lab/lab4.ipynb

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      "authorship_tag": "ABX9TyO1d65+6U2tGg+uMZOU/WsE",
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      "name": "python3",
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      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/drshahizan/Python_EDA/blob/main/lab/lab4.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Data Analysis for the current project is quite basic. It includes some minimal EDA and cleaning. A corresponding EDA Notebook is available in the project's repo."
      ],
      "metadata": {
        "id": "vAZWYfhfYfkQ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Libraries Import\n",
        "For the purpose of data loading and subsequent data cleaning we need standard Python libraries - Pandas and Numpy"
      ],
      "metadata": {
        "id": "669JlQSrSc29"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Importing libraries\n",
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "wlyWfvZUSkNt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Loading Data"
      ],
      "metadata": {
        "id": "OoWq4oCNSn8U"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Loading data from a cvs file\n",
        "data = pd.read_csv('https://raw.githubusercontent.com/drshahizan/dataset/main/led.csv')\n",
        "\n",
        "#Initial data check\n",
        "data.head(5)"
      ],
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          "height": 352
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              "       Country  Year      Status  Life expectancy   Adult Mortality  \\\n",
              "0  Afghanistan  2015  Developing              65.0            263.0   \n",
              "1  Afghanistan  2014  Developing              59.9            271.0   \n",
              "2  Afghanistan  2013  Developing              59.9            268.0   \n",
              "3  Afghanistan  2012  Developing              59.5            272.0   \n",
              "4  Afghanistan  2011  Developing              59.2            275.0   \n",
              "\n",
              "   infant deaths  Alcohol  percentage expenditure  Hepatitis B  Measles   ...  \\\n",
              "0             62     0.01               71.279624         65.0      1154  ...   \n",
              "1             64     0.01               73.523582         62.0       492  ...   \n",
              "2             66     0.01               73.219243         64.0       430  ...   \n",
              "3             69     0.01               78.184215         67.0      2787  ...   \n",
              "4             71     0.01                7.097109         68.0      3013  ...   \n",
              "\n",
              "   Polio  Total expenditure  Diphtheria    HIV/AIDS         GDP  Population  \\\n",
              "0    6.0               8.16         65.0        0.1  584.259210  33736494.0   \n",
              "1   58.0               8.18         62.0        0.1  612.696514    327582.0   \n",
              "2   62.0               8.13         64.0        0.1  631.744976  31731688.0   \n",
              "3   67.0               8.52         67.0        0.1  669.959000   3696958.0   \n",
              "4   68.0               7.87         68.0        0.1   63.537231   2978599.0   \n",
              "\n",
              "    thinness  1-19 years   thinness 5-9 years  \\\n",
              "0                   17.2                 17.3   \n",
              "1                   17.5                 17.5   \n",
              "2                   17.7                 17.7   \n",
              "3                   17.9                 18.0   \n",
              "4                   18.2                 18.2   \n",
              "\n",
              "   Income composition of resources  Schooling  \n",
              "0                            0.479       10.1  \n",
              "1                            0.476       10.0  \n",
              "2                            0.470        9.9  \n",
              "3                            0.463        9.8  \n",
              "4                            0.454        9.5  \n",
              "\n",
              "[5 rows x 22 columns]"
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              "      <th>Country</th>\n",
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              "      <td>Afghanistan</td>\n",
              "      <td>2015</td>\n",
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              "      <td>263.0</td>\n",
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              "      <td>17.2</td>\n",
              "      <td>17.3</td>\n",
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              "      <th>1</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2014</td>\n",
              "      <td>Developing</td>\n",
              "      <td>59.9</td>\n",
              "      <td>271.0</td>\n",
              "      <td>64</td>\n",
              "      <td>0.01</td>\n",
              "      <td>73.523582</td>\n",
              "      <td>62.0</td>\n",
              "      <td>492</td>\n",
              "      <td>...</td>\n",
              "      <td>58.0</td>\n",
              "      <td>8.18</td>\n",
              "      <td>62.0</td>\n",
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              "      <td>612.696514</td>\n",
              "      <td>327582.0</td>\n",
              "      <td>17.5</td>\n",
              "      <td>17.5</td>\n",
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              "      <td>10.0</td>\n",
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              "      <th>2</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>59.9</td>\n",
              "      <td>268.0</td>\n",
              "      <td>66</td>\n",
              "      <td>0.01</td>\n",
              "      <td>73.219243</td>\n",
              "      <td>64.0</td>\n",
              "      <td>430</td>\n",
              "      <td>...</td>\n",
              "      <td>62.0</td>\n",
              "      <td>8.13</td>\n",
              "      <td>64.0</td>\n",
              "      <td>0.1</td>\n",
              "      <td>631.744976</td>\n",
              "      <td>31731688.0</td>\n",
              "      <td>17.7</td>\n",
              "      <td>17.7</td>\n",
              "      <td>0.470</td>\n",
              "      <td>9.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2012</td>\n",
              "      <td>Developing</td>\n",
              "      <td>59.5</td>\n",
              "      <td>272.0</td>\n",
              "      <td>69</td>\n",
              "      <td>0.01</td>\n",
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              "      <td>3696958.0</td>\n",
              "      <td>17.9</td>\n",
              "      <td>18.0</td>\n",
              "      <td>0.463</td>\n",
              "      <td>9.8</td>\n",
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              "      <th>4</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2011</td>\n",
              "      <td>Developing</td>\n",
              "      <td>59.2</td>\n",
              "      <td>275.0</td>\n",
              "      <td>71</td>\n",
              "      <td>0.01</td>\n",
              "      <td>7.097109</td>\n",
              "      <td>68.0</td>\n",
              "      <td>3013</td>\n",
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              "      <td>68.0</td>\n",
              "      <td>7.87</td>\n",
              "      <td>68.0</td>\n",
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              "      <td>2978599.0</td>\n",
              "      <td>18.2</td>\n",
              "      <td>18.2</td>\n",
              "      <td>0.454</td>\n",
              "      <td>9.5</td>\n",
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Exploring Data"
      ],
      "metadata": {
        "id": "Km7JWPOTS2L_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Checking unique countries number\n",
        "data['Country'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uxYeaYhYS0d_",
        "outputId": "4e31c958-6b42-4a5a-8aa7-a78b9cd07a2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Afghanistan', 'Albania', 'Algeria', 'Angola',\n",
              "       'Antigua and Barbuda', 'Argentina', 'Armenia', 'Australia',\n",
              "       'Austria', 'Azerbaijan', 'Bahamas', 'Bahrain', 'Bangladesh',\n",
              "       'Barbados', 'Belarus', 'Belgium', 'Belize', 'Benin', 'Bhutan',\n",
              "       'Bolivia (Plurinational State of)', 'Bosnia and Herzegovina',\n",
              "       'Botswana', 'Brazil', 'Brunei Darussalam', 'Bulgaria',\n",
              "       'Burkina Faso', 'Burundi', \"Côte d'Ivoire\", 'Cabo Verde',\n",
              "       'Cambodia', 'Cameroon', 'Canada', 'Central African Republic',\n",
              "       'Chad', 'Chile', 'China', 'Colombia', 'Comoros', 'Congo',\n",
              "       'Cook Islands', 'Costa Rica', 'Croatia', 'Cuba', 'Cyprus',\n",
              "       'Czechia', \"Democratic People's Republic of Korea\",\n",
              "       'Democratic Republic of the Congo', 'Denmark', 'Djibouti',\n",
              "       'Dominica', 'Dominican Republic', 'Ecuador', 'Egypt',\n",
              "       'El Salvador', 'Equatorial Guinea', 'Eritrea', 'Estonia',\n",
              "       'Ethiopia', 'Fiji', 'Finland', 'France', 'Gabon', 'Gambia',\n",
              "       'Georgia', 'Germany', 'Ghana', 'Greece', 'Grenada', 'Guatemala',\n",
              "       'Guinea', 'Guinea-Bissau', 'Guyana', 'Haiti', 'Honduras',\n",
              "       'Hungary', 'Iceland', 'India', 'Indonesia',\n",
              "       'Iran (Islamic Republic of)', 'Iraq', 'Ireland', 'Israel', 'Italy',\n",
              "       'Jamaica', 'Japan', 'Jordan', 'Kazakhstan', 'Kenya', 'Kiribati',\n",
              "       'Kuwait', 'Kyrgyzstan', \"Lao People's Democratic Republic\",\n",
              "       'Latvia', 'Lebanon', 'Lesotho', 'Liberia', 'Libya', 'Lithuania',\n",
              "       'Luxembourg', 'Madagascar', 'Malawi', 'Malaysia', 'Maldives',\n",
              "       'Mali', 'Malta', 'Marshall Islands', 'Mauritania', 'Mauritius',\n",
              "       'Mexico', 'Micronesia (Federated States of)', 'Monaco', 'Mongolia',\n",
              "       'Montenegro', 'Morocco', 'Mozambique', 'Myanmar', 'Namibia',\n",
              "       'Nauru', 'Nepal', 'Netherlands', 'New Zealand', 'Nicaragua',\n",
              "       'Niger', 'Nigeria', 'Niue', 'Norway', 'Oman', 'Pakistan', 'Palau',\n",
              "       'Panama', 'Papua New Guinea', 'Paraguay', 'Peru', 'Philippines',\n",
              "       'Poland', 'Portugal', 'Qatar', 'Republic of Korea',\n",
              "       'Republic of Moldova', 'Romania', 'Russian Federation', 'Rwanda',\n",
              "       'Saint Kitts and Nevis', 'Saint Lucia',\n",
              "       'Saint Vincent and the Grenadines', 'Samoa', 'San Marino',\n",
              "       'Sao Tome and Principe', 'Saudi Arabia', 'Senegal', 'Serbia',\n",
              "       'Seychelles', 'Sierra Leone', 'Singapore', 'Slovakia', 'Slovenia',\n",
              "       'Solomon Islands', 'Somalia', 'South Africa', 'South Sudan',\n",
              "       'Spain', 'Sri Lanka', 'Sudan', 'Suriname', 'Swaziland', 'Sweden',\n",
              "       'Switzerland', 'Syrian Arab Republic', 'Tajikistan', 'Thailand',\n",
              "       'The former Yugoslav republic of Macedonia', 'Timor-Leste', 'Togo',\n",
              "       'Tonga', 'Trinidad and Tobago', 'Tunisia', 'Turkey',\n",
              "       'Turkmenistan', 'Tuvalu', 'Uganda', 'Ukraine',\n",
              "       'United Arab Emirates',\n",
              "       'United Kingdom of Great Britain and Northern Ireland',\n",
              "       'United Republic of Tanzania', 'United States of America',\n",
              "       'Uruguay', 'Uzbekistan', 'Vanuatu',\n",
              "       'Venezuela (Bolivarian Republic of)', 'Viet Nam', 'Yemen',\n",
              "       'Zambia', 'Zimbabwe'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of unique countries represented in the dataset\n",
        "len(data['Country'].unique())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i-40bwDZTP9J",
        "outputId": "63ab8035-41a4-4248-d4c7-adc7046db01d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "193"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "#Getting info on our data\n",
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gq5lUdDMTVej",
        "outputId": "af477ec6-f616-4c4c-b2bd-4fb07acba0d6"
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      "execution_count": null,
      "outputs": [
        {
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 2938 entries, 0 to 2937\n",
            "Data columns (total 22 columns):\n",
            " #   Column                           Non-Null Count  Dtype  \n",
            "---  ------                           --------------  -----  \n",
            " 0   Country                          2938 non-null   object \n",
            " 1   Year                             2938 non-null   int64  \n",
            " 2   Status                           2938 non-null   object \n",
            " 3   Life expectancy                  2928 non-null   float64\n",
            " 4   Adult Mortality                  2928 non-null   float64\n",
            " 5   infant deaths                    2938 non-null   int64  \n",
            " 6   Alcohol                          2744 non-null   float64\n",
            " 7   percentage expenditure           2938 non-null   float64\n",
            " 8   Hepatitis B                      2385 non-null   float64\n",
            " 9   Measles                          2938 non-null   int64  \n",
            " 10   BMI                             2904 non-null   float64\n",
            " 11  under-five deaths                2938 non-null   int64  \n",
            " 12  Polio                            2919 non-null   float64\n",
            " 13  Total expenditure                2712 non-null   float64\n",
            " 14  Diphtheria                       2919 non-null   float64\n",
            " 15   HIV/AIDS                        2938 non-null   float64\n",
            " 16  GDP                              2490 non-null   float64\n",
            " 17  Population                       2286 non-null   float64\n",
            " 18   thinness  1-19 years            2904 non-null   float64\n",
            " 19   thinness 5-9 years              2904 non-null   float64\n",
            " 20  Income composition of resources  2771 non-null   float64\n",
            " 21  Schooling                        2775 non-null   float64\n",
            "dtypes: float64(16), int64(4), object(2)\n",
            "memory usage: 505.1+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Numerical fields \n",
        "data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "7COxcUQvTaPF",
        "outputId": "94a69670-1acf-4aa5-b99a-300a3c0f6c96"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Year  Life expectancy   Adult Mortality  infant deaths  \\\n",
              "count  2938.000000       2928.000000      2928.000000    2938.000000   \n",
              "mean   2007.518720         69.224932       164.796448      30.303948   \n",
              "std       4.613841          9.523867       124.292079     117.926501   \n",
              "min    2000.000000         36.300000         1.000000       0.000000   \n",
              "25%    2004.000000         63.100000        74.000000       0.000000   \n",
              "50%    2008.000000         72.100000       144.000000       3.000000   \n",
              "75%    2012.000000         75.700000       228.000000      22.000000   \n",
              "max    2015.000000         89.000000       723.000000    1800.000000   \n",
              "\n",
              "           Alcohol  percentage expenditure  Hepatitis B       Measles   \\\n",
              "count  2744.000000             2938.000000  2385.000000    2938.000000   \n",
              "mean      4.602861              738.251295    80.940461    2419.592240   \n",
              "std       4.052413             1987.914858    25.070016   11467.272489   \n",
              "min       0.010000                0.000000     1.000000       0.000000   \n",
              "25%       0.877500                4.685343    77.000000       0.000000   \n",
              "50%       3.755000               64.912906    92.000000      17.000000   \n",
              "75%       7.702500              441.534144    97.000000     360.250000   \n",
              "max      17.870000            19479.911610    99.000000  212183.000000   \n",
              "\n",
              "              BMI   under-five deaths         Polio  Total expenditure  \\\n",
              "count  2904.000000         2938.000000  2919.000000         2712.00000   \n",
              "mean     38.321247           42.035739    82.550188            5.93819   \n",
              "std      20.044034          160.445548    23.428046            2.49832   \n",
              "min       1.000000            0.000000     3.000000            0.37000   \n",
              "25%      19.300000            0.000000    78.000000            4.26000   \n",
              "50%      43.500000            4.000000    93.000000            5.75500   \n",
              "75%      56.200000           28.000000    97.000000            7.49250   \n",
              "max      87.300000         2500.000000    99.000000           17.60000   \n",
              "\n",
              "       Diphtheria      HIV/AIDS            GDP    Population  \\\n",
              "count  2919.000000  2938.000000    2490.000000  2.286000e+03   \n",
              "mean     82.324084     1.742103    7483.158469  1.275338e+07   \n",
              "std      23.716912     5.077785   14270.169342  6.101210e+07   \n",
              "min       2.000000     0.100000       1.681350  3.400000e+01   \n",
              "25%      78.000000     0.100000     463.935626  1.957932e+05   \n",
              "50%      93.000000     0.100000    1766.947595  1.386542e+06   \n",
              "75%      97.000000     0.800000    5910.806335  7.420359e+06   \n",
              "max      99.000000    50.600000  119172.741800  1.293859e+09   \n",
              "\n",
              "        thinness  1-19 years   thinness 5-9 years  \\\n",
              "count            2904.000000          2904.000000   \n",
              "mean                4.839704             4.870317   \n",
              "std                 4.420195             4.508882   \n",
              "min                 0.100000             0.100000   \n",
              "25%                 1.600000             1.500000   \n",
              "50%                 3.300000             3.300000   \n",
              "75%                 7.200000             7.200000   \n",
              "max                27.700000            28.600000   \n",
              "\n",
              "       Income composition of resources    Schooling  \n",
              "count                      2771.000000  2775.000000  \n",
              "mean                          0.627551    11.992793  \n",
              "std                           0.210904     3.358920  \n",
              "min                           0.000000     0.000000  \n",
              "25%                           0.493000    10.100000  \n",
              "50%                           0.677000    12.300000  \n",
              "75%                           0.779000    14.300000  \n",
              "max                           0.948000    20.700000  "
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Life expectancy</th>\n",
              "      <th>Adult Mortality</th>\n",
              "      <th>infant deaths</th>\n",
              "      <th>Alcohol</th>\n",
              "      <th>percentage expenditure</th>\n",
              "      <th>Hepatitis B</th>\n",
              "      <th>Measles</th>\n",
              "      <th>BMI</th>\n",
              "      <th>under-five deaths</th>\n",
              "      <th>Polio</th>\n",
              "      <th>Total expenditure</th>\n",
              "      <th>Diphtheria</th>\n",
              "      <th>HIV/AIDS</th>\n",
              "      <th>GDP</th>\n",
              "      <th>Population</th>\n",
              "      <th>thinness  1-19 years</th>\n",
              "      <th>thinness 5-9 years</th>\n",
              "      <th>Income composition of resources</th>\n",
              "      <th>Schooling</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>2938.000000</td>\n",
              "      <td>2928.000000</td>\n",
              "      <td>2928.000000</td>\n",
              "      <td>2938.000000</td>\n",
              "      <td>2744.000000</td>\n",
              "      <td>2938.000000</td>\n",
              "      <td>2385.000000</td>\n",
              "      <td>2938.000000</td>\n",
              "      <td>2904.000000</td>\n",
              "      <td>2938.000000</td>\n",
              "      <td>2919.000000</td>\n",
              "      <td>2712.00000</td>\n",
              "      <td>2919.000000</td>\n",
              "      <td>2938.000000</td>\n",
              "      <td>2490.000000</td>\n",
              "      <td>2.286000e+03</td>\n",
              "      <td>2904.000000</td>\n",
              "      <td>2904.000000</td>\n",
              "      <td>2771.000000</td>\n",
              "      <td>2775.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2007.518720</td>\n",
              "      <td>69.224932</td>\n",
              "      <td>164.796448</td>\n",
              "      <td>30.303948</td>\n",
              "      <td>4.602861</td>\n",
              "      <td>738.251295</td>\n",
              "      <td>80.940461</td>\n",
              "      <td>2419.592240</td>\n",
              "      <td>38.321247</td>\n",
              "      <td>42.035739</td>\n",
              "      <td>82.550188</td>\n",
              "      <td>5.93819</td>\n",
              "      <td>82.324084</td>\n",
              "      <td>1.742103</td>\n",
              "      <td>7483.158469</td>\n",
              "      <td>1.275338e+07</td>\n",
              "      <td>4.839704</td>\n",
              "      <td>4.870317</td>\n",
              "      <td>0.627551</td>\n",
              "      <td>11.992793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>4.613841</td>\n",
              "      <td>9.523867</td>\n",
              "      <td>124.292079</td>\n",
              "      <td>117.926501</td>\n",
              "      <td>4.052413</td>\n",
              "      <td>1987.914858</td>\n",
              "      <td>25.070016</td>\n",
              "      <td>11467.272489</td>\n",
              "      <td>20.044034</td>\n",
              "      <td>160.445548</td>\n",
              "      <td>23.428046</td>\n",
              "      <td>2.49832</td>\n",
              "      <td>23.716912</td>\n",
              "      <td>5.077785</td>\n",
              "      <td>14270.169342</td>\n",
              "      <td>6.101210e+07</td>\n",
              "      <td>4.420195</td>\n",
              "      <td>4.508882</td>\n",
              "      <td>0.210904</td>\n",
              "      <td>3.358920</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>2000.000000</td>\n",
              "      <td>36.300000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.37000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>1.681350</td>\n",
              "      <td>3.400000e+01</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2004.000000</td>\n",
              "      <td>63.100000</td>\n",
              "      <td>74.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.877500</td>\n",
              "      <td>4.685343</td>\n",
              "      <td>77.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>19.300000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>78.000000</td>\n",
              "      <td>4.26000</td>\n",
              "      <td>78.000000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>463.935626</td>\n",
              "      <td>1.957932e+05</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>1.500000</td>\n",
              "      <td>0.493000</td>\n",
              "      <td>10.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2008.000000</td>\n",
              "      <td>72.100000</td>\n",
              "      <td>144.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.755000</td>\n",
              "      <td>64.912906</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>43.500000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>93.000000</td>\n",
              "      <td>5.75500</td>\n",
              "      <td>93.000000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>1766.947595</td>\n",
              "      <td>1.386542e+06</td>\n",
              "      <td>3.300000</td>\n",
              "      <td>3.300000</td>\n",
              "      <td>0.677000</td>\n",
              "      <td>12.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2012.000000</td>\n",
              "      <td>75.700000</td>\n",
              "      <td>228.000000</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>7.702500</td>\n",
              "      <td>441.534144</td>\n",
              "      <td>97.000000</td>\n",
              "      <td>360.250000</td>\n",
              "      <td>56.200000</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>97.000000</td>\n",
              "      <td>7.49250</td>\n",
              "      <td>97.000000</td>\n",
              "      <td>0.800000</td>\n",
              "      <td>5910.806335</td>\n",
              "      <td>7.420359e+06</td>\n",
              "      <td>7.200000</td>\n",
              "      <td>7.200000</td>\n",
              "      <td>0.779000</td>\n",
              "      <td>14.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2015.000000</td>\n",
              "      <td>89.000000</td>\n",
              "      <td>723.000000</td>\n",
              "      <td>1800.000000</td>\n",
              "      <td>17.870000</td>\n",
              "      <td>19479.911610</td>\n",
              "      <td>99.000000</td>\n",
              "      <td>212183.000000</td>\n",
              "      <td>87.300000</td>\n",
              "      <td>2500.000000</td>\n",
              "      <td>99.000000</td>\n",
              "      <td>17.60000</td>\n",
              "      <td>99.000000</td>\n",
              "      <td>50.600000</td>\n",
              "      <td>119172.741800</td>\n",
              "      <td>1.293859e+09</td>\n",
              "      <td>27.700000</td>\n",
              "      <td>28.600000</td>\n",
              "      <td>0.948000</td>\n",
              "      <td>20.700000</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Countries are divided into 'Developed' and 'Developing' in the 'Status' field\n",
        "data['Status'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x9kZg-24TekQ",
        "outputId": "1199f8c4-a8e0-4612-976d-dfa13fbdfb9e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Developing', 'Developed'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#List of developed countries\n",
        "data[data['Status']=='Developed']['Country'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W8knGVBQTjD1",
        "outputId": "c9652ce6-123b-4be7-d2c2-669bb13b11b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Australia', 'Austria', 'Belgium', 'Bulgaria', 'Croatia', 'Cyprus',\n",
              "       'Czechia', 'Denmark', 'Germany', 'Hungary', 'Iceland', 'Ireland',\n",
              "       'Italy', 'Japan', 'Latvia', 'Lithuania', 'Luxembourg', 'Malta',\n",
              "       'Netherlands', 'New Zealand', 'Norway', 'Poland', 'Portugal',\n",
              "       'Romania', 'Singapore', 'Slovakia', 'Slovenia', 'Spain', 'Sweden',\n",
              "       'Switzerland',\n",
              "       'United Kingdom of Great Britain and Northern Ireland',\n",
              "       'United States of America'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "It must be noted a list of developed countries automatically includes all the EU countries + Australia, Japan, New Zealand, Norway, Singapore, Switzerland and the US.\n",
        "\n",
        "It is a bit surprising it includes relatively poor countries such as Romania and Bulgaria, but does not include Canada and South Korea, for example.\n",
        "\n",
        "For each country we have the following data fields:"
      ],
      "metadata": {
        "id": "gHfs1zs1TpKR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Getting data fields\n",
        "data.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2El8bBZsTql5",
        "outputId": "25194eeb-74cf-4547-9e2e-43cbe449f19e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Country', 'Year', 'Status', 'Life expectancy ', 'Adult Mortality',\n",
              "       'infant deaths', 'Alcohol', 'percentage expenditure', 'Hepatitis B',\n",
              "       'Measles ', ' BMI ', 'under-five deaths ', 'Polio', 'Total expenditure',\n",
              "       'Diphtheria ', ' HIV/AIDS', 'GDP', 'Population',\n",
              "       ' thinness  1-19 years', ' thinness 5-9 years',\n",
              "       'Income composition of resources', 'Schooling'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Bringing filed names to consistency\n",
        "data.columns = [column.lower().strip() for column in data.columns]"
      ],
      "metadata": {
        "id": "SGMl6EDdTxYE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Let's look at particular countries' data.\n",
        "\n"
      ],
      "metadata": {
        "id": "Z1ZN3Z33T7jl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Romania\n",
        "data[data['country']=='Romania'][['country' ,'year', 'status', 'life expectancy',\n",
        "       'infant deaths', 'alcohol',  'bmi',    'gdp', 'population'\n",
        "      ]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "id": "QUZcOvA1T1Or",
        "outputId": "109aa131-d073-4623-997e-03f87042932e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      country  year     status  life expectancy  infant deaths  alcohol   bmi  \\\n",
              "2119  Romania  2015  Developed             75.0              2      NaN   6.7   \n",
              "2120  Romania  2014  Developed             74.8              2     0.01  59.9   \n",
              "2121  Romania  2013  Developed             74.6              2     9.59  59.2   \n",
              "2122  Romania  2012  Developed             74.4              2     9.58  58.4   \n",
              "2123  Romania  2011  Developed             74.3              2     9.10  57.7   \n",
              "2124  Romania  2010  Developed             73.4              2     9.00  56.9   \n",
              "2125  Romania  2009  Developed             73.1              2    10.40  56.3   \n",
              "2126  Romania  2008  Developed             73.1              2    11.90  55.6   \n",
              "2127  Romania  2007  Developed             72.9              3    10.60  55.0   \n",
              "2128  Romania  2006  Developed             72.5              3     8.51  54.4   \n",
              "2129  Romania  2005  Developed             71.9              3     7.68  53.9   \n",
              "2130  Romania  2004  Developed             71.7              4     9.82  53.4   \n",
              "2131  Romania  2003  Developed             71.1              4     8.78  52.9   \n",
              "2132  Romania  2002  Developed             77.0              4     9.62  52.4   \n",
              "2133  Romania  2001  Developed             78.0              4     9.78  51.9   \n",
              "2134  Romania  2000  Developed             77.0              4    10.16  51.4   \n",
              "\n",
              "              gdp  population  \n",
              "2119  8958.788593  19815481.0  \n",
              "2120    12.277330   1998979.0  \n",
              "2121  9585.266593  19983693.0  \n",
              "2122  8558.397660     25835.0  \n",
              "2123    92.277825   2147528.0  \n",
              "2124  8297.483621   2246871.0  \n",
              "2125   822.183290   2367487.0  \n",
              "2126  1136.473560   2537875.0  \n",
              "2127  8214.185378   2882982.0  \n",
              "2128  5828.745662   2119376.0  \n",
              "2129  4676.315183  21319685.0  \n",
              "2130  3552.924520  21451748.0  \n",
              "2131  2774.955860  21574326.0  \n",
              "2132  2124.873613   2173496.0  \n",
              "2133  1839.729450   2213197.0  \n",
              "2134  1668.162731  22442971.0  "
            ],
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              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>year</th>\n",
              "      <th>status</th>\n",
              "      <th>life expectancy</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2119</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2015</td>\n",
              "      <td>Developed</td>\n",
              "      <td>75.0</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>8958.788593</td>\n",
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              "      <th>2120</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2014</td>\n",
              "      <td>Developed</td>\n",
              "      <td>74.8</td>\n",
              "      <td>2</td>\n",
              "      <td>0.01</td>\n",
              "      <td>59.9</td>\n",
              "      <td>12.277330</td>\n",
              "      <td>1998979.0</td>\n",
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              "    <tr>\n",
              "      <th>2121</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developed</td>\n",
              "      <td>74.6</td>\n",
              "      <td>2</td>\n",
              "      <td>9.59</td>\n",
              "      <td>59.2</td>\n",
              "      <td>9585.266593</td>\n",
              "      <td>19983693.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2122</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2012</td>\n",
              "      <td>Developed</td>\n",
              "      <td>74.4</td>\n",
              "      <td>2</td>\n",
              "      <td>9.58</td>\n",
              "      <td>58.4</td>\n",
              "      <td>8558.397660</td>\n",
              "      <td>25835.0</td>\n",
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              "    <tr>\n",
              "      <th>2123</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2011</td>\n",
              "      <td>Developed</td>\n",
              "      <td>74.3</td>\n",
              "      <td>2</td>\n",
              "      <td>9.10</td>\n",
              "      <td>57.7</td>\n",
              "      <td>92.277825</td>\n",
              "      <td>2147528.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2124</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2010</td>\n",
              "      <td>Developed</td>\n",
              "      <td>73.4</td>\n",
              "      <td>2</td>\n",
              "      <td>9.00</td>\n",
              "      <td>56.9</td>\n",
              "      <td>8297.483621</td>\n",
              "      <td>2246871.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2125</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2009</td>\n",
              "      <td>Developed</td>\n",
              "      <td>73.1</td>\n",
              "      <td>2</td>\n",
              "      <td>10.40</td>\n",
              "      <td>56.3</td>\n",
              "      <td>822.183290</td>\n",
              "      <td>2367487.0</td>\n",
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              "    <tr>\n",
              "      <th>2126</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2008</td>\n",
              "      <td>Developed</td>\n",
              "      <td>73.1</td>\n",
              "      <td>2</td>\n",
              "      <td>11.90</td>\n",
              "      <td>55.6</td>\n",
              "      <td>1136.473560</td>\n",
              "      <td>2537875.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2127</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2007</td>\n",
              "      <td>Developed</td>\n",
              "      <td>72.9</td>\n",
              "      <td>3</td>\n",
              "      <td>10.60</td>\n",
              "      <td>55.0</td>\n",
              "      <td>8214.185378</td>\n",
              "      <td>2882982.0</td>\n",
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              "    <tr>\n",
              "      <th>2128</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2006</td>\n",
              "      <td>Developed</td>\n",
              "      <td>72.5</td>\n",
              "      <td>3</td>\n",
              "      <td>8.51</td>\n",
              "      <td>54.4</td>\n",
              "      <td>5828.745662</td>\n",
              "      <td>2119376.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2129</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2005</td>\n",
              "      <td>Developed</td>\n",
              "      <td>71.9</td>\n",
              "      <td>3</td>\n",
              "      <td>7.68</td>\n",
              "      <td>53.9</td>\n",
              "      <td>4676.315183</td>\n",
              "      <td>21319685.0</td>\n",
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              "    <tr>\n",
              "      <th>2130</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2004</td>\n",
              "      <td>Developed</td>\n",
              "      <td>71.7</td>\n",
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              "      <td>3552.924520</td>\n",
              "      <td>21451748.0</td>\n",
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              "    <tr>\n",
              "      <th>2131</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2003</td>\n",
              "      <td>Developed</td>\n",
              "      <td>71.1</td>\n",
              "      <td>4</td>\n",
              "      <td>8.78</td>\n",
              "      <td>52.9</td>\n",
              "      <td>2774.955860</td>\n",
              "      <td>21574326.0</td>\n",
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              "    <tr>\n",
              "      <th>2132</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2002</td>\n",
              "      <td>Developed</td>\n",
              "      <td>77.0</td>\n",
              "      <td>4</td>\n",
              "      <td>9.62</td>\n",
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              "      <td>2124.873613</td>\n",
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              "    <tr>\n",
              "      <th>2133</th>\n",
              "      <td>Romania</td>\n",
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              "      <td>Developed</td>\n",
              "      <td>78.0</td>\n",
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              "      <td>9.78</td>\n",
              "      <td>51.9</td>\n",
              "      <td>1839.729450</td>\n",
              "      <td>2213197.0</td>\n",
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              "    <tr>\n",
              "      <th>2134</th>\n",
              "      <td>Romania</td>\n",
              "      <td>2000</td>\n",
              "      <td>Developed</td>\n",
              "      <td>77.0</td>\n",
              "      <td>4</td>\n",
              "      <td>10.16</td>\n",
              "      <td>51.4</td>\n",
              "      <td>1668.162731</td>\n",
              "      <td>22442971.0</td>\n",
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          },
          "metadata": {},
          "execution_count": 12
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Canada\n",
        "data[data['country']=='Canada'][['country' ,'year', 'status', 'life expectancy',\n",
        "       'infant deaths', 'alcohol',  'bmi',    'gdp', 'population'\n",
        "      ]]"
      ],
      "metadata": {
        "colab": {
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          "height": 551
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        "id": "8WvNF6stT_z4",
        "outputId": "17d29d0d-27b6-41a2-a044-7f42ad5e2c47"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    country  year      status  life expectancy  infant deaths  alcohol   bmi  \\\n",
              "496  Canada  2015  Developing             82.2              2      NaN  67.0   \n",
              "497  Canada  2014  Developing             82.0              2      8.1  66.4   \n",
              "498  Canada  2013  Developing             81.8              2      8.2  65.8   \n",
              "499  Canada  2012  Developing             81.6              2      8.3  65.3   \n",
              "500  Canada  2011  Developing             81.5              2      8.2  64.7   \n",
              "501  Canada  2010  Developing             81.2              2      8.4  64.1   \n",
              "502  Canada  2009  Developing             81.0              2      8.4  63.6   \n",
              "503  Canada  2008  Developing             87.0              2      8.3  63.0   \n",
              "504  Canada  2007  Developing             85.0              2      8.3  62.5   \n",
              "505  Canada  2006  Developing             85.0              2      8.2  61.9   \n",
              "506  Canada  2005  Developing             81.0              2      8.0  61.3   \n",
              "507  Canada  2004  Developing             80.0              2      7.8   6.6   \n",
              "508  Canada  2003  Developing             79.7              2      7.7   6.0   \n",
              "509  Canada  2002  Developing             79.5              2      7.7  59.3   \n",
              "510  Canada  2001  Developing             79.4              2      7.6  58.5   \n",
              "511  Canada  2000  Developing             79.1              2      7.6  57.8   \n",
              "\n",
              "             gdp  population  \n",
              "496  43315.74400   3584861.0  \n",
              "497    544.43376  35544564.0  \n",
              "498  52413.72116  35155451.0  \n",
              "499  52496.69487   3475545.0  \n",
              "500   5282.21760   3434278.0  \n",
              "501  47447.47620    345274.0  \n",
              "502   4773.45436  33628571.0  \n",
              "503  46596.33599  33245773.0  \n",
              "504  44544.52680  32887928.0  \n",
              "505   4386.69948    325755.0  \n",
              "506  36189.58838     32312.0  \n",
              "507  31979.87195     31995.0  \n",
              "508  28172.14883     31676.0  \n",
              "509  24167.84310     31362.0  \n",
              "510  23691.59472     31819.0  \n",
              "511  24124.16917     37697.0  "
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              "    <tr>\n",
              "      <th>496</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2015</td>\n",
              "      <td>Developing</td>\n",
              "      <td>82.2</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>67.0</td>\n",
              "      <td>43315.74400</td>\n",
              "      <td>3584861.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>497</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2014</td>\n",
              "      <td>Developing</td>\n",
              "      <td>82.0</td>\n",
              "      <td>2</td>\n",
              "      <td>8.1</td>\n",
              "      <td>66.4</td>\n",
              "      <td>544.43376</td>\n",
              "      <td>35544564.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>498</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>81.8</td>\n",
              "      <td>2</td>\n",
              "      <td>8.2</td>\n",
              "      <td>65.8</td>\n",
              "      <td>52413.72116</td>\n",
              "      <td>35155451.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>499</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2012</td>\n",
              "      <td>Developing</td>\n",
              "      <td>81.6</td>\n",
              "      <td>2</td>\n",
              "      <td>8.3</td>\n",
              "      <td>65.3</td>\n",
              "      <td>52496.69487</td>\n",
              "      <td>3475545.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>500</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2011</td>\n",
              "      <td>Developing</td>\n",
              "      <td>81.5</td>\n",
              "      <td>2</td>\n",
              "      <td>8.2</td>\n",
              "      <td>64.7</td>\n",
              "      <td>5282.21760</td>\n",
              "      <td>3434278.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2010</td>\n",
              "      <td>Developing</td>\n",
              "      <td>81.2</td>\n",
              "      <td>2</td>\n",
              "      <td>8.4</td>\n",
              "      <td>64.1</td>\n",
              "      <td>47447.47620</td>\n",
              "      <td>345274.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2009</td>\n",
              "      <td>Developing</td>\n",
              "      <td>81.0</td>\n",
              "      <td>2</td>\n",
              "      <td>8.4</td>\n",
              "      <td>63.6</td>\n",
              "      <td>4773.45436</td>\n",
              "      <td>33628571.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2008</td>\n",
              "      <td>Developing</td>\n",
              "      <td>87.0</td>\n",
              "      <td>2</td>\n",
              "      <td>8.3</td>\n",
              "      <td>63.0</td>\n",
              "      <td>46596.33599</td>\n",
              "      <td>33245773.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>504</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2007</td>\n",
              "      <td>Developing</td>\n",
              "      <td>85.0</td>\n",
              "      <td>2</td>\n",
              "      <td>8.3</td>\n",
              "      <td>62.5</td>\n",
              "      <td>44544.52680</td>\n",
              "      <td>32887928.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>505</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2006</td>\n",
              "      <td>Developing</td>\n",
              "      <td>85.0</td>\n",
              "      <td>2</td>\n",
              "      <td>8.2</td>\n",
              "      <td>61.9</td>\n",
              "      <td>4386.69948</td>\n",
              "      <td>325755.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>506</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2005</td>\n",
              "      <td>Developing</td>\n",
              "      <td>81.0</td>\n",
              "      <td>2</td>\n",
              "      <td>8.0</td>\n",
              "      <td>61.3</td>\n",
              "      <td>36189.58838</td>\n",
              "      <td>32312.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>507</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2004</td>\n",
              "      <td>Developing</td>\n",
              "      <td>80.0</td>\n",
              "      <td>2</td>\n",
              "      <td>7.8</td>\n",
              "      <td>6.6</td>\n",
              "      <td>31979.87195</td>\n",
              "      <td>31995.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>508</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2003</td>\n",
              "      <td>Developing</td>\n",
              "      <td>79.7</td>\n",
              "      <td>2</td>\n",
              "      <td>7.7</td>\n",
              "      <td>6.0</td>\n",
              "      <td>28172.14883</td>\n",
              "      <td>31676.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>509</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2002</td>\n",
              "      <td>Developing</td>\n",
              "      <td>79.5</td>\n",
              "      <td>2</td>\n",
              "      <td>7.7</td>\n",
              "      <td>59.3</td>\n",
              "      <td>24167.84310</td>\n",
              "      <td>31362.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>510</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2001</td>\n",
              "      <td>Developing</td>\n",
              "      <td>79.4</td>\n",
              "      <td>2</td>\n",
              "      <td>7.6</td>\n",
              "      <td>58.5</td>\n",
              "      <td>23691.59472</td>\n",
              "      <td>31819.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>511</th>\n",
              "      <td>Canada</td>\n",
              "      <td>2000</td>\n",
              "      <td>Developing</td>\n",
              "      <td>79.1</td>\n",
              "      <td>2</td>\n",
              "      <td>7.6</td>\n",
              "      <td>57.8</td>\n",
              "      <td>24124.16917</td>\n",
              "      <td>37697.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Missing Values"
      ],
      "metadata": {
        "id": "qH7ThaEgUFky"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Missing values stats\n",
        "data.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K3YNM10uUJRy",
        "outputId": "07a7f0e2-dda2-4c89-808c-8cd0195194bb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "country                              0\n",
              "year                                 0\n",
              "status                               0\n",
              "life expectancy                     10\n",
              "adult mortality                     10\n",
              "infant deaths                        0\n",
              "alcohol                            194\n",
              "percentage expenditure               0\n",
              "hepatitis b                        553\n",
              "measles                              0\n",
              "bmi                                 34\n",
              "under-five deaths                    0\n",
              "polio                               19\n",
              "total expenditure                  226\n",
              "diphtheria                          19\n",
              "hiv/aids                             0\n",
              "gdp                                448\n",
              "population                         652\n",
              "thinness  1-19 years                34\n",
              "thinness 5-9 years                  34\n",
              "income composition of resources    167\n",
              "schooling                          163\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Since the main purpose of this work is Bokeh visualization library demo, we could reduce our dataset's size without loosing consistency by omitting the fileds with the most missing values."
      ],
      "metadata": {
        "id": "U6hWfcPhUOO0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Reduced size dataset\n",
        "data_reduced = data[['country', 'year', 'status', 'life expectancy',\n",
        "       'measles', 'bmi', 'under-five deaths', 'polio', 'hiv/aids']]"
      ],
      "metadata": {
        "id": "m8LRly_kUPOV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Reduced size dataset's missing values stats\n",
        "data_reduced.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NMWtkfbJUUrZ",
        "outputId": "8465a885-94e1-4ad6-b87f-e5629ca9c06b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "country               0\n",
              "year                  0\n",
              "status                0\n",
              "life expectancy      10\n",
              "measles               0\n",
              "bmi                  34\n",
              "under-five deaths     0\n",
              "polio                19\n",
              "hiv/aids              0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Life expectancy\n",
        "data_reduced[data_reduced['life expectancy'].isna()==True]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "r0CmPd1dUY8y",
        "outputId": "410a0aa4-5ddf-4470-e3b7-a4dd5bb43636"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    country  year      status  life expectancy  measles   bmi  \\\n",
              "624            Cook Islands  2013  Developing              NaN        0  82.8   \n",
              "769                Dominica  2013  Developing              NaN        0  58.4   \n",
              "1650       Marshall Islands  2013  Developing              NaN        0  81.6   \n",
              "1715                 Monaco  2013  Developing              NaN        0   NaN   \n",
              "1812                  Nauru  2013  Developing              NaN        0  87.3   \n",
              "1909                   Niue  2013  Developing              NaN        0  77.3   \n",
              "1958                  Palau  2013  Developing              NaN        0  83.3   \n",
              "2167  Saint Kitts and Nevis  2013  Developing              NaN        0   5.2   \n",
              "2216             San Marino  2013  Developing              NaN        0   NaN   \n",
              "2713                 Tuvalu  2013  Developing              NaN        0  79.3   \n",
              "\n",
              "      under-five deaths  polio  hiv/aids  \n",
              "624                   0   98.0       0.1  \n",
              "769                   0   96.0       0.1  \n",
              "1650                  0   79.0       0.1  \n",
              "1715                  0   99.0       0.1  \n",
              "1812                  0   87.0       0.1  \n",
              "1909                  0   99.0       0.1  \n",
              "1958                  0   99.0       0.1  \n",
              "2167                  0   96.0       0.1  \n",
              "2216                  0   69.0       0.1  \n",
              "2713                  0    9.0       0.1  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>year</th>\n",
              "      <th>status</th>\n",
              "      <th>life expectancy</th>\n",
              "      <th>measles</th>\n",
              "      <th>bmi</th>\n",
              "      <th>under-five deaths</th>\n",
              "      <th>polio</th>\n",
              "      <th>hiv/aids</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>624</th>\n",
              "      <td>Cook Islands</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>82.8</td>\n",
              "      <td>0</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0.1</td>\n",
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              "    <tr>\n",
              "      <th>769</th>\n",
              "      <td>Dominica</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>58.4</td>\n",
              "      <td>0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>0.1</td>\n",
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              "    <tr>\n",
              "      <th>1650</th>\n",
              "      <td>Marshall Islands</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>81.6</td>\n",
              "      <td>0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>0.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1715</th>\n",
              "      <td>Monaco</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>0.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1812</th>\n",
              "      <td>Nauru</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>87.3</td>\n",
              "      <td>0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>0.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1909</th>\n",
              "      <td>Niue</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>77.3</td>\n",
              "      <td>0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>0.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1958</th>\n",
              "      <td>Palau</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>83.3</td>\n",
              "      <td>0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>0.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2167</th>\n",
              "      <td>Saint Kitts and Nevis</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>5.2</td>\n",
              "      <td>0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>0.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2216</th>\n",
              "      <td>San Marino</td>\n",
              "      <td>2013</td>\n",
              "      <td>Developing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>79.3</td>\n",
              "      <td>0</td>\n",
              "      <td>9.0</td>\n",
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          },
          "metadata": {},
          "execution_count": 17
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#BMI\n",
        "data_reduced[data_reduced['bmi'].isna()==True]"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "b0W6VILhUdOD",
        "outputId": "43041e96-3de5-4e5e-b069-33a59a6858d2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          country  year      status  life expectancy  measles  bmi  \\\n",
              "1715       Monaco  2013  Developing              NaN        0  NaN   \n",
              "2216   San Marino  2013  Developing              NaN        0  NaN   \n",
              "2409  South Sudan  2015  Developing             57.3      878  NaN   \n",
              "2410  South Sudan  2014  Developing             56.6      441  NaN   \n",
              "2411  South Sudan  2013  Developing             56.4      525  NaN   \n",
              "2412  South Sudan  2012  Developing             56.0     1952  NaN   \n",
              "2413  South Sudan  2011  Developing             55.4     1256  NaN   \n",
              "2414  South Sudan  2010  Developing             55.0        0  NaN   \n",
              "2415  South Sudan  2009  Developing             54.3        0  NaN   \n",
              "2416  South Sudan  2008  Developing             53.6        0  NaN   \n",
              "2417  South Sudan  2007  Developing             53.1        0  NaN   \n",
              "2418  South Sudan  2006  Developing             52.5        0  NaN   \n",
              "2419  South Sudan  2005  Developing             51.9        0  NaN   \n",
              "2420  South Sudan  2004  Developing             51.4        0  NaN   \n",
              "2421  South Sudan  2003  Developing             58.0        0  NaN   \n",
              "2422  South Sudan  2002  Developing             52.0        0  NaN   \n",
              "2423  South Sudan  2001  Developing             49.6        0  NaN   \n",
              "2424  South Sudan  2000  Developing             48.9        0  NaN   \n",
              "2457        Sudan  2015  Developing             64.1     3585  NaN   \n",
              "2458        Sudan  2014  Developing             63.8      676  NaN   \n",
              "2459        Sudan  2013  Developing             63.5     2813  NaN   \n",
              "2460        Sudan  2012  Developing             63.2     8523  NaN   \n",
              "2461        Sudan  2011  Developing             62.7     5616  NaN   \n",
              "2462        Sudan  2010  Developing             62.5      680  NaN   \n",
              "2463        Sudan  2009  Developing             62.0       68  NaN   \n",
              "2464        Sudan  2008  Developing             61.8      129  NaN   \n",
              "2465        Sudan  2007  Developing             61.4      327  NaN   \n",
              "2466        Sudan  2006  Developing             61.0      228  NaN   \n",
              "2467        Sudan  2005  Developing             67.0     1374  NaN   \n",
              "2468        Sudan  2004  Developing             59.7     9562  NaN   \n",
              "2469        Sudan  2003  Developing             59.6     4381  NaN   \n",
              "2470        Sudan  2002  Developing             59.4     4529  NaN   \n",
              "2471        Sudan  2001  Developing             58.9     4362  NaN   \n",
              "2472        Sudan  2000  Developing             58.6     2875  NaN   \n",
              "\n",
              "      under-five deaths  polio  hiv/aids  \n",
              "1715                  0   99.0       0.1  \n",
              "2216                  0   69.0       0.1  \n",
              "2409                 39   41.0       3.4  \n",
              "2410                 39   44.0       3.5  \n",
              "2411                 40    5.0       3.6  \n",
              "2412                 40   64.0       3.8  \n",
              "2413                 41   66.0       3.9  \n",
              "2414                 41    NaN       4.0  \n",
              "2415                 42    NaN       4.2  \n",
              "2416                 42    NaN       4.2  \n",
              "2417                 43    NaN       4.2  \n",
              "2418                 43    NaN       4.1  \n",
              "2419                 44    NaN       3.9  \n",
              "2420                 45    NaN       3.8  \n",
              "2421                 46    NaN       3.5  \n",
              "2422                 48    NaN       3.3  \n",
              "2423                 49    NaN       3.0  \n",
              "2424                 50    NaN       2.7  \n",
              "2457                 85   93.0       0.3  \n",
              "2458                 86   94.0       0.3  \n",
              "2459                 88   93.0       0.3  \n",
              "2460                 89   92.0       0.3  \n",
              "2461                 91   93.0       0.3  \n",
              "2462                 92    9.0       0.3  \n",
              "2463                 94   81.0       0.3  \n",
              "2464                 95   85.0       0.3  \n",
              "2465                 97   84.0       0.3  \n",
              "2466                 99   77.0       0.2  \n",
              "2467                101   78.0       0.2  \n",
              "2468                102   74.0       0.2  \n",
              "2469                104   69.0       0.2  \n",
              "2470                106    6.0       0.2  \n",
              "2471                108   66.0       0.2  \n",
              "2472                109   62.0       0.1  "
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              "      <th>2410</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <td>South Sudan</td>\n",
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              "      <th>2412</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <th>2413</th>\n",
              "      <td>South Sudan</td>\n",
              "      <td>2011</td>\n",
              "      <td>Developing</td>\n",
              "      <td>55.4</td>\n",
              "      <td>1256</td>\n",
              "      <td>NaN</td>\n",
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              "      <th>2414</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <td>Developing</td>\n",
              "      <td>55.0</td>\n",
              "      <td>0</td>\n",
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              "      <th>2415</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <td>Developing</td>\n",
              "      <td>54.3</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
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              "      <th>2416</th>\n",
              "      <td>South Sudan</td>\n",
              "      <td>2008</td>\n",
              "      <td>Developing</td>\n",
              "      <td>53.6</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>42</td>\n",
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              "      <th>2417</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <td>Developing</td>\n",
              "      <td>53.1</td>\n",
              "      <td>0</td>\n",
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              "      <td>South Sudan</td>\n",
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              "      <td>Sudan</td>\n",
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              "      <th>2463</th>\n",
              "      <td>Sudan</td>\n",
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              "      <td>62.0</td>\n",
              "      <td>68</td>\n",
              "      <td>NaN</td>\n",
              "      <td>94</td>\n",
              "      <td>81.0</td>\n",
              "      <td>0.3</td>\n",
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              "      <th>2464</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2008</td>\n",
              "      <td>Developing</td>\n",
              "      <td>61.8</td>\n",
              "      <td>129</td>\n",
              "      <td>NaN</td>\n",
              "      <td>95</td>\n",
              "      <td>85.0</td>\n",
              "      <td>0.3</td>\n",
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              "      <th>2465</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2007</td>\n",
              "      <td>Developing</td>\n",
              "      <td>61.4</td>\n",
              "      <td>327</td>\n",
              "      <td>NaN</td>\n",
              "      <td>97</td>\n",
              "      <td>84.0</td>\n",
              "      <td>0.3</td>\n",
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              "      <th>2466</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2006</td>\n",
              "      <td>Developing</td>\n",
              "      <td>61.0</td>\n",
              "      <td>228</td>\n",
              "      <td>NaN</td>\n",
              "      <td>99</td>\n",
              "      <td>77.0</td>\n",
              "      <td>0.2</td>\n",
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              "    <tr>\n",
              "      <th>2467</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2005</td>\n",
              "      <td>Developing</td>\n",
              "      <td>67.0</td>\n",
              "      <td>1374</td>\n",
              "      <td>NaN</td>\n",
              "      <td>101</td>\n",
              "      <td>78.0</td>\n",
              "      <td>0.2</td>\n",
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              "    <tr>\n",
              "      <th>2468</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2004</td>\n",
              "      <td>Developing</td>\n",
              "      <td>59.7</td>\n",
              "      <td>9562</td>\n",
              "      <td>NaN</td>\n",
              "      <td>102</td>\n",
              "      <td>74.0</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2469</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2003</td>\n",
              "      <td>Developing</td>\n",
              "      <td>59.6</td>\n",
              "      <td>4381</td>\n",
              "      <td>NaN</td>\n",
              "      <td>104</td>\n",
              "      <td>69.0</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2470</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2002</td>\n",
              "      <td>Developing</td>\n",
              "      <td>59.4</td>\n",
              "      <td>4529</td>\n",
              "      <td>NaN</td>\n",
              "      <td>106</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.2</td>\n",
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              "    <tr>\n",
              "      <th>2471</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2001</td>\n",
              "      <td>Developing</td>\n",
              "      <td>58.9</td>\n",
              "      <td>4362</td>\n",
              "      <td>NaN</td>\n",
              "      <td>108</td>\n",
              "      <td>66.0</td>\n",
              "      <td>0.2</td>\n",
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              "    <tr>\n",
              "      <th>2472</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>2000</td>\n",
              "      <td>Developing</td>\n",
              "      <td>58.6</td>\n",
              "      <td>2875</td>\n",
              "      <td>NaN</td>\n",
              "      <td>109</td>\n",
              "      <td>62.0</td>\n",
              "      <td>0.1</td>\n",
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          },
          "metadata": {},
          "execution_count": 18
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Polio\n",
        "data_reduced[data_reduced['polio'].isna()==True]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "f6-kQWWIUia2",
        "outputId": "a356ae4d-db19-4bed-c35c-2361b2e3335d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          country  year      status  life expectancy  measles   bmi  \\\n",
              "1742   Montenegro  2005  Developing             73.6        0  55.7   \n",
              "1743   Montenegro  2004  Developing             73.5        0  55.0   \n",
              "1744   Montenegro  2003  Developing             73.5        0  54.2   \n",
              "1745   Montenegro  2002  Developing             73.4        0  53.5   \n",
              "1746   Montenegro  2001  Developing             73.3        0  52.7   \n",
              "1747   Montenegro  2000  Developing             73.0        0  51.9   \n",
              "2414  South Sudan  2010  Developing             55.0        0   NaN   \n",
              "2415  South Sudan  2009  Developing             54.3        0   NaN   \n",
              "2416  South Sudan  2008  Developing             53.6        0   NaN   \n",
              "2417  South Sudan  2007  Developing             53.1        0   NaN   \n",
              "2418  South Sudan  2006  Developing             52.5        0   NaN   \n",
              "2419  South Sudan  2005  Developing             51.9        0   NaN   \n",
              "2420  South Sudan  2004  Developing             51.4        0   NaN   \n",
              "2421  South Sudan  2003  Developing             58.0        0   NaN   \n",
              "2422  South Sudan  2002  Developing             52.0        0   NaN   \n",
              "2423  South Sudan  2001  Developing             49.6        0   NaN   \n",
              "2424  South Sudan  2000  Developing             48.9        0   NaN   \n",
              "2615  Timor-Leste  2001  Developing             59.4        0  12.3   \n",
              "2616  Timor-Leste  2000  Developing             58.7        0  11.9   \n",
              "\n",
              "      under-five deaths  polio  hiv/aids  \n",
              "1742                  0    NaN       0.1  \n",
              "1743                  0    NaN       0.1  \n",
              "1744                  0    NaN       0.1  \n",
              "1745                  0    NaN       0.1  \n",
              "1746                  0    NaN       0.1  \n",
              "1747                  0    NaN       0.1  \n",
              "2414                 41    NaN       4.0  \n",
              "2415                 42    NaN       4.2  \n",
              "2416                 42    NaN       4.2  \n",
              "2417                 43    NaN       4.2  \n",
              "2418                 43    NaN       4.1  \n",
              "2419                 44    NaN       3.9  \n",
              "2420                 45    NaN       3.8  \n",
              "2421                 46    NaN       3.5  \n",
              "2422                 48    NaN       3.3  \n",
              "2423                 49    NaN       3.0  \n",
              "2424                 50    NaN       2.7  \n",
              "2615                  4    NaN       0.1  \n",
              "2616                  4    NaN       0.1  "
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              "      <th>1742</th>\n",
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              "      <td>Montenegro</td>\n",
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              "      <th>2414</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <td>55.0</td>\n",
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              "      <th>2415</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <td>South Sudan</td>\n",
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              "      <td>South Sudan</td>\n",
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              "      <th>2418</th>\n",
              "      <td>South Sudan</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0fec0c68-9517-4179-ab9b-a367ef513f98')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
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              "    .colab-df-convert:hover {\n",
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              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-0fec0c68-9517-4179-ab9b-a367ef513f98 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0fec0c68-9517-4179-ab9b-a367ef513f98');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "As one can see, missing values do not pose any significant threat to the idea of future dataset's use for vizulaization purposes, hence we could drop the data entries with missed fields entirely."
      ],
      "metadata": {
        "id": "fjVOXZVvUpyV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Dropping entries with missing values and creating a cleaned dataset\n",
        "data_clean = data_reduced.dropna()\n",
        "\n",
        "#Checking the clean dataset\n",
        "data_clean.isna().sum()"
      ],
      "metadata": {
        "id": "Lx3pZkb-Utse",
        "outputId": "38482200-c5c2-4f64-bb77-479277a8beea",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "country              0\n",
              "year                 0\n",
              "status               0\n",
              "life expectancy      0\n",
              "measles              0\n",
              "bmi                  0\n",
              "under-five deaths    0\n",
              "polio                0\n",
              "hiv/aids             0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    }
  ]
}