574 lines
34 KiB
Text
574 lines
34 KiB
Text
{
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"cells": [
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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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"# Data Exploration\n",
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"\n"
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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": 21,
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"metadata": {
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"collapsed": true,
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"import os\n",
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"import pandas as pd\n",
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"import settings\n",
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"\n",
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"% matplotlib inline"
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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>\n",
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" .dataframe thead tr:only-child th {\n",
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" text-align: right;\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: left;\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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"</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>Nation</th>\n",
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" <th>Year</th>\n",
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" <th>Pop</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>North America</td>\n",
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" <td>1980</td>\n",
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" <td>320.27638</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>Bermuda</td>\n",
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" <td>1980</td>\n",
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" <td>0.05473</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>Argentina</td>\n",
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" <td>1980</td>\n",
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" <td>28.3698</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>Former U.S.S.R.</td>\n",
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" <td>1980</td>\n",
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" <td>265.92182</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>Georgia</td>\n",
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" <td>1980</td>\n",
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" <td>--</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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" Nation Year Pop\n",
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"0 North America 1980 320.27638\n",
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"1 Bermuda 1980 0.05473\n",
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"2 Argentina 1980 28.3698\n",
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"3 Former U.S.S.R. 1980 265.92182\n",
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"4 Georgia 1980 --"
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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 = pd.read_csv(os.path.join(settings.data_dir, 'pop_by_country_long_form.csv'))\n",
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"df['Year'] = df['Year'].str[4:].astype(int)\n",
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"df.head()"
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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": 28,
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"metadata": {
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"scrolled": true
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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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"array(['North America', 'Bermuda', 'Argentina', 'Former U.S.S.R.',\n",
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" 'Georgia', 'Kazakhstan', 'Kyrgyzstan', 'Latvia', 'Lithuania',\n",
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" 'Moldova', 'Russia', 'Tajikistan', 'Turkmenistan', 'Aruba',\n",
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" 'Ukraine', 'Uzbekistan', 'Middle East', 'Bahrain', 'Iran', 'Iraq',\n",
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" 'Israel', 'Jordan', 'Kuwait', 'Lebanon', 'Bahamas, The', 'Oman',\n",
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" 'Palestine', 'Qatar', 'Saudi Arabia', 'Syria',\n",
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" 'United Arab Emirates', 'Yemen', 'Africa', 'Algeria', 'Angola',\n",
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" 'Barbados', 'Benin', 'Botswana', 'Burkina Faso', 'Burundi',\n",
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" 'Cameroon', 'Cape Verde', 'Central African Republic', 'Chad',\n",
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" 'Comoros', 'Congo (Brazzaville)', 'Belize', 'Congo (Kinshasa)',\n",
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" 'Cote dIvoire (IvoryCoast)', 'Djibouti', 'Egypt',\n",
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" 'Equatorial Guinea', 'Eritrea', 'Ethiopia', 'Gabon', 'Gambia, The',\n",
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" 'Ghana', 'Bolivia', 'Guinea', 'Guinea-Bissau', 'Kenya', 'Lesotho',\n",
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" 'Liberia', 'Libya', 'Madagascar', 'Malawi', 'Mali', 'Mauritania',\n",
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" 'Brazil', 'Mauritius', 'Morocco', 'Mozambique', 'Namibia', 'Niger',\n",
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" 'Nigeria', 'Reunion', 'Rwanda', 'Saint Helena',\n",
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" 'Sao Tome and Principe', 'Cayman Islands', 'Senegal', 'Seychelles',\n",
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" 'Sierra Leone', 'Somalia', 'South Africa', 'Sudan', 'Swaziland',\n",
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" 'Tanzania', 'Togo', 'Tunisia', 'Chile', 'Uganda', 'Western Sahara',\n",
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" 'Zambia', 'Zimbabwe', 'Asia & Oceania', 'Afghanistan',\n",
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" 'American Samoa', 'Australia', 'Bangladesh', 'Bhutan', 'Colombia',\n",
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" 'Brunei', 'Burma (Myanmar)', 'Cambodia', 'China', 'Cook Islands',\n",
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" 'Fiji', 'French Polynesia', 'Guam', 'Hawaiian Trade Zone',\n",
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" 'Hong Kong', 'Canada', 'Costa Rica', 'India', 'Indonesia', 'Japan',\n",
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" 'Kiribati', 'Korea, North', 'Korea, South', 'Laos', 'Macau',\n",
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" 'Malaysia', 'Maldives', 'Cuba', 'Mongolia', 'Nauru', 'Nepal',\n",
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" 'New Caledonia', 'New Zealand', 'Niue', 'Pakistan',\n",
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" 'Papua New Guinea', 'Philippines', 'Samoa', 'Dominica', 'Singapore',\n",
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" 'Solomon Islands', 'Sri Lanka', 'Taiwan', 'Thailand',\n",
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" 'Timor-Leste (East Timor)', 'Tonga', 'U.S. Pacific Islands',\n",
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" 'Vanuatu', 'Vietnam', 'Dominican Republic', 'Wake Island', 'World',\n",
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" 'Ecuador', 'El Salvador', 'Falkland Islands (Islas Malvinas)',\n",
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" 'French Guiana', 'Grenada', 'Guadeloupe', 'Greenland', 'Guatemala',\n",
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" 'Guyana', 'Haiti', 'Honduras', 'Jamaica', 'Martinique',\n",
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" 'Montserrat', 'Netherlands Antilles', 'Nicaragua', 'Panama',\n",
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" 'Mexico', 'Paraguay', 'Peru', 'Puerto Rico',\n",
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" 'Saint Kitts and Nevis', 'Saint Lucia', 'Saint Vincent/Grenadines',\n",
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" 'Suriname', 'Trinidad and Tobago', 'Turks and Caicos Islands',\n",
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" 'Uruguay', 'Saint Pierre and Miquelon', 'Venezuela',\n",
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" 'Virgin Islands, U.S.', 'Virgin Islands, British', 'Europe',\n",
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" 'Albania', 'Austria', 'Belgium', 'Bosnia and Herzegovina',\n",
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" 'Bulgaria', 'Croatia', 'United States', 'Cyprus', 'Czech Republic',\n",
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" 'Denmark', 'Faroe Islands', 'Finland', 'Former Czechoslovakia',\n",
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" 'Former Serbia and Montenegro', 'Former Yugoslavia', 'France',\n",
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" 'Germany', 'Central & South America', 'Germany, East',\n",
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" 'Germany, West', 'Gibraltar', 'Greece', 'Hungary', 'Iceland',\n",
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" 'Ireland', 'Italy', 'Luxembourg', 'Macedonia', 'Antarctica',\n",
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" 'Malta', 'Montenegro', 'Netherlands', 'Norway', 'Poland',\n",
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" 'Portugal', 'Romania', 'Serbia', 'Slovakia', 'Slovenia',\n",
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" 'Antigua and Barbuda', 'Spain', 'Sweden', 'Switzerland', 'Turkey',\n",
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" 'United Kingdom', 'Eurasia', 'Armenia', 'Azerbaijan', 'Belarus',\n",
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" 'Estonia'], dtype=object)"
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]
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},
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"execution_count": 28,
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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.Nation.drop_duplicates().values"
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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": 78,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Object `to_json` not found.\n"
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]
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}
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],
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"source": [
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"nation = 'United States'\n",
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"df2 = df.groupby(['Year', 'Nation']).sum().unstack()\n",
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"df2.columns = df2.columns.droplevel()#[nation]\n",
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"df2[[nation]].rename(columns={'United States':'Series', 'Year':'Values'}).to_json?"
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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": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"df2[[nation]].rename(columns={'United States':'Series', 'Year':'Values'}).to_json"
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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": 97,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'labels:[1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010]\\nseries: [227.22468, 229.46571, 231.66446, 233.79199, 235.8249, 237.9238, 240.13289, 242.28892, 244.49898, 246.81923, 249.62281, 252.98094, 256.51422, 259.91859, 263.12582, 266.27839, 269.39428, 272.64693, 275.8541, 279.04017, 282.17196, 285.08156, 287.80391, 290.32642, 293.04574, 295.75315, 298.59321, 301.5799, 304.37485, 307.00655, 310.23286]'"
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]
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},
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"execution_count": 97,
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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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"f'labels:{df2.index.astype(int).tolist()}, series: [{df2[nation].astype(float).tolist()}]'"
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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 = pd.read_csv(os.path.join(settings.data_dir, 'pop_by_country_long_form.csv'))\n",
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"df['Year'] = df['Year'].str[4:].astype(int)\n",
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"df2 = df.groupby(['Year', 'Nation']).sum().unstack()\n",
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"df2.columns = df2.columns.droplevel()\n",
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"nations = df2.columns"
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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": 33,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt"
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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": 36,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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r97EnPYfY8FDm3TKIwV3bOB1LpFJU7CJnSM3M56lV+/l4bwadWjXhhV8M4Mr+nWigM0Yl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\nFxFxGRW7iIjL/H/U9KEeLyXnkAAAAABJRU5ErkJggg==\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0xb22bcc0>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig, ax = plt.subplots()\n",
|
|
"df2[nations[12]].astype(float).plot(ax=ax);"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"items = ['mpl/' + nation for nation in df2.columns]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[('mpl/Afghanistan', 'mpl/Afghanistan'),\n",
|
|
" ('mpl/Africa', 'mpl/Africa'),\n",
|
|
" ('mpl/Albania', 'mpl/Albania'),\n",
|
|
" ('mpl/Algeria', 'mpl/Algeria'),\n",
|
|
" ('mpl/American Samoa', 'mpl/American Samoa'),\n",
|
|
" ('mpl/Angola', 'mpl/Angola'),\n",
|
|
" ('mpl/Antarctica', 'mpl/Antarctica'),\n",
|
|
" ('mpl/Antigua and Barbuda', 'mpl/Antigua and Barbuda'),\n",
|
|
" ('mpl/Argentina', 'mpl/Argentina'),\n",
|
|
" ('mpl/Armenia', 'mpl/Armenia'),\n",
|
|
" ('mpl/Aruba', 'mpl/Aruba'),\n",
|
|
" ('mpl/Asia & Oceania', 'mpl/Asia & Oceania'),\n",
|
|
" ('mpl/Australia', 'mpl/Australia'),\n",
|
|
" ('mpl/Austria', 'mpl/Austria'),\n",
|
|
" ('mpl/Azerbaijan', 'mpl/Azerbaijan'),\n",
|
|
" ('mpl/Bahamas, The', 'mpl/Bahamas, The'),\n",
|
|
" ('mpl/Bahrain', 'mpl/Bahrain'),\n",
|
|
" ('mpl/Bangladesh', 'mpl/Bangladesh'),\n",
|
|
" ('mpl/Barbados', 'mpl/Barbados'),\n",
|
|
" ('mpl/Belarus', 'mpl/Belarus'),\n",
|
|
" ('mpl/Belgium', 'mpl/Belgium'),\n",
|
|
" ('mpl/Belize', 'mpl/Belize'),\n",
|
|
" ('mpl/Benin', 'mpl/Benin'),\n",
|
|
" ('mpl/Bermuda', 'mpl/Bermuda'),\n",
|
|
" ('mpl/Bhutan', 'mpl/Bhutan'),\n",
|
|
" ('mpl/Bolivia', 'mpl/Bolivia'),\n",
|
|
" ('mpl/Bosnia and Herzegovina', 'mpl/Bosnia and Herzegovina'),\n",
|
|
" ('mpl/Botswana', 'mpl/Botswana'),\n",
|
|
" ('mpl/Brazil', 'mpl/Brazil'),\n",
|
|
" ('mpl/Brunei', 'mpl/Brunei'),\n",
|
|
" ('mpl/Bulgaria', 'mpl/Bulgaria'),\n",
|
|
" ('mpl/Burkina Faso', 'mpl/Burkina Faso'),\n",
|
|
" ('mpl/Burma (Myanmar)', 'mpl/Burma (Myanmar)'),\n",
|
|
" ('mpl/Burundi', 'mpl/Burundi'),\n",
|
|
" ('mpl/Cambodia', 'mpl/Cambodia'),\n",
|
|
" ('mpl/Cameroon', 'mpl/Cameroon'),\n",
|
|
" ('mpl/Canada', 'mpl/Canada'),\n",
|
|
" ('mpl/Cape Verde', 'mpl/Cape Verde'),\n",
|
|
" ('mpl/Cayman Islands', 'mpl/Cayman Islands'),\n",
|
|
" ('mpl/Central & South America', 'mpl/Central & South America'),\n",
|
|
" ('mpl/Central African Republic', 'mpl/Central African Republic'),\n",
|
|
" ('mpl/Chad', 'mpl/Chad'),\n",
|
|
" ('mpl/Chile', 'mpl/Chile'),\n",
|
|
" ('mpl/China', 'mpl/China'),\n",
|
|
" ('mpl/Colombia', 'mpl/Colombia'),\n",
|
|
" ('mpl/Comoros', 'mpl/Comoros'),\n",
|
|
" ('mpl/Congo (Brazzaville)', 'mpl/Congo (Brazzaville)'),\n",
|
|
" ('mpl/Congo (Kinshasa)', 'mpl/Congo (Kinshasa)'),\n",
|
|
" ('mpl/Cook Islands', 'mpl/Cook Islands'),\n",
|
|
" ('mpl/Costa Rica', 'mpl/Costa Rica'),\n",
|
|
" ('mpl/Cote dIvoire (IvoryCoast)', 'mpl/Cote dIvoire (IvoryCoast)'),\n",
|
|
" ('mpl/Croatia', 'mpl/Croatia'),\n",
|
|
" ('mpl/Cuba', 'mpl/Cuba'),\n",
|
|
" ('mpl/Cyprus', 'mpl/Cyprus'),\n",
|
|
" ('mpl/Czech Republic', 'mpl/Czech Republic'),\n",
|
|
" ('mpl/Denmark', 'mpl/Denmark'),\n",
|
|
" ('mpl/Djibouti', 'mpl/Djibouti'),\n",
|
|
" ('mpl/Dominica', 'mpl/Dominica'),\n",
|
|
" ('mpl/Dominican Republic', 'mpl/Dominican Republic'),\n",
|
|
" ('mpl/Ecuador', 'mpl/Ecuador'),\n",
|
|
" ('mpl/Egypt', 'mpl/Egypt'),\n",
|
|
" ('mpl/El Salvador', 'mpl/El Salvador'),\n",
|
|
" ('mpl/Equatorial Guinea', 'mpl/Equatorial Guinea'),\n",
|
|
" ('mpl/Eritrea', 'mpl/Eritrea'),\n",
|
|
" ('mpl/Estonia', 'mpl/Estonia'),\n",
|
|
" ('mpl/Ethiopia', 'mpl/Ethiopia'),\n",
|
|
" ('mpl/Eurasia', 'mpl/Eurasia'),\n",
|
|
" ('mpl/Europe', 'mpl/Europe'),\n",
|
|
" ('mpl/Falkland Islands (Islas Malvinas)',\n",
|
|
" 'mpl/Falkland Islands (Islas Malvinas)'),\n",
|
|
" ('mpl/Faroe Islands', 'mpl/Faroe Islands'),\n",
|
|
" ('mpl/Fiji', 'mpl/Fiji'),\n",
|
|
" ('mpl/Finland', 'mpl/Finland'),\n",
|
|
" ('mpl/Former Czechoslovakia', 'mpl/Former Czechoslovakia'),\n",
|
|
" ('mpl/Former Serbia and Montenegro', 'mpl/Former Serbia and Montenegro'),\n",
|
|
" ('mpl/Former U.S.S.R.', 'mpl/Former U.S.S.R.'),\n",
|
|
" ('mpl/Former Yugoslavia', 'mpl/Former Yugoslavia'),\n",
|
|
" ('mpl/France', 'mpl/France'),\n",
|
|
" ('mpl/French Guiana', 'mpl/French Guiana'),\n",
|
|
" ('mpl/French Polynesia', 'mpl/French Polynesia'),\n",
|
|
" ('mpl/Gabon', 'mpl/Gabon'),\n",
|
|
" ('mpl/Gambia, The', 'mpl/Gambia, The'),\n",
|
|
" ('mpl/Georgia', 'mpl/Georgia'),\n",
|
|
" ('mpl/Germany', 'mpl/Germany'),\n",
|
|
" ('mpl/Germany, East', 'mpl/Germany, East'),\n",
|
|
" ('mpl/Germany, West', 'mpl/Germany, West'),\n",
|
|
" ('mpl/Ghana', 'mpl/Ghana'),\n",
|
|
" ('mpl/Gibraltar', 'mpl/Gibraltar'),\n",
|
|
" ('mpl/Greece', 'mpl/Greece'),\n",
|
|
" ('mpl/Greenland', 'mpl/Greenland'),\n",
|
|
" ('mpl/Grenada', 'mpl/Grenada'),\n",
|
|
" ('mpl/Guadeloupe', 'mpl/Guadeloupe'),\n",
|
|
" ('mpl/Guam', 'mpl/Guam'),\n",
|
|
" ('mpl/Guatemala', 'mpl/Guatemala'),\n",
|
|
" ('mpl/Guinea', 'mpl/Guinea'),\n",
|
|
" ('mpl/Guinea-Bissau', 'mpl/Guinea-Bissau'),\n",
|
|
" ('mpl/Guyana', 'mpl/Guyana'),\n",
|
|
" ('mpl/Haiti', 'mpl/Haiti'),\n",
|
|
" ('mpl/Hawaiian Trade Zone', 'mpl/Hawaiian Trade Zone'),\n",
|
|
" ('mpl/Honduras', 'mpl/Honduras'),\n",
|
|
" ('mpl/Hong Kong', 'mpl/Hong Kong'),\n",
|
|
" ('mpl/Hungary', 'mpl/Hungary'),\n",
|
|
" ('mpl/Iceland', 'mpl/Iceland'),\n",
|
|
" ('mpl/India', 'mpl/India'),\n",
|
|
" ('mpl/Indonesia', 'mpl/Indonesia'),\n",
|
|
" ('mpl/Iran', 'mpl/Iran'),\n",
|
|
" ('mpl/Iraq', 'mpl/Iraq'),\n",
|
|
" ('mpl/Ireland', 'mpl/Ireland'),\n",
|
|
" ('mpl/Israel', 'mpl/Israel'),\n",
|
|
" ('mpl/Italy', 'mpl/Italy'),\n",
|
|
" ('mpl/Jamaica', 'mpl/Jamaica'),\n",
|
|
" ('mpl/Japan', 'mpl/Japan'),\n",
|
|
" ('mpl/Jordan', 'mpl/Jordan'),\n",
|
|
" ('mpl/Kazakhstan', 'mpl/Kazakhstan'),\n",
|
|
" ('mpl/Kenya', 'mpl/Kenya'),\n",
|
|
" ('mpl/Kiribati', 'mpl/Kiribati'),\n",
|
|
" ('mpl/Korea, North', 'mpl/Korea, North'),\n",
|
|
" ('mpl/Korea, South', 'mpl/Korea, South'),\n",
|
|
" ('mpl/Kuwait', 'mpl/Kuwait'),\n",
|
|
" ('mpl/Kyrgyzstan', 'mpl/Kyrgyzstan'),\n",
|
|
" ('mpl/Laos', 'mpl/Laos'),\n",
|
|
" ('mpl/Latvia', 'mpl/Latvia'),\n",
|
|
" ('mpl/Lebanon', 'mpl/Lebanon'),\n",
|
|
" ('mpl/Lesotho', 'mpl/Lesotho'),\n",
|
|
" ('mpl/Liberia', 'mpl/Liberia'),\n",
|
|
" ('mpl/Libya', 'mpl/Libya'),\n",
|
|
" ('mpl/Lithuania', 'mpl/Lithuania'),\n",
|
|
" ('mpl/Luxembourg', 'mpl/Luxembourg'),\n",
|
|
" ('mpl/Macau', 'mpl/Macau'),\n",
|
|
" ('mpl/Macedonia', 'mpl/Macedonia'),\n",
|
|
" ('mpl/Madagascar', 'mpl/Madagascar'),\n",
|
|
" ('mpl/Malawi', 'mpl/Malawi'),\n",
|
|
" ('mpl/Malaysia', 'mpl/Malaysia'),\n",
|
|
" ('mpl/Maldives', 'mpl/Maldives'),\n",
|
|
" ('mpl/Mali', 'mpl/Mali'),\n",
|
|
" ('mpl/Malta', 'mpl/Malta'),\n",
|
|
" ('mpl/Martinique', 'mpl/Martinique'),\n",
|
|
" ('mpl/Mauritania', 'mpl/Mauritania'),\n",
|
|
" ('mpl/Mauritius', 'mpl/Mauritius'),\n",
|
|
" ('mpl/Mexico', 'mpl/Mexico'),\n",
|
|
" ('mpl/Middle East', 'mpl/Middle East'),\n",
|
|
" ('mpl/Moldova', 'mpl/Moldova'),\n",
|
|
" ('mpl/Mongolia', 'mpl/Mongolia'),\n",
|
|
" ('mpl/Montenegro', 'mpl/Montenegro'),\n",
|
|
" ('mpl/Montserrat', 'mpl/Montserrat'),\n",
|
|
" ('mpl/Morocco', 'mpl/Morocco'),\n",
|
|
" ('mpl/Mozambique', 'mpl/Mozambique'),\n",
|
|
" ('mpl/Namibia', 'mpl/Namibia'),\n",
|
|
" ('mpl/Nauru', 'mpl/Nauru'),\n",
|
|
" ('mpl/Nepal', 'mpl/Nepal'),\n",
|
|
" ('mpl/Netherlands', 'mpl/Netherlands'),\n",
|
|
" ('mpl/Netherlands Antilles', 'mpl/Netherlands Antilles'),\n",
|
|
" ('mpl/New Caledonia', 'mpl/New Caledonia'),\n",
|
|
" ('mpl/New Zealand', 'mpl/New Zealand'),\n",
|
|
" ('mpl/Nicaragua', 'mpl/Nicaragua'),\n",
|
|
" ('mpl/Niger', 'mpl/Niger'),\n",
|
|
" ('mpl/Nigeria', 'mpl/Nigeria'),\n",
|
|
" ('mpl/Niue', 'mpl/Niue'),\n",
|
|
" ('mpl/North America', 'mpl/North America'),\n",
|
|
" ('mpl/Norway', 'mpl/Norway'),\n",
|
|
" ('mpl/Oman', 'mpl/Oman'),\n",
|
|
" ('mpl/Pakistan', 'mpl/Pakistan'),\n",
|
|
" ('mpl/Palestine', 'mpl/Palestine'),\n",
|
|
" ('mpl/Panama', 'mpl/Panama'),\n",
|
|
" ('mpl/Papua New Guinea', 'mpl/Papua New Guinea'),\n",
|
|
" ('mpl/Paraguay', 'mpl/Paraguay'),\n",
|
|
" ('mpl/Peru', 'mpl/Peru'),\n",
|
|
" ('mpl/Philippines', 'mpl/Philippines'),\n",
|
|
" ('mpl/Poland', 'mpl/Poland'),\n",
|
|
" ('mpl/Portugal', 'mpl/Portugal'),\n",
|
|
" ('mpl/Puerto Rico', 'mpl/Puerto Rico'),\n",
|
|
" ('mpl/Qatar', 'mpl/Qatar'),\n",
|
|
" ('mpl/Reunion', 'mpl/Reunion'),\n",
|
|
" ('mpl/Romania', 'mpl/Romania'),\n",
|
|
" ('mpl/Russia', 'mpl/Russia'),\n",
|
|
" ('mpl/Rwanda', 'mpl/Rwanda'),\n",
|
|
" ('mpl/Saint Helena', 'mpl/Saint Helena'),\n",
|
|
" ('mpl/Saint Kitts and Nevis', 'mpl/Saint Kitts and Nevis'),\n",
|
|
" ('mpl/Saint Lucia', 'mpl/Saint Lucia'),\n",
|
|
" ('mpl/Saint Pierre and Miquelon', 'mpl/Saint Pierre and Miquelon'),\n",
|
|
" ('mpl/Saint Vincent/Grenadines', 'mpl/Saint Vincent/Grenadines'),\n",
|
|
" ('mpl/Samoa', 'mpl/Samoa'),\n",
|
|
" ('mpl/Sao Tome and Principe', 'mpl/Sao Tome and Principe'),\n",
|
|
" ('mpl/Saudi Arabia', 'mpl/Saudi Arabia'),\n",
|
|
" ('mpl/Senegal', 'mpl/Senegal'),\n",
|
|
" ('mpl/Serbia', 'mpl/Serbia'),\n",
|
|
" ('mpl/Seychelles', 'mpl/Seychelles'),\n",
|
|
" ('mpl/Sierra Leone', 'mpl/Sierra Leone'),\n",
|
|
" ('mpl/Singapore', 'mpl/Singapore'),\n",
|
|
" ('mpl/Slovakia', 'mpl/Slovakia'),\n",
|
|
" ('mpl/Slovenia', 'mpl/Slovenia'),\n",
|
|
" ('mpl/Solomon Islands', 'mpl/Solomon Islands'),\n",
|
|
" ('mpl/Somalia', 'mpl/Somalia'),\n",
|
|
" ('mpl/South Africa', 'mpl/South Africa'),\n",
|
|
" ('mpl/Spain', 'mpl/Spain'),\n",
|
|
" ('mpl/Sri Lanka', 'mpl/Sri Lanka'),\n",
|
|
" ('mpl/Sudan', 'mpl/Sudan'),\n",
|
|
" ('mpl/Suriname', 'mpl/Suriname'),\n",
|
|
" ('mpl/Swaziland', 'mpl/Swaziland'),\n",
|
|
" ('mpl/Sweden', 'mpl/Sweden'),\n",
|
|
" ('mpl/Switzerland', 'mpl/Switzerland'),\n",
|
|
" ('mpl/Syria', 'mpl/Syria'),\n",
|
|
" ('mpl/Taiwan', 'mpl/Taiwan'),\n",
|
|
" ('mpl/Tajikistan', 'mpl/Tajikistan'),\n",
|
|
" ('mpl/Tanzania', 'mpl/Tanzania'),\n",
|
|
" ('mpl/Thailand', 'mpl/Thailand'),\n",
|
|
" ('mpl/Timor-Leste (East Timor)', 'mpl/Timor-Leste (East Timor)'),\n",
|
|
" ('mpl/Togo', 'mpl/Togo'),\n",
|
|
" ('mpl/Tonga', 'mpl/Tonga'),\n",
|
|
" ('mpl/Trinidad and Tobago', 'mpl/Trinidad and Tobago'),\n",
|
|
" ('mpl/Tunisia', 'mpl/Tunisia'),\n",
|
|
" ('mpl/Turkey', 'mpl/Turkey'),\n",
|
|
" ('mpl/Turkmenistan', 'mpl/Turkmenistan'),\n",
|
|
" ('mpl/Turks and Caicos Islands', 'mpl/Turks and Caicos Islands'),\n",
|
|
" ('mpl/U.S. Pacific Islands', 'mpl/U.S. Pacific Islands'),\n",
|
|
" ('mpl/Uganda', 'mpl/Uganda'),\n",
|
|
" ('mpl/Ukraine', 'mpl/Ukraine'),\n",
|
|
" ('mpl/United Arab Emirates', 'mpl/United Arab Emirates'),\n",
|
|
" ('mpl/United Kingdom', 'mpl/United Kingdom'),\n",
|
|
" ('mpl/United States', 'mpl/United States'),\n",
|
|
" ('mpl/Uruguay', 'mpl/Uruguay'),\n",
|
|
" ('mpl/Uzbekistan', 'mpl/Uzbekistan'),\n",
|
|
" ('mpl/Vanuatu', 'mpl/Vanuatu'),\n",
|
|
" ('mpl/Venezuela', 'mpl/Venezuela'),\n",
|
|
" ('mpl/Vietnam', 'mpl/Vietnam'),\n",
|
|
" ('mpl/Virgin Islands, U.S.', 'mpl/Virgin Islands, U.S.'),\n",
|
|
" ('mpl/Virgin Islands, British', 'mpl/Virgin Islands, British'),\n",
|
|
" ('mpl/Wake Island', 'mpl/Wake Island'),\n",
|
|
" ('mpl/Western Sahara', 'mpl/Western Sahara'),\n",
|
|
" ('mpl/World', 'mpl/World'),\n",
|
|
" ('mpl/Yemen', 'mpl/Yemen'),\n",
|
|
" ('mpl/Zambia', 'mpl/Zambia'),\n",
|
|
" ('mpl/Zimbabwe', 'mpl/Zimbabwe')]"
|
|
]
|
|
},
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"list(zip(items, items))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python [default]",
|
|
"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": "3.6.1"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|