Multindex.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Country</th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>Australia</td>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>3.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>Britain</td>\n",
       "      <td>4.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>Canada</td>\n",
       "      <td>4.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date    Country  Price in US Dollars\n",
       "0 2016-01-01  Argentina                 2.39\n",
       "1 2016-01-01  Australia                 3.74\n",
       "2 2016-01-01     Brazil                 3.35\n",
       "3 2016-01-01    Britain                 4.22\n",
       "4 2016-01-01     Canada                 4.14"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac = pd.read_csv(\"bigmac.csv\", parse_dates=[\"Date\"])\n",
    "bigmac.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date                   datetime64[ns]\n",
       "Country                      category\n",
       "Price in US Dollars           float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 652 entries, 0 to 651\n",
      "Data columns (total 3 columns):\n",
      "Date                   652 non-null datetime64[ns]\n",
      "Country                652 non-null category\n",
      "Price in US Dollars    652 non-null float64\n",
      "dtypes: category(1), datetime64[ns](1), float64(1)\n",
      "memory usage: 13.9 KB\n"
     ]
    }
   ],
   "source": [
    "bigmac.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "58"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac[\"Country\"].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bigmac[\"Country\"] = bigmac[\"Country\"].astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bigmac.set_index(keys = [\"Date\",\"Country\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bigmac.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FrozenList(['Date', 'Country'])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.multi.MultiIndex"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(bigmac.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2010-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>1.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>4.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Britain</th>\n",
       "      <td>3.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>3.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Price in US Dollars\n",
       "Date       Country                       \n",
       "2010-01-01 Argentina                 1.84\n",
       "           Australia                 3.98\n",
       "           Brazil                    4.76\n",
       "           Britain                   3.67\n",
       "           Canada                    3.97"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac = pd.read_csv(\"bigmac.csv\", parse_dates=[\"Date\"], index_col=[\"Date\",\"Country\"])\n",
    "bigmac.sort_index(inplace=True)\n",
    "bigmac.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2010-01-01', '2010-01-01', '2010-01-01', '2010-01-01',\n",
       "               '2010-01-01', '2010-01-01', '2010-01-01', '2010-01-01',\n",
       "               '2010-01-01', '2010-01-01',\n",
       "               ...\n",
       "               '2016-01-01', '2016-01-01', '2016-01-01', '2016-01-01',\n",
       "               '2016-01-01', '2016-01-01', '2016-01-01', '2016-01-01',\n",
       "               '2016-01-01', '2016-01-01'],\n",
       "              dtype='datetime64[ns]', name='Date', length=652, freq=None)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.get_level_values(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bigmac.index.set_names([\"Date\",\"Country\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2010-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>1.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>4.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Britain</th>\n",
       "      <td>3.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>3.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Price in US Dollars\n",
       "Date       Country                       \n",
       "2010-01-01 Argentina                 1.84\n",
       "           Australia                 3.98\n",
       "           Brazil                    4.76\n",
       "           Britain                   3.67\n",
       "           Canada                    3.97"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2010-01-01</th>\n",
       "      <th>Uruguay</th>\n",
       "      <td>3.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>3.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ukraine</th>\n",
       "      <td>1.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UAE</th>\n",
       "      <td>2.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>3.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thailand</th>\n",
       "      <td>2.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan</th>\n",
       "      <td>2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Switzerland</th>\n",
       "      <td>6.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sweden</th>\n",
       "      <td>5.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sri Lanka</th>\n",
       "      <td>1.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Korea</th>\n",
       "      <td>2.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>2.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <td>3.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>2.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poland</th>\n",
       "      <td>2.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philippines</th>\n",
       "      <td>2.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peru</th>\n",
       "      <td>2.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pakistan</th>\n",
       "      <td>2.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norway</th>\n",
       "      <td>7.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand</th>\n",
       "      <td>3.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>2.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malaysia</th>\n",
       "      <td>2.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lithuania</th>\n",
       "      <td>2.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latvia</th>\n",
       "      <td>3.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>3.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>2.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>3.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hong Kong</th>\n",
       "      <td>1.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2016-01-01</th>\n",
       "      <th>Mexico</th>\n",
       "      <td>2.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malaysia</th>\n",
       "      <td>1.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>3.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>4.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>4.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ireland</th>\n",
       "      <td>4.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>2.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>3.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hong Kong</th>\n",
       "      <td>2.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>3.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>3.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>4.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finland</th>\n",
       "      <td>4.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Euro area</th>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Estonia</th>\n",
       "      <td>3.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Egypt</th>\n",
       "      <td>2.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Denmark</th>\n",
       "      <td>4.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Czech Republic</th>\n",
       "      <td>2.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Costa Rica</th>\n",
       "      <td>4.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colombia</th>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>2.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chile</th>\n",
       "      <td>2.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>4.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Britain</th>\n",
       "      <td>4.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>3.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belgium</th>\n",
       "      <td>4.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>3.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>652 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Price in US Dollars\n",
       "Date       Country                            \n",
       "2010-01-01 Uruguay                        3.32\n",
       "           United States                  3.58\n",
       "           Ukraine                        1.83\n",
       "           UAE                            2.99\n",
       "           Turkey                         3.83\n",
       "           Thailand                       2.11\n",
       "           Taiwan                         2.36\n",
       "           Switzerland                    6.30\n",
       "           Sweden                         5.51\n",
       "           Sri Lanka                      1.83\n",
       "           South Korea                    2.98\n",
       "           South Africa                   2.46\n",
       "           Singapore                      3.19\n",
       "           Saudi Arabia                   2.67\n",
       "           Russia                         2.34\n",
       "           Poland                         2.86\n",
       "           Philippines                    2.21\n",
       "           Peru                           2.81\n",
       "           Pakistan                       2.42\n",
       "           Norway                         7.02\n",
       "           New Zealand                    3.61\n",
       "           Mexico                         2.50\n",
       "           Malaysia                       2.08\n",
       "           Lithuania                      2.87\n",
       "           Latvia                         3.09\n",
       "           Japan                          3.50\n",
       "           Israel                         3.99\n",
       "           Indonesia                      2.24\n",
       "           Hungary                        3.86\n",
       "           Hong Kong                      1.91\n",
       "...                                        ...\n",
       "2016-01-01 Mexico                         2.81\n",
       "           Malaysia                       1.82\n",
       "           Japan                          3.12\n",
       "           Italy                          4.30\n",
       "           Israel                         4.29\n",
       "           Ireland                        4.25\n",
       "           Indonesia                      2.19\n",
       "           India                          1.90\n",
       "           Hungary                        3.08\n",
       "           Hong Kong                      2.48\n",
       "           Greece                         3.60\n",
       "           Germany                        3.86\n",
       "           France                         4.41\n",
       "           Finland                        4.41\n",
       "           Euro area                      4.00\n",
       "           Estonia                        3.23\n",
       "           Egypt                          2.16\n",
       "           Denmark                        4.32\n",
       "           Czech Republic                 2.98\n",
       "           Costa Rica                     4.02\n",
       "           Colombia                       2.43\n",
       "           China                          2.68\n",
       "           Chile                          2.94\n",
       "           Canada                         4.14\n",
       "           Britain                        4.22\n",
       "           Brazil                         3.35\n",
       "           Belgium                        4.25\n",
       "           Austria                        3.76\n",
       "           Australia                      3.74\n",
       "           Argentina                      2.39\n",
       "\n",
       "[652 rows x 1 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.sort_index(ascending=[True,False])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date        Country\n",
       "2010-01-01  Norway     7.02\n",
       "Name: Price in US Dollars, dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.loc[(\"2010-01-01\",\"Norway\"),\"Price in US Dollars\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2010-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>1.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>4.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Britain</th>\n",
       "      <td>3.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>3.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Price in US Dollars\n",
       "Date       Country                       \n",
       "2010-01-01 Argentina                 1.84\n",
       "           Australia                 3.98\n",
       "           Brazil                    4.76\n",
       "           Britain                   3.67\n",
       "           Canada                    3.97"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.transpose()\n",
    "\n",
    "bigmac.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'Price in US Dollars'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: an integer is required",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2441\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2442\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2443\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine._date_check_type\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Price in US Dollars'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Int64HashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: an integer is required",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/datetimes.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   1426\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1427\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1428\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2443\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2444\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2445\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.DatetimeEngine._date_check_type\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Price in US Dollars'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32mpandas/_libs/tslib.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslib.convert_str_to_tsobject (pandas/_libs/tslib.c:29306)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/src/datetime.pxd\u001b[0m in \u001b[0;36mdatetime._string_to_dts (pandas/_libs/tslib.c:97369)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Error parsing datetime string \"Price in US Dollars\" at position 0",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32mpandas/_libs/tslib.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslib.convert_str_to_tsobject (pandas/_libs/tslib.c:29750)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/tslib.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslib.parse_datetime_string (pandas/_libs/tslib.c:35351)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/dateutil/parser.py\u001b[0m in \u001b[0;36mparse\u001b[0;34m(timestr, parserinfo, **kwargs)\u001b[0m\n\u001b[1;32m   1181\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1182\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mDEFAULTPARSER\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimestr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1183\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/dateutil/parser.py\u001b[0m in \u001b[0;36mparse\u001b[0;34m(self, timestr, default, ignoretz, tzinfos, **kwargs)\u001b[0m\n\u001b[1;32m    558\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 559\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Unknown string format\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    560\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Unknown string format",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/datetimes.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   1434\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1435\u001b[0;31m                 \u001b[0mstamp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTimestamp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtz\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1436\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstamp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/tslib.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslib.Timestamp.__new__ (pandas/_libs/tslib.c:10051)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/tslib.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslib.convert_to_tsobject (pandas/_libs/tslib.c:27453)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/tslib.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslib.convert_str_to_tsobject (pandas/_libs/tslib.c:29803)\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: could not convert string to Timestamp",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-51-1215296a0abe>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mbigmac\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Price in US Dollars\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m    119\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    120\u001b[0m             \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply_if_callable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 121\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    122\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    123\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1075\u001b[0m                     \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1076\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1077\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1078\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1079\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_iterable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_label\u001b[0;34m(self, label, axis)\u001b[0m\n\u001b[1;32m    134\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mIndexingError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'no slices here, handle elsewhere'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    135\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 136\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_xs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    138\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mxs\u001b[0;34m(self, key, axis, level, drop_level)\u001b[0m\n\u001b[1;32m   2028\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mMultiIndex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2029\u001b[0m             loc, new_index = self.index.get_loc_level(key,\n\u001b[0;32m-> 2030\u001b[0;31m                                                       drop_level=drop_level)\n\u001b[0m\u001b[1;32m   2031\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2032\u001b[0m             \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/multi.py\u001b[0m in \u001b[0;36mget_loc_level\u001b[0;34m(self, key, level, drop_level)\u001b[0m\n\u001b[1;32m   2161\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmaybe_droplevels\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0milevels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdrop_level\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2162\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2163\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_level_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2164\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmaybe_droplevels\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdrop_level\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2165\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/multi.py\u001b[0m in \u001b[0;36m_get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m   2241\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2242\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2243\u001b[0;31m             \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlevel_index\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2244\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mslice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2245\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mloc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/datetimes.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   1436\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstamp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1437\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1438\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1439\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1440\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_maybe_cast_slice_bound\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mside\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Price in US Dollars'"
     ]
    }
   ],
   "source": [
    "bigmac.ix[\"Price in US Dollars\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2010-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>1.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>4.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Britain</th>\n",
       "      <td>3.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>3.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Price in US Dollars\n",
       "Date       Country                       \n",
       "2010-01-01 Argentina                 1.84\n",
       "           Australia                 3.98\n",
       "           Brazil                    4.76\n",
       "           Britain                   3.67\n",
       "           Canada                    3.97"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac = pd.read_csv(\"bigmac.csv\", parse_dates=[\"Date\"], index_col=[\"Date\",\"Country\"])\n",
    "bigmac.sort_index(inplace=True)\n",
    "bigmac.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>1.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>4.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Britain</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chile</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>1.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colombia</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Costa Rica</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Czech Republic</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Denmark</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>5.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Egypt</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Euro area</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>4.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hong Kong</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>1.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latvia</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lithuania</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malaysia</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norway</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>7.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pakistan</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peru</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philippines</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poland</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>4.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malaysia</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>1.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norway</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>5.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pakistan</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peru</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philippines</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poland</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>1.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>1.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Korea</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sri Lanka</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sweden</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>5.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Switzerland</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>6.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thailand</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UAE</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ukraine</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>1.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>4.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Venezuela</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>0.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vietnam</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>652 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Price in US Dollars\n",
       "Country        Date                           \n",
       "Argentina      2010-01-01                 1.84\n",
       "Australia      2010-01-01                 3.98\n",
       "Brazil         2010-01-01                 4.76\n",
       "Britain        2010-01-01                 3.67\n",
       "Canada         2010-01-01                 3.97\n",
       "Chile          2010-01-01                 3.18\n",
       "China          2010-01-01                 1.83\n",
       "Colombia       2010-01-01                 3.91\n",
       "Costa Rica     2010-01-01                 3.52\n",
       "Czech Republic 2010-01-01                 3.71\n",
       "Denmark        2010-01-01                 5.99\n",
       "Egypt          2010-01-01                 2.38\n",
       "Euro area      2010-01-01                 4.84\n",
       "Hong Kong      2010-01-01                 1.91\n",
       "Hungary        2010-01-01                 3.86\n",
       "Indonesia      2010-01-01                 2.24\n",
       "Israel         2010-01-01                 3.99\n",
       "Japan          2010-01-01                 3.50\n",
       "Latvia         2010-01-01                 3.09\n",
       "Lithuania      2010-01-01                 2.87\n",
       "Malaysia       2010-01-01                 2.08\n",
       "Mexico         2010-01-01                 2.50\n",
       "New Zealand    2010-01-01                 3.61\n",
       "Norway         2010-01-01                 7.02\n",
       "Pakistan       2010-01-01                 2.42\n",
       "Peru           2010-01-01                 2.81\n",
       "Philippines    2010-01-01                 2.21\n",
       "Poland         2010-01-01                 2.86\n",
       "Russia         2010-01-01                 2.34\n",
       "Saudi Arabia   2010-01-01                 2.67\n",
       "...                                        ...\n",
       "Italy          2016-01-01                 4.30\n",
       "Japan          2016-01-01                 3.12\n",
       "Malaysia       2016-01-01                 1.82\n",
       "Mexico         2016-01-01                 2.81\n",
       "Netherlands    2016-01-01                 3.71\n",
       "New Zealand    2016-01-01                 3.91\n",
       "Norway         2016-01-01                 5.21\n",
       "Pakistan       2016-01-01                 2.86\n",
       "Peru           2016-01-01                 2.93\n",
       "Philippines    2016-01-01                 2.79\n",
       "Poland         2016-01-01                 2.37\n",
       "Portugal       2016-01-01                 3.23\n",
       "Russia         2016-01-01                 1.53\n",
       "Saudi Arabia   2016-01-01                 3.20\n",
       "Singapore      2016-01-01                 3.27\n",
       "South Africa   2016-01-01                 1.77\n",
       "South Korea    2016-01-01                 3.59\n",
       "Spain          2016-01-01                 3.76\n",
       "Sri Lanka      2016-01-01                 2.43\n",
       "Sweden         2016-01-01                 5.23\n",
       "Switzerland    2016-01-01                 6.44\n",
       "Taiwan         2016-01-01                 2.08\n",
       "Thailand       2016-01-01                 3.09\n",
       "Turkey         2016-01-01                 3.41\n",
       "UAE            2016-01-01                 3.54\n",
       "Ukraine        2016-01-01                 1.54\n",
       "United States  2016-01-01                 4.93\n",
       "Uruguay        2016-01-01                 3.74\n",
       "Venezuela      2016-01-01                 0.66\n",
       "Vietnam        2016-01-01                 2.67\n",
       "\n",
       "[652 rows x 1 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.swaplevel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Population</th>\n",
       "      <th>GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Arab World</th>\n",
       "      <th>2015</th>\n",
       "      <td>392022276.0</td>\n",
       "      <td>2.530102e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>384222592.0</td>\n",
       "      <td>2.873600e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>376504253.0</td>\n",
       "      <td>2.846994e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>368802611.0</td>\n",
       "      <td>2.773270e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>361031820.0</td>\n",
       "      <td>2.497945e+12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Population           GDP\n",
       "country    year                           \n",
       "Arab World 2015  392022276.0  2.530102e+12\n",
       "           2014  384222592.0  2.873600e+12\n",
       "           2013  376504253.0  2.846994e+12\n",
       "           2012  368802611.0  2.773270e+12\n",
       "           2011  361031820.0  2.497945e+12"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world = pd.read_csv(\"worldstats.csv\", index_col=[\"country\",\"year\"])\n",
    "world.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country     year            \n",
       "Arab World  2015  Population    3.920223e+08\n",
       "                  GDP           2.530102e+12\n",
       "            2014  Population    3.842226e+08\n",
       "                  GDP           2.873600e+12\n",
       "            2013  Population    3.765043e+08\n",
       "                  GDP           2.846994e+12\n",
       "            2012  Population    3.688026e+08\n",
       "                  GDP           2.773270e+12\n",
       "            2011  Population    3.610318e+08\n",
       "                  GDP           2.497945e+12\n",
       "            2010  Population    3.531122e+08\n",
       "                  GDP           2.103825e+12\n",
       "            2009  Population    3.450542e+08\n",
       "                  GDP           1.798878e+12\n",
       "            2008  Population    3.368865e+08\n",
       "                  GDP           2.081343e+12\n",
       "            2007  Population    3.287666e+08\n",
       "                  GDP           1.641666e+12\n",
       "            2006  Population    3.209067e+08\n",
       "                  GDP           1.404190e+12\n",
       "            2005  Population    3.134309e+08\n",
       "                  GDP           1.184735e+12\n",
       "            2004  Population    3.063874e+08\n",
       "                  GDP           9.639180e+11\n",
       "            2003  Population    2.997320e+08\n",
       "                  GDP           8.218702e+11\n",
       "            2002  Population    2.934026e+08\n",
       "                  GDP           7.279939e+11\n",
       "            2001  Population    2.872918e+08\n",
       "                  GDP           7.221506e+11\n",
       "                                    ...     \n",
       "Zimbabwe    1974  Population    5.967861e+06\n",
       "                  GDP           3.982161e+09\n",
       "            1973  Population    5.768382e+06\n",
       "                  GDP           3.309354e+09\n",
       "            1972  Population    5.573312e+06\n",
       "                  GDP           2.677729e+09\n",
       "            1971  Population    5.385342e+06\n",
       "                  GDP           2.178716e+09\n",
       "            1970  Population    5.206311e+06\n",
       "                  GDP           1.884206e+09\n",
       "            1969  Population    5.036321e+06\n",
       "                  GDP           1.747999e+09\n",
       "            1968  Population    4.874113e+06\n",
       "                  GDP           1.479600e+09\n",
       "            1967  Population    4.718612e+06\n",
       "                  GDP           1.397002e+09\n",
       "            1966  Population    4.568320e+06\n",
       "                  GDP           1.281750e+09\n",
       "            1965  Population    4.422132e+06\n",
       "                  GDP           1.311436e+09\n",
       "            1964  Population    4.279561e+06\n",
       "                  GDP           1.217138e+09\n",
       "            1963  Population    4.140804e+06\n",
       "                  GDP           1.159512e+09\n",
       "            1962  Population    4.006262e+06\n",
       "                  GDP           1.117602e+09\n",
       "            1961  Population    3.876638e+06\n",
       "                  GDP           1.096647e+09\n",
       "            1960  Population    3.752390e+06\n",
       "                  GDP           1.052990e+09\n",
       "Length: 22422, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world.stack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 11211 entries, (Arab World, 2015) to (Zimbabwe, 1960)\n",
      "Data columns (total 2 columns):\n",
      "Population    11211 non-null float64\n",
      "GDP           11211 non-null float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 210.5+ KB\n"
     ]
    }
   ],
   "source": [
    "world.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Population</th>\n",
       "      <th>GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Arab World</th>\n",
       "      <th>2015</th>\n",
       "      <td>392022276.0</td>\n",
       "      <td>2.530102e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>384222592.0</td>\n",
       "      <td>2.873600e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>376504253.0</td>\n",
       "      <td>2.846994e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>368802611.0</td>\n",
       "      <td>2.773270e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>361031820.0</td>\n",
       "      <td>2.497945e+12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Population           GDP\n",
       "country    year                           \n",
       "Arab World 2015  392022276.0  2.530102e+12\n",
       "           2014  384222592.0  2.873600e+12\n",
       "           2013  376504253.0  2.846994e+12\n",
       "           2012  368802611.0  2.773270e+12\n",
       "           2011  361031820.0  2.497945e+12"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(world.stack().to_frame())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "s = world.stack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Population</th>\n",
       "      <th>GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">Afghanistan</th>\n",
       "      <th>1960</th>\n",
       "      <td>8994793.0</td>\n",
       "      <td>5.377778e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1961</th>\n",
       "      <td>9164945.0</td>\n",
       "      <td>5.488889e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1962</th>\n",
       "      <td>9343772.0</td>\n",
       "      <td>5.466667e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1963</th>\n",
       "      <td>9531555.0</td>\n",
       "      <td>7.511112e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1964</th>\n",
       "      <td>9728645.0</td>\n",
       "      <td>8.000000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1965</th>\n",
       "      <td>9935358.0</td>\n",
       "      <td>1.006667e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1966</th>\n",
       "      <td>10148841.0</td>\n",
       "      <td>1.400000e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1967</th>\n",
       "      <td>10368600.0</td>\n",
       "      <td>1.673333e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1968</th>\n",
       "      <td>10599790.0</td>\n",
       "      <td>1.373333e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969</th>\n",
       "      <td>10849510.0</td>\n",
       "      <td>1.408889e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>11121097.0</td>\n",
       "      <td>1.748887e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1971</th>\n",
       "      <td>11412821.0</td>\n",
       "      <td>1.831109e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1972</th>\n",
       "      <td>11716896.0</td>\n",
       "      <td>1.595555e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>12022514.0</td>\n",
       "      <td>1.733333e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1974</th>\n",
       "      <td>12315553.0</td>\n",
       "      <td>2.155555e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>12582954.0</td>\n",
       "      <td>2.366667e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>12831361.0</td>\n",
       "      <td>2.555556e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1977</th>\n",
       "      <td>13056499.0</td>\n",
       "      <td>2.953333e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1978</th>\n",
       "      <td>13222547.0</td>\n",
       "      <td>3.300000e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1979</th>\n",
       "      <td>13283279.0</td>\n",
       "      <td>3.697940e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>13211412.0</td>\n",
       "      <td>3.641723e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>12996923.0</td>\n",
       "      <td>3.478788e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>20531160.0</td>\n",
       "      <td>2.461666e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>21487079.0</td>\n",
       "      <td>4.128818e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>22507368.0</td>\n",
       "      <td>4.583649e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>23499850.0</td>\n",
       "      <td>5.285462e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>24399948.0</td>\n",
       "      <td>6.275076e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>25183615.0</td>\n",
       "      <td>7.057598e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>25877544.0</td>\n",
       "      <td>9.843842e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>26528741.0</td>\n",
       "      <td>1.019053e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">Zimbabwe</th>\n",
       "      <th>1986</th>\n",
       "      <td>9198874.0</td>\n",
       "      <td>6.217524e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>9535657.0</td>\n",
       "      <td>6.741215e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>9866776.0</td>\n",
       "      <td>7.814784e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>10184966.0</td>\n",
       "      <td>8.286323e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>10484771.0</td>\n",
       "      <td>8.783817e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>10763036.0</td>\n",
       "      <td>8.641482e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>11019717.0</td>\n",
       "      <td>6.751472e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>11256512.0</td>\n",
       "      <td>6.563813e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>11476807.0</td>\n",
       "      <td>6.890675e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>11683136.0</td>\n",
       "      <td>7.111271e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>11877664.0</td>\n",
       "      <td>8.553147e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>12059858.0</td>\n",
       "      <td>8.529572e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>12226742.0</td>\n",
       "      <td>6.401968e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>12374019.0</td>\n",
       "      <td>6.858013e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>12499981.0</td>\n",
       "      <td>6.689958e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>12603988.0</td>\n",
       "      <td>6.777385e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>12691431.0</td>\n",
       "      <td>6.342116e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>12774162.0</td>\n",
       "      <td>5.727592e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>12867828.0</td>\n",
       "      <td>5.805598e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>12984418.0</td>\n",
       "      <td>5.755215e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>13127942.0</td>\n",
       "      <td>5.443896e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>13297798.0</td>\n",
       "      <td>5.291950e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>13495462.0</td>\n",
       "      <td>4.415703e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>13720997.0</td>\n",
       "      <td>8.157077e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>13973897.0</td>\n",
       "      <td>9.422161e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>14255592.0</td>\n",
       "      <td>1.095623e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>14565482.0</td>\n",
       "      <td>1.239272e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>14898092.0</td>\n",
       "      <td>1.349023e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>15245855.0</td>\n",
       "      <td>1.419691e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>15602751.0</td>\n",
       "      <td>1.389294e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11211 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Population           GDP\n",
       "country     year                          \n",
       "Afghanistan 1960   8994793.0  5.377778e+08\n",
       "            1961   9164945.0  5.488889e+08\n",
       "            1962   9343772.0  5.466667e+08\n",
       "            1963   9531555.0  7.511112e+08\n",
       "            1964   9728645.0  8.000000e+08\n",
       "            1965   9935358.0  1.006667e+09\n",
       "            1966  10148841.0  1.400000e+09\n",
       "            1967  10368600.0  1.673333e+09\n",
       "            1968  10599790.0  1.373333e+09\n",
       "            1969  10849510.0  1.408889e+09\n",
       "            1970  11121097.0  1.748887e+09\n",
       "            1971  11412821.0  1.831109e+09\n",
       "            1972  11716896.0  1.595555e+09\n",
       "            1973  12022514.0  1.733333e+09\n",
       "            1974  12315553.0  2.155555e+09\n",
       "            1975  12582954.0  2.366667e+09\n",
       "            1976  12831361.0  2.555556e+09\n",
       "            1977  13056499.0  2.953333e+09\n",
       "            1978  13222547.0  3.300000e+09\n",
       "            1979  13283279.0  3.697940e+09\n",
       "            1980  13211412.0  3.641723e+09\n",
       "            1981  12996923.0  3.478788e+09\n",
       "            2001  20531160.0  2.461666e+09\n",
       "            2002  21487079.0  4.128818e+09\n",
       "            2003  22507368.0  4.583649e+09\n",
       "            2004  23499850.0  5.285462e+09\n",
       "            2005  24399948.0  6.275076e+09\n",
       "            2006  25183615.0  7.057598e+09\n",
       "            2007  25877544.0  9.843842e+09\n",
       "            2008  26528741.0  1.019053e+10\n",
       "...                      ...           ...\n",
       "Zimbabwe    1986   9198874.0  6.217524e+09\n",
       "            1987   9535657.0  6.741215e+09\n",
       "            1988   9866776.0  7.814784e+09\n",
       "            1989  10184966.0  8.286323e+09\n",
       "            1990  10484771.0  8.783817e+09\n",
       "            1991  10763036.0  8.641482e+09\n",
       "            1992  11019717.0  6.751472e+09\n",
       "            1993  11256512.0  6.563813e+09\n",
       "            1994  11476807.0  6.890675e+09\n",
       "            1995  11683136.0  7.111271e+09\n",
       "            1996  11877664.0  8.553147e+09\n",
       "            1997  12059858.0  8.529572e+09\n",
       "            1998  12226742.0  6.401968e+09\n",
       "            1999  12374019.0  6.858013e+09\n",
       "            2000  12499981.0  6.689958e+09\n",
       "            2001  12603988.0  6.777385e+09\n",
       "            2002  12691431.0  6.342116e+09\n",
       "            2003  12774162.0  5.727592e+09\n",
       "            2004  12867828.0  5.805598e+09\n",
       "            2005  12984418.0  5.755215e+09\n",
       "            2006  13127942.0  5.443896e+09\n",
       "            2007  13297798.0  5.291950e+09\n",
       "            2008  13495462.0  4.415703e+09\n",
       "            2009  13720997.0  8.157077e+09\n",
       "            2010  13973897.0  9.422161e+09\n",
       "            2011  14255592.0  1.095623e+10\n",
       "            2012  14565482.0  1.239272e+10\n",
       "            2013  14898092.0  1.349023e+10\n",
       "            2014  15245855.0  1.419691e+10\n",
       "            2015  15602751.0  1.389294e+10\n",
       "\n",
       "[11211 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            year  country               \n",
       "Population  1960  Afghanistan               8.994793e+06\n",
       "                  Albania                            NaN\n",
       "                  Algeria                   1.112489e+07\n",
       "                  Andorra                            NaN\n",
       "                  Angola                             NaN\n",
       "                  Antigua and Barbuda                NaN\n",
       "                  Arab World                         NaN\n",
       "                  Argentina                          NaN\n",
       "                  Armenia                            NaN\n",
       "                  Aruba                              NaN\n",
       "                  Australia                 1.027648e+07\n",
       "                  Austria                   7.047539e+06\n",
       "                  Azerbaijan                         NaN\n",
       "                  Bahamas, The              1.095260e+05\n",
       "                  Bahrain                            NaN\n",
       "                  Bangladesh                4.820070e+07\n",
       "                  Barbados                           NaN\n",
       "                  Belarus                            NaN\n",
       "                  Belgium                   9.153489e+06\n",
       "                  Belize                    9.206800e+04\n",
       "                  Benin                     2.431620e+06\n",
       "                  Bermuda                   4.440000e+04\n",
       "                  Bhutan                             NaN\n",
       "                  Bolivia                   3.693451e+06\n",
       "                  Bosnia and Herzegovina             NaN\n",
       "                  Botswana                  5.240290e+05\n",
       "                  Brazil                    7.249358e+07\n",
       "                  Brunei Darussalam                  NaN\n",
       "                  Bulgaria                           NaN\n",
       "                  Burkina Faso              4.829291e+06\n",
       "                                                ...     \n",
       "GDP         2015  Switzerland               6.647375e+11\n",
       "                  Syrian Arab Republic               NaN\n",
       "                  Tajikistan                7.853450e+09\n",
       "                  Tanzania                  4.489539e+10\n",
       "                  Thailand                  3.952816e+11\n",
       "                  Timor-Leste               1.412378e+09\n",
       "                  Togo                      4.002724e+09\n",
       "                  Tonga                              NaN\n",
       "                  Trinidad and Tobago       2.780575e+10\n",
       "                  Tunisia                   4.301509e+10\n",
       "                  Turkey                    7.182211e+11\n",
       "                  Turkmenistan              3.733423e+10\n",
       "                  Tuvalu                             NaN\n",
       "                  Uganda                    2.636924e+10\n",
       "                  Ukraine                   9.061502e+10\n",
       "                  United Arab Emirates      3.702927e+11\n",
       "                  United Kingdom            2.848755e+12\n",
       "                  United States             1.794700e+13\n",
       "                  Upper middle income       1.973288e+13\n",
       "                  Uruguay                   5.344270e+10\n",
       "                  Uzbekistan                6.673280e+10\n",
       "                  Vanuatu                            NaN\n",
       "                  Venezuela, RB                      NaN\n",
       "                  Vietnam                   1.935994e+11\n",
       "                  Virgin Islands (U.S.)              NaN\n",
       "                  West Bank and Gaza        1.267740e+10\n",
       "                  World                     7.343364e+13\n",
       "                  Yemen, Rep.                        NaN\n",
       "                  Zambia                    2.120156e+10\n",
       "                  Zimbabwe                  1.389294e+10\n",
       "Length: 28224, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.unstack().unstack().unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>1966</th>\n",
       "      <th>1967</th>\n",
       "      <th>1968</th>\n",
       "      <th>1969</th>\n",
       "      <th>...</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\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 rowspan=\"2\" valign=\"top\">Afghanistan</th>\n",
       "      <th>Population</th>\n",
       "      <td>8.994793e+06</td>\n",
       "      <td>9.164945e+06</td>\n",
       "      <td>9.343772e+06</td>\n",
       "      <td>9.531555e+06</td>\n",
       "      <td>9.728645e+06</td>\n",
       "      <td>9.935358e+06</td>\n",
       "      <td>1.014884e+07</td>\n",
       "      <td>1.036860e+07</td>\n",
       "      <td>1.059979e+07</td>\n",
       "      <td>1.084951e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>2.518362e+07</td>\n",
       "      <td>2.587754e+07</td>\n",
       "      <td>2.652874e+07</td>\n",
       "      <td>2.720729e+07</td>\n",
       "      <td>2.796221e+07</td>\n",
       "      <td>2.880917e+07</td>\n",
       "      <td>2.972680e+07</td>\n",
       "      <td>3.068250e+07</td>\n",
       "      <td>3.162751e+07</td>\n",
       "      <td>3.252656e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>5.377778e+08</td>\n",
       "      <td>5.488889e+08</td>\n",
       "      <td>5.466667e+08</td>\n",
       "      <td>7.511112e+08</td>\n",
       "      <td>8.000000e+08</td>\n",
       "      <td>1.006667e+09</td>\n",
       "      <td>1.400000e+09</td>\n",
       "      <td>1.673333e+09</td>\n",
       "      <td>1.373333e+09</td>\n",
       "      <td>1.408889e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>7.057598e+09</td>\n",
       "      <td>9.843842e+09</td>\n",
       "      <td>1.019053e+10</td>\n",
       "      <td>1.248694e+10</td>\n",
       "      <td>1.593680e+10</td>\n",
       "      <td>1.793024e+10</td>\n",
       "      <td>2.053654e+10</td>\n",
       "      <td>2.004633e+10</td>\n",
       "      <td>2.005019e+10</td>\n",
       "      <td>1.919944e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Albania</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.992547e+06</td>\n",
       "      <td>2.970017e+06</td>\n",
       "      <td>2.947314e+06</td>\n",
       "      <td>2.927519e+06</td>\n",
       "      <td>2.913021e+06</td>\n",
       "      <td>2.904780e+06</td>\n",
       "      <td>2.900247e+06</td>\n",
       "      <td>2.896652e+06</td>\n",
       "      <td>2.893654e+06</td>\n",
       "      <td>2.889167e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.992642e+09</td>\n",
       "      <td>1.070101e+10</td>\n",
       "      <td>1.288135e+10</td>\n",
       "      <td>1.204421e+10</td>\n",
       "      <td>1.192695e+10</td>\n",
       "      <td>1.289087e+10</td>\n",
       "      <td>1.231978e+10</td>\n",
       "      <td>1.278103e+10</td>\n",
       "      <td>1.327796e+10</td>\n",
       "      <td>1.145560e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Algeria</th>\n",
       "      <th>Population</th>\n",
       "      <td>1.112489e+07</td>\n",
       "      <td>1.140486e+07</td>\n",
       "      <td>1.169015e+07</td>\n",
       "      <td>1.198513e+07</td>\n",
       "      <td>1.229597e+07</td>\n",
       "      <td>1.262695e+07</td>\n",
       "      <td>1.298027e+07</td>\n",
       "      <td>1.335420e+07</td>\n",
       "      <td>1.374438e+07</td>\n",
       "      <td>1.414444e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>3.374933e+07</td>\n",
       "      <td>3.426197e+07</td>\n",
       "      <td>3.481106e+07</td>\n",
       "      <td>3.540179e+07</td>\n",
       "      <td>3.603616e+07</td>\n",
       "      <td>3.671713e+07</td>\n",
       "      <td>3.743943e+07</td>\n",
       "      <td>3.818614e+07</td>\n",
       "      <td>3.893433e+07</td>\n",
       "      <td>3.966652e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>2.723638e+09</td>\n",
       "      <td>2.434767e+09</td>\n",
       "      <td>2.001461e+09</td>\n",
       "      <td>2.703004e+09</td>\n",
       "      <td>2.909340e+09</td>\n",
       "      <td>3.136284e+09</td>\n",
       "      <td>3.039859e+09</td>\n",
       "      <td>3.370870e+09</td>\n",
       "      <td>3.852147e+09</td>\n",
       "      <td>4.257253e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>1.170273e+11</td>\n",
       "      <td>1.349771e+11</td>\n",
       "      <td>1.710007e+11</td>\n",
       "      <td>1.372110e+11</td>\n",
       "      <td>1.612073e+11</td>\n",
       "      <td>2.000131e+11</td>\n",
       "      <td>2.090474e+11</td>\n",
       "      <td>2.097035e+11</td>\n",
       "      <td>2.135185e+11</td>\n",
       "      <td>1.668386e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Andorra</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.337300e+04</td>\n",
       "      <td>8.487800e+04</td>\n",
       "      <td>8.561600e+04</td>\n",
       "      <td>8.547400e+04</td>\n",
       "      <td>8.441900e+04</td>\n",
       "      <td>8.232600e+04</td>\n",
       "      <td>7.931600e+04</td>\n",
       "      <td>7.590200e+04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.536452e+09</td>\n",
       "      <td>4.010785e+09</td>\n",
       "      <td>4.001349e+09</td>\n",
       "      <td>3.649863e+09</td>\n",
       "      <td>3.346317e+09</td>\n",
       "      <td>3.427236e+09</td>\n",
       "      <td>3.146178e+09</td>\n",
       "      <td>3.249101e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Angola</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.854147e+07</td>\n",
       "      <td>1.918391e+07</td>\n",
       "      <td>1.984225e+07</td>\n",
       "      <td>2.052010e+07</td>\n",
       "      <td>2.121995e+07</td>\n",
       "      <td>2.194230e+07</td>\n",
       "      <td>2.268563e+07</td>\n",
       "      <td>2.344820e+07</td>\n",
       "      <td>2.422752e+07</td>\n",
       "      <td>2.502197e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.178948e+10</td>\n",
       "      <td>6.044892e+10</td>\n",
       "      <td>8.417803e+10</td>\n",
       "      <td>7.549238e+10</td>\n",
       "      <td>8.247091e+10</td>\n",
       "      <td>1.041159e+11</td>\n",
       "      <td>1.153984e+11</td>\n",
       "      <td>1.249121e+11</td>\n",
       "      <td>1.267751e+11</td>\n",
       "      <td>1.026431e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Antigua and Barbuda</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.346700e+04</td>\n",
       "      <td>8.439700e+04</td>\n",
       "      <td>8.535000e+04</td>\n",
       "      <td>8.630000e+04</td>\n",
       "      <td>8.723300e+04</td>\n",
       "      <td>8.815200e+04</td>\n",
       "      <td>8.906900e+04</td>\n",
       "      <td>8.998500e+04</td>\n",
       "      <td>9.090000e+04</td>\n",
       "      <td>9.181800e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.135144e+09</td>\n",
       "      <td>1.289254e+09</td>\n",
       "      <td>1.347350e+09</td>\n",
       "      <td>1.206410e+09</td>\n",
       "      <td>1.135539e+09</td>\n",
       "      <td>1.129918e+09</td>\n",
       "      <td>1.204713e+09</td>\n",
       "      <td>1.200588e+09</td>\n",
       "      <td>1.220976e+09</td>\n",
       "      <td>1.297285e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Arab World</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.155571e+08</td>\n",
       "      <td>1.188239e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>3.209067e+08</td>\n",
       "      <td>3.287666e+08</td>\n",
       "      <td>3.368865e+08</td>\n",
       "      <td>3.450542e+08</td>\n",
       "      <td>3.531122e+08</td>\n",
       "      <td>3.610318e+08</td>\n",
       "      <td>3.688026e+08</td>\n",
       "      <td>3.765043e+08</td>\n",
       "      <td>3.842226e+08</td>\n",
       "      <td>3.920223e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.552596e+10</td>\n",
       "      <td>2.817577e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.404190e+12</td>\n",
       "      <td>1.641666e+12</td>\n",
       "      <td>2.081343e+12</td>\n",
       "      <td>1.798878e+12</td>\n",
       "      <td>2.103825e+12</td>\n",
       "      <td>2.497945e+12</td>\n",
       "      <td>2.773270e+12</td>\n",
       "      <td>2.846994e+12</td>\n",
       "      <td>2.873600e+12</td>\n",
       "      <td>2.530102e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Argentina</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.128768e+07</td>\n",
       "      <td>2.162184e+07</td>\n",
       "      <td>2.195393e+07</td>\n",
       "      <td>2.228339e+07</td>\n",
       "      <td>2.260875e+07</td>\n",
       "      <td>2.293220e+07</td>\n",
       "      <td>2.326127e+07</td>\n",
       "      <td>2.360599e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>3.955875e+07</td>\n",
       "      <td>3.996990e+07</td>\n",
       "      <td>4.038186e+07</td>\n",
       "      <td>4.079864e+07</td>\n",
       "      <td>4.122288e+07</td>\n",
       "      <td>4.165562e+07</td>\n",
       "      <td>4.209522e+07</td>\n",
       "      <td>4.253830e+07</td>\n",
       "      <td>4.298003e+07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.445060e+10</td>\n",
       "      <td>1.827212e+10</td>\n",
       "      <td>2.560525e+10</td>\n",
       "      <td>2.834471e+10</td>\n",
       "      <td>2.863047e+10</td>\n",
       "      <td>2.425667e+10</td>\n",
       "      <td>2.643686e+10</td>\n",
       "      <td>3.125628e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.626665e+11</td>\n",
       "      <td>3.293175e+11</td>\n",
       "      <td>4.037820e+11</td>\n",
       "      <td>3.766279e+11</td>\n",
       "      <td>4.616402e+11</td>\n",
       "      <td>5.578902e+11</td>\n",
       "      <td>6.043785e+11</td>\n",
       "      <td>6.239320e+11</td>\n",
       "      <td>5.480549e+11</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Armenia</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.002161e+06</td>\n",
       "      <td>2.988117e+06</td>\n",
       "      <td>2.975029e+06</td>\n",
       "      <td>2.966108e+06</td>\n",
       "      <td>2.963496e+06</td>\n",
       "      <td>2.967984e+06</td>\n",
       "      <td>2.978339e+06</td>\n",
       "      <td>2.992192e+06</td>\n",
       "      <td>3.006154e+06</td>\n",
       "      <td>3.017712e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.384452e+09</td>\n",
       "      <td>9.206302e+09</td>\n",
       "      <td>1.166204e+10</td>\n",
       "      <td>8.647937e+09</td>\n",
       "      <td>9.260285e+09</td>\n",
       "      <td>1.014211e+10</td>\n",
       "      <td>1.061932e+10</td>\n",
       "      <td>1.112147e+10</td>\n",
       "      <td>1.164444e+10</td>\n",
       "      <td>1.056140e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Aruba</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.008300e+05</td>\n",
       "      <td>1.012180e+05</td>\n",
       "      <td>1.013420e+05</td>\n",
       "      <td>1.014160e+05</td>\n",
       "      <td>1.015970e+05</td>\n",
       "      <td>1.019360e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.421475e+09</td>\n",
       "      <td>2.623726e+09</td>\n",
       "      <td>2.791961e+09</td>\n",
       "      <td>2.498933e+09</td>\n",
       "      <td>2.467704e+09</td>\n",
       "      <td>2.584464e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Australia</th>\n",
       "      <th>Population</th>\n",
       "      <td>1.027648e+07</td>\n",
       "      <td>1.048300e+07</td>\n",
       "      <td>1.074200e+07</td>\n",
       "      <td>1.095000e+07</td>\n",
       "      <td>1.116700e+07</td>\n",
       "      <td>1.138800e+07</td>\n",
       "      <td>1.165100e+07</td>\n",
       "      <td>1.179900e+07</td>\n",
       "      <td>1.200900e+07</td>\n",
       "      <td>1.226300e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>2.069790e+07</td>\n",
       "      <td>2.082760e+07</td>\n",
       "      <td>2.124920e+07</td>\n",
       "      <td>2.169170e+07</td>\n",
       "      <td>2.203175e+07</td>\n",
       "      <td>2.234002e+07</td>\n",
       "      <td>2.272825e+07</td>\n",
       "      <td>2.311735e+07</td>\n",
       "      <td>2.346409e+07</td>\n",
       "      <td>2.378117e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.856759e+10</td>\n",
       "      <td>1.963938e+10</td>\n",
       "      <td>1.988353e+10</td>\n",
       "      <td>2.149737e+10</td>\n",
       "      <td>2.375406e+10</td>\n",
       "      <td>2.592564e+10</td>\n",
       "      <td>2.725053e+10</td>\n",
       "      <td>3.037854e+10</td>\n",
       "      <td>3.264195e+10</td>\n",
       "      <td>3.660656e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>7.468808e+11</td>\n",
       "      <td>8.530533e+11</td>\n",
       "      <td>1.054558e+12</td>\n",
       "      <td>9.265638e+11</td>\n",
       "      <td>1.142251e+12</td>\n",
       "      <td>1.389919e+12</td>\n",
       "      <td>1.537478e+12</td>\n",
       "      <td>1.563951e+12</td>\n",
       "      <td>1.454675e+12</td>\n",
       "      <td>1.339539e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Austria</th>\n",
       "      <th>Population</th>\n",
       "      <td>7.047539e+06</td>\n",
       "      <td>7.086299e+06</td>\n",
       "      <td>7.129864e+06</td>\n",
       "      <td>7.175811e+06</td>\n",
       "      <td>7.223801e+06</td>\n",
       "      <td>7.270889e+06</td>\n",
       "      <td>7.322066e+06</td>\n",
       "      <td>7.376998e+06</td>\n",
       "      <td>7.415403e+06</td>\n",
       "      <td>7.441055e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>8.268641e+06</td>\n",
       "      <td>8.295487e+06</td>\n",
       "      <td>8.321496e+06</td>\n",
       "      <td>8.343323e+06</td>\n",
       "      <td>8.363404e+06</td>\n",
       "      <td>8.391643e+06</td>\n",
       "      <td>8.429991e+06</td>\n",
       "      <td>8.479375e+06</td>\n",
       "      <td>8.541575e+06</td>\n",
       "      <td>8.611088e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>6.592694e+09</td>\n",
       "      <td>7.311750e+09</td>\n",
       "      <td>7.756110e+09</td>\n",
       "      <td>8.374175e+09</td>\n",
       "      <td>9.169984e+09</td>\n",
       "      <td>9.994071e+09</td>\n",
       "      <td>1.088768e+10</td>\n",
       "      <td>1.157943e+10</td>\n",
       "      <td>1.244063e+10</td>\n",
       "      <td>1.358280e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>3.343094e+11</td>\n",
       "      <td>3.864590e+11</td>\n",
       "      <td>4.276115e+11</td>\n",
       "      <td>3.975943e+11</td>\n",
       "      <td>3.902351e+11</td>\n",
       "      <td>4.290107e+11</td>\n",
       "      <td>4.073730e+11</td>\n",
       "      <td>4.286986e+11</td>\n",
       "      <td>4.368875e+11</td>\n",
       "      <td>3.740559e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Azerbaijan</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.484550e+06</td>\n",
       "      <td>8.581300e+06</td>\n",
       "      <td>8.763400e+06</td>\n",
       "      <td>8.947243e+06</td>\n",
       "      <td>9.054332e+06</td>\n",
       "      <td>9.173082e+06</td>\n",
       "      <td>9.295784e+06</td>\n",
       "      <td>9.416801e+06</td>\n",
       "      <td>9.535079e+06</td>\n",
       "      <td>9.651349e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.098302e+10</td>\n",
       "      <td>3.305034e+10</td>\n",
       "      <td>4.885248e+10</td>\n",
       "      <td>4.429149e+10</td>\n",
       "      <td>5.290270e+10</td>\n",
       "      <td>6.595163e+10</td>\n",
       "      <td>6.873091e+10</td>\n",
       "      <td>7.356048e+10</td>\n",
       "      <td>7.519801e+10</td>\n",
       "      <td>5.304714e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Bahamas, The</th>\n",
       "      <th>Population</th>\n",
       "      <td>1.095260e+05</td>\n",
       "      <td>1.151080e+05</td>\n",
       "      <td>1.210830e+05</td>\n",
       "      <td>1.273310e+05</td>\n",
       "      <td>1.336970e+05</td>\n",
       "      <td>1.400490e+05</td>\n",
       "      <td>1.463640e+05</td>\n",
       "      <td>1.526070e+05</td>\n",
       "      <td>1.586290e+05</td>\n",
       "      <td>1.642500e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>3.358010e+05</td>\n",
       "      <td>3.422590e+05</td>\n",
       "      <td>3.485870e+05</td>\n",
       "      <td>3.547800e+05</td>\n",
       "      <td>3.608300e+05</td>\n",
       "      <td>3.667110e+05</td>\n",
       "      <td>3.723880e+05</td>\n",
       "      <td>3.778410e+05</td>\n",
       "      <td>3.830540e+05</td>\n",
       "      <td>3.880190e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.698023e+08</td>\n",
       "      <td>1.900962e+08</td>\n",
       "      <td>2.122528e+08</td>\n",
       "      <td>2.377428e+08</td>\n",
       "      <td>2.666641e+08</td>\n",
       "      <td>3.003922e+08</td>\n",
       "      <td>3.400000e+08</td>\n",
       "      <td>3.901961e+08</td>\n",
       "      <td>4.449020e+08</td>\n",
       "      <td>5.281373e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>7.965588e+09</td>\n",
       "      <td>8.318996e+09</td>\n",
       "      <td>8.246650e+09</td>\n",
       "      <td>7.820420e+09</td>\n",
       "      <td>7.909580e+09</td>\n",
       "      <td>7.889750e+09</td>\n",
       "      <td>8.234470e+09</td>\n",
       "      <td>8.431750e+09</td>\n",
       "      <td>8.510500e+09</td>\n",
       "      <td>8.884441e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Bahrain</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>9.408080e+05</td>\n",
       "      <td>1.026568e+06</td>\n",
       "      <td>1.115777e+06</td>\n",
       "      <td>1.196774e+06</td>\n",
       "      <td>1.261319e+06</td>\n",
       "      <td>1.306014e+06</td>\n",
       "      <td>1.333577e+06</td>\n",
       "      <td>1.349427e+06</td>\n",
       "      <td>1.361930e+06</td>\n",
       "      <td>1.377237e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.850505e+10</td>\n",
       "      <td>2.173000e+10</td>\n",
       "      <td>2.571088e+10</td>\n",
       "      <td>2.293822e+10</td>\n",
       "      <td>2.571327e+10</td>\n",
       "      <td>2.904407e+10</td>\n",
       "      <td>3.075646e+10</td>\n",
       "      <td>3.289761e+10</td>\n",
       "      <td>3.385106e+10</td>\n",
       "      <td>3.222149e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">United Arab Emirates</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5.171255e+06</td>\n",
       "      <td>6.010100e+06</td>\n",
       "      <td>6.900142e+06</td>\n",
       "      <td>7.705423e+06</td>\n",
       "      <td>8.329453e+06</td>\n",
       "      <td>8.734722e+06</td>\n",
       "      <td>8.952542e+06</td>\n",
       "      <td>9.039978e+06</td>\n",
       "      <td>9.086139e+06</td>\n",
       "      <td>9.156963e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.221059e+11</td>\n",
       "      <td>2.579161e+11</td>\n",
       "      <td>3.154746e+11</td>\n",
       "      <td>2.535474e+11</td>\n",
       "      <td>2.860493e+11</td>\n",
       "      <td>3.485261e+11</td>\n",
       "      <td>3.734295e+11</td>\n",
       "      <td>3.871921e+11</td>\n",
       "      <td>3.994513e+11</td>\n",
       "      <td>3.702927e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">United Kingdom</th>\n",
       "      <th>Population</th>\n",
       "      <td>5.240000e+07</td>\n",
       "      <td>5.280000e+07</td>\n",
       "      <td>5.325000e+07</td>\n",
       "      <td>5.365000e+07</td>\n",
       "      <td>5.400000e+07</td>\n",
       "      <td>5.434805e+07</td>\n",
       "      <td>5.464850e+07</td>\n",
       "      <td>5.494360e+07</td>\n",
       "      <td>5.521170e+07</td>\n",
       "      <td>5.544175e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>6.084682e+07</td>\n",
       "      <td>6.132246e+07</td>\n",
       "      <td>6.180700e+07</td>\n",
       "      <td>6.227627e+07</td>\n",
       "      <td>6.276636e+07</td>\n",
       "      <td>6.325892e+07</td>\n",
       "      <td>6.370030e+07</td>\n",
       "      <td>6.412823e+07</td>\n",
       "      <td>6.461316e+07</td>\n",
       "      <td>6.513823e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>7.232805e+10</td>\n",
       "      <td>7.669436e+10</td>\n",
       "      <td>8.060194e+10</td>\n",
       "      <td>8.544377e+10</td>\n",
       "      <td>9.338760e+10</td>\n",
       "      <td>1.005958e+11</td>\n",
       "      <td>1.070907e+11</td>\n",
       "      <td>1.111854e+11</td>\n",
       "      <td>1.047027e+11</td>\n",
       "      <td>1.126769e+11</td>\n",
       "      <td>...</td>\n",
       "      <td>2.588077e+12</td>\n",
       "      <td>2.969734e+12</td>\n",
       "      <td>2.793377e+12</td>\n",
       "      <td>2.314577e+12</td>\n",
       "      <td>2.403504e+12</td>\n",
       "      <td>2.594905e+12</td>\n",
       "      <td>2.630473e+12</td>\n",
       "      <td>2.712296e+12</td>\n",
       "      <td>2.990201e+12</td>\n",
       "      <td>2.848755e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">United States</th>\n",
       "      <th>Population</th>\n",
       "      <td>1.806710e+08</td>\n",
       "      <td>1.836910e+08</td>\n",
       "      <td>1.865380e+08</td>\n",
       "      <td>1.892420e+08</td>\n",
       "      <td>1.918890e+08</td>\n",
       "      <td>1.943030e+08</td>\n",
       "      <td>1.965600e+08</td>\n",
       "      <td>1.987120e+08</td>\n",
       "      <td>2.007060e+08</td>\n",
       "      <td>2.026770e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>2.983799e+08</td>\n",
       "      <td>3.012312e+08</td>\n",
       "      <td>3.040940e+08</td>\n",
       "      <td>3.067715e+08</td>\n",
       "      <td>3.093469e+08</td>\n",
       "      <td>3.117189e+08</td>\n",
       "      <td>3.141026e+08</td>\n",
       "      <td>3.164274e+08</td>\n",
       "      <td>3.189074e+08</td>\n",
       "      <td>3.214188e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>5.433000e+11</td>\n",
       "      <td>5.633000e+11</td>\n",
       "      <td>6.051000e+11</td>\n",
       "      <td>6.386000e+11</td>\n",
       "      <td>6.858000e+11</td>\n",
       "      <td>7.437000e+11</td>\n",
       "      <td>8.150000e+11</td>\n",
       "      <td>8.617000e+11</td>\n",
       "      <td>9.425000e+11</td>\n",
       "      <td>1.019900e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>1.385589e+13</td>\n",
       "      <td>1.447764e+13</td>\n",
       "      <td>1.471858e+13</td>\n",
       "      <td>1.441874e+13</td>\n",
       "      <td>1.496437e+13</td>\n",
       "      <td>1.551793e+13</td>\n",
       "      <td>1.615526e+13</td>\n",
       "      <td>1.666316e+13</td>\n",
       "      <td>1.734807e+13</td>\n",
       "      <td>1.794700e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Upper middle income</th>\n",
       "      <th>Population</th>\n",
       "      <td>1.154592e+09</td>\n",
       "      <td>1.159145e+09</td>\n",
       "      <td>1.176093e+09</td>\n",
       "      <td>1.204372e+09</td>\n",
       "      <td>1.232266e+09</td>\n",
       "      <td>1.261069e+09</td>\n",
       "      <td>1.292755e+09</td>\n",
       "      <td>1.323615e+09</td>\n",
       "      <td>1.355381e+09</td>\n",
       "      <td>1.388827e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>2.380136e+09</td>\n",
       "      <td>2.397567e+09</td>\n",
       "      <td>2.415306e+09</td>\n",
       "      <td>2.433652e+09</td>\n",
       "      <td>2.452055e+09</td>\n",
       "      <td>2.470971e+09</td>\n",
       "      <td>2.490586e+09</td>\n",
       "      <td>2.510573e+09</td>\n",
       "      <td>2.530632e+09</td>\n",
       "      <td>2.550326e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.854612e+11</td>\n",
       "      <td>1.690732e+11</td>\n",
       "      <td>1.777957e+11</td>\n",
       "      <td>1.955819e+11</td>\n",
       "      <td>2.144250e+11</td>\n",
       "      <td>2.397244e+11</td>\n",
       "      <td>2.666625e+11</td>\n",
       "      <td>2.766866e+11</td>\n",
       "      <td>2.898954e+11</td>\n",
       "      <td>3.221882e+11</td>\n",
       "      <td>...</td>\n",
       "      <td>8.620784e+12</td>\n",
       "      <td>1.073130e+13</td>\n",
       "      <td>1.312644e+13</td>\n",
       "      <td>1.263584e+13</td>\n",
       "      <td>1.530029e+13</td>\n",
       "      <td>1.829801e+13</td>\n",
       "      <td>1.955543e+13</td>\n",
       "      <td>2.080729e+13</td>\n",
       "      <td>2.133305e+13</td>\n",
       "      <td>1.973288e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Uruguay</th>\n",
       "      <th>Population</th>\n",
       "      <td>2.538651e+06</td>\n",
       "      <td>2.571691e+06</td>\n",
       "      <td>2.603887e+06</td>\n",
       "      <td>2.635128e+06</td>\n",
       "      <td>2.665387e+06</td>\n",
       "      <td>2.694535e+06</td>\n",
       "      <td>2.722874e+06</td>\n",
       "      <td>2.750093e+06</td>\n",
       "      <td>2.774771e+06</td>\n",
       "      <td>2.795044e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>3.331041e+06</td>\n",
       "      <td>3.339750e+06</td>\n",
       "      <td>3.350832e+06</td>\n",
       "      <td>3.362761e+06</td>\n",
       "      <td>3.374414e+06</td>\n",
       "      <td>3.385610e+06</td>\n",
       "      <td>3.396753e+06</td>\n",
       "      <td>3.407969e+06</td>\n",
       "      <td>3.419516e+06</td>\n",
       "      <td>3.431555e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.242289e+09</td>\n",
       "      <td>1.547389e+09</td>\n",
       "      <td>1.710004e+09</td>\n",
       "      <td>1.539682e+09</td>\n",
       "      <td>1.975702e+09</td>\n",
       "      <td>1.890769e+09</td>\n",
       "      <td>1.809184e+09</td>\n",
       "      <td>1.597721e+09</td>\n",
       "      <td>1.593675e+09</td>\n",
       "      <td>2.004435e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>1.957946e+10</td>\n",
       "      <td>2.341057e+10</td>\n",
       "      <td>3.036621e+10</td>\n",
       "      <td>3.166091e+10</td>\n",
       "      <td>4.028468e+10</td>\n",
       "      <td>4.796244e+10</td>\n",
       "      <td>5.126540e+10</td>\n",
       "      <td>5.753123e+10</td>\n",
       "      <td>5.723577e+10</td>\n",
       "      <td>5.344270e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Uzbekistan</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.648825e+07</td>\n",
       "      <td>2.686800e+07</td>\n",
       "      <td>2.730280e+07</td>\n",
       "      <td>2.776740e+07</td>\n",
       "      <td>2.856240e+07</td>\n",
       "      <td>2.933940e+07</td>\n",
       "      <td>2.977450e+07</td>\n",
       "      <td>3.024320e+07</td>\n",
       "      <td>3.075770e+07</td>\n",
       "      <td>3.129950e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.703090e+10</td>\n",
       "      <td>2.231139e+10</td>\n",
       "      <td>2.793403e+10</td>\n",
       "      <td>3.281683e+10</td>\n",
       "      <td>3.933277e+10</td>\n",
       "      <td>4.532432e+10</td>\n",
       "      <td>5.118344e+10</td>\n",
       "      <td>5.679566e+10</td>\n",
       "      <td>6.313285e+10</td>\n",
       "      <td>6.673280e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Vanuatu</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.146350e+05</td>\n",
       "      <td>2.199560e+05</td>\n",
       "      <td>2.253350e+05</td>\n",
       "      <td>2.307820e+05</td>\n",
       "      <td>2.362990e+05</td>\n",
       "      <td>2.418760e+05</td>\n",
       "      <td>2.474980e+05</td>\n",
       "      <td>2.531650e+05</td>\n",
       "      <td>2.588830e+05</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.393768e+08</td>\n",
       "      <td>5.264283e+08</td>\n",
       "      <td>6.079586e+08</td>\n",
       "      <td>6.100666e+08</td>\n",
       "      <td>7.008043e+08</td>\n",
       "      <td>7.921497e+08</td>\n",
       "      <td>7.817029e+08</td>\n",
       "      <td>8.017876e+08</td>\n",
       "      <td>8.149546e+08</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Venezuela, RB</th>\n",
       "      <th>Population</th>\n",
       "      <td>8.146845e+06</td>\n",
       "      <td>8.461684e+06</td>\n",
       "      <td>8.790590e+06</td>\n",
       "      <td>9.130346e+06</td>\n",
       "      <td>9.476255e+06</td>\n",
       "      <td>9.824694e+06</td>\n",
       "      <td>1.017514e+07</td>\n",
       "      <td>1.052805e+07</td>\n",
       "      <td>1.088200e+07</td>\n",
       "      <td>1.123549e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>2.722123e+07</td>\n",
       "      <td>2.767066e+07</td>\n",
       "      <td>2.811672e+07</td>\n",
       "      <td>2.855861e+07</td>\n",
       "      <td>2.899574e+07</td>\n",
       "      <td>2.942763e+07</td>\n",
       "      <td>2.985424e+07</td>\n",
       "      <td>3.027604e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>8.607600e+09</td>\n",
       "      <td>8.923367e+09</td>\n",
       "      <td>9.873398e+09</td>\n",
       "      <td>1.066338e+10</td>\n",
       "      <td>9.113581e+09</td>\n",
       "      <td>9.602945e+09</td>\n",
       "      <td>1.009657e+10</td>\n",
       "      <td>1.047278e+10</td>\n",
       "      <td>1.147091e+10</td>\n",
       "      <td>1.192757e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.834775e+11</td>\n",
       "      <td>2.303642e+11</td>\n",
       "      <td>3.156002e+11</td>\n",
       "      <td>3.294190e+11</td>\n",
       "      <td>3.938015e+11</td>\n",
       "      <td>3.164822e+11</td>\n",
       "      <td>3.812862e+11</td>\n",
       "      <td>3.713366e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Vietnam</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>8.331120e+07</td>\n",
       "      <td>8.421850e+07</td>\n",
       "      <td>8.511870e+07</td>\n",
       "      <td>8.602500e+07</td>\n",
       "      <td>8.693250e+07</td>\n",
       "      <td>8.786030e+07</td>\n",
       "      <td>8.880920e+07</td>\n",
       "      <td>8.975950e+07</td>\n",
       "      <td>9.072890e+07</td>\n",
       "      <td>9.170380e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.637166e+10</td>\n",
       "      <td>7.741443e+10</td>\n",
       "      <td>9.913030e+10</td>\n",
       "      <td>1.060146e+11</td>\n",
       "      <td>1.159317e+11</td>\n",
       "      <td>1.355395e+11</td>\n",
       "      <td>1.558200e+11</td>\n",
       "      <td>1.712220e+11</td>\n",
       "      <td>1.862047e+11</td>\n",
       "      <td>1.935994e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Virgin Islands (U.S.)</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.200000e+04</td>\n",
       "      <td>3.410000e+04</td>\n",
       "      <td>3.630000e+04</td>\n",
       "      <td>3.870000e+04</td>\n",
       "      <td>4.130000e+04</td>\n",
       "      <td>4.400000e+04</td>\n",
       "      <td>4.730000e+04</td>\n",
       "      <td>5.080000e+04</td>\n",
       "      <td>5.460000e+04</td>\n",
       "      <td>5.860000e+04</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>2.420000e+07</td>\n",
       "      <td>2.570000e+07</td>\n",
       "      <td>3.690000e+07</td>\n",
       "      <td>4.140000e+07</td>\n",
       "      <td>5.380000e+07</td>\n",
       "      <td>6.650000e+07</td>\n",
       "      <td>8.410000e+07</td>\n",
       "      <td>1.154000e+08</td>\n",
       "      <td>1.738000e+08</td>\n",
       "      <td>2.113000e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">West Bank and Gaza</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.406334e+06</td>\n",
       "      <td>3.494496e+06</td>\n",
       "      <td>3.596688e+06</td>\n",
       "      <td>3.702218e+06</td>\n",
       "      <td>3.811102e+06</td>\n",
       "      <td>3.927051e+06</td>\n",
       "      <td>4.046901e+06</td>\n",
       "      <td>4.169506e+06</td>\n",
       "      <td>4.294682e+06</td>\n",
       "      <td>4.422143e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.910100e+09</td>\n",
       "      <td>5.505800e+09</td>\n",
       "      <td>6.673500e+09</td>\n",
       "      <td>7.268200e+09</td>\n",
       "      <td>8.913100e+09</td>\n",
       "      <td>1.045985e+10</td>\n",
       "      <td>1.127940e+10</td>\n",
       "      <td>1.247600e+10</td>\n",
       "      <td>1.271560e+10</td>\n",
       "      <td>1.267740e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">World</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.035056e+09</td>\n",
       "      <td>3.076121e+09</td>\n",
       "      <td>3.129064e+09</td>\n",
       "      <td>3.193947e+09</td>\n",
       "      <td>3.259355e+09</td>\n",
       "      <td>3.326054e+09</td>\n",
       "      <td>3.395866e+09</td>\n",
       "      <td>3.465297e+09</td>\n",
       "      <td>3.535512e+09</td>\n",
       "      <td>3.609910e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>6.594722e+09</td>\n",
       "      <td>6.675833e+09</td>\n",
       "      <td>6.758303e+09</td>\n",
       "      <td>6.840956e+09</td>\n",
       "      <td>6.923684e+09</td>\n",
       "      <td>7.006908e+09</td>\n",
       "      <td>7.089452e+09</td>\n",
       "      <td>7.176092e+09</td>\n",
       "      <td>7.260780e+09</td>\n",
       "      <td>7.346633e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.364643e+12</td>\n",
       "      <td>1.420440e+12</td>\n",
       "      <td>1.524573e+12</td>\n",
       "      <td>1.638187e+12</td>\n",
       "      <td>1.799675e+12</td>\n",
       "      <td>1.959900e+12</td>\n",
       "      <td>2.125397e+12</td>\n",
       "      <td>2.262923e+12</td>\n",
       "      <td>2.440549e+12</td>\n",
       "      <td>2.686747e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>5.107451e+13</td>\n",
       "      <td>5.758343e+13</td>\n",
       "      <td>6.312856e+13</td>\n",
       "      <td>5.983553e+13</td>\n",
       "      <td>6.564782e+13</td>\n",
       "      <td>7.284314e+13</td>\n",
       "      <td>7.442836e+13</td>\n",
       "      <td>7.643132e+13</td>\n",
       "      <td>7.810634e+13</td>\n",
       "      <td>7.343364e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Yemen, Rep.</th>\n",
       "      <th>Population</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.109397e+07</td>\n",
       "      <td>2.170110e+07</td>\n",
       "      <td>2.232270e+07</td>\n",
       "      <td>2.295423e+07</td>\n",
       "      <td>2.359197e+07</td>\n",
       "      <td>2.423494e+07</td>\n",
       "      <td>2.488279e+07</td>\n",
       "      <td>2.553322e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.908173e+10</td>\n",
       "      <td>2.563367e+10</td>\n",
       "      <td>3.039720e+10</td>\n",
       "      <td>2.845950e+10</td>\n",
       "      <td>3.090675e+10</td>\n",
       "      <td>3.107886e+10</td>\n",
       "      <td>3.207477e+10</td>\n",
       "      <td>3.595450e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Zambia</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.049586e+06</td>\n",
       "      <td>3.142848e+06</td>\n",
       "      <td>3.240664e+06</td>\n",
       "      <td>3.342894e+06</td>\n",
       "      <td>3.449266e+06</td>\n",
       "      <td>3.559687e+06</td>\n",
       "      <td>3.674088e+06</td>\n",
       "      <td>3.792864e+06</td>\n",
       "      <td>3.916928e+06</td>\n",
       "      <td>4.047479e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>1.238151e+07</td>\n",
       "      <td>1.273868e+07</td>\n",
       "      <td>1.311458e+07</td>\n",
       "      <td>1.350785e+07</td>\n",
       "      <td>1.391744e+07</td>\n",
       "      <td>1.434353e+07</td>\n",
       "      <td>1.478658e+07</td>\n",
       "      <td>1.524609e+07</td>\n",
       "      <td>1.572134e+07</td>\n",
       "      <td>1.621177e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>6.987397e+08</td>\n",
       "      <td>6.823597e+08</td>\n",
       "      <td>6.792797e+08</td>\n",
       "      <td>7.043397e+08</td>\n",
       "      <td>8.226397e+08</td>\n",
       "      <td>1.061200e+09</td>\n",
       "      <td>1.239000e+09</td>\n",
       "      <td>1.340639e+09</td>\n",
       "      <td>1.573739e+09</td>\n",
       "      <td>1.926399e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>1.275686e+10</td>\n",
       "      <td>1.405696e+10</td>\n",
       "      <td>1.791086e+10</td>\n",
       "      <td>1.532834e+10</td>\n",
       "      <td>2.026555e+10</td>\n",
       "      <td>2.345952e+10</td>\n",
       "      <td>2.550306e+10</td>\n",
       "      <td>2.804552e+10</td>\n",
       "      <td>2.713464e+10</td>\n",
       "      <td>2.120156e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Zimbabwe</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.752390e+06</td>\n",
       "      <td>3.876638e+06</td>\n",
       "      <td>4.006262e+06</td>\n",
       "      <td>4.140804e+06</td>\n",
       "      <td>4.279561e+06</td>\n",
       "      <td>4.422132e+06</td>\n",
       "      <td>4.568320e+06</td>\n",
       "      <td>4.718612e+06</td>\n",
       "      <td>4.874113e+06</td>\n",
       "      <td>5.036321e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>1.312794e+07</td>\n",
       "      <td>1.329780e+07</td>\n",
       "      <td>1.349546e+07</td>\n",
       "      <td>1.372100e+07</td>\n",
       "      <td>1.397390e+07</td>\n",
       "      <td>1.425559e+07</td>\n",
       "      <td>1.456548e+07</td>\n",
       "      <td>1.489809e+07</td>\n",
       "      <td>1.524586e+07</td>\n",
       "      <td>1.560275e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.052990e+09</td>\n",
       "      <td>1.096647e+09</td>\n",
       "      <td>1.117602e+09</td>\n",
       "      <td>1.159512e+09</td>\n",
       "      <td>1.217138e+09</td>\n",
       "      <td>1.311436e+09</td>\n",
       "      <td>1.281750e+09</td>\n",
       "      <td>1.397002e+09</td>\n",
       "      <td>1.479600e+09</td>\n",
       "      <td>1.747999e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>5.443896e+09</td>\n",
       "      <td>5.291950e+09</td>\n",
       "      <td>4.415703e+09</td>\n",
       "      <td>8.157077e+09</td>\n",
       "      <td>9.422161e+09</td>\n",
       "      <td>1.095623e+10</td>\n",
       "      <td>1.239272e+10</td>\n",
       "      <td>1.349023e+10</td>\n",
       "      <td>1.419691e+10</td>\n",
       "      <td>1.389294e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "year                                      1960          1961          1962  \\\n",
       "country                                                                      \n",
       "Afghanistan           Population  8.994793e+06  9.164945e+06  9.343772e+06   \n",
       "                      GDP         5.377778e+08  5.488889e+08  5.466667e+08   \n",
       "Albania               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Algeria               Population  1.112489e+07  1.140486e+07  1.169015e+07   \n",
       "                      GDP         2.723638e+09  2.434767e+09  2.001461e+09   \n",
       "Andorra               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Angola                Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Antigua and Barbuda   Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Arab World            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Argentina             Population           NaN           NaN  2.128768e+07   \n",
       "                      GDP                  NaN           NaN  2.445060e+10   \n",
       "Armenia               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Aruba                 Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Australia             Population  1.027648e+07  1.048300e+07  1.074200e+07   \n",
       "                      GDP         1.856759e+10  1.963938e+10  1.988353e+10   \n",
       "Austria               Population  7.047539e+06  7.086299e+06  7.129864e+06   \n",
       "                      GDP         6.592694e+09  7.311750e+09  7.756110e+09   \n",
       "Azerbaijan            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Bahamas, The          Population  1.095260e+05  1.151080e+05  1.210830e+05   \n",
       "                      GDP         1.698023e+08  1.900962e+08  2.122528e+08   \n",
       "Bahrain               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "...                                        ...           ...           ...   \n",
       "United Arab Emirates  Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "United Kingdom        Population  5.240000e+07  5.280000e+07  5.325000e+07   \n",
       "                      GDP         7.232805e+10  7.669436e+10  8.060194e+10   \n",
       "United States         Population  1.806710e+08  1.836910e+08  1.865380e+08   \n",
       "                      GDP         5.433000e+11  5.633000e+11  6.051000e+11   \n",
       "Upper middle income   Population  1.154592e+09  1.159145e+09  1.176093e+09   \n",
       "                      GDP         1.854612e+11  1.690732e+11  1.777957e+11   \n",
       "Uruguay               Population  2.538651e+06  2.571691e+06  2.603887e+06   \n",
       "                      GDP         1.242289e+09  1.547389e+09  1.710004e+09   \n",
       "Uzbekistan            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Vanuatu               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Venezuela, RB         Population  8.146845e+06  8.461684e+06  8.790590e+06   \n",
       "                      GDP         8.607600e+09  8.923367e+09  9.873398e+09   \n",
       "Vietnam               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Virgin Islands (U.S.) Population  3.200000e+04  3.410000e+04  3.630000e+04   \n",
       "                      GDP         2.420000e+07  2.570000e+07  3.690000e+07   \n",
       "West Bank and Gaza    Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "World                 Population  3.035056e+09  3.076121e+09  3.129064e+09   \n",
       "                      GDP         1.364643e+12  1.420440e+12  1.524573e+12   \n",
       "Yemen, Rep.           Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Zambia                Population  3.049586e+06  3.142848e+06  3.240664e+06   \n",
       "                      GDP         6.987397e+08  6.823597e+08  6.792797e+08   \n",
       "Zimbabwe              Population  3.752390e+06  3.876638e+06  4.006262e+06   \n",
       "                      GDP         1.052990e+09  1.096647e+09  1.117602e+09   \n",
       "\n",
       "year                                      1963          1964          1965  \\\n",
       "country                                                                      \n",
       "Afghanistan           Population  9.531555e+06  9.728645e+06  9.935358e+06   \n",
       "                      GDP         7.511112e+08  8.000000e+08  1.006667e+09   \n",
       "Albania               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Algeria               Population  1.198513e+07  1.229597e+07  1.262695e+07   \n",
       "                      GDP         2.703004e+09  2.909340e+09  3.136284e+09   \n",
       "Andorra               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Angola                Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Antigua and Barbuda   Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Arab World            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Argentina             Population  2.162184e+07  2.195393e+07  2.228339e+07   \n",
       "                      GDP         1.827212e+10  2.560525e+10  2.834471e+10   \n",
       "Armenia               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Aruba                 Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Australia             Population  1.095000e+07  1.116700e+07  1.138800e+07   \n",
       "                      GDP         2.149737e+10  2.375406e+10  2.592564e+10   \n",
       "Austria               Population  7.175811e+06  7.223801e+06  7.270889e+06   \n",
       "                      GDP         8.374175e+09  9.169984e+09  9.994071e+09   \n",
       "Azerbaijan            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Bahamas, The          Population  1.273310e+05  1.336970e+05  1.400490e+05   \n",
       "                      GDP         2.377428e+08  2.666641e+08  3.003922e+08   \n",
       "Bahrain               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "...                                        ...           ...           ...   \n",
       "United Arab Emirates  Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "United Kingdom        Population  5.365000e+07  5.400000e+07  5.434805e+07   \n",
       "                      GDP         8.544377e+10  9.338760e+10  1.005958e+11   \n",
       "United States         Population  1.892420e+08  1.918890e+08  1.943030e+08   \n",
       "                      GDP         6.386000e+11  6.858000e+11  7.437000e+11   \n",
       "Upper middle income   Population  1.204372e+09  1.232266e+09  1.261069e+09   \n",
       "                      GDP         1.955819e+11  2.144250e+11  2.397244e+11   \n",
       "Uruguay               Population  2.635128e+06  2.665387e+06  2.694535e+06   \n",
       "                      GDP         1.539682e+09  1.975702e+09  1.890769e+09   \n",
       "Uzbekistan            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Vanuatu               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Venezuela, RB         Population  9.130346e+06  9.476255e+06  9.824694e+06   \n",
       "                      GDP         1.066338e+10  9.113581e+09  9.602945e+09   \n",
       "Vietnam               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Virgin Islands (U.S.) Population  3.870000e+04  4.130000e+04  4.400000e+04   \n",
       "                      GDP         4.140000e+07  5.380000e+07  6.650000e+07   \n",
       "West Bank and Gaza    Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "World                 Population  3.193947e+09  3.259355e+09  3.326054e+09   \n",
       "                      GDP         1.638187e+12  1.799675e+12  1.959900e+12   \n",
       "Yemen, Rep.           Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Zambia                Population  3.342894e+06  3.449266e+06  3.559687e+06   \n",
       "                      GDP         7.043397e+08  8.226397e+08  1.061200e+09   \n",
       "Zimbabwe              Population  4.140804e+06  4.279561e+06  4.422132e+06   \n",
       "                      GDP         1.159512e+09  1.217138e+09  1.311436e+09   \n",
       "\n",
       "year                                      1966          1967          1968  \\\n",
       "country                                                                      \n",
       "Afghanistan           Population  1.014884e+07  1.036860e+07  1.059979e+07   \n",
       "                      GDP         1.400000e+09  1.673333e+09  1.373333e+09   \n",
       "Albania               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Algeria               Population  1.298027e+07  1.335420e+07  1.374438e+07   \n",
       "                      GDP         3.039859e+09  3.370870e+09  3.852147e+09   \n",
       "Andorra               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Angola                Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Antigua and Barbuda   Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Arab World            Population           NaN           NaN  1.155571e+08   \n",
       "                      GDP                  NaN           NaN  2.552596e+10   \n",
       "Argentina             Population  2.260875e+07  2.293220e+07  2.326127e+07   \n",
       "                      GDP         2.863047e+10  2.425667e+10  2.643686e+10   \n",
       "Armenia               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Aruba                 Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Australia             Population  1.165100e+07  1.179900e+07  1.200900e+07   \n",
       "                      GDP         2.725053e+10  3.037854e+10  3.264195e+10   \n",
       "Austria               Population  7.322066e+06  7.376998e+06  7.415403e+06   \n",
       "                      GDP         1.088768e+10  1.157943e+10  1.244063e+10   \n",
       "Azerbaijan            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Bahamas, The          Population  1.463640e+05  1.526070e+05  1.586290e+05   \n",
       "                      GDP         3.400000e+08  3.901961e+08  4.449020e+08   \n",
       "Bahrain               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "...                                        ...           ...           ...   \n",
       "United Arab Emirates  Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "United Kingdom        Population  5.464850e+07  5.494360e+07  5.521170e+07   \n",
       "                      GDP         1.070907e+11  1.111854e+11  1.047027e+11   \n",
       "United States         Population  1.965600e+08  1.987120e+08  2.007060e+08   \n",
       "                      GDP         8.150000e+11  8.617000e+11  9.425000e+11   \n",
       "Upper middle income   Population  1.292755e+09  1.323615e+09  1.355381e+09   \n",
       "                      GDP         2.666625e+11  2.766866e+11  2.898954e+11   \n",
       "Uruguay               Population  2.722874e+06  2.750093e+06  2.774771e+06   \n",
       "                      GDP         1.809184e+09  1.597721e+09  1.593675e+09   \n",
       "Uzbekistan            Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Vanuatu               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Venezuela, RB         Population  1.017514e+07  1.052805e+07  1.088200e+07   \n",
       "                      GDP         1.009657e+10  1.047278e+10  1.147091e+10   \n",
       "Vietnam               Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Virgin Islands (U.S.) Population  4.730000e+04  5.080000e+04  5.460000e+04   \n",
       "                      GDP         8.410000e+07  1.154000e+08  1.738000e+08   \n",
       "West Bank and Gaza    Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "World                 Population  3.395866e+09  3.465297e+09  3.535512e+09   \n",
       "                      GDP         2.125397e+12  2.262923e+12  2.440549e+12   \n",
       "Yemen, Rep.           Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "Zambia                Population  3.674088e+06  3.792864e+06  3.916928e+06   \n",
       "                      GDP         1.239000e+09  1.340639e+09  1.573739e+09   \n",
       "Zimbabwe              Population  4.568320e+06  4.718612e+06  4.874113e+06   \n",
       "                      GDP         1.281750e+09  1.397002e+09  1.479600e+09   \n",
       "\n",
       "year                                      1969      ...               2006  \\\n",
       "country                                             ...                      \n",
       "Afghanistan           Population  1.084951e+07      ...       2.518362e+07   \n",
       "                      GDP         1.408889e+09      ...       7.057598e+09   \n",
       "Albania               Population           NaN      ...       2.992547e+06   \n",
       "                      GDP                  NaN      ...       8.992642e+09   \n",
       "Algeria               Population  1.414444e+07      ...       3.374933e+07   \n",
       "                      GDP         4.257253e+09      ...       1.170273e+11   \n",
       "Andorra               Population           NaN      ...       8.337300e+04   \n",
       "                      GDP                  NaN      ...       3.536452e+09   \n",
       "Angola                Population           NaN      ...       1.854147e+07   \n",
       "                      GDP                  NaN      ...       4.178948e+10   \n",
       "Antigua and Barbuda   Population           NaN      ...       8.346700e+04   \n",
       "                      GDP                  NaN      ...       1.135144e+09   \n",
       "Arab World            Population  1.188239e+08      ...       3.209067e+08   \n",
       "                      GDP         2.817577e+10      ...       1.404190e+12   \n",
       "Argentina             Population  2.360599e+07      ...       3.955875e+07   \n",
       "                      GDP         3.125628e+10      ...       2.626665e+11   \n",
       "Armenia               Population           NaN      ...       3.002161e+06   \n",
       "                      GDP                  NaN      ...       6.384452e+09   \n",
       "Aruba                 Population           NaN      ...       1.008300e+05   \n",
       "                      GDP                  NaN      ...       2.421475e+09   \n",
       "Australia             Population  1.226300e+07      ...       2.069790e+07   \n",
       "                      GDP         3.660656e+10      ...       7.468808e+11   \n",
       "Austria               Population  7.441055e+06      ...       8.268641e+06   \n",
       "                      GDP         1.358280e+10      ...       3.343094e+11   \n",
       "Azerbaijan            Population           NaN      ...       8.484550e+06   \n",
       "                      GDP                  NaN      ...       2.098302e+10   \n",
       "Bahamas, The          Population  1.642500e+05      ...       3.358010e+05   \n",
       "                      GDP         5.281373e+08      ...       7.965588e+09   \n",
       "Bahrain               Population           NaN      ...       9.408080e+05   \n",
       "                      GDP                  NaN      ...       1.850505e+10   \n",
       "...                                        ...      ...                ...   \n",
       "United Arab Emirates  Population           NaN      ...       5.171255e+06   \n",
       "                      GDP                  NaN      ...       2.221059e+11   \n",
       "United Kingdom        Population  5.544175e+07      ...       6.084682e+07   \n",
       "                      GDP         1.126769e+11      ...       2.588077e+12   \n",
       "United States         Population  2.026770e+08      ...       2.983799e+08   \n",
       "                      GDP         1.019900e+12      ...       1.385589e+13   \n",
       "Upper middle income   Population  1.388827e+09      ...       2.380136e+09   \n",
       "                      GDP         3.221882e+11      ...       8.620784e+12   \n",
       "Uruguay               Population  2.795044e+06      ...       3.331041e+06   \n",
       "                      GDP         2.004435e+09      ...       1.957946e+10   \n",
       "Uzbekistan            Population           NaN      ...       2.648825e+07   \n",
       "                      GDP                  NaN      ...       1.703090e+10   \n",
       "Vanuatu               Population           NaN      ...       2.146350e+05   \n",
       "                      GDP                  NaN      ...       4.393768e+08   \n",
       "Venezuela, RB         Population  1.123549e+07      ...       2.722123e+07   \n",
       "                      GDP         1.192757e+10      ...       1.834775e+11   \n",
       "Vietnam               Population           NaN      ...       8.331120e+07   \n",
       "                      GDP                  NaN      ...       6.637166e+10   \n",
       "Virgin Islands (U.S.) Population  5.860000e+04      ...                NaN   \n",
       "                      GDP         2.113000e+08      ...                NaN   \n",
       "West Bank and Gaza    Population           NaN      ...       3.406334e+06   \n",
       "                      GDP                  NaN      ...       4.910100e+09   \n",
       "World                 Population  3.609910e+09      ...       6.594722e+09   \n",
       "                      GDP         2.686747e+12      ...       5.107451e+13   \n",
       "Yemen, Rep.           Population           NaN      ...       2.109397e+07   \n",
       "                      GDP                  NaN      ...       1.908173e+10   \n",
       "Zambia                Population  4.047479e+06      ...       1.238151e+07   \n",
       "                      GDP         1.926399e+09      ...       1.275686e+10   \n",
       "Zimbabwe              Population  5.036321e+06      ...       1.312794e+07   \n",
       "                      GDP         1.747999e+09      ...       5.443896e+09   \n",
       "\n",
       "year                                      2007          2008          2009  \\\n",
       "country                                                                      \n",
       "Afghanistan           Population  2.587754e+07  2.652874e+07  2.720729e+07   \n",
       "                      GDP         9.843842e+09  1.019053e+10  1.248694e+10   \n",
       "Albania               Population  2.970017e+06  2.947314e+06  2.927519e+06   \n",
       "                      GDP         1.070101e+10  1.288135e+10  1.204421e+10   \n",
       "Algeria               Population  3.426197e+07  3.481106e+07  3.540179e+07   \n",
       "                      GDP         1.349771e+11  1.710007e+11  1.372110e+11   \n",
       "Andorra               Population  8.487800e+04  8.561600e+04  8.547400e+04   \n",
       "                      GDP         4.010785e+09  4.001349e+09  3.649863e+09   \n",
       "Angola                Population  1.918391e+07  1.984225e+07  2.052010e+07   \n",
       "                      GDP         6.044892e+10  8.417803e+10  7.549238e+10   \n",
       "Antigua and Barbuda   Population  8.439700e+04  8.535000e+04  8.630000e+04   \n",
       "                      GDP         1.289254e+09  1.347350e+09  1.206410e+09   \n",
       "Arab World            Population  3.287666e+08  3.368865e+08  3.450542e+08   \n",
       "                      GDP         1.641666e+12  2.081343e+12  1.798878e+12   \n",
       "Argentina             Population  3.996990e+07  4.038186e+07  4.079864e+07   \n",
       "                      GDP         3.293175e+11  4.037820e+11  3.766279e+11   \n",
       "Armenia               Population  2.988117e+06  2.975029e+06  2.966108e+06   \n",
       "                      GDP         9.206302e+09  1.166204e+10  8.647937e+09   \n",
       "Aruba                 Population  1.012180e+05  1.013420e+05  1.014160e+05   \n",
       "                      GDP         2.623726e+09  2.791961e+09  2.498933e+09   \n",
       "Australia             Population  2.082760e+07  2.124920e+07  2.169170e+07   \n",
       "                      GDP         8.530533e+11  1.054558e+12  9.265638e+11   \n",
       "Austria               Population  8.295487e+06  8.321496e+06  8.343323e+06   \n",
       "                      GDP         3.864590e+11  4.276115e+11  3.975943e+11   \n",
       "Azerbaijan            Population  8.581300e+06  8.763400e+06  8.947243e+06   \n",
       "                      GDP         3.305034e+10  4.885248e+10  4.429149e+10   \n",
       "Bahamas, The          Population  3.422590e+05  3.485870e+05  3.547800e+05   \n",
       "                      GDP         8.318996e+09  8.246650e+09  7.820420e+09   \n",
       "Bahrain               Population  1.026568e+06  1.115777e+06  1.196774e+06   \n",
       "                      GDP         2.173000e+10  2.571088e+10  2.293822e+10   \n",
       "...                                        ...           ...           ...   \n",
       "United Arab Emirates  Population  6.010100e+06  6.900142e+06  7.705423e+06   \n",
       "                      GDP         2.579161e+11  3.154746e+11  2.535474e+11   \n",
       "United Kingdom        Population  6.132246e+07  6.180700e+07  6.227627e+07   \n",
       "                      GDP         2.969734e+12  2.793377e+12  2.314577e+12   \n",
       "United States         Population  3.012312e+08  3.040940e+08  3.067715e+08   \n",
       "                      GDP         1.447764e+13  1.471858e+13  1.441874e+13   \n",
       "Upper middle income   Population  2.397567e+09  2.415306e+09  2.433652e+09   \n",
       "                      GDP         1.073130e+13  1.312644e+13  1.263584e+13   \n",
       "Uruguay               Population  3.339750e+06  3.350832e+06  3.362761e+06   \n",
       "                      GDP         2.341057e+10  3.036621e+10  3.166091e+10   \n",
       "Uzbekistan            Population  2.686800e+07  2.730280e+07  2.776740e+07   \n",
       "                      GDP         2.231139e+10  2.793403e+10  3.281683e+10   \n",
       "Vanuatu               Population  2.199560e+05  2.253350e+05  2.307820e+05   \n",
       "                      GDP         5.264283e+08  6.079586e+08  6.100666e+08   \n",
       "Venezuela, RB         Population  2.767066e+07  2.811672e+07  2.855861e+07   \n",
       "                      GDP         2.303642e+11  3.156002e+11  3.294190e+11   \n",
       "Vietnam               Population  8.421850e+07  8.511870e+07  8.602500e+07   \n",
       "                      GDP         7.741443e+10  9.913030e+10  1.060146e+11   \n",
       "Virgin Islands (U.S.) Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "West Bank and Gaza    Population  3.494496e+06  3.596688e+06  3.702218e+06   \n",
       "                      GDP         5.505800e+09  6.673500e+09  7.268200e+09   \n",
       "World                 Population  6.675833e+09  6.758303e+09  6.840956e+09   \n",
       "                      GDP         5.758343e+13  6.312856e+13  5.983553e+13   \n",
       "Yemen, Rep.           Population  2.170110e+07  2.232270e+07  2.295423e+07   \n",
       "                      GDP         2.563367e+10  3.039720e+10  2.845950e+10   \n",
       "Zambia                Population  1.273868e+07  1.311458e+07  1.350785e+07   \n",
       "                      GDP         1.405696e+10  1.791086e+10  1.532834e+10   \n",
       "Zimbabwe              Population  1.329780e+07  1.349546e+07  1.372100e+07   \n",
       "                      GDP         5.291950e+09  4.415703e+09  8.157077e+09   \n",
       "\n",
       "year                                      2010          2011          2012  \\\n",
       "country                                                                      \n",
       "Afghanistan           Population  2.796221e+07  2.880917e+07  2.972680e+07   \n",
       "                      GDP         1.593680e+10  1.793024e+10  2.053654e+10   \n",
       "Albania               Population  2.913021e+06  2.904780e+06  2.900247e+06   \n",
       "                      GDP         1.192695e+10  1.289087e+10  1.231978e+10   \n",
       "Algeria               Population  3.603616e+07  3.671713e+07  3.743943e+07   \n",
       "                      GDP         1.612073e+11  2.000131e+11  2.090474e+11   \n",
       "Andorra               Population  8.441900e+04  8.232600e+04  7.931600e+04   \n",
       "                      GDP         3.346317e+09  3.427236e+09  3.146178e+09   \n",
       "Angola                Population  2.121995e+07  2.194230e+07  2.268563e+07   \n",
       "                      GDP         8.247091e+10  1.041159e+11  1.153984e+11   \n",
       "Antigua and Barbuda   Population  8.723300e+04  8.815200e+04  8.906900e+04   \n",
       "                      GDP         1.135539e+09  1.129918e+09  1.204713e+09   \n",
       "Arab World            Population  3.531122e+08  3.610318e+08  3.688026e+08   \n",
       "                      GDP         2.103825e+12  2.497945e+12  2.773270e+12   \n",
       "Argentina             Population  4.122288e+07  4.165562e+07  4.209522e+07   \n",
       "                      GDP         4.616402e+11  5.578902e+11  6.043785e+11   \n",
       "Armenia               Population  2.963496e+06  2.967984e+06  2.978339e+06   \n",
       "                      GDP         9.260285e+09  1.014211e+10  1.061932e+10   \n",
       "Aruba                 Population  1.015970e+05  1.019360e+05           NaN   \n",
       "                      GDP         2.467704e+09  2.584464e+09           NaN   \n",
       "Australia             Population  2.203175e+07  2.234002e+07  2.272825e+07   \n",
       "                      GDP         1.142251e+12  1.389919e+12  1.537478e+12   \n",
       "Austria               Population  8.363404e+06  8.391643e+06  8.429991e+06   \n",
       "                      GDP         3.902351e+11  4.290107e+11  4.073730e+11   \n",
       "Azerbaijan            Population  9.054332e+06  9.173082e+06  9.295784e+06   \n",
       "                      GDP         5.290270e+10  6.595163e+10  6.873091e+10   \n",
       "Bahamas, The          Population  3.608300e+05  3.667110e+05  3.723880e+05   \n",
       "                      GDP         7.909580e+09  7.889750e+09  8.234470e+09   \n",
       "Bahrain               Population  1.261319e+06  1.306014e+06  1.333577e+06   \n",
       "                      GDP         2.571327e+10  2.904407e+10  3.075646e+10   \n",
       "...                                        ...           ...           ...   \n",
       "United Arab Emirates  Population  8.329453e+06  8.734722e+06  8.952542e+06   \n",
       "                      GDP         2.860493e+11  3.485261e+11  3.734295e+11   \n",
       "United Kingdom        Population  6.276636e+07  6.325892e+07  6.370030e+07   \n",
       "                      GDP         2.403504e+12  2.594905e+12  2.630473e+12   \n",
       "United States         Population  3.093469e+08  3.117189e+08  3.141026e+08   \n",
       "                      GDP         1.496437e+13  1.551793e+13  1.615526e+13   \n",
       "Upper middle income   Population  2.452055e+09  2.470971e+09  2.490586e+09   \n",
       "                      GDP         1.530029e+13  1.829801e+13  1.955543e+13   \n",
       "Uruguay               Population  3.374414e+06  3.385610e+06  3.396753e+06   \n",
       "                      GDP         4.028468e+10  4.796244e+10  5.126540e+10   \n",
       "Uzbekistan            Population  2.856240e+07  2.933940e+07  2.977450e+07   \n",
       "                      GDP         3.933277e+10  4.532432e+10  5.118344e+10   \n",
       "Vanuatu               Population  2.362990e+05  2.418760e+05  2.474980e+05   \n",
       "                      GDP         7.008043e+08  7.921497e+08  7.817029e+08   \n",
       "Venezuela, RB         Population  2.899574e+07  2.942763e+07  2.985424e+07   \n",
       "                      GDP         3.938015e+11  3.164822e+11  3.812862e+11   \n",
       "Vietnam               Population  8.693250e+07  8.786030e+07  8.880920e+07   \n",
       "                      GDP         1.159317e+11  1.355395e+11  1.558200e+11   \n",
       "Virgin Islands (U.S.) Population           NaN           NaN           NaN   \n",
       "                      GDP                  NaN           NaN           NaN   \n",
       "West Bank and Gaza    Population  3.811102e+06  3.927051e+06  4.046901e+06   \n",
       "                      GDP         8.913100e+09  1.045985e+10  1.127940e+10   \n",
       "World                 Population  6.923684e+09  7.006908e+09  7.089452e+09   \n",
       "                      GDP         6.564782e+13  7.284314e+13  7.442836e+13   \n",
       "Yemen, Rep.           Population  2.359197e+07  2.423494e+07  2.488279e+07   \n",
       "                      GDP         3.090675e+10  3.107886e+10  3.207477e+10   \n",
       "Zambia                Population  1.391744e+07  1.434353e+07  1.478658e+07   \n",
       "                      GDP         2.026555e+10  2.345952e+10  2.550306e+10   \n",
       "Zimbabwe              Population  1.397390e+07  1.425559e+07  1.456548e+07   \n",
       "                      GDP         9.422161e+09  1.095623e+10  1.239272e+10   \n",
       "\n",
       "year                                      2013          2014          2015  \n",
       "country                                                                     \n",
       "Afghanistan           Population  3.068250e+07  3.162751e+07  3.252656e+07  \n",
       "                      GDP         2.004633e+10  2.005019e+10  1.919944e+10  \n",
       "Albania               Population  2.896652e+06  2.893654e+06  2.889167e+06  \n",
       "                      GDP         1.278103e+10  1.327796e+10  1.145560e+10  \n",
       "Algeria               Population  3.818614e+07  3.893433e+07  3.966652e+07  \n",
       "                      GDP         2.097035e+11  2.135185e+11  1.668386e+11  \n",
       "Andorra               Population  7.590200e+04           NaN           NaN  \n",
       "                      GDP         3.249101e+09           NaN           NaN  \n",
       "Angola                Population  2.344820e+07  2.422752e+07  2.502197e+07  \n",
       "                      GDP         1.249121e+11  1.267751e+11  1.026431e+11  \n",
       "Antigua and Barbuda   Population  8.998500e+04  9.090000e+04  9.181800e+04  \n",
       "                      GDP         1.200588e+09  1.220976e+09  1.297285e+09  \n",
       "Arab World            Population  3.765043e+08  3.842226e+08  3.920223e+08  \n",
       "                      GDP         2.846994e+12  2.873600e+12  2.530102e+12  \n",
       "Argentina             Population  4.253830e+07  4.298003e+07           NaN  \n",
       "                      GDP         6.239320e+11  5.480549e+11           NaN  \n",
       "Armenia               Population  2.992192e+06  3.006154e+06  3.017712e+06  \n",
       "                      GDP         1.112147e+10  1.164444e+10  1.056140e+10  \n",
       "Aruba                 Population           NaN           NaN           NaN  \n",
       "                      GDP                  NaN           NaN           NaN  \n",
       "Australia             Population  2.311735e+07  2.346409e+07  2.378117e+07  \n",
       "                      GDP         1.563951e+12  1.454675e+12  1.339539e+12  \n",
       "Austria               Population  8.479375e+06  8.541575e+06  8.611088e+06  \n",
       "                      GDP         4.286986e+11  4.368875e+11  3.740559e+11  \n",
       "Azerbaijan            Population  9.416801e+06  9.535079e+06  9.651349e+06  \n",
       "                      GDP         7.356048e+10  7.519801e+10  5.304714e+10  \n",
       "Bahamas, The          Population  3.778410e+05  3.830540e+05  3.880190e+05  \n",
       "                      GDP         8.431750e+09  8.510500e+09  8.884441e+09  \n",
       "Bahrain               Population  1.349427e+06  1.361930e+06  1.377237e+06  \n",
       "                      GDP         3.289761e+10  3.385106e+10  3.222149e+10  \n",
       "...                                        ...           ...           ...  \n",
       "United Arab Emirates  Population  9.039978e+06  9.086139e+06  9.156963e+06  \n",
       "                      GDP         3.871921e+11  3.994513e+11  3.702927e+11  \n",
       "United Kingdom        Population  6.412823e+07  6.461316e+07  6.513823e+07  \n",
       "                      GDP         2.712296e+12  2.990201e+12  2.848755e+12  \n",
       "United States         Population  3.164274e+08  3.189074e+08  3.214188e+08  \n",
       "                      GDP         1.666316e+13  1.734807e+13  1.794700e+13  \n",
       "Upper middle income   Population  2.510573e+09  2.530632e+09  2.550326e+09  \n",
       "                      GDP         2.080729e+13  2.133305e+13  1.973288e+13  \n",
       "Uruguay               Population  3.407969e+06  3.419516e+06  3.431555e+06  \n",
       "                      GDP         5.753123e+10  5.723577e+10  5.344270e+10  \n",
       "Uzbekistan            Population  3.024320e+07  3.075770e+07  3.129950e+07  \n",
       "                      GDP         5.679566e+10  6.313285e+10  6.673280e+10  \n",
       "Vanuatu               Population  2.531650e+05  2.588830e+05           NaN  \n",
       "                      GDP         8.017876e+08  8.149546e+08           NaN  \n",
       "Venezuela, RB         Population  3.027604e+07           NaN           NaN  \n",
       "                      GDP         3.713366e+11           NaN           NaN  \n",
       "Vietnam               Population  8.975950e+07  9.072890e+07  9.170380e+07  \n",
       "                      GDP         1.712220e+11  1.862047e+11  1.935994e+11  \n",
       "Virgin Islands (U.S.) Population           NaN           NaN           NaN  \n",
       "                      GDP                  NaN           NaN           NaN  \n",
       "West Bank and Gaza    Population  4.169506e+06  4.294682e+06  4.422143e+06  \n",
       "                      GDP         1.247600e+10  1.271560e+10  1.267740e+10  \n",
       "World                 Population  7.176092e+09  7.260780e+09  7.346633e+09  \n",
       "                      GDP         7.643132e+13  7.810634e+13  7.343364e+13  \n",
       "Yemen, Rep.           Population  2.553322e+07           NaN           NaN  \n",
       "                      GDP         3.595450e+10           NaN           NaN  \n",
       "Zambia                Population  1.524609e+07  1.572134e+07  1.621177e+07  \n",
       "                      GDP         2.804552e+10  2.713464e+10  2.120156e+10  \n",
       "Zimbabwe              Population  1.489809e+07  1.524586e+07  1.560275e+07  \n",
       "                      GDP         1.349023e+10  1.419691e+10  1.389294e+10  \n",
       "\n",
       "[504 rows x 56 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.unstack(2)\n",
    "s.unstack(\"year\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Arab World</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Zimbabwe</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>2015</th>\n",
       "      <th>2014</th>\n",
       "      <th>2013</th>\n",
       "      <th>2012</th>\n",
       "      <th>2011</th>\n",
       "      <th>2010</th>\n",
       "      <th>2009</th>\n",
       "      <th>2008</th>\n",
       "      <th>2007</th>\n",
       "      <th>2006</th>\n",
       "      <th>...</th>\n",
       "      <th>1969</th>\n",
       "      <th>1968</th>\n",
       "      <th>1967</th>\n",
       "      <th>1966</th>\n",
       "      <th>1965</th>\n",
       "      <th>1964</th>\n",
       "      <th>1963</th>\n",
       "      <th>1962</th>\n",
       "      <th>1961</th>\n",
       "      <th>1960</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Population</th>\n",
       "      <td>3.920223e+08</td>\n",
       "      <td>3.842226e+08</td>\n",
       "      <td>3.765043e+08</td>\n",
       "      <td>3.688026e+08</td>\n",
       "      <td>3.610318e+08</td>\n",
       "      <td>3.531122e+08</td>\n",
       "      <td>3.450542e+08</td>\n",
       "      <td>3.368865e+08</td>\n",
       "      <td>3.287666e+08</td>\n",
       "      <td>3.209067e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>5.036321e+06</td>\n",
       "      <td>4.874113e+06</td>\n",
       "      <td>4.718612e+06</td>\n",
       "      <td>4.568320e+06</td>\n",
       "      <td>4.422132e+06</td>\n",
       "      <td>4.279561e+06</td>\n",
       "      <td>4.140804e+06</td>\n",
       "      <td>4.006262e+06</td>\n",
       "      <td>3.876638e+06</td>\n",
       "      <td>3.752390e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>2.530102e+12</td>\n",
       "      <td>2.873600e+12</td>\n",
       "      <td>2.846994e+12</td>\n",
       "      <td>2.773270e+12</td>\n",
       "      <td>2.497945e+12</td>\n",
       "      <td>2.103825e+12</td>\n",
       "      <td>1.798878e+12</td>\n",
       "      <td>2.081343e+12</td>\n",
       "      <td>1.641666e+12</td>\n",
       "      <td>1.404190e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>1.747999e+09</td>\n",
       "      <td>1.479600e+09</td>\n",
       "      <td>1.397002e+09</td>\n",
       "      <td>1.281750e+09</td>\n",
       "      <td>1.311436e+09</td>\n",
       "      <td>1.217138e+09</td>\n",
       "      <td>1.159512e+09</td>\n",
       "      <td>1.117602e+09</td>\n",
       "      <td>1.096647e+09</td>\n",
       "      <td>1.052990e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 11211 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "country       Arab World                                            \\\n",
       "year                2015          2014          2013          2012   \n",
       "Population  3.920223e+08  3.842226e+08  3.765043e+08  3.688026e+08   \n",
       "GDP         2.530102e+12  2.873600e+12  2.846994e+12  2.773270e+12   \n",
       "\n",
       "country                                                             \\\n",
       "year                2011          2010          2009          2008   \n",
       "Population  3.610318e+08  3.531122e+08  3.450542e+08  3.368865e+08   \n",
       "GDP         2.497945e+12  2.103825e+12  1.798878e+12  2.081343e+12   \n",
       "\n",
       "country                                     ...           Zimbabwe  \\\n",
       "year                2007          2006      ...               1969   \n",
       "Population  3.287666e+08  3.209067e+08      ...       5.036321e+06   \n",
       "GDP         1.641666e+12  1.404190e+12      ...       1.747999e+09   \n",
       "\n",
       "country                                                             \\\n",
       "year                1968          1967          1966          1965   \n",
       "Population  4.874113e+06  4.718612e+06  4.568320e+06  4.422132e+06   \n",
       "GDP         1.479600e+09  1.397002e+09  1.281750e+09  1.311436e+09   \n",
       "\n",
       "country                                                             \\\n",
       "year                1964          1963          1962          1961   \n",
       "Population  4.279561e+06  4.140804e+06  4.006262e+06  3.876638e+06   \n",
       "GDP         1.217138e+09  1.159512e+09  1.117602e+09  1.096647e+09   \n",
       "\n",
       "country                   \n",
       "year                1960  \n",
       "Population  3.752390e+06  \n",
       "GDP         1.052990e+09  \n",
       "\n",
       "[2 rows x 11211 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.unstack(level = [\"country\",\"year\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = s.unstack(level = [\"year\"], fill_value = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>2015</th>\n",
       "      <th>2014</th>\n",
       "      <th>2013</th>\n",
       "      <th>2012</th>\n",
       "      <th>2011</th>\n",
       "      <th>2010</th>\n",
       "      <th>2009</th>\n",
       "      <th>2008</th>\n",
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       "      <th>1967</th>\n",
       "      <th>1966</th>\n",
       "      <th>1965</th>\n",
       "      <th>1964</th>\n",
       "      <th>1963</th>\n",
       "      <th>1962</th>\n",
       "      <th>1961</th>\n",
       "      <th>1960</th>\n",
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       "    <tr>\n",
       "      <th>country</th>\n",
       "      <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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       "      <th></th>\n",
       "      <th></th>\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 rowspan=\"2\" valign=\"top\">Afghanistan</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.252656e+07</td>\n",
       "      <td>3.162751e+07</td>\n",
       "      <td>3.068250e+07</td>\n",
       "      <td>2.972680e+07</td>\n",
       "      <td>2.880917e+07</td>\n",
       "      <td>2.796221e+07</td>\n",
       "      <td>2.720729e+07</td>\n",
       "      <td>2.652874e+07</td>\n",
       "      <td>2.587754e+07</td>\n",
       "      <td>2.518362e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>1.084951e+07</td>\n",
       "      <td>1.059979e+07</td>\n",
       "      <td>1.036860e+07</td>\n",
       "      <td>1.014884e+07</td>\n",
       "      <td>9.935358e+06</td>\n",
       "      <td>9.728645e+06</td>\n",
       "      <td>9.531555e+06</td>\n",
       "      <td>9.343772e+06</td>\n",
       "      <td>9.164945e+06</td>\n",
       "      <td>8.994793e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.919944e+10</td>\n",
       "      <td>2.005019e+10</td>\n",
       "      <td>2.004633e+10</td>\n",
       "      <td>2.053654e+10</td>\n",
       "      <td>1.793024e+10</td>\n",
       "      <td>1.593680e+10</td>\n",
       "      <td>1.248694e+10</td>\n",
       "      <td>1.019053e+10</td>\n",
       "      <td>9.843842e+09</td>\n",
       "      <td>7.057598e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>1.408889e+09</td>\n",
       "      <td>1.373333e+09</td>\n",
       "      <td>1.673333e+09</td>\n",
       "      <td>1.400000e+09</td>\n",
       "      <td>1.006667e+09</td>\n",
       "      <td>8.000000e+08</td>\n",
       "      <td>7.511112e+08</td>\n",
       "      <td>5.466667e+08</td>\n",
       "      <td>5.488889e+08</td>\n",
       "      <td>5.377778e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Albania</th>\n",
       "      <th>Population</th>\n",
       "      <td>2.889167e+06</td>\n",
       "      <td>2.893654e+06</td>\n",
       "      <td>2.896652e+06</td>\n",
       "      <td>2.900247e+06</td>\n",
       "      <td>2.904780e+06</td>\n",
       "      <td>2.913021e+06</td>\n",
       "      <td>2.927519e+06</td>\n",
       "      <td>2.947314e+06</td>\n",
       "      <td>2.970017e+06</td>\n",
       "      <td>2.992547e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.145560e+10</td>\n",
       "      <td>1.327796e+10</td>\n",
       "      <td>1.278103e+10</td>\n",
       "      <td>1.231978e+10</td>\n",
       "      <td>1.289087e+10</td>\n",
       "      <td>1.192695e+10</td>\n",
       "      <td>1.204421e+10</td>\n",
       "      <td>1.288135e+10</td>\n",
       "      <td>1.070101e+10</td>\n",
       "      <td>8.992642e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.966652e+07</td>\n",
       "      <td>3.893433e+07</td>\n",
       "      <td>3.818614e+07</td>\n",
       "      <td>3.743943e+07</td>\n",
       "      <td>3.671713e+07</td>\n",
       "      <td>3.603616e+07</td>\n",
       "      <td>3.540179e+07</td>\n",
       "      <td>3.481106e+07</td>\n",
       "      <td>3.426197e+07</td>\n",
       "      <td>3.374933e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>1.414444e+07</td>\n",
       "      <td>1.374438e+07</td>\n",
       "      <td>1.335420e+07</td>\n",
       "      <td>1.298027e+07</td>\n",
       "      <td>1.262695e+07</td>\n",
       "      <td>1.229597e+07</td>\n",
       "      <td>1.198513e+07</td>\n",
       "      <td>1.169015e+07</td>\n",
       "      <td>1.140486e+07</td>\n",
       "      <td>1.112489e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "year                            2015          2014          2013  \\\n",
       "country                                                            \n",
       "Afghanistan Population  3.252656e+07  3.162751e+07  3.068250e+07   \n",
       "            GDP         1.919944e+10  2.005019e+10  2.004633e+10   \n",
       "Albania     Population  2.889167e+06  2.893654e+06  2.896652e+06   \n",
       "            GDP         1.145560e+10  1.327796e+10  1.278103e+10   \n",
       "Algeria     Population  3.966652e+07  3.893433e+07  3.818614e+07   \n",
       "\n",
       "year                            2012          2011          2010  \\\n",
       "country                                                            \n",
       "Afghanistan Population  2.972680e+07  2.880917e+07  2.796221e+07   \n",
       "            GDP         2.053654e+10  1.793024e+10  1.593680e+10   \n",
       "Albania     Population  2.900247e+06  2.904780e+06  2.913021e+06   \n",
       "            GDP         1.231978e+10  1.289087e+10  1.192695e+10   \n",
       "Algeria     Population  3.743943e+07  3.671713e+07  3.603616e+07   \n",
       "\n",
       "year                            2009          2008          2007  \\\n",
       "country                                                            \n",
       "Afghanistan Population  2.720729e+07  2.652874e+07  2.587754e+07   \n",
       "            GDP         1.248694e+10  1.019053e+10  9.843842e+09   \n",
       "Albania     Population  2.927519e+06  2.947314e+06  2.970017e+06   \n",
       "            GDP         1.204421e+10  1.288135e+10  1.070101e+10   \n",
       "Algeria     Population  3.540179e+07  3.481106e+07  3.426197e+07   \n",
       "\n",
       "year                            2006      ...               1969  \\\n",
       "country                                   ...                      \n",
       "Afghanistan Population  2.518362e+07      ...       1.084951e+07   \n",
       "            GDP         7.057598e+09      ...       1.408889e+09   \n",
       "Albania     Population  2.992547e+06      ...                NaN   \n",
       "            GDP         8.992642e+09      ...                NaN   \n",
       "Algeria     Population  3.374933e+07      ...       1.414444e+07   \n",
       "\n",
       "year                            1968          1967          1966  \\\n",
       "country                                                            \n",
       "Afghanistan Population  1.059979e+07  1.036860e+07  1.014884e+07   \n",
       "            GDP         1.373333e+09  1.673333e+09  1.400000e+09   \n",
       "Albania     Population           NaN           NaN           NaN   \n",
       "            GDP                  NaN           NaN           NaN   \n",
       "Algeria     Population  1.374438e+07  1.335420e+07  1.298027e+07   \n",
       "\n",
       "year                            1965          1964          1963  \\\n",
       "country                                                            \n",
       "Afghanistan Population  9.935358e+06  9.728645e+06  9.531555e+06   \n",
       "            GDP         1.006667e+09  8.000000e+08  7.511112e+08   \n",
       "Albania     Population           NaN           NaN           NaN   \n",
       "            GDP                  NaN           NaN           NaN   \n",
       "Algeria     Population  1.262695e+07  1.229597e+07  1.198513e+07   \n",
       "\n",
       "year                            1962          1961          1960  \n",
       "country                                                           \n",
       "Afghanistan Population  9.343772e+06  9.164945e+06  8.994793e+06  \n",
       "            GDP         5.466667e+08  5.488889e+08  5.377778e+08  \n",
       "Albania     Population           NaN           NaN           NaN  \n",
       "            GDP                  NaN           NaN           NaN  \n",
       "Algeria     Population  1.169015e+07  1.140486e+07  1.112489e+07  \n",
       "\n",
       "[5 rows x 56 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "sales = pd.read_csv(\"salesmen.csv\", parse_dates = [\"Date\"])\n",
    "sales[\"Salesman\"] = sales[\"Salesman\"].astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Salesman</th>\n",
       "      <th>Revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>Bob</td>\n",
       "      <td>7172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-02</td>\n",
       "      <td>Bob</td>\n",
       "      <td>6362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>Bob</td>\n",
       "      <td>5982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-04</td>\n",
       "      <td>Bob</td>\n",
       "      <td>7917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>Bob</td>\n",
       "      <td>7837</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date Salesman  Revenue\n",
       "0 2016-01-01      Bob     7172\n",
       "1 2016-01-02      Bob     6362\n",
       "2 2016-01-03      Bob     5982\n",
       "3 2016-01-04      Bob     7917\n",
       "4 2016-01-05      Bob     7837"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Salesman</th>\n",
       "      <th>Bob</th>\n",
       "      <th>Dave</th>\n",
       "      <th>Jeb</th>\n",
       "      <th>Oscar</th>\n",
       "      <th>Ronald</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\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>2016-01-01</th>\n",
       "      <td>7172</td>\n",
       "      <td>1864</td>\n",
       "      <td>4430</td>\n",
       "      <td>5250</td>\n",
       "      <td>2639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-02</th>\n",
       "      <td>6362</td>\n",
       "      <td>8278</td>\n",
       "      <td>8026</td>\n",
       "      <td>8661</td>\n",
       "      <td>4951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-03</th>\n",
       "      <td>5982</td>\n",
       "      <td>4226</td>\n",
       "      <td>5188</td>\n",
       "      <td>7075</td>\n",
       "      <td>2703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-04</th>\n",
       "      <td>7917</td>\n",
       "      <td>3868</td>\n",
       "      <td>3144</td>\n",
       "      <td>2524</td>\n",
       "      <td>4258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>7837</td>\n",
       "      <td>2287</td>\n",
       "      <td>938</td>\n",
       "      <td>2793</td>\n",
       "      <td>7771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>1744</td>\n",
       "      <td>7859</td>\n",
       "      <td>8702</td>\n",
       "      <td>7794</td>\n",
       "      <td>5930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>918</td>\n",
       "      <td>8597</td>\n",
       "      <td>4250</td>\n",
       "      <td>9728</td>\n",
       "      <td>1933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>9863</td>\n",
       "      <td>3092</td>\n",
       "      <td>9719</td>\n",
       "      <td>5263</td>\n",
       "      <td>5709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-09</th>\n",
       "      <td>8337</td>\n",
       "      <td>1794</td>\n",
       "      <td>5614</td>\n",
       "      <td>7144</td>\n",
       "      <td>4707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-10</th>\n",
       "      <td>7543</td>\n",
       "      <td>7105</td>\n",
       "      <td>301</td>\n",
       "      <td>7663</td>\n",
       "      <td>8267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>1053</td>\n",
       "      <td>6851</td>\n",
       "      <td>9489</td>\n",
       "      <td>8888</td>\n",
       "      <td>1340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-12</th>\n",
       "      <td>4362</td>\n",
       "      <td>7147</td>\n",
       "      <td>8719</td>\n",
       "      <td>3092</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-13</th>\n",
       "      <td>6812</td>\n",
       "      <td>6160</td>\n",
       "      <td>2349</td>\n",
       "      <td>6139</td>\n",
       "      <td>7540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-14</th>\n",
       "      <td>9047</td>\n",
       "      <td>7533</td>\n",
       "      <td>7690</td>\n",
       "      <td>5235</td>\n",
       "      <td>4214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-15</th>\n",
       "      <td>3594</td>\n",
       "      <td>9883</td>\n",
       "      <td>6917</td>\n",
       "      <td>5507</td>\n",
       "      <td>5346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-16</th>\n",
       "      <td>9800</td>\n",
       "      <td>3622</td>\n",
       "      <td>474</td>\n",
       "      <td>4947</td>\n",
       "      <td>9636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-17</th>\n",
       "      <td>7215</td>\n",
       "      <td>4565</td>\n",
       "      <td>8963</td>\n",
       "      <td>3325</td>\n",
       "      <td>6058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-18</th>\n",
       "      <td>7744</td>\n",
       "      <td>8246</td>\n",
       "      <td>2351</td>\n",
       "      <td>2611</td>\n",
       "      <td>3602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-19</th>\n",
       "      <td>9560</td>\n",
       "      <td>9229</td>\n",
       "      <td>5512</td>\n",
       "      <td>1905</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-20</th>\n",
       "      <td>9863</td>\n",
       "      <td>8358</td>\n",
       "      <td>9509</td>\n",
       "      <td>6005</td>\n",
       "      <td>9352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-21</th>\n",
       "      <td>547</td>\n",
       "      <td>4229</td>\n",
       "      <td>2453</td>\n",
       "      <td>2798</td>\n",
       "      <td>6781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-22</th>\n",
       "      <td>3505</td>\n",
       "      <td>4417</td>\n",
       "      <td>2875</td>\n",
       "      <td>879</td>\n",
       "      <td>5166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-23</th>\n",
       "      <td>6969</td>\n",
       "      <td>358</td>\n",
       "      <td>8853</td>\n",
       "      <td>4245</td>\n",
       "      <td>2479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-24</th>\n",
       "      <td>696</td>\n",
       "      <td>7817</td>\n",
       "      <td>6705</td>\n",
       "      <td>3798</td>\n",
       "      <td>4835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-25</th>\n",
       "      <td>4302</td>\n",
       "      <td>6354</td>\n",
       "      <td>2882</td>\n",
       "      <td>1143</td>\n",
       "      <td>9750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-26</th>\n",
       "      <td>9427</td>\n",
       "      <td>7544</td>\n",
       "      <td>1009</td>\n",
       "      <td>871</td>\n",
       "      <td>8738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-27</th>\n",
       "      <td>7990</td>\n",
       "      <td>2255</td>\n",
       "      <td>4020</td>\n",
       "      <td>2403</td>\n",
       "      <td>1768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-28</th>\n",
       "      <td>6271</td>\n",
       "      <td>3419</td>\n",
       "      <td>1735</td>\n",
       "      <td>3691</td>\n",
       "      <td>7264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-29</th>\n",
       "      <td>5804</td>\n",
       "      <td>1378</td>\n",
       "      <td>6477</td>\n",
       "      <td>418</td>\n",
       "      <td>8545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-30</th>\n",
       "      <td>3285</td>\n",
       "      <td>6456</td>\n",
       "      <td>2253</td>\n",
       "      <td>7776</td>\n",
       "      <td>658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-02</th>\n",
       "      <td>5570</td>\n",
       "      <td>9842</td>\n",
       "      <td>982</td>\n",
       "      <td>5589</td>\n",
       "      <td>5956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-03</th>\n",
       "      <td>7910</td>\n",
       "      <td>4284</td>\n",
       "      <td>9363</td>\n",
       "      <td>6009</td>\n",
       "      <td>2252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-04</th>\n",
       "      <td>2869</td>\n",
       "      <td>8389</td>\n",
       "      <td>5980</td>\n",
       "      <td>537</td>\n",
       "      <td>1484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-05</th>\n",
       "      <td>4013</td>\n",
       "      <td>3089</td>\n",
       "      <td>8999</td>\n",
       "      <td>3895</td>\n",
       "      <td>2867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-06</th>\n",
       "      <td>1695</td>\n",
       "      <td>9142</td>\n",
       "      <td>4896</td>\n",
       "      <td>3060</td>\n",
       "      <td>5734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-07</th>\n",
       "      <td>1010</td>\n",
       "      <td>3707</td>\n",
       "      <td>4634</td>\n",
       "      <td>295</td>\n",
       "      <td>5409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-08</th>\n",
       "      <td>1149</td>\n",
       "      <td>3073</td>\n",
       "      <td>5930</td>\n",
       "      <td>5038</td>\n",
       "      <td>9951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-09</th>\n",
       "      <td>4432</td>\n",
       "      <td>6820</td>\n",
       "      <td>8592</td>\n",
       "      <td>258</td>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-10</th>\n",
       "      <td>194</td>\n",
       "      <td>3938</td>\n",
       "      <td>3530</td>\n",
       "      <td>9392</td>\n",
       "      <td>8713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-11</th>\n",
       "      <td>7676</td>\n",
       "      <td>8805</td>\n",
       "      <td>1134</td>\n",
       "      <td>690</td>\n",
       "      <td>5843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-12</th>\n",
       "      <td>7290</td>\n",
       "      <td>3917</td>\n",
       "      <td>9004</td>\n",
       "      <td>5621</td>\n",
       "      <td>4524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-13</th>\n",
       "      <td>7253</td>\n",
       "      <td>9168</td>\n",
       "      <td>8031</td>\n",
       "      <td>3284</td>\n",
       "      <td>5193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-14</th>\n",
       "      <td>9777</td>\n",
       "      <td>2632</td>\n",
       "      <td>3162</td>\n",
       "      <td>2245</td>\n",
       "      <td>8161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-15</th>\n",
       "      <td>7933</td>\n",
       "      <td>2051</td>\n",
       "      <td>4408</td>\n",
       "      <td>3449</td>\n",
       "      <td>9557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-16</th>\n",
       "      <td>6742</td>\n",
       "      <td>1148</td>\n",
       "      <td>3020</td>\n",
       "      <td>1763</td>\n",
       "      <td>2318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-17</th>\n",
       "      <td>5641</td>\n",
       "      <td>8921</td>\n",
       "      <td>6126</td>\n",
       "      <td>1641</td>\n",
       "      <td>9042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-18</th>\n",
       "      <td>8445</td>\n",
       "      <td>9203</td>\n",
       "      <td>5843</td>\n",
       "      <td>1022</td>\n",
       "      <td>7979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-19</th>\n",
       "      <td>3065</td>\n",
       "      <td>4255</td>\n",
       "      <td>8136</td>\n",
       "      <td>3366</td>\n",
       "      <td>2734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-20</th>\n",
       "      <td>3864</td>\n",
       "      <td>7209</td>\n",
       "      <td>2082</td>\n",
       "      <td>364</td>\n",
       "      <td>5757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-21</th>\n",
       "      <td>4080</td>\n",
       "      <td>1335</td>\n",
       "      <td>5940</td>\n",
       "      <td>3579</td>\n",
       "      <td>359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-22</th>\n",
       "      <td>5294</td>\n",
       "      <td>6986</td>\n",
       "      <td>4389</td>\n",
       "      <td>6476</td>\n",
       "      <td>825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-23</th>\n",
       "      <td>5063</td>\n",
       "      <td>5507</td>\n",
       "      <td>9</td>\n",
       "      <td>6495</td>\n",
       "      <td>9210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-24</th>\n",
       "      <td>1731</td>\n",
       "      <td>5520</td>\n",
       "      <td>8230</td>\n",
       "      <td>9346</td>\n",
       "      <td>4114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-25</th>\n",
       "      <td>8325</td>\n",
       "      <td>4004</td>\n",
       "      <td>6569</td>\n",
       "      <td>8321</td>\n",
       "      <td>7490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-26</th>\n",
       "      <td>6664</td>\n",
       "      <td>3211</td>\n",
       "      <td>1572</td>\n",
       "      <td>6172</td>\n",
       "      <td>6170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-27</th>\n",
       "      <td>2045</td>\n",
       "      <td>2843</td>\n",
       "      <td>6666</td>\n",
       "      <td>835</td>\n",
       "      <td>2981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-28</th>\n",
       "      <td>100</td>\n",
       "      <td>8888</td>\n",
       "      <td>1243</td>\n",
       "      <td>3073</td>\n",
       "      <td>6129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-29</th>\n",
       "      <td>4115</td>\n",
       "      <td>9490</td>\n",
       "      <td>3498</td>\n",
       "      <td>6424</td>\n",
       "      <td>7662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-30</th>\n",
       "      <td>2577</td>\n",
       "      <td>3594</td>\n",
       "      <td>8858</td>\n",
       "      <td>7088</td>\n",
       "      <td>2570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>3845</td>\n",
       "      <td>6830</td>\n",
       "      <td>9717</td>\n",
       "      <td>8408</td>\n",
       "      <td>2619</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Salesman     Bob  Dave   Jeb  Oscar  Ronald\n",
       "Date                                       \n",
       "2016-01-01  7172  1864  4430   5250    2639\n",
       "2016-01-02  6362  8278  8026   8661    4951\n",
       "2016-01-03  5982  4226  5188   7075    2703\n",
       "2016-01-04  7917  3868  3144   2524    4258\n",
       "2016-01-05  7837  2287   938   2793    7771\n",
       "2016-01-06  1744  7859  8702   7794    5930\n",
       "2016-01-07   918  8597  4250   9728    1933\n",
       "2016-01-08  9863  3092  9719   5263    5709\n",
       "2016-01-09  8337  1794  5614   7144    4707\n",
       "2016-01-10  7543  7105   301   7663    8267\n",
       "2016-01-11  1053  6851  9489   8888    1340\n",
       "2016-01-12  4362  7147  8719   3092     279\n",
       "2016-01-13  6812  6160  2349   6139    7540\n",
       "2016-01-14  9047  7533  7690   5235    4214\n",
       "2016-01-15  3594  9883  6917   5507    5346\n",
       "2016-01-16  9800  3622   474   4947    9636\n",
       "2016-01-17  7215  4565  8963   3325    6058\n",
       "2016-01-18  7744  8246  2351   2611    3602\n",
       "2016-01-19  9560  9229  5512   1905     316\n",
       "2016-01-20  9863  8358  9509   6005    9352\n",
       "2016-01-21   547  4229  2453   2798    6781\n",
       "2016-01-22  3505  4417  2875    879    5166\n",
       "2016-01-23  6969   358  8853   4245    2479\n",
       "2016-01-24   696  7817  6705   3798    4835\n",
       "2016-01-25  4302  6354  2882   1143    9750\n",
       "2016-01-26  9427  7544  1009    871    8738\n",
       "2016-01-27  7990  2255  4020   2403    1768\n",
       "2016-01-28  6271  3419  1735   3691    7264\n",
       "2016-01-29  5804  1378  6477    418    8545\n",
       "2016-01-30  3285  6456  2253   7776     658\n",
       "...          ...   ...   ...    ...     ...\n",
       "2016-12-02  5570  9842   982   5589    5956\n",
       "2016-12-03  7910  4284  9363   6009    2252\n",
       "2016-12-04  2869  8389  5980    537    1484\n",
       "2016-12-05  4013  3089  8999   3895    2867\n",
       "2016-12-06  1695  9142  4896   3060    5734\n",
       "2016-12-07  1010  3707  4634    295    5409\n",
       "2016-12-08  1149  3073  5930   5038    9951\n",
       "2016-12-09  4432  6820  8592    258      96\n",
       "2016-12-10   194  3938  3530   9392    8713\n",
       "2016-12-11  7676  8805  1134    690    5843\n",
       "2016-12-12  7290  3917  9004   5621    4524\n",
       "2016-12-13  7253  9168  8031   3284    5193\n",
       "2016-12-14  9777  2632  3162   2245    8161\n",
       "2016-12-15  7933  2051  4408   3449    9557\n",
       "2016-12-16  6742  1148  3020   1763    2318\n",
       "2016-12-17  5641  8921  6126   1641    9042\n",
       "2016-12-18  8445  9203  5843   1022    7979\n",
       "2016-12-19  3065  4255  8136   3366    2734\n",
       "2016-12-20  3864  7209  2082    364    5757\n",
       "2016-12-21  4080  1335  5940   3579     359\n",
       "2016-12-22  5294  6986  4389   6476     825\n",
       "2016-12-23  5063  5507     9   6495    9210\n",
       "2016-12-24  1731  5520  8230   9346    4114\n",
       "2016-12-25  8325  4004  6569   8321    7490\n",
       "2016-12-26  6664  3211  1572   6172    6170\n",
       "2016-12-27  2045  2843  6666    835    2981\n",
       "2016-12-28   100  8888  1243   3073    6129\n",
       "2016-12-29  4115  9490  3498   6424    7662\n",
       "2016-12-30  2577  3594  8858   7088    2570\n",
       "2016-12-31  3845  6830  9717   8408    2619\n",
       "\n",
       "[366 rows x 5 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.pivot(index=\"Date\", columns=\"Salesman\", values=\"Revenue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>City</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Item</th>\n",
       "      <th>Spend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Wanda</td>\n",
       "      <td>Female</td>\n",
       "      <td>Stamford</td>\n",
       "      <td>Weekly</td>\n",
       "      <td>Burger</td>\n",
       "      <td>15.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Eric</td>\n",
       "      <td>Male</td>\n",
       "      <td>Stamford</td>\n",
       "      <td>Daily</td>\n",
       "      <td>Chalupa</td>\n",
       "      <td>10.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Charles</td>\n",
       "      <td>Male</td>\n",
       "      <td>New York</td>\n",
       "      <td>Never</td>\n",
       "      <td>Sushi</td>\n",
       "      <td>42.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Anna</td>\n",
       "      <td>Female</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Once</td>\n",
       "      <td>Ice Cream</td>\n",
       "      <td>11.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Deborah</td>\n",
       "      <td>Female</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Daily</td>\n",
       "      <td>Chalupa</td>\n",
       "      <td>23.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  First Name  Gender          City Frequency       Item  Spend\n",
       "0      Wanda  Female      Stamford    Weekly     Burger  15.66\n",
       "1       Eric    Male      Stamford     Daily    Chalupa  10.56\n",
       "2    Charles    Male      New York     Never      Sushi  42.14\n",
       "3       Anna  Female  Philadelphia      Once  Ice Cream  11.01\n",
       "4    Deborah  Female  Philadelphia     Daily    Chalupa  23.49"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "foods = pd.read_csv(\"foods.csv\")\n",
    "foods.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>New York</th>\n",
       "      <th>Philadelphia</th>\n",
       "      <th>Stamford</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gender</th>\n",
       "      <th>Item</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">Female</th>\n",
       "      <th>Burger</th>\n",
       "      <td>1239.04</td>\n",
       "      <td>1639.24</td>\n",
       "      <td>1216.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burrito</th>\n",
       "      <td>978.95</td>\n",
       "      <td>1458.76</td>\n",
       "      <td>1820.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chalupa</th>\n",
       "      <td>876.58</td>\n",
       "      <td>1673.33</td>\n",
       "      <td>1602.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Donut</th>\n",
       "      <td>1446.78</td>\n",
       "      <td>1639.26</td>\n",
       "      <td>1656.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ice Cream</th>\n",
       "      <td>1521.62</td>\n",
       "      <td>1479.22</td>\n",
       "      <td>1032.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sushi</th>\n",
       "      <td>1480.29</td>\n",
       "      <td>1742.88</td>\n",
       "      <td>1459.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">Male</th>\n",
       "      <th>Burger</th>\n",
       "      <td>1294.09</td>\n",
       "      <td>938.18</td>\n",
       "      <td>1439.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burrito</th>\n",
       "      <td>1399.40</td>\n",
       "      <td>1312.93</td>\n",
       "      <td>1300.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chalupa</th>\n",
       "      <td>1227.77</td>\n",
       "      <td>1114.23</td>\n",
       "      <td>1150.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Donut</th>\n",
       "      <td>1345.27</td>\n",
       "      <td>1249.36</td>\n",
       "      <td>1421.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ice Cream</th>\n",
       "      <td>1603.63</td>\n",
       "      <td>2191.27</td>\n",
       "      <td>1059.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sushi</th>\n",
       "      <td>1396.15</td>\n",
       "      <td>1395.88</td>\n",
       "      <td>1267.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "City              New York  Philadelphia  Stamford\n",
       "Gender Item                                       \n",
       "Female Burger      1239.04       1639.24   1216.02\n",
       "       Burrito      978.95       1458.76   1820.11\n",
       "       Chalupa      876.58       1673.33   1602.35\n",
       "       Donut       1446.78       1639.26   1656.96\n",
       "       Ice Cream   1521.62       1479.22   1032.03\n",
       "       Sushi       1480.29       1742.88   1459.91\n",
       "Male   Burger      1294.09        938.18   1439.16\n",
       "       Burrito     1399.40       1312.93   1300.29\n",
       "       Chalupa     1227.77       1114.23   1150.26\n",
       "       Donut       1345.27       1249.36   1421.13\n",
       "       Ice Cream   1603.63       2191.27   1059.22\n",
       "       Sushi       1396.15       1395.88   1267.82"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "foods.pivot_table(values=\"Spend\", index=[\"Gender\",\"Item\"], columns=\"City\", aggfunc=\"sum\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Salesman</th>\n",
       "      <th>Q1</th>\n",
       "      <th>Q2</th>\n",
       "      <th>Q3</th>\n",
       "      <th>Q4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Boris</td>\n",
       "      <td>602908</td>\n",
       "      <td>233879</td>\n",
       "      <td>354479</td>\n",
       "      <td>32704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bob</td>\n",
       "      <td>43790</td>\n",
       "      <td>514863</td>\n",
       "      <td>297151</td>\n",
       "      <td>544493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tommy</td>\n",
       "      <td>392668</td>\n",
       "      <td>113579</td>\n",
       "      <td>430882</td>\n",
       "      <td>247231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Travis</td>\n",
       "      <td>834663</td>\n",
       "      <td>266785</td>\n",
       "      <td>749238</td>\n",
       "      <td>570524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Donald</td>\n",
       "      <td>580935</td>\n",
       "      <td>411379</td>\n",
       "      <td>110390</td>\n",
       "      <td>651572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Salesman      Q1      Q2      Q3      Q4\n",
       "0    Boris  602908  233879  354479   32704\n",
       "1      Bob   43790  514863  297151  544493\n",
       "2    Tommy  392668  113579  430882  247231\n",
       "3   Travis  834663  266785  749238  570524\n",
       "4   Donald  580935  411379  110390  651572"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales = pd.read_csv(\"quarters.csv\")\n",
    "sales.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Salesman</th>\n",
       "      <th>Quater</th>\n",
       "      <th>Revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Boris</td>\n",
       "      <td>Q1</td>\n",
       "      <td>602908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bob</td>\n",
       "      <td>Q1</td>\n",
       "      <td>43790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tommy</td>\n",
       "      <td>Q1</td>\n",
       "      <td>392668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Travis</td>\n",
       "      <td>Q1</td>\n",
       "      <td>834663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Donald</td>\n",
       "      <td>Q1</td>\n",
       "      <td>580935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ted</td>\n",
       "      <td>Q1</td>\n",
       "      <td>656644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Jeb</td>\n",
       "      <td>Q1</td>\n",
       "      <td>486141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Stacy</td>\n",
       "      <td>Q1</td>\n",
       "      <td>479662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Morgan</td>\n",
       "      <td>Q1</td>\n",
       "      <td>992673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Boris</td>\n",
       "      <td>Q2</td>\n",
       "      <td>233879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Bob</td>\n",
       "      <td>Q2</td>\n",
       "      <td>514863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Tommy</td>\n",
       "      <td>Q2</td>\n",
       "      <td>113579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Travis</td>\n",
       "      <td>Q2</td>\n",
       "      <td>266785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Donald</td>\n",
       "      <td>Q2</td>\n",
       "      <td>411379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Ted</td>\n",
       "      <td>Q2</td>\n",
       "      <td>70803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Jeb</td>\n",
       "      <td>Q2</td>\n",
       "      <td>600753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Stacy</td>\n",
       "      <td>Q2</td>\n",
       "      <td>742806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Morgan</td>\n",
       "      <td>Q2</td>\n",
       "      <td>879183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Boris</td>\n",
       "      <td>Q3</td>\n",
       "      <td>354479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Bob</td>\n",
       "      <td>Q3</td>\n",
       "      <td>297151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Tommy</td>\n",
       "      <td>Q3</td>\n",
       "      <td>430882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Travis</td>\n",
       "      <td>Q3</td>\n",
       "      <td>749238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Donald</td>\n",
       "      <td>Q3</td>\n",
       "      <td>110390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Ted</td>\n",
       "      <td>Q3</td>\n",
       "      <td>375948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Jeb</td>\n",
       "      <td>Q3</td>\n",
       "      <td>742716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Stacy</td>\n",
       "      <td>Q3</td>\n",
       "      <td>770712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Morgan</td>\n",
       "      <td>Q3</td>\n",
       "      <td>37945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Boris</td>\n",
       "      <td>Q4</td>\n",
       "      <td>32704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Bob</td>\n",
       "      <td>Q4</td>\n",
       "      <td>544493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Tommy</td>\n",
       "      <td>Q4</td>\n",
       "      <td>247231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Travis</td>\n",
       "      <td>Q4</td>\n",
       "      <td>570524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Donald</td>\n",
       "      <td>Q4</td>\n",
       "      <td>651572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Ted</td>\n",
       "      <td>Q4</td>\n",
       "      <td>321388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Jeb</td>\n",
       "      <td>Q4</td>\n",
       "      <td>404995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Stacy</td>\n",
       "      <td>Q4</td>\n",
       "      <td>2501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Morgan</td>\n",
       "      <td>Q4</td>\n",
       "      <td>293710</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Salesman Quater  Revenue\n",
       "0     Boris     Q1   602908\n",
       "1       Bob     Q1    43790\n",
       "2     Tommy     Q1   392668\n",
       "3    Travis     Q1   834663\n",
       "4    Donald     Q1   580935\n",
       "5       Ted     Q1   656644\n",
       "6       Jeb     Q1   486141\n",
       "7     Stacy     Q1   479662\n",
       "8    Morgan     Q1   992673\n",
       "9     Boris     Q2   233879\n",
       "10      Bob     Q2   514863\n",
       "11    Tommy     Q2   113579\n",
       "12   Travis     Q2   266785\n",
       "13   Donald     Q2   411379\n",
       "14      Ted     Q2    70803\n",
       "15      Jeb     Q2   600753\n",
       "16    Stacy     Q2   742806\n",
       "17   Morgan     Q2   879183\n",
       "18    Boris     Q3   354479\n",
       "19      Bob     Q3   297151\n",
       "20    Tommy     Q3   430882\n",
       "21   Travis     Q3   749238\n",
       "22   Donald     Q3   110390\n",
       "23      Ted     Q3   375948\n",
       "24      Jeb     Q3   742716\n",
       "25    Stacy     Q3   770712\n",
       "26   Morgan     Q3    37945\n",
       "27    Boris     Q4    32704\n",
       "28      Bob     Q4   544493\n",
       "29    Tommy     Q4   247231\n",
       "30   Travis     Q4   570524\n",
       "31   Donald     Q4   651572\n",
       "32      Ted     Q4   321388\n",
       "33      Jeb     Q4   404995\n",
       "34    Stacy     Q4     2501\n",
       "35   Morgan     Q4   293710"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.melt(id_vars=\"Salesman\",var_name=\"Quater\", value_name=\"Revenue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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