Multi Index.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0a51bb16",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "17ea36a3",
   "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",
       "  </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"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac = pd.read_csv(\"bigmac.csv\", parse_dates = [\"Date\"])\n",
    "bigmac.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d056e705",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date                   datetime64[ns]\n",
       "Country                        object\n",
       "Price in US Dollars           float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c0ab1cd8",
   "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",
      " #   Column               Non-Null Count  Dtype         \n",
      "---  ------               --------------  -----         \n",
      " 0   Date                 652 non-null    datetime64[ns]\n",
      " 1   Country              652 non-null    object        \n",
      " 2   Price in US Dollars  652 non-null    float64       \n",
      "dtypes: datetime64[ns](1), float64(1), object(1)\n",
      "memory usage: 15.4+ KB\n"
     ]
    }
   ],
   "source": [
    "bigmac.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5767a86",
   "metadata": {},
   "source": [
    "# set_index() sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1e380152",
   "metadata": {},
   "outputs": [],
   "source": [
    "bigmac.set_index(keys = [\"Date\", \"Country\"], inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "35d06ea5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2016-01-01</th>\n",
       "      <th>Ukraine</th>\n",
       "      <td>1.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>4.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Venezuela</th>\n",
       "      <td>0.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vietnam</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",
       "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\n",
       "...                                       ...\n",
       "2016-01-01 Ukraine                       1.54\n",
       "           United States                 4.93\n",
       "           Uruguay                       3.74\n",
       "           Venezuela                     0.66\n",
       "           Vietnam                       2.67\n",
       "\n",
       "[652 rows x 1 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "03cb9fff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>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>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>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2016-01-01</th>\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",
       "...                                       ...\n",
       "2016-01-01 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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.sort_index(ascending = [True, False])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cc760b06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\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>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=\"3\" 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",
       "  </tbody>\n",
       "</table>\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"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.sort_index(ascending = [True, False], inplace = True)\n",
    "bigmac.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5b4d3e34",
   "metadata": {},
   "outputs": [],
   "source": [
    "bigmac.sort_index(level = 1)\n",
    "bigmac.sort_index(level = \"Country\", ascending = True)\n",
    "bigmac.sort_index(level = \"Country\", ascending = True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9ed54a4b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MultiIndex([('2010-01-01', 'Argentina'),\n",
       "            ('2010-07-01', 'Argentina'),\n",
       "            ('2011-07-01', 'Argentina'),\n",
       "            ('2012-01-01', 'Argentina'),\n",
       "            ('2012-07-01', 'Argentina'),\n",
       "            ('2013-01-01', 'Argentina'),\n",
       "            ('2013-07-01', 'Argentina'),\n",
       "            ('2014-01-01', 'Argentina'),\n",
       "            ('2014-07-01', 'Argentina'),\n",
       "            ('2015-01-01', 'Argentina'),\n",
       "            ...\n",
       "            ('2014-01-01', 'Venezuela'),\n",
       "            ('2014-07-01', 'Venezuela'),\n",
       "            ('2015-01-01', 'Venezuela'),\n",
       "            ('2015-07-01', 'Venezuela'),\n",
       "            ('2016-01-01', 'Venezuela'),\n",
       "            ('2014-01-01',   'Vietnam'),\n",
       "            ('2014-07-01',   'Vietnam'),\n",
       "            ('2015-01-01',   'Vietnam'),\n",
       "            ('2015-07-01',   'Vietnam'),\n",
       "            ('2016-01-01',   'Vietnam')],\n",
       "           names=['Date', 'Country'], length=652)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "076fe552",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.multi.MultiIndex"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(bigmac.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6989ffd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Timestamp('2010-01-01 00:00:00'), 'Argentina')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "470fdc31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tuple"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(bigmac.index[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "583410a3",
   "metadata": {},
   "source": [
    "# get_level_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ba491f4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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=\"3\" valign=\"top\">2016-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>3.35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Price in US Dollars\n",
       "Date       Country                       \n",
       "2016-01-01 Argentina                 2.39\n",
       "           Australia                 3.74\n",
       "           Brazil                    3.35"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac = pd.read_csv(\"bigmac.csv\", parse_dates = [\"Date\"], index_col = [\"Date\", \"Country\"])\n",
    "bigmac.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "73338e6c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['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",
       "               ...\n",
       "               '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",
       "              dtype='datetime64[ns]', name='Date', length=652, freq=None)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.get_level_values(\"Date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6127a683",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['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",
       "               ...\n",
       "               '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",
       "              dtype='datetime64[ns]', name='Date', length=652, freq=None)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.get_level_values(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c3a9a6a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Argentina', 'Australia', 'Brazil', 'Britain', 'Canada', 'Chile',\n",
       "       'China', 'Colombia', 'Costa Rica', 'Czech Republic',\n",
       "       ...\n",
       "       'Sri Lanka', 'Sweden', 'Switzerland', 'Taiwan', 'Thailand', 'Turkey',\n",
       "       'UAE', 'Ukraine', 'United States', 'Uruguay'],\n",
       "      dtype='object', name='Country', length=652)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.get_level_values(\"Country\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1d2d312b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Argentina', 'Australia', 'Brazil', 'Britain', 'Canada', 'Chile',\n",
       "       'China', 'Colombia', 'Costa Rica', 'Czech Republic',\n",
       "       ...\n",
       "       'Sri Lanka', 'Sweden', 'Switzerland', 'Taiwan', 'Thailand', 'Turkey',\n",
       "       'UAE', 'Ukraine', 'United States', 'Uruguay'],\n",
       "      dtype='object', name='Country', length=652)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.get_level_values(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "758b379b",
   "metadata": {},
   "source": [
    "# change index level name using set_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "32f5a3e6",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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=\"3\" valign=\"top\">2016-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>3.35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Price in US Dollars\n",
       "Date       Country                       \n",
       "2016-01-01 Argentina                 2.39\n",
       "           Australia                 3.74\n",
       "           Brazil                    3.35"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9ad72803",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price in US Dollars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th>Location</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2016-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>3.35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Price in US Dollars\n",
       "Date       Location                      \n",
       "2016-01-01 Argentina                 2.39\n",
       "           Australia                 3.74\n",
       "           Brazil                    3.35"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.set_names(\"Location\", level = 1)\n",
    "bigmac.index.set_names(\"Location\", level = \"Country\")\n",
    "bigmac.index.set_names(\"Location\", level = 1, inplace = True)\n",
    "bigmac.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e7369169",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MultiIndex([('2016-01-01',      'Argentina'),\n",
       "            ('2016-01-01',      'Australia'),\n",
       "            ('2016-01-01',         'Brazil'),\n",
       "            ('2016-01-01',        'Britain'),\n",
       "            ('2016-01-01',         'Canada'),\n",
       "            ('2016-01-01',          'Chile'),\n",
       "            ('2016-01-01',          'China'),\n",
       "            ('2016-01-01',       'Colombia'),\n",
       "            ('2016-01-01',     'Costa Rica'),\n",
       "            ('2016-01-01', 'Czech Republic'),\n",
       "            ...\n",
       "            ('2010-01-01',      'Sri Lanka'),\n",
       "            ('2010-01-01',         'Sweden'),\n",
       "            ('2010-01-01',    'Switzerland'),\n",
       "            ('2010-01-01',         'Taiwan'),\n",
       "            ('2010-01-01',       'Thailand'),\n",
       "            ('2010-01-01',         'Turkey'),\n",
       "            ('2010-01-01',            'UAE'),\n",
       "            ('2010-01-01',        'Ukraine'),\n",
       "            ('2010-01-01',  'United States'),\n",
       "            ('2010-01-01',        'Uruguay')],\n",
       "           names=['day', 'Location'], length=652)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.index.set_names([\"day\", \"Location\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3666a79f",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2dd90936",
   "metadata": {},
   "source": [
    "# extract rows in multi index using loc[] and iloc[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6833f18d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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=\"3\" 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",
       "  </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"
      ]
     },
     "execution_count": 22,
     "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(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fd258634",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date        Country  \n",
       "2016-01-01  Argentina    2.39\n",
       "Name: Price in US Dollars, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.loc[(\"2016-01-01\", \"Argentina\"), \"Price in US Dollars\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3a09e595",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date        Country       \n",
       "2016-01-01  Argentina         2.39\n",
       "            Australia         3.74\n",
       "            Austria           3.76\n",
       "            Belgium           4.25\n",
       "            Brazil            3.35\n",
       "            Britain           4.22\n",
       "            Canada            4.14\n",
       "            Chile             2.94\n",
       "            China             2.68\n",
       "            Colombia          2.43\n",
       "            Costa Rica        4.02\n",
       "            Czech Republic    2.98\n",
       "            Denmark           4.32\n",
       "            Egypt             2.16\n",
       "            Estonia           3.23\n",
       "            Euro area         4.00\n",
       "            Finland           4.41\n",
       "            France            4.41\n",
       "            Germany           3.86\n",
       "            Greece            3.60\n",
       "            Hong Kong         2.48\n",
       "            Hungary           3.08\n",
       "            India             1.90\n",
       "            Indonesia         2.19\n",
       "            Ireland           4.25\n",
       "            Israel            4.29\n",
       "            Italy             4.30\n",
       "            Japan             3.12\n",
       "            Malaysia          1.82\n",
       "            Mexico            2.81\n",
       "            Netherlands       3.71\n",
       "            New Zealand       3.91\n",
       "            Norway            5.21\n",
       "            Pakistan          2.86\n",
       "            Peru              2.93\n",
       "            Philippines       2.79\n",
       "            Poland            2.37\n",
       "            Portugal          3.23\n",
       "            Russia            1.53\n",
       "            Saudi Arabia      3.20\n",
       "            Singapore         3.27\n",
       "            South Africa      1.77\n",
       "            South Korea       3.59\n",
       "            Spain             3.76\n",
       "            Sri Lanka         2.43\n",
       "            Sweden            5.23\n",
       "            Switzerland       6.44\n",
       "            Taiwan            2.08\n",
       "            Thailand          3.09\n",
       "            Turkey            3.41\n",
       "            UAE               3.54\n",
       "            Ukraine           1.54\n",
       "            United States     4.93\n",
       "            Uruguay           3.74\n",
       "            Venezuela         0.66\n",
       "            Vietnam           2.67\n",
       "Name: Price in US Dollars, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.loc[(\"2016-01-01\", ), \"Price in US Dollars\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ff74384d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.84"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.iloc[0, 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "193dfa74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Price in US Dollars    1.84\n",
       "Name: (2010-01-01 00:00:00, Argentina), dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "61ca5a9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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=\"4\" 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",
       "  </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"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.iloc[0:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "65991233",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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=\"2\" valign=\"top\">2010-01-01</th>\n",
       "      <th>Argentina</th>\n",
       "      <td>1.84</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",
       "           Canada                    3.97"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.iloc[[0, 4]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5efe9228",
   "metadata": {},
   "source": [
    "# transpose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "af864f9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac = pd.read_csv(\"bigmac.csv\", parse_dates = [\"Date\"] ,index_col = [\"Date\", \"Country\"]).sort_index()\n",
    "bigmac.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "550e0dcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th colspan=\"10\" halign=\"left\">2010-01-01</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">2016-01-01</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th>Argentina</th>\n",
       "      <th>Australia</th>\n",
       "      <th>Brazil</th>\n",
       "      <th>Britain</th>\n",
       "      <th>Canada</th>\n",
       "      <th>Chile</th>\n",
       "      <th>China</th>\n",
       "      <th>Colombia</th>\n",
       "      <th>Costa Rica</th>\n",
       "      <th>Czech Republic</th>\n",
       "      <th>...</th>\n",
       "      <th>Switzerland</th>\n",
       "      <th>Taiwan</th>\n",
       "      <th>Thailand</th>\n",
       "      <th>Turkey</th>\n",
       "      <th>UAE</th>\n",
       "      <th>Ukraine</th>\n",
       "      <th>United States</th>\n",
       "      <th>Uruguay</th>\n",
       "      <th>Venezuela</th>\n",
       "      <th>Vietnam</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Price in US Dollars</th>\n",
       "      <td>1.84</td>\n",
       "      <td>3.98</td>\n",
       "      <td>4.76</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.97</td>\n",
       "      <td>3.18</td>\n",
       "      <td>1.83</td>\n",
       "      <td>3.91</td>\n",
       "      <td>3.52</td>\n",
       "      <td>3.71</td>\n",
       "      <td>...</td>\n",
       "      <td>6.44</td>\n",
       "      <td>2.08</td>\n",
       "      <td>3.09</td>\n",
       "      <td>3.41</td>\n",
       "      <td>3.54</td>\n",
       "      <td>1.54</td>\n",
       "      <td>4.93</td>\n",
       "      <td>3.74</td>\n",
       "      <td>0.66</td>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 652 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Date                2010-01-01                                              \\\n",
       "Country              Argentina Australia Brazil Britain Canada Chile China   \n",
       "Price in US Dollars       1.84      3.98   4.76    3.67   3.97  3.18  1.83   \n",
       "\n",
       "Date                                                    ...  2016-01-01  \\\n",
       "Country             Colombia Costa Rica Czech Republic  ... Switzerland   \n",
       "Price in US Dollars     3.91       3.52           3.71  ...        6.44   \n",
       "\n",
       "Date                                                                    \\\n",
       "Country             Taiwan Thailand Turkey   UAE Ukraine United States   \n",
       "Price in US Dollars   2.08     3.09   3.41  3.54    1.54          4.93   \n",
       "\n",
       "Date                                           \n",
       "Country             Uruguay Venezuela Vietnam  \n",
       "Price in US Dollars    3.74      0.66    2.67  \n",
       "\n",
       "[1 rows x 652 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmacT = bigmac.transpose()\n",
    "bigmacT.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7de98345",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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\n",
       "                             ... \n",
       "2016-01-01  Ukraine          1.54\n",
       "            United States    4.93\n",
       "            Uruguay          3.74\n",
       "            Venezuela        0.66\n",
       "            Vietnam          2.67\n",
       "Name: Price in US Dollars, Length: 652, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmacT.loc[\"Price in US Dollars\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "74171873",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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\n",
       "                             ... \n",
       "2016-01-01  Ukraine          1.54\n",
       "            United States    4.93\n",
       "            Uruguay          3.74\n",
       "            Venezuela        0.66\n",
       "            Vietnam          2.67\n",
       "Name: Price in US Dollars, Length: 652, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmacT.loc[\"Price in US Dollars\",]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e17d04a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th colspan=\"10\" halign=\"left\">2010-01-01</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">2016-01-01</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th>Argentina</th>\n",
       "      <th>Australia</th>\n",
       "      <th>Brazil</th>\n",
       "      <th>Britain</th>\n",
       "      <th>Canada</th>\n",
       "      <th>Chile</th>\n",
       "      <th>China</th>\n",
       "      <th>Colombia</th>\n",
       "      <th>Costa Rica</th>\n",
       "      <th>Czech Republic</th>\n",
       "      <th>...</th>\n",
       "      <th>Switzerland</th>\n",
       "      <th>Taiwan</th>\n",
       "      <th>Thailand</th>\n",
       "      <th>Turkey</th>\n",
       "      <th>UAE</th>\n",
       "      <th>Ukraine</th>\n",
       "      <th>United States</th>\n",
       "      <th>Uruguay</th>\n",
       "      <th>Venezuela</th>\n",
       "      <th>Vietnam</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Price in US Dollars</th>\n",
       "      <td>1.84</td>\n",
       "      <td>3.98</td>\n",
       "      <td>4.76</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.97</td>\n",
       "      <td>3.18</td>\n",
       "      <td>1.83</td>\n",
       "      <td>3.91</td>\n",
       "      <td>3.52</td>\n",
       "      <td>3.71</td>\n",
       "      <td>...</td>\n",
       "      <td>6.44</td>\n",
       "      <td>2.08</td>\n",
       "      <td>3.09</td>\n",
       "      <td>3.41</td>\n",
       "      <td>3.54</td>\n",
       "      <td>1.54</td>\n",
       "      <td>4.93</td>\n",
       "      <td>3.74</td>\n",
       "      <td>0.66</td>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 652 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Date                2010-01-01                                              \\\n",
       "Country              Argentina Australia Brazil Britain Canada Chile China   \n",
       "Price in US Dollars       1.84      3.98   4.76    3.67   3.97  3.18  1.83   \n",
       "\n",
       "Date                                                    ...  2016-01-01  \\\n",
       "Country             Colombia Costa Rica Czech Republic  ... Switzerland   \n",
       "Price in US Dollars     3.91       3.52           3.71  ...        6.44   \n",
       "\n",
       "Date                                                                    \\\n",
       "Country             Taiwan Thailand Turkey   UAE Ukraine United States   \n",
       "Price in US Dollars   2.08     3.09   3.41  3.54    1.54          4.93   \n",
       "\n",
       "Date                                           \n",
       "Country             Uruguay Venezuela Vietnam  \n",
       "Price in US Dollars    3.74      0.66    2.67  \n",
       "\n",
       "[1 rows x 652 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmacT.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3d544ee8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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\n",
       "            Chile             3.18\n",
       "            China             1.83\n",
       "            Colombia          3.91\n",
       "            Costa Rica        3.52\n",
       "            Czech Republic    3.71\n",
       "            Denmark           5.99\n",
       "            Egypt             2.38\n",
       "            Euro area         4.84\n",
       "            Hong Kong         1.91\n",
       "            Hungary           3.86\n",
       "            Indonesia         2.24\n",
       "            Israel            3.99\n",
       "            Japan             3.50\n",
       "            Latvia            3.09\n",
       "            Lithuania         2.87\n",
       "            Malaysia          2.08\n",
       "            Mexico            2.50\n",
       "            New Zealand       3.61\n",
       "            Norway            7.02\n",
       "            Pakistan          2.42\n",
       "            Peru              2.81\n",
       "            Philippines       2.21\n",
       "            Poland            2.86\n",
       "            Russia            2.34\n",
       "            Saudi Arabia      2.67\n",
       "            Singapore         3.19\n",
       "            South Africa      2.46\n",
       "            South Korea       2.98\n",
       "            Sri Lanka         1.83\n",
       "            Sweden            5.51\n",
       "            Switzerland       6.30\n",
       "            Taiwan            2.36\n",
       "            Thailand          2.11\n",
       "            Turkey            3.83\n",
       "            UAE               2.99\n",
       "            Ukraine           1.83\n",
       "            United States     3.58\n",
       "            Uruguay           3.32\n",
       "Name: Price in US Dollars, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmacT.loc[\"Price in US Dollars\", \"2010-01-01\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "35663b29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date        Country\n",
       "2010-01-01  China      1.83\n",
       "Name: Price in US Dollars, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmacT.loc[\"Price in US Dollars\", (\"2010-01-01\", \"China\")]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48618d01",
   "metadata": {},
   "source": [
    "# swap level()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3cad785f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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 = pd.read_csv(\"bigmac.csv\", parse_dates = [\"Date\"] ,index_col = [\"Date\", \"Country\"]).sort_index()\n",
    "bigmac.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6c666a70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</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",
       "...                                       ...\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": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.swaplevel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "562988f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</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",
       "...                                       ...\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": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigmac.swaplevel(\"Date\", \"Country\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "6d7c1821",
   "metadata": {},
   "outputs": [],
   "source": [
    "bigmac = bigmac.swaplevel(\"Date\", \"Country\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "775285da",
   "metadata": {},
   "source": [
    "# stack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "c9f0406d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Population</th>\n",
       "      <th>GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <th>Arab World</th>\n",
       "      <td>392022276.0</td>\n",
       "      <td>2.530102e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>Arab World</th>\n",
       "      <td>384222592.0</td>\n",
       "      <td>2.873600e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>Arab World</th>\n",
       "      <td>376504253.0</td>\n",
       "      <td>2.846994e+12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Population           GDP\n",
       "year country                              \n",
       "2015 Arab World  392022276.0  2.530102e+12\n",
       "2014 Arab World  384222592.0  2.873600e+12\n",
       "2013 Arab World  376504253.0  2.846994e+12"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world = pd.read_csv(\"worldstats.csv\", index_col = (\"year\", \"country\"))\n",
    "world.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "adb10cad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year  country               \n",
       "2015  Arab World  Population    3.920223e+08\n",
       "                  GDP           2.530102e+12\n",
       "2014  Arab World  Population    3.842226e+08\n",
       "                  GDP           2.873600e+12\n",
       "2013  Arab World  Population    3.765043e+08\n",
       "                                    ...     \n",
       "1962  Zimbabwe    GDP           1.117602e+09\n",
       "1961  Zimbabwe    Population    3.876638e+06\n",
       "                  GDP           1.096647e+09\n",
       "1960  Zimbabwe    Population    3.752390e+06\n",
       "                  GDP           1.052990e+09\n",
       "Length: 22422, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world.stack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "5a7a20a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year  country               \n",
       "2015  Arab World  Population    3.920223e+08\n",
       "                  GDP           2.530102e+12\n",
       "2014  Arab World  Population    3.842226e+08\n",
       "dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2 = world.stack()\n",
    "world2.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76859f93",
   "metadata": {},
   "source": [
    "# unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2cb6c7e2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Population</th>\n",
       "      <th>GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1960</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>8.994793e+06</td>\n",
       "      <td>5.377778e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>1.112489e+07</td>\n",
       "      <td>2.723638e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>1.027648e+07</td>\n",
       "      <td>1.856759e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>7.047539e+06</td>\n",
       "      <td>6.592694e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bahamas, The</th>\n",
       "      <td>1.095260e+05</td>\n",
       "      <td>1.698023e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2015</th>\n",
       "      <th>Vietnam</th>\n",
       "      <td>9.170380e+07</td>\n",
       "      <td>1.935994e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Bank and Gaza</th>\n",
       "      <td>4.422143e+06</td>\n",
       "      <td>1.267740e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>World</th>\n",
       "      <td>7.346633e+09</td>\n",
       "      <td>7.343364e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\n",
       "      <td>1.621177e+07</td>\n",
       "      <td>2.120156e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>1.560275e+07</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",
       "year country                                       \n",
       "1960 Afghanistan         8.994793e+06  5.377778e+08\n",
       "     Algeria             1.112489e+07  2.723638e+09\n",
       "     Australia           1.027648e+07  1.856759e+10\n",
       "     Austria             7.047539e+06  6.592694e+09\n",
       "     Bahamas, The        1.095260e+05  1.698023e+08\n",
       "...                               ...           ...\n",
       "2015 Vietnam             9.170380e+07  1.935994e+11\n",
       "     West Bank and Gaza  4.422143e+06  1.267740e+10\n",
       "     World               7.346633e+09  7.343364e+13\n",
       "     Zambia              1.621177e+07  2.120156e+10\n",
       "     Zimbabwe            1.560275e+07  1.389294e+10\n",
       "\n",
       "[11211 rows x 2 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "08f1b8f6",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"10\" halign=\"left\">Population</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <th>Albania</th>\n",
       "      <th>Algeria</th>\n",
       "      <th>Andorra</th>\n",
       "      <th>Angola</th>\n",
       "      <th>Antigua and Barbuda</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Argentina</th>\n",
       "      <th>Armenia</th>\n",
       "      <th>Aruba</th>\n",
       "      <th>...</th>\n",
       "      <th>Uzbekistan</th>\n",
       "      <th>Vanuatu</th>\n",
       "      <th>Venezuela, RB</th>\n",
       "      <th>Vietnam</th>\n",
       "      <th>Virgin Islands (U.S.)</th>\n",
       "      <th>West Bank and Gaza</th>\n",
       "      <th>World</th>\n",
       "      <th>Yemen, Rep.</th>\n",
       "      <th>Zambia</th>\n",
       "      <th>Zimbabwe</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</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>1960</th>\n",
       "      <td>8994793.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11124892.0</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.607600e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.420000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.364643e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.987397e+08</td>\n",
       "      <td>1.052990e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1961</th>\n",
       "      <td>9164945.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11404859.0</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.923367e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.570000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.420440e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.823597e+08</td>\n",
       "      <td>1.096647e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1962</th>\n",
       "      <td>9343772.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11690152.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21287682.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.873398e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.690000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.524573e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.792797e+08</td>\n",
       "      <td>1.117602e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1963</th>\n",
       "      <td>9531555.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11985130.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21621845.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.066338e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.140000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.638187e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.043397e+08</td>\n",
       "      <td>1.159512e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1964</th>\n",
       "      <td>9728645.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12295973.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21953926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.113581e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.380000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.799675e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.226397e+08</td>\n",
       "      <td>1.217138e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1965</th>\n",
       "      <td>9935358.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12626953.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22283389.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.602945e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.650000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.959900e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.061200e+09</td>\n",
       "      <td>1.311436e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1966</th>\n",
       "      <td>10148841.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12980269.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22608747.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.009657e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.410000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.125397e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.239000e+09</td>\n",
       "      <td>1.281750e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1967</th>\n",
       "      <td>10368600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13354197.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22932201.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.047278e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.154000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.262923e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.340639e+09</td>\n",
       "      <td>1.397002e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1968</th>\n",
       "      <td>10599790.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13744383.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115557094.0</td>\n",
       "      <td>23261273.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.147091e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.738000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.440549e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.573739e+09</td>\n",
       "      <td>1.479600e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969</th>\n",
       "      <td>10849510.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14144437.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118823872.0</td>\n",
       "      <td>23605992.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.192757e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.113000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.686747e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.926399e+09</td>\n",
       "      <td>1.747999e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>11121097.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14550033.0</td>\n",
       "      <td>24279.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>122128175.0</td>\n",
       "      <td>23973062.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.299312e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.190000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.950656e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.788779e+09</td>\n",
       "      <td>1.884206e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1971</th>\n",
       "      <td>11412821.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14960111.0</td>\n",
       "      <td>25560.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125439089.0</td>\n",
       "      <td>24366442.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.447156e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.570000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.259057e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.653259e+09</td>\n",
       "      <td>2.178716e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1972</th>\n",
       "      <td>11716896.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15377095.0</td>\n",
       "      <td>26892.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>128801209.0</td>\n",
       "      <td>24782950.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.592287e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.071000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.757853e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.872417e+09</td>\n",
       "      <td>2.677729e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>12022514.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15804428.0</td>\n",
       "      <td>28231.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>132298955.0</td>\n",
       "      <td>25213388.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.944593e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.516000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.578523e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.434255e+09</td>\n",
       "      <td>3.309354e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1974</th>\n",
       "      <td>12315553.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16247113.0</td>\n",
       "      <td>29514.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>136044481.0</td>\n",
       "      <td>25644505.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.908710e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.954000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.279355e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.910981e+09</td>\n",
       "      <td>3.982161e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>12582954.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16709098.0</td>\n",
       "      <td>30706.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140114424.0</td>\n",
       "      <td>26066975.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.141316e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.998000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.880305e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.442672e+09</td>\n",
       "      <td>4.371301e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>12831361.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17190236.0</td>\n",
       "      <td>31781.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144542039.0</td>\n",
       "      <td>26477153.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.627232e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.400000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.400883e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.742859e+09</td>\n",
       "      <td>4.318372e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1977</th>\n",
       "      <td>13056499.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17690184.0</td>\n",
       "      <td>32769.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70223.0</td>\n",
       "      <td>149296257.0</td>\n",
       "      <td>26878567.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.233706e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.618000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.237905e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.515297e+09</td>\n",
       "      <td>4.364382e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1978</th>\n",
       "      <td>13222547.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18212331.0</td>\n",
       "      <td>33746.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70508.0</td>\n",
       "      <td>154303887.0</td>\n",
       "      <td>27277742.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.650764e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.129000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.521725e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.811032e+09</td>\n",
       "      <td>4.351600e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1979</th>\n",
       "      <td>13283279.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18760761.0</td>\n",
       "      <td>34819.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70553.0</td>\n",
       "      <td>159455867.0</td>\n",
       "      <td>27684530.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.192588e+08</td>\n",
       "      <td>5.575055e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.067000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.903841e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.353445e+09</td>\n",
       "      <td>5.177459e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>13211412.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19337723.0</td>\n",
       "      <td>36063.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70301.0</td>\n",
       "      <td>164670713.0</td>\n",
       "      <td>28105889.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.134232e+08</td>\n",
       "      <td>6.713512e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.278000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.115409e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.884531e+09</td>\n",
       "      <td>6.678868e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>12996923.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19943667.0</td>\n",
       "      <td>37502.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69750.0</td>\n",
       "      <td>169926632.0</td>\n",
       "      <td>28543366.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.874641e+07</td>\n",
       "      <td>7.549883e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.218000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.144748e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.008126e+09</td>\n",
       "      <td>8.011374e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20575701.0</td>\n",
       "      <td>39112.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68950.0</td>\n",
       "      <td>175237742.0</td>\n",
       "      <td>28993989.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.814464e+07</td>\n",
       "      <td>7.669365e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.326000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.134460e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.871117e+09</td>\n",
       "      <td>8.539701e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21228288.0</td>\n",
       "      <td>40862.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>67958.0</td>\n",
       "      <td>180606318.0</td>\n",
       "      <td>29454739.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.101238e+08</td>\n",
       "      <td>7.858650e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.169000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.160740e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.321048e+09</td>\n",
       "      <td>7.764067e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2904429.0</td>\n",
       "      <td>21893857.0</td>\n",
       "      <td>42704.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66863.0</td>\n",
       "      <td>186005735.0</td>\n",
       "      <td>29920907.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.355538e+08</td>\n",
       "      <td>5.595234e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.854000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.204953e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.719519e+09</td>\n",
       "      <td>6.352126e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2964762.0</td>\n",
       "      <td>22565908.0</td>\n",
       "      <td>44597.0</td>\n",
       "      <td>9745209.0</td>\n",
       "      <td>65744.0</td>\n",
       "      <td>191564251.0</td>\n",
       "      <td>30388781.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.236985e+08</td>\n",
       "      <td>5.793574e+10</td>\n",
       "      <td>1.409469e+10</td>\n",
       "      <td>9.904000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.267287e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.252455e+09</td>\n",
       "      <td>5.637259e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3022635.0</td>\n",
       "      <td>23241276.0</td>\n",
       "      <td>46515.0</td>\n",
       "      <td>10023700.0</td>\n",
       "      <td>64605.0</td>\n",
       "      <td>197202142.0</td>\n",
       "      <td>30857242.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.186914e+08</td>\n",
       "      <td>5.891511e+10</td>\n",
       "      <td>2.633662e+10</td>\n",
       "      <td>1.035600e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.499712e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.664414e+09</td>\n",
       "      <td>6.217524e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3083605.0</td>\n",
       "      <td>23917889.0</td>\n",
       "      <td>48458.0</td>\n",
       "      <td>10285712.0</td>\n",
       "      <td>63484.0</td>\n",
       "      <td>202851923.0</td>\n",
       "      <td>31326473.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.308341e+08</td>\n",
       "      <td>4.534379e+10</td>\n",
       "      <td>3.665811e+10</td>\n",
       "      <td>1.147800e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.706395e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.265251e+09</td>\n",
       "      <td>6.741215e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3142336.0</td>\n",
       "      <td>24591493.0</td>\n",
       "      <td>50431.0</td>\n",
       "      <td>10544904.0</td>\n",
       "      <td>62538.0</td>\n",
       "      <td>208546282.0</td>\n",
       "      <td>31795515.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.485454e+08</td>\n",
       "      <td>5.842840e+10</td>\n",
       "      <td>2.542381e+10</td>\n",
       "      <td>1.204600e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.910918e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.728878e+09</td>\n",
       "      <td>7.814784e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3227943.0</td>\n",
       "      <td>25257671.0</td>\n",
       "      <td>52449.0</td>\n",
       "      <td>10820992.0</td>\n",
       "      <td>61967.0</td>\n",
       "      <td>214250542.0</td>\n",
       "      <td>32263559.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.444822e+08</td>\n",
       "      <td>4.214230e+10</td>\n",
       "      <td>6.293305e+09</td>\n",
       "      <td>1.343900e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.006077e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.994673e+09</td>\n",
       "      <td>8.286323e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3286542.0</td>\n",
       "      <td>25912364.0</td>\n",
       "      <td>54511.0</td>\n",
       "      <td>11127870.0</td>\n",
       "      <td>61906.0</td>\n",
       "      <td>222117305.0</td>\n",
       "      <td>32729740.0</td>\n",
       "      <td>3544695.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.336061e+10</td>\n",
       "      <td>1.583974e+08</td>\n",
       "      <td>4.702751e+10</td>\n",
       "      <td>6.471740e+09</td>\n",
       "      <td>1.564700e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.256312e+13</td>\n",
       "      <td>5.647252e+09</td>\n",
       "      <td>3.288382e+09</td>\n",
       "      <td>8.783817e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3266790.0</td>\n",
       "      <td>26554277.0</td>\n",
       "      <td>56674.0</td>\n",
       "      <td>11472173.0</td>\n",
       "      <td>62412.0</td>\n",
       "      <td>228171034.0</td>\n",
       "      <td>33193920.0</td>\n",
       "      <td>3511912.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.367762e+10</td>\n",
       "      <td>1.888700e+08</td>\n",
       "      <td>5.173436e+10</td>\n",
       "      <td>9.613370e+09</td>\n",
       "      <td>1.671200e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.389846e+13</td>\n",
       "      <td>5.930370e+09</td>\n",
       "      <td>3.378882e+09</td>\n",
       "      <td>8.641482e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3247039.0</td>\n",
       "      <td>27180921.0</td>\n",
       "      <td>58904.0</td>\n",
       "      <td>11848971.0</td>\n",
       "      <td>63434.0</td>\n",
       "      <td>232417246.0</td>\n",
       "      <td>33655149.0</td>\n",
       "      <td>3449497.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.294130e+10</td>\n",
       "      <td>1.961426e+08</td>\n",
       "      <td>5.847036e+10</td>\n",
       "      <td>9.866990e+09</td>\n",
       "      <td>1.770900e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.537482e+13</td>\n",
       "      <td>6.463650e+09</td>\n",
       "      <td>3.181922e+09</td>\n",
       "      <td>6.751472e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3227287.0</td>\n",
       "      <td>27785977.0</td>\n",
       "      <td>61003.0</td>\n",
       "      <td>12246786.0</td>\n",
       "      <td>64868.0</td>\n",
       "      <td>238628852.0</td>\n",
       "      <td>34110912.0</td>\n",
       "      <td>3369673.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.309901e+10</td>\n",
       "      <td>1.880804e+08</td>\n",
       "      <td>5.810756e+10</td>\n",
       "      <td>1.318095e+10</td>\n",
       "      <td>1.996000e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.580571e+13</td>\n",
       "      <td>5.368271e+09</td>\n",
       "      <td>3.273238e+09</td>\n",
       "      <td>6.563813e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3207536.0</td>\n",
       "      <td>28362015.0</td>\n",
       "      <td>62707.0</td>\n",
       "      <td>12648483.0</td>\n",
       "      <td>66550.0</td>\n",
       "      <td>244893420.0</td>\n",
       "      <td>34558114.0</td>\n",
       "      <td>3289943.0</td>\n",
       "      <td>76700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.289916e+10</td>\n",
       "      <td>2.192603e+08</td>\n",
       "      <td>5.652990e+10</td>\n",
       "      <td>1.628643e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.843300e+09</td>\n",
       "      <td>2.770637e+13</td>\n",
       "      <td>4.167356e+09</td>\n",
       "      <td>3.656648e+09</td>\n",
       "      <td>6.890675e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3187784.0</td>\n",
       "      <td>28904300.0</td>\n",
       "      <td>63854.0</td>\n",
       "      <td>13042666.0</td>\n",
       "      <td>68349.0</td>\n",
       "      <td>252591048.0</td>\n",
       "      <td>34994818.0</td>\n",
       "      <td>3223173.0</td>\n",
       "      <td>80326.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.335047e+10</td>\n",
       "      <td>2.339021e+08</td>\n",
       "      <td>7.488874e+10</td>\n",
       "      <td>2.073616e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.282800e+09</td>\n",
       "      <td>3.065894e+13</td>\n",
       "      <td>4.258789e+09</td>\n",
       "      <td>3.807067e+09</td>\n",
       "      <td>7.111271e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3168033.0</td>\n",
       "      <td>29411839.0</td>\n",
       "      <td>64291.0</td>\n",
       "      <td>13424813.0</td>\n",
       "      <td>70245.0</td>\n",
       "      <td>258423164.0</td>\n",
       "      <td>35419683.0</td>\n",
       "      <td>3173425.0</td>\n",
       "      <td>83195.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.394889e+10</td>\n",
       "      <td>2.451776e+08</td>\n",
       "      <td>6.825859e+10</td>\n",
       "      <td>2.465747e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.409600e+09</td>\n",
       "      <td>3.132499e+13</td>\n",
       "      <td>5.785685e+09</td>\n",
       "      <td>3.597221e+09</td>\n",
       "      <td>8.553147e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3148281.0</td>\n",
       "      <td>29887717.0</td>\n",
       "      <td>64147.0</td>\n",
       "      <td>13801868.0</td>\n",
       "      <td>72232.0</td>\n",
       "      <td>264153948.0</td>\n",
       "      <td>35833965.0</td>\n",
       "      <td>3137652.0</td>\n",
       "      <td>85447.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.474460e+10</td>\n",
       "      <td>2.558902e+08</td>\n",
       "      <td>8.583739e+10</td>\n",
       "      <td>2.684370e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.759800e+09</td>\n",
       "      <td>3.124076e+13</td>\n",
       "      <td>6.839039e+09</td>\n",
       "      <td>4.303282e+09</td>\n",
       "      <td>8.529572e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3128530.0</td>\n",
       "      <td>30336880.0</td>\n",
       "      <td>63888.0</td>\n",
       "      <td>14187710.0</td>\n",
       "      <td>74206.0</td>\n",
       "      <td>269795252.0</td>\n",
       "      <td>36241578.0</td>\n",
       "      <td>3112958.0</td>\n",
       "      <td>87276.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.498897e+10</td>\n",
       "      <td>2.623013e+08</td>\n",
       "      <td>9.133854e+10</td>\n",
       "      <td>2.720960e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.067800e+09</td>\n",
       "      <td>3.112270e+13</td>\n",
       "      <td>6.325220e+09</td>\n",
       "      <td>3.537683e+09</td>\n",
       "      <td>6.401968e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3108778.0</td>\n",
       "      <td>30766551.0</td>\n",
       "      <td>64161.0</td>\n",
       "      <td>14601983.0</td>\n",
       "      <td>76041.0</td>\n",
       "      <td>275503565.0</td>\n",
       "      <td>36648054.0</td>\n",
       "      <td>3093820.0</td>\n",
       "      <td>89004.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.707847e+10</td>\n",
       "      <td>2.679992e+08</td>\n",
       "      <td>9.797414e+10</td>\n",
       "      <td>2.868366e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.271200e+09</td>\n",
       "      <td>3.228297e+13</td>\n",
       "      <td>7.641101e+09</td>\n",
       "      <td>3.404312e+09</td>\n",
       "      <td>6.858013e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3089027.0</td>\n",
       "      <td>31183658.0</td>\n",
       "      <td>65399.0</td>\n",
       "      <td>15058638.0</td>\n",
       "      <td>77648.0</td>\n",
       "      <td>281326250.0</td>\n",
       "      <td>37057453.0</td>\n",
       "      <td>3076098.0</td>\n",
       "      <td>90858.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.376037e+10</td>\n",
       "      <td>2.720147e+08</td>\n",
       "      <td>1.171476e+11</td>\n",
       "      <td>3.364009e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.313600e+09</td>\n",
       "      <td>3.332130e+13</td>\n",
       "      <td>9.636342e+09</td>\n",
       "      <td>3.600683e+09</td>\n",
       "      <td>6.689958e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>20531160.0</td>\n",
       "      <td>3060173.0</td>\n",
       "      <td>31590320.0</td>\n",
       "      <td>67770.0</td>\n",
       "      <td>15562791.0</td>\n",
       "      <td>78972.0</td>\n",
       "      <td>287291826.0</td>\n",
       "      <td>37471535.0</td>\n",
       "      <td>3060036.0</td>\n",
       "      <td>92894.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.140135e+10</td>\n",
       "      <td>2.579269e+08</td>\n",
       "      <td>1.229097e+11</td>\n",
       "      <td>3.529135e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.003700e+09</td>\n",
       "      <td>3.313421e+13</td>\n",
       "      <td>9.854042e+09</td>\n",
       "      <td>4.094481e+09</td>\n",
       "      <td>6.777385e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>21487079.0</td>\n",
       "      <td>3051010.0</td>\n",
       "      <td>31990387.0</td>\n",
       "      <td>71046.0</td>\n",
       "      <td>16109696.0</td>\n",
       "      <td>80030.0</td>\n",
       "      <td>293402563.0</td>\n",
       "      <td>37889443.0</td>\n",
       "      <td>3047249.0</td>\n",
       "      <td>94995.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.687951e+09</td>\n",
       "      <td>2.626038e+08</td>\n",
       "      <td>9.288959e+10</td>\n",
       "      <td>3.794790e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.555800e+09</td>\n",
       "      <td>3.441805e+13</td>\n",
       "      <td>1.069328e+10</td>\n",
       "      <td>4.193846e+09</td>\n",
       "      <td>6.342116e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>22507368.0</td>\n",
       "      <td>3039616.0</td>\n",
       "      <td>32394886.0</td>\n",
       "      <td>74783.0</td>\n",
       "      <td>16691395.0</td>\n",
       "      <td>80904.0</td>\n",
       "      <td>299731956.0</td>\n",
       "      <td>38309475.0</td>\n",
       "      <td>3036420.0</td>\n",
       "      <td>97015.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.012811e+10</td>\n",
       "      <td>3.144631e+08</td>\n",
       "      <td>8.362219e+10</td>\n",
       "      <td>4.271707e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.968000e+09</td>\n",
       "      <td>3.865630e+13</td>\n",
       "      <td>1.177777e+10</td>\n",
       "      <td>4.901840e+09</td>\n",
       "      <td>5.727592e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>23499850.0</td>\n",
       "      <td>3026939.0</td>\n",
       "      <td>32817225.0</td>\n",
       "      <td>78337.0</td>\n",
       "      <td>17295500.0</td>\n",
       "      <td>81718.0</td>\n",
       "      <td>306387415.0</td>\n",
       "      <td>38728778.0</td>\n",
       "      <td>3025982.0</td>\n",
       "      <td>98742.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.203002e+10</td>\n",
       "      <td>3.649969e+08</td>\n",
       "      <td>1.124514e+11</td>\n",
       "      <td>4.942411e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.329200e+09</td>\n",
       "      <td>4.355213e+13</td>\n",
       "      <td>1.387350e+10</td>\n",
       "      <td>6.221078e+09</td>\n",
       "      <td>5.805598e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>24399948.0</td>\n",
       "      <td>3011487.0</td>\n",
       "      <td>33267887.0</td>\n",
       "      <td>81223.0</td>\n",
       "      <td>17912942.0</td>\n",
       "      <td>82565.0</td>\n",
       "      <td>313430911.0</td>\n",
       "      <td>39145491.0</td>\n",
       "      <td>3014917.0</td>\n",
       "      <td>100031.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.430751e+10</td>\n",
       "      <td>3.949626e+08</td>\n",
       "      <td>1.455135e+11</td>\n",
       "      <td>5.763326e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.831800e+09</td>\n",
       "      <td>4.714259e+13</td>\n",
       "      <td>1.675377e+10</td>\n",
       "      <td>8.331870e+09</td>\n",
       "      <td>5.755215e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>25183615.0</td>\n",
       "      <td>2992547.0</td>\n",
       "      <td>33749328.0</td>\n",
       "      <td>83373.0</td>\n",
       "      <td>18541467.0</td>\n",
       "      <td>83467.0</td>\n",
       "      <td>320906736.0</td>\n",
       "      <td>39558750.0</td>\n",
       "      <td>3002161.0</td>\n",
       "      <td>100830.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.703090e+10</td>\n",
       "      <td>4.393768e+08</td>\n",
       "      <td>1.834775e+11</td>\n",
       "      <td>6.637166e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.910100e+09</td>\n",
       "      <td>5.107451e+13</td>\n",
       "      <td>1.908173e+10</td>\n",
       "      <td>1.275686e+10</td>\n",
       "      <td>5.443896e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>25877544.0</td>\n",
       "      <td>2970017.0</td>\n",
       "      <td>34261971.0</td>\n",
       "      <td>84878.0</td>\n",
       "      <td>19183907.0</td>\n",
       "      <td>84397.0</td>\n",
       "      <td>328766559.0</td>\n",
       "      <td>39969903.0</td>\n",
       "      <td>2988117.0</td>\n",
       "      <td>101218.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.231139e+10</td>\n",
       "      <td>5.264283e+08</td>\n",
       "      <td>2.303642e+11</td>\n",
       "      <td>7.741443e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.505800e+09</td>\n",
       "      <td>5.758343e+13</td>\n",
       "      <td>2.563367e+10</td>\n",
       "      <td>1.405696e+10</td>\n",
       "      <td>5.291950e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>26528741.0</td>\n",
       "      <td>2947314.0</td>\n",
       "      <td>34811059.0</td>\n",
       "      <td>85616.0</td>\n",
       "      <td>19842251.0</td>\n",
       "      <td>85350.0</td>\n",
       "      <td>336886468.0</td>\n",
       "      <td>40381860.0</td>\n",
       "      <td>2975029.0</td>\n",
       "      <td>101342.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.793403e+10</td>\n",
       "      <td>6.079586e+08</td>\n",
       "      <td>3.156002e+11</td>\n",
       "      <td>9.913030e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.673500e+09</td>\n",
       "      <td>6.312856e+13</td>\n",
       "      <td>3.039720e+10</td>\n",
       "      <td>1.791086e+10</td>\n",
       "      <td>4.415703e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>27207291.0</td>\n",
       "      <td>2927519.0</td>\n",
       "      <td>35401790.0</td>\n",
       "      <td>85474.0</td>\n",
       "      <td>20520103.0</td>\n",
       "      <td>86300.0</td>\n",
       "      <td>345054176.0</td>\n",
       "      <td>40798641.0</td>\n",
       "      <td>2966108.0</td>\n",
       "      <td>101416.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.281683e+10</td>\n",
       "      <td>6.100666e+08</td>\n",
       "      <td>3.294190e+11</td>\n",
       "      <td>1.060146e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.268200e+09</td>\n",
       "      <td>5.983553e+13</td>\n",
       "      <td>2.845950e+10</td>\n",
       "      <td>1.532834e+10</td>\n",
       "      <td>8.157077e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>27962207.0</td>\n",
       "      <td>2913021.0</td>\n",
       "      <td>36036159.0</td>\n",
       "      <td>84419.0</td>\n",
       "      <td>21219954.0</td>\n",
       "      <td>87233.0</td>\n",
       "      <td>353112237.0</td>\n",
       "      <td>41222875.0</td>\n",
       "      <td>2963496.0</td>\n",
       "      <td>101597.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.933277e+10</td>\n",
       "      <td>7.008043e+08</td>\n",
       "      <td>3.938015e+11</td>\n",
       "      <td>1.159317e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.913100e+09</td>\n",
       "      <td>6.564782e+13</td>\n",
       "      <td>3.090675e+10</td>\n",
       "      <td>2.026555e+10</td>\n",
       "      <td>9.422161e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>28809167.0</td>\n",
       "      <td>2904780.0</td>\n",
       "      <td>36717132.0</td>\n",
       "      <td>82326.0</td>\n",
       "      <td>21942296.0</td>\n",
       "      <td>88152.0</td>\n",
       "      <td>361031820.0</td>\n",
       "      <td>41655616.0</td>\n",
       "      <td>2967984.0</td>\n",
       "      <td>101936.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.532432e+10</td>\n",
       "      <td>7.921497e+08</td>\n",
       "      <td>3.164822e+11</td>\n",
       "      <td>1.355395e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.045985e+10</td>\n",
       "      <td>7.284314e+13</td>\n",
       "      <td>3.107886e+10</td>\n",
       "      <td>2.345952e+10</td>\n",
       "      <td>1.095623e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>29726803.0</td>\n",
       "      <td>2900247.0</td>\n",
       "      <td>37439427.0</td>\n",
       "      <td>79316.0</td>\n",
       "      <td>22685632.0</td>\n",
       "      <td>89069.0</td>\n",
       "      <td>368802611.0</td>\n",
       "      <td>42095224.0</td>\n",
       "      <td>2978339.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5.118344e+10</td>\n",
       "      <td>7.817029e+08</td>\n",
       "      <td>3.812862e+11</td>\n",
       "      <td>1.558200e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.127940e+10</td>\n",
       "      <td>7.442836e+13</td>\n",
       "      <td>3.207477e+10</td>\n",
       "      <td>2.550306e+10</td>\n",
       "      <td>1.239272e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>30682500.0</td>\n",
       "      <td>2896652.0</td>\n",
       "      <td>38186135.0</td>\n",
       "      <td>75902.0</td>\n",
       "      <td>23448202.0</td>\n",
       "      <td>89985.0</td>\n",
       "      <td>376504253.0</td>\n",
       "      <td>42538304.0</td>\n",
       "      <td>2992192.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5.679566e+10</td>\n",
       "      <td>8.017876e+08</td>\n",
       "      <td>3.713366e+11</td>\n",
       "      <td>1.712220e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.247600e+10</td>\n",
       "      <td>7.643132e+13</td>\n",
       "      <td>3.595450e+10</td>\n",
       "      <td>2.804552e+10</td>\n",
       "      <td>1.349023e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>31627506.0</td>\n",
       "      <td>2893654.0</td>\n",
       "      <td>38934334.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24227524.0</td>\n",
       "      <td>90900.0</td>\n",
       "      <td>384222592.0</td>\n",
       "      <td>42980026.0</td>\n",
       "      <td>3006154.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.313285e+10</td>\n",
       "      <td>8.149546e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.862047e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.271560e+10</td>\n",
       "      <td>7.810634e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.713464e+10</td>\n",
       "      <td>1.419691e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>32526562.0</td>\n",
       "      <td>2889167.0</td>\n",
       "      <td>39666519.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25021974.0</td>\n",
       "      <td>91818.0</td>\n",
       "      <td>392022276.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3017712.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.673280e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.935994e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.267740e+10</td>\n",
       "      <td>7.343364e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.120156e+10</td>\n",
       "      <td>1.389294e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>56 rows × 504 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Population                                              \\\n",
       "country Afghanistan    Albania     Algeria  Andorra      Angola   \n",
       "year                                                              \n",
       "1960      8994793.0        NaN  11124892.0      NaN         NaN   \n",
       "1961      9164945.0        NaN  11404859.0      NaN         NaN   \n",
       "1962      9343772.0        NaN  11690152.0      NaN         NaN   \n",
       "1963      9531555.0        NaN  11985130.0      NaN         NaN   \n",
       "1964      9728645.0        NaN  12295973.0      NaN         NaN   \n",
       "1965      9935358.0        NaN  12626953.0      NaN         NaN   \n",
       "1966     10148841.0        NaN  12980269.0      NaN         NaN   \n",
       "1967     10368600.0        NaN  13354197.0      NaN         NaN   \n",
       "1968     10599790.0        NaN  13744383.0      NaN         NaN   \n",
       "1969     10849510.0        NaN  14144437.0      NaN         NaN   \n",
       "1970     11121097.0        NaN  14550033.0  24279.0         NaN   \n",
       "1971     11412821.0        NaN  14960111.0  25560.0         NaN   \n",
       "1972     11716896.0        NaN  15377095.0  26892.0         NaN   \n",
       "1973     12022514.0        NaN  15804428.0  28231.0         NaN   \n",
       "1974     12315553.0        NaN  16247113.0  29514.0         NaN   \n",
       "1975     12582954.0        NaN  16709098.0  30706.0         NaN   \n",
       "1976     12831361.0        NaN  17190236.0  31781.0         NaN   \n",
       "1977     13056499.0        NaN  17690184.0  32769.0         NaN   \n",
       "1978     13222547.0        NaN  18212331.0  33746.0         NaN   \n",
       "1979     13283279.0        NaN  18760761.0  34819.0         NaN   \n",
       "1980     13211412.0        NaN  19337723.0  36063.0         NaN   \n",
       "1981     12996923.0        NaN  19943667.0  37502.0         NaN   \n",
       "1982            NaN        NaN  20575701.0  39112.0         NaN   \n",
       "1983            NaN        NaN  21228288.0  40862.0         NaN   \n",
       "1984            NaN  2904429.0  21893857.0  42704.0         NaN   \n",
       "1985            NaN  2964762.0  22565908.0  44597.0   9745209.0   \n",
       "1986            NaN  3022635.0  23241276.0  46515.0  10023700.0   \n",
       "1987            NaN  3083605.0  23917889.0  48458.0  10285712.0   \n",
       "1988            NaN  3142336.0  24591493.0  50431.0  10544904.0   \n",
       "1989            NaN  3227943.0  25257671.0  52449.0  10820992.0   \n",
       "1990            NaN  3286542.0  25912364.0  54511.0  11127870.0   \n",
       "1991            NaN  3266790.0  26554277.0  56674.0  11472173.0   \n",
       "1992            NaN  3247039.0  27180921.0  58904.0  11848971.0   \n",
       "1993            NaN  3227287.0  27785977.0  61003.0  12246786.0   \n",
       "1994            NaN  3207536.0  28362015.0  62707.0  12648483.0   \n",
       "1995            NaN  3187784.0  28904300.0  63854.0  13042666.0   \n",
       "1996            NaN  3168033.0  29411839.0  64291.0  13424813.0   \n",
       "1997            NaN  3148281.0  29887717.0  64147.0  13801868.0   \n",
       "1998            NaN  3128530.0  30336880.0  63888.0  14187710.0   \n",
       "1999            NaN  3108778.0  30766551.0  64161.0  14601983.0   \n",
       "2000            NaN  3089027.0  31183658.0  65399.0  15058638.0   \n",
       "2001     20531160.0  3060173.0  31590320.0  67770.0  15562791.0   \n",
       "2002     21487079.0  3051010.0  31990387.0  71046.0  16109696.0   \n",
       "2003     22507368.0  3039616.0  32394886.0  74783.0  16691395.0   \n",
       "2004     23499850.0  3026939.0  32817225.0  78337.0  17295500.0   \n",
       "2005     24399948.0  3011487.0  33267887.0  81223.0  17912942.0   \n",
       "2006     25183615.0  2992547.0  33749328.0  83373.0  18541467.0   \n",
       "2007     25877544.0  2970017.0  34261971.0  84878.0  19183907.0   \n",
       "2008     26528741.0  2947314.0  34811059.0  85616.0  19842251.0   \n",
       "2009     27207291.0  2927519.0  35401790.0  85474.0  20520103.0   \n",
       "2010     27962207.0  2913021.0  36036159.0  84419.0  21219954.0   \n",
       "2011     28809167.0  2904780.0  36717132.0  82326.0  21942296.0   \n",
       "2012     29726803.0  2900247.0  37439427.0  79316.0  22685632.0   \n",
       "2013     30682500.0  2896652.0  38186135.0  75902.0  23448202.0   \n",
       "2014     31627506.0  2893654.0  38934334.0      NaN  24227524.0   \n",
       "2015     32526562.0  2889167.0  39666519.0      NaN  25021974.0   \n",
       "\n",
       "                                                                           \\\n",
       "country Antigua and Barbuda   Arab World   Argentina    Armenia     Aruba   \n",
       "year                                                                        \n",
       "1960                    NaN          NaN         NaN        NaN       NaN   \n",
       "1961                    NaN          NaN         NaN        NaN       NaN   \n",
       "1962                    NaN          NaN  21287682.0        NaN       NaN   \n",
       "1963                    NaN          NaN  21621845.0        NaN       NaN   \n",
       "1964                    NaN          NaN  21953926.0        NaN       NaN   \n",
       "1965                    NaN          NaN  22283389.0        NaN       NaN   \n",
       "1966                    NaN          NaN  22608747.0        NaN       NaN   \n",
       "1967                    NaN          NaN  22932201.0        NaN       NaN   \n",
       "1968                    NaN  115557094.0  23261273.0        NaN       NaN   \n",
       "1969                    NaN  118823872.0  23605992.0        NaN       NaN   \n",
       "1970                    NaN  122128175.0  23973062.0        NaN       NaN   \n",
       "1971                    NaN  125439089.0  24366442.0        NaN       NaN   \n",
       "1972                    NaN  128801209.0  24782950.0        NaN       NaN   \n",
       "1973                    NaN  132298955.0  25213388.0        NaN       NaN   \n",
       "1974                    NaN  136044481.0  25644505.0        NaN       NaN   \n",
       "1975                    NaN  140114424.0  26066975.0        NaN       NaN   \n",
       "1976                    NaN  144542039.0  26477153.0        NaN       NaN   \n",
       "1977                70223.0  149296257.0  26878567.0        NaN       NaN   \n",
       "1978                70508.0  154303887.0  27277742.0        NaN       NaN   \n",
       "1979                70553.0  159455867.0  27684530.0        NaN       NaN   \n",
       "1980                70301.0  164670713.0  28105889.0        NaN       NaN   \n",
       "1981                69750.0  169926632.0  28543366.0        NaN       NaN   \n",
       "1982                68950.0  175237742.0  28993989.0        NaN       NaN   \n",
       "1983                67958.0  180606318.0  29454739.0        NaN       NaN   \n",
       "1984                66863.0  186005735.0  29920907.0        NaN       NaN   \n",
       "1985                65744.0  191564251.0  30388781.0        NaN       NaN   \n",
       "1986                64605.0  197202142.0  30857242.0        NaN       NaN   \n",
       "1987                63484.0  202851923.0  31326473.0        NaN       NaN   \n",
       "1988                62538.0  208546282.0  31795515.0        NaN       NaN   \n",
       "1989                61967.0  214250542.0  32263559.0        NaN       NaN   \n",
       "1990                61906.0  222117305.0  32729740.0  3544695.0       NaN   \n",
       "1991                62412.0  228171034.0  33193920.0  3511912.0       NaN   \n",
       "1992                63434.0  232417246.0  33655149.0  3449497.0       NaN   \n",
       "1993                64868.0  238628852.0  34110912.0  3369673.0       NaN   \n",
       "1994                66550.0  244893420.0  34558114.0  3289943.0   76700.0   \n",
       "1995                68349.0  252591048.0  34994818.0  3223173.0   80326.0   \n",
       "1996                70245.0  258423164.0  35419683.0  3173425.0   83195.0   \n",
       "1997                72232.0  264153948.0  35833965.0  3137652.0   85447.0   \n",
       "1998                74206.0  269795252.0  36241578.0  3112958.0   87276.0   \n",
       "1999                76041.0  275503565.0  36648054.0  3093820.0   89004.0   \n",
       "2000                77648.0  281326250.0  37057453.0  3076098.0   90858.0   \n",
       "2001                78972.0  287291826.0  37471535.0  3060036.0   92894.0   \n",
       "2002                80030.0  293402563.0  37889443.0  3047249.0   94995.0   \n",
       "2003                80904.0  299731956.0  38309475.0  3036420.0   97015.0   \n",
       "2004                81718.0  306387415.0  38728778.0  3025982.0   98742.0   \n",
       "2005                82565.0  313430911.0  39145491.0  3014917.0  100031.0   \n",
       "2006                83467.0  320906736.0  39558750.0  3002161.0  100830.0   \n",
       "2007                84397.0  328766559.0  39969903.0  2988117.0  101218.0   \n",
       "2008                85350.0  336886468.0  40381860.0  2975029.0  101342.0   \n",
       "2009                86300.0  345054176.0  40798641.0  2966108.0  101416.0   \n",
       "2010                87233.0  353112237.0  41222875.0  2963496.0  101597.0   \n",
       "2011                88152.0  361031820.0  41655616.0  2967984.0  101936.0   \n",
       "2012                89069.0  368802611.0  42095224.0  2978339.0       NaN   \n",
       "2013                89985.0  376504253.0  42538304.0  2992192.0       NaN   \n",
       "2014                90900.0  384222592.0  42980026.0  3006154.0       NaN   \n",
       "2015                91818.0  392022276.0         NaN  3017712.0       NaN   \n",
       "\n",
       "         ...           GDP                                            \\\n",
       "country  ...    Uzbekistan       Vanuatu Venezuela, RB       Vietnam   \n",
       "year     ...                                                           \n",
       "1960     ...           NaN           NaN  8.607600e+09           NaN   \n",
       "1961     ...           NaN           NaN  8.923367e+09           NaN   \n",
       "1962     ...           NaN           NaN  9.873398e+09           NaN   \n",
       "1963     ...           NaN           NaN  1.066338e+10           NaN   \n",
       "1964     ...           NaN           NaN  9.113581e+09           NaN   \n",
       "1965     ...           NaN           NaN  9.602945e+09           NaN   \n",
       "1966     ...           NaN           NaN  1.009657e+10           NaN   \n",
       "1967     ...           NaN           NaN  1.047278e+10           NaN   \n",
       "1968     ...           NaN           NaN  1.147091e+10           NaN   \n",
       "1969     ...           NaN           NaN  1.192757e+10           NaN   \n",
       "1970     ...           NaN           NaN  1.299312e+10           NaN   \n",
       "1971     ...           NaN           NaN  1.447156e+10           NaN   \n",
       "1972     ...           NaN           NaN  1.592287e+10           NaN   \n",
       "1973     ...           NaN           NaN  1.944593e+10           NaN   \n",
       "1974     ...           NaN           NaN  2.908710e+10           NaN   \n",
       "1975     ...           NaN           NaN  3.141316e+10           NaN   \n",
       "1976     ...           NaN           NaN  3.627232e+10           NaN   \n",
       "1977     ...           NaN           NaN  4.233706e+10           NaN   \n",
       "1978     ...           NaN           NaN  4.650764e+10           NaN   \n",
       "1979     ...           NaN  1.192588e+08  5.575055e+10           NaN   \n",
       "1980     ...           NaN  1.134232e+08  6.713512e+10           NaN   \n",
       "1981     ...           NaN  9.874641e+07  7.549883e+10           NaN   \n",
       "1982     ...           NaN  9.814464e+07  7.669365e+10           NaN   \n",
       "1983     ...           NaN  1.101238e+08  7.858650e+10           NaN   \n",
       "1984     ...           NaN  1.355538e+08  5.595234e+10           NaN   \n",
       "1985     ...           NaN  1.236985e+08  5.793574e+10  1.409469e+10   \n",
       "1986     ...           NaN  1.186914e+08  5.891511e+10  2.633662e+10   \n",
       "1987     ...           NaN  1.308341e+08  4.534379e+10  3.665811e+10   \n",
       "1988     ...           NaN  1.485454e+08  5.842840e+10  2.542381e+10   \n",
       "1989     ...           NaN  1.444822e+08  4.214230e+10  6.293305e+09   \n",
       "1990     ...  1.336061e+10  1.583974e+08  4.702751e+10  6.471740e+09   \n",
       "1991     ...  1.367762e+10  1.888700e+08  5.173436e+10  9.613370e+09   \n",
       "1992     ...  1.294130e+10  1.961426e+08  5.847036e+10  9.866990e+09   \n",
       "1993     ...  1.309901e+10  1.880804e+08  5.810756e+10  1.318095e+10   \n",
       "1994     ...  1.289916e+10  2.192603e+08  5.652990e+10  1.628643e+10   \n",
       "1995     ...  1.335047e+10  2.339021e+08  7.488874e+10  2.073616e+10   \n",
       "1996     ...  1.394889e+10  2.451776e+08  6.825859e+10  2.465747e+10   \n",
       "1997     ...  1.474460e+10  2.558902e+08  8.583739e+10  2.684370e+10   \n",
       "1998     ...  1.498897e+10  2.623013e+08  9.133854e+10  2.720960e+10   \n",
       "1999     ...  1.707847e+10  2.679992e+08  9.797414e+10  2.868366e+10   \n",
       "2000     ...  1.376037e+10  2.720147e+08  1.171476e+11  3.364009e+10   \n",
       "2001     ...  1.140135e+10  2.579269e+08  1.229097e+11  3.529135e+10   \n",
       "2002     ...  9.687951e+09  2.626038e+08  9.288959e+10  3.794790e+10   \n",
       "2003     ...  1.012811e+10  3.144631e+08  8.362219e+10  4.271707e+10   \n",
       "2004     ...  1.203002e+10  3.649969e+08  1.124514e+11  4.942411e+10   \n",
       "2005     ...  1.430751e+10  3.949626e+08  1.455135e+11  5.763326e+10   \n",
       "2006     ...  1.703090e+10  4.393768e+08  1.834775e+11  6.637166e+10   \n",
       "2007     ...  2.231139e+10  5.264283e+08  2.303642e+11  7.741443e+10   \n",
       "2008     ...  2.793403e+10  6.079586e+08  3.156002e+11  9.913030e+10   \n",
       "2009     ...  3.281683e+10  6.100666e+08  3.294190e+11  1.060146e+11   \n",
       "2010     ...  3.933277e+10  7.008043e+08  3.938015e+11  1.159317e+11   \n",
       "2011     ...  4.532432e+10  7.921497e+08  3.164822e+11  1.355395e+11   \n",
       "2012     ...  5.118344e+10  7.817029e+08  3.812862e+11  1.558200e+11   \n",
       "2013     ...  5.679566e+10  8.017876e+08  3.713366e+11  1.712220e+11   \n",
       "2014     ...  6.313285e+10  8.149546e+08           NaN  1.862047e+11   \n",
       "2015     ...  6.673280e+10           NaN           NaN  1.935994e+11   \n",
       "\n",
       "                                                                              \\\n",
       "country Virgin Islands (U.S.) West Bank and Gaza         World   Yemen, Rep.   \n",
       "year                                                                           \n",
       "1960             2.420000e+07                NaN  1.364643e+12           NaN   \n",
       "1961             2.570000e+07                NaN  1.420440e+12           NaN   \n",
       "1962             3.690000e+07                NaN  1.524573e+12           NaN   \n",
       "1963             4.140000e+07                NaN  1.638187e+12           NaN   \n",
       "1964             5.380000e+07                NaN  1.799675e+12           NaN   \n",
       "1965             6.650000e+07                NaN  1.959900e+12           NaN   \n",
       "1966             8.410000e+07                NaN  2.125397e+12           NaN   \n",
       "1967             1.154000e+08                NaN  2.262923e+12           NaN   \n",
       "1968             1.738000e+08                NaN  2.440549e+12           NaN   \n",
       "1969             2.113000e+08                NaN  2.686747e+12           NaN   \n",
       "1970             2.190000e+08                NaN  2.950656e+12           NaN   \n",
       "1971             2.570000e+08                NaN  3.259057e+12           NaN   \n",
       "1972             3.071000e+08                NaN  3.757853e+12           NaN   \n",
       "1973             3.516000e+08                NaN  4.578523e+12           NaN   \n",
       "1974             3.954000e+08                NaN  5.279355e+12           NaN   \n",
       "1975             3.998000e+08                NaN  5.880305e+12           NaN   \n",
       "1976             4.400000e+08                NaN  6.400883e+12           NaN   \n",
       "1977             4.618000e+08                NaN  7.237905e+12           NaN   \n",
       "1978             5.129000e+08                NaN  8.521725e+12           NaN   \n",
       "1979             6.067000e+08                NaN  9.903841e+12           NaN   \n",
       "1980             7.278000e+08                NaN  1.115409e+13           NaN   \n",
       "1981             8.218000e+08                NaN  1.144748e+13           NaN   \n",
       "1982             8.326000e+08                NaN  1.134460e+13           NaN   \n",
       "1983             9.169000e+08                NaN  1.160740e+13           NaN   \n",
       "1984             9.854000e+08                NaN  1.204953e+13           NaN   \n",
       "1985             9.904000e+08                NaN  1.267287e+13           NaN   \n",
       "1986             1.035600e+09                NaN  1.499712e+13           NaN   \n",
       "1987             1.147800e+09                NaN  1.706395e+13           NaN   \n",
       "1988             1.204600e+09                NaN  1.910918e+13           NaN   \n",
       "1989             1.343900e+09                NaN  2.006077e+13           NaN   \n",
       "1990             1.564700e+09                NaN  2.256312e+13  5.647252e+09   \n",
       "1991             1.671200e+09                NaN  2.389846e+13  5.930370e+09   \n",
       "1992             1.770900e+09                NaN  2.537482e+13  6.463650e+09   \n",
       "1993             1.996000e+09                NaN  2.580571e+13  5.368271e+09   \n",
       "1994                      NaN       2.843300e+09  2.770637e+13  4.167356e+09   \n",
       "1995                      NaN       3.282800e+09  3.065894e+13  4.258789e+09   \n",
       "1996                      NaN       3.409600e+09  3.132499e+13  5.785685e+09   \n",
       "1997                      NaN       3.759800e+09  3.124076e+13  6.839039e+09   \n",
       "1998                      NaN       4.067800e+09  3.112270e+13  6.325220e+09   \n",
       "1999                      NaN       4.271200e+09  3.228297e+13  7.641101e+09   \n",
       "2000                      NaN       4.313600e+09  3.332130e+13  9.636342e+09   \n",
       "2001                      NaN       4.003700e+09  3.313421e+13  9.854042e+09   \n",
       "2002                      NaN       3.555800e+09  3.441805e+13  1.069328e+10   \n",
       "2003                      NaN       3.968000e+09  3.865630e+13  1.177777e+10   \n",
       "2004                      NaN       4.329200e+09  4.355213e+13  1.387350e+10   \n",
       "2005                      NaN       4.831800e+09  4.714259e+13  1.675377e+10   \n",
       "2006                      NaN       4.910100e+09  5.107451e+13  1.908173e+10   \n",
       "2007                      NaN       5.505800e+09  5.758343e+13  2.563367e+10   \n",
       "2008                      NaN       6.673500e+09  6.312856e+13  3.039720e+10   \n",
       "2009                      NaN       7.268200e+09  5.983553e+13  2.845950e+10   \n",
       "2010                      NaN       8.913100e+09  6.564782e+13  3.090675e+10   \n",
       "2011                      NaN       1.045985e+10  7.284314e+13  3.107886e+10   \n",
       "2012                      NaN       1.127940e+10  7.442836e+13  3.207477e+10   \n",
       "2013                      NaN       1.247600e+10  7.643132e+13  3.595450e+10   \n",
       "2014                      NaN       1.271560e+10  7.810634e+13           NaN   \n",
       "2015                      NaN       1.267740e+10  7.343364e+13           NaN   \n",
       "\n",
       "                                     \n",
       "country        Zambia      Zimbabwe  \n",
       "year                                 \n",
       "1960     6.987397e+08  1.052990e+09  \n",
       "1961     6.823597e+08  1.096647e+09  \n",
       "1962     6.792797e+08  1.117602e+09  \n",
       "1963     7.043397e+08  1.159512e+09  \n",
       "1964     8.226397e+08  1.217138e+09  \n",
       "1965     1.061200e+09  1.311436e+09  \n",
       "1966     1.239000e+09  1.281750e+09  \n",
       "1967     1.340639e+09  1.397002e+09  \n",
       "1968     1.573739e+09  1.479600e+09  \n",
       "1969     1.926399e+09  1.747999e+09  \n",
       "1970     1.788779e+09  1.884206e+09  \n",
       "1971     1.653259e+09  2.178716e+09  \n",
       "1972     1.872417e+09  2.677729e+09  \n",
       "1973     2.434255e+09  3.309354e+09  \n",
       "1974     2.910981e+09  3.982161e+09  \n",
       "1975     2.442672e+09  4.371301e+09  \n",
       "1976     2.742859e+09  4.318372e+09  \n",
       "1977     2.515297e+09  4.364382e+09  \n",
       "1978     2.811032e+09  4.351600e+09  \n",
       "1979     3.353445e+09  5.177459e+09  \n",
       "1980     3.884531e+09  6.678868e+09  \n",
       "1981     4.008126e+09  8.011374e+09  \n",
       "1982     3.871117e+09  8.539701e+09  \n",
       "1983     3.321048e+09  7.764067e+09  \n",
       "1984     2.719519e+09  6.352126e+09  \n",
       "1985     2.252455e+09  5.637259e+09  \n",
       "1986     1.664414e+09  6.217524e+09  \n",
       "1987     2.265251e+09  6.741215e+09  \n",
       "1988     3.728878e+09  7.814784e+09  \n",
       "1989     3.994673e+09  8.286323e+09  \n",
       "1990     3.288382e+09  8.783817e+09  \n",
       "1991     3.378882e+09  8.641482e+09  \n",
       "1992     3.181922e+09  6.751472e+09  \n",
       "1993     3.273238e+09  6.563813e+09  \n",
       "1994     3.656648e+09  6.890675e+09  \n",
       "1995     3.807067e+09  7.111271e+09  \n",
       "1996     3.597221e+09  8.553147e+09  \n",
       "1997     4.303282e+09  8.529572e+09  \n",
       "1998     3.537683e+09  6.401968e+09  \n",
       "1999     3.404312e+09  6.858013e+09  \n",
       "2000     3.600683e+09  6.689958e+09  \n",
       "2001     4.094481e+09  6.777385e+09  \n",
       "2002     4.193846e+09  6.342116e+09  \n",
       "2003     4.901840e+09  5.727592e+09  \n",
       "2004     6.221078e+09  5.805598e+09  \n",
       "2005     8.331870e+09  5.755215e+09  \n",
       "2006     1.275686e+10  5.443896e+09  \n",
       "2007     1.405696e+10  5.291950e+09  \n",
       "2008     1.791086e+10  4.415703e+09  \n",
       "2009     1.532834e+10  8.157077e+09  \n",
       "2010     2.026555e+10  9.422161e+09  \n",
       "2011     2.345952e+10  1.095623e+10  \n",
       "2012     2.550306e+10  1.239272e+10  \n",
       "2013     2.804552e+10  1.349023e+10  \n",
       "2014     2.713464e+10  1.419691e+10  \n",
       "2015     2.120156e+10  1.389294e+10  \n",
       "\n",
       "[56 rows x 504 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack().unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "a50af3f2",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            country      year\n",
       "Population  Afghanistan  1960    8.994793e+06\n",
       "                         1961    9.164945e+06\n",
       "                         1962    9.343772e+06\n",
       "                         1963    9.531555e+06\n",
       "                         1964    9.728645e+06\n",
       "                                     ...     \n",
       "GDP         Zimbabwe     2011    1.095623e+10\n",
       "                         2012    1.239272e+10\n",
       "                         2013    1.349023e+10\n",
       "                         2014    1.419691e+10\n",
       "                         2015    1.389294e+10\n",
       "Length: 28224, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack().unstack().unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "a5dd3f15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year  country               \n",
       "2015  Arab World  Population    3.920223e+08\n",
       "                  GDP           2.530102e+12\n",
       "2014  Arab World  Population    3.842226e+08\n",
       "dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9694dd1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>Population</th>\n",
       "      <th>GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1960</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>8.994793e+06</td>\n",
       "      <td>5.377778e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>1.112489e+07</td>\n",
       "      <td>2.723638e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>1.027648e+07</td>\n",
       "      <td>1.856759e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>7.047539e+06</td>\n",
       "      <td>6.592694e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bahamas, The</th>\n",
       "      <td>1.095260e+05</td>\n",
       "      <td>1.698023e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2015</th>\n",
       "      <th>Vietnam</th>\n",
       "      <td>9.170380e+07</td>\n",
       "      <td>1.935994e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Bank and Gaza</th>\n",
       "      <td>4.422143e+06</td>\n",
       "      <td>1.267740e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>World</th>\n",
       "      <td>7.346633e+09</td>\n",
       "      <td>7.343364e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\n",
       "      <td>1.621177e+07</td>\n",
       "      <td>2.120156e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>1.560275e+07</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",
       "year country                                       \n",
       "1960 Afghanistan         8.994793e+06  5.377778e+08\n",
       "     Algeria             1.112489e+07  2.723638e+09\n",
       "     Australia           1.027648e+07  1.856759e+10\n",
       "     Austria             7.047539e+06  6.592694e+09\n",
       "     Bahamas, The        1.095260e+05  1.698023e+08\n",
       "...                               ...           ...\n",
       "2015 Vietnam             9.170380e+07  1.935994e+11\n",
       "     West Bank and Gaza  4.422143e+06  1.267740e+10\n",
       "     World               7.346633e+09  7.343364e+13\n",
       "     Zambia              1.621177e+07  2.120156e+10\n",
       "     Zimbabwe            1.560275e+07  1.389294e+10\n",
       "\n",
       "[11211 rows x 2 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "51ca8e54",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <th>Albania</th>\n",
       "      <th>Algeria</th>\n",
       "      <th>Andorra</th>\n",
       "      <th>Angola</th>\n",
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       "      <th>West Bank and Gaza</th>\n",
       "      <th>World</th>\n",
       "      <th>Yemen, Rep.</th>\n",
       "      <th>Zambia</th>\n",
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       "      <th>year</th>\n",
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       "      <th rowspan=\"2\" valign=\"top\">1960</th>\n",
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       "      <td>8.994793e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.112489e+07</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.146845e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32000.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.607600e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24200000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.364643e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.987397e+08</td>\n",
       "      <td>1.052990e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1961</th>\n",
       "      <th>Population</th>\n",
       "      <td>9.164945e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.140486e+07</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.461684e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.076121e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.142848e+06</td>\n",
       "      <td>3.876638e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>5.488889e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.434767e+09</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.923367e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25700000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.420440e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.823597e+08</td>\n",
       "      <td>1.096647e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1962</th>\n",
       "      <th>Population</th>\n",
       "      <td>9.343772e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.169015e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.128768e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.790590e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.129064e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.240664e+06</td>\n",
       "      <td>4.006262e+06</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>2013</th>\n",
       "      <th>GDP</th>\n",
       "      <td>2.004633e+10</td>\n",
       "      <td>1.278103e+10</td>\n",
       "      <td>2.097035e+11</td>\n",
       "      <td>3.249101e+09</td>\n",
       "      <td>1.249121e+11</td>\n",
       "      <td>1.200588e+09</td>\n",
       "      <td>2.846994e+12</td>\n",
       "      <td>6.239320e+11</td>\n",
       "      <td>1.112147e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5.679566e+10</td>\n",
       "      <td>8.017876e+08</td>\n",
       "      <td>3.713366e+11</td>\n",
       "      <td>1.712220e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.247600e+10</td>\n",
       "      <td>7.643132e+13</td>\n",
       "      <td>3.595450e+10</td>\n",
       "      <td>2.804552e+10</td>\n",
       "      <td>1.349023e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2014</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.162751e+07</td>\n",
       "      <td>2.893654e+06</td>\n",
       "      <td>3.893433e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.422752e+07</td>\n",
       "      <td>9.090000e+04</td>\n",
       "      <td>3.842226e+08</td>\n",
       "      <td>4.298003e+07</td>\n",
       "      <td>3.006154e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.075770e+07</td>\n",
       "      <td>2.588830e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.072890e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.294682e+06</td>\n",
       "      <td>7.260780e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.572134e+07</td>\n",
       "      <td>1.524586e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>2.005019e+10</td>\n",
       "      <td>1.327796e+10</td>\n",
       "      <td>2.135185e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.267751e+11</td>\n",
       "      <td>1.220976e+09</td>\n",
       "      <td>2.873600e+12</td>\n",
       "      <td>5.480549e+11</td>\n",
       "      <td>1.164444e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.313285e+10</td>\n",
       "      <td>8.149546e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.862047e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.271560e+10</td>\n",
       "      <td>7.810634e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.713464e+10</td>\n",
       "      <td>1.419691e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2015</th>\n",
       "      <th>Population</th>\n",
       "      <td>3.252656e+07</td>\n",
       "      <td>2.889167e+06</td>\n",
       "      <td>3.966652e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.502197e+07</td>\n",
       "      <td>9.181800e+04</td>\n",
       "      <td>3.920223e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.017712e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.129950e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.170380e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.422143e+06</td>\n",
       "      <td>7.346633e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.621177e+07</td>\n",
       "      <td>1.560275e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP</th>\n",
       "      <td>1.919944e+10</td>\n",
       "      <td>1.145560e+10</td>\n",
       "      <td>1.668386e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.026431e+11</td>\n",
       "      <td>1.297285e+09</td>\n",
       "      <td>2.530102e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.056140e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.673280e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.935994e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.267740e+10</td>\n",
       "      <td>7.343364e+13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.120156e+10</td>\n",
       "      <td>1.389294e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>112 rows × 252 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "country           Afghanistan       Albania       Algeria       Andorra  \\\n",
       "year                                                                      \n",
       "1960 Population  8.994793e+06           NaN  1.112489e+07           NaN   \n",
       "     GDP         5.377778e+08           NaN  2.723638e+09           NaN   \n",
       "1961 Population  9.164945e+06           NaN  1.140486e+07           NaN   \n",
       "     GDP         5.488889e+08           NaN  2.434767e+09           NaN   \n",
       "1962 Population  9.343772e+06           NaN  1.169015e+07           NaN   \n",
       "...                       ...           ...           ...           ...   \n",
       "2013 GDP         2.004633e+10  1.278103e+10  2.097035e+11  3.249101e+09   \n",
       "2014 Population  3.162751e+07  2.893654e+06  3.893433e+07           NaN   \n",
       "     GDP         2.005019e+10  1.327796e+10  2.135185e+11           NaN   \n",
       "2015 Population  3.252656e+07  2.889167e+06  3.966652e+07           NaN   \n",
       "     GDP         1.919944e+10  1.145560e+10  1.668386e+11           NaN   \n",
       "\n",
       "country                Angola  Antigua and Barbuda    Arab World  \\\n",
       "year                                                               \n",
       "1960 Population           NaN                  NaN           NaN   \n",
       "     GDP                  NaN                  NaN           NaN   \n",
       "1961 Population           NaN                  NaN           NaN   \n",
       "     GDP                  NaN                  NaN           NaN   \n",
       "1962 Population           NaN                  NaN           NaN   \n",
       "...                       ...                  ...           ...   \n",
       "2013 GDP         1.249121e+11         1.200588e+09  2.846994e+12   \n",
       "2014 Population  2.422752e+07         9.090000e+04  3.842226e+08   \n",
       "     GDP         1.267751e+11         1.220976e+09  2.873600e+12   \n",
       "2015 Population  2.502197e+07         9.181800e+04  3.920223e+08   \n",
       "     GDP         1.026431e+11         1.297285e+09  2.530102e+12   \n",
       "\n",
       "country             Argentina       Armenia  Aruba  ...    Uzbekistan  \\\n",
       "year                                                ...                 \n",
       "1960 Population           NaN           NaN    NaN  ...           NaN   \n",
       "     GDP                  NaN           NaN    NaN  ...           NaN   \n",
       "1961 Population           NaN           NaN    NaN  ...           NaN   \n",
       "     GDP                  NaN           NaN    NaN  ...           NaN   \n",
       "1962 Population  2.128768e+07           NaN    NaN  ...           NaN   \n",
       "...                       ...           ...    ...  ...           ...   \n",
       "2013 GDP         6.239320e+11  1.112147e+10    NaN  ...  5.679566e+10   \n",
       "2014 Population  4.298003e+07  3.006154e+06    NaN  ...  3.075770e+07   \n",
       "     GDP         5.480549e+11  1.164444e+10    NaN  ...  6.313285e+10   \n",
       "2015 Population           NaN  3.017712e+06    NaN  ...  3.129950e+07   \n",
       "     GDP                  NaN  1.056140e+10    NaN  ...  6.673280e+10   \n",
       "\n",
       "country               Vanuatu  Venezuela, RB       Vietnam  \\\n",
       "year                                                         \n",
       "1960 Population           NaN   8.146845e+06           NaN   \n",
       "     GDP                  NaN   8.607600e+09           NaN   \n",
       "1961 Population           NaN   8.461684e+06           NaN   \n",
       "     GDP                  NaN   8.923367e+09           NaN   \n",
       "1962 Population           NaN   8.790590e+06           NaN   \n",
       "...                       ...            ...           ...   \n",
       "2013 GDP         8.017876e+08   3.713366e+11  1.712220e+11   \n",
       "2014 Population  2.588830e+05            NaN  9.072890e+07   \n",
       "     GDP         8.149546e+08            NaN  1.862047e+11   \n",
       "2015 Population           NaN            NaN  9.170380e+07   \n",
       "     GDP                  NaN            NaN  1.935994e+11   \n",
       "\n",
       "country          Virgin Islands (U.S.)  West Bank and Gaza         World  \\\n",
       "year                                                                       \n",
       "1960 Population                32000.0                 NaN  3.035056e+09   \n",
       "     GDP                    24200000.0                 NaN  1.364643e+12   \n",
       "1961 Population                34100.0                 NaN  3.076121e+09   \n",
       "     GDP                    25700000.0                 NaN  1.420440e+12   \n",
       "1962 Population                36300.0                 NaN  3.129064e+09   \n",
       "...                                ...                 ...           ...   \n",
       "2013 GDP                           NaN        1.247600e+10  7.643132e+13   \n",
       "2014 Population                    NaN        4.294682e+06  7.260780e+09   \n",
       "     GDP                           NaN        1.271560e+10  7.810634e+13   \n",
       "2015 Population                    NaN        4.422143e+06  7.346633e+09   \n",
       "     GDP                           NaN        1.267740e+10  7.343364e+13   \n",
       "\n",
       "country           Yemen, Rep.        Zambia      Zimbabwe  \n",
       "year                                                       \n",
       "1960 Population           NaN  3.049586e+06  3.752390e+06  \n",
       "     GDP                  NaN  6.987397e+08  1.052990e+09  \n",
       "1961 Population           NaN  3.142848e+06  3.876638e+06  \n",
       "     GDP                  NaN  6.823597e+08  1.096647e+09  \n",
       "1962 Population           NaN  3.240664e+06  4.006262e+06  \n",
       "...                       ...           ...           ...  \n",
       "2013 GDP         3.595450e+10  2.804552e+10  1.349023e+10  \n",
       "2014 Population           NaN  1.572134e+07  1.524586e+07  \n",
       "     GDP                  NaN  2.713464e+10  1.419691e+10  \n",
       "2015 Population           NaN  1.621177e+07  1.560275e+07  \n",
       "     GDP                  NaN  2.120156e+10  1.389294e+10  \n",
       "\n",
       "[112 rows x 252 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "6203a2cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
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       "  <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>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>...</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>Yemen, Rep.</th>\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",
       "...                              ...           ...           ...   \n",
       "Yemen, Rep. 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",
       "...                              ...           ...           ...   \n",
       "Yemen, Rep. 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",
       "...                              ...           ...           ...   \n",
       "Yemen, Rep. 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          2007  \\\n",
       "country                               ...                               \n",
       "Afghanistan Population  1.084951e+07  ...  2.518362e+07  2.587754e+07   \n",
       "            GDP         1.408889e+09  ...  7.057598e+09  9.843842e+09   \n",
       "Albania     Population           NaN  ...  2.992547e+06  2.970017e+06   \n",
       "            GDP                  NaN  ...  8.992642e+09  1.070101e+10   \n",
       "Algeria     Population  1.414444e+07  ...  3.374933e+07  3.426197e+07   \n",
       "...                              ...  ...           ...           ...   \n",
       "Yemen, Rep. GDP                  NaN  ...  1.908173e+10  2.563367e+10   \n",
       "Zambia      Population  4.047479e+06  ...  1.238151e+07  1.273868e+07   \n",
       "            GDP         1.926399e+09  ...  1.275686e+10  1.405696e+10   \n",
       "Zimbabwe    Population  5.036321e+06  ...  1.312794e+07  1.329780e+07   \n",
       "            GDP         1.747999e+09  ...  5.443896e+09  5.291950e+09   \n",
       "\n",
       "year                            2008          2009          2010  \\\n",
       "country                                                            \n",
       "Afghanistan Population  2.652874e+07  2.720729e+07  2.796221e+07   \n",
       "            GDP         1.019053e+10  1.248694e+10  1.593680e+10   \n",
       "Albania     Population  2.947314e+06  2.927519e+06  2.913021e+06   \n",
       "            GDP         1.288135e+10  1.204421e+10  1.192695e+10   \n",
       "Algeria     Population  3.481106e+07  3.540179e+07  3.603616e+07   \n",
       "...                              ...           ...           ...   \n",
       "Yemen, Rep. GDP         3.039720e+10  2.845950e+10  3.090675e+10   \n",
       "Zambia      Population  1.311458e+07  1.350785e+07  1.391744e+07   \n",
       "            GDP         1.791086e+10  1.532834e+10  2.026555e+10   \n",
       "Zimbabwe    Population  1.349546e+07  1.372100e+07  1.397390e+07   \n",
       "            GDP         4.415703e+09  8.157077e+09  9.422161e+09   \n",
       "\n",
       "year                            2011          2012          2013  \\\n",
       "country                                                            \n",
       "Afghanistan Population  2.880917e+07  2.972680e+07  3.068250e+07   \n",
       "            GDP         1.793024e+10  2.053654e+10  2.004633e+10   \n",
       "Albania     Population  2.904780e+06  2.900247e+06  2.896652e+06   \n",
       "            GDP         1.289087e+10  1.231978e+10  1.278103e+10   \n",
       "Algeria     Population  3.671713e+07  3.743943e+07  3.818614e+07   \n",
       "...                              ...           ...           ...   \n",
       "Yemen, Rep. GDP         3.107886e+10  3.207477e+10  3.595450e+10   \n",
       "Zambia      Population  1.434353e+07  1.478658e+07  1.524609e+07   \n",
       "            GDP         2.345952e+10  2.550306e+10  2.804552e+10   \n",
       "Zimbabwe    Population  1.425559e+07  1.456548e+07  1.489809e+07   \n",
       "            GDP         1.095623e+10  1.239272e+10  1.349023e+10   \n",
       "\n",
       "year                            2014          2015  \n",
       "country                                             \n",
       "Afghanistan Population  3.162751e+07  3.252656e+07  \n",
       "            GDP         2.005019e+10  1.919944e+10  \n",
       "Albania     Population  2.893654e+06  2.889167e+06  \n",
       "            GDP         1.327796e+10  1.145560e+10  \n",
       "Algeria     Population  3.893433e+07  3.966652e+07  \n",
       "...                              ...           ...  \n",
       "Yemen, Rep. GDP                  NaN           NaN  \n",
       "Zambia      Population  1.572134e+07  1.621177e+07  \n",
       "            GDP         2.713464e+10  2.120156e+10  \n",
       "Zimbabwe    Population  1.524586e+07  1.560275e+07  \n",
       "            GDP         1.419691e+10  1.389294e+10  \n",
       "\n",
       "[504 rows x 56 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "6296bd4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Population</th>\n",
       "      <th>GDP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1960</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>8.994793e+06</td>\n",
       "      <td>5.377778e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>1.112489e+07</td>\n",
       "      <td>2.723638e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>1.027648e+07</td>\n",
       "      <td>1.856759e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>7.047539e+06</td>\n",
       "      <td>6.592694e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bahamas, The</th>\n",
       "      <td>1.095260e+05</td>\n",
       "      <td>1.698023e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2015</th>\n",
       "      <th>Vietnam</th>\n",
       "      <td>9.170380e+07</td>\n",
       "      <td>1.935994e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Bank and Gaza</th>\n",
       "      <td>4.422143e+06</td>\n",
       "      <td>1.267740e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>World</th>\n",
       "      <td>7.346633e+09</td>\n",
       "      <td>7.343364e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\n",
       "      <td>1.621177e+07</td>\n",
       "      <td>2.120156e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>1.560275e+07</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",
       "year country                                       \n",
       "1960 Afghanistan         8.994793e+06  5.377778e+08\n",
       "     Algeria             1.112489e+07  2.723638e+09\n",
       "     Australia           1.027648e+07  1.856759e+10\n",
       "     Austria             7.047539e+06  6.592694e+09\n",
       "     Bahamas, The        1.095260e+05  1.698023e+08\n",
       "...                               ...           ...\n",
       "2015 Vietnam             9.170380e+07  1.935994e+11\n",
       "     West Bank and Gaza  4.422143e+06  1.267740e+10\n",
       "     World               7.346633e+09  7.343364e+13\n",
       "     Zambia              1.621177e+07  2.120156e+10\n",
       "     Zimbabwe            1.560275e+07  1.389294e+10\n",
       "\n",
       "[11211 rows x 2 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack(-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "cf6f82ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year  country               \n",
       "2015  Arab World  Population    3.920223e+08\n",
       "                  GDP           2.530102e+12\n",
       "2014  Arab World  Population    3.842226e+08\n",
       "dtype: float64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "34eda9f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>2015</th>\n",
       "      <th>2014</th>\n",
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       "      <th>1960</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>...</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</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": [
       "year                2015          2014          2013          2012  \\\n",
       "country       Arab World    Arab World    Arab World    Arab World   \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",
       "year                2011          2010          2009          2008  \\\n",
       "country       Arab World    Arab World    Arab World    Arab World   \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",
       "year                2007          2006  ...          1969          1968  \\\n",
       "country       Arab World    Arab World  ...      Zimbabwe      Zimbabwe   \n",
       "Population  3.287666e+08  3.209067e+08  ...  5.036321e+06  4.874113e+06   \n",
       "GDP         1.641666e+12  1.404190e+12  ...  1.747999e+09  1.479600e+09   \n",
       "\n",
       "year                1967          1966          1965          1964  \\\n",
       "country         Zimbabwe      Zimbabwe      Zimbabwe      Zimbabwe   \n",
       "Population  4.718612e+06  4.568320e+06  4.422132e+06  4.279561e+06   \n",
       "GDP         1.397002e+09  1.281750e+09  1.311436e+09  1.217138e+09   \n",
       "\n",
       "year                1963          1962          1961          1960  \n",
       "country         Zimbabwe      Zimbabwe      Zimbabwe      Zimbabwe  \n",
       "Population  4.140804e+06  4.006262e+06  3.876638e+06  3.752390e+06  \n",
       "GDP         1.159512e+09  1.117602e+09  1.096647e+09  1.052990e+09  \n",
       "\n",
       "[2 rows x 11211 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack(level = [0, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "1f043dc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>2014</th>\n",
       "      <th>2013</th>\n",
       "      <th>2012</th>\n",
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       "      <th>1961</th>\n",
       "      <th>1960</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>Arab World</th>\n",
       "      <th>...</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>Zimbabwe</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": [
       "year                2015          2014          2013          2012  \\\n",
       "country       Arab World    Arab World    Arab World    Arab World   \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",
       "year                2011          2010          2009          2008  \\\n",
       "country       Arab World    Arab World    Arab World    Arab World   \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",
       "year                2007          2006  ...          1969          1968  \\\n",
       "country       Arab World    Arab World  ...      Zimbabwe      Zimbabwe   \n",
       "Population  3.287666e+08  3.209067e+08  ...  5.036321e+06  4.874113e+06   \n",
       "GDP         1.641666e+12  1.404190e+12  ...  1.747999e+09  1.479600e+09   \n",
       "\n",
       "year                1967          1966          1965          1964  \\\n",
       "country         Zimbabwe      Zimbabwe      Zimbabwe      Zimbabwe   \n",
       "Population  4.718612e+06  4.568320e+06  4.422132e+06  4.279561e+06   \n",
       "GDP         1.397002e+09  1.281750e+09  1.311436e+09  1.217138e+09   \n",
       "\n",
       "year                1963          1962          1961          1960  \n",
       "country         Zimbabwe      Zimbabwe      Zimbabwe      Zimbabwe  \n",
       "Population  4.140804e+06  4.006262e+06  3.876638e+06  3.752390e+06  \n",
       "GDP         1.159512e+09  1.117602e+09  1.096647e+09  1.052990e+09  \n",
       "\n",
       "[2 rows x 11211 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world2.unstack(level = [\"year\", \"country\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46745923",
   "metadata": {},
   "source": [
    "# pivot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "74aa934b",
   "metadata": {},
   "outputs": [],
   "source": [
    "salesman = pd.read_csv(\"salesmen.csv\", parse_dates = [\"Date\"])\n",
    "salesman[\"Salesman\"] = salesman[\"Salesman\"].astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "6e79e2f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\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>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",
       "  </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"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salesman.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "88062f2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</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",
       "...          ...   ...   ...    ...     ...\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": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salesman.pivot(index = \"Date\", columns = \"Salesman\", values = \"Revenue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "5ceab966",
   "metadata": {},
   "outputs": [],
   "source": [
    "salesman2 = salesman.pivot(index = \"Date\", columns = \"Salesman\", values = \"Revenue\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce84a992",
   "metadata": {},
   "source": [
    "# pivot_table()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "64b6c08f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "foods = pd.read_csv(\"foods.csv\")\n",
    "foods.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "95335b46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Spend</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>City</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>99.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philadelphia</th>\n",
       "      <td>99.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stamford</th>\n",
       "      <td>99.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Spend\n",
       "City               \n",
       "New York      99.51\n",
       "Philadelphia  99.68\n",
       "Stamford      99.87"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "foods.pivot_table(values = \"Spend\", index = \"City\", aggfunc = \"max\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03573371",
   "metadata": {},
   "source": [
    "# pd.melt()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "c6b77c0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "sales = pd.read_csv(\"quarters.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "bc238fd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "  </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"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "a581ab52",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Salesman</th>\n",
       "      <th>Quarter</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 Quarter  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": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.melt(sales, id_vars = \"Salesman\", var_name = \"Quarter\", value_name = \"Revenue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfd1b763",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "262b8a46",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b3b628d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4f4c6342",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
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