визуализация-данных-6.11.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "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>Градусы</th>\n",
       "      <th>Влажность</th>\n",
       "      <th>Давление</th>\n",
       "      <th>Ветер (м/с)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Город</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Улан-Удэ</th>\n",
       "      <td>9°</td>\n",
       "      <td>32%</td>\n",
       "      <td>717 мм</td>\n",
       "      <td>4 м/с</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ульяновск</th>\n",
       "      <td>2°</td>\n",
       "      <td>56!%</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>4 м/с</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уссурийск</th>\n",
       "      <td>10°</td>\n",
       "      <td>59%</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>5 м/с</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уфа</th>\n",
       "      <td>1°</td>\n",
       "      <td>75%</td>\n",
       "      <td>752 мм</td>\n",
       "      <td>8 м/с</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Самара</th>\n",
       "      <td>2°</td>\n",
       "      <td>58%</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>1 м/с</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Градусы Влажность Давление Ветер (м/с)\n",
       "Город                                           \n",
       "Улан-Удэ       9°       32%   717 мм       4 м/с\n",
       "Ульяновск      2°      56!%   754 мм       4 м/с\n",
       "Уссурийск     10°       59%   754 мм       5 м/с\n",
       "Уфа            1°       75%   752 мм       8 м/с\n",
       "Самара         2°       58%   754 мм       1 м/с"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df = pd.read_csv('https://docs.google.com/spreadsheets/d/1VSZqGFuDI9ebuBdSLPcy8Gyi9085eLuLnn9Kou7Ao6U/export?gid=1385166020&format=csv', header=6, index_col=0, skipfooter=1, engine='python')\n",
    "test_df.rename(columns={'Ветер':'Ветер (м/с)'}, inplace=True)\n",
    "test_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>Градусы</th>\n",
       "      <th>Влажность</th>\n",
       "      <th>Давление</th>\n",
       "      <th>Ветер (км/x)</th>\n",
       "      <th>Ветер (м/с)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Город</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>Улан-Удэ</th>\n",
       "      <td>9°</td>\n",
       "      <td>32</td>\n",
       "      <td>717 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ульяновск</th>\n",
       "      <td>2°</td>\n",
       "      <td>56</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уссурийск</th>\n",
       "      <td>10°</td>\n",
       "      <td>59</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уфа</th>\n",
       "      <td>1°</td>\n",
       "      <td>75</td>\n",
       "      <td>752 мм</td>\n",
       "      <td>28.8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Самара</th>\n",
       "      <td>2°</td>\n",
       "      <td>58</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Санкт-Петербург</th>\n",
       "      <td>5°</td>\n",
       "      <td>96</td>\n",
       "      <td>755 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Саранск</th>\n",
       "      <td>1°</td>\n",
       "      <td>81</td>\n",
       "      <td>749 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Саратов</th>\n",
       "      <td>4°</td>\n",
       "      <td>65</td>\n",
       "      <td>753 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Севастополь</th>\n",
       "      <td>17°</td>\n",
       "      <td>66</td>\n",
       "      <td>767 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Симферополь</th>\n",
       "      <td>13°</td>\n",
       "      <td>75</td>\n",
       "      <td>752 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Смоленск</th>\n",
       "      <td>5°</td>\n",
       "      <td>96</td>\n",
       "      <td>740 мм</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сочи</th>\n",
       "      <td>14°</td>\n",
       "      <td>58</td>\n",
       "      <td>767 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ставрополь</th>\n",
       "      <td>13°</td>\n",
       "      <td>67</td>\n",
       "      <td>729 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Стерлитамак</th>\n",
       "      <td>1°</td>\n",
       "      <td>70</td>\n",
       "      <td>750 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сургут</th>\n",
       "      <td>-1°</td>\n",
       "      <td>100</td>\n",
       "      <td>743 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сыктывкар</th>\n",
       "      <td>-3°</td>\n",
       "      <td>74</td>\n",
       "      <td>749 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Нижний Тагил</th>\n",
       "      <td>-1°</td>\n",
       "      <td>75</td>\n",
       "      <td>731 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новокузнецк</th>\n",
       "      <td>10°</td>\n",
       "      <td>85</td>\n",
       "      <td>729 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новороссийск</th>\n",
       "      <td>15°</td>\n",
       "      <td>50</td>\n",
       "      <td>768 мм</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новосибирск</th>\n",
       "      <td>10°</td>\n",
       "      <td>48</td>\n",
       "      <td>739 мм</td>\n",
       "      <td>21.6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Градусы  Влажность Давление  Ветер (км/x)  Ветер (м/с)\n",
       "Город                                                                 \n",
       "Улан-Удэ             9°         32   717 мм          14.4            4\n",
       "Ульяновск            2°         56   754 мм          14.4            4\n",
       "Уссурийск           10°         59   754 мм          18.0            5\n",
       "Уфа                  1°         75   752 мм          28.8            8\n",
       "Самара               2°         58   754 мм           3.6            1\n",
       "Санкт-Петербург      5°         96   755 мм          10.8            3\n",
       "Саранск              1°         81   749 мм          10.8            3\n",
       "Саратов              4°         65   753 мм          10.8            3\n",
       "Севастополь         17°         66   767 мм          14.4            4\n",
       "Симферополь         13°         75   752 мм          18.0            5\n",
       "Смоленск             5°         96   740 мм           7.2            2\n",
       "Сочи                14°         58   767 мм          14.4            4\n",
       "Ставрополь          13°         67   729 мм          14.4            4\n",
       "Стерлитамак          1°         70   750 мм          10.8            3\n",
       "Сургут              -1°        100   743 мм          14.4            4\n",
       "Сыктывкар           -3°         74   749 мм          10.8            3\n",
       "Нижний Тагил        -1°         75   731 мм          18.0            5\n",
       "Новокузнецк         10°         85   729 мм          18.0            5\n",
       "Новороссийск        15°         50   768 мм           7.2            2\n",
       "Новосибирск         10°         48   739 мм          21.6            6"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df['Влажность'] = test_df['Влажность'].str.replace('[!%*]', '').astype(int)\n",
    "test_df['Ветер (м/с)'] = test_df['Ветер (м/с)'].str.replace('[!(м/с)]', '').astype(int)\n",
    "test_df.insert(3, 'Ветер (км/x)', test_df['Ветер (м/с)'] * 3.6)\n",
    "test_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>Градусы</th>\n",
       "      <th>Влажность</th>\n",
       "      <th>Давление</th>\n",
       "      <th>Ветер (км/x)</th>\n",
       "      <th>Ветер (м/с)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Город</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>Улан-Удэ</th>\n",
       "      <td>9</td>\n",
       "      <td>32</td>\n",
       "      <td>717 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ульяновск</th>\n",
       "      <td>2</td>\n",
       "      <td>56</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уссурийск</th>\n",
       "      <td>10</td>\n",
       "      <td>59</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уфа</th>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "      <td>752 мм</td>\n",
       "      <td>28.8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Самара</th>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Санкт-Петербург</th>\n",
       "      <td>5</td>\n",
       "      <td>96</td>\n",
       "      <td>755 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Саранск</th>\n",
       "      <td>1</td>\n",
       "      <td>81</td>\n",
       "      <td>749 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Саратов</th>\n",
       "      <td>4</td>\n",
       "      <td>65</td>\n",
       "      <td>753 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Смоленск</th>\n",
       "      <td>5</td>\n",
       "      <td>96</td>\n",
       "      <td>740 мм</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Стерлитамак</th>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "      <td>750 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сургут</th>\n",
       "      <td>-1</td>\n",
       "      <td>100</td>\n",
       "      <td>743 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сыктывкар</th>\n",
       "      <td>-3</td>\n",
       "      <td>74</td>\n",
       "      <td>749 мм</td>\n",
       "      <td>10.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Нижний Тагил</th>\n",
       "      <td>-1</td>\n",
       "      <td>75</td>\n",
       "      <td>731 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новокузнецк</th>\n",
       "      <td>10</td>\n",
       "      <td>85</td>\n",
       "      <td>729 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новосибирск</th>\n",
       "      <td>10</td>\n",
       "      <td>48</td>\n",
       "      <td>739 мм</td>\n",
       "      <td>21.6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Градусы  Влажность Давление  Ветер (км/x)  Ветер (м/с)\n",
       "Город                                                                  \n",
       "Улан-Удэ               9         32   717 мм          14.4            4\n",
       "Ульяновск              2         56   754 мм          14.4            4\n",
       "Уссурийск             10         59   754 мм          18.0            5\n",
       "Уфа                    1         75   752 мм          28.8            8\n",
       "Самара                 2         58   754 мм           3.6            1\n",
       "Санкт-Петербург        5         96   755 мм          10.8            3\n",
       "Саранск                1         81   749 мм          10.8            3\n",
       "Саратов                4         65   753 мм          10.8            3\n",
       "Смоленск               5         96   740 мм           7.2            2\n",
       "Стерлитамак            1         70   750 мм          10.8            3\n",
       "Сургут                -1        100   743 мм          14.4            4\n",
       "Сыктывкар             -3         74   749 мм          10.8            3\n",
       "Нижний Тагил          -1         75   731 мм          18.0            5\n",
       "Новокузнецк           10         85   729 мм          18.0            5\n",
       "Новосибирск           10         48   739 мм          21.6            6"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# test_df['Градусы'] = test_df['Градусы'].str.replace('°', '').astype(int)\n",
    "test_df[~(test_df['Градусы'] > 10)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Задания:\n",
    "# 1. Скачать третий лист в таблице (ссылка на таблицу в чате) -- создать df, такой, что \n",
    "# -- город должен быть индексом\n",
    "# -- первые строки про погоду не считались\n",
    "# -- строка с городом \"Хабаровск\" (последняя) не считалась\n",
    "# -- Название колонки \"Ветер\" должно быть переименовано в Ветер (м/с)\n",
    "# 2. Удалить ° из значений колонки Градусы\n",
    "# 3. Удалить м/с и все лишние символы из значений колонки Ветер (м/с)\n",
    "# 4. Добавить колонку Ветер (км/ч) перед Ветер (м/с) и заполнить значениями\n",
    "# 5. Удалить из таблицы строки, для которых верно, что температура > 10\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Градусы</th>\n",
       "      <th>Влажность</th>\n",
       "      <th>Давление</th>\n",
       "      <th>Ветер (км/x)</th>\n",
       "      <th>Ветер (м/с)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Город</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>Улан-Удэ</th>\n",
       "      <td>9</td>\n",
       "      <td>32</td>\n",
       "      <td>717 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ульяновск</th>\n",
       "      <td>2</td>\n",
       "      <td>56</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>14.4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уссурийск</th>\n",
       "      <td>10</td>\n",
       "      <td>59</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уфа</th>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "      <td>752 мм</td>\n",
       "      <td>28.8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Самара</th>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Градусы  Влажность Давление  Ветер (км/x)  Ветер (м/с)\n",
       "Город                                                            \n",
       "Улан-Удэ         9         32   717 мм          14.4            4\n",
       "Ульяновск        2         56   754 мм          14.4            4\n",
       "Уссурийск       10         59   754 мм          18.0            5\n",
       "Уфа              1         75   752 мм          28.8            8\n",
       "Самара           2         58   754 мм           3.6            1"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Градусы</th>\n",
       "      <th>Влажность</th>\n",
       "      <th>Давление</th>\n",
       "      <th>Ветер (км/x)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Город</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Улан-Удэ</th>\n",
       "      <td>9</td>\n",
       "      <td>32</td>\n",
       "      <td>717 мм</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ульяновск</th>\n",
       "      <td>2</td>\n",
       "      <td>56</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уссурийск</th>\n",
       "      <td>10</td>\n",
       "      <td>59</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Уфа</th>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "      <td>752 мм</td>\n",
       "      <td>28.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Самара</th>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>754 мм</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Санкт-Петербург</th>\n",
       "      <td>5</td>\n",
       "      <td>96</td>\n",
       "      <td>755 мм</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Саранск</th>\n",
       "      <td>1</td>\n",
       "      <td>81</td>\n",
       "      <td>749 мм</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Саратов</th>\n",
       "      <td>4</td>\n",
       "      <td>65</td>\n",
       "      <td>753 мм</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Севастополь</th>\n",
       "      <td>17</td>\n",
       "      <td>66</td>\n",
       "      <td>767 мм</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Симферополь</th>\n",
       "      <td>13</td>\n",
       "      <td>75</td>\n",
       "      <td>752 мм</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Смоленск</th>\n",
       "      <td>5</td>\n",
       "      <td>96</td>\n",
       "      <td>740 мм</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сочи</th>\n",
       "      <td>14</td>\n",
       "      <td>58</td>\n",
       "      <td>767 мм</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ставрополь</th>\n",
       "      <td>13</td>\n",
       "      <td>67</td>\n",
       "      <td>729 мм</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Стерлитамак</th>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "      <td>750 мм</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сургут</th>\n",
       "      <td>-1</td>\n",
       "      <td>100</td>\n",
       "      <td>743 мм</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Сыктывкар</th>\n",
       "      <td>-3</td>\n",
       "      <td>74</td>\n",
       "      <td>749 мм</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Нижний Тагил</th>\n",
       "      <td>-1</td>\n",
       "      <td>75</td>\n",
       "      <td>731 мм</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новокузнецк</th>\n",
       "      <td>10</td>\n",
       "      <td>85</td>\n",
       "      <td>729 мм</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новороссийск</th>\n",
       "      <td>15</td>\n",
       "      <td>50</td>\n",
       "      <td>768 мм</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Новосибирск</th>\n",
       "      <td>10</td>\n",
       "      <td>48</td>\n",
       "      <td>739 мм</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Градусы  Влажность Давление  Ветер (км/x)\n",
       "Город                                                     \n",
       "Улан-Удэ               9         32   717 мм          14.4\n",
       "Ульяновск              2         56   754 мм          14.4\n",
       "Уссурийск             10         59   754 мм          18.0\n",
       "Уфа                    1         75   752 мм          28.8\n",
       "Самара                 2         58   754 мм           3.6\n",
       "Санкт-Петербург        5         96   755 мм          10.8\n",
       "Саранск                1         81   749 мм          10.8\n",
       "Саратов                4         65   753 мм          10.8\n",
       "Севастополь           17         66   767 мм          14.4\n",
       "Симферополь           13         75   752 мм          18.0\n",
       "Смоленск               5         96   740 мм           7.2\n",
       "Сочи                  14         58   767 мм          14.4\n",
       "Ставрополь            13         67   729 мм          14.4\n",
       "Стерлитамак            1         70   750 мм          10.8\n",
       "Сургут                -1        100   743 мм          14.4\n",
       "Сыктывкар             -3         74   749 мм          10.8\n",
       "Нижний Тагил          -1         75   731 мм          18.0\n",
       "Новокузнецк           10         85   729 мм          18.0\n",
       "Новороссийск          15         50   768 мм           7.2\n",
       "Новосибирск           10         48   739 мм          21.6"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df[['Градусы', 'Влажность']]\n",
    "test_df.iloc[[0, 2, 3]]\n",
    "test_df.loc[['Ульяновск', 'Уфа']]\n",
    "test_df.loc['Сургут':'Новороссийск':2]\n",
    "test_df.iloc[:2]\n",
    "test_df['Сургут':'Новороссийск']\n",
    "test_df.loc['Сургут':'Новороссийск', ::-1]\n",
    "test_df.iloc[:, :-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Градусы', 'Влажность', 'Давление', 'Ветер (км/x)', 'Ветер (м/с)'], dtype='object')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.index\n",
    "test_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      "text/plain": [
       "          a  key\n",
       "0  0.176776  100\n",
       "1  0.977885  101"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({'a':np.random.random(10000), 'key':range(100, 10100)})\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "989 µs ± 0 ns per loop (mean ± std. dev. of 1 run, 500 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit -n500 -r1 df[df['key'] == 10099]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.set_index(['key'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>104</th>\n",
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      ],
      "text/plain": [
       "            a\n",
       "key          \n",
       "100  0.176776\n",
       "101  0.977885\n",
       "102  0.318154\n",
       "103  0.053124\n",
       "104  0.670197"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "302 µs ± 0 ns per loop (mean ± std. dev. of 1 run, 500 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit -n500 -r1 df.loc[10099]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>0.176776</td>\n",
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       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>0.033511</td>\n",
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       "    <tr>\n",
       "      <th>10000</th>\n",
       "      <td>0.322682</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              a\n",
       "key            \n",
       "100    0.176776\n",
       "1000   0.033511\n",
       "10000  0.322682"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reindex([100, 1000, 10000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>104</td>\n",
       "      <td>0.670197</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   key         a\n",
       "0  100  0.176776\n",
       "1  101  0.977885\n",
       "2  102  0.318154\n",
       "3  103  0.053124\n",
       "4  104  0.670197"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reset_index().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas_datareader as pdr\n",
    "from pandas_datareader import wb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FrozenList([['Afghanistan', 'Albania', 'Algeria', 'American Samoa', 'Andorra', 'Angola', 'Antigua and Barbuda', 'Arab World', 'Argentina', 'Armenia', 'Aruba', 'Australia', 'Austria', 'Azerbaijan', 'Bahamas, The', 'Bahrain', 'Bangladesh', 'Barbados', 'Belarus', 'Belgium', 'Belize', 'Benin', 'Bermuda', 'Bhutan', 'Bolivia', 'Bosnia and Herzegovina', 'Botswana', 'Brazil', 'British Virgin Islands', 'Brunei Darussalam', 'Bulgaria', 'Burkina Faso', 'Burundi', 'Cabo Verde', 'Cambodia', 'Cameroon', 'Canada', 'Caribbean small states', 'Cayman Islands', 'Central African Republic', 'Central Europe and the Baltics', 'Chad', 'Channel Islands', 'Chile', 'China', 'Colombia', 'Comoros', 'Congo, Dem. Rep.', 'Congo, Rep.', 'Costa Rica', 'Cote d'Ivoire', 'Croatia', 'Cuba', 'Curacao', 'Cyprus', 'Czech Republic', 'Denmark', 'Djibouti', 'Dominica', 'Dominican Republic', 'Early-demographic dividend', 'East Asia & Pacific', 'East Asia & Pacific (IDA & IBRD countries)', 'East Asia & Pacific (excluding high income)', 'Ecuador', 'Egypt, Arab Rep.', 'El Salvador', 'Equatorial Guinea', 'Eritrea', 'Estonia', 'Eswatini', 'Ethiopia', 'Euro area', 'Europe & Central Asia', 'Europe & Central Asia (IDA & IBRD countries)', 'Europe & Central Asia (excluding high income)', 'European Union', 'Faroe Islands', 'Fiji', 'Finland', 'Fragile and conflict affected situations', 'France', 'French Polynesia', 'Gabon', 'Gambia, The', 'Georgia', 'Germany', 'Ghana', 'Gibraltar', 'Greece', 'Greenland', 'Grenada', 'Guam', 'Guatemala', 'Guinea', 'Guinea-Bissau', 'Guyana', 'Haiti', 'Heavily indebted poor countries (HIPC)', 'High income', ...], ['1980', '1981', '1982', '1983', '1984', '1985', '1986', '1987', '1988', '1989', '1990', '1991', '1992', '1993', '1994', '1995', '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015', '2016', '2017', '2018', '2019', '2020']])"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries = wb.get_countries()\n",
    "df = wb.download(indicator=\"SP.DYN.LE00.IN\", country=countries['iso2c'], start='1980', end='2020')\n",
    "df.index.levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "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>country</th>\n",
       "      <th>year</th>\n",
       "      <th>SP.DYN.LE00.IN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2019</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2018</td>\n",
       "      <td>76.152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2017</td>\n",
       "      <td>76.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2016</td>\n",
       "      <td>75.868</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year  SP.DYN.LE00.IN\n",
       "0   Aruba  2020             NaN\n",
       "1   Aruba  2019             NaN\n",
       "2   Aruba  2018          76.152\n",
       "3   Aruba  2017          76.010\n",
       "4   Aruba  2016          75.868"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reset_index(inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "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>country</th>\n",
       "      <th>year</th>\n",
       "      <th>LSp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2019</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2018</td>\n",
       "      <td>76.152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2017</td>\n",
       "      <td>76.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>2016</td>\n",
       "      <td>75.868</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year     LSp\n",
       "0   Aruba  2020     NaN\n",
       "1   Aruba  2019     NaN\n",
       "2   Aruba  2018  76.152\n",
       "3   Aruba  2017  76.010\n",
       "4   Aruba  2016  75.868"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.rename(columns={'SP.DYN.LE00.IN':'LSp'}, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>year</th>\n",
       "      <th>1980</th>\n",
       "      <th>1981</th>\n",
       "      <th>1982</th>\n",
       "      <th>1983</th>\n",
       "      <th>1984</th>\n",
       "      <th>1985</th>\n",
       "      <th>1986</th>\n",
       "      <th>1987</th>\n",
       "      <th>1988</th>\n",
       "      <th>1989</th>\n",
       "      <th>...</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>43.244</td>\n",
       "      <td>43.923</td>\n",
       "      <td>44.617</td>\n",
       "      <td>45.324</td>\n",
       "      <td>46.040</td>\n",
       "      <td>46.761</td>\n",
       "      <td>47.486</td>\n",
       "      <td>48.211</td>\n",
       "      <td>48.930</td>\n",
       "      <td>49.640</td>\n",
       "      <td>...</td>\n",
       "      <td>61.553</td>\n",
       "      <td>62.054</td>\n",
       "      <td>62.525</td>\n",
       "      <td>62.966</td>\n",
       "      <td>63.377</td>\n",
       "      <td>63.763</td>\n",
       "      <td>64.130</td>\n",
       "      <td>64.486</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>70.208</td>\n",
       "      <td>70.416</td>\n",
       "      <td>70.635</td>\n",
       "      <td>70.876</td>\n",
       "      <td>71.134</td>\n",
       "      <td>71.388</td>\n",
       "      <td>71.605</td>\n",
       "      <td>71.760</td>\n",
       "      <td>71.843</td>\n",
       "      <td>71.860</td>\n",
       "      <td>...</td>\n",
       "      <td>76.914</td>\n",
       "      <td>77.252</td>\n",
       "      <td>77.554</td>\n",
       "      <td>77.813</td>\n",
       "      <td>78.025</td>\n",
       "      <td>78.194</td>\n",
       "      <td>78.333</td>\n",
       "      <td>78.458</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>58.198</td>\n",
       "      <td>59.519</td>\n",
       "      <td>60.813</td>\n",
       "      <td>62.029</td>\n",
       "      <td>63.130</td>\n",
       "      <td>64.087</td>\n",
       "      <td>64.884</td>\n",
       "      <td>65.545</td>\n",
       "      <td>66.097</td>\n",
       "      <td>66.554</td>\n",
       "      <td>...</td>\n",
       "      <td>75.199</td>\n",
       "      <td>75.436</td>\n",
       "      <td>75.661</td>\n",
       "      <td>75.878</td>\n",
       "      <td>76.090</td>\n",
       "      <td>76.298</td>\n",
       "      <td>76.499</td>\n",
       "      <td>76.693</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "year              1980    1981    1982    1983    1984    1985    1986  \\\n",
       "country                                                                  \n",
       "Afghanistan     43.244  43.923  44.617  45.324  46.040  46.761  47.486   \n",
       "Albania         70.208  70.416  70.635  70.876  71.134  71.388  71.605   \n",
       "Algeria         58.198  59.519  60.813  62.029  63.130  64.087  64.884   \n",
       "American Samoa     NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "Andorra            NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "\n",
       "year              1987    1988    1989  ...    2011    2012    2013    2014  \\\n",
       "country                                 ...                                   \n",
       "Afghanistan     48.211  48.930  49.640  ...  61.553  62.054  62.525  62.966   \n",
       "Albania         71.760  71.843  71.860  ...  76.914  77.252  77.554  77.813   \n",
       "Algeria         65.545  66.097  66.554  ...  75.199  75.436  75.661  75.878   \n",
       "American Samoa     NaN     NaN     NaN  ...     NaN     NaN     NaN     NaN   \n",
       "Andorra            NaN     NaN     NaN  ...     NaN     NaN     NaN     NaN   \n",
       "\n",
       "year              2015    2016    2017    2018  2019  2020  \n",
       "country                                                     \n",
       "Afghanistan     63.377  63.763  64.130  64.486   NaN   NaN  \n",
       "Albania         78.025  78.194  78.333  78.458   NaN   NaN  \n",
       "Algeria         76.090  76.298  76.499  76.693   NaN   NaN  \n",
       "American Samoa     NaN     NaN     NaN     NaN   NaN   NaN  \n",
       "Andorra            NaN     NaN     NaN     NaN   NaN   NaN  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.pivot(index='country', columns='year', values='LSp')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1301"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "383"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dropna(how='all', axis=1, inplace=True)\n",
    "df.dropna(how='all', inplace=True)\n",
    "df.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>year</th>\n",
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       "    </tr>\n",
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       "      <th>country</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>43.244</td>\n",
       "      <td>43.923</td>\n",
       "      <td>44.617</td>\n",
       "      <td>45.324</td>\n",
       "      <td>46.040</td>\n",
       "      <td>46.761</td>\n",
       "      <td>47.486</td>\n",
       "      <td>48.211</td>\n",
       "      <td>48.930</td>\n",
       "      <td>49.640</td>\n",
       "      <td>...</td>\n",
       "      <td>60.484</td>\n",
       "      <td>61.028</td>\n",
       "      <td>61.553</td>\n",
       "      <td>62.054</td>\n",
       "      <td>62.525</td>\n",
       "      <td>62.966</td>\n",
       "      <td>63.377</td>\n",
       "      <td>63.763</td>\n",
       "      <td>64.130</td>\n",
       "      <td>64.486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>70.208</td>\n",
       "      <td>70.416</td>\n",
       "      <td>70.635</td>\n",
       "      <td>70.876</td>\n",
       "      <td>71.134</td>\n",
       "      <td>71.388</td>\n",
       "      <td>71.605</td>\n",
       "      <td>71.760</td>\n",
       "      <td>71.843</td>\n",
       "      <td>71.860</td>\n",
       "      <td>...</td>\n",
       "      <td>76.221</td>\n",
       "      <td>76.562</td>\n",
       "      <td>76.914</td>\n",
       "      <td>77.252</td>\n",
       "      <td>77.554</td>\n",
       "      <td>77.813</td>\n",
       "      <td>78.025</td>\n",
       "      <td>78.194</td>\n",
       "      <td>78.333</td>\n",
       "      <td>78.458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>58.198</td>\n",
       "      <td>59.519</td>\n",
       "      <td>60.813</td>\n",
       "      <td>62.029</td>\n",
       "      <td>63.130</td>\n",
       "      <td>64.087</td>\n",
       "      <td>64.884</td>\n",
       "      <td>65.545</td>\n",
       "      <td>66.097</td>\n",
       "      <td>66.554</td>\n",
       "      <td>...</td>\n",
       "      <td>74.644</td>\n",
       "      <td>74.938</td>\n",
       "      <td>75.199</td>\n",
       "      <td>75.436</td>\n",
       "      <td>75.661</td>\n",
       "      <td>75.878</td>\n",
       "      <td>76.090</td>\n",
       "      <td>76.298</td>\n",
       "      <td>76.499</td>\n",
       "      <td>76.693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>44.178</td>\n",
       "      <td>44.404</td>\n",
       "      <td>44.611</td>\n",
       "      <td>44.799</td>\n",
       "      <td>44.966</td>\n",
       "      <td>45.107</td>\n",
       "      <td>45.213</td>\n",
       "      <td>45.283</td>\n",
       "      <td>45.317</td>\n",
       "      <td>45.324</td>\n",
       "      <td>...</td>\n",
       "      <td>54.311</td>\n",
       "      <td>55.350</td>\n",
       "      <td>56.330</td>\n",
       "      <td>57.236</td>\n",
       "      <td>58.054</td>\n",
       "      <td>58.776</td>\n",
       "      <td>59.398</td>\n",
       "      <td>59.925</td>\n",
       "      <td>60.379</td>\n",
       "      <td>60.782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Antigua and Barbuda</th>\n",
       "      <td>68.482</td>\n",
       "      <td>68.818</td>\n",
       "      <td>69.156</td>\n",
       "      <td>69.491</td>\n",
       "      <td>69.820</td>\n",
       "      <td>70.137</td>\n",
       "      <td>70.440</td>\n",
       "      <td>70.728</td>\n",
       "      <td>71.004</td>\n",
       "      <td>71.267</td>\n",
       "      <td>...</td>\n",
       "      <td>75.683</td>\n",
       "      <td>75.823</td>\n",
       "      <td>75.956</td>\n",
       "      <td>76.087</td>\n",
       "      <td>76.218</td>\n",
       "      <td>76.349</td>\n",
       "      <td>76.483</td>\n",
       "      <td>76.617</td>\n",
       "      <td>76.752</td>\n",
       "      <td>76.885</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "year                   1980    1981    1982    1983    1984    1985    1986  \\\n",
       "country                                                                       \n",
       "Afghanistan          43.244  43.923  44.617  45.324  46.040  46.761  47.486   \n",
       "Albania              70.208  70.416  70.635  70.876  71.134  71.388  71.605   \n",
       "Algeria              58.198  59.519  60.813  62.029  63.130  64.087  64.884   \n",
       "Angola               44.178  44.404  44.611  44.799  44.966  45.107  45.213   \n",
       "Antigua and Barbuda  68.482  68.818  69.156  69.491  69.820  70.137  70.440   \n",
       "\n",
       "year                   1987    1988    1989  ...    2009    2010    2011  \\\n",
       "country                                      ...                           \n",
       "Afghanistan          48.211  48.930  49.640  ...  60.484  61.028  61.553   \n",
       "Albania              71.760  71.843  71.860  ...  76.221  76.562  76.914   \n",
       "Algeria              65.545  66.097  66.554  ...  74.644  74.938  75.199   \n",
       "Angola               45.283  45.317  45.324  ...  54.311  55.350  56.330   \n",
       "Antigua and Barbuda  70.728  71.004  71.267  ...  75.683  75.823  75.956   \n",
       "\n",
       "year                   2012    2013    2014    2015    2016    2017    2018  \n",
       "country                                                                      \n",
       "Afghanistan          62.054  62.525  62.966  63.377  63.763  64.130  64.486  \n",
       "Albania              77.252  77.554  77.813  78.025  78.194  78.333  78.458  \n",
       "Algeria              75.436  75.661  75.878  76.090  76.298  76.499  76.693  \n",
       "Angola               57.236  58.054  58.776  59.398  59.925  60.379  60.782  \n",
       "Antigua and Barbuda  76.087  76.218  76.349  76.483  76.617  76.752  76.885  \n",
       "\n",
       "[5 rows x 39 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "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>year</th>\n",
       "      <th>1980</th>\n",
       "      <th>1981</th>\n",
       "      <th>1982</th>\n",
       "      <th>1983</th>\n",
       "      <th>1984</th>\n",
       "      <th>1985</th>\n",
       "      <th>1986</th>\n",
       "      <th>1987</th>\n",
       "      <th>1988</th>\n",
       "      <th>1989</th>\n",
       "      <th>...</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>43.244</td>\n",
       "      <td>43.923</td>\n",
       "      <td>44.617</td>\n",
       "      <td>45.324</td>\n",
       "      <td>46.040</td>\n",
       "      <td>46.761</td>\n",
       "      <td>47.486</td>\n",
       "      <td>48.211</td>\n",
       "      <td>48.930</td>\n",
       "      <td>49.640</td>\n",
       "      <td>...</td>\n",
       "      <td>61.028</td>\n",
       "      <td>61.553</td>\n",
       "      <td>62.054</td>\n",
       "      <td>62.525</td>\n",
       "      <td>62.966</td>\n",
       "      <td>63.377</td>\n",
       "      <td>63.763</td>\n",
       "      <td>64.130</td>\n",
       "      <td>64.486</td>\n",
       "      <td>54.898359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>70.208</td>\n",
       "      <td>70.416</td>\n",
       "      <td>70.635</td>\n",
       "      <td>70.876</td>\n",
       "      <td>71.134</td>\n",
       "      <td>71.388</td>\n",
       "      <td>71.605</td>\n",
       "      <td>71.760</td>\n",
       "      <td>71.843</td>\n",
       "      <td>71.860</td>\n",
       "      <td>...</td>\n",
       "      <td>76.562</td>\n",
       "      <td>76.914</td>\n",
       "      <td>77.252</td>\n",
       "      <td>77.554</td>\n",
       "      <td>77.813</td>\n",
       "      <td>78.025</td>\n",
       "      <td>78.194</td>\n",
       "      <td>78.333</td>\n",
       "      <td>78.458</td>\n",
       "      <td>73.989103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>58.198</td>\n",
       "      <td>59.519</td>\n",
       "      <td>60.813</td>\n",
       "      <td>62.029</td>\n",
       "      <td>63.130</td>\n",
       "      <td>64.087</td>\n",
       "      <td>64.884</td>\n",
       "      <td>65.545</td>\n",
       "      <td>66.097</td>\n",
       "      <td>66.554</td>\n",
       "      <td>...</td>\n",
       "      <td>74.938</td>\n",
       "      <td>75.199</td>\n",
       "      <td>75.436</td>\n",
       "      <td>75.661</td>\n",
       "      <td>75.878</td>\n",
       "      <td>76.090</td>\n",
       "      <td>76.298</td>\n",
       "      <td>76.499</td>\n",
       "      <td>76.693</td>\n",
       "      <td>69.888513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>44.178</td>\n",
       "      <td>44.404</td>\n",
       "      <td>44.611</td>\n",
       "      <td>44.799</td>\n",
       "      <td>44.966</td>\n",
       "      <td>45.107</td>\n",
       "      <td>45.213</td>\n",
       "      <td>45.283</td>\n",
       "      <td>45.317</td>\n",
       "      <td>45.324</td>\n",
       "      <td>...</td>\n",
       "      <td>55.350</td>\n",
       "      <td>56.330</td>\n",
       "      <td>57.236</td>\n",
       "      <td>58.054</td>\n",
       "      <td>58.776</td>\n",
       "      <td>59.398</td>\n",
       "      <td>59.925</td>\n",
       "      <td>60.379</td>\n",
       "      <td>60.782</td>\n",
       "      <td>49.477872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Antigua and Barbuda</th>\n",
       "      <td>68.482</td>\n",
       "      <td>68.818</td>\n",
       "      <td>69.156</td>\n",
       "      <td>69.491</td>\n",
       "      <td>69.820</td>\n",
       "      <td>70.137</td>\n",
       "      <td>70.440</td>\n",
       "      <td>70.728</td>\n",
       "      <td>71.004</td>\n",
       "      <td>71.267</td>\n",
       "      <td>...</td>\n",
       "      <td>75.823</td>\n",
       "      <td>75.956</td>\n",
       "      <td>76.087</td>\n",
       "      <td>76.218</td>\n",
       "      <td>76.349</td>\n",
       "      <td>76.483</td>\n",
       "      <td>76.617</td>\n",
       "      <td>76.752</td>\n",
       "      <td>76.885</td>\n",
       "      <td>73.369179</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "year                   1980    1981    1982    1983    1984    1985    1986  \\\n",
       "country                                                                       \n",
       "Afghanistan          43.244  43.923  44.617  45.324  46.040  46.761  47.486   \n",
       "Albania              70.208  70.416  70.635  70.876  71.134  71.388  71.605   \n",
       "Algeria              58.198  59.519  60.813  62.029  63.130  64.087  64.884   \n",
       "Angola               44.178  44.404  44.611  44.799  44.966  45.107  45.213   \n",
       "Antigua and Barbuda  68.482  68.818  69.156  69.491  69.820  70.137  70.440   \n",
       "\n",
       "year                   1987    1988    1989  ...    2010    2011    2012  \\\n",
       "country                                      ...                           \n",
       "Afghanistan          48.211  48.930  49.640  ...  61.028  61.553  62.054   \n",
       "Albania              71.760  71.843  71.860  ...  76.562  76.914  77.252   \n",
       "Algeria              65.545  66.097  66.554  ...  74.938  75.199  75.436   \n",
       "Angola               45.283  45.317  45.324  ...  55.350  56.330  57.236   \n",
       "Antigua and Barbuda  70.728  71.004  71.267  ...  75.823  75.956  76.087   \n",
       "\n",
       "year                   2013    2014    2015    2016    2017    2018       mean  \n",
       "country                                                                         \n",
       "Afghanistan          62.525  62.966  63.377  63.763  64.130  64.486  54.898359  \n",
       "Albania              77.554  77.813  78.025  78.194  78.333  78.458  73.989103  \n",
       "Algeria              75.661  75.878  76.090  76.298  76.499  76.693  69.888513  \n",
       "Angola               58.054  58.776  59.398  59.925  60.379  60.782  49.477872  \n",
       "Antigua and Barbuda  76.218  76.349  76.483  76.617  76.752  76.885  73.369179  \n",
       "\n",
       "[5 rows x 40 columns]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['mean'] = df.mean(axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/pandas/plotting/_core.py:393: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(xticklabels)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='year'>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "years = list(map(str, range(1980, 2019)))\n",
    "Angola = df.loc['Angola', years]\n",
    "Angola.plot()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}