Panda_df_series.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d78ccb93-eb17-4bed-8be9-2ecb00e237e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e1b1b4d9-7f6d-495b-8c36-7748d519060c",
   "metadata": {},
   "outputs": [],
   "source": [
    "random_items = np.random.randint(25, size=(10)) # 随机生成0-24整数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "337b9ae5-c4f7-4596-8658-68300cfa8076",
   "metadata": {},
   "outputs": [],
   "source": [
    "series_data = pd.Series(random_items)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6531af8d-e879-4f18-9a07-3e6cbf232a9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    20\n",
       "1    13\n",
       "2     7\n",
       "3     6\n",
       "4    24\n",
       "5    22\n",
       "6     8\n",
       "7     0\n",
       "8    10\n",
       "9     9\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0a2afeb1-5447-482d-b5a8-92a6b2443c7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series_data[9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "54222e07-bdb7-4d56-9fc6-9b54f2d69b86",
   "metadata": {},
   "outputs": [],
   "source": [
    "letter_index = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i','j']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "56f0b5c3-86ea-4e77-b740-2c13a47a839e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    20\n",
       "b    13\n",
       "c     7\n",
       "d     6\n",
       "e    24\n",
       "f    22\n",
       "g     8\n",
       "h     0\n",
       "i    10\n",
       "j     9\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_series_data = pd.Series(random_items, index = letter_index)\n",
    "new_series_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3be2a8a3-8011-41b3-b1cb-857cbc1d32b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_data = {'a':1, 'b':2, 'c':3, 'd':4, 'e':5}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d98b3b98-73ff-4125-b589-f63985e0ea0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "e    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_series = pd.Series(dict_data)\n",
    "dict_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f002d83b-60a8-4727-9c5c-3af62496aeb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "e    5\n",
       "Name: first_series, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_series = pd.Series(dict_data, name='first_series')\n",
    "dict_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7818f5e1-667f-46d0-b352-a2bd32a0f798",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "e    5\n",
       "Name: rename_series, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_series.rename('rename_series')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "359af9b5-cf3c-4034-bf9c-30382b145373",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "e    5\n",
       "Name: first_series, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8c999af7-7144-4159-bddd-596502e0c519",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_series.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e0a55d07-22a1-4275-893a-fa71333e874b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "d    4\n",
       "e    5\n",
       "Name: first_series, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_series[dict_series > dict_series.median()] #获取序列中所有大于中位数的值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0a705de5-dfdb-4636-9e3b-fa63964123e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "dict = {\n",
    "    'one': [1, 2, 3, 4],\n",
    "    'two': [4, 3, 2, 1]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3a2773e0-3121-4513-b848-2d1c0338184e",
   "metadata": {},
   "outputs": [
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       "   one  two\n",
       "0    1    4\n",
       "1    2    3\n",
       "2    3    2\n",
       "3    4    1"
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   "source": [
    "dict_df = pd.DataFrame(dict)\n",
    "dict_df"
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   "execution_count": 25,
   "id": "ec46e7f4-5d9b-4a3b-b6b2-fbca33e1f574",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "3    4\n",
       "Name: one, dtype: int64"
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     "execution_count": 25,
     "metadata": {},
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    "dict_df['one']"
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   "execution_count": 26,
   "id": "0e5588ff-10f9-4009-b718-3bfa1ebf82ee",
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    {
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      "text/plain": [
       "0    4\n",
       "1    3\n",
       "2    2\n",
       "3    1\n",
       "Name: two, dtype: int64"
      ]
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     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "dict_df['two']"
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   "execution_count": 27,
   "id": "8061d4dd-5991-45f5-9414-ab1f66a8519d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
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     "execution_count": 27,
     "metadata": {},
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   "source": [
    "type(dict_df['two'])"
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   "cell_type": "code",
   "execution_count": 28,
   "id": "6a24e5d8-5539-4451-92da-53d85417d120",
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    {
     "data": {
      "text/plain": [
       "(4, 2)"
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     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "dict_df.shape"
   ]
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  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "30cbddad-7b51-485f-90bd-d6e904f8b54b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'one': a    1\n",
       " b    2\n",
       " c    3\n",
       " Name: col_one, dtype: int64,\n",
       " 'two': a    1\n",
       " b    2\n",
       " c    3\n",
       " d    4\n",
       " e    5\n",
       " Name: col_two, dtype: int64}"
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     "execution_count": 29,
     "metadata": {},
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   "source": [
    "d_data = {\n",
    "    'one': pd.Series([1, 2, 3], name='col_one', index=['a', 'b', 'c']),\n",
    "    'two': pd.Series([1, 2, 3, 4, 5], name='col_two', index=['a', 'b', 'c', 'd', 'e'])\n",
    "}\n",
    "d_data"
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   "execution_count": 30,
   "id": "f821b586-9860-41ec-987f-258afeee9d98",
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       "   one  two\n",
       "a  1.0    1\n",
       "b  2.0    2\n",
       "c  3.0    3\n",
       "d  NaN    4\n",
       "e  NaN    5"
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     "metadata": {},
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   "source": [
    "df_data = pd.DataFrame(d_data)\n",
    "df_data"
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   "id": "c139b38d-dd1d-4d5d-ad54-bcd3ae07a1a9",
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       "  index  one  two\n",
       "0     a  1.0    1\n",
       "1     b  2.0    2\n",
       "2     c  3.0    3\n",
       "3     d  NaN    4\n",
       "4     e  NaN    5"
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     "execution_count": 31,
     "metadata": {},
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   ],
   "source": [
    "new_df = df_data.reset_index() # 重新设置index\n",
    "new_df"
   ]
  },
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   "cell_type": "code",
   "execution_count": 32,
   "id": "20b2a992-5079-4e9f-8529-87fd93793969",
   "metadata": {},
   "outputs": [
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       "   one  two\n",
       "0  1.0    1\n",
       "1  2.0    2\n",
       "2  3.0    3\n",
       "3  NaN    4\n",
       "4  NaN    5"
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     "execution_count": 32,
     "metadata": {},
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   "source": [
    "new_df = df_data.reset_index(drop = True) # 重新设置index并删掉原来的index\n",
    "new_df"
   ]
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  {
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   "execution_count": 33,
   "id": "ac3f3517-0bfc-4f4e-94d4-c1c9d456311b",
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   "outputs": [
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       "   one  two\n",
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     "execution_count": 33,
     "metadata": {},
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   "execution_count": 34,
   "id": "188b6078-10e7-4356-b1c7-e12f9a6aff5e",
   "metadata": {},
   "outputs": [
    {
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       "   one  two\n",
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   "execution_count": 35,
   "id": "3e5185c2-2ec8-4bc5-8e99-76acc1912495",
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_data_path = 'https://raw.githubusercontent.com/turingplanet/pandas-intro/main/public-datasets/country_info.csv'"
   ]
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       "      <td>0,188</td>\n",
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       "      <td>13,8</td>\n",
       "      <td>0,04</td>\n",
       "      <td>-0,39</td>\n",
       "      <td>31</td>\n",
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       "      <td>70,0</td>\n",
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       "      <td>4,61</td>\n",
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       "      <td>0,298</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>57794</td>\n",
       "      <td>199</td>\n",
       "      <td>290,4</td>\n",
       "      <td>58,29</td>\n",
       "      <td>-20,71</td>\n",
       "      <td>9,27</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>97,0</td>\n",
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       "      <td>4,05</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>100,0</td>\n",
       "      <td>497,2</td>\n",
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       "      <td>0,00</td>\n",
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       "      <td>145,2</td>\n",
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       "      <td>3,92</td>\n",
       "      <td>0,09</td>\n",
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       "      <td>0,63</td>\n",
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       "      <th>223</th>\n",
       "      <td>Western Sahara</td>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>273008</td>\n",
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       "      <td>1,0</td>\n",
       "      <td>0,42</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0,02</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0,4</td>\n",
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       "    <tr>\n",
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       "      <td>Yemen</td>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>21456188</td>\n",
       "      <td>527970</td>\n",
       "      <td>40,6</td>\n",
       "      <td>0,36</td>\n",
       "      <td>0</td>\n",
       "      <td>61,5</td>\n",
       "      <td>800.0</td>\n",
       "      <td>50,2</td>\n",
       "      <td>37,2</td>\n",
       "      <td>2,78</td>\n",
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       "      <td>0,393</td>\n",
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       "      <th>225</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
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       "      <td>752614</td>\n",
       "      <td>15,3</td>\n",
       "      <td>0,00</td>\n",
       "      <td>0</td>\n",
       "      <td>88,29</td>\n",
       "      <td>800.0</td>\n",
       "      <td>80,6</td>\n",
       "      <td>8,2</td>\n",
       "      <td>7,08</td>\n",
       "      <td>0,03</td>\n",
       "      <td>92,9</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>19,93</td>\n",
       "      <td>0,22</td>\n",
       "      <td>0,29</td>\n",
       "      <td>0,489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>12236805</td>\n",
       "      <td>390580</td>\n",
       "      <td>31,3</td>\n",
       "      <td>0,00</td>\n",
       "      <td>0</td>\n",
       "      <td>67,69</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>90,7</td>\n",
       "      <td>26,8</td>\n",
       "      <td>8,32</td>\n",
       "      <td>0,34</td>\n",
       "      <td>91,34</td>\n",
       "      <td>2</td>\n",
       "      <td>28,01</td>\n",
       "      <td>21,84</td>\n",
       "      <td>0,179</td>\n",
       "      <td>0,243</td>\n",
       "      <td>0,579</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>227 rows × 20 columns</p>\n",
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      ],
      "text/plain": [
       "             Country                               Region  Population  \\\n",
       "0       Afghanistan         ASIA (EX. NEAR EAST)             31056997   \n",
       "1           Albania   EASTERN EUROPE                          3581655   \n",
       "2           Algeria   NORTHERN AFRICA                        32930091   \n",
       "3    American Samoa   OCEANIA                                   57794   \n",
       "4           Andorra   WESTERN EUROPE                            71201   \n",
       "..               ...                                  ...         ...   \n",
       "222       West Bank   NEAR EAST                               2460492   \n",
       "223  Western Sahara   NORTHERN AFRICA                          273008   \n",
       "224           Yemen   NEAR EAST                              21456188   \n",
       "225          Zambia   SUB-SAHARAN AFRICA                     11502010   \n",
       "226        Zimbabwe   SUB-SAHARAN AFRICA                     12236805   \n",
       "\n",
       "     Area (sq. mi.) Pop. Density (per sq. mi.) Coastline (coast/area ratio)  \\\n",
       "0            647500                       48,0                         0,00   \n",
       "1             28748                      124,6                         1,26   \n",
       "2           2381740                       13,8                         0,04   \n",
       "3               199                      290,4                        58,29   \n",
       "4               468                      152,1                         0,00   \n",
       "..              ...                        ...                          ...   \n",
       "222            5860                      419,9                         0,00   \n",
       "223          266000                        1,0                         0,42   \n",
       "224          527970                       40,6                         0,36   \n",
       "225          752614                       15,3                         0,00   \n",
       "226          390580                       31,3                         0,00   \n",
       "\n",
       "    Net migration Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "0           23,06                             163,07               700.0   \n",
       "1           -4,93                              21,52              4500.0   \n",
       "2           -0,39                                 31              6000.0   \n",
       "3          -20,71                               9,27              8000.0   \n",
       "4             6,6                               4,05             19000.0   \n",
       "..            ...                                ...                 ...   \n",
       "222          2,98                              19,62               800.0   \n",
       "223           NaN                                NaN                 NaN   \n",
       "224             0                               61,5               800.0   \n",
       "225             0                              88,29               800.0   \n",
       "226             0                              67,69              1900.0   \n",
       "\n",
       "    Literacy (%) Phones (per 1000) Arable (%) Crops (%) Other (%) Climate  \\\n",
       "0           36,0               3,2      12,13      0,22     87,65       1   \n",
       "1           86,5              71,2      21,09      4,42     74,49       3   \n",
       "2           70,0              78,1       3,22      0,25     96,53       1   \n",
       "3           97,0             259,5         10        15        75       2   \n",
       "4          100,0             497,2       2,22         0     97,78       3   \n",
       "..           ...               ...        ...       ...       ...     ...   \n",
       "222          NaN             145,2       16,9     18,97     64,13       3   \n",
       "223          NaN               NaN       0,02         0     99,98       1   \n",
       "224         50,2              37,2       2,78      0,24     96,98       1   \n",
       "225         80,6               8,2       7,08      0,03      92,9       2   \n",
       "226         90,7              26,8       8,32      0,34     91,34       2   \n",
       "\n",
       "    Birthrate Deathrate Agriculture Industry Service  \n",
       "0        46,6     20,34        0,38     0,24    0,38  \n",
       "1       15,11      5,22       0,232    0,188   0,579  \n",
       "2       17,14      4,61       0,101      0,6   0,298  \n",
       "3       22,46      3,27         NaN      NaN     NaN  \n",
       "4        8,71      6,25         NaN      NaN     NaN  \n",
       "..        ...       ...         ...      ...     ...  \n",
       "222     31,67      3,92        0,09     0,28    0,63  \n",
       "223       NaN       NaN         NaN      NaN     0,4  \n",
       "224     42,89       8,3       0,135    0,472   0,393  \n",
       "225        41     19,93        0,22     0,29   0,489  \n",
       "226     28,01     21,84       0,179    0,243   0,579  \n",
       "\n",
       "[227 rows x 20 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info = pd.read_csv(csv_data_path)\n",
    "cou_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "85530f44-5534-44be-8dba-85bd6bb98ef7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "(227, 20)"
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     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.shape\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "85300893-cc76-408c-869e-866c96077d2d",
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>31056997</td>\n",
       "      <td>647500</td>\n",
       "      <td>48,0</td>\n",
       "      <td>0,00</td>\n",
       "      <td>23,06</td>\n",
       "      <td>163,07</td>\n",
       "      <td>700.0</td>\n",
       "      <td>36,0</td>\n",
       "      <td>3,2</td>\n",
       "      <td>12,13</td>\n",
       "      <td>0,22</td>\n",
       "      <td>87,65</td>\n",
       "      <td>1</td>\n",
       "      <td>46,6</td>\n",
       "      <td>20,34</td>\n",
       "      <td>0,38</td>\n",
       "      <td>0,24</td>\n",
       "      <td>0,38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>3581655</td>\n",
       "      <td>28748</td>\n",
       "      <td>124,6</td>\n",
       "      <td>1,26</td>\n",
       "      <td>-4,93</td>\n",
       "      <td>21,52</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>86,5</td>\n",
       "      <td>71,2</td>\n",
       "      <td>21,09</td>\n",
       "      <td>4,42</td>\n",
       "      <td>74,49</td>\n",
       "      <td>3</td>\n",
       "      <td>15,11</td>\n",
       "      <td>5,22</td>\n",
       "      <td>0,232</td>\n",
       "      <td>0,188</td>\n",
       "      <td>0,579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>32930091</td>\n",
       "      <td>2381740</td>\n",
       "      <td>13,8</td>\n",
       "      <td>0,04</td>\n",
       "      <td>-0,39</td>\n",
       "      <td>31</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>70,0</td>\n",
       "      <td>78,1</td>\n",
       "      <td>3,22</td>\n",
       "      <td>0,25</td>\n",
       "      <td>96,53</td>\n",
       "      <td>1</td>\n",
       "      <td>17,14</td>\n",
       "      <td>4,61</td>\n",
       "      <td>0,101</td>\n",
       "      <td>0,6</td>\n",
       "      <td>0,298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>57794</td>\n",
       "      <td>199</td>\n",
       "      <td>290,4</td>\n",
       "      <td>58,29</td>\n",
       "      <td>-20,71</td>\n",
       "      <td>9,27</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>97,0</td>\n",
       "      <td>259,5</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>75</td>\n",
       "      <td>2</td>\n",
       "      <td>22,46</td>\n",
       "      <td>3,27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>71201</td>\n",
       "      <td>468</td>\n",
       "      <td>152,1</td>\n",
       "      <td>0,00</td>\n",
       "      <td>6,6</td>\n",
       "      <td>4,05</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>100,0</td>\n",
       "      <td>497,2</td>\n",
       "      <td>2,22</td>\n",
       "      <td>0</td>\n",
       "      <td>97,78</td>\n",
       "      <td>3</td>\n",
       "      <td>8,71</td>\n",
       "      <td>6,25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country                               Region  Population  \\\n",
       "0     Afghanistan         ASIA (EX. NEAR EAST)             31056997   \n",
       "1         Albania   EASTERN EUROPE                          3581655   \n",
       "2         Algeria   NORTHERN AFRICA                        32930091   \n",
       "3  American Samoa   OCEANIA                                   57794   \n",
       "4         Andorra   WESTERN EUROPE                            71201   \n",
       "\n",
       "   Area (sq. mi.) Pop. Density (per sq. mi.) Coastline (coast/area ratio)  \\\n",
       "0          647500                       48,0                         0,00   \n",
       "1           28748                      124,6                         1,26   \n",
       "2         2381740                       13,8                         0,04   \n",
       "3             199                      290,4                        58,29   \n",
       "4             468                      152,1                         0,00   \n",
       "\n",
       "  Net migration Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "0         23,06                             163,07               700.0   \n",
       "1         -4,93                              21,52              4500.0   \n",
       "2         -0,39                                 31              6000.0   \n",
       "3        -20,71                               9,27              8000.0   \n",
       "4           6,6                               4,05             19000.0   \n",
       "\n",
       "  Literacy (%) Phones (per 1000) Arable (%) Crops (%) Other (%) Climate  \\\n",
       "0         36,0               3,2      12,13      0,22     87,65       1   \n",
       "1         86,5              71,2      21,09      4,42     74,49       3   \n",
       "2         70,0              78,1       3,22      0,25     96,53       1   \n",
       "3         97,0             259,5         10        15        75       2   \n",
       "4        100,0             497,2       2,22         0     97,78       3   \n",
       "\n",
       "  Birthrate Deathrate Agriculture Industry Service  \n",
       "0      46,6     20,34        0,38     0,24    0,38  \n",
       "1     15,11      5,22       0,232    0,188   0,579  \n",
       "2     17,14      4,61       0,101      0,6   0,298  \n",
       "3     22,46      3,27         NaN      NaN     NaN  \n",
       "4      8,71      6,25         NaN      NaN     NaN  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "9be3faa2-c68a-471f-a96e-6f8a2b8079ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Country', 'Region', 'Population', 'Area (sq. mi.)',\n",
       "       'Pop. Density (per sq. mi.)', 'Coastline (coast/area ratio)',\n",
       "       'Net migration', 'Infant mortality (per 1000 births)',\n",
       "       'GDP ($ per capita)', 'Literacy (%)', 'Phones (per 1000)', 'Arable (%)',\n",
       "       'Crops (%)', 'Other (%)', 'Climate', 'Birthrate', 'Deathrate',\n",
       "       'Agriculture', 'Industry', 'Service'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "7d5105e7-0e15-40aa-8da0-db0a52a6bd21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Population</th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <th>Net migration</th>\n",
       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Literacy (%)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Arable (%)</th>\n",
       "      <th>Crops (%)</th>\n",
       "      <th>Other (%)</th>\n",
       "      <th>Climate</th>\n",
       "      <th>Birthrate</th>\n",
       "      <th>Deathrate</th>\n",
       "      <th>Agriculture</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Service</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>31056997</td>\n",
       "      <td>647500</td>\n",
       "      <td>48,0</td>\n",
       "      <td>0,00</td>\n",
       "      <td>23,06</td>\n",
       "      <td>163,07</td>\n",
       "      <td>700.0</td>\n",
       "      <td>36,0</td>\n",
       "      <td>3,2</td>\n",
       "      <td>12,13</td>\n",
       "      <td>0,22</td>\n",
       "      <td>87,65</td>\n",
       "      <td>1</td>\n",
       "      <td>46,6</td>\n",
       "      <td>20,34</td>\n",
       "      <td>0,38</td>\n",
       "      <td>0,24</td>\n",
       "      <td>0,38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>3581655</td>\n",
       "      <td>28748</td>\n",
       "      <td>124,6</td>\n",
       "      <td>1,26</td>\n",
       "      <td>-4,93</td>\n",
       "      <td>21,52</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>86,5</td>\n",
       "      <td>71,2</td>\n",
       "      <td>21,09</td>\n",
       "      <td>4,42</td>\n",
       "      <td>74,49</td>\n",
       "      <td>3</td>\n",
       "      <td>15,11</td>\n",
       "      <td>5,22</td>\n",
       "      <td>0,232</td>\n",
       "      <td>0,188</td>\n",
       "      <td>0,579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>32930091</td>\n",
       "      <td>2381740</td>\n",
       "      <td>13,8</td>\n",
       "      <td>0,04</td>\n",
       "      <td>-0,39</td>\n",
       "      <td>31</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>70,0</td>\n",
       "      <td>78,1</td>\n",
       "      <td>3,22</td>\n",
       "      <td>0,25</td>\n",
       "      <td>96,53</td>\n",
       "      <td>1</td>\n",
       "      <td>17,14</td>\n",
       "      <td>4,61</td>\n",
       "      <td>0,101</td>\n",
       "      <td>0,6</td>\n",
       "      <td>0,298</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Country                               Region  Population  \\\n",
       "0  Afghanistan         ASIA (EX. NEAR EAST)             31056997   \n",
       "1      Albania   EASTERN EUROPE                          3581655   \n",
       "2      Algeria   NORTHERN AFRICA                        32930091   \n",
       "\n",
       "   Area (sq. mi.) Pop. Density (per sq. mi.) Coastline (coast/area ratio)  \\\n",
       "0          647500                       48,0                         0,00   \n",
       "1           28748                      124,6                         1,26   \n",
       "2         2381740                       13,8                         0,04   \n",
       "\n",
       "  Net migration Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "0         23,06                             163,07               700.0   \n",
       "1         -4,93                              21,52              4500.0   \n",
       "2         -0,39                                 31              6000.0   \n",
       "\n",
       "  Literacy (%) Phones (per 1000) Arable (%) Crops (%) Other (%) Climate  \\\n",
       "0         36,0               3,2      12,13      0,22     87,65       1   \n",
       "1         86,5              71,2      21,09      4,42     74,49       3   \n",
       "2         70,0              78,1       3,22      0,25     96,53       1   \n",
       "\n",
       "  Birthrate Deathrate Agriculture Industry Service  \n",
       "0      46,6     20,34        0,38     0,24    0,38  \n",
       "1     15,11      5,22       0,232    0,188   0,579  \n",
       "2     17,14      4,61       0,101      0,6   0,298  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "1acea182-f845-410d-a0c3-9ed01a929e6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0            ASIA (EX. NEAR EAST)         \n",
       "1      EASTERN EUROPE                     \n",
       "2      NORTHERN AFRICA                    \n",
       "3      OCEANIA                            \n",
       "4      WESTERN EUROPE                     \n",
       "                      ...                 \n",
       "222    NEAR EAST                          \n",
       "223    NORTHERN AFRICA                    \n",
       "224    NEAR EAST                          \n",
       "225    SUB-SAHARAN AFRICA                 \n",
       "226    SUB-SAHARAN AFRICA                 \n",
       "Name: Region, Length: 227, dtype: object"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info[\"Region\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "64948ac1-dae6-41eb-bfa7-2c8b84caae2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Region</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>Afghanistan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>Albania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>Algeria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>American Samoa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>Andorra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>West Bank</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>Western Sahara</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>Yemen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>Zambia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>Zimbabwe</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>227 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Region          Country\n",
       "0          ASIA (EX. NEAR EAST)              Afghanistan \n",
       "1    EASTERN EUROPE                              Albania \n",
       "2    NORTHERN AFRICA                             Algeria \n",
       "3    OCEANIA                              American Samoa \n",
       "4    WESTERN EUROPE                              Andorra \n",
       "..                                   ...              ...\n",
       "222  NEAR EAST                                 West Bank \n",
       "223  NORTHERN AFRICA                      Western Sahara \n",
       "224  NEAR EAST                                     Yemen \n",
       "225  SUB-SAHARAN AFRICA                           Zambia \n",
       "226  SUB-SAHARAN AFRICA                         Zimbabwe \n",
       "\n",
       "[227 rows x 2 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info[['Region','Country']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "dbbc50e9-de60-4777-bead-8a1680048f80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country                                                           Israel \n",
       "Region                                NEAR EAST                          \n",
       "Population                                                        6352117\n",
       "Area (sq. mi.)                                                      20770\n",
       "Pop. Density (per sq. mi.)                                          305,8\n",
       "Coastline (coast/area ratio)                                         1,31\n",
       "Net migration                                                        0,68\n",
       "Infant mortality (per 1000 births)                                   7,03\n",
       "GDP ($ per capita)                                                19800.0\n",
       "Literacy (%)                                                         95,4\n",
       "Phones (per 1000)                                                   462,3\n",
       "Arable (%)                                                          16,39\n",
       "Crops (%)                                                            4,17\n",
       "Other (%)                                                           79,44\n",
       "Climate                                                                 3\n",
       "Birthrate                                                           17,97\n",
       "Deathrate                                                            6,18\n",
       "Agriculture                                                         0,026\n",
       "Industry                                                            0,317\n",
       "Service                                                             0,657\n",
       "Name: 100, dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.iloc[100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "301bd0ae-65c0-4244-91a2-342ee86633ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>2381740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>199</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "           Country  Area (sq. mi.)\n",
       "2         Algeria          2381740\n",
       "3  American Samoa              199"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.iloc[[2, 3], [0, 3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "3fb731a0-6715-493a-992e-2a98ba65d39a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2381740</td>\n",
       "      <td>0,04</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>58,29</td>\n",
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      ],
      "text/plain": [
       "   Area (sq. mi.) Coastline (coast/area ratio)\n",
       "2         2381740                         0,04\n",
       "3             199                        58,29"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.iloc[[2, 3], [3, 5]] #获取特定行及特定列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "dc52bbd7-1938-4bc6-b077-bc3b6e9332fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Net migration</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>28748</td>\n",
       "      <td>-4,93</td>\n",
       "      <td>1,26</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2381740</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
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      ],
      "text/plain": [
       "   Area (sq. mi.) Net migration Coastline (coast/area ratio)\n",
       "1           28748         -4,93                         1,26\n",
       "2         2381740         -0,39                         0,04\n",
       "3             199        -20,71                        58,29"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.iloc[[1,2,3], [3,6,5]] #获取特定行及特定列并且可调整顺序，只能用数字索引，且不能连续行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "67e70ad8-1a42-498b-bd41-a7dee3ea0604",
   "metadata": {},
   "outputs": [],
   "source": [
    "cou_info['Country'] = cou_info['Country'].str.strip() #把Country列中开头和尾部的空格去掉"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a6896d4b-1a87-4bdf-b732-2aee1c31cdd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>Population</th>\n",
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       "    <tr>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>31056997</td>\n",
       "      <td>647500</td>\n",
       "      <td>48,0</td>\n",
       "      <td>0,00</td>\n",
       "      <td>23,06</td>\n",
       "      <td>163,07</td>\n",
       "      <td>700.0</td>\n",
       "      <td>36,0</td>\n",
       "      <td>3,2</td>\n",
       "      <td>12,13</td>\n",
       "      <td>0,22</td>\n",
       "      <td>87,65</td>\n",
       "      <td>1</td>\n",
       "      <td>46,6</td>\n",
       "      <td>20,34</td>\n",
       "      <td>0,38</td>\n",
       "      <td>0,24</td>\n",
       "      <td>0,38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>3581655</td>\n",
       "      <td>28748</td>\n",
       "      <td>124,6</td>\n",
       "      <td>1,26</td>\n",
       "      <td>-4,93</td>\n",
       "      <td>21,52</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>86,5</td>\n",
       "      <td>71,2</td>\n",
       "      <td>21,09</td>\n",
       "      <td>4,42</td>\n",
       "      <td>74,49</td>\n",
       "      <td>3</td>\n",
       "      <td>15,11</td>\n",
       "      <td>5,22</td>\n",
       "      <td>0,232</td>\n",
       "      <td>0,188</td>\n",
       "      <td>0,579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>32930091</td>\n",
       "      <td>2381740</td>\n",
       "      <td>13,8</td>\n",
       "      <td>0,04</td>\n",
       "      <td>-0,39</td>\n",
       "      <td>31</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>70,0</td>\n",
       "      <td>78,1</td>\n",
       "      <td>3,22</td>\n",
       "      <td>0,25</td>\n",
       "      <td>96,53</td>\n",
       "      <td>1</td>\n",
       "      <td>17,14</td>\n",
       "      <td>4,61</td>\n",
       "      <td>0,101</td>\n",
       "      <td>0,6</td>\n",
       "      <td>0,298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</th>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>57794</td>\n",
       "      <td>199</td>\n",
       "      <td>290,4</td>\n",
       "      <td>58,29</td>\n",
       "      <td>-20,71</td>\n",
       "      <td>9,27</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>97,0</td>\n",
       "      <td>259,5</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>75</td>\n",
       "      <td>2</td>\n",
       "      <td>22,46</td>\n",
       "      <td>3,27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>71201</td>\n",
       "      <td>468</td>\n",
       "      <td>152,1</td>\n",
       "      <td>0,00</td>\n",
       "      <td>6,6</td>\n",
       "      <td>4,05</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>100,0</td>\n",
       "      <td>497,2</td>\n",
       "      <td>2,22</td>\n",
       "      <td>0</td>\n",
       "      <td>97,78</td>\n",
       "      <td>3</td>\n",
       "      <td>8,71</td>\n",
       "      <td>6,25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>West Bank</th>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>2460492</td>\n",
       "      <td>5860</td>\n",
       "      <td>419,9</td>\n",
       "      <td>0,00</td>\n",
       "      <td>2,98</td>\n",
       "      <td>19,62</td>\n",
       "      <td>800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>145,2</td>\n",
       "      <td>16,9</td>\n",
       "      <td>18,97</td>\n",
       "      <td>64,13</td>\n",
       "      <td>3</td>\n",
       "      <td>31,67</td>\n",
       "      <td>3,92</td>\n",
       "      <td>0,09</td>\n",
       "      <td>0,28</td>\n",
       "      <td>0,63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Sahara</th>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>273008</td>\n",
       "      <td>266000</td>\n",
       "      <td>1,0</td>\n",
       "      <td>0,42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0,02</td>\n",
       "      <td>0</td>\n",
       "      <td>99,98</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0,4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>21456188</td>\n",
       "      <td>527970</td>\n",
       "      <td>40,6</td>\n",
       "      <td>0,36</td>\n",
       "      <td>0</td>\n",
       "      <td>61,5</td>\n",
       "      <td>800.0</td>\n",
       "      <td>50,2</td>\n",
       "      <td>37,2</td>\n",
       "      <td>2,78</td>\n",
       "      <td>0,24</td>\n",
       "      <td>96,98</td>\n",
       "      <td>1</td>\n",
       "      <td>42,89</td>\n",
       "      <td>8,3</td>\n",
       "      <td>0,135</td>\n",
       "      <td>0,472</td>\n",
       "      <td>0,393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>11502010</td>\n",
       "      <td>752614</td>\n",
       "      <td>15,3</td>\n",
       "      <td>0,00</td>\n",
       "      <td>0</td>\n",
       "      <td>88,29</td>\n",
       "      <td>800.0</td>\n",
       "      <td>80,6</td>\n",
       "      <td>8,2</td>\n",
       "      <td>7,08</td>\n",
       "      <td>0,03</td>\n",
       "      <td>92,9</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>19,93</td>\n",
       "      <td>0,22</td>\n",
       "      <td>0,29</td>\n",
       "      <td>0,489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>12236805</td>\n",
       "      <td>390580</td>\n",
       "      <td>31,3</td>\n",
       "      <td>0,00</td>\n",
       "      <td>0</td>\n",
       "      <td>67,69</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>90,7</td>\n",
       "      <td>26,8</td>\n",
       "      <td>8,32</td>\n",
       "      <td>0,34</td>\n",
       "      <td>91,34</td>\n",
       "      <td>2</td>\n",
       "      <td>28,01</td>\n",
       "      <td>21,84</td>\n",
       "      <td>0,179</td>\n",
       "      <td>0,243</td>\n",
       "      <td>0,579</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>227 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Region  Population  \\\n",
       "Country                                                           \n",
       "Afghanistan           ASIA (EX. NEAR EAST)             31056997   \n",
       "Albania         EASTERN EUROPE                          3581655   \n",
       "Algeria         NORTHERN AFRICA                        32930091   \n",
       "American Samoa  OCEANIA                                   57794   \n",
       "Andorra         WESTERN EUROPE                            71201   \n",
       "...                                             ...         ...   \n",
       "West Bank       NEAR EAST                               2460492   \n",
       "Western Sahara  NORTHERN AFRICA                          273008   \n",
       "Yemen           NEAR EAST                              21456188   \n",
       "Zambia          SUB-SAHARAN AFRICA                     11502010   \n",
       "Zimbabwe        SUB-SAHARAN AFRICA                     12236805   \n",
       "\n",
       "                Area (sq. mi.) Pop. Density (per sq. mi.)  \\\n",
       "Country                                                     \n",
       "Afghanistan             647500                       48,0   \n",
       "Albania                  28748                      124,6   \n",
       "Algeria                2381740                       13,8   \n",
       "American Samoa             199                      290,4   \n",
       "Andorra                    468                      152,1   \n",
       "...                        ...                        ...   \n",
       "West Bank                 5860                      419,9   \n",
       "Western Sahara          266000                        1,0   \n",
       "Yemen                   527970                       40,6   \n",
       "Zambia                  752614                       15,3   \n",
       "Zimbabwe                390580                       31,3   \n",
       "\n",
       "               Coastline (coast/area ratio) Net migration  \\\n",
       "Country                                                     \n",
       "Afghanistan                            0,00         23,06   \n",
       "Albania                                1,26         -4,93   \n",
       "Algeria                                0,04         -0,39   \n",
       "American Samoa                        58,29        -20,71   \n",
       "Andorra                                0,00           6,6   \n",
       "...                                     ...           ...   \n",
       "West Bank                              0,00          2,98   \n",
       "Western Sahara                         0,42           NaN   \n",
       "Yemen                                  0,36             0   \n",
       "Zambia                                 0,00             0   \n",
       "Zimbabwe                               0,00             0   \n",
       "\n",
       "               Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "Country                                                                 \n",
       "Afghanistan                                163,07               700.0   \n",
       "Albania                                     21,52              4500.0   \n",
       "Algeria                                        31              6000.0   \n",
       "American Samoa                               9,27              8000.0   \n",
       "Andorra                                      4,05             19000.0   \n",
       "...                                           ...                 ...   \n",
       "West Bank                                   19,62               800.0   \n",
       "Western Sahara                                NaN                 NaN   \n",
       "Yemen                                        61,5               800.0   \n",
       "Zambia                                      88,29               800.0   \n",
       "Zimbabwe                                    67,69              1900.0   \n",
       "\n",
       "               Literacy (%) Phones (per 1000) Arable (%) Crops (%) Other (%)  \\\n",
       "Country                                                                        \n",
       "Afghanistan            36,0               3,2      12,13      0,22     87,65   \n",
       "Albania                86,5              71,2      21,09      4,42     74,49   \n",
       "Algeria                70,0              78,1       3,22      0,25     96,53   \n",
       "American Samoa         97,0             259,5         10        15        75   \n",
       "Andorra               100,0             497,2       2,22         0     97,78   \n",
       "...                     ...               ...        ...       ...       ...   \n",
       "West Bank               NaN             145,2       16,9     18,97     64,13   \n",
       "Western Sahara          NaN               NaN       0,02         0     99,98   \n",
       "Yemen                  50,2              37,2       2,78      0,24     96,98   \n",
       "Zambia                 80,6               8,2       7,08      0,03      92,9   \n",
       "Zimbabwe               90,7              26,8       8,32      0,34     91,34   \n",
       "\n",
       "               Climate Birthrate Deathrate Agriculture Industry Service  \n",
       "Country                                                                  \n",
       "Afghanistan          1      46,6     20,34        0,38     0,24    0,38  \n",
       "Albania              3     15,11      5,22       0,232    0,188   0,579  \n",
       "Algeria              1     17,14      4,61       0,101      0,6   0,298  \n",
       "American Samoa       2     22,46      3,27         NaN      NaN     NaN  \n",
       "Andorra              3      8,71      6,25         NaN      NaN     NaN  \n",
       "...                ...       ...       ...         ...      ...     ...  \n",
       "West Bank            3     31,67      3,92        0,09     0,28    0,63  \n",
       "Western Sahara       1       NaN       NaN         NaN      NaN     0,4  \n",
       "Yemen                1     42,89       8,3       0,135    0,472   0,393  \n",
       "Zambia               2        41     19,93        0,22     0,29   0,489  \n",
       "Zimbabwe             2     28,01     21,84       0,179    0,243   0,579  \n",
       "\n",
       "[227 rows x 19 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.set_index(['Country'], drop = True, inplace = True)\n",
    "cou_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c77d7bec-83b1-443c-b267-ab7727f1d50c",
   "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>Region</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\n",
       "      <td>NEAR EAST</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Region\n",
       "Country                                     \n",
       "China          ASIA (EX. NEAR EAST)         \n",
       "Yemen    NEAR EAST                          "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.loc[['China','Yemen'], ['Region']] #获取特定行及特定列并且可调整顺序，用loc即可用名称进行检索，使用innerlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "20cfadb0-7164-4925-ada1-3da61a80a3ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>Population</th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <th>Net migration</th>\n",
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       "    <tr>\n",
       "      <th>Country</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>China</th>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>1313973713</td>\n",
       "      <td>9596960</td>\n",
       "      <td>136,9</td>\n",
       "      <td>0,15</td>\n",
       "      <td>-0,4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colombia</th>\n",
       "      <td>LATIN AMER. &amp; CARIB</td>\n",
       "      <td>43593035</td>\n",
       "      <td>1138910</td>\n",
       "      <td>38,3</td>\n",
       "      <td>0,28</td>\n",
       "      <td>-0,31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comoros</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>690948</td>\n",
       "      <td>2170</td>\n",
       "      <td>318,4</td>\n",
       "      <td>15,67</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congo, Dem. Rep.</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>62660551</td>\n",
       "      <td>2345410</td>\n",
       "      <td>26,7</td>\n",
       "      <td>0,00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congo, Repub. of the</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>3702314</td>\n",
       "      <td>342000</td>\n",
       "      <td>10,8</td>\n",
       "      <td>0,05</td>\n",
       "      <td>-0,17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Isle of Man</th>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>75441</td>\n",
       "      <td>572</td>\n",
       "      <td>131,9</td>\n",
       "      <td>27,97</td>\n",
       "      <td>5,36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>6352117</td>\n",
       "      <td>20770</td>\n",
       "      <td>305,8</td>\n",
       "      <td>1,31</td>\n",
       "      <td>0,68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>58133509</td>\n",
       "      <td>301230</td>\n",
       "      <td>193,0</td>\n",
       "      <td>2,52</td>\n",
       "      <td>2,07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jamaica</th>\n",
       "      <td>LATIN AMER. &amp; CARIB</td>\n",
       "      <td>2758124</td>\n",
       "      <td>10991</td>\n",
       "      <td>250,9</td>\n",
       "      <td>9,30</td>\n",
       "      <td>-4,92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>127463611</td>\n",
       "      <td>377835</td>\n",
       "      <td>337,4</td>\n",
       "      <td>7,87</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   Region  Population  \\\n",
       "Country                                                                 \n",
       "China                       ASIA (EX. NEAR EAST)           1313973713   \n",
       "Colombia                          LATIN AMER. & CARIB        43593035   \n",
       "Comoros               SUB-SAHARAN AFRICA                       690948   \n",
       "Congo, Dem. Rep.      SUB-SAHARAN AFRICA                     62660551   \n",
       "Congo, Repub. of the  SUB-SAHARAN AFRICA                      3702314   \n",
       "...                                                   ...         ...   \n",
       "Isle of Man           WESTERN EUROPE                            75441   \n",
       "Israel                NEAR EAST                               6352117   \n",
       "Italy                 WESTERN EUROPE                         58133509   \n",
       "Jamaica                           LATIN AMER. & CARIB         2758124   \n",
       "Japan                       ASIA (EX. NEAR EAST)            127463611   \n",
       "\n",
       "                      Area (sq. mi.) Pop. Density (per sq. mi.)  \\\n",
       "Country                                                           \n",
       "China                        9596960                      136,9   \n",
       "Colombia                     1138910                       38,3   \n",
       "Comoros                         2170                      318,4   \n",
       "Congo, Dem. Rep.             2345410                       26,7   \n",
       "Congo, Repub. of the          342000                       10,8   \n",
       "...                              ...                        ...   \n",
       "Isle of Man                      572                      131,9   \n",
       "Israel                         20770                      305,8   \n",
       "Italy                         301230                      193,0   \n",
       "Jamaica                        10991                      250,9   \n",
       "Japan                         377835                      337,4   \n",
       "\n",
       "                     Coastline (coast/area ratio) Net migration  \n",
       "Country                                                          \n",
       "China                                        0,15          -0,4  \n",
       "Colombia                                     0,28         -0,31  \n",
       "Comoros                                     15,67             0  \n",
       "Congo, Dem. Rep.                             0,00             0  \n",
       "Congo, Repub. of the                         0,05         -0,17  \n",
       "...                                           ...           ...  \n",
       "Isle of Man                                 27,97          5,36  \n",
       "Israel                                       1,31          0,68  \n",
       "Italy                                        2,52          2,07  \n",
       "Jamaica                                      9,30         -4,92  \n",
       "Japan                                        7,87             0  \n",
       "\n",
       "[62 rows x 6 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.loc['China':'Japan', 'Region':'Net migration'] #可获取范围内的相关数据,此时用的是一个list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "36cc2872-6c37-4b38-978a-977f00e1b458",
   "metadata": {},
   "outputs": [],
   "source": [
    "#作业："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "e06adc12-3af1-4bf3-ac93-87356363b42b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>Population</th>\n",
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       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
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       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Literacy (%)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Arable (%)</th>\n",
       "      <th>Crops (%)</th>\n",
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       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>31056997</td>\n",
       "      <td>647500</td>\n",
       "      <td>48,0</td>\n",
       "      <td>0,00</td>\n",
       "      <td>23,06</td>\n",
       "      <td>163,07</td>\n",
       "      <td>700.0</td>\n",
       "      <td>36,0</td>\n",
       "      <td>3,2</td>\n",
       "      <td>12,13</td>\n",
       "      <td>0,22</td>\n",
       "      <td>87,65</td>\n",
       "      <td>1</td>\n",
       "      <td>46,6</td>\n",
       "      <td>20,34</td>\n",
       "      <td>0,38</td>\n",
       "      <td>0,24</td>\n",
       "      <td>0,38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>3581655</td>\n",
       "      <td>28748</td>\n",
       "      <td>124,6</td>\n",
       "      <td>1,26</td>\n",
       "      <td>-4,93</td>\n",
       "      <td>21,52</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>86,5</td>\n",
       "      <td>71,2</td>\n",
       "      <td>21,09</td>\n",
       "      <td>4,42</td>\n",
       "      <td>74,49</td>\n",
       "      <td>3</td>\n",
       "      <td>15,11</td>\n",
       "      <td>5,22</td>\n",
       "      <td>0,232</td>\n",
       "      <td>0,188</td>\n",
       "      <td>0,579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>32930091</td>\n",
       "      <td>2381740</td>\n",
       "      <td>13,8</td>\n",
       "      <td>0,04</td>\n",
       "      <td>-0,39</td>\n",
       "      <td>31</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>70,0</td>\n",
       "      <td>78,1</td>\n",
       "      <td>3,22</td>\n",
       "      <td>0,25</td>\n",
       "      <td>96,53</td>\n",
       "      <td>1</td>\n",
       "      <td>17,14</td>\n",
       "      <td>4,61</td>\n",
       "      <td>0,101</td>\n",
       "      <td>0,6</td>\n",
       "      <td>0,298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</th>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>57794</td>\n",
       "      <td>199</td>\n",
       "      <td>290,4</td>\n",
       "      <td>58,29</td>\n",
       "      <td>-20,71</td>\n",
       "      <td>9,27</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>97,0</td>\n",
       "      <td>259,5</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>75</td>\n",
       "      <td>2</td>\n",
       "      <td>22,46</td>\n",
       "      <td>3,27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>71201</td>\n",
       "      <td>468</td>\n",
       "      <td>152,1</td>\n",
       "      <td>0,00</td>\n",
       "      <td>6,6</td>\n",
       "      <td>4,05</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>100,0</td>\n",
       "      <td>497,2</td>\n",
       "      <td>2,22</td>\n",
       "      <td>0</td>\n",
       "      <td>97,78</td>\n",
       "      <td>3</td>\n",
       "      <td>8,71</td>\n",
       "      <td>6,25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>SUB-SAHARAN AFRICA</td>\n",
       "      <td>12127071</td>\n",
       "      <td>1246700</td>\n",
       "      <td>9,7</td>\n",
       "      <td>0,13</td>\n",
       "      <td>0</td>\n",
       "      <td>191,19</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>42,0</td>\n",
       "      <td>7,8</td>\n",
       "      <td>2,41</td>\n",
       "      <td>0,24</td>\n",
       "      <td>97,35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45,11</td>\n",
       "      <td>24,2</td>\n",
       "      <td>0,096</td>\n",
       "      <td>0,658</td>\n",
       "      <td>0,246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anguilla</th>\n",
       "      <td>LATIN AMER. &amp; CARIB</td>\n",
       "      <td>13477</td>\n",
       "      <td>102</td>\n",
       "      <td>132,1</td>\n",
       "      <td>59,80</td>\n",
       "      <td>10,76</td>\n",
       "      <td>21,03</td>\n",
       "      <td>8600.0</td>\n",
       "      <td>95,0</td>\n",
       "      <td>460,0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "      <td>14,17</td>\n",
       "      <td>5,34</td>\n",
       "      <td>0,04</td>\n",
       "      <td>0,18</td>\n",
       "      <td>0,78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Antigua &amp; Barbuda</th>\n",
       "      <td>LATIN AMER. &amp; CARIB</td>\n",
       "      <td>69108</td>\n",
       "      <td>443</td>\n",
       "      <td>156,0</td>\n",
       "      <td>34,54</td>\n",
       "      <td>-6,15</td>\n",
       "      <td>19,46</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>89,0</td>\n",
       "      <td>549,9</td>\n",
       "      <td>18,18</td>\n",
       "      <td>4,55</td>\n",
       "      <td>77,27</td>\n",
       "      <td>2</td>\n",
       "      <td>16,93</td>\n",
       "      <td>5,37</td>\n",
       "      <td>0,038</td>\n",
       "      <td>0,22</td>\n",
       "      <td>0,743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>LATIN AMER. &amp; CARIB</td>\n",
       "      <td>39921833</td>\n",
       "      <td>2766890</td>\n",
       "      <td>14,4</td>\n",
       "      <td>0,18</td>\n",
       "      <td>0,61</td>\n",
       "      <td>15,18</td>\n",
       "      <td>11200.0</td>\n",
       "      <td>97,1</td>\n",
       "      <td>220,4</td>\n",
       "      <td>12,31</td>\n",
       "      <td>0,48</td>\n",
       "      <td>87,21</td>\n",
       "      <td>3</td>\n",
       "      <td>16,73</td>\n",
       "      <td>7,55</td>\n",
       "      <td>0,095</td>\n",
       "      <td>0,358</td>\n",
       "      <td>0,547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Armenia</th>\n",
       "      <td>C.W. OF IND. STATES</td>\n",
       "      <td>2976372</td>\n",
       "      <td>29800</td>\n",
       "      <td>99,9</td>\n",
       "      <td>0,00</td>\n",
       "      <td>-6,47</td>\n",
       "      <td>23,28</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>98,6</td>\n",
       "      <td>195,7</td>\n",
       "      <td>17,55</td>\n",
       "      <td>2,3</td>\n",
       "      <td>80,15</td>\n",
       "      <td>4</td>\n",
       "      <td>12,07</td>\n",
       "      <td>8,23</td>\n",
       "      <td>0,239</td>\n",
       "      <td>0,343</td>\n",
       "      <td>0,418</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Region  Population  \\\n",
       "Country                                                              \n",
       "Afghanistan              ASIA (EX. NEAR EAST)             31056997   \n",
       "Albania            EASTERN EUROPE                          3581655   \n",
       "Algeria            NORTHERN AFRICA                        32930091   \n",
       "American Samoa     OCEANIA                                   57794   \n",
       "Andorra            WESTERN EUROPE                            71201   \n",
       "Angola             SUB-SAHARAN AFRICA                     12127071   \n",
       "Anguilla                       LATIN AMER. & CARIB           13477   \n",
       "Antigua & Barbuda              LATIN AMER. & CARIB           69108   \n",
       "Argentina                      LATIN AMER. & CARIB        39921833   \n",
       "Armenia                           C.W. OF IND. STATES      2976372   \n",
       "\n",
       "                   Area (sq. mi.) Pop. Density (per sq. mi.)  \\\n",
       "Country                                                        \n",
       "Afghanistan                647500                       48,0   \n",
       "Albania                     28748                      124,6   \n",
       "Algeria                   2381740                       13,8   \n",
       "American Samoa                199                      290,4   \n",
       "Andorra                       468                      152,1   \n",
       "Angola                    1246700                        9,7   \n",
       "Anguilla                      102                      132,1   \n",
       "Antigua & Barbuda             443                      156,0   \n",
       "Argentina                 2766890                       14,4   \n",
       "Armenia                     29800                       99,9   \n",
       "\n",
       "                  Coastline (coast/area ratio) Net migration  \\\n",
       "Country                                                        \n",
       "Afghanistan                               0,00         23,06   \n",
       "Albania                                   1,26         -4,93   \n",
       "Algeria                                   0,04         -0,39   \n",
       "American Samoa                           58,29        -20,71   \n",
       "Andorra                                   0,00           6,6   \n",
       "Angola                                    0,13             0   \n",
       "Anguilla                                 59,80         10,76   \n",
       "Antigua & Barbuda                        34,54         -6,15   \n",
       "Argentina                                 0,18          0,61   \n",
       "Armenia                                   0,00         -6,47   \n",
       "\n",
       "                  Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "Country                                                                    \n",
       "Afghanistan                                   163,07               700.0   \n",
       "Albania                                        21,52              4500.0   \n",
       "Algeria                                           31              6000.0   \n",
       "American Samoa                                  9,27              8000.0   \n",
       "Andorra                                         4,05             19000.0   \n",
       "Angola                                        191,19              1900.0   \n",
       "Anguilla                                       21,03              8600.0   \n",
       "Antigua & Barbuda                              19,46             11000.0   \n",
       "Argentina                                      15,18             11200.0   \n",
       "Armenia                                        23,28              3500.0   \n",
       "\n",
       "                  Literacy (%) Phones (per 1000) Arable (%) Crops (%)  \\\n",
       "Country                                                                 \n",
       "Afghanistan               36,0               3,2      12,13      0,22   \n",
       "Albania                   86,5              71,2      21,09      4,42   \n",
       "Algeria                   70,0              78,1       3,22      0,25   \n",
       "American Samoa            97,0             259,5         10        15   \n",
       "Andorra                  100,0             497,2       2,22         0   \n",
       "Angola                    42,0               7,8       2,41      0,24   \n",
       "Anguilla                  95,0             460,0          0         0   \n",
       "Antigua & Barbuda         89,0             549,9      18,18      4,55   \n",
       "Argentina                 97,1             220,4      12,31      0,48   \n",
       "Armenia                   98,6             195,7      17,55       2,3   \n",
       "\n",
       "                  Other (%) Climate Birthrate Deathrate Agriculture Industry  \\\n",
       "Country                                                                        \n",
       "Afghanistan           87,65       1      46,6     20,34        0,38     0,24   \n",
       "Albania               74,49       3     15,11      5,22       0,232    0,188   \n",
       "Algeria               96,53       1     17,14      4,61       0,101      0,6   \n",
       "American Samoa           75       2     22,46      3,27         NaN      NaN   \n",
       "Andorra               97,78       3      8,71      6,25         NaN      NaN   \n",
       "Angola                97,35     NaN     45,11      24,2       0,096    0,658   \n",
       "Anguilla                100       2     14,17      5,34        0,04     0,18   \n",
       "Antigua & Barbuda     77,27       2     16,93      5,37       0,038     0,22   \n",
       "Argentina             87,21       3     16,73      7,55       0,095    0,358   \n",
       "Armenia               80,15       4     12,07      8,23       0,239    0,343   \n",
       "\n",
       "                  Service  \n",
       "Country                    \n",
       "Afghanistan          0,38  \n",
       "Albania             0,579  \n",
       "Algeria             0,298  \n",
       "American Samoa        NaN  \n",
       "Andorra               NaN  \n",
       "Angola              0,246  \n",
       "Anguilla             0,78  \n",
       "Antigua & Barbuda   0,743  \n",
       "Argentina           0,547  \n",
       "Armenia             0,418  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cou_info.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe318b08-a7c9-410f-a97c-0a2c50e247ef",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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