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886 lines
266 KiB
886 lines
266 KiB
2 years ago
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"cells": [
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"___\n",
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"\n",
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"<a href='http://www.pieriandata.com'><img src='../Pierian_Data_Logo.png'/></a>\n",
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"___\n",
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"<center><em>Copyright by Pierian Data Inc.</em></center>\n",
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"<center><em>For more information, visit us at <a href='http://www.pieriandata.com'>www.pieriandata.com</a></em></center>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Matrix Plots\n",
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"\n",
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"**NOTE: Make sure to watch the video lecture, not all datasets are well suited for a heatmap or clustermap.**"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Imports"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## The Data\n",
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"\n",
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"World Population Prospects publishes United Nations population estimates for all world countries and every year from 1950 to 2020, as well as projections for different scenarios (low, middle and high variants) from 2020 to 2100. The figures presented here correspond to middle variant projections for the given year.\n",
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"\n",
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"https://www.ined.fr/en/everything_about_population/data/all-countries/?lst_continent=900&lst_pays=926\n",
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"\n",
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"Source : Estimates for the current year based on data from the World Population Prospects. United Nations."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# 2020 Projections\n",
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"df = pd.read_csv('country_table.csv')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Countries</th>\n",
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" <th>Birth rate</th>\n",
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" <th>Mortality rate</th>\n",
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" <th>Life expectancy</th>\n",
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" <th>Infant mortality rate</th>\n",
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" <th>Growth rate</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>AFRICA</td>\n",
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" <td>32.577</td>\n",
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" <td>7.837</td>\n",
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" <td>63.472</td>\n",
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" <td>44.215</td>\n",
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" <td>24.40</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>ASIA</td>\n",
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" <td>15.796</td>\n",
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" <td>7.030</td>\n",
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" <td>73.787</td>\n",
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" <td>23.185</td>\n",
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" <td>8.44</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>EUROPE</td>\n",
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" <td>10.118</td>\n",
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" <td>11.163</td>\n",
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" <td>78.740</td>\n",
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" <td>3.750</td>\n",
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" <td>0.38</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>LATIN AMERICA AND THE CARIBBEAN</td>\n",
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" <td>15.886</td>\n",
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" <td>6.444</td>\n",
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" <td>75.649</td>\n",
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" <td>14.570</td>\n",
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" <td>8.89</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>NORTHERN AMERICA</td>\n",
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" <td>11.780</td>\n",
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" <td>8.833</td>\n",
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" <td>79.269</td>\n",
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" <td>5.563</td>\n",
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" <td>6.11</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td>OCEANIA</td>\n",
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" <td>16.235</td>\n",
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" <td>6.788</td>\n",
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" <td>78.880</td>\n",
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" <td>16.939</td>\n",
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" <td>12.79</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>WORLD</td>\n",
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" <td>17.963</td>\n",
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" <td>7.601</td>\n",
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" <td>72.766</td>\n",
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" <td>27.492</td>\n",
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" <td>10.36</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Countries Birth rate Mortality rate \\\n",
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"0 AFRICA 32.577 7.837 \n",
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"1 ASIA 15.796 7.030 \n",
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"2 EUROPE 10.118 11.163 \n",
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"3 LATIN AMERICA AND THE CARIBBEAN 15.886 6.444 \n",
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"4 NORTHERN AMERICA 11.780 8.833 \n",
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"5 OCEANIA 16.235 6.788 \n",
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"6 WORLD 17.963 7.601 \n",
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"\n",
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" Life expectancy Infant mortality rate Growth rate \n",
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"0 63.472 44.215 24.40 \n",
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"1 73.787 23.185 8.44 \n",
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"2 78.740 3.750 0.38 \n",
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"3 75.649 14.570 8.89 \n",
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"4 79.269 5.563 6.11 \n",
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"5 78.880 16.939 12.79 \n",
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"6 72.766 27.492 10.36 "
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Heatmap"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"df = df.set_index('Countries')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Birth rate</th>\n",
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" <th>Mortality rate</th>\n",
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" <th>Life expectancy</th>\n",
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" <th>Infant mortality rate</th>\n",
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" <th>Growth rate</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>Countries</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>AFRICA</th>\n",
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" <td>32.577</td>\n",
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" <td>7.837</td>\n",
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" <td>63.472</td>\n",
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" <td>44.215</td>\n",
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" <td>24.40</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>ASIA</th>\n",
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" <td>15.796</td>\n",
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" <td>7.030</td>\n",
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" <td>73.787</td>\n",
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" <td>23.185</td>\n",
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" <td>8.44</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>EUROPE</th>\n",
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" <td>10.118</td>\n",
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" <td>11.163</td>\n",
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" <td>78.740</td>\n",
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" <td>3.750</td>\n",
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" <td>0.38</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>LATIN AMERICA AND THE CARIBBEAN</th>\n",
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" <td>15.886</td>\n",
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" <td>6.444</td>\n",
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" <td>75.649</td>\n",
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" <td>14.570</td>\n",
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" <td>8.89</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>NORTHERN AMERICA</th>\n",
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" <td>11.780</td>\n",
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" <td>8.833</td>\n",
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" <td>79.269</td>\n",
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" <td>5.563</td>\n",
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" <td>6.11</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>OCEANIA</th>\n",
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" <td>16.235</td>\n",
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" <td>6.788</td>\n",
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" <td>78.880</td>\n",
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" <td>16.939</td>\n",
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" <td>12.79</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>WORLD</th>\n",
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" <td>17.963</td>\n",
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" <td>7.601</td>\n",
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" <td>72.766</td>\n",
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" <td>27.492</td>\n",
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" <td>10.36</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Birth rate Mortality rate Life expectancy \\\n",
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"Countries \n",
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"AFRICA 32.577 7.837 63.472 \n",
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"ASIA 15.796 7.030 73.787 \n",
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"EUROPE 10.118 11.163 78.740 \n",
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"LATIN AMERICA AND THE CARIBBEAN 15.886 6.444 75.649 \n",
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"NORTHERN AMERICA 11.780 8.833 79.269 \n",
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"OCEANIA 16.235 6.788 78.880 \n",
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"WORLD 17.963 7.601 72.766 \n",
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"\n",
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" Infant mortality rate Growth rate \n",
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"Countries \n",
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"AFRICA 44.215 24.40 \n",
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"ASIA 23.185 8.44 \n",
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"EUROPE 3.750 0.38 \n",
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"LATIN AMERICA AND THE CARIBBEAN 14.570 8.89 \n",
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"NORTHERN AMERICA 5.563 6.11 \n",
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"OCEANIA 16.939 12.79 \n",
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"WORLD 27.492 10.36 "
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
|
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"source": [
|
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"df"
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]
|
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},
|
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{
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||
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"cell_type": "code",
|
||
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"execution_count": 6,
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"metadata": {},
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||
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"outputs": [
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{
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"data": {
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"text/plain": [
|
||
|
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"<AxesSubplot:ylabel='Countries'>"
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]
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},
|
||
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"execution_count": 6,
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||
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"metadata": {},
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||
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"output_type": "execute_result"
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|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Clearly shows life expectancy in different units\n",
|
||
|
|
"sns.heatmap(df)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"rates = df.drop('Life expectancy',axis=1)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:ylabel='Countries'>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.heatmap(rates)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:ylabel='Countries'>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.heatmap(rates,linewidth=0.5)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:ylabel='Countries'>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.heatmap(rates,linewidth=0.5,annot=True)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:ylabel='Countries'>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Note how its not palette here\n",
|
||
|
|
"sns.heatmap(rates,linewidth=0.5,annot=True,cmap='viridis')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:ylabel='Countries'>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Set colorbar based on value from dataset\n",
|
||
|
|
"sns.heatmap(rates,linewidth=0.5,annot=True,cmap='viridis',center=40)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:ylabel='Countries'>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Set colorbar based on value from dataset\n",
|
||
|
|
"sns.heatmap(rates,linewidth=0.5,annot=True,cmap='viridis',center=1)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Clustermap\n",
|
||
|
|
"\n",
|
||
|
|
"Plot a matrix dataset as a hierarchically-clustered heatmap."
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<seaborn.matrix.ClusterGrid at 0x158e27976c8>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 720x720 with 4 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.clustermap(rates)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<seaborn.matrix.ClusterGrid at 0x158e235c9c8>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 720x720 with 4 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.clustermap(rates,col_cluster=False)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 16,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<seaborn.matrix.ClusterGrid at 0x158e2ffc848>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 16,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 864x576 with 4 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.clustermap(rates,col_cluster=False,figsize=(12,8),cbar_pos=(-0.1, .2, .03, .4))"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"rates.index.set_names('',inplace=True)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/html": [
|
||
|
|
"<div>\n",
|
||
|
|
"<style scoped>\n",
|
||
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
||
|
|
" vertical-align: middle;\n",
|
||
|
|
" }\n",
|
||
|
|
"\n",
|
||
|
|
" .dataframe tbody tr th {\n",
|
||
|
|
" vertical-align: top;\n",
|
||
|
|
" }\n",
|
||
|
|
"\n",
|
||
|
|
" .dataframe thead th {\n",
|
||
|
|
" text-align: right;\n",
|
||
|
|
" }\n",
|
||
|
|
"</style>\n",
|
||
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
||
|
|
" <thead>\n",
|
||
|
|
" <tr style=\"text-align: right;\">\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th>Birth rate</th>\n",
|
||
|
|
" <th>Mortality rate</th>\n",
|
||
|
|
" <th>Infant mortality rate</th>\n",
|
||
|
|
" <th>Growth rate</th>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" <th></th>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" </thead>\n",
|
||
|
|
" <tbody>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>AFRICA</th>\n",
|
||
|
|
" <td>32.577</td>\n",
|
||
|
|
" <td>7.837</td>\n",
|
||
|
|
" <td>44.215</td>\n",
|
||
|
|
" <td>24.40</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>ASIA</th>\n",
|
||
|
|
" <td>15.796</td>\n",
|
||
|
|
" <td>7.030</td>\n",
|
||
|
|
" <td>23.185</td>\n",
|
||
|
|
" <td>8.44</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>EUROPE</th>\n",
|
||
|
|
" <td>10.118</td>\n",
|
||
|
|
" <td>11.163</td>\n",
|
||
|
|
" <td>3.750</td>\n",
|
||
|
|
" <td>0.38</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>LATIN AMERICA AND THE CARIBBEAN</th>\n",
|
||
|
|
" <td>15.886</td>\n",
|
||
|
|
" <td>6.444</td>\n",
|
||
|
|
" <td>14.570</td>\n",
|
||
|
|
" <td>8.89</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>NORTHERN AMERICA</th>\n",
|
||
|
|
" <td>11.780</td>\n",
|
||
|
|
" <td>8.833</td>\n",
|
||
|
|
" <td>5.563</td>\n",
|
||
|
|
" <td>6.11</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>OCEANIA</th>\n",
|
||
|
|
" <td>16.235</td>\n",
|
||
|
|
" <td>6.788</td>\n",
|
||
|
|
" <td>16.939</td>\n",
|
||
|
|
" <td>12.79</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>WORLD</th>\n",
|
||
|
|
" <td>17.963</td>\n",
|
||
|
|
" <td>7.601</td>\n",
|
||
|
|
" <td>27.492</td>\n",
|
||
|
|
" <td>10.36</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" </tbody>\n",
|
||
|
|
"</table>\n",
|
||
|
|
"</div>"
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
" Birth rate Mortality rate \\\n",
|
||
|
|
" \n",
|
||
|
|
"AFRICA 32.577 7.837 \n",
|
||
|
|
"ASIA 15.796 7.030 \n",
|
||
|
|
"EUROPE 10.118 11.163 \n",
|
||
|
|
"LATIN AMERICA AND THE CARIBBEAN 15.886 6.444 \n",
|
||
|
|
"NORTHERN AMERICA 11.780 8.833 \n",
|
||
|
|
"OCEANIA 16.235 6.788 \n",
|
||
|
|
"WORLD 17.963 7.601 \n",
|
||
|
|
"\n",
|
||
|
|
" Infant mortality rate Growth rate \n",
|
||
|
|
" \n",
|
||
|
|
"AFRICA 44.215 24.40 \n",
|
||
|
|
"ASIA 23.185 8.44 \n",
|
||
|
|
"EUROPE 3.750 0.38 \n",
|
||
|
|
"LATIN AMERICA AND THE CARIBBEAN 14.570 8.89 \n",
|
||
|
|
"NORTHERN AMERICA 5.563 6.11 \n",
|
||
|
|
"OCEANIA 16.939 12.79 \n",
|
||
|
|
"WORLD 27.492 10.36 "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"rates"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 19,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<seaborn.matrix.ClusterGrid at 0x158e354b508>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 19,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 864x576 with 4 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Recall you can always edit the DF before seaborn\n",
|
||
|
|
"sns.clustermap(rates,col_cluster=False,figsize=(12,8),cbar_pos=(-0.1, .2, .03, .4))"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"----\n",
|
||
|
|
"----"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"anaconda-cloud": {},
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.7.6"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 1
|
||
|
|
}
|