcPlcNEc\nayaWijG/YT5HjTyKIjKDw6y1tMXbcDvc+N1+ztjlDF5Y/gLhRJhpg6Yxr2Ee5046lzJ/GYOCg1jd\ntpor376Sw0cczorWFUBmNLnH4WFE4SicU0bgTMZxLnuCa2ddy4TiCTgdTqraq6iP1FMfqefsd77F\nwyc/vMHVuN/VM/3mA0FbvI017Wuo7qhmUukkiv3Zja4XEdneKNC3wUljT2Jm1Uxqw7XMOHAGRd4N\nR2lPKpvE9PHTmVs/l0unXsrogtE8evyjFPuKu65Om6PN/G3u33hi8RNA5wj1g64l5A6xrGUZv5/5\ne4aGhvLDPX7IkOAQnjzxSdI2TcAV4IDKAza4Fc5i+bj+Y36wxw84eaeTWdm6koumXMSw0DBKA+uu\nhs/wf5v9Oq/Mh+YN7Rqc15HoYHje8I0ml8klCxoWcM5/zgHgwMoDufrAqyn09s1KdiIifUmBvg3K\nAmVcf/D1JNNJirxFOB0bToda5Cvikj0vIZqKku/Jx+lwUuIv2WCbkCdEyqa6nifSCay1NEYb+dGr\nP2J563JmMYthecPYrWw3JpVOIuAObLKeQm8hV+17Ff9Y8A/On3Q+Jf4S8jx5+FwbDjgr9BUyxTel\n63nQFeSpE5+iNdZKsa84q9vHtlcf13/c9XhewzwSqb5byU5EpC8p0LfR1q7u/G7/Fm/1cjlcXDj5\nQlpjrUSSEX61768o8BbQEGnA41w3aYrb6eavH/+VGQfO2Gyg53nyOHb0sRw24jD8Lj8Ok93Efy6n\ni/JAOeWB8qy2354dM+oYHlz4IHWROn405UcE3cH+LklEpFdotbV+0pHoIG3TG4z2XtO+hhvfv5HB\nwcFMqZjCVW9fxUNffau0KmMAACAASURBVEiDybqpPlJP2qYJuoMKdOkOrbYmA5oCfYBpj7dTF65j\nbcsqxpfsTEmwDGMMyVSS1ngrXpd3XSgl4xBuAJsGXwF4Nz/V7Pqaok0k00l8Lt92cftYsr6eZF0d\nrtLSzApxDi1BIP1CgS4Dmv5nHGBCnhBltoDmp95j1j33E25pIpqMMrN6Jue9eB7Xz7qepmhTZuO6\nBXDTHvCnXUkvehaSsa0evzHSyGX/vYwjHjmCOz+5k9ZYay9/R92TrK9nxbfPZNlJJ7P0xJNINfTu\nwjciItsrBfoAk4jFeO3ev7LwzdeY//orvPHPe2mNtXLRKxexqGkRD3/2MPPq54G12Fl3QSIC1uJ4\n5xYiHXVbPf6KthW8V/0eKZvizrl3Ek72zOplqxrDXP3sAp6bW0VzON4jx4TMkq/xpZlpb1MNDSTr\nN700rIjIjk6BPuBs3AVijNngdrV8bz4Yg93lq9A5+Ut4zKHMapy31aNXBCpwOTJjIQcFB3U97o66\nthjT73iXO95YygUPvM+SuvZuH/NzDr8f/7SpAHhGjcJVVtZjxxYRySUa5T7AuL0+Dv72dzHGgcPh\n5MDTz8TvL+Ceo+/h3vn3MrViKiPyRwAQH7I78fPfIB5r5aNINZEtrPD2uWJfMY8d/xgLGhawZ8We\nPTLgzlpLQ8e65v769p67QneVlDD0T38iHYng8PlwlWqAoIjIpmhQ3ABhrSXc0gxAIL+AVDIBGFzr\nrf9trd1oOtb6SD0vrXiJ8kA5UyqmZD9pSjoFySi4A11X+V9WNJFi5rJGfvvMfCYOyed/j5tAScjb\nrWOKDEAaFCcDmgJ9gGhYs4rHr/k11sLJV/yaksphvXeyjnpY9BwsfAb2Og+G7wOe7t3OFU+maI0k\n8bod5PncPVSoyICiQJcBTX3oA0AiGuWNf/ydltoaWutqeP3+u4lHI9kfYFs+lHXUQ9NyeOpC+PR5\n+MepEGna5pq/yONyUprnVZiLiPQTBfoA4HC5KB02sut56fAROF1ZBGM6DfWL4emL4aMHswvmtR9A\ntHm9Y6RgvUVmRERk+6RBcQOA0+ViyjEnUDZiJFjLsIm743Rl8aMJ18HdR2Wuut+/B87+Dwzfe8v7\nrP0ACofBfhfB0tdg8jfAqf5uEZHtnQJ9gAjk5zN+3wO3bSdrIda27nk2V+gTvwa37Qd7nJEJc29+\nZpY5ERHZrqnJfXvmK4Dp/4SKiTDl2zB06tb3yR8CF7wNoQps0UhSYw6jIxwjlUptfV8RERmwNMp9\ne5dKZPrEXT7wbtu87I1rV/PPX16GxXLq//6eilFje6lIkZygUe4yoOkKfXvndEOwbJvDPBGN8vr9\ndxHtaCfW0cFbD95PPBqhMdJIVXsVjZHGXipYRER6gwI9xyVSCeoj9esWdOnkdLsZPG6XrudDxu1M\nW7qDy16/jCMfPZJLXruEhogWQhER2V5oUFwOioU7aFizioZVK6mcNIkfvXcZTuPkDwf9gbJAZi50\nh9PJpMOOYtCYnQAoHzmaumQzs6pnATCndg7tiXZK/CX99n2IiEj2FOg5qHHtGv75y8sAKB81hm9/\nezqXzrqCp5c8zdm7nd21nT8vnxG7TV73PByjPFBObbiWUn8pAVegz2sXEZEvR4Geg5rWrl73uGot\nu3iLARiWv+XpZEv9pTx47IOsalvF0LyhPbJwi4iI9A0Feg4aMWkPBu+0M41rVnHYuRfQ4Exww8E3\nMLViy7e1GWMoC5R1NcuLiMj2Q7et5ahwawvpVApvIIDb6+vvckRygW5bkwFNV+g5KpCv2d9ERHYk\num1NREQkByjQRUREcoACXUREJAco0EVERHKAAl1ERCQHKNBFRERygAJdREQkByjQRUREcoACXURE\nJAco0EVERHKAAl1ERCQHKNClR1lraa6p4rX7/sbi994h2t7e3yWJiOwQFOjSo8ItzTx45U+Z88wT\nPHn972muqervkkREdggKdOlR1lqi7W1dzyNtLf1YjYjIjqNfAt0Yc7QxZpExZrEx5mf9UYP0Dl8w\nyAmX/oKSYSOYePARVIzeqb9LEhHZIRhrbd+e0Bgn8ClwBLAamAWcbq2dv7l9pk6damfPnt1HFUp3\npRIJYuEOnG4P3kCgv8sR6SmmvwsQ2ZL+uELfC1hsrV1qrY0DDwIn9EMd0kucbjeBgkKFuYhIH+qP\nQK8EVq33fHXnaxswxpxnjJltjJldV1fXZ8WJiIhsjwbsoDhr7R3W2qnW2qllZWX9XY6IiMiA1h+B\nvgYYtt7zoZ2viYiIyJfUH4E+C9jJGDPKGOMBpgNP9UMdIiIiOcPV1ye01iaNMRcCLwBO4C5r7by+\nrkNERCSX9HmgA1hr/w38uz/OLSIikosG7KA4ERERyZ4CXUREJAco0EVERHKAAl1ERCQHKNBFRERy\nQJ8vzvJlGGPqgBXbsEsB0N11O7f1GNlsv7VttvT+pt7L9rVSoH4rtfW0XPsZbMvrX3ytP/7+N1VH\nXxwjl38G9dbao7t5DJHeY63NuS/gjr4+Rjbbb22bLb2/qfe24bXZ+hl072ewLa9/8bX++PvXz2Bg\n/Az0pa++/MrVJven++EY2Wy/tW229P6m3sv2tf6Qaz+DbXldP4PubZNLPwORPrNdNLlL9xhjZltr\np/Z3HTsq/f33P/0MZEeQq1fosqE7+ruAHZz+/vuffgaS83SFLiIikgN0hS4iIpIDFOgiIiI5QIEu\nIiKSAxToIiIiOUCBLiIikgMU6CIiIjlAgS4iIpIDFOgiIiI5QIEuIiKSAxTossMzxjxvjGk2xjzz\nhdcPNca8b4z5xBhzjzHG1fn6CcaYj40xHxpjZhtjDlhvn2uNMfOMMQuMMTcaY0xffz8ismNSoMt2\nzxjj7OYhrgO+9YVjOoB7gOnW2onACuDMzrdfBna31k4Gzgb+1rnPfsD+wCRgIjANOKibtYmIZEWB\nLn3GGPMbY8yP1nv+e2PMxZ2PLzfGzOq88r1qvW2eMMbM6bzqPW+919uNMdcbYz4C9u1OXdbal4G2\nL7xcAsSttZ92Pn8R+Frn9u123SIIQeDzxxbwAR7AC7iBmu7UJiKSLQW69KW7gG9D1xXwdOB+Y8yR\nwE7AXsBkYE9jzFc69znbWrsnMBW4yBhT0vl6EJhprd3dWvvm+ifp/HDw4Sa+btyGWusBlzHm8yU3\nTwGGrXeOk4wxC4FnyVylY619B3gVqOr8esFau2Abziki8qW5+rsA2XFYa5cbYxqMMXsAFcAH1tqG\nzkA/Evigc9MQmYB/nUyIn9T5+rDO1xuAFPDoZs5zHZlm9O7Uao0x04EbjDFe4D+d5/z8/ceBxzs/\nePwWONwYMxbYBRjaudmLxpgDrbVvdKcWEZFsKNClr/0N+A4wiMwVO4ABZlhrb19/Q2PMwcDhwL7W\n2rAx5jUyTdoAUWttik0wxlwOfHMTb71urb0o20I7r7gP7DzmkcC4TWzzujFmtDGmFDgJeNda2965\nz3NkugMU6CLS69TkLn3tceBoMgPGXuh87QXgbGNMCMAYU2mMKQcKgKbOMN8Z2CebE1hrr7PWTt7E\nV9Zh3llHeeefXuCnwF86n4/9fPS6MWYKmf7yBmAlcJAxxmWMcZMZEKcmdxHpE7pClz5lrY0bY14F\nmj+/wrbW/scYswvwTmdOtgNnAM8D5xtjFgCLgHd7oyZjzBvAzkDIGLMaOMda+wJwuTHmODIffG+z\n1r7SucvXgG8bYxJABPh6ZxP9I8ChwFwyA+Set9Y+3Rs1i4h8kVk3WFek93UOhnsfONVa+1l/1yMi\nkivU5C59xhgzAVgMvKwwFxHpWbpCFxERyQG6QhcREckBCnQREZEcsF2Mcj/66KPt888/399liMiO\nTQvtyIC2XVyh19fX93cJIiIiA9p2EegiIiKyZQp0ERGRHKBAFxERyQEKdBERkRygQBcREckBCnQR\nEZEcoEAXERHJAQp0ERGRHKBAFxERyQEKdBERkRygQBcREckBCnQREZEcoEAXERHJAQp0ERGRHKBA\nFxERyQEKdBERkRygQBcREckBCnQREZEcoEAXERHJAQp0ERGRHKBAFxERyQEKdBERkRygQBcREckB\nCnQREZEcoEAXERHJAQp0ERGRHKBAFxERyQG9GujGmB8bY+YZYz4xxvzTGOMzxowyxsw0xiw2xjxk\njPH0Zg0iIiI7gl4LdGNMJXARMNVaOxFwAtOB/wNusNaOBZqAc3qrBhERkR1Fbze5uwC/McYFBIAq\n4FDgkc737wFO7OUaREREcl6vBbq1dg3wB2AlmSBvAeYAzdbaZOdmq4HKTe1vjDnPGDPbGDO7rq6u\nt8oUERHJCb3Z5F4EnACMAoYAQeDobPe31t5hrZ1qrZ1aVlbWS1WKiIjkht5scj8cWGatrbPWJoDH\ngP2Bws4meIChwJperEFERGSH0JuBvhLYxxgTMMYY4DBgPvAqcErnNmcCT/ZiDSIiIjuE3uxDn0lm\n8Nv7wNzOc90B/BS4xBizGCgB7uytGkRERHYUxlrb3zVs1dSpU+3s2bP7uwwR2bGZ/i5AZEs0U5yI\niEgOUKCLiIjkAAW6iIhIDlCgi4iI5AAFuoiISA5QoIuIiOQABbqIiEgOUKCLiIjkAAW6iIhIDlCg\ni4iI5AAFuoiISA5QoIuIiOQABbqIiEgOUKCLiIjkAAW6iIhIDlCgi4iI5AAFuoiISA5QoIuIiOQA\nBbqIiEgOUKCLiIjkAAW6iIhIDlCgi4iI5AAFuoiISA5QoIuIiOQABbqIiEgOUKCLiIjkAAW6iIhI\nDlCgi4iI5AAFuoiISA5QoIuIiOQABbqIiEgOUKCLiIjkAAW6iIhIDlCgi4iI5AAFuoiISA5QoIuI\niOQAV38XILI9S7a0EJ03j/iKleQffhiusrL+LklEdlC6QhfphsiHH7Lq7HNIrFxBoqqKRHV1f5ck\nIjsoBbpIN8Q/W0zR6afjKi9n+fTTWfHNMxTqItIvFOgi3ZD/1eMIHX4Y9bf9BdJpEmvW0PbSS/1d\nlojsgBToIt3grqjAO3Ysvt0mdr3m32030ukU0Y52kol4P1YnIjsSDYoT6SZ3RQWV115LZO5c3EMq\ncQ4qZ+2iBbz1rwcYuvMEphxzAv68/P4uU0RynAJdpAe4SkrIO/hgANqbGnn0978imYizev5chu26\nO8MnTurfAkUk5ynQRbop2dhIxzvv4izIxzcx0/RuHOt6s5wu/TMTkd6n/2kkZyWbmkisWIkJBnBX\nVODM7/lm71R7O7XX/YGWxx8HYNBvriL/a1/jtCtnMPOxhxi2626UDh+JTSYxCnYR6UUaFCc5KR0O\n0/C3O1k+fTrLvno84ffe65Xz2Hic6MKFXc8jH8/FYQyDxuzEMRddzqR9DqT17rupuvJKElVVvVKD\niAgo0CVHpaNRwu++0/W8/Y03sNb2+Hmc+flUXPEzHMEgrkGDKPnuuV3N7W6vl9Zn/039TTfT8uhj\n1N1yK+31dbQ11BMLd/R4LSKyY1OgS05y5OVR+oMfgMuFIy+Pom+egTGmx89jXC78kycz+vnnGPXI\nw3iGD9/g/XRHOwDO0lK8Z5zOvT+7mDu+/x3mv/4q8Wikx+sRkR2XOvUkJzncboL77svYl18C48BV\nUtx75/J4cGxmDvfCU04l+tliXOXlLF4wl0hbKwAzH3+InfbeD4/P32t1iciORYEuOcvh9+Pw929g\nukpLGPybqyCVwtZUYcwDWJtm2MRJuDyere6fbGwk9umnOIuLcQ8ejDMvrw+qFpHtkQJdZBs0dsRJ\nptJ4XU4KAu6s9nEGgwCUuN2c/afbCbc2UzhoCL5gaIv7pdraqL32WlqeeBKAYX/7K6EDDujeNyAi\nOUt96CJZqm+P8f0H5rD3jJe57oWFNHVsflrXVGsrHTNnUn/HHcRXrsSm03j8fgoHDWbIuF0I5Bds\n9Xw2FiM85/2u5+GZvTNSX0RygwJdJEurGsO8u7QRa+H+mStpjyU3u21syRJWnvkd6v54A8tP+zrJ\n+vptPp8jFKLs4ovA4cBZVEThKV/rTvkikuPU5C6SpfI8H26nIZGylAQ9eF2b/zwcW/Qp3nHjMCef\nBlhIp7f5fA6fj9ChhzL2tVcxxuAsKelG9SKS6xToIlkqCXl47uID+XBVM/uMLqE05O16Lx2Nkmxo\nILFyJZ6ddiJ0+GHUTtmPX76yCmMMM0yQ0dZu861zzkAAZyDQ09+KiOQg0xuTbfS0qVOn2tmzZ/d3\nGSKbFVu8mKUnnQyJBK4hQyh49CmOv+1dqlujAAwt8vP49/ejLM/Xz5VKN/T8RAYiPUh96CI9oOOd\ndyCRACC5di3pdJrG9QbN1bXFGPgfnUVke6ZAF+kBwX33BXfmNjbXkCEETJqfHbNz1/u/OHYXgh71\ncIlI71GTu0gP2KAPfcwY3OXltEUTtEYyI+Hz/S7yfNndty4DlprcZUDTJYNID3D4fHgqK/FUVna9\nludzK8RFpM+oyV1ERCQH9GqgG2MKjTGPGGMWGmMWGGP2NcYUG2NeNMZ81vlnUW/WICIisiPo7Sv0\nPwPPW2t3BnYHFgA/A1621u4EvNz5XGS7l2pro/2NN6j+7e+IfvoZtnPUu4hIX+i1QXHGmALgQ2C0\nXe8kxphFwMHW2ipjzGDgNWvt+C0dS4PidmzJ+nqaHn4Ed3kZoUMPxVU0MBt1YkuXsvSYYwFwBIOM\nfu7fuMvL+7kq6UEaFCcDWm8OihsF1AF3G2N2B+YAFwMV1tqqzm2qgYperEG2c6mWFtb+/Bd0vP46\nAIOu+jVFX/96t46ZDodJNjaSamzEPXQoruKeWSs91dq6wTlIpTZfQyRCqqUFm0zizM/HmZ/fIzWI\nyI6rN5vcXcAU4DZr7R5AB19oXu+8ct9kE4Ex5jxjzGxjzOy6urpeLFMGMptMkqyp6XqeWL2m28eM\nLVvGkiOPYvlpX6fmd78nUd9AoqqKRE0N6Wj0Sx/XM2IEhadPxz1iBIN/+1scW1i7PDpvPosPP4Il\nhx9By1NPk47FvvR5RUSgdwN9NbDaWjuz8/kjZAK+prOpnc4/aze1s7X2DmvtVGvt1LKysl4sUwYy\nZ1ERQ66ZgWf0aALTplH0rTM2u61NJknU1ZGord1iMIffe69rsZSOd94hVV/H4kMPY8nhRxCZOxdr\nLTadJr5qFY333Et0wYLMFfdWuIqKKL/0UkY+cD/5xx2LM7Tp9c6ttTQ/8TgkM/eotzz+GOmOjq0e\nX0RkS3ot0K211cAqY8zn/eOHAfOBp4AzO187E3iyt2qQ7Z9xOPCOG8eIe++h8sY/b7FPOrZ0KUv/\n5xgWH3Y44VmzNjsoLe/ww3F29sMXn3M2bS+9DNZiEwkabr+ddEcHyfp6lp96GjUzZrDslFNJNjZm\nVa8zFMJVWorDt/k5240xFJ54ErgyPV4FJ38NRzCY1fFFRDantyeW+SHwgDHGAywFziLzIeJfxphz\ngBXAab1cgwwAyaYmbCKBcbm2uc/aOJ24Sku3uI1NpWi8627S7e0A1N10M76JEzc5gM5dWcmop56E\nZBLjdlN99Yyu9/xTpmB8PmhtJdXcnHkxlSJZVY27ogLj7pmJYny7TmDsSy929aE7vN6t7yQisgW9\nGujW2g+BqZt467DePK8MLMnGRqp/81vann+ewH77Unnddbh6eG1v43QSPOAAWp54AoDA3ntt9irZ\nOBy41+vGGfSLX5B36KE4gkH8k3fH4XKRDgYp+e65ND7wD4J77YXFkmpp2eoHi2w5/H4cfn+PHEtE\nBDSXu/SB+KpVLDniyK7no//9LN7Ro3v8PKmWFhJVVaTDYTyjRnX79rbw+++Tbm8nvmIFHXPmMOSq\nq3AWFPRQtbId0m1rMqBpLnfpdcbnw1VeRrK2Dkd+Po7NDBbrLmdBQY8Grnf0aDpmzwaHk8G//KXC\nXEQGNF2hS6+z1pKsrSX26ad4x47FVVaGcfXvZ8l0NEpsyRLaX36ZvKOOwjNqFA6Pp19rkgFPV+gy\noCnQZYeUqK5m8RFHQiKB8fkY8/xzJNaspf211yg44Xg8I0b02AA4yRkKdBnQ1OQuO6R0NAqdt7XZ\naJR0LMaKb30L0mma/vGPjaZtjSSStEeTeFxOCvwKehEZeLR8quyQnIWFFJ97Du7KIZRefBE4HF2T\nzaQ7OromfQFojyZ5+qMqjr/5LX7+2Mc0tGtWNxEZeNTkLjusVHs7NhLFBPzYeJz6W26h/bX/Uvqj\niwlOm0ayvh53eTnN3hDTZrzC5/9U/n7WNA4er0VXdkBqcpcBTU3ussNyhkLw+Yj7YJCyH19Cyfnn\nQzrN8lNOJVlbi7O0lBGPPkKBz01zJNNEXxrSJDAiMvAo0GWHl6ipofXpZ/CMHYN/jz1IrF5Nsjaz\nxECqvp5UVRWPf38/7n13BfuNKWFYUaCfKxYR2ZgCXXZoyYYGVn3vfGILFwIw7G9/xTt+PK6yMpJ1\ndTiLi3EPGcKoshBXfnXXfq5WRGTzFOiyQ7PpNInVq7uex5cvJ7j//ox67FHia9fiHjy4x6Z7FRHp\nTRrlLgNSMpWkNlzLwsaFNEQaevz4qdZWEjU1GIeDwdfMwFlYiH/yZPKPOgpjDK6yMgK77467vBzj\n0D8TERn4dIUuA1JdpI4TnzyRcDLMlPIp3HDIDRT7tm2Vts1JtbXReN/91N90E+5hwxjxwP2Mevqp\nzKpu27gSnIjIQKFLDxmQlrQsIZwMA/B+7fsk08mt7JE9G41Sf8stACRWrSL87kzcZWUKcxHZrinQ\nZUAaVzSOwcHBAJw09iS8zu7dKpZqbSW6aBHhOXOw1uKbNCnzhsOBd+fx3S1XRKTfqcldBqTyQDn/\nOOYfxNNxAq4ABd7urXTW8fbbrPnRjwEo/s6ZDLv5JiKfzMMzYjiuck0SIyLbPwW6DFilgexHlycb\nGrDxOMbr3ajp3KbTtL/5Ztfz8HuzKDnvPPIOPqjHahUR6W9qcpftXrKhgVXfPY/FhxzKmssuJ9mw\n4ah443BQ/O0zceTlgctF6Q9+kHksIpJDdIUu2734ypVE588HIPz226Ta2nDk55NubgaPB1dBAd7R\noxj97LNgLc78PBxaGlVEcoyu0GW7566o6Fq73BEK4QiFiMyZw/JvnsHan/yEZH0DxuXCXV6Gu6Ic\nh9/fzxWLiPQ8XaFLr7LJJDaZxOHz9do5nMXFjHryCcLvf0Bw770gnWbNJZeSamwksXIl7a+9SuEp\np/Ta+UVEBgIFuvSaZGMjjffdR/yzxZRdegmekSMxZsMVKBM1NTQ/8ijeMaMJ7LMPrsLCbT6Pw+fD\nO3o03tGjM+dtaMBVXk6qsREA16DB3f9mREQGOAW69JqOt96i4ba/ABBdsICRDz6Iq2zdyPVkQwOr\nzr+A2IIFAAy97TbyDjm42+d1lZQw7C+3ZT4ojB+Hf6IWVRGR3KdAl15jk+tmd7OJBBa74fvpNMnq\n6q7niTVreuzc7kGDKLvwBz12PBGRgU6D4qTXhA46iKJvfpPA3nsz7I47Nro/3JmfT+Ufr8c1ZAiB\nffYh/+ijtni8dCxGoqaG+MqVJJube7N0EZHtjrHWbn2rfjZ16lQ7e/bs/i5DvoR0NIqNx3Hk5W3U\nfw6QjsdJt7SAywXBIJH2Vmw6jTcYwusPbLBt9NNPWX7Kqdh4nOJzz6X0/O/hDIX66lsR2fgXWGQA\n0RW69CqHz4czP3+TYQ7g8HhwlZXhKiqidvkS7vzhufz1wnNYMutdksnEBtu2v/YaNh4HoPXpp0lH\nIhsdL9XeTqK2lmTngDgRkR2FAl2y0hyOs7opTE1rlFS651t1wq2ZK/OJhxwB1vLBC8+Q+EJghw45\nBGdZGYFLLifwx5uwgWDXe8n6eupuvpmm++4n9tlnrLnsso1mjOuuWDJFMpXu0WOKiPQUDYqTrWqP\nJrj7reX8+eXPKPC7eerC/RlREtz6jlkKtzTz3C1/pHrJZ+x90tfZ89gTCRWX4P7CveueESMoevp5\nfvXMAla+1czV5XF29fkw0QjV11xD2zPPAlB81ndwlZaRrK3FVVLSIzWuaQoz47mFDC7wcf5BYygJ\ndW/1NxGRnqYrdNmqcDzFPe8sB6AlkuDVRbU9evyapYtZ/tH7RNvbeP3+u5h63ElM2u8rODq7LFOt\nraQjERweD/9ZWMdzn1Qzb20rF9w/h8ZwHJJJUrXrakrWN+AoKMDZQ+ubN3bE+OE/P+SZj6v46xvL\neGTO6h45rohIT1Kgy1Z53U4O36UCAI/Twb6js18FLRv5ZeuWL512zPGwYCFVP76UhtvvIL52Lasv\nupia319NsqmJkpCna9uioAenMTgLChj066vw7rwz/smTKf3B9yk5+6weC3RrIZVe19Se7IUuBxGR\n7tIod8lKY0eMurY4+X4XRQEPPrezx44di4RpWrOa6iWfMWG3PVhy1NGQyAyIG3L9H6i/+Wbiy5ZT\nfOklpI4/mddXdPBZbTvnHjCKwYWZedmttZmZ4Yzpuj0u3NpCOpXCFwzh8ng2e/5srGjo4NdPzaci\n38tlR42nVE3uOyKNcpcBTX3okpXioJfiYO+EmNcfYNDYcQwaO45EdTWkUl3v2UQCHJ0fHrxeFj33\nKF896TSCew3f4BjGmA36y9ubGnnyut/RXFPFURdczMhJU7Y51OvbY8STaXxuJyNKgtx0+mRcTkeP\nfpgREekpanKXAaM9lqDBeCm/7jq848dT+I1vENxnH7w7jaX4oh9ScOih7JxykP54LsmWli0ea/F7\n71C95FOi7W385/abiHa0b1Mt9W0xzrp7Fvtd8wpXPPYxDR0xQj63wlxEBixdoUufS6RS1LfHWdMU\nYWhRAJ/bQWHAw8qGCMfe9DbH7lLGKT+/lqnjB+EKBSi58ko61q6l6tLLiH70Ec3A0NtuJe+QQzZ7\njpKhw7oeFw2uxOHctiCua48xd03mQ8ML82r45bET6MGB/SIiPU6BLn2uti3O4df/l0gixa5D8rni\nf3Zh/KAQi+valHYwuAAAIABJREFUsBaemV/Hi5828MaE4XgbG6ltDhMI5BNfurTrGNGFi7YY6GUj\nR3PalTNoqlrLmD33IpBfsE01Fgc9FAbcNIcTjCjJfOgQERnIFOiySTaZJNnQQKK6Gk9lJa7SnhvZ\nvqy+nUgi008+b20rbpfhxfm1/M/ECnYelMfi2nZ+/dUJ5HvdmIQLRyTC3xfGmf6TK+j4zZW4hgyh\n8MQTtngOXzDEsAm7MWzCbl+qxtKQl+cv/gqrm8KMKAlSlqdBcCIysCnQZZOSDY0s/erxpFtb8YwZ\nw4h7/t5joT6+Ip/RpUGW1ndwyp5DWVDVxk5lIYqCXu4/d2/SaUthooP2h/5JOh6j4uij+UYetCVL\nGPHii7hcTtxfohZrLXVtMTpiSfJ8bkq3ENJOh2FQgY9BBb7NbrO+ZCJBS00Vyz/+gFGT96SgYhBO\np/55iUjfyep/HGNMGfBdYOT6+1hrz+6dsqS/JWuqSbe2AhBfsqRrDvWeUJbn5aHv7Us0kaKuLUp7\nLMnEynwa2mMkU5Y8Z5rGv9xO0333ARBbuJDyn/yEQcEgzkBgK0ffvLr2GCfc8hZVLVF2qyzg7rOm\n9djtZ9G2Vu7/2Y9IJuK89dD9nH3DXwgV98wsdSIi2cj2EuJJ4A3gJSC1lW0lB7iHDMEzdizxxYsJ\nHXUkxu/v0eN/3oQ9rDgT0PXtMc69ZxYfrmrhzlN3Yadly7q2ja9chXG5uhXmADUtUapaogDMXdNC\nJN5zv8qJWJRkIvOhJxGNkEwktrKHiEjPyjbQA9ban/ZqJTJg2HSadCjIiPvvw4bDGL8fV1FRr55z\nTVOED1dlRpX/4c3VPHr55cQWLcImEgz65S9w5ud3bVvXFiUcTxHwuLapb3tQgY/KQj9rmiNMHlaI\n39Nzt6D5gnlMPuo4Fr3zBhMPPhxvQEPiRaRvZTVTnDHmd8Db1tp/935JG9NMcX0n1tHB0vffY+Hb\nrzP5yGOp3GVXPL6Nr86ttSRra4l9+hnencbSFioknEjjdTk3CNl0OEyqtRWMwVlYiMO76QCuboly\n6PWvEY6nGF4c4MkL9iEUzdw77ioqwrgynz3r2mJ8+66ZLKhqY8LgfO45e69tCvXa1igd8RR5XtcW\n+9C/jFi4g2QshsvrVaDnJs0UJwNatlfoFwM/N8bEgASZX2xrrc3f8m6yvYm0t/Lvm68HYNmHc/ju\nzXduMtCTdfUsP+VUknV1BH93Dbcykgdnr2ZokZ9HL9iPinwfNpmk492ZrP7hDzFOJ8Pv+TuBPfbY\n5HmLQ25evOQglta1M74ij6I8H+RtfN72WJIFVW0AzK9qpSOW3KZAL8/PbpDbl+ENBBXkItJvsrq5\n1lqbZ611WGv91tr8zucK8xxk11uExFrL5lpwbDRCsq4OADN+Fx6cnVmBbHVThPlrM4Pp0h0dNNx1\nF6RS2HicxnvvI72ZwXUep5PKQj8H7lS2xdANep2MLMn0pY8qDRLwauY2ERHYhtvWjDFFwE5A1/+2\n1trXe6Mo6T/+vAIOO+cCFr39BpOPOg5fMLTJ7RyhEKHDD6f9pZdwhNvZc3gRc1Y24Xc72akis4/x\n+8k77FAind0leUccjqObi6SU5/n41/n70hZJkud3UZ7Xe1fcIiLbk2z70M8l0+w+FPgQ2Ad4x1p7\naO+Wl6E+9N6TCoczt6d1LkPq8PlIJZMkYlHcPj/OLUyZmmxqwsbjGI+HZneAquYIZXk+ioNuPK7M\nfqmWlsyVvMuFq7h4g8FtPaEtkmBxXTvz1rZy+C4VWd83LvIlqA9dBrRt6UOfBrxrrT3EGLMzcHXv\nlSV9wSaThN+dyeoLL8z0cf/9bgJ77onT5cLp2vSV+frWH/leCpu8p9tZUICzYNumXd0WK5vCnHTr\n2wDc/dZyHvrePpSGvLRE4sxe3sT7K5uYPm141+1xIiK5KtsJqqPW2iiAMcZrrV0IjO+9sqQvpDs6\naLz7bkinsYkEjffeSzoW6++ytsmK+nDX45WNHaTTmRanZfVhzrlnNre8uoTpd7xLXVu0v0oUEekT\n2Qb6amNMIfAE8KIx5klgRe+VJX3B+P3kHXccprNfO+/IIzd7W1lLOE5ta5TWaHYTpiTr6ogtW9Y1\ncK63TBtVzD6ji8n3u7jm5EmEvOtub/tcfXuMrXcsiYhs37LqQ99gB2MOAgqA5621PTcf6BaoD713\ndDQ30bhmFfklZfjSFlcotMk+7saOGFf/eyHPf1LN9GnD+MGhYykKrDe4rb0WUgnwBMFfSLKujuVn\nfIvEihV4Ro1ixH334iotJdLWRiqZwOPz4+nBmecaOzJTxoa8LgKdgd7QHuM3T8/n4zUt/O+xu7Df\n2FKtZS7dpT50GdC2ZZT7FOAAwAJv9VWYS+8ItzTz2IwrqV2+FJfbw3duuI2CzQxYa+pI8MiczG1p\nf3tzGWfuN5KigId0NIqJ1GHuOQaaV8JXLof9fkiqo4PEikwDTnzZMtIdYcKeFl6842ZWzf+YfU76\nOrsdehTeYM/cs10c3LhVoSTk5bcnTSSeSJHvXzdIT0QkV2XV5G6M+RVwD1BCZvzT3caYX/ZmYdK7\n0qkUtcsz64snE3Ga1q7JvJ621LZFqWmNEo4lAQh6XV3rgef7XHhcmcfJujpSHz+bCXOAN66HRBRn\nKIRn7FgAvOPH4wgFaVyzmsWz3iHW0cF/77+LeDTSVYtNpUg2NGRmlOtB+T43pXk+hbmI7BCyvUL/\nJrD7egPjriFz+9rveqsw6V1Oj4c9/uerfPDc0xRXDqV02AiiLS2kw1HqGjr4v3dqOG3vERwxoYLi\noJtnLzqQ95Y2st/YEkqCmeb28PsfEBq/GzickE5hK6diHE5cpaWM+PvdpMNhHIEArpISgokYxjiw\nNk2goBCHI/OhwCaTROfPp+qXv8Q9pJLBv/ttj669LiKyo8j2PvRXgZOstc2dzwuBx3Qf+vYt2t5G\nIhbDYvnw+WeYPG4iVd//AcbpJHTrHfxqbpQZJ0/a7NSq8TVraLrnTkpOPQYTrcExYk9M/qBNbxuJ\n0Lh2FasXzGenvfYhv6wCY0ymv3366STWZFoIyn/2U0q+850e+f4+n5Wuu5PZiHRSH7oMaNleobcA\n84wxL5LpQz8CeM8YcyOAtfaiXqpPepEvlIc3EOSVv99Onj9I0y23km7LzJOeuvN2vnbWpV1N7Zvi\nHjyY4u9egE0moWIcZguTxnj8fgaNGcegMeM2fMPpxFlc3BXorvLy7n9jZLoDav/0J2wyRfmll+Iu\nL+uR44qIDFTZBvrjnV+fe63nS5H+YBwOQsWltNXWMHT8eHj3XQA8u+3GARMGk+dzb3Ffd1n3gtJV\nXMzQm2+i8d778I4aSXC//TZ4vzWaYMHaVj5c1cxxuw+hsnDro+PTsRg1f7ie1iefBMDG4wy5+vc4\nenhNdxGRgSSrQLfW3vP548453YdZaz/utaqkT+126JEseONVfAfvQmivaTjcHny7TcQV6JtpVN0V\nFVRcftkm31vdFOHrd2Q+ZNz37goe//7+2a2ulkxu8Hhbb88UEdneZBXoxpjXgOM7t58D1Bpj3rLW\nXtKLtUkfCLc0k4hF2Xn/gwgWFsG4gTUBYHXzutHw1S3RrILZ4fVS/tOfYBNxbCpNxS9/gTOgqV9F\nJLdl2+ReYK1t7Vyk5V5r7ZXGGF2hb+fCLc08e+MfWPnJhxQOGsL0q/4vE+oDyO7DCjlilwo+XtPM\nz4/ZpWsmuK1xl5cz+JprwFqcW7nfPdncDGmLs6gQYzTuSUS2T9kGussYMxg4DfhFL9YjfSgRi7Ly\nkw8BaK5eS3NNVbcDPZlI0Fy9liVzZjJ6yl4UDR6Cy73hKPN4NEIiEsHhduMP5W3xeCUhL9edOol4\nMk2e34XfnfVcSFldlcdXrmLtz36GTSQYMuNqPKNHYxzZzogsIjJwZPs/12+AF4Al1tpZxpjRwGe9\nV5b0BafHS0FF5jYzj99Pfln3R5hH21p54OeX8OY/7+UfP7+ESNuGk8XEwmHmv/Eq9/zkh7xw6w2E\nW1u2eszCgIfyfN82hXkilaK2NUpj++YnNEw2NrLm0kuJvP8+0blzWfW980k2NmZ9DhGRgSTbQXEP\nAw+v93wp8LXeKkr6RqiwiOlXXUtzdRUF5RUECrrf3J5MxEnGY+s93nAxl3g0zMt/uxWAJXPeo3rJ\np4zeY1q3z7u+RCrFnBXN/PihDxlc4OO2M/akIn8TA/zSadKRdX306UgE0ho8JyLbp2ynfh1njHnZ\nGPNJ5/NJ2U79aoxxGmM+MMY80/l8lDFmpjFmsTHmIWOMZv3oR6GiYobusit5JaU4nd2fItUbCLL3\nSacRKi5h2glfw/eF/muHceDPW3e/eqiopNvn/KKmjgSXPfwRVS1R3l/ZzMOzV21yO2dREUNmXI2z\nsBBHKETlH6/HWVTY4/WIiPSFbGeK+y9wOXC7tXaPztc+sdZOzGLfS4CpQL619jhjzL/IzDL3oDHm\nL8BH1trbtnQMzRSXnUhbK631dXh8PgIFhXgDPbP4Sbbq22JEEil8LkPAxnC5PXi/0I9t02maa6uZ\n9+pLDJ0wkUFjxuELhXq0jqaOOBc8MId3l2aaz2/5xh4cO2nIJre1ySTJpiYAnAUFmlVOtkQjJmVA\ny7ZTMmCtfe8LI4CTm9v4c8aYocCxwO+BS0zmAIcC3+jc5B7g18AWA122Lh6NMuupR5n11KMAnHzF\nVYyavGefnb++LcY598zio9UtTBpawJ1nTqMssPH94sbhwBcMkV9ezqfvvoUvlEeZf/QGrQOpVJoV\njWEe/2AN+48pZdfK/C1OcPNFRUEPN07fgyc+XMuwIj/7jN58K4BxuTaYHKcuXEc0FSXoDlLsK876\nnCIi/S3bQK83xowhM+0rxphTgKos9vsT8BPg86HMJUCztfbzDwOrgcpN7WiMOQ84D2D48OFZlrnj\nSsaiLP/o/a7nS99/r08CPdXaSrK+nrZgCR+tzgxw+3h1Cx2x5GYngFnx8Qe8eMfNACye9Q7fvu5m\nQkXrwrO+I86Jt75FayTJTa8s5sUff2WbAh2gPN/HeV8ZvU371IXrOP3Z06kJ17DP4H34v6/8n0Jd\nRLYb2Y5y/wFwO7CzMWYN8CPg/C3tYIw5Dqi11s75MoVZa++w1k611k4t6+b0ormmLdbGvPp5vLTi\nJRoiDQB4AgH2OvFUjHHg8fvZ/fBjer0Oay1tr7zC0mOOxV29lmHFmalVhxb58bkddMQ23Yjj8njX\ne+zZ6N7vZCpNa2TdvjWt0V6ofmPLWpZRE64B4N2qd4km++a8IiI9YYtX6MaYi621fwYGW2sPN8YE\nAYe1ti2LY+8PHG+MOQbwAfnAn4FCY4yr8yp9KLCme9/Cjmdh00LOfuFsAA6sPJAZB8ygwFfA6CnT\n+O4td2EcDvz5Bb1eh43FaH/pZQBiV1zGv276C83+fPL8bn7/7wX43E5+dvTOlIQ2vFKv3HkCB55+\nJjXLlrD/aWcQKCgknkwTSaQIeZyEvC4uOWInbv/vUqaNKmaXwZtf9KUnjcgfQb4nn9Z4K+OLxuN1\nZjHFrIjIALG1JvezyITwTcAUa21Htge21l4BXAFgjDkYuMxa+01jzMPAKcCDwJnAk1+i7h3a/Ib5\nXY8XNi4kns7ca+3x+fH4+m4BEofPR/FZ36H99dfB5aIwGSZUWMYRf3qT6tbMrWt7jyzmlKnDNtjP\nn5fPtOO/RjqVwul20xyO8+j7q3lpfi3nHjiKfceUcNb+o5i+13DcDgdFwb4ZqFbiL+GJE56gIdpA\nmb+MEn/Pj8AXEektWwv0BcaYz4AhX5jq1QDWWjvpS5zzp8CDxpjfAR8Ad36JY+zQjhp5FI98+ghr\n29fy071+Sr6nb65gN8U3cSJjXnmZVGMj9bfehm/yZK4/+gC++a+FAOT5N/0rZhwOnJ0zslW3Rvnt\nMwsAeG95I2/+9BAGF/i3ud+8u1wOF2WBMsoC6uIRke3PFgPdWnu6MWYQmVnijv+yJ7HWvkbnkqud\nk9Ls9WWPJTAoOIi/H/130jZNyBPC6+q/pmGH10uqtZWV3zmLVGMjbc8/z2533sn3DxlDWcjLvqNL\niHYkMAa8gU0HtHO9PnTdFyQi8uVsdZS7tbYa2L0PapFtsKXm4PpIPdUd1VQEKijxl+Aw2z43eTyS\npLG6g/pV7YycVEqocPMfGgxgE+vNCJeIc9kR42lLtLK0aT5rmqqYWLA7pckSgvkbH6c8z8uMk3fj\nP/NqOPfAURRuJvhFRGTztjixjDHmX9ba04wxc+m8Ze3zt/jyTe7bTBPLZK8+Us+Zz53JyraVlPhK\nePirD3+pJuS6lW386+pZABQNDnDij6cQyN90X7ZNJIgsmE/d9TfgmDCO5q8dxLChuzKrehaX/Dez\nwu7+gw/gstG/YOzYoZs8RiptiSZSBDxOrXgmA5V+MWVA29oV+sWdfx7X24VIz4gmo6xsW8m0ir04\nddh0iDngSywF3lq/bo7zltrIFtchN243kTGVvPb9vamK1/PQOxfy0LEPMat6Vtc2nzTOxT1p8/8f\nOh2GYJZLowIkm5qIfPgR6XCY4L774Cped794Kpki0p4k0honVOTFn7f5QXXheJL2WBKHMZSGNKpd\nRLZfW+tDr+r8c0XflCPdFXAHOGvCWRxXcAqzHljLm/krOPLcEMECL+GWZqy1BAq2vu734LGFDBlX\nSMPqdg74+k54fFsJW4fh6ZqXWdS0CJ/TR4G3gOk7T+fZZc/SGm/lexPPpzCUR0NHjHgyjdfloDiY\nXYCmo1FSbW0YY3CVlgLQ8vTT1F49A4DC00+n4ieX4/BnRvi3N8d58KqZJBNphu5SzJHnTMAf2jjU\nI4kkLy+o5fJHPmJ4cYB7z96bQQWbWMRFRGQ7sLX70NvYsKm96y0yTe79N7xaNqnYV8zZY8/juRvn\n0VwTprkmzCf/XcPEg4p5bMaVpBIJvnrJFZRUDtvicQL5Ho4+byLWWtJJS83yFgorggTzPRjHxh8G\nSvwl/OWIv7CidQWVoUqKfEWU+kt54oQnSNkUQXcQUj5ueH4h989cyd6jirj1m3tudI/6F6WjUTre\neos1l12Oq7yc4Xffhbu8nNj8dbfuxRYtwsZi0Bno9SvbSCbSAKxe2Eg6tenWhbZIkv998hOiiTSf\n1rTz/LwqvrPfqC3WIyIyUG1xtJS1Ns9am7+JrzyF+QAQ74CW1dCyJvO4k8/jJVC47oo0r8TH3Ff+\nQ+2yJTSsXskrd/2FaEf7Vg/vD3mwaXjp7vmsXtDERy+vJNy2+fXFS/2l7FmxJ4OCg/A4PTgdTsoC\nZVQEKvDWNNNxy418z1fDrw4ezsxlTaxt2fpMbKm2Nqp/fRU2EiGxYgVN//gHxuWi9IILcA8dirOk\nhIorrsCRv+7XsWJUPsHO73/Xr1TidG3619zlNIyrWLcwzM6D9CstItuv7DstZaustTREM1OxlvhK\nNmrWTts0zdFmXA4X+d5uhkc6BcvegAdPB2Ng+j9h7BHgcOALujn8OxOY/+ZaQkVeRu5Wypx/x7p2\nzSspw+nM7kefTqaZdtwoPvjPSvJL/djNXO2GW1tYNW8uDqeDyp13JbDeTHWphgZWfPObJGvrADjy\n3n/y1wIvpVlMGGNcLtwjR5Csy+zrGzceAPfw4Yx88J9Ya3EVFWEc60I7VOTj1CumkUqmcXtd+IKb\nHjVfHPRyyzf25I3P6hhREmRsec+u+iYi0pcU6D1oResKLnrlIgBuPPRGRhaM7HovlU7xWdNn/OKt\nX1ARqOA3+/+GUn8pHfEOFjYt5M3Vb3L82OMZnjccpyOLdcnjHfDe7WDTmU6R926H4fuBL7MOTrDA\ny7Rj1zUfT/mf4wkVlZCMx5hw4CG4fev6iuOpOLFUjJA7tHHfujG8cu8CWuszV9NlI/LYZd/BG2zS\nHG5kzbKFfPjsY1R/9imTjzqOA79xZtesdTadxjqcBL/yFZJVVXg6WrjvnL2zmgHOVVTE0BtuoPW5\n53APGYJ/zz07y1rXn74pwYLs+ufL8rycPGXTI+9FRLYnCvQeEklE+OOcP7KsdRkAf5zzR6458BoC\n7swQ8+ZYMz954ycsa1nGp02f8thnj3HepPNojDVy1vNnYbE8tOghnjjxCcoD5Vs/odsPE06AJa9k\nrtCnfQ/cmx/OHsgvYPKRGy/Y0hRt4u55d7OgYQGX7HkJ44rGbfCBwuEyrH+3jqOz/zyRSuN2OmiI\nNPDbd39LdbiaK757GY47H2LNwnkk4/GuQHfk5+P952M88UkNe40uJVASYHjIi8eVxQcXwFVaSvG3\nvpXVtiIiOyoFeg9xOV2MyB/R9Xxk/kjcznVNvU7jpNhXzLKWTOCX+TP3hrfGW7Gd4w7bEm2kbTrL\nMzpgp6PgB+8Rdhaw9OO5RBY9wYSvHEqwsGizeyXSCWLJGEF3EGMM79e+z92f3A3A+S+dzyPHP9JV\nG0Agz8NxF07inceXUDQ4yJCdi3jovZW8vbSBy48az4trnuLlVZkFWv73/d/wv0d9H3/ChcfvJ522\nOByGxoThlDvnUNceg5eX8PD39iUcT1Hu81AfT7CmOcrOg/K2OkBOREQ2T4HeQ9wON9+d9F0mlEwg\nlopx0NCDcDvWBXqhr5Brv3ItDyx4gMpQJYcMOwSAIcEhnDbuNN5e+zZn73Y2IXeW/bj1C+GBU2g9\n+z+0JCN4Rlaw9o0lvHTnrRx9wY/wBoLUhmv5tOlTRheMptxfTnuinQcXPcjipsVcPOViHMbBmIIx\nVAQqqAnX4HK4MHbDJndjDEWDghxx9q44nYYP17Tw08fmAtARS3LMfoVd2+Z78xkxcXe8hPjLmyuo\nbY3x/+zdd3zU9eHH8dfndu4uOyFAMGxBBQFBBXHvPYq2Wme1tUNrW7XV2mpt7a9DbbVWbZ1Vq9Zd\nd917i4ALZO+Vndzl5vfu8/vjYiDsFQLH++kjD3Pf+ckg7/t8vp9xwUGDsBbq21Y8w1/emuCrhc30\nr81ghxRy5gOfcOCQSm745sjVmuHr4/U4WYcCTwHF/q5fQU5EZHulQN8CYukY81vn8/Gyjzmo5iCq\nw9VrnG61R7AHPxv9s07bSgOl/Gz0z/jhyB8S9oYJeDZgHLSThDevhUGHMi/dyHdf+h7JTJJrRv+G\nwk+9ZByHulgdZzx/BkvblhL0BHnmpGeY1zKPW6bcwt8O+htXvnclnyz/hKFlQ7n10Fu57dPb+OGI\nH1JWULbGW3r9uebxcp+H5783jkjK4fevTGevqrH8Ys9fsDiymO8M+w49QlXc+fYcrn9xBgAza6Pc\nfNpI/vSN4dz4ykxG1ZRQHPTSLxxg4vNTGTcy9xz8k3lNpDOdWyfqYnWc9cJZLIos4oxdzuAHI36g\nUBcRWQsF+hbQlGzitOdOI2Mz3PH5HTxx/BMbNd1q2BcmzPpr5s3JZqY1TCOdTTP8oMspnv4ij0x/\nhLiTm9Xt33P+w9+O+AsF4UKaYktZ2rYUgJgToy5W1/Emo9hfzCfLPwFyy6/G03EqCyp5ef7LfL/k\n+2u8dyySIhVzCGcNHz48m2Qszb9+sgc3TPkzUaeF3+3zO4oDubBtiq0Y2hZNODhpy6H9K9j3B7nw\nTkXTfPbUXHoOKKYoDMcM68GY/hWrzRT3ZcOXLIosAuD+afdz9tBzSNe5CZf619pzXURkR7Xxq3bI\nahrjjWRsBsiFrpN1tvg9sjbLM7Oe4fyXz+eCVy/gX/P/R2bYN9i/z/4dx4zrNY6SwnKMy0XQE+T4\ngbkF8kZUjiCSjhBNR7lk9CX43D76FOZ6dlcU5EL2ga8ewOv2rrFlIR5N8eo9U3ngNx/w1I2TOeDb\nQ2hrTjFv2hJmt87gvSXvkcyuaFI/Z5/+HLFbFaP7lnLDN0fw/r+m8dCvP+CDO6dS5vHQozDAvif2\nZecxCd69+wbO79XIycPKVwv0QSWD8Ltzz9VHVIxg+awID//+I+Z+WrfOqWhFRHZEqqFvAdWF1Rze\n93A+WPoBZ+16Vm5WtC3MyTp8Wv8pADuX7swBfQ6g0etnTNWePHnCk8TSMXqFe9GUaqY1HaHYV8zP\nx/ycC0deSNyJ05RsIlQQYlj5MLxuL3cefifL25ZTHa7m3cXvcumYSzveAKwqk86y4MtGAOKRNE1L\n2wiW+OhVU8rQJUO5Yu8rKPWv6IhXWejn+lNG4GQs6foEi2c0A7BsdisZJ0u4NEA2E+HJ667BZrPM\n/3QS5+46DIo7j82vDFby7EnPsjS6jFKnktf/lutQOP+LBgbvWYXHu2G95EVEdgQK9C2gLFDGVeOu\nIpVJUeApIOzb8hOU+Nw+fjTiR8xsnMnV467mkjcvYXlsOdeMv4bD+h6G27h5ZvYzXP3+1biNm1sP\nuhnvlFoGjh9PJBZjVv00bp/xL/599L9ZFFnEmS+cScgboqawhn8e+s9Oz86drENjopF0Np0bm+5z\nM+ygar54fTH+oIeeA4s55oe7Ey7zc3mfy9f43L8wkGsSb3MshWUBIo0J+u9e0WnWNmPMinmF19Ay\n4Hf76RnqSWWgBwu/bCQeTeP2uhh5aI3CXERkFetcPnVbka/LpzpZh7gTJ+gJbtBkMlmbJZKK8MTM\nJ/jrJ38FcsPfHjn2ETxuDxe+eiGf1uVq8Uf3P5qLep7D5P89zcwP32PA3uMoOWoMJugjkopw+duX\nAxDyhnjmxGeoLKiA6HJwUsx3ZTjtudOJpCN8f/fv0yvUi6pgFbsEhxFwF1AQ9uJyb/jTmraWJE46\ni8/v7lj5LJ1MsmTGNCa/8AxDxu3LgFF74Q+tvWUjncyQjKXBGAJhL55VpnONJtLE0xkKA14CCnvp\nGlo+VbZpeobeTVqTrTwx8wkueeMS3l3yLvF0fL3nuIyLYn8x43qNw+/2E3AHuGDkBWTJUuA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ZWVXV1MERGR7VqXBroxxksuzB+w1j7Rvnm5MaZX+/5eQG1XlkFERGRH0JW93A1wFzDNWvvXlXY9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HC5wOXCP2TIRnV6Skroce65pBoaWH3NtSQWLmTwY4+y5PQzSJWX4x81ioH33L1RqAfzfRx0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\n7DfURry6mvI/3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Mc1Zl1kV6BA3wlVNVVx84KbWVq9lGv2v4a9i/fG20PTkXbF+KLxPH/i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\nhd7P5Pg6XotcRESkI70zA4iIiIhkl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YTmMH7ZGDO2+Tx7N58rC/gS+Im1drIx5k/AWcAt\nwL3ALGvtUmPM/sCdwGG99pOKiHSBAl12NvOttWsAjDEfASOAWmC9tfZ9AGttXfPzBwG3N2/7zBiz\nCtgc6G9Ya+uBemNMLfBs8/ZFwD7GmBzgQODJ5kYASK0hLyLSLynQZWcT2er7BN3/f3jr8yS3epxs\nPqcLqLHWTurm+UVEepXuoYsTfA4MMsZMBWi+f+4B3gLObN42FhjevO92NV/lrzDGnNJ8vDHGTMxE\n8SIiPUGBLjs9a20UOA243RizEHiF1L3xOwGXMWYRqXvs51hrIx2fqY0zgfOaz7kYmNGzlYuI9BwN\nWxMREXEAXaGLiIg4gAJdRETEARToIiIiDqBAFxERcQAFuoiIiAMo0EVERBxAgS4iIuIACnQREREH\n+P/b55ba7KFehAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "ZGA2VtaOszNw", + "colab_type": "code", + "outputId": "20bc010f-5883-44d8-ee0e-f043e08d49c0", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2231 + } + }, + "cell_type": "code", + "source": [ + "for year in years:\n", + "\n", + " sns.relplot(x='income', y='lifespan', hue='region', size='population', \n", + " data=df[df.year==year])\n", + "\n", + " plt.xscale('log')\n", + " plt.xlim((150, 150000))\n", + " plt.ylim((20, 90))\n", + " plt.title(year)\n", + " plt.axhline(y=50, color='grey');" + ], + "execution_count": 46, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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N7cnJUQdNRHov3UMXacYM8hLrg3dBrv43kd7FzDY1s6fN7B0zm2Vm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\nrDM71I765cuhsZHEkCFYjgaopF06tSx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P0fJc+la504HdcfKT74vzpeQ1EZngZmdrXbfdgOvca5VIS6KTu4C/quqHIjIK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\nH9yZ7ikOBgYtLHxuFakdnWiLIjvdyQtThpGyT9rU1YWrWVO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d5T4auF1EYkAY53l5HvBvEfEB04B/uNveADwiIn+iefB8HXjBHdB2wSae/2ng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1tK1xzvMJI4r4ZEkJ972/mBVl9SRamCDldNi4cGwvHj5pEI9MHMm5PQTnnQ8y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\nE1UtFZH/BW7CK15SqKqHicgk4BeqeqKIjMe7XZsClAEXqur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9/C9aF8dUxih22Hf8v59qyefAwSLSH0BEvCIyAFgE9M3cIwc4vZntPwXOyDw+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\nnt8E3OLuOwFrgAu7oQ0iIt0uHo/H4vH4jcAqYA6wKh6P39gFyVkAHPi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7Ciz5gcBHH8FHH4GuM3LuXIxNLIUDMFl1Dp1awM9fFdNrkButtAhDbh5VoWr+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\nkDSD6ETgW5KeIpuv5LD08mVk17P/Cvwzb7NvS5qTbhn7G9l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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "metadata": { + "id": "of4BLMuhtpB9", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### 100 years ago, few countires had lifespans _above_ 50 years" + ] + }, + { + "metadata": { + "id": "7MF3Ki1Wtn57", + "colab_type": "code", + "outputId": "3749be0a-66a0-4c17-8eae-6bb36d657dc7", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 173 + } + }, + "cell_type": "code", + "source": [ + "df[(df.year==1918) & (df.lifespan >= 50)]" + ], + "execution_count": 47, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearincomelifespanpopulationcountryregion
19171918761054.955066003Australiaeast_asia_pacific
103331918639356.243165276Denmarkeurope_central_asia
182111918257651.11115504Icelandeurope_central_asia
281131918447950.282576646Norwayeurope_central_asia
\n", + "
" + ], + "text/plain": [ + " year income lifespan population country region\n", + "1917 1918 7610 54.95 5066003 Australia east_asia_pacific\n", + "10333 1918 6393 56.24 3165276 Denmark europe_central_asia\n", + "18211 1918 2576 51.11 115504 Iceland europe_central_asia\n", + "28113 1918 4479 50.28 2576646 Norway europe_central_asia" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 47 + } + ] + }, + { + "metadata": { + "id": "5DHLjCPnuAm8", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Today, no countries have lifespans _below_ 50 years" + ] + }, + { + "metadata": { + "id": "uSMaZwfhuEMj", + "colab_type": "code", + "outputId": "b9faf932-48ab-4322-d762-cb0fdc315785", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49 + } + }, + "cell_type": "code", + "source": [ + "df[(df.year==2018) & (df.lifespan < 50)]" + ], + "execution_count": 48, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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yearincomelifespanpopulationcountryregion
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" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [year, income, lifespan, population, country, region]\n", + "Index: []" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 48 + } + ] + }, + { + "metadata": { + "id": "KV8xHfvmh0kL", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Get interactive with Google Colab" + ] + }, + { + "metadata": { + "id": "GEBsYUXPhzO8", + "colab_type": "code", + "cellView": "both", + "outputId": "a4f041ff-1a4a-4a81-e306-a152c43035aa", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 386 + } + }, + "cell_type": "code", + "source": [ + "year = 2006 #@param {type:\"slider\", min:1800, max:2018, step:1}\n", + "\n", + "sns.relplot(x='income', y='lifespan', hue='region', size='population', \n", + " data=df[df.year==year])\n", + "\n", + "plt.xscale('log')\n", + "plt.xlim((150, 150000))\n", + "plt.ylim((20, 90))\n", + "plt.title(year);" + ], + "execution_count": 49, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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PBCDz4osJKc3bD9zD2/93L/6Kciw5OVhzcpIT2gCjtpaaN98ErQl+/z2V2Lj/o5+55Ln5\nzJy3kcqgJIgUoi3JkLsQHSTkj/LxU8vZuLSc7gPTmfSbQWR0azitaVUwyuyFW/h8ZSmXTezP6F7p\nOKxm/OEYwWgCs0nt0bN4IxYjXlzMpksuIVFdQ8//PIRz5EjUTs+54xUV6HicuMXMOw8/wIZFCwEY\ncPB4pl55LbZ6k9xiJSWsPelkjJoaXNffyD+cI3h7UVHd/n+cNpLTxvTsTPnWO01Dxf5JeuhCtEIg\nEmddWYCvV5dRVm8JWksYCU3x+moOPXsQ8fFZPLZwE0VVDZcH3VQZ4vb/LePzn0s594nvqQome9Ae\nh5XcNMceBXNILhOrePJJouuS68eL/3IXiepdq5pZMjOx5uZicjh2SPSSnEyndzm276zX6X7vvTim\n/5KPlxfvsP/NHwvxR5oelWhv8WiCaLhj2yBEW5EHWUK0wqoSP7/4f1+hNYwpyODRc8eQ5W5ZULU5\nLEz6zWBWJKJc/3pyhvicVaU8e+EhuwTohLE9WBpa44yFiG4oJl5Vha1XrxbnS2+IY+jQ7W3r3x9l\nszV6rNXh4uiLr2TO0/9FWcwcdd4MbA7nDscoiwVbz57YevbECEYZ2TOd79dV1O0/tF8mTlvHzXQP\n1Ub5/u111JaHOfz0gaTnydp10blJQBedntZ6rw/bfrW6jG1PqxZsqCSRaPmjK6vdTMGwTL79YXPd\ntpKaCIkGHoMVZLm4/rhBzF1Zyk0nDEYtXMCa3/0OAPeRR9D9nnuwZOzZenbPlCn0zMnBqKrCffgR\nu6w9r6/MH+H8F5dz9LBTAMVYk5OGy6UkZbhs/OuM0Vz32k8sLaxm6vB8zjqkN5aW5mZvJm1ogrVR\nwoEYTo8NV9quX05WzStmyZxkXit/ZZhTfn9gg8cJ0VlIQBedVlUwytxVZXy9uoyLj+hL32wPZtPe\nCexTh3fj4c/X4I/EOX1sT2yW1gUmq93CccPz+WRFCevLg9z9yxGkO3fNkJbhsnHxEX05e1wBbmIU\nvfFG3b7A3C/Q0VasQd+JJT0d78SJzTo2bmiWFdWyrKgWgKNH9KR7etM93B4ZTh7+zUFE4wZuuwW3\nve3+/PgrK4hFImhtJRax4vbZefmv8wj7Y+T09nLSlaN2CdYm8/b/V5RJyRNy0elJQBed1sbyIFe9\nlJyU9d6SrXx0zZHkevdO5rHemS4+uWYi4XgCr8NKuqv1Pbscr51//Wo0sYQm3WXFam74y4HdYsZu\nMaO1Be8xU/B/+ikAjtGjUNY9+6ccr6xEh0Iom61ZRVTcNjNXTxnIo3PXMmFANr0zmzdcvSe/p8YE\nKit56dbrqCktoWDkQYw67iJiYS9hf/JLTunGWhIxY5fz+h+US21FhJqyEON/0R+XV3rnonOTgC46\nrZrw9l5pIBJnby7YsJhN5Pl2/fIQ89cQDWvMFnB4XWBuXj7ylgQ6pRTeyZOxv/Yq8ZJSnKNG7tEz\n9HhlFSX3/oPqN97A2rMnBS++gHU3SV98LhsXHt6Xs8b1xmY2tUugbq7qkq3UlJYAsGHRD4w/7RIc\nHhtp2Q5qysL0GpqJ2bbrlySn18a4aX0xEhqLVbLWic5PArrotIZ293H2uN4s2FjJdccOIs3Zsf87\nR2v9rP2xjG/fKSKvwMWkMwfgzGi7sqjBaBx/OI7NYiLd58Pp8zX73NLaCIbWuG1mPI4d26QjYapT\nQ/ixzZsJL12224AO4HVY8e50rXAgRkVRACNhkNXDg9PT/oE+LTcPly+dYHUV+QMHEQ4auDMUv7x+\nDPGogc1hxtlI79tkMtFOj/GF2OskoItOK9Nt48YThhCJJfA6LNgsHdfL8pdXobHyyYvrQcPaqghD\nD62mIKOpqWK7CscS1IRimJQi27t9prs/HOftRYXc9+HPHNgrg7tPHdHspWpF1SFOf+QbNleG+PPJ\nQzl9bC889Z5fK4sV+wEDiaxchbLZsA/o36I2b2MYmp+/LeLLV1cDcPCJfThoah8srZxf0FxuXzrn\n3PNvIsEANqcbs8WNw2PDtJfmUwixr5CALjo1j92yQ3DqCPHqahZvrqJ3TgYOt7Xu2a0rs/FZ4ttE\nQ3FC/hixSBxHuo35W6q58sWF5KU5eP7iQ8j3JZeCBaJxvl5Tzq/H9ebnrX6WF9Vw+MCcZrVv7srS\nuhSx933wMyeOyN/hd2bJzqL3U08R3bwZS04Olqyslv4KADDiBoWrtq9dL1pdTSKaaPeArkwmPBmZ\neDL2fOmeEJ2ZBHQh9lBUK55bUk55bREPXj2K1d8V032gj7Rs527P3bK6ilXfFWF3mOg+vju3zF6C\nPxLHX+rnlXmb+P2UA+qOHZjn4bu1FUwalENBlotAJI7bbsEIhzECAZTTWVcHPF5ZhY7HMDkcjOiR\njkmBoeGg3um7TLozEgYh3JQk8sl1pGGxtm6Y3GIzM/bEPmxeUYFhaA45pR+2ZuZsL/dHqA7FcNst\nZLltWBqZGCiEaJwEdLHfi0XiRILJbGF2lxWrffdD9/HSUoxQCJPLjcPr4bhB2fz+tSVMe3YeN00d\nzPCBGaypCLFxXSVjCtLJaWD2fSJukGaLMKL2M4yVW7AefQMDcz11vemh3dPqjl1WWMM/P1zJgb3S\nWbylmjEFGfzvp0LOH5VD+P33qHzhBTxHHE7WpZeC1hTedDPBr74i4/zz6X/BBXx8zUQKq0IMyU8j\nw71jwA7Vxph51/dEQ3HsLgtn3TYOd3rrMs9ldnfz6zsOBcDhtiSXg+1GRSDKja8v5qPlxficVt77\n/RF0T9/9lyEhxI4koIv9mmFoilZX885/FqGBqZcNp/ewLMxN9BDjZWVsOPdcouvW4xg+nF6P/peJ\ng/P4+oZsasJx8nxOlmyu5tePfwfA4G5eXrh43C7PvM0WEyyYS9V/HwbAVVbGvf96kC/WVNDd52RI\n/vbn75sqglxx1AAG5nqYt74CraGoOgz+WorvvBOAijVr8B49BZPXQ+Dzz5PbHnuMjDPPpF+PDPrl\nNPwIIBaJE00VhokE48SiiVb9LgHMZhNuX8u+DMQTBh+l0sJWh2IsK6qRgC5EK0hAF/u1WDjOwg83\nYqRSqy78cCP5/dMxu5sI6JWVRNetT74uKaEMG3e9tQy7xcSNU4eQ4bLxxaqyuuNXbK0l1kAmuXg0\nguWwQ8mb+SKB12YRW7SIjFiQXx7Uc5djjx2Wx4byIL969FsAZv2whRcuGYcyBZPlTret2bNaMKdn\ngNUKsRjmrCyUtemZ9jaXlT7Ds1i/pJy+o7Kx7+XVAlaLiZNG5PP24iIy3TaG5qft/iQhxC4koIv9\nmsVmptewTDb/XAlAryGZWHZesxwoA50AZzaYzZjT07F07068sBDnjMu47e0VfLgs2cN0WMzcPm0Y\n0w/swdNfrycUS3DSyHzsFhOxRIJyf4xo3CDdYaJi9TJm33snWsNJv/0DvX57GeZGJqR18zlZXeKv\nex+KJXBZzRgOLz3uv5+KF17AM/FI7H36oBwO+r0xi+CPP+I54ghQyS8hjaWGdXltTD5/CEZcY7Ko\nVi01qwhE8IcTOKwmsj32Fs0wz3DZuGP6MK4/fhBOq5nsPSw0I8T+SgK62K+ZLSaGTuhOj4HpaA3p\nuU60SRFLGMnJY9Vb4NXzIFgOpz4B3UZhzcmh78szSdTWEs3Ihv+trLueTlUc65fj4vPrJxGKJkhz\nWshw21hd4ueUh74kGE0w+8KR/Pjs4yTiyaHuOa8+z1l3/qPJnPRD8tOYMiSXb9dWcO74AnLTHLjd\nNvSUo3EfNh7ldGJKFVSxDxiAraCA0OLFFF7/Ryy5ufT4vwcaXV++J+vFK4NRbp29lHcWF5HltvH2\nVYfXzc6PhOIoxW4nx2W57S0ubiOE2JEEdLHfc7itOPomk7SU1IS5740lWExw9TEHkPPtw7B5XvLA\nWRfDBe+DJze5vCsnBztw57ThWM0mHFYTVx9zQN0s8ry0HSfXfbK8mGDq+fSy4gDenFzKN28EIC0n\nD5N5N0HPY+e+00cRjRs4bea6pC7KasXs8xGoqmDdVwtI75ZPdq8+mMNhCm+4kdiWLcS2bKHqlVfI\nufLKtvq11YnGDd5ZnKxzXh6IsnJrLfk+JzXlIea88DNmm4mJZw5q9UQ7IUTzSEAXIiUYjXPn28t4\ne1EyOMUNzV0jjsL2zYPJA1zZoHadAd/N5+C+00ehFBihBFUlQax28y6TwyYNyuX+j1YSiRtsDSku\nmXEV8956DW0kGPeLX+H07j4JTWMpVoM11cy6+w5K1q0BYPoNf6ag7wCs+d2IbdoEgLVXr2b/LlrC\nZjYxeXAun64oYWCehwNz0yhcXcW3s9dStLoKAIvVzORzBmPpwHKpQnR1EtCFSNE62dvcJhwzMHoe\nDJNvhdoiOOI6cDf8jNtpMxOsifLuw4soXleDN8vB0VeOpCwRZ3A3L3aLmT5ZLuZcPwlLNII3FkKF\nQkw8/TfJofI9zD+qDYOyjRvq3m9d/TP9DzqYHv/8J1WzZmHt0QP3hMP36DMak+G28Y/TRlITjpFh\ntvDho0vof2Dzkt4IIdqOZG8QIsWciHDr1AOYPDiXY4bm8fvD8li7YAHhg6+g+Ii/srjWRWltpNHz\no5E4xetqAKgtD1NVHuK3zy+gMhAFwG41083nxLFyGWunTGHN0VOofvMtgoEQa0v9LCusptzf+PWb\nYrHZOfyscwFw+dIZNnFKcntODtmXXorvpJPASBBetYpYSQk6HqfMH2FjeYCSmnCrPrO+LI+dvtke\nrCZFTVmIpV8Wctgv+9N7aCZ9R2cz4dQB0jsXop1JD10IIB6PserbL/nm9ZmcM2kqaIOP//4g/spy\nTn/gaX7x+ELKA1H6Zrt55dLx5Hh3fR4cNjTZvTyUbfKT3dNNn2zNzMlZpIdq0G4rymLBiEapeu01\nMJIjAdWvv0Zg9GGc9OwSAMYUZPDoOWN2WLOeSBhEAjGUUo0WGbG7XIw8+jgGH3YkJrMZly99x/sr\nL2fTZb8lvHgxJp+Pvm+8AdE4qrSCrU4fqnc3ctL2vPSs3WVl8rlD+PTZ5fz4ySaOOncwNoel2Rnj\nhBCtJ//KhADCtbXMef5JIoEAP7z2bN12i81OcaWf8lQve11ZgFCs4cQr3xRWcsDp/TjSZSfNHKLk\nqqsIL/qJDW43/d7+H9b8fEw2G77p06h9/33QGu/JJ/P0svK6ayzYUEl1MEpaqAaz14u22ChZX8On\nzy3n0GPy6Nnbisluw5yZiWmn9eV2lxu7y91g23QkQnjxYgCM6mqia9ZQddddxDZswHvUZPQtf4Y2\nCOgWq4megzP51S2HYDK3bgmcaH9KqVOAoVrruzu6LaLtyJC72O9prUkk4kQCgV32xaMRfBaDAbnJ\nLGvj+mbiamTo+IiBOTw2bwMz3vgRZSQIL/oJACMQILJuXd1xrrFj6f/Jx/T/8AOcJ53CJ6mJYwBH\nDc7EZq5l6+xXqfnoI8K1Ed5+6CcGDPPimvcOa489ljVTTyC6dm2L7lE5HLgOTaZkteTkYO3Vi1hh\nIQCRr77E24aj4RZrMlucBPO9QyW16G+51votCeZdj/TQxX4pVlxMeP0GIvmDWDy3kO4D0znq/N/x\n2dMP7nLsnH//ladv/Qfa6sBpazzxSbbHzt2njiQWN7BGg6SdcAI1776LtUd37AMG1B1ndrsxu5M9\naYuheeScMfx+5kLG9/dxzEFBrvn6D4wYNISLnMNJMwyUSdGjj5Pa+18EQAeDVM2aRbc//anumoY2\nKA+VUxYqI8eVQ7Yze4e2WTIz6fHP+zD8fpTTiQbMXi+JigrSf/0brK49752LvUcp1Qf4APgOGAPc\nq5S6DLADa4ALtNZ+pdQJwP1AAPgK6Ke1PkkpdT4wVmt9ZepaTwLZQGnq3I1KqaeBGmAs0A34o9b6\ntb11j6LlJKCLTskwDBLRKFZHywNRvKyM9Wf9muwHHmHW/T8SCydY9mURUy8bii83j+qS4h2OD1ZX\nkW7VeDJdu712mmPbMLidvFtuJueaqzHZ7VhyGp71bTIphnVP4+UZ44mpak6efQKRRITlFcuZOOZg\nxlsSnHTlKGo2luI4ZByBDz8AwDNx4g7XKQ+Vc9r/TqMiXEH/9P48fuzjuwb1rCxIZaLThkG/N2dj\nRKPJLxhpkm61ExoInAesBmYBU7TWAaXUDcA1Sql7gf8CR2qt1ymlXmrkOg8Cz2itn1FKXQj8G5ie\n2pcPHA4MBt4CJKDvwySgizb+Akj5AAAgAElEQVRnGJqwP4bJpHB4ms4j3hqh2hoWffIBRSuXc9AJ\n08gfOAirvfmBXcdixAsL0SYzsfD25+HxsAlXWvoOAV0pE1OvvAa7e/e1zXdmycyEzN3X6FZKke21\nUxYy4bF6iCSSM93Tc3pi9aWR6zFIy3ZiGX4rsXPOxpKViSVnx4xvZaEyKsIVAKypWlN3jUY/02Rq\n9EuG6DQ2aK2/VUqdBAwFvkplGrQB35AMwmu11tue97wEzGjgOuOBX6ZePwfcW2/fbK21ASxTSuW1\nwz2INiQBXbQpI2FQttnPx08vw5Vm55gLh7a4+tburP1hHl++9Ezy9cL5XPzQEy0K6MrlIvOii4h+\n+wXjTxzPgk+3klvgJb+nnalnX8SKH+dTtGEtGfk9GH3sibgzMrDa2z/LWaYjk6ePf5pnlz3L2Lyx\nFKT3BcBkNuFKswFZ2LIbXgef48qhf3p/1lSt4fAeh+O07Fm1stLaMFpDhtuK1SzLzfZR2yZ9KOAj\nrfVZ9XcqpUa3wWfU/2bY/AT9okNIQBdtKhyI8/FTy6jcGqSyKMiSuVsYd3K/Nv2M+j1obRjEwrtf\nR50wEvhjfuxmOw6fj+zLLkXHYqQrK4OOLMBsNmFJBMGew9gTp6NtVswWK2bL3vsnYlIm+vj6cOuh\ntzaZ070h2c5sHj/2cSKJCE6Lk0zH7kcGGrO5Msh5T35PVTDGo+eOYXTP9CbLyYoO9y3wH6XUAK31\naqWUG+gB/Az0U0r10VqvB37VyPlfA2eS7J3/BvhiL7RZtAP5VyralMmkUr3JJG9m20+2Gj5pCp7M\nZE+1/5hxOL1NP/+NJWIsLlvM7z79Hf/+4d9UB6uoCdSyesUSYkYYV5oNh8eKxedLzgBPS8PmcO5x\nMI/EEmysCPLZzyWU1G7/0hFLGJT7I/gj8QbPa2kw3ybbmU0PTw8ybOnEKypI1NS26jqPf7GONaUB\nygNRbntzKVWhWKuuI/YOrXUpcD7wklJqEanhdq11CLgceF8ptQCoBaobuMTvgAtS554D/H6vNFy0\nOaX1rnWa9zVjx47V8+fP7+hmiGYKVEdYMncL3gwHfUdnt8vypUBVJYl4DKvNjjPN1+SxpcFSTpl9\nCv6YH5My8enU93n+6iuIx6K4MzI5++8P4MlofY+2MZsqghz9zzlEEwb9czy8PONQvE4L89dX8rd3\nlzOyp4/rjxtEZhtWGdOGQWTlSopuvhlLXjfy77wDS3b27k+s55X5m/jja4sAmDa6O3dNH15XCGY/\n1+mGnJVSntRsdwX8B1iltf5XR7dLtA8Zchdtzu2zt/kw+y6fkZ5BdSjGspJatqwt5LD+WWQ3kL0N\nkj1eu9leN+QeqqkmHksmiglUVtSVMG1rmyqCRBPJjHBrSv3EDU11KMZFz8wjHDNYWljDMUO7MXlw\nwyVNWyNRUcGWa68jumYNLF1G1ciRZF92aYuucczQPJ48/2AqA1EmDcqRYN65XaKUOo/kRLmFJGe9\niy5KArrotBZurOT8p5KlTY8cmM3/nXUgGQ1UI0u3pvPEcU/yxOLHGZUzCl9WLn1Gj2HDooUcePxJ\n2Bx7NoGsMQPzvAzrnsbSwhouPbIfTquJaMLA57QSjqVmsjvbOFharWSc/Rui69ZTPWsW5qyWjzxk\nuGxt+iVDdJxUb1x65PuJdgvoSqlBwMv1NvUDbgOeTW3vA6wHztBaV7ZXO0TXtXjz9seBy4tqiSWM\nXY6JxhOsLwvy8vwQB3a7lOMKuuN1WjnhymsxEgnMViuOVixJqw7FKKuN4DWbsGuF2aSwu61Y7dtn\nhOd47Tx74SHEDY3DasLntKG15uVLx/Pkl+s4uE8m/XIaTtXaWkZNDYHP52DOzKTPK69gTm/6cYQQ\nouvYK8/QlVJmYAswDrgCqNBa362UuhHI0Frf0NT58gxdNGRLVYhf/fcbimvC3H/GaKYMycVp2/E7\naqJqM6EfXiGaM4I3S3JIz8zhFwf2aPK6Zf4IHyzdSrrTyvj+2WS6d+z1JxIGr/2wmXVb/RxhcvDj\n/9ajFBw3Yzh9RmRhtnTMMq94ZWWyAMtPyZSz2b+7kpwrruiQtnRRne4Zuti/7K0h96OBNVrrDUqp\nacCk1PZngM+BJgO66BihmmoSiQRmixWn19vRzdlFj3Qnb1w+Aa01XocV58451v2lmJ+fjqdsFQAn\nn/Uey01ND3HXhGLc8sYS3l+6FYA/nzyUCyb03eGYcNzg/SXFXHpIAYseWw4ka6nPe3s93Qek42zL\nxOgtpOqtGVcWefYtxP5kbwX0M0lmKQLI01oXpV5vBST70D4oWFPNuw/9kw0//cDgwydy1HkzcO1m\nNnlHaKiMaR1tQPVmYgdeSGjURVisHkZ7ml5GF40brCn1171fVlhDwjAwm7av8HTZzFxyRF/KK8Nk\ndHNRsj65PCyzuwuTpeUrQf3hOMFoHKvZRIa79SsCLBkZ9LjvH5Tc90/MOTmkn37aDvvjlZXoeByT\ny1WXS14I0XW0+5C7UsoGFALDtNbFSqkqrXV6vf2VWuuMBs6bQSpNYe/evcds2LChXdspdrR1zSpe\nuOnquvcXPvAoGfndO7BFrRALwqb5bKqEV++7D20YTL7wt4w46hgstoYDZyxhsGBDJTOenU+a08oL\nF4+jIGvX4BeOJagJxXDEYfHnm7HZzQw7oscOa/CboyYUY+b3G3ngk1WMLcjgX78avUMt9NYwIhGU\n2Yyqt44+Xl7OlmuuJbR4MbnXXYfvlJMxe1o+d2A/t98NuSulvtZaH9bR7RDNszcSy0wFftBab0vv\nVayUygdI/Sxp6CSt9aNa67Fa67E5knN6r3P50jGlhm8tdvteSX3a5qwudK9xLP3+B7SRnDC3bM4n\nxCKNZ5azmk0c1Dudj6+dyBuXH9ZgMAdwWM3kpjlIy3Qw4ZcDOPjEvi0O5gDBcJS/vbeCYDTB3FVl\nrCyqafE1dmay23cI5gChxUsIfvcdOhik+C9/wQgG9/hzRNellLIASDDvXPbGkPtZbB9uh2TFnvOA\nu1M/39wLbRAt5PSm8Zu//Yv1P/2QzMa2Dwy3J/x+DL8fTCYsmZm7BK2GKKud4ZOmsPyLzzASCYZP\nPna3FdpsFjO59Z6Dh/y1xMJhlElhd7nbdplbKESPdCdbqkKYFOT72qeMqa1XT1AKtMbau/cOz9pF\n++pz4zu/Bv4G9AY2Ajetv/vEF/f0ukqp2UAvwAH8n9b6UaWUH3gYOAEoAm4iWWylN/AHrfVbqUnK\nd5Ocy2QH/qO1/q9SahLwF6CSZGGXA5RSfq21J/V5NwBnAwbwntb6RqXUJSRHUm0kq76do7WWb4sd\npF2H3FM5hTeSrMFbndqWBbxC8n+wDSSXrVU0dR2Z5S6MSISa996j6E83YXK76TPzpR1qjDclFgkT\n9vsxEgkcbg/2Fjw/DtVU8/mzj7Psi88wmc1MvuAyhh5xVKvKtjYkunkzWwNxvtpYy8iePgryfHgy\n2/7LUyIQILZxI+Hly3FPmIA1T6autEKLh9xTwfwxoH7t3SBwyZ4GdaVUpta6QinlBOYBE4Ey4ASt\n9XtKqTcAN3AiyWpsz2itR6ceZ+Zqre9SStlJ1kk/HSgA3gGGb6vQti2gK6WmAreSLNEarPfZWVrr\n8tSxdwHFWusH9+S+ROu1aw9dax0AsnbaVk5y1rvoioLl8PN7sHUxHHQuZA0Ay54P1xu1tZT/91HQ\nGsPvp/LlV+h2803NOtdqd2C1O4hFIlisLZv5HaiuYtkXnyXbkEjw2TOP0n/MIW0W0C2ZmeRFijjZ\nUY09uxvWdgjmQLLm+ZAhOIYMaZfri0b9jR2DOan3fwP2tJd+lVLqF6nXvUjWR48C76e2LQYiWuuY\nUmoxydwfAMcCI5VS22ZN+uqd+329cqv1TQGe2tb7rtcJG54K5OmAB/hgD+9J7AHJFLcfi0XCVBYV\nsmXFUvoddDBp2bko0x5Mq0jEYP7T8OmdyfcLnoarfoC0ptd9N4dyOHBNOIzouuTfGs/EI5t9biwS\nYeuaVfzw7pt0P2Aww486ZrcFXbYxjB2T1WjDoC3HtEwuF/b+/bH379+GVxX7kN4t3N4sqeHxKcD4\nVI/5c5JD7zG9fdjVIFX+VGttbHsuTnKk4Xda6w8auGaAlnkamK61/kkpdT7blySLDiABfT8WrKnh\n+T/9AW0YfPP6TM6998EWFSlJ1NaSqKlBmcyYfWmYTDFYP3f7AfEwVG1uk4Bu9njIueIK0k85BZPX\n26KCI2F/La/ddTNGIsHqed/g8qUzbGLzBok86Rn0GjaSTUuTxUrGTT8Dh8tNvLwCVLKH3Rw6Hide\nUQGJBCaPB/M+uK5ftIuNJIeyG9q+J3xAZSqYDwYObcG5HwC/VUp9muq9H0Ay8VdTPgJuU0q9UH/I\nHfACRUopK8nSq7u7jmhHEtD3Y6GaqrrZ36GaaoxEotnnGtEotR9+SNHNt4DZTK9HH8Vz6DgYfiqs\n/Tx5kDMDMhr6W9Y6lowMLBm7rHDcrWg4tMO9VW0tbPa5Ll86J/3hBsJ+P2aLBYfHi1FYyJZrr0OZ\nTfS4/35svXff2Yqu38D6M8/E8PvJu+020n8xHZOzfXLIi33KTTT8DL15z4sa9z5wmVJqOcm659+2\n4NzHSQ6//5CqwlYKTG/qBK31+0qp0cB8pVQUeJfkPdwKfJe6xnckA7zoIFI+dT8WrKnmkyceZuPi\nHxl7yqmMOmZqs/Oax6uq2HTpZXVpRr3HH0/3e+/BlAhA8TIoXw39j0r2zk0dO6M6WFPNew/9k/U/\n/YA7PYOz/vIPfLndWnWteEVF8r4XLwbAdcjB9Pz3vzGnpzd5XvE991Lx1FMAWLp3p+/LM7HIcszO\nplXr0NtrlrsQO5Me+n7MleZjyiVXkIjFsDoc2J07z91pnMnpxHfyScmArhS+aadgstkAG/SZkPxv\nH+FK8zH1ymuJRSKYLRbc6S3v5ddRClVvYp2yWqEZ8w48Rx5ZF9Dd48ej2mhSndj3pYK3BHDR7qSH\nLlotUVNDoqoKzBbMvrR2yTxmBIMkqmvQiTjmtDTMac2bzNaeolu2sPXPfwaTmfw7bsean7/bcxJ+\nP/HSUhJV1dj6FLTq0UFLGLEYiYoKDL8fc5oPS07z5xyIRu13meJE5yIBXew1wVgQf8yPQpHlzMKk\ndt+z9X/5FZsuvRQSCXJv+CMZZ565Tzx7TtQm87fvq5Pbwj//zPqzfo0OBrH27k2fF56XIf49JwFd\n7NP2RupXIYjEI8zZPIdjXjuGU986lU3VG9ndl0kjHKZq5kxITWirnPkyRqClq2rah9nr3WeDuY7H\nKX/iSXQqvWts40ZCixZ3cKuEEO1NArpouVAVrP4YPrkTyteAsfvZ8f6Yn4cWPoShDSojlcxe/iqJ\n6uomz1F2O55jj6l775k0kVpTlNJg6R7fQpdmNmPr3WuHTZa83A5qjBBib5FJcaLlKtbC86cmXy94\nCn77DXibnjVuN9s5OG8sG2uTy2/H+kYQ27wZSxOzw5VSeCdNwvn228SDAVY7azj/nRPp5u7Gc1Of\nI9spz4UbopQi46yziJeUEl6yBN+pp2Lt1Wv3JwohOjUJ6KLlquqVsg1WgBHf7Skem4erRl3JCdkT\nSbd6sX82H8vJB+32vG0T4cpqt3D2rN8AsLl2MxWhir0a0I1QCK01ZlfzVwJ0JEtWFrk33oAOhzF5\nPKkVCEKIrkyG3EXLFUyAXuPAbIOjbgZb82a3Z3pyOChnNAWmHHqcclqLsr3ZTFYGZQwCIN+dT4aj\nfWeJ1xcrLaXw5lsouvFGYsXFuz9hH2F2ubBkZkowFw1SSk1SSh1W7/3T9fK7t/VnPa6UGtoe1xbb\nSQ9dtJwnF858Mfns3OoER/OXklkyM5udLhVAa01l0Ra+feUF/nHaXeCx4bF5yXHtOGPbMDTB6gjl\nW/xkdvfg9tkwmff8+6oRjVL6z/upfffd1AZN/j13Y25BxTaxn7vdt0tiGW6v3hfWpU8C/MDX7f1B\nWuuL2/szhPTQRWu5s8Gb16Jg3hyV4UrKgmXURpPLwoI11bz9wD2s/OYL3vrTzVR9t2yXYA4Qqo3y\n8l3zePuhRcz8y/eE/LG2a1T9LwYmU7Ku+D4gUVtLtLCQWHExRjTa0c0RDUkG88dI5nNXqZ+Ppba3\nmlLKrZR6Ryn1k1JqiVLqV0qpo5VSC5VSi5VST6ZKo6KUWq+Uyk69HquU+lwp1Qe4DLhaKfWjUuqI\n1KWPVEp9rZRa21RvXSnlUUp9opT6IfV50xprV2r750qpsanXDyul5iulliql7tiT34PYkfTQxT6j\nPFTO9XOv56eSn7hw+IWcPfRsrEqRU9CHo888jXSvDZtZQ00ROHxg2/48OxqKEw7E6l6HamO4fdvL\ntpb5I1QFY6Q5LGR57JhNzQvKJpuN3D/8AZ0wIBYj94Y/7hPP0Y1QiOo336L4rrtQdjsFLzyPc/jw\njm6W2FV7lU89HijUWp8IoJTyAUuAo7XWK5VSzwK/BR5o6GSt9Xql1COAX2t9X+oaFwH5wOHAYOAt\n4LVGPj8M/EJrXZP6svCtUuqtRtq1s5tTtdTNwCdKqZFa60Wt+SWIHUkPXewzFpYsZN7WeUSNKI8s\neoRALIDL4+W4006gxxdX4X7heKzPToV/j4Yfnk0un0uxu6zk9UmOFmT39OBK256etdwf4bLnFzDl\n/jkc98BcSmsjLWqXJSeH/DtuJ+f229haXsqCd2bjryhvm5tupYTfT8XTTwOgIxEqZ86sK7Qj9int\nUj6VZK3zY5RS96R6132AdVrrlan9zwDNrzG83WyttaG1XgbkNXGcAv6mlFoEfAz0SB2/Q7u01g2t\nTT1DKfUDsBAYBsiz9TYiPXTRqEAsQCAawMDArMzNzu7WWt3c25e+ua1uLCYLBEoxPXcK+Eu2HxgP\nw/s3QLcRdTnjXWk2Trh8JPFYAovVjCtt+0SwaNxg/vpKACqDMTaUB+jmazqXeqC6CrTGleZDmUyY\n7HZK163hldtvAGDJ5x9z+i134fI1XZSlvZicTtxHHE7VSzMB8E4+es9q2Yv20i7lU1O98IOAE4C7\ngE+bODzO9s7b7ooI1P+229Qw1m+AHGBMqgTresCxc7uUUp9ore+su6BSfYHrgIO11pVKqaeb0SbR\nTBLQRYMi8QiLSxdTEa7glq9uwW118+zUZ+nr69sm149GwkQDAVAKZ1oaZrOF3t7ePDj5Qb4p/IbT\nDzidTEcmrP9yx2Be3xf3Qd4wcCaDav0gXp/daubowbl8sqKE7j4HfbKbntBWXVLM7H/8hVgkzLRr\nbyG7dwFKKapLttYdU1NajNGBPWKzx0POVVeRPn16sj68pHXdV7VL+VSlVHegQmv9vFKqCrgS6KOU\nGqC1Xg2cA8xJHb4eGAO8B5xa7zK1QGsnwfiAklQwP4rUl5YG2rXzZLg0IABUK6XygKnA561sg9iJ\nBHTRIH/Mz9bAVl5Y8QIxI0ZVpIrnlj3HbeNv2+NrxyIR1i74nncfvA+r3c4Zf/47uX36k2ZPY1Kv\nSUzqNWn7wdVbGr9QbREkUpPBDAMCJVC9GdK6gzMLrMln6JluG/eeNpJAJI7DaiY3rfEOgZGI881r\nL1G2cT0Anzz5MNOuvwWnx0vBqAPpPWIU5Zs3MeWiy7G7Oname2vrw4u96PbqF7ndB20/y30E8A+l\nlAHESD4v9wGvKqUswDzgkdSxdwBPKKX+wo7B83/Aa6kJbb9r4ee/APxPKbUYmA+saKJddbTWPyml\nFqaO3wR81cLPFU2QgC4a5DA7sJvtDMsaxoqK5L/Vcd3Gtfg68WgUs9WKqjczPBIM8NnTj6INg2go\nxJczn+OkP9zQcPnWHk0knyk4HOypfOr+Injk8GSiG4sDLp0LOYPqDs3y2Mny2Bu50HbKZCaje4+6\n9+nd8jFbkv9M3L4MTvr9DRjxOHa3B8serO8O+aPUVkSwOcw4vTbsTvmn2GUlg3ebLlPTWn8AfNDA\nrgMbOPYL4IAGtq8ERtbb9MVO+xtNMKG1LgPGN7BrfUPt0lpPqvf6/MauK/aM/BURDXLb3Bza/VBG\n5ozkmIJjSLen09Pbs9nnJ2IxSjeu4/s3X6dgxGgOGH84Tk8y+JotFjK6dSdYnZzUltmjFxaLteEL\neXJhwJRk7vj6bB6YcFVyHTzAz+8lgzkkn7F//RCc/ACYzC26b6UUIyYfizczi2g4xAHjJmBzbK/u\n5vTu+TK9SCjOd2+tZencQgBO+O1I+o6SNLZCiD0jAV00KsORQYYjgx7eHrs/eCchfy0v3/En4pEI\nq777itw+/XAOTPaYnd40Trr6Rn784B0cXi9DjzgKs7WRgO7Kgl88AvOfgnmPQ7g6GeCPuRO83bcf\nlzlgx/PyhkErJ/C50nwMPXJyq85tjng0wbqfyurer15QTMHwzDZJhCNEW1JKjQCe22lzRGvd8uE6\n0e4koIt2obVBIrY9uUssuuNSMU9GJoefeU7zLubOgSOuhTEXgDYazk6XPwKm3A6LXoa+k2DEaftM\nApidWe1mhhyWz4L3NqBMiqETukswF/skrfViYHRHt0M0j9pdTep9wdixY/X8+fM7uhmiBWLhMBuX\n/MQ3r79Ez6HDGTf9jFYNV4dqa1jx1Vwqt27h4JNPxZvVxNB0PJrswds924fi91HhQIxIIIbZasLu\nsmC1y3frTmDf/IYoRIr8FRHtwupw0Gf0GPIPGIzFbsdmb91S03UL5/PpU8nJultXr2T6H2/DldZQ\n8inAYgNP51i+5XBbcbgbecwghBCtIAFdtBuzxdJ48G2A1nqH2fCQfBa/Tdjvl2xoQgjRCAnoot2E\n42FsZttus8uFampY8c1cKrZs4uBTTiMte3sve/CEiRT+vIya0lKOufR3LfqCIIQQ+xMJ6KLNxRNx\nVlat5NFFjzImbwwn9zuZdEc6sUgCrTU2x47/221c+hOfPpkcVi9cuYJT/3RHXUpVty+dYy+9CiMe\nx+HxSnpTIVpIKXU79YqwtPG11wNjU+vS9zlKqRzgbcAGXJVak19//+PA/anc9Z2eBHTR5iojlVzw\n/gUE40E+2fgJQzKHMMw1gi9eXUUsnODIswbhzdz+TD1UW1P3OhLwo/WOw+odnZFNiD0x4pkRu9RD\nX3ze4n2hHnqHUkpZtNbxdv6Yo4HFDdVjV0qZu1qddunuiDan0cSM7UvWwokwS77Ywqp5JaxfXM5n\nz68gEty+/4BxExg8YSLd+h/AydfchFOG1UUXkQrmu9RDT21vtUbqoe9S97zeKaOUUt8opVYppS5p\n4rr5Sqm5qRrpS7bVSd9NDfPf1auLPjh1/CGpz1uYqq8+KLX9fKXUW0qpT0mWTm2srnofpdRypdRj\nqc/8UCnV6NIVpdQlSql5qd/H60opl1JqNHAvMC11P06llF8p9U+l1E/A+J3qtB+fasdPSqlPmrqP\nfZX00EWb89l8/Ofo//DQwocYnTuaYVnDWBbaPiJntqgd1oi7fOlMufgKjHhMhtVFV7M366Hf08Tx\nI4FDATewUCn1jta6sIHjfg18oLX+a6pe+ba2N1XDvExrfZBS6nKSldQuJpmr/QitdVwpNSV1v9sK\nwxwEjExdz0LDddUBBgJnaa0vUUq9kjr/+Ubub5bW+rHU7+Iu4CKt9YNKqdtIPhK4MrXPDXyntb42\n9Z7UzxySX7yO1FqvU0plpq7b1H3scySgixaJR6OE/bUYhoHd7W4w/7rdYufgbgfznyn/wW6247Q4\nOfBYN4ahiYbiHDqt/y65y+2uBvK4C9H5tWc99H8qpe4B3tZaf7HzCpGdvKm1DgEhpdRnwCHA7AaO\nmwc8qZSykqyN/mNq+xlKqRkkY0Y+yRrm2wL6rNTPBcAvU699wDNKqYGABuqv0fxIa53K01xXV/1I\nwGB7XXVI1nff9vkLSNZ8b8zwVCBPBzw0nOceIAG83sD2Q4G5Wut1APXa19R97HMkoItmiRtxQvEQ\ntRu28ModfyIRj3PiVdcz8ODx/7+9O4+Psrz6P/45SchCWMOiiAsoqGi1qKlVQYtaLdpW1Mdq1Vat\nVh7rvvRXtbXVLi61VatWn9YVtLVWUSvu4oLiCqEqCogiirJvgZCQhCzn98d9BYaQZbLMTDL5vl+v\neWXm3q4rM5Az93Vf9zkNpm3NysiiT87mWuHde2Uz6oRhuENmnFnRytYWs+KLBRRsN5j8PgVtKoYi\nkiJJqYcehoibqnteP4NYgxnF3P31EFy/C0wws5uJirY0VcO8Lg1kDZtjyu+BV939ODMbwpZV3spi\nnjdYV73eceuO3VS2qAnAsaGa2xnAmEa2q3D3miaOU19Tv0eHo7FNadaGqg1MWzSNRz9+lA9efDZK\n6erOf599ko0V5XEfJyMjowXBfC2P/PZKHr/+au6/9GeUrStubffTSq3rPvxO5pdE9c9jtVc99A3u\n/g/gT0TD2F8Q1T2HrYeFx5lZrpn1Iwp2Mxo57k7A8jB8fU84bkM1zJvTG6irfXxGM9ttVVe9FXoC\nS8PIwqmt2P8d4BAzGwoQM+Qe7+/RISQ0oJtZHzObZGYfhwkOB5pZgZlNCZMzppiZCjp3MNU11azY\nsIIlpUsoqSyhZGMJF0+9mNcWv8a2++696fr38P0Poltu6zLAAayrXEfRsiImfzaZ1eWrt1hXW1PF\nmiWLgKhy29plDV3u61oWly7m92//nofmPsTairWp7o7EIcxmPxtYSHRWvBA4ux1mue8FTDez94Gr\ngT8Q1T2/1cyKiM5oY80CXiUKXL9v5Po5RMG+rmb5ScCt7v4BUFfD/CHiq2F+I3B9OE5TI8H/BAot\nqqt+GpvrqrfUr4F3Q99afAx3XwmMBx4PE+b+HVbF+3t0CAnN5W5mE4Fp7n6PmWUTTbD4JbDG3W8w\nsyuAvu5+eVPHUS735Jq/dj6nPnMqG6o3cOE+FzJul3GMfXwsVbVVjN/tLE4deiJU19K9d29ye/Sk\ntraGdcuXMffN1xmy948QZLYAACAASURBVEj67zCE7Lzmc6m/vPBlLp56MQCF2xRy85ib6Zsbfb8r\nX1/CGw8/yKyXnqPf9jvyg19fS36frvvdb3X5as568Sw+W/sZALeMuYVv7/TtFPeqy1Eud+nQEvaN\nI8y6PIQwTOHuG4GN4baEMWGziUTXJJoM6JJcT3z6BBuqo1HCB+Y8wLhdxnHPkffwj7n/YOeBw+nW\ntyc9s3tStrGMdZXryNxQw0O/uoyKslLemfQvzrrtrrgC+vsr39/0fN6aeVTXbr4lNa9nL0affBoH\nHH8SGVlZ5Pfu09Ahugx3p3Rj6abX6zeub2JrEemKEjmEMBRYCdxvZl8nmqV4EbCNuy8N2yxj84xG\n6SBGDx7NA3MeAGD/bfcnJyuHfbfZlz3770lOZg4Aqzas4vrp11NcWcxN+15HRVkUbNxrqSgtpffA\n5ts5cdcTeeqzp1hTsYaL9r2I/G5bJpDJ69ETevRs31+uk+qb25fbDruNa9+5liG9h/CtHb6V6i5J\nJ2adtM65md0BjKq3+FZ3vz8V/eloEjbkHm7WfwcY5e7vmtmtQAlwgbv3idmu2N23GksNt0iMB9hx\nxx33W7hwYUL62ZUUVxRTXl1OdmY2/fMaL0O6fuN6Vm5YyZqKNezSZ5dNw+B13J2bZt7ExNkTAbhm\nv6vYeUkPiiY/xk5778voH/44rpzrtV7LmvI11FJL96zu9Mju0bZfMM3Vei0llSV0y+y21ZcfSQoN\nuUuHlsgz9EXAInd/N7yeBFwBLDezQe6+1MwGASsa2tnd7wLugugaegL72SUUVxRz/bvX89wXzzG4\nx2AeOOoBBnZv+DS6Z3Y0pL4zOze43szonrn5vvGnFj3HbaNvYdf9DyIrOzvuVK0ZlkH/7k3UN5ct\nZFgGfXK79qUHEWlcwgK6uy8zs6/MbDd3n0eUU3dOeJwO3BB+PpmoPshmlTWVPPfFc0A0W/qT4k8a\nDejx+OHuP6SsuozV5au5eL+L6ZXfdSespbvyqnI2VG8gLyuP7t2UAEiko0r0NPwLgH+GGe4LgJ8Q\n3Sr3iJmdRXQLx4kJ7oMA3TK6sWvfXfmk+BNyM3PZuXfDZ9/xKsgr4JL9LqHWa8nOVMKXdFVSWcLj\nnz7OpE8ncdTQozh1xKlbJAwSkY4jobettZeucNuau7No/SIenPMgIweOZNTgUfTOad8iJavLV/Pl\n+i8ZlD+Ifrn96JaZvCyGFdUVlFWVkZuVq+u/ncji9YsZ+/jYTa+fPu5pdurV2twfnZ6uoUuHFtcZ\nekhcfzZRLt1N+7j7mYnpVtezumI1Z7xwBis2rOBf8/7FhLET2G+b/ZrfsQX65fWjX16/Vu27cn0l\n6yuq6JGTxcBeLUsms37jep767Cke+vghDhh0AOeNPG+riXbSMWVlZJGTmUNlTSVZlrXpLgeRRDOz\nPsAp7n5nK/b9gnaq025mvyPK8/5SW4+VaPEOuT9JlM/3JbbOQCTtwN0pqdxcF3xd5boU9mZLK9dX\ncOo97/LJ8lJ2KMjjsZ8dxMCe8Qf1ko0lXD/9egAWlizkiJ2O4JuDOvTdMRL0ye3Dg0c/yHOfP8cR\nOx7R7qNGXcHc3UdsVQ99xMdzU1YP3ZJTh7w99AHOBbYK6Mn8Hdz9N8lopz3Em/q1u7tf7u6PuPtj\ndY+E9qyL6ZXdi1sPu5XhfYZzzM7HsM/AfVLdpU3KKmv4ZHl0n/lXa8pZG1PLPJ5LNpmWSYZt/qeW\nm9X6dLGSXDmZOYwoGMGl+13KXgP2Ii+r+YRBslkI5lvVQw/L28TMfmRm00Ot77+bWaaZlcasPyEU\nUsHMJpjZ38zsXeDGkIL7P2Y2y8zeMbO9w3bXmNmD1kDtdDP7fxbVHJ9lW9dEr9+308J2H5jZg2HZ\nAItqlc8Ij1Exbd5nUW3yBWZ2YTjMDcAu4ff7k5mNMbNpobzqnLDvf8xspkU108e34L3bar/w/k2w\nqA78h2Z2Scx7d0J4/pvQ94/M7C6zpkvcJVu8Z+hPm9nR7v5sQnvTheVk5fCNbb7BPUfeQ3Zmdoe6\nJzs/J4thA3swf0Up2/fNo0/3bpSXlPDxm1NZs3Qx3zjmBHr1H9Do/r2ye3Hrobfyz7n/ZPTg0Qm/\nBltZXUl5dTl53fI0RCyplpB66GY2gijX+qhQ2OROmi9Ksj1wkLvXmNntwHvufqyZHQY8AIwM221V\nOx34GlF98v2JvphMNrND3P31Bvq2J3BVaGtVTKGTW4Fb3P0NM9uRqMTpiLBud+BQoiIr88zs/4hu\nc/6au48Mxx1DVCzma3VlToEzQ131PGCGmT3m7lsWhmjYVvsRXVIe7O5fC+01NPvzr+7+u7D+QeB7\nwFNxtJcU8Qb0i4BfmlklUEX0gbq790pYz7qgbpndKMgraH7DJBvQM4d/nX1AdA09N4uBPXOZ/dqb\nvDLhLgCWfPIx/3Plb+neSHrW7t26c/Dgg9lvm/3Iy8ojKyNxN1esrVzLpE8m8cqXr3Dgdgfy4xE/\nxsz4av1XlFaVslvf3XT9XpIpUfXQDyeqrDYjnCTm0UhOjxiPxpQOHU2oyObur5hZPzOr+3veUO30\n0cCRREVaIKo5PhzYKqADh4W2VoXj19UW/zawR8xJbS8zqztzecbdK4FKM1tB4xlEp8cEc4ALzey4\n8HyH0Kd4AnpD+80Ddg5fdp4BXmxgv0PN7BdEX8oKgNl0toDu7sq/2YFU1VRtmjGerOHrAT1zGNBz\n89luecnma/wVpaV4M2U9MzMy6Zmd+H9GH6z4gFv/eysAH676kKG9h1KQW8D/TvlfAE7Z/RQu2vci\n3U8tyZKQeuhEJ1UT3f3KLRaaXRbzsv4fhzLi01DtdAOud/e/t6iXW8oADnD3itiFIcDXr33eWGza\n9DuEM/ZvAwe6+wYzm8rWv/NWGtsv1Hr/OvAd4ByiW6rPjNkvl+h6fqG7f2Vm18TTXjLFXT7VzPqa\n2f5mdkjdI5Edk4aVbixlysIpnPfyefz1/b9SXNG6OuEllSV8vu5zPi3+tFUT8EYcfCg777c/A3Ya\nyuHnX0h1TkIr8cZtUemiLV5/WfIln6/d/IX+/RXvU1FTUX83kURJSD104GXgBDMbCFH9bgu1zM1s\nhJllAMc1sf80whB9CHCr3L1uVm5DtdNfAM6sO6M2s8F1bTfgFeAHYf/Y2uIvEuUmISwf2cC+sdYT\nDcE3pjdQHILy7kSXCeLR4H5m1h/ICPPDriIa3o9VF7xXhffhhDjbS5p4b1v7KdGw+/bA+0RvwNtE\nQyuSROs2ruPyaVFxulmrZjGiYATf3fm7LT7OtMXTuGLaFQBcsu8lnDriVHKy4r/eXJFTS+1Ru9HT\nd+f3n/+Fg6sO5sy9EncX49qKtSxcv5Asy2L7nts3Otv6sB0O465Zd7GmYg29snsxevBoHKdXdi82\nVG/ggn0uoFc3XSmS5Bjx8dyH5u4+Atp5lru7zzGzq4AXQ/CuAs4juu78NFFhrCKiofGGXAPcZ2az\niL5gnB6zrq52en82105fEq7bvx3OqEuBH9HAML+7zzaza4HXzKyGaJj+DOBC4I7QZhbRcP05TfyO\nq83sTTP7CHiOaBg81vPAOWY2l2i4/J3GjhXnfoOJionVnZ1sMfrh7mvN7G7gI6LCYjPibC9p4kos\nY1Hx+W8A77j7yPCt5jp3Pz7RHYSukVgmXp+v+5xj/nPMptdX7n8lp7RwwmxlTSVXTruSKQunALDP\nwH24/bDbW3RL0qryVZz5/Jl8XhKd/f6i8Bf8eM8ft6gfcfe3upL7Z9/PHe/fAcCvvvkrfrDrD8jM\nyNxq21qvZXX5atZUrKGyppJbZt6CmfGbA35Dfrd8emX3atEXF5EYHWpGcyKEYeRSd/9zqvsiLRfv\n7KQKd68wM8wsx90/NrPdEtozaVBBTgETx05kVfkq3lj8BkcOObLFx8jJzOHUEacy9aup1HgNPxrx\nI3IzWnYpqF9uP24//Hb+XPRnduixA9/dpeWjBPGqrKnk7SVvb3r91pK3GDdsHHkZW99ClWEZDOg+\ngAzL4Kcv/pT5a+eTnZFNVkYWA7o3PhNfRKSzi/cM/QmiPOwXEw2zFwPd3P3oxHYvkq5n6LVeS63X\nxj3r2935dO2nnPvSuWRYBncefifD+g5rVdvTl02nW0aU+vXlhS9z+p6ntyrglVeVs75qPVW1VXTP\n6p6QGeQ1tTW8u/RdznvlPDItk3uOvIeRA5u7/BaNIiwsWch2+dtRkFegW9ikrdL+DL0lwjXylxtY\ndXict44lVEfvXyK0OJe7mX2LaFLB8+6+MSG9qicdA/rq8tVM+GgC6zau49yR57Jt/rbN7lOysYRL\nXr2E6cumA3Dw4IP507f+1Krc6K9++SoXvhrlbxiQN4BHvv9IkzXSG7O0dCmnPnsqK8tXcuROR3LV\nAVclJKhXVFewbuM6DKNPTh8VhJFUUECXDq0ls9z3DRl89iaqc56UYJ6OKqoruO2925gwZwJPzH+C\nC165gDXla5rdr1tGN3bsufn21aG9h246y26pfQbuw88Lf85RQ4/i7iPvZkXZCpaXLae6tmXZFN9c\n8iYry1cC8OLCF9lQXX9Cb/vIzcplm+7bMLD7QAVzEZEGxDvL/TfAD4DHw6L7zexRd/9DwnqWxqpq\nq1haunTT6+Vly6nx5lPk52XlccG+FzC873AyMzI5YqcjWh3c+uT24bQ9TmNd5TounXopM5bPoEe3\nHjx57JMtqpM+omDEpucDuw8kO6Nl/SnZWEJldSV5WXkdKjueiEhnE+819HnA1+sSAoR0ee+7e1Im\nxqXbkLu780nxJ5z5wpmUV5fzp0P+xOjBo1My+/qr9V9x9OObp0I8dPRD7DVgr7j3L6sq44t1XzCv\neB4HbXdQXJcO6hRXFHPbf2/jla9e4bjhx3HGnmeo1rZ0ZBpylw4t3iH3JWyZEScHWNz+3ekazIxh\nfYbx5LFP8sL/vMCowaNSditVfrd8vrltVPlsaO+hDOoxqMX779l/T44ffnyLgjnAyg0rmfTpJNZU\nrOHeD+9l/cb1LdpfRBpnZseY2RWNrCttZHlsIZKpZlaYyD42xsxGmlnCJ12b2S9jng8J97y39ZgD\nzOxdM3vPzA5uYP09ZrZHW9tpSLy3ra0DZpvZFKI0gEcA083sNgB3v7CpnWVrmRmZrZqE1t4Kcgu4\n8ZAbKa8uJycrJ6l9ys/OJ8MyqPVasjOyWzxcLyKNc/fJwORU96OVRgKFQEIKgoUqaUaUse+6dj78\n4cCH7v7TBtrNbGh5e4k3oD8RHnWmtn9XpDllVWV0y+jW7pPCUlUQpm9OX+77zn28tPAlvr/L9zXc\nLmnpjnNe2aoe+nl/O6xNmeLMbAhRxrN3gIOIspbdD/wWGEiU1nUPorzj55vZUKLqbj2AJ2OOY8Dt\nRCdpXwENTnY2syPDsXOAz4CfuHtjZ/n7ATeHtlYBZ7j7UotKsY4HsoH5wI9D+tUfAFcT5XBfR5Rn\n/XdAnpmNJsoh/+8G2rmG6D3dOfz8i7vfFtZdyuY87Pe4+1/Ce/YC8C5RYZvpoY33iYqs/ArIDNng\nDiIahR4XCtU09Htu9fsAuwI3huMWAgcSZe37e/i9zjOzPwA/d/ciMxtL9G8jkyj97uFmtj9RZbpc\noDy81/Ma6sNWfWrFbWt9gR3cfVaLdmyDdLuG3lI1tTUsWLeAm2fezPC+w/nJnj9p261hlaWwsRTM\noEdjRY2Sp9Zrt6iXLtJBtfgaegjmd7NlCdUNwNltCeohOM0H9iEKRjOAD4CzgGOI8ob8h80BfTIw\nyd0fMLPzgD+6ew8zOx74GTCWqMLZHOCn7j4pFC35OfAF0YToo9y9zMwuB3LqyojW61c34DWiQLjS\nzE4CvuPuZ5pZv7r7v0NQW+7ut4dMpGPdfbGZ9QkpVs+o63sT78E1RBXgNpVdBbYluhNrAlGKciMK\n4D8iyp+ygKis6zvhGKXuXpefvu49LXT3983sEWCyu/+jkfYb+3226LuZOXCSuz8SXte9rwuB/wKH\nuPvnZlYQSrr2Aja4e7WZfRv4mbv/T2PvQ6x4Z7lPJfpHkgXMBFaY2Zvufmk8+0vziiuKeWfpO6yt\nXMuROx1Jv7x+W6w756VzWLFhBW8sfoPd+u7WqvztAFSWwUeT4OlLoOcgOPN56NPySo4rN6zkgTkP\nUJBbwLhh4yjIbd1Z/uLSxdw7616G9R3G0UOPpk+uztIlrSSkHnrwubt/CGBms4GX3d1DgBxSb9tR\nhHKpwIPAH8PzQ4B/hbKqS8zslQbaOYDobP/NkMc9m6iWR0N2I6qdPiVsmwnU3dLztRD4+hCdvb8Q\nlr8JTAgB9HFapqGyq6OBJ9y9DMDMHgcOJrr8sLAumDfic3d/PzyfydbvY6zGfp/6aoDHGlh+APB6\nXTnYmDKzvYGJZjac6BJ33Pcmxzvk3tvdS0KRlgfc/eqQYF/ayTMLnuGPM6L/Y9OXTud3o363RbnR\nlo6kNGrjenj+CvBaKFkMRffDt68GoiQxpVWl5GbmUpBbQH52wwlrSipLuOrNq3hryVsAVNdWc/be\nZ7e4K6vKVzH+xfF8uT6qJNkzuyff3+X7rfzFRDqkRNVDhy1LjtbGvK6l4b/trf0jYsAUdz85zm1n\nu/uBDaybABzr7h+Es9gxAO5+jpl9E/guMDMM2ccr3rKrdZorIVv/eFvnl95sAg38Pg2oiKlDH4/f\nA6+6+3Fh1GBqvDvGO86ZZWaDiOrDPt2Cjkkcamtr+XTtp5teLyxZSFVN1abXfXP78vcj/s7owaM5\nY88zOGi7g1rfWEYW9Bu++fWgvQFYUbaCS6ZewvGTj+ey1y6jZGNJIweAaq9mTcXmRDjLNiyjtpl6\n6A1ytij/WpegRiSNNFb3vK310FvqTeCH4fmpMctfB04ys8zwN/7QBvZ9BxhlZsMAzCzfzHZtpJ15\nwAAzOzBs283M9gzregJLw7D8pj6Y2S7u/q67/4boevMONF86tSnTgGPNrLuZ5ROVkZ3WyLZVoT+t\n0eDv0wLvAIeE+Q2xZWZ7s/kusjNacsB4A/rviIYTPnP3GWa2M/BpM/tInDIyMhi/13iG9BpC35y+\n/PqAX9MrZ3OJz8yMTIb3Hc6fv/VnLtjngrZdP8/vD6c+CmP/CKc8AkO/BUBxZTGzV88GYO6auU0G\n1z45fbh29LUM6zOMfQfuy/i9xrfqGnjPnJ7cNOYmtu+xPQdsewDH7HJM8zuJdC6JqofeUhcRTcj6\nkKhMaJ0niP6WzwEeoIGhdHdfSRRY/hVGZt8Gdm+okZBB9ATgj2b2AVG57bozkF8TXc9+E/g4Zrc/\nmdmH4Zaxt4jmArwK7GFm74fr8HFz9/8SnT1PD+3d4+7vNbL5XcAsM/tnS9oIGvt94u3nSqJJdY+H\n96pu4t+NwPVm9h7xj6IDrZgUlwpdZVLc6vLV1HotfXL60C2ztV8aW2d52XLGPTmOsqoy8rLymHzs\n5CbvK6/1Woorism0zDZd966qqWLdxnVkZWRplrt0dK1KLJOIWe4iDYk3U9yuwP8B27j718xsb+CY\nZKV+7SoBPVE2VG1g0fpFzFo1i1HbjWLb/G0JE1Y2qa6pZtmGZXyw8gP26r8Xg/IHJf1LhUgHp0xx\n0qHFezp/N/D/iO6lw91nmdlDgHK5p8Dq8tV8uf5LBnYfSEFuAXlZTc3bgNUVqznx6ROp8RoGdh/I\nw999eKtSqVmZWWzfc3u277l9IrueFtZUrKGmtoZe2b1SluFPJNUsKqs9tN7iy929sdnerW3nJ0SX\nDGK96e7ntWc7TbR/B9FdArFudff7k9F+S8Qb0Lu7+/R6Z3UtK8sl7WJNxRoue+0yZi6fSZZl8e/v\n/5td+zY2PyWyrGzZpuIvKzasiKsQjDRsxYYVXPDKBSwpXcJ1o69j/233V1CXLsndj0tSO/cTJc1J\niWR9cWgP8c5kWmVmuxBuewi5fpc2vYskQk1tDTOXzwSi2eZFy5q/FLFL7104YNABdMvoxrlfP5fu\nWfVvi5V4Pf/F88xZPYe1lWu5+q2rm7wbQEQkmeI9Qz+PaDbg7ma2GPic1k3TlzbKzszmmF2OYfJn\nk+nZrScHD94q9/9WCvKifO3VtdXkZuVucX+7tMzOvXfe9HynXjuRldGiSagiIgnT5KQ4M7vI3W81\ns1Hu/ma4py/D3ZNaFkuT4rZUXFFMaVUpOZk59MvtR2ZGZqq71GWsq1zHx2s+5sv1X3Lo9ofSv3vq\nC+xI0mhSnHRozQX09919pJn91933TWK/tqCALiIdgAK6dGjNXUOfa2afAruZ2ayYx4dK/Soi0nmZ\n2bHtWZfbzArrSmqngsXUf7d6NcnN7FkzS/tEF01eAHT3k81sW6IscUrjJdIO1m9cz5LSJSwpXcJe\nA/ZKag16kRjHEqXyntMeB3P3IiBlQ6n16r/Xr0neWOrXtNLsjB53XwZ8PQl9EekSZq2cxTkvnQPA\nbn13464j7kpZTXpJvJtO+t5WmeIu+/fTbc4UZ2Y/Ai4kqn72LnAu8FfgG0RFRSa5+9Vh2xuITsqq\ngReJqpodA3zLzK4C/sfdP2ugjbhqmLv7IWY2hqjO9/daUtM7FDY5jiiH+WDgH+7+27DuP0S53XOJ\n7v2+KyxvqI74GUAhcA9b1ySfS1TSdJWZnUZUvtSBWe7+4/jf9Y6tyYBuZo+4+4kh/2/sxXYD3N33\nTmjvRNLQ64te3/R8XvE8qmqrmthaOrMQzGProe8E3H3TSd+jLUHdzEYAJwGj3L3KzO4kuvPoV6Gm\ndibwcsjquZgoYO4eyqvW1RyfDDzt7pOaaOpxd787tPkHonrrtwO/IapzvriRoeyPgYNjanpfx+by\nrQ3Zn6js6gZghpk9E874zwy/T15Y/hjRpeK7iakjHnugUMv8N2xZk7zufdsTuIqoJvqq+vt2ds2d\noddl5/leaw5uZl8QVc2pAardvTC8gf8mqjP7BXCiuxc3dgyRdHPssGOZ9MkkNtZu5PAdDycnU4lp\n0lii6qEfDuxHFOQgOiNfAZxoZuOJ/rYPIqpjPgeoAO41s6dpWcXM1tYwb2lN7ynuvho21S8fTTR8\nf6GZ1SWw2QEYDgyg4Tri8TgMeNTdV7Vi3w6vuWvoS8PPhW1o49C6Ny+4AnjZ3W8IExiuAC5vw/FF\nOpWde+/Ms8c/S3l1Ob1yerWpuI10eImqh27ARHe/ctOCqAznFOAb7l5sZhOA3HCWvD/Rl4ATgPOJ\nAls8JtC6GuYtreld/3YrD0P43wYODMP8U4mG3qURTc5yN7P1ZlbSwGO9mbU2RdY4YGJ4PpFoYoZI\nl5GTlcM2+dswpPcQCnLTasRPtpaoeugvAyeY2UDYVEt7R6AMWGdm2wBHhXU9gN7u/ixwCZvnRMVT\nc7wlNcxjtbSm9xFmVhCG1o8lGgHoDRSHYL47cEDYtrE64vF4BfiBmfVrxb4dXpMB3d17unuvBh49\n3b1XU/vWHQJ40cxmhmEgiCq21aWNXQZs04b+i3R66yrWsap8FdW1Ko+QhhJSD93d5xBdC34x3EI8\nBagE3iO6fv0QUVCEKCg/HbZ7A7g0LH8Y+H/h1q5dGmmqJTXMY7W0pvd04DFgFvBYuH7+PJBlZnOB\nG4gCeVN1xJvl7rOBa4HXwr43x7tvZ5DQeuhmNjhMmhhI9A/uAmCyu/eJ2abY3fs2sO94og+NHXfc\ncb+FC9sy6i/SMa3asIor37iSpWVLuXbUtezZf0+lk+24WpVYJlGz3NNF3ez0ugls0noJDehbNGR2\nDVAKnA2McfelZjYImOruuzW1rzLFSbqa8NEEbpp5EwDb99ieB496UOlkOy5liksABfT2E2+1tRYz\ns3wz61n3HDgS+Ijoxv/Tw2anA08mqg8iHd22+dtuej6g+wDl5ZeUMLM7zOz9eo+ftHMb32mgjSfc\nfYKCeftI2Bm6me0MPBFeZgEPufu1YTLCI0TDTwuJbltr8tYBnaFLulpbsZa3lrzFl+u/5PjhxzOw\n+8BUd0kapzN06dCSNuTeFgrojSuuKGbR+kXkd8tnQPcBKo0qkjgK6NKhJWzIXRKvrKqMu2fdzSnP\nnsK4J8fx7tJ3U90lERFJEQX0TqyiuoI3lryx6fUrX75CTW1NCnskIiKpooDeifXo1oMz9jwDgJzM\nHE4ecbImVYlIm5nZkHCPeXPbnBLzOqXlUyW+G/6lg8rJyuHInY7kwO0OJNMy6ZOjFKIikjRDgFMI\nOelTXT5VdIbe6fXI7sGg/EEM7D6Q7MzsVHdHRJIgnB1/bGb/NLO5ZjbJzLqb2eEh89uHZnafmeWE\n7b8wsxvD8ulmNiwsn2BmJ8Qct7SRtqaZ2X/D46Cw6gbg4HD72SVmNiYUfyGkcf2Pmc0ys3csqvqG\nmV0T+jXVzBaY2YWJfq+6EgV0EZHOaTfgTncfAZQQpXSdAJzk7nsRjcD+LGb7dWH5X4G/tKCdFcAR\n7r4vUcnWumH1K4Bp7j7S3W+pt89vgfdCie1fAg/ErNsd+A5RydSrQ554aQcK6JJS6zeup7KmMtXd\nEOmMvnL3unzt/yCqpva5u38Slk0EDonZ/l8xPw9sQTvdgLvN7EPgUaKSrM0ZDTwI4O6vAP3MrK7+\nxzPuXhmqcK5A9TzajQK6pERNbQ2fFH/CZa9dxs1FN1NcUZzqLol0NvWTiKxtwfZ1z6sJccDMMoCG\nrttdAiwnqtJW2Mg2LRH7Db4GzeVqNwrokhLFlcWc+9K5vL3kbR76+CFeWvhSqrsk0tnsaGZ1Z9qn\nEE1IG1J3fRz4MfBazPYnxfx8Ozz/AqirZX4M0dl4fb2Bpe5eG45ZdytNU+VXpxHKrYa65qvcvbUl\ntyVO+mYkqVHv3MJMSbhEWmgecJ6Z3QfMAS4kKjH6qJllATOAv8Vs3zeUUK0ETg7L7gaeDKVEnyeq\np17fncBjZnZavW1mATVh3wlEpVvrXAPcF9rbwOb6HZJASv0qKVHrtSxYu4A/F/2Zob2HMn7v8fTN\n3aqKrkhH0mG+y3R3xQAAEaNJREFUdZrZEOBpd/9anNt/QVTRbFUCuyUppjN0icvq8tUsLl3Mtvnb\nUpBTQFZm2/7pZFgGw/oO48/f+jPZmdm65U5EpI0U0NNAdW01WRmJ+yhXla/ipy/+lM/WfkZ+t3z+\nM+4/W5T9bIse2T3a5TgiXYm7fwHEdXYeth+SsM5Ih6FJcZ1YcUUx9390P9e8dQ2L1y9OWDsbazby\n2drPgKggzMKShQlrS0REWkcBvRN7a8lb3DzzZp787EnOf+V8VpevTkg7uVm5jNpuFADb5W/Hzr13\nTkg7IiLSehpy78RKN27O0lhWVUaiJjgW5BZw3cHXsaFqA7lZufTP65+QdkREpPUU0DuxI3Y6gg9W\nfcCXJV/yq2/+KqGzxAtyCyjILUjY8UVEpG1021onV1ZVRlVNFb1yepFhuoIikkAd5rY1ADMbC9xK\nlOjlHne/IcVdkhTTGXonl98tv+HcTiKStswsE7gDOAJYBMwws8nuPie1PZNU0imdiEjnsz8w390X\nuPtG4GFgXIr7JCmmM3QRkQQrLCzMAvoDq4qKiqrb4ZCDga9iXi8CvtkOx5VOTGfoIiIJVFhYeBCw\nEvgcWBlei7Q7BXRpV2sr1vLUZ0/x1/f+yvKy5anujkhKhTPzZ4A+QG74+UxhYWFmkzs2bzGwQ8zr\n7cMy6cI05C7tasayGfzyjV8C8PaSt7n98Ns7/e1uq8pXsWDdAnbsuSP9cvvRLVOzECVu/YkCeaxc\nYACwrA3HnQEMN7OhRIH8h0QlVKULU0CXdrV8w+az8pXlK6mtrU1hb9pudflqznrhLBasW0BeVh6T\nj53cbnnspUtYBVSwZVCvIBqCbzV3rzaz84EXiG5bu8/dZ7flmNL5achd2tXYoWMZPXg0Q3sN5cZD\nbqRPTp9Ud6lNqmqrWLBuAQDl1eUsKV2S4h5JZxImwH0XWEsUyNcC3y0qKqpp67Hd/Vl339Xdd3H3\na9t6POn8dIYu7ap/Xn9uOPgGqmur6Z3TO6FV4JIhNzOX44YdxxPzn2DXvruyU6+dUt0l6WSKiore\nKiws7E80zL6yPYK5SEOUKU6kGWsr1lJZU0lWRhb98vqlujuSOh0qU5x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"application/javascript": [ + "window[\"c9034228-e91d-11e8-a4a0-0242ac1c0002\"] = google.colab.output.getActiveOutputArea();\n", + "//# sourceURL=js_6765c56afe" + ], + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [ + "id1_content_0", + "outputarea_id1" + ] + } + }, + { + "output_type": "display_data", + "data": { + "application/javascript": [ + "window[\"c90387e2-e91d-11e8-a4a0-0242ac1c0002\"] = document.querySelector(\"#id1_content_0\");\n", + "//# sourceURL=js_093ee4cef4" + ], + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [ + "id1_content_0", + "outputarea_id1" + ] + } + }, + { + "output_type": "display_data", + "data": { + "application/javascript": [ + "window[\"c903ca40-e91d-11e8-a4a0-0242ac1c0002\"] = google.colab.output.setActiveOutputArea(window[\"c90387e2-e91d-11e8-a4a0-0242ac1c0002\"]);\n", + "//# sourceURL=js_318a3645aa" + ], + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [ + "id1_content_0", + "outputarea_id1" + ] + } + }, + { + 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9ATCxF9oiA0j9vI9ZetXVAHxy2ulsMe0/ZOW3ukCViIikod2AbmZ3ufuRYVZk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\nmgSJYWxasJcr5rVcj703OIcNY/Avn6L+vffJvGo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uS2Ar92XnFeD1GNcdLCK/xvtCVgR8Tn8L6KraduPXuv/ABcCrSWuVMb2gbbOb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\nFTMZmjWUa8ddSygeIt2dzuF9DwegLlLH6rrVOMSBoz5KxZJ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lU0VkENCgqv8C/gLsAwwTkR3dVc4EPnZfLwf2dF+f2Gw3tXS+3GkOsM4N5ofg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\nUAjam7sdrIJoI6RkQCCzxbZ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ASSv720QNEhE/cC9wkqruCTwG/Nn9+EVV/ZGq7gosBM53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\nMUw7WEDvg0SEQcFBfLBl56r6N9a/QW3MVp4bk2DbaTplrNL+EqqHA+c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2rW0r3bbW/kRCMYK1UcKBKJn5rrRk6Yr7fMSrawi6vSzwG6YtruLI4cV8u6iC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\n8K4AGDKkLWoY+Et2q0qWk5bTjq1puUQH881lVVTX1ZOdEaB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Pnpz0fzdidTpx5+Zx9KVXEZ01CxIJ4jpOVXhn5beKkIeN1QECBjvZt/4RU+fO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\nIL9nBfTP1n/GD6b+gPzsfG4ZdwvD+gxLd5Ok59M1dOnW2rp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FG9w7516cZicvHvcixWnFu6We+xjVTaHs1VQLXVF2UBGq4PzpF5LjyKHfqD6M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\nbAWe+cDxEbG0LcfvCXpSMAc4crsjqa+vZ/HKxZw2+jQG9xv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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [ + "id1_content_5", + "outputarea_id1", + "user_output" + ] + } + }, + { + "output_type": "display_data", + "data": { + "application/javascript": [ + "window[\"cb7a72c4-e91d-11e8-a4a0-0242ac1c0002\"] = google.colab.output.setActiveOutputArea(window[\"cb16ede4-e91d-11e8-a4a0-0242ac1c0002\"]);\n", + "//# sourceURL=js_d7c061e426" + ], + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [ + "id1_content_5", + "outputarea_id1" + ] + } + } + ] + }, + { + "metadata": { + "id": "38Pn_TGIvQX6", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Stretch goals\n", + "- [ipywidgets](https://github.com/jupyter-widgets/ipywidgets)\n", + "- [Matplotlib animation](https://matplotlib.org/examples/animation/index.html)\n", + "- [Connected scatter plots](http://www.thefunctionalart.com/2012/09/in-praise-of-connected-scatter-plots.html)\n", + "- [Idyll markup language](https://idyll-lang.org/) for \"scrollytelling\"" + ] + }, + { + "metadata": { + "id": "HM7VL4I33T0R", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Homework" + ] + }, + { + "metadata": { + "id": "QPChwEIP_ZDW", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Hypothesis is that landlocked countries recovered slower in terms of income and life expectancy compared to those that had a coastline." + ] + }, + { + "metadata": { + "id": "B7QlCcqpu8Ay", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "b9cf7c0f-4814-433f-9f1f-b34ae75e245b" + }, + "cell_type": "code", + "source": [ + "# Just to make sure, get everything again\n", + "income = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--income_per_person_gdppercapita_ppp_inflation_adjusted--by--geo--time.csv')\n", + "lifespan = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--life_expectancy_years--by--geo--time.csv')\n", + "population = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--datapoints--population_total--by--geo--time.csv')\n", + "entities = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--entities--geo--country.csv')\n", + "concepts = pd.read_csv('https://raw.githubusercontent.com/open-numbers/ddf--gapminder--systema_globalis/master/ddf--concepts.csv')\n", + "\n", + "income.shape, lifespan.shape, population.shape, entities.shape, concepts.shape" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "((44268, 3), (44370, 3), (51939, 3), (273, 33), (590, 16))" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + } + ] + }, + { + "metadata": { + "id": "5ZKT1hJ635F-", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 142 + }, + "outputId": "6ccf209d-d828-4485-dae6-21e838744ac7" + }, + "cell_type": "code", + "source": [ + "income.head().T # contains geo, time (year), income_per_person_gdppercapita_ppp_inflation_adjusted (income)" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " country landlocked\n", + "0 abkh NaN\n", + "1 abw coastline\n", + "2 afg landlocked\n", + "3 ago coastline\n", + "4 aia coastline" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 100 + } + ] + }, + { + "metadata": { + "id": "AsXrUIZd-2Df", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "885b3296-34fd-44a0-a606-9885ec0391cf" + }, + "cell_type": "code", + "source": [ + "countries_landlocked.isna().sum().sum()" + ], + "execution_count": 101, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "18" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 101 + } + ] + }, + { + "metadata": { + "id": "lvNFF8qV-8uP", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "3868fe7a-a4b7-4d2c-ebb8-c86dbdeeb3d4" + }, + "cell_type": "code", + "source": [ + "countries_landlocked.shape" + ], + "execution_count": 102, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(273, 2)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 102 + } + ] + }, + { + "metadata": { + "id": "QqIvgFJs_Blv", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "b000d743-ab2a-4623-a343-74a1f9d4d272" + }, + "cell_type": "code", + "source": [ + "# We're losing 18 / 223 = 6.5% of countries if we consider dropping those rows\n", + "# that have landlocked column of NaN. It's not much data, so let's do it - \n", + "# should not matter for testing our hypothesis.\n", + "countries_landlocked.dropna(inplace = True)\n", + "countries_landlocked.shape" + ], + "execution_count": 103, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(255, 2)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 103 + } + ] + }, + { + "metadata": { + "id": "GKhvHhYXAgfK", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 68 + }, + "outputId": "607d6090-bd05-49b1-e26b-d2a149109417" + }, + "cell_type": "code", + "source": [ + "# This tells us if there are different spellings with the same\n", + "# meaning (landlocked/coastline)\n", + "countries_landlocked['landlocked'].value_counts()" + ], + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "coastline 208\n", + "landlocked 47\n", + "Name: landlocked, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 10 + } + ] + }, + { + "metadata": { + "id": "mRHi2WRqBU7B", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 2071 + }, + "outputId": "5dde089a-5378-4ebb-8df3-b2bed07df499" + }, + "cell_type": "code", + "source": [ + "# Replace 'landlocked' with true, 'coastline' with false\n", + "countries_landlocked. \\\n", + " replace({'landlocked': { 'landlocked': True, 'coastline': False}},\n", + " inplace = True)\n", + "# countries_landlocked.head()\n", + "countries_landlocked" + ], + "execution_count": 48, + "outputs": [ + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.6/dist-packages/pandas/core/generic.py:4550: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n", + " regex=regex)\n" + ], + "name": "stderr" + }, + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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countrylandlocked
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6alaFalse
7albFalse
8andTrue
9antFalse
10areFalse
11argFalse
12armTrue
13asmFalse
15atgFalse
16ausFalse
17autTrue
18azeTrue
19bdiTrue
20belFalse
21benFalse
22bfaTrue
23bgdFalse
24bgrFalse
25bhrFalse
26bhsFalse
27bihFalse
28blrTrue
29blzFalse
30bmuFalse
31bolTrue
.........
241tkmTrue
242tlsFalse
243tonFalse
245ttoFalse
246tunFalse
247turFalse
248tuvFalse
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251ugaTrue
252ukrFalse
253uryFalse
254usaFalse
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258vctFalse
259venFalse
260vgbFalse
261virFalse
262vnmFalse
263vutFalse
264wlfFalse
265wsmFalse
266yemFalse
267yem_northFalse
268yem_southFalse
269yugFalse
270zafFalse
271zmbTrue
272zweTrue
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" + ], + "text/plain": [ + " country landlocked geo time life_expectancy_years\n", + "0 abw False abw 1800 34.42\n", + "1 abw False abw 1801 34.42\n", + "2 abw False abw 1802 34.42\n", + "3 abw False abw 1803 34.42\n", + "4 abw False abw 1804 34.42" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 55 + } + ] + }, + { + "metadata": { + "id": "FABUKD2yYmBz", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 80 + }, + "outputId": "1fcfd78c-1a93-4576-b2aa-1261ec0acb53" + }, + "cell_type": "code", + "source": [ + "lifespan_and_landlocked[(lifespan_and_landlocked.country == 'abw') &\n", + " (lifespan_and_landlocked.time == 1800)]" + ], + "execution_count": 56, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " country landlocked time life_expectancy_years geo \\\n", + "0 abw False 1800 34.42 abw \n", + "1 abw False 1801 34.42 abw \n", + "2 abw False 1802 34.42 abw \n", + "3 abw False 1803 34.42 abw \n", + "4 abw False 1804 34.42 abw \n", + "\n", + " income_per_person_gdppercapita_ppp_inflation_adjusted \n", + "0 833 \n", + "1 833 \n", + "2 833 \n", + "3 833 \n", + "4 833 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 61 + } + ] + }, + { + "metadata": { + "id": "91wrZyS_ZhxE", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "outputId": "a4af583c-85be-49ac-e4f9-030f1d710df2" + }, + "cell_type": "code", + "source": [ + "countries.drop(columns = ['geo'], inplace = True)\n", + "countries.head()" + ], + "execution_count": 63, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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countrylandlockedyearlifespanincome
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219afgTrue180028.21603
438agoFalse180026.98618
657albFalse180035.40667
923areFalse180030.70998
1142argFalse180033.201507
1361armTrue180034.00514
1580atgFalse180033.54757
1799ausFalse180034.05814
2018autTrue180034.401847
2237azeTrue180029.17775
2456bdiTrue180031.50418
2675belFalse180040.002411
2894benFalse180031.00597
3113bfaTrue180029.20480
3332bgdFalse180025.50876
3551bgrFalse180035.801088
3770bhrFalse180030.301235
3989bhsFalse180035.181445
4208bihFalse180035.10669
4427blrTrue180036.20608
4646blzFalse180026.50579
4912bolTrue180033.00854
5131braFalse180032.001108
5350brbFalse180032.12913
5569brnFalse180029.201512
5788btnTrue180028.80629
6007bwaTrue180033.60397
6226cafTrue180030.00424
6445canFalse180039.001313
..................
35222sweFalse180032.161413
35441swzTrue180032.30490
35660sycFalse180037.00792
35879syrFalse180031.101080
36098tcdTrue180030.90418
36317tgoFalse180031.30682
36536thaFalse180030.40931
36755tjkTrue180024.24556
36974tkmTrue180024.00943
37193tlsFalse180028.95521
37412tonFalse180028.20663
37631ttoFalse180032.901230
37850tunFalse180028.80715
38069turFalse180035.001221
38288twnFalse180028.30995
38505tzaFalse180032.20562
38724ugaTrue180025.30464
38943ukrFalse180036.60763
39162uryFalse180032.901757
39381usaFalse180039.412127
39600uzbTrue180026.93502
39819vctFalse180025.99838
40038venFalse180032.20682
40257vnmFalse180032.00861
40476vutFalse180024.30585
40695wsmFalse180025.401400
40914yemFalse180023.39877
41133zafFalse180033.501479
41352zmbTrue180032.60663
41571zweTrue180033.70869
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190 rows × 5 columns

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" + ], + "text/plain": [ + " country landlocked year lifespan income\n", + "0 abw False 1800 34.42 833\n", + "219 afg True 1800 28.21 603\n", + "438 ago False 1800 26.98 618\n", + "657 alb False 1800 35.40 667\n", + "923 are False 1800 30.70 998\n", + "1142 arg False 1800 33.20 1507\n", + "1361 arm True 1800 34.00 514\n", + "1580 atg False 1800 33.54 757\n", + "1799 aus False 1800 34.05 814\n", + "2018 aut True 1800 34.40 1847\n", + "2237 aze True 1800 29.17 775\n", + "2456 bdi True 1800 31.50 418\n", + "2675 bel False 1800 40.00 2411\n", + "2894 ben False 1800 31.00 597\n", + "3113 bfa True 1800 29.20 480\n", + "3332 bgd False 1800 25.50 876\n", + "3551 bgr False 1800 35.80 1088\n", + "3770 bhr False 1800 30.30 1235\n", + "3989 bhs False 1800 35.18 1445\n", + "4208 bih False 1800 35.10 669\n", + "4427 blr True 1800 36.20 608\n", + "4646 blz False 1800 26.50 579\n", + "4912 bol True 1800 33.00 854\n", + "5131 bra False 1800 32.00 1108\n", + "5350 brb False 1800 32.12 913\n", + "5569 brn False 1800 29.20 1512\n", + "5788 btn True 1800 28.80 629\n", + "6007 bwa True 1800 33.60 397\n", + "6226 caf True 1800 30.00 424\n", + "6445 can False 1800 39.00 1313\n", + "... ... ... ... ... ...\n", + "35222 swe False 1800 32.16 1413\n", + "35441 swz True 1800 32.30 490\n", + "35660 syc False 1800 37.00 792\n", + "35879 syr False 1800 31.10 1080\n", + "36098 tcd True 1800 30.90 418\n", + "36317 tgo False 1800 31.30 682\n", + "36536 tha False 1800 30.40 931\n", + "36755 tjk True 1800 24.24 556\n", + "36974 tkm True 1800 24.00 943\n", + "37193 tls False 1800 28.95 521\n", + "37412 ton False 1800 28.20 663\n", + "37631 tto False 1800 32.90 1230\n", + "37850 tun False 1800 28.80 715\n", + "38069 tur False 1800 35.00 1221\n", + "38288 twn False 1800 28.30 995\n", + "38505 tza False 1800 32.20 562\n", + "38724 uga True 1800 25.30 464\n", + "38943 ukr False 1800 36.60 763\n", + "39162 ury False 1800 32.90 1757\n", + "39381 usa False 1800 39.41 2127\n", + "39600 uzb True 1800 26.93 502\n", + "39819 vct False 1800 25.99 838\n", + "40038 ven False 1800 32.20 682\n", + "40257 vnm False 1800 32.00 861\n", + "40476 vut False 1800 24.30 585\n", + "40695 wsm False 1800 25.40 1400\n", + "40914 yem False 1800 23.39 877\n", + "41133 zaf False 1800 33.50 1479\n", + "41352 zmb True 1800 32.60 663\n", + "41571 zwe True 1800 33.70 869\n", + "\n", + "[190 rows x 5 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 70 + } + ] + }, + { + "metadata": { + "id": "btWE-SHwdnsQ", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "sns.relplot?" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "ZLIXmL4IMl1Q", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + }, + "outputId": "1d9dd519-106b-4210-8502-cfc751854b8f" + }, + "cell_type": "code", + "source": [ + "import matplotlib.ticker as ticker\n", + "\n", + "# Let's take 1910 so the 1918 flu does not change the trend.\n", + "# Idea is to show the trend over decades, not due to a\n", + "# particular instance.\n", + "sample_years = [1818, 1910, 2018]\n", + "sampled = countries[countries.year.isin(sample_years)]\n", + "ax = sns.relplot(x = 'income', y = 'lifespan', hue = 'landlocked',\n", + " col = 'year', data = sampled);\n", + "plt.xscale('log')\n", + "plt.xticks([1000, 10000, 100000], \n", + " ['1000', '10,000', '100,000']);\n" + ], + "execution_count": 97, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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UG2/PHMET87ZhNuq4dVJ30p1mqr1BHp67Na7vk9/mcvHgtvTOcrFge1msXa9T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\ntuTR/GMn7TIxVVu2Z8MO1jRu5az/epSGp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