data visualization6_산점도(world_indexes).ipynb

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       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Human Development Index HDI-2014</th>\n",
       "      <th>Gini coefficient 2005-2013</th>\n",
       "      <th>Adolescent birth rate 15-19 per 100k 20102015</th>\n",
       "      <th>Birth registration funder age 5 2005-2013</th>\n",
       "      <th>Carbon dioxide emissionsAverage annual growth</th>\n",
       "      <th>Carbon dioxide emissions per capita 2011 Tones</th>\n",
       "      <th>Change forest percentable 1900 to 2012</th>\n",
       "      <th>Change mobile usage 2009 2014</th>\n",
       "      <th>Consumer price index 2013</th>\n",
       "      <th>...</th>\n",
       "      <th>Renewable sources percentage of total 2012</th>\n",
       "      <th>Research and development expenditure  2005-2012</th>\n",
       "      <th>Secondary 2008-2014</th>\n",
       "      <th>Share of seats in parliament percentage held by womand 2014</th>\n",
       "      <th>Stock of immigrants percentage of population 2013</th>\n",
       "      <th>Taxes on income profit and capital gain 205 2013</th>\n",
       "      <th>Tertiary -2008-2014</th>\n",
       "      <th>Total tax revenue of GDP 2005-2013</th>\n",
       "      <th>Tuberculosis rate per thousands 2012</th>\n",
       "      <th>Under-five Mortality 2013 thousands</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Norway</td>\n",
       "      <td>0.943877</td>\n",
       "      <td>26.83</td>\n",
       "      <td>7.834</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.778925</td>\n",
       "      <td>9.192879</td>\n",
       "      <td>11.914567</td>\n",
       "      <td>5.22</td>\n",
       "      <td>104.194175</td>\n",
       "      <td>...</td>\n",
       "      <td>47.752676</td>\n",
       "      <td>1.654740</td>\n",
       "      <td>111.061300</td>\n",
       "      <td>39.644970</td>\n",
       "      <td>13.772622</td>\n",
       "      <td>31.798391</td>\n",
       "      <td>74.10112</td>\n",
       "      <td>27.288097</td>\n",
       "      <td>0.14</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Australia</td>\n",
       "      <td>0.934958</td>\n",
       "      <td>34.01</td>\n",
       "      <td>12.059</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.090351</td>\n",
       "      <td>16.519210</td>\n",
       "      <td>-4.561812</td>\n",
       "      <td>30.27</td>\n",
       "      <td>107.789440</td>\n",
       "      <td>...</td>\n",
       "      <td>4.632202</td>\n",
       "      <td>2.385620</td>\n",
       "      <td>135.535430</td>\n",
       "      <td>30.530973</td>\n",
       "      <td>27.711793</td>\n",
       "      <td>65.333748</td>\n",
       "      <td>86.33409</td>\n",
       "      <td>21.361426</td>\n",
       "      <td>0.19</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>0.929613</td>\n",
       "      <td>32.35</td>\n",
       "      <td>1.900</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>-1.101254</td>\n",
       "      <td>4.625230</td>\n",
       "      <td>8.567416</td>\n",
       "      <td>16.72</td>\n",
       "      <td>99.317229</td>\n",
       "      <td>...</td>\n",
       "      <td>49.659398</td>\n",
       "      <td>2.870460</td>\n",
       "      <td>96.306380</td>\n",
       "      <td>28.455285</td>\n",
       "      <td>28.906998</td>\n",
       "      <td>22.673299</td>\n",
       "      <td>55.56190</td>\n",
       "      <td>9.759124</td>\n",
       "      <td>0.22</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>0.923328</td>\n",
       "      <td>26.88</td>\n",
       "      <td>5.101</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>-1.767733</td>\n",
       "      <td>7.248329</td>\n",
       "      <td>23.029974</td>\n",
       "      <td>1.83</td>\n",
       "      <td>106.057718</td>\n",
       "      <td>...</td>\n",
       "      <td>26.767245</td>\n",
       "      <td>2.984160</td>\n",
       "      <td>124.659270</td>\n",
       "      <td>37.988827</td>\n",
       "      <td>9.909512</td>\n",
       "      <td>39.677938</td>\n",
       "      <td>79.59763</td>\n",
       "      <td>33.395651</td>\n",
       "      <td>0.40</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>0.921794</td>\n",
       "      <td>28.87</td>\n",
       "      <td>6.165</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>-0.252734</td>\n",
       "      <td>10.064490</td>\n",
       "      <td>5.922602</td>\n",
       "      <td>-4.31</td>\n",
       "      <td>107.474154</td>\n",
       "      <td>...</td>\n",
       "      <td>6.671366</td>\n",
       "      <td>2.156760</td>\n",
       "      <td>129.912770</td>\n",
       "      <td>36.888889</td>\n",
       "      <td>11.724418</td>\n",
       "      <td>23.533104</td>\n",
       "      <td>77.34356</td>\n",
       "      <td>19.724059</td>\n",
       "      <td>0.17</td>\n",
       "      <td>4.0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>Burundi</td>\n",
       "      <td>0.399928</td>\n",
       "      <td>33.27</td>\n",
       "      <td>30.256</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>0.630172</td>\n",
       "      <td>0.021909</td>\n",
       "      <td>-41.730104</td>\n",
       "      <td>195.33</td>\n",
       "      <td>140.018625</td>\n",
       "      <td>...</td>\n",
       "      <td>53.544693</td>\n",
       "      <td>0.121260</td>\n",
       "      <td>33.102310</td>\n",
       "      <td>34.931507</td>\n",
       "      <td>2.504071</td>\n",
       "      <td>19.855360</td>\n",
       "      <td>3.16599</td>\n",
       "      <td>11.006974</td>\n",
       "      <td>18.00</td>\n",
       "      <td>82.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>Chad</td>\n",
       "      <td>0.391906</td>\n",
       "      <td>43.30</td>\n",
       "      <td>152.015</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>0.861268</td>\n",
       "      <td>0.044623</td>\n",
       "      <td>-13.298246</td>\n",
       "      <td>98.14</td>\n",
       "      <td>109.954331</td>\n",
       "      <td>...</td>\n",
       "      <td>88.289148</td>\n",
       "      <td>0.612717</td>\n",
       "      <td>22.794100</td>\n",
       "      <td>14.893617</td>\n",
       "      <td>3.423823</td>\n",
       "      <td>27.618325</td>\n",
       "      <td>2.25039</td>\n",
       "      <td>15.978897</td>\n",
       "      <td>18.00</td>\n",
       "      <td>147.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>Eritrea</td>\n",
       "      <td>0.390899</td>\n",
       "      <td>36.75</td>\n",
       "      <td>65.280</td>\n",
       "      <td>99.333333</td>\n",
       "      <td>2.709607</td>\n",
       "      <td>0.087768</td>\n",
       "      <td>-6.033313</td>\n",
       "      <td>151.49</td>\n",
       "      <td>113.652667</td>\n",
       "      <td>...</td>\n",
       "      <td>78.271531</td>\n",
       "      <td>0.226783</td>\n",
       "      <td>42.522027</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.249450</td>\n",
       "      <td>17.402965</td>\n",
       "      <td>2.04323</td>\n",
       "      <td>13.265781</td>\n",
       "      <td>4.60</td>\n",
       "      <td>49.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>Central African Republic</td>\n",
       "      <td>0.350131</td>\n",
       "      <td>56.30</td>\n",
       "      <td>98.334</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>-1.829932</td>\n",
       "      <td>0.064475</td>\n",
       "      <td>-2.835840</td>\n",
       "      <td>54.91</td>\n",
       "      <td>108.757088</td>\n",
       "      <td>...</td>\n",
       "      <td>80.467360</td>\n",
       "      <td>0.253410</td>\n",
       "      <td>17.791890</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>2.907818</td>\n",
       "      <td>6.902223</td>\n",
       "      <td>2.84086</td>\n",
       "      <td>9.455153</td>\n",
       "      <td>50.00</td>\n",
       "      <td>139.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>Niger</td>\n",
       "      <td>0.348254</td>\n",
       "      <td>31.16</td>\n",
       "      <td>204.789</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>1.835631</td>\n",
       "      <td>0.086170</td>\n",
       "      <td>-39.372751</td>\n",
       "      <td>161.65</td>\n",
       "      <td>105.786143</td>\n",
       "      <td>...</td>\n",
       "      <td>26.755224</td>\n",
       "      <td>0.088957</td>\n",
       "      <td>15.924760</td>\n",
       "      <td>13.274336</td>\n",
       "      <td>0.741921</td>\n",
       "      <td>11.558007</td>\n",
       "      <td>1.75417</td>\n",
       "      <td>11.337822</td>\n",
       "      <td>16.00</td>\n",
       "      <td>104.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>188 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Id  Human Development Index HDI-2014  \\\n",
       "0                      Norway                          0.943877   \n",
       "1                   Australia                          0.934958   \n",
       "2                 Switzerland                          0.929613   \n",
       "3                     Denmark                          0.923328   \n",
       "4                 Netherlands                          0.921794   \n",
       "..                        ...                               ...   \n",
       "183                   Burundi                          0.399928   \n",
       "184                      Chad                          0.391906   \n",
       "185                   Eritrea                          0.390899   \n",
       "186  Central African Republic                          0.350131   \n",
       "187                     Niger                          0.348254   \n",
       "\n",
       "     Gini coefficient 2005-2013  \\\n",
       "0                         26.83   \n",
       "1                         34.01   \n",
       "2                         32.35   \n",
       "3                         26.88   \n",
       "4                         28.87   \n",
       "..                          ...   \n",
       "183                       33.27   \n",
       "184                       43.30   \n",
       "185                       36.75   \n",
       "186                       56.30   \n",
       "187                       31.16   \n",
       "\n",
       "     Adolescent birth rate 15-19 per 100k 20102015  \\\n",
       "0                                            7.834   \n",
       "1                                           12.059   \n",
       "2                                            1.900   \n",
       "3                                            5.101   \n",
       "4                                            6.165   \n",
       "..                                             ...   \n",
       "183                                         30.256   \n",
       "184                                        152.015   \n",
       "185                                         65.280   \n",
       "186                                         98.334   \n",
       "187                                        204.789   \n",
       "\n",
       "     Birth registration funder age 5 2005-2013  \\\n",
       "0                                   100.000000   \n",
       "1                                   100.000000   \n",
       "2                                   100.000000   \n",
       "3                                   100.000000   \n",
       "4                                   100.000000   \n",
       "..                                         ...   \n",
       "183                                  75.000000   \n",
       "184                                  16.000000   \n",
       "185                                  99.333333   \n",
       "186                                  61.000000   \n",
       "187                                  64.000000   \n",
       "\n",
       "     Carbon dioxide emissionsAverage annual growth  \\\n",
       "0                                         0.778925   \n",
       "1                                         1.090351   \n",
       "2                                        -1.101254   \n",
       "3                                        -1.767733   \n",
       "4                                        -0.252734   \n",
       "..                                             ...   \n",
       "183                                       0.630172   \n",
       "184                                       0.861268   \n",
       "185                                       2.709607   \n",
       "186                                      -1.829932   \n",
       "187                                       1.835631   \n",
       "\n",
       "     Carbon dioxide emissions per capita 2011 Tones  \\\n",
       "0                                          9.192879   \n",
       "1                                         16.519210   \n",
       "2                                          4.625230   \n",
       "3                                          7.248329   \n",
       "4                                         10.064490   \n",
       "..                                              ...   \n",
       "183                                        0.021909   \n",
       "184                                        0.044623   \n",
       "185                                        0.087768   \n",
       "186                                        0.064475   \n",
       "187                                        0.086170   \n",
       "\n",
       "     Change forest percentable 1900 to 2012  Change mobile usage 2009 2014  \\\n",
       "0                                 11.914567                           5.22   \n",
       "1                                 -4.561812                          30.27   \n",
       "2                                  8.567416                          16.72   \n",
       "3                                 23.029974                           1.83   \n",
       "4                                  5.922602                          -4.31   \n",
       "..                                      ...                            ...   \n",
       "183                              -41.730104                         195.33   \n",
       "184                              -13.298246                          98.14   \n",
       "185                               -6.033313                         151.49   \n",
       "186                               -2.835840                          54.91   \n",
       "187                              -39.372751                         161.65   \n",
       "\n",
       "     Consumer price index 2013  ...  \\\n",
       "0                   104.194175  ...   \n",
       "1                   107.789440  ...   \n",
       "2                    99.317229  ...   \n",
       "3                   106.057718  ...   \n",
       "4                   107.474154  ...   \n",
       "..                         ...  ...   \n",
       "183                 140.018625  ...   \n",
       "184                 109.954331  ...   \n",
       "185                 113.652667  ...   \n",
       "186                 108.757088  ...   \n",
       "187                 105.786143  ...   \n",
       "\n",
       "     Renewable sources percentage of total 2012  \\\n",
       "0                                     47.752676   \n",
       "1                                      4.632202   \n",
       "2                                     49.659398   \n",
       "3                                     26.767245   \n",
       "4                                      6.671366   \n",
       "..                                          ...   \n",
       "183                                   53.544693   \n",
       "184                                   88.289148   \n",
       "185                                   78.271531   \n",
       "186                                   80.467360   \n",
       "187                                   26.755224   \n",
       "\n",
       "     Research and development expenditure  2005-2012  Secondary 2008-2014  \\\n",
       "0                                           1.654740           111.061300   \n",
       "1                                           2.385620           135.535430   \n",
       "2                                           2.870460            96.306380   \n",
       "3                                           2.984160           124.659270   \n",
       "4                                           2.156760           129.912770   \n",
       "..                                               ...                  ...   \n",
       "183                                         0.121260            33.102310   \n",
       "184                                         0.612717            22.794100   \n",
       "185                                         0.226783            42.522027   \n",
       "186                                         0.253410            17.791890   \n",
       "187                                         0.088957            15.924760   \n",
       "\n",
       "     Share of seats in parliament percentage held by womand 2014  \\\n",
       "0                                            39.644970             \n",
       "1                                            30.530973             \n",
       "2                                            28.455285             \n",
       "3                                            37.988827             \n",
       "4                                            36.888889             \n",
       "..                                                 ...             \n",
       "183                                          34.931507             \n",
       "184                                          14.893617             \n",
       "185                                          22.000000             \n",
       "186                                          12.500000             \n",
       "187                                          13.274336             \n",
       "\n",
       "     Stock of immigrants percentage of population 2013  \\\n",
       "0                                            13.772622   \n",
       "1                                            27.711793   \n",
       "2                                            28.906998   \n",
       "3                                             9.909512   \n",
       "4                                            11.724418   \n",
       "..                                                 ...   \n",
       "183                                           2.504071   \n",
       "184                                           3.423823   \n",
       "185                                           0.249450   \n",
       "186                                           2.907818   \n",
       "187                                           0.741921   \n",
       "\n",
       "     Taxes on income profit and capital gain 205 2013  Tertiary -2008-2014  \\\n",
       "0                                           31.798391             74.10112   \n",
       "1                                           65.333748             86.33409   \n",
       "2                                           22.673299             55.56190   \n",
       "3                                           39.677938             79.59763   \n",
       "4                                           23.533104             77.34356   \n",
       "..                                                ...                  ...   \n",
       "183                                         19.855360              3.16599   \n",
       "184                                         27.618325              2.25039   \n",
       "185                                         17.402965              2.04323   \n",
       "186                                          6.902223              2.84086   \n",
       "187                                         11.558007              1.75417   \n",
       "\n",
       "     Total tax revenue of GDP 2005-2013  Tuberculosis rate per thousands 2012  \\\n",
       "0                             27.288097                                  0.14   \n",
       "1                             21.361426                                  0.19   \n",
       "2                              9.759124                                  0.22   \n",
       "3                             33.395651                                  0.40   \n",
       "4                             19.724059                                  0.17   \n",
       "..                                  ...                                   ...   \n",
       "183                           11.006974                                 18.00   \n",
       "184                           15.978897                                 18.00   \n",
       "185                           13.265781                                  4.60   \n",
       "186                            9.455153                                 50.00   \n",
       "187                           11.337822                                 16.00   \n",
       "\n",
       "     Under-five Mortality 2013 thousands  \n",
       "0                                    2.8  \n",
       "1                                    4.0  \n",
       "2                                    4.2  \n",
       "3                                    3.5  \n",
       "4                                    4.0  \n",
       "..                                   ...  \n",
       "183                                 82.9  \n",
       "184                                147.5  \n",
       "185                                 49.9  \n",
       "186                                139.2  \n",
       "187                                104.2  \n",
       "\n",
       "[188 rows x 66 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "\n",
    "# 데이터 값의 산점도를 출력하고 연관성을 확인한다.\n",
    "df = pd.read_csv('C:/Users/Kwon JaeWoo/Desktop/codeit_데이터사이언스 입문/world_indexes.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Life expectancy at birth- years</th>\n",
       "      <th>Internet users percentage of population 2014</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Life expectancy at birth- years</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.807354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Internet users percentage of population 2014</th>\n",
       "      <td>0.807354</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              Life expectancy at birth- years  \\\n",
       "Life expectancy at birth- years                                      1.000000   \n",
       "Internet users percentage of population 2014                         0.807354   \n",
       "\n",
       "                                              Internet users percentage of population 2014  \n",
       "Life expectancy at birth- years                                                   0.807354  \n",
       "Internet users percentage of population 2014                                      1.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind = 'scatter', x = 'Life expectancy at birth- years', y = 'Internet users percentage of population 2014')\n",
    "# 상관계수 출력하기\n",
    "df[['Life expectancy at birth- years','Internet users percentage of population 2014']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Forest area percentage of total land area 2012', ylabel='Carbon dioxide emissionsAverage annual growth'>"
      ]
     },
     "execution_count": 3,
     "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": [
    "df.plot(kind = 'scatter', x = 'Forest area percentage of total land area 2012', y = 'Carbon dioxide emissionsAverage annual growth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Internet users percentage of population 2014', ylabel='Forest area percentage of total land area 2012'>"
      ]
     },
     "execution_count": 4,
     "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": [
    "df.plot(kind = 'scatter', x = 'Internet users percentage of population 2014', y = 'Forest area percentage of total land area 2012')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Life expectancy at birth- years', ylabel='Carbon dioxide emissionsAverage annual growth'>"
      ]
     },
     "execution_count": 5,
     "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": [
    "df.plot(kind = 'scatter', x = 'Life expectancy at birth- years', y = 'Carbon dioxide emissionsAverage annual growth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Life expectancy at birth- years', ylabel='Forest area percentage of total land area 2012'>"
      ]
     },
     "execution_count": 6,
     "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": [
    "df.plot(kind = 'scatter', x = 'Life expectancy at birth- years', y = 'Forest area percentage of total land area 2012')"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}