2021_OLYMPICS.ipynb

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  "metadata": {
    "colab": {
      "name": "2021 OLYMPICS",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyN5iC5i4eEoc1Jo4vQtUrQO",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/vishalpoonacha/Techwarts_Olympic-Dataset/blob/main/2021_OLYMPICS.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M2moi8FUeYtE"
      },
      "source": [
        "import numpy as np \n",
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "id": "amtC8PP8fuLs",
        "outputId": "d99f43de-d3b2-4646-9568-936a18d75e60"
      },
      "source": [
        "athletes=pd.read_excel('/content/Athletes.xlsx')\n",
        "coaches=pd.read_excel('/content/Coaches.xlsx')\n",
        "entriesGender=pd.read_excel('/content/EntriesGender.xlsx')\n",
        "medals=pd.read_excel('/content/Medals.xlsx')\n",
        "teams=pd.read_excel('/content/Teams.xlsx')\n",
        "athletes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>NOC</th>\n",
              "      <th>Discipline</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AALERUD Katrine</td>\n",
              "      <td>Norway</td>\n",
              "      <td>Cycling Road</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ABAD Nestor</td>\n",
              "      <td>Spain</td>\n",
              "      <td>Artistic Gymnastics</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ABAGNALE Giovanni</td>\n",
              "      <td>Italy</td>\n",
              "      <td>Rowing</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ABALDE Alberto</td>\n",
              "      <td>Spain</td>\n",
              "      <td>Basketball</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ABALDE Tamara</td>\n",
              "      <td>Spain</td>\n",
              "      <td>Basketball</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11080</th>\n",
              "      <td>ZWICKER Martin Detlef</td>\n",
              "      <td>Germany</td>\n",
              "      <td>Hockey</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11081</th>\n",
              "      <td>ZWOLINSKA Klaudia</td>\n",
              "      <td>Poland</td>\n",
              "      <td>Canoe Slalom</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11082</th>\n",
              "      <td>ZYKOVA Yulia</td>\n",
              "      <td>ROC</td>\n",
              "      <td>Shooting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11083</th>\n",
              "      <td>ZYUZINA Ekaterina</td>\n",
              "      <td>ROC</td>\n",
              "      <td>Sailing</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11084</th>\n",
              "      <td>ZYZANSKA Sylwia</td>\n",
              "      <td>Poland</td>\n",
              "      <td>Archery</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>11085 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                        Name      NOC           Discipline\n",
              "0            AALERUD Katrine   Norway         Cycling Road\n",
              "1                ABAD Nestor    Spain  Artistic Gymnastics\n",
              "2          ABAGNALE Giovanni    Italy               Rowing\n",
              "3             ABALDE Alberto    Spain           Basketball\n",
              "4              ABALDE Tamara    Spain           Basketball\n",
              "...                      ...      ...                  ...\n",
              "11080  ZWICKER Martin Detlef  Germany               Hockey\n",
              "11081      ZWOLINSKA Klaudia   Poland         Canoe Slalom\n",
              "11082           ZYKOVA Yulia      ROC             Shooting\n",
              "11083      ZYUZINA Ekaterina      ROC              Sailing\n",
              "11084        ZYZANSKA Sylwia   Poland              Archery\n",
              "\n",
              "[11085 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uLRAqOEEME-i",
        "outputId": "2d8b8f91-2ebc-45b8-d12c-e2fe356496a7"
      },
      "source": [
        "nan_values=athletes.isna()\n",
        "nan_columns=nan_values.any()\n",
        "nan_columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name          False\n",
              "NOC           False\n",
              "Discipline    False\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7opZf8nlNxgF",
        "outputId": "11013cdc-a93f-4f41-cfac-a60a94ce3332"
      },
      "source": [
        "nan_values=coaches.isna()\n",
        "nan_columns=nan_values.any()\n",
        "nan_columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name          False\n",
              "NOC           False\n",
              "Discipline    False\n",
              "Event          True\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
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        "id": "4rU55_qNOAYW",
        "outputId": "7932c658-1791-4129-926f-d7d0d144b61f"
      },
      "source": [
        "coaches['Event'].fillna(\"No Event\", inplace = True)\n",
        "coaches"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>NOC</th>\n",
              "      <th>Discipline</th>\n",
              "      <th>Event</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ABDELMAGID Wael</td>\n",
              "      <td>Egypt</td>\n",
              "      <td>Football</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ABE Junya</td>\n",
              "      <td>Japan</td>\n",
              "      <td>Volleyball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ABE Katsuhiko</td>\n",
              "      <td>Japan</td>\n",
              "      <td>Basketball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ADAMA Cherif</td>\n",
              "      <td>Côte d'Ivoire</td>\n",
              "      <td>Football</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AGEBA Yuya</td>\n",
              "      <td>Japan</td>\n",
              "      <td>Volleyball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>389</th>\n",
              "      <td>ZAMORA PEDREIRA Javier</td>\n",
              "      <td>Spain</td>\n",
              "      <td>Basketball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>390</th>\n",
              "      <td>ZAMPIERI Francesca</td>\n",
              "      <td>Liechtenstein</td>\n",
              "      <td>Artistic Swimming</td>\n",
              "      <td>Duet</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>391</th>\n",
              "      <td>ZHANG Xiaohuan</td>\n",
              "      <td>People's Republic of China</td>\n",
              "      <td>Artistic Swimming</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>392</th>\n",
              "      <td>ZIJP Simon</td>\n",
              "      <td>Netherlands</td>\n",
              "      <td>Hockey</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>393</th>\n",
              "      <td>ZONDI Nkuliso</td>\n",
              "      <td>South Africa</td>\n",
              "      <td>Hockey</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>394 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Name  ...     Event\n",
              "0           ABDELMAGID Wael  ...  No Event\n",
              "1                 ABE Junya  ...  No Event\n",
              "2             ABE Katsuhiko  ...  No Event\n",
              "3              ADAMA Cherif  ...  No Event\n",
              "4                AGEBA Yuya  ...  No Event\n",
              "..                      ...  ...       ...\n",
              "389  ZAMORA PEDREIRA Javier  ...  No Event\n",
              "390      ZAMPIERI Francesca  ...      Duet\n",
              "391          ZHANG Xiaohuan  ...  No Event\n",
              "392              ZIJP Simon  ...  No Event\n",
              "393           ZONDI Nkuliso  ...     Women\n",
              "\n",
              "[394 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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        },
        "id": "yF5GfOdJOFph",
        "outputId": "5f2042ab-3f45-457c-c5f6-71aede5fc798"
      },
      "source": [
        "nan_values=entriesGender.isna()\n",
        "nan_columns=nan_values.any()\n",
        "nan_columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Discipline    False\n",
              "Female        False\n",
              "Male          False\n",
              "Total         False\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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        },
        "id": "auHjggM0PJoO",
        "outputId": "d3b73690-ecb5-44b0-8b23-6d60d6414450"
      },
      "source": [
        "nan_values=medals.isna()\n",
        "nan_columns=nan_values.any()\n",
        "nan_columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Rank             False\n",
              "Team/NOC         False\n",
              "Gold             False\n",
              "Silver           False\n",
              "Bronze           False\n",
              "Total            False\n",
              "Rank by Total    False\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i9c1e8p-PNiY",
        "outputId": "fe7e3533-05f7-43e0-b953-009f3fdc9657"
      },
      "source": [
        "nan_values=teams.isna()\n",
        "nan_columns=nan_values.any()\n",
        "nan_columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name          False\n",
              "Discipline    False\n",
              "NOC           False\n",
              "Event         False\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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          "height": 415
        },
        "id": "WZrxEwcQPVA1",
        "outputId": "7fe95b83-ba4f-488e-9984-8202e6414e12"
      },
      "source": [
        "athletes['NOC'] = athletes['NOC'].str.upper()\n",
        "athletes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>NOC</th>\n",
              "      <th>Discipline</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AALERUD Katrine</td>\n",
              "      <td>NORWAY</td>\n",
              "      <td>Cycling Road</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ABAD Nestor</td>\n",
              "      <td>SPAIN</td>\n",
              "      <td>Artistic Gymnastics</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ABAGNALE Giovanni</td>\n",
              "      <td>ITALY</td>\n",
              "      <td>Rowing</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ABALDE Alberto</td>\n",
              "      <td>SPAIN</td>\n",
              "      <td>Basketball</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ABALDE Tamara</td>\n",
              "      <td>SPAIN</td>\n",
              "      <td>Basketball</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
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              "    <tr>\n",
              "      <th>11080</th>\n",
              "      <td>ZWICKER Martin Detlef</td>\n",
              "      <td>GERMANY</td>\n",
              "      <td>Hockey</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11081</th>\n",
              "      <td>ZWOLINSKA Klaudia</td>\n",
              "      <td>POLAND</td>\n",
              "      <td>Canoe Slalom</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11082</th>\n",
              "      <td>ZYKOVA Yulia</td>\n",
              "      <td>ROC</td>\n",
              "      <td>Shooting</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11083</th>\n",
              "      <td>ZYUZINA Ekaterina</td>\n",
              "      <td>ROC</td>\n",
              "      <td>Sailing</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11084</th>\n",
              "      <td>ZYZANSKA Sylwia</td>\n",
              "      <td>POLAND</td>\n",
              "      <td>Archery</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>11085 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                        Name      NOC           Discipline\n",
              "0            AALERUD Katrine   NORWAY         Cycling Road\n",
              "1                ABAD Nestor    SPAIN  Artistic Gymnastics\n",
              "2          ABAGNALE Giovanni    ITALY               Rowing\n",
              "3             ABALDE Alberto    SPAIN           Basketball\n",
              "4              ABALDE Tamara    SPAIN           Basketball\n",
              "...                      ...      ...                  ...\n",
              "11080  ZWICKER Martin Detlef  GERMANY               Hockey\n",
              "11081      ZWOLINSKA Klaudia   POLAND         Canoe Slalom\n",
              "11082           ZYKOVA Yulia      ROC             Shooting\n",
              "11083      ZYUZINA Ekaterina      ROC              Sailing\n",
              "11084        ZYZANSKA Sylwia   POLAND              Archery\n",
              "\n",
              "[11085 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
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        "id": "3pkKAFoPPyR9",
        "outputId": "01efb11f-d967-4c98-cdad-2dcae0bdef3f"
      },
      "source": [
        "coaches['NOC'] = coaches['NOC'].str.upper()\n",
        "coaches"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>NOC</th>\n",
              "      <th>Discipline</th>\n",
              "      <th>Event</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ABDELMAGID Wael</td>\n",
              "      <td>EGYPT</td>\n",
              "      <td>Football</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ABE Junya</td>\n",
              "      <td>JAPAN</td>\n",
              "      <td>Volleyball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ABE Katsuhiko</td>\n",
              "      <td>JAPAN</td>\n",
              "      <td>Basketball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ADAMA Cherif</td>\n",
              "      <td>CÔTE D'IVOIRE</td>\n",
              "      <td>Football</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AGEBA Yuya</td>\n",
              "      <td>JAPAN</td>\n",
              "      <td>Volleyball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>389</th>\n",
              "      <td>ZAMORA PEDREIRA Javier</td>\n",
              "      <td>SPAIN</td>\n",
              "      <td>Basketball</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>390</th>\n",
              "      <td>ZAMPIERI Francesca</td>\n",
              "      <td>LIECHTENSTEIN</td>\n",
              "      <td>Artistic Swimming</td>\n",
              "      <td>Duet</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>391</th>\n",
              "      <td>ZHANG Xiaohuan</td>\n",
              "      <td>PEOPLE'S REPUBLIC OF CHINA</td>\n",
              "      <td>Artistic Swimming</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>392</th>\n",
              "      <td>ZIJP Simon</td>\n",
              "      <td>NETHERLANDS</td>\n",
              "      <td>Hockey</td>\n",
              "      <td>No Event</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>393</th>\n",
              "      <td>ZONDI Nkuliso</td>\n",
              "      <td>SOUTH AFRICA</td>\n",
              "      <td>Hockey</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>394 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Name  ...     Event\n",
              "0           ABDELMAGID Wael  ...  No Event\n",
              "1                 ABE Junya  ...  No Event\n",
              "2             ABE Katsuhiko  ...  No Event\n",
              "3              ADAMA Cherif  ...  No Event\n",
              "4                AGEBA Yuya  ...  No Event\n",
              "..                      ...  ...       ...\n",
              "389  ZAMORA PEDREIRA Javier  ...  No Event\n",
              "390      ZAMPIERI Francesca  ...      Duet\n",
              "391          ZHANG Xiaohuan  ...  No Event\n",
              "392              ZIJP Simon  ...  No Event\n",
              "393           ZONDI Nkuliso  ...     Women\n",
              "\n",
              "[394 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "id": "cuWlqSgEQkFI",
        "outputId": "8a1e6b1a-a5d5-46aa-b0c3-658913c390da"
      },
      "source": [
        "medals['Team/NOC'] = medals['Team/NOC'].str.upper()\n",
        "medals"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Rank</th>\n",
              "      <th>Team/NOC</th>\n",
              "      <th>Gold</th>\n",
              "      <th>Silver</th>\n",
              "      <th>Bronze</th>\n",
              "      <th>Total</th>\n",
              "      <th>Rank by Total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>UNITED STATES OF AMERICA</td>\n",
              "      <td>39</td>\n",
              "      <td>41</td>\n",
              "      <td>33</td>\n",
              "      <td>113</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>PEOPLE'S REPUBLIC OF CHINA</td>\n",
              "      <td>38</td>\n",
              "      <td>32</td>\n",
              "      <td>18</td>\n",
              "      <td>88</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>JAPAN</td>\n",
              "      <td>27</td>\n",
              "      <td>14</td>\n",
              "      <td>17</td>\n",
              "      <td>58</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>GREAT BRITAIN</td>\n",
              "      <td>22</td>\n",
              "      <td>21</td>\n",
              "      <td>22</td>\n",
              "      <td>65</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>ROC</td>\n",
              "      <td>20</td>\n",
              "      <td>28</td>\n",
              "      <td>23</td>\n",
              "      <td>71</td>\n",
              "      <td>3</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>86</td>\n",
              "      <td>GHANA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>86</td>\n",
              "      <td>GRENADA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90</th>\n",
              "      <td>86</td>\n",
              "      <td>KUWAIT</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>91</th>\n",
              "      <td>86</td>\n",
              "      <td>REPUBLIC OF MOLDOVA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>86</td>\n",
              "      <td>SYRIAN ARAB REPUBLIC</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>93 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    Rank                    Team/NOC  Gold  ...  Bronze  Total  Rank by Total\n",
              "0      1    UNITED STATES OF AMERICA    39  ...      33    113              1\n",
              "1      2  PEOPLE'S REPUBLIC OF CHINA    38  ...      18     88              2\n",
              "2      3                       JAPAN    27  ...      17     58              5\n",
              "3      4               GREAT BRITAIN    22  ...      22     65              4\n",
              "4      5                         ROC    20  ...      23     71              3\n",
              "..   ...                         ...   ...  ...     ...    ...            ...\n",
              "88    86                       GHANA     0  ...       1      1             77\n",
              "89    86                     GRENADA     0  ...       1      1             77\n",
              "90    86                      KUWAIT     0  ...       1      1             77\n",
              "91    86         REPUBLIC OF MOLDOVA     0  ...       1      1             77\n",
              "92    86        SYRIAN ARAB REPUBLIC     0  ...       1      1             77\n",
              "\n",
              "[93 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "id": "fRmgQYFMRB6A",
        "outputId": "231567c7-8311-4554-860a-c8f0e3947990"
      },
      "source": [
        "teams['NOC'] = teams['NOC'].str.upper()\n",
        "teams"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Name</th>\n",
              "      <th>Discipline</th>\n",
              "      <th>NOC</th>\n",
              "      <th>Event</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Belgium</td>\n",
              "      <td>3x3 Basketball</td>\n",
              "      <td>BELGIUM</td>\n",
              "      <td>Men</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>China</td>\n",
              "      <td>3x3 Basketball</td>\n",
              "      <td>PEOPLE'S REPUBLIC OF CHINA</td>\n",
              "      <td>Men</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>China</td>\n",
              "      <td>3x3 Basketball</td>\n",
              "      <td>PEOPLE'S REPUBLIC OF CHINA</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>France</td>\n",
              "      <td>3x3 Basketball</td>\n",
              "      <td>FRANCE</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Italy</td>\n",
              "      <td>3x3 Basketball</td>\n",
              "      <td>ITALY</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>738</th>\n",
              "      <td>South Africa</td>\n",
              "      <td>Water Polo</td>\n",
              "      <td>SOUTH AFRICA</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>739</th>\n",
              "      <td>Spain</td>\n",
              "      <td>Water Polo</td>\n",
              "      <td>SPAIN</td>\n",
              "      <td>Men</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>740</th>\n",
              "      <td>Spain</td>\n",
              "      <td>Water Polo</td>\n",
              "      <td>SPAIN</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>741</th>\n",
              "      <td>United States</td>\n",
              "      <td>Water Polo</td>\n",
              "      <td>UNITED STATES OF AMERICA</td>\n",
              "      <td>Men</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>742</th>\n",
              "      <td>United States</td>\n",
              "      <td>Water Polo</td>\n",
              "      <td>UNITED STATES OF AMERICA</td>\n",
              "      <td>Women</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>743 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              Name      Discipline                         NOC  Event\n",
              "0          Belgium  3x3 Basketball                     BELGIUM    Men\n",
              "1            China  3x3 Basketball  PEOPLE'S REPUBLIC OF CHINA    Men\n",
              "2            China  3x3 Basketball  PEOPLE'S REPUBLIC OF CHINA  Women\n",
              "3           France  3x3 Basketball                      FRANCE  Women\n",
              "4            Italy  3x3 Basketball                       ITALY  Women\n",
              "..             ...             ...                         ...    ...\n",
              "738   South Africa      Water Polo                SOUTH AFRICA  Women\n",
              "739          Spain      Water Polo                       SPAIN    Men\n",
              "740          Spain      Water Polo                       SPAIN  Women\n",
              "741  United States      Water Polo    UNITED STATES OF AMERICA    Men\n",
              "742  United States      Water Polo    UNITED STATES OF AMERICA  Women\n",
              "\n",
              "[743 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 510
        },
        "id": "x5LFvgOORIwZ",
        "outputId": "604c1441-4e9e-43ea-e369-67787e9db388"
      },
      "source": [
        "population=pd.read_excel('/content/Population data Assignment 1 Predict This.xlsx')\n",
        "population"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Country</th>\n",
              "      <th>Population</th>\n",
              "      <th>Independence year</th>\n",
              "      <th>Annual Sports Budget</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>USA</td>\n",
              "      <td>328200000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>China</td>\n",
              "      <td>1390000000</td>\n",
              "      <td>1949</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Japan</td>\n",
              "      <td>126300000</td>\n",
              "      <td>660</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Great Britain</td>\n",
              "      <td>66600000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Russia (ROC)</td>\n",
              "      <td>144400000</td>\n",
              "      <td>1990</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Australia</td>\n",
              "      <td>25400000</td>\n",
              "      <td>1901</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Netherlands</td>\n",
              "      <td>17300000</td>\n",
              "      <td>1648</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>France</td>\n",
              "      <td>67100000</td>\n",
              "      <td>1789</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Germany</td>\n",
              "      <td>83000000</td>\n",
              "      <td>1871</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Italy</td>\n",
              "      <td>60400000</td>\n",
              "      <td>1848</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Canada</td>\n",
              "      <td>37600000</td>\n",
              "      <td>1867</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Brazil</td>\n",
              "      <td>211000000</td>\n",
              "      <td>1822</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>New Zealand</td>\n",
              "      <td>4920000</td>\n",
              "      <td>1835</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Cuba</td>\n",
              "      <td>11300000</td>\n",
              "      <td>1898</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Hungary</td>\n",
              "      <td>9770000</td>\n",
              "      <td>1849</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Country  Population  Independence year  Annual Sports Budget\n",
              "0             USA   328200000               1776                   NaN\n",
              "1           China  1390000000               1949                   NaN\n",
              "2           Japan   126300000                660                   NaN\n",
              "3   Great Britain    66600000               1776                   NaN\n",
              "4    Russia (ROC)   144400000               1990                   NaN\n",
              "5       Australia    25400000               1901                   NaN\n",
              "6     Netherlands    17300000               1648                   NaN\n",
              "7          France    67100000               1789                   NaN\n",
              "8         Germany    83000000               1871                   NaN\n",
              "9           Italy    60400000               1848                   NaN\n",
              "10         Canada    37600000               1867                   NaN\n",
              "11         Brazil   211000000               1822                   NaN\n",
              "12    New Zealand     4920000               1835                   NaN\n",
              "13           Cuba    11300000               1898                   NaN\n",
              "14        Hungary     9770000               1849                   NaN"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 510
        },
        "id": "xQVTKf2dSObl",
        "outputId": "b5a5839f-2f6b-4ec1-b389-c8b8dce4e339"
      },
      "source": [
        "population.to_csv (\"population.csv\", \n",
        "                  index = None,\n",
        "                  header=True)\n",
        "Population = pd.DataFrame(pd.read_csv(\"population.csv\"))\n",
        "Population"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Country</th>\n",
              "      <th>Population</th>\n",
              "      <th>Independence year</th>\n",
              "      <th>Annual Sports Budget</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>USA</td>\n",
              "      <td>328200000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>China</td>\n",
              "      <td>1390000000</td>\n",
              "      <td>1949</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Japan</td>\n",
              "      <td>126300000</td>\n",
              "      <td>660</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Great Britain</td>\n",
              "      <td>66600000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Russia (ROC)</td>\n",
              "      <td>144400000</td>\n",
              "      <td>1990</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Australia</td>\n",
              "      <td>25400000</td>\n",
              "      <td>1901</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Netherlands</td>\n",
              "      <td>17300000</td>\n",
              "      <td>1648</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>France</td>\n",
              "      <td>67100000</td>\n",
              "      <td>1789</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Germany</td>\n",
              "      <td>83000000</td>\n",
              "      <td>1871</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Italy</td>\n",
              "      <td>60400000</td>\n",
              "      <td>1848</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Canada</td>\n",
              "      <td>37600000</td>\n",
              "      <td>1867</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Brazil</td>\n",
              "      <td>211000000</td>\n",
              "      <td>1822</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>New Zealand</td>\n",
              "      <td>4920000</td>\n",
              "      <td>1835</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Cuba</td>\n",
              "      <td>11300000</td>\n",
              "      <td>1898</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Hungary</td>\n",
              "      <td>9770000</td>\n",
              "      <td>1849</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Country  Population  Independence year  Annual Sports Budget\n",
              "0             USA   328200000               1776                   NaN\n",
              "1           China  1390000000               1949                   NaN\n",
              "2           Japan   126300000                660                   NaN\n",
              "3   Great Britain    66600000               1776                   NaN\n",
              "4    Russia (ROC)   144400000               1990                   NaN\n",
              "5       Australia    25400000               1901                   NaN\n",
              "6     Netherlands    17300000               1648                   NaN\n",
              "7          France    67100000               1789                   NaN\n",
              "8         Germany    83000000               1871                   NaN\n",
              "9           Italy    60400000               1848                   NaN\n",
              "10         Canada    37600000               1867                   NaN\n",
              "11         Brazil   211000000               1822                   NaN\n",
              "12    New Zealand     4920000               1835                   NaN\n",
              "13           Cuba    11300000               1898                   NaN\n",
              "14        Hungary     9770000               1849                   NaN"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 510
        },
        "id": "jt68I5Q0SqOd",
        "outputId": "c5f757b6-a262-4085-c941-3c4963be3b04"
      },
      "source": [
        "Population.rename(columns={'Country': 'Team/NOC'}, inplace=True)\n",
        "Population"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Team/NOC</th>\n",
              "      <th>Population</th>\n",
              "      <th>Independence year</th>\n",
              "      <th>Annual Sports Budget</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>USA</td>\n",
              "      <td>328200000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>China</td>\n",
              "      <td>1390000000</td>\n",
              "      <td>1949</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Japan</td>\n",
              "      <td>126300000</td>\n",
              "      <td>660</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Great Britain</td>\n",
              "      <td>66600000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Russia (ROC)</td>\n",
              "      <td>144400000</td>\n",
              "      <td>1990</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Australia</td>\n",
              "      <td>25400000</td>\n",
              "      <td>1901</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Netherlands</td>\n",
              "      <td>17300000</td>\n",
              "      <td>1648</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>France</td>\n",
              "      <td>67100000</td>\n",
              "      <td>1789</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Germany</td>\n",
              "      <td>83000000</td>\n",
              "      <td>1871</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Italy</td>\n",
              "      <td>60400000</td>\n",
              "      <td>1848</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Canada</td>\n",
              "      <td>37600000</td>\n",
              "      <td>1867</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Brazil</td>\n",
              "      <td>211000000</td>\n",
              "      <td>1822</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>New Zealand</td>\n",
              "      <td>4920000</td>\n",
              "      <td>1835</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Cuba</td>\n",
              "      <td>11300000</td>\n",
              "      <td>1898</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Hungary</td>\n",
              "      <td>9770000</td>\n",
              "      <td>1849</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Team/NOC  Population  Independence year  Annual Sports Budget\n",
              "0             USA   328200000               1776                   NaN\n",
              "1           China  1390000000               1949                   NaN\n",
              "2           Japan   126300000                660                   NaN\n",
              "3   Great Britain    66600000               1776                   NaN\n",
              "4    Russia (ROC)   144400000               1990                   NaN\n",
              "5       Australia    25400000               1901                   NaN\n",
              "6     Netherlands    17300000               1648                   NaN\n",
              "7          France    67100000               1789                   NaN\n",
              "8         Germany    83000000               1871                   NaN\n",
              "9           Italy    60400000               1848                   NaN\n",
              "10         Canada    37600000               1867                   NaN\n",
              "11         Brazil   211000000               1822                   NaN\n",
              "12    New Zealand     4920000               1835                   NaN\n",
              "13           Cuba    11300000               1898                   NaN\n",
              "14        Hungary     9770000               1849                   NaN"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 510
        },
        "id": "AQmx561kWlUE",
        "outputId": "02fd7665-a91e-448a-a423-a6ff72299f52"
      },
      "source": [
        "Population['Team/NOC'] = Population['Team/NOC'].str.upper()\n",
        "Population"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Team/NOC</th>\n",
              "      <th>Population</th>\n",
              "      <th>Independence year</th>\n",
              "      <th>Annual Sports Budget</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>USA</td>\n",
              "      <td>328200000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHINA</td>\n",
              "      <td>1390000000</td>\n",
              "      <td>1949</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>JAPAN</td>\n",
              "      <td>126300000</td>\n",
              "      <td>660</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>GREAT BRITAIN</td>\n",
              "      <td>66600000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>RUSSIA (ROC)</td>\n",
              "      <td>144400000</td>\n",
              "      <td>1990</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>AUSTRALIA</td>\n",
              "      <td>25400000</td>\n",
              "      <td>1901</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>NETHERLANDS</td>\n",
              "      <td>17300000</td>\n",
              "      <td>1648</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>FRANCE</td>\n",
              "      <td>67100000</td>\n",
              "      <td>1789</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>GERMANY</td>\n",
              "      <td>83000000</td>\n",
              "      <td>1871</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>ITALY</td>\n",
              "      <td>60400000</td>\n",
              "      <td>1848</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>CANADA</td>\n",
              "      <td>37600000</td>\n",
              "      <td>1867</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>BRAZIL</td>\n",
              "      <td>211000000</td>\n",
              "      <td>1822</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>NEW ZEALAND</td>\n",
              "      <td>4920000</td>\n",
              "      <td>1835</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>CUBA</td>\n",
              "      <td>11300000</td>\n",
              "      <td>1898</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>HUNGARY</td>\n",
              "      <td>9770000</td>\n",
              "      <td>1849</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Team/NOC  Population  Independence year  Annual Sports Budget\n",
              "0             USA   328200000               1776                   NaN\n",
              "1           CHINA  1390000000               1949                   NaN\n",
              "2           JAPAN   126300000                660                   NaN\n",
              "3   GREAT BRITAIN    66600000               1776                   NaN\n",
              "4    RUSSIA (ROC)   144400000               1990                   NaN\n",
              "5       AUSTRALIA    25400000               1901                   NaN\n",
              "6     NETHERLANDS    17300000               1648                   NaN\n",
              "7          FRANCE    67100000               1789                   NaN\n",
              "8         GERMANY    83000000               1871                   NaN\n",
              "9           ITALY    60400000               1848                   NaN\n",
              "10         CANADA    37600000               1867                   NaN\n",
              "11         BRAZIL   211000000               1822                   NaN\n",
              "12    NEW ZEALAND     4920000               1835                   NaN\n",
              "13           CUBA    11300000               1898                   NaN\n",
              "14        HUNGARY     9770000               1849                   NaN"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "id": "DGMDl9zMW8cW",
        "outputId": "90346c23-f83e-40d9-883d-26a3841bce94"
      },
      "source": [
        "medals[\"Team/NOC\"].replace({'UNITED STATES OF AMERICA': 'USA','ROC':'RUSSIA(ROC)',\"PEOPLE'S REPUBLIC OF CHINA\":'CHINA'}, inplace=True)\n",
        "medals"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Rank</th>\n",
              "      <th>Team/NOC</th>\n",
              "      <th>Gold</th>\n",
              "      <th>Silver</th>\n",
              "      <th>Bronze</th>\n",
              "      <th>Total</th>\n",
              "      <th>Rank by Total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>USA</td>\n",
              "      <td>39</td>\n",
              "      <td>41</td>\n",
              "      <td>33</td>\n",
              "      <td>113</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>CHINA</td>\n",
              "      <td>38</td>\n",
              "      <td>32</td>\n",
              "      <td>18</td>\n",
              "      <td>88</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>JAPAN</td>\n",
              "      <td>27</td>\n",
              "      <td>14</td>\n",
              "      <td>17</td>\n",
              "      <td>58</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>GREAT BRITAIN</td>\n",
              "      <td>22</td>\n",
              "      <td>21</td>\n",
              "      <td>22</td>\n",
              "      <td>65</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>RUSSIA(ROC)</td>\n",
              "      <td>20</td>\n",
              "      <td>28</td>\n",
              "      <td>23</td>\n",
              "      <td>71</td>\n",
              "      <td>3</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>86</td>\n",
              "      <td>GHANA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>86</td>\n",
              "      <td>GRENADA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90</th>\n",
              "      <td>86</td>\n",
              "      <td>KUWAIT</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>91</th>\n",
              "      <td>86</td>\n",
              "      <td>REPUBLIC OF MOLDOVA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>86</td>\n",
              "      <td>SYRIAN ARAB REPUBLIC</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>93 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    Rank              Team/NOC  Gold  Silver  Bronze  Total  Rank by Total\n",
              "0      1                   USA    39      41      33    113              1\n",
              "1      2                 CHINA    38      32      18     88              2\n",
              "2      3                 JAPAN    27      14      17     58              5\n",
              "3      4         GREAT BRITAIN    22      21      22     65              4\n",
              "4      5           RUSSIA(ROC)    20      28      23     71              3\n",
              "..   ...                   ...   ...     ...     ...    ...            ...\n",
              "88    86                 GHANA     0       0       1      1             77\n",
              "89    86               GRENADA     0       0       1      1             77\n",
              "90    86                KUWAIT     0       0       1      1             77\n",
              "91    86   REPUBLIC OF MOLDOVA     0       0       1      1             77\n",
              "92    86  SYRIAN ARAB REPUBLIC     0       0       1      1             77\n",
              "\n",
              "[93 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 479
        },
        "id": "oVFVdb_CXSHV",
        "outputId": "46d76ada-f2da-466d-8e23-014a724491ca"
      },
      "source": [
        "medals_population=pd.merge(medals,Population,on=\"Team/NOC\")\n",
        "medals_population"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Rank</th>\n",
              "      <th>Team/NOC</th>\n",
              "      <th>Gold</th>\n",
              "      <th>Silver</th>\n",
              "      <th>Bronze</th>\n",
              "      <th>Total</th>\n",
              "      <th>Rank by Total</th>\n",
              "      <th>Population</th>\n",
              "      <th>Independence year</th>\n",
              "      <th>Annual Sports Budget</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>USA</td>\n",
              "      <td>39</td>\n",
              "      <td>41</td>\n",
              "      <td>33</td>\n",
              "      <td>113</td>\n",
              "      <td>1</td>\n",
              "      <td>328200000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>CHINA</td>\n",
              "      <td>38</td>\n",
              "      <td>32</td>\n",
              "      <td>18</td>\n",
              "      <td>88</td>\n",
              "      <td>2</td>\n",
              "      <td>1390000000</td>\n",
              "      <td>1949</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>JAPAN</td>\n",
              "      <td>27</td>\n",
              "      <td>14</td>\n",
              "      <td>17</td>\n",
              "      <td>58</td>\n",
              "      <td>5</td>\n",
              "      <td>126300000</td>\n",
              "      <td>660</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>GREAT BRITAIN</td>\n",
              "      <td>22</td>\n",
              "      <td>21</td>\n",
              "      <td>22</td>\n",
              "      <td>65</td>\n",
              "      <td>4</td>\n",
              "      <td>66600000</td>\n",
              "      <td>1776</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6</td>\n",
              "      <td>AUSTRALIA</td>\n",
              "      <td>17</td>\n",
              "      <td>7</td>\n",
              "      <td>22</td>\n",
              "      <td>46</td>\n",
              "      <td>6</td>\n",
              "      <td>25400000</td>\n",
              "      <td>1901</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>7</td>\n",
              "      <td>NETHERLANDS</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>14</td>\n",
              "      <td>36</td>\n",
              "      <td>9</td>\n",
              "      <td>17300000</td>\n",
              "      <td>1648</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>8</td>\n",
              "      <td>FRANCE</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>11</td>\n",
              "      <td>33</td>\n",
              "      <td>10</td>\n",
              "      <td>67100000</td>\n",
              "      <td>1789</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>9</td>\n",
              "      <td>GERMANY</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>16</td>\n",
              "      <td>37</td>\n",
              "      <td>8</td>\n",
              "      <td>83000000</td>\n",
              "      <td>1871</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>10</td>\n",
              "      <td>ITALY</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>20</td>\n",
              "      <td>40</td>\n",
              "      <td>7</td>\n",
              "      <td>60400000</td>\n",
              "      <td>1848</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>11</td>\n",
              "      <td>CANADA</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>11</td>\n",
              "      <td>24</td>\n",
              "      <td>11</td>\n",
              "      <td>37600000</td>\n",
              "      <td>1867</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>12</td>\n",
              "      <td>BRAZIL</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>21</td>\n",
              "      <td>12</td>\n",
              "      <td>211000000</td>\n",
              "      <td>1822</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>13</td>\n",
              "      <td>NEW ZEALAND</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "      <td>4920000</td>\n",
              "      <td>1835</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>14</td>\n",
              "      <td>CUBA</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11300000</td>\n",
              "      <td>1898</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>15</td>\n",
              "      <td>HUNGARY</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "      <td>9770000</td>\n",
              "      <td>1849</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Rank       Team/NOC  ...  Independence year  Annual Sports Budget\n",
              "0      1            USA  ...               1776                   NaN\n",
              "1      2          CHINA  ...               1949                   NaN\n",
              "2      3          JAPAN  ...                660                   NaN\n",
              "3      4  GREAT BRITAIN  ...               1776                   NaN\n",
              "4      6      AUSTRALIA  ...               1901                   NaN\n",
              "5      7    NETHERLANDS  ...               1648                   NaN\n",
              "6      8         FRANCE  ...               1789                   NaN\n",
              "7      9        GERMANY  ...               1871                   NaN\n",
              "8     10          ITALY  ...               1848                   NaN\n",
              "9     11         CANADA  ...               1867                   NaN\n",
              "10    12         BRAZIL  ...               1822                   NaN\n",
              "11    13    NEW ZEALAND  ...               1835                   NaN\n",
              "12    14           CUBA  ...               1898                   NaN\n",
              "13    15        HUNGARY  ...               1849                   NaN\n",
              "\n",
              "[14 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "3iWiY6odXYLO",
        "outputId": "061c2234-f261-4999-f631-221590bf0912"
      },
      "source": [
        "import plotly.express as px\n",
        "fig = px.scatter(medals_population, x=\"Gold\", y=\"Population\", color='Team/NOC')\n",
        "fig.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "            Plotly.purge(gd);\n",
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          },
          "metadata": {}
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "TYs-ArjjZ1fY",
        "outputId": "8364d5ab-0bc3-45b8-8a6a-134cd19a20cc"
      },
      "source": [
        "import plotly.express as px\n",
        "fig = px.scatter(medals_population, x=\"Silver\", y=\"Population\", color='Team/NOC')\n",
        "fig.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
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              "var notebookContainer = gd.closest('#notebook-container');\n",
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          "metadata": {}
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "DRoR4OFXbaiC",
        "outputId": "7de96c89-a57e-4d1a-cbc9-823b1c5383f4"
      },
      "source": [
        "import plotly.express as px\n",
        "fig = px.scatter(medals_population, x=\"Bronze\", y=\"Population\", color='Team/NOC')\n",
        "fig.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
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              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
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              "    x.observe(notebookContainer, {childList: true});\n",
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              "    x.observe(outputEl, {childList: true});\n",
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              "                \n",
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              "</body>\n",
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "wtRbyZT2bitp",
        "outputId": "2a8160cf-e973-456b-c555-8a9790b87ab5"
      },
      "source": [
        "import plotly.express as px\n",
        "fig = px.scatter(medals_population, x=\"Total\", y=\"Population\", color='Team/NOC')\n",
        "fig.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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        "outputId": "5ade7cbb-d7ad-49d8-ce3b-6b557b991d34"
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      "source": [
        "medals_population['Years of Independence'] = medals_population['Independence year'].map(lambda x: 2021 - x)\n",
        "medals_population.head(20)\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
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          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Rank</th>\n",
              "      <th>Team/NOC</th>\n",
              "      <th>Gold</th>\n",
              "      <th>Silver</th>\n",
              "      <th>Bronze</th>\n",
              "      <th>Total</th>\n",
              "      <th>Rank by Total</th>\n",
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              "      <th>Annual Sports Budget</th>\n",
              "      <th>Years of Independence</th>\n",
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              "  <tbody>\n",
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              "      <td>1</td>\n",
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              "      <td>39</td>\n",
              "      <td>41</td>\n",
              "      <td>33</td>\n",
              "      <td>113</td>\n",
              "      <td>1</td>\n",
              "      <td>328200000</td>\n",
              "      <td>1776</td>\n",
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              "      <td>245</td>\n",
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              "      <td>2</td>\n",
              "      <td>CHINA</td>\n",
              "      <td>38</td>\n",
              "      <td>32</td>\n",
              "      <td>18</td>\n",
              "      <td>88</td>\n",
              "      <td>2</td>\n",
              "      <td>1390000000</td>\n",
              "      <td>1949</td>\n",
              "      <td>NaN</td>\n",
              "      <td>72</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>JAPAN</td>\n",
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              "      <td>126300000</td>\n",
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              "      <td>1361</td>\n",
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              "      <td>GREAT BRITAIN</td>\n",
              "      <td>22</td>\n",
              "      <td>21</td>\n",
              "      <td>22</td>\n",
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              "      <td>4</td>\n",
              "      <td>66600000</td>\n",
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              "      <td>AUSTRALIA</td>\n",
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              "      <td>7</td>\n",
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              "      <td>25400000</td>\n",
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              "      <td>NETHERLANDS</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>14</td>\n",
              "      <td>36</td>\n",
              "      <td>9</td>\n",
              "      <td>17300000</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>373</td>\n",
              "    </tr>\n",
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              "      <th>6</th>\n",
              "      <td>8</td>\n",
              "      <td>FRANCE</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>11</td>\n",
              "      <td>33</td>\n",
              "      <td>10</td>\n",
              "      <td>67100000</td>\n",
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              "      <th>7</th>\n",
              "      <td>9</td>\n",
              "      <td>GERMANY</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>16</td>\n",
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              "      <td>83000000</td>\n",
              "      <td>1871</td>\n",
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              "      <td>10</td>\n",
              "      <td>ITALY</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>20</td>\n",
              "      <td>40</td>\n",
              "      <td>7</td>\n",
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              "      <td>11</td>\n",
              "      <td>CANADA</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>11</td>\n",
              "      <td>24</td>\n",
              "      <td>11</td>\n",
              "      <td>37600000</td>\n",
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              "      <td>154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>12</td>\n",
              "      <td>BRAZIL</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>21</td>\n",
              "      <td>12</td>\n",
              "      <td>211000000</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>13</td>\n",
              "      <td>NEW ZEALAND</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "      <td>4920000</td>\n",
              "      <td>1835</td>\n",
              "      <td>NaN</td>\n",
              "      <td>186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>14</td>\n",
              "      <td>CUBA</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11300000</td>\n",
              "      <td>1898</td>\n",
              "      <td>NaN</td>\n",
              "      <td>123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>15</td>\n",
              "      <td>HUNGARY</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "      <td>9770000</td>\n",
              "      <td>1849</td>\n",
              "      <td>NaN</td>\n",
              "      <td>172</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Rank       Team/NOC  ...  Annual Sports Budget  Years of Independence\n",
              "0      1            USA  ...                   NaN                    245\n",
              "1      2          CHINA  ...                   NaN                     72\n",
              "2      3          JAPAN  ...                   NaN                   1361\n",
              "3      4  GREAT BRITAIN  ...                   NaN                    245\n",
              "4      6      AUSTRALIA  ...                   NaN                    120\n",
              "5      7    NETHERLANDS  ...                   NaN                    373\n",
              "6      8         FRANCE  ...                   NaN                    232\n",
              "7      9        GERMANY  ...                   NaN                    150\n",
              "8     10          ITALY  ...                   NaN                    173\n",
              "9     11         CANADA  ...                   NaN                    154\n",
              "10    12         BRAZIL  ...                   NaN                    199\n",
              "11    13    NEW ZEALAND  ...                   NaN                    186\n",
              "12    14           CUBA  ...                   NaN                    123\n",
              "13    15        HUNGARY  ...                   NaN                    172\n",
              "\n",
              "[14 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
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    {
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        "id": "c6xXiaEib5RY",
        "outputId": "1707f9c9-96dc-48d9-bd6f-43db209c444f"
      },
      "source": [
        "import plotly.express as px\n",
        "fig = px.scatter(medals_population, x=\"Gold\", y=\"Years of Independence\", color='Team/NOC')\n",
        "fig.show()"
      ],
      "execution_count": null,
      "outputs": [
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      "source": [
        "entriesGender['Highest Divide'] = entriesGender.apply(lambda x: x['Male'] - x['Female'], axis = 1)"
      ],
      "execution_count": null,
      "outputs": []
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        "outputId": "ecdb07b8-6560-47c9-83e1-4568d10c0a54"
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        "entriesGender_s = entriesGender.sort_values(by = 'Highest Divide', ascending = False)\n",
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      "execution_count": null,
      "outputs": [
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              "      <td>264</td>\n",
              "      <td>344</td>\n",
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              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Cycling Road</td>\n",
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              "      <td>131</td>\n",
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              "      <td>61</td>\n",
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              "      Discipline  Female  Male  Total  Highest Divide\n",
              "4      Athletics     969  1072   2041             103\n",
              "45     Wrestling      96   193    289              97\n",
              "9         Boxing     102   187    289              85\n",
              "20      Football     264   344    608              80\n",
              "15  Cycling Road      70   131    201              61"
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      "source": [
        "entriesGender_s[0:4]"
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      "execution_count": null,
      "outputs": [
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              "      <th>Discipline</th>\n",
              "      <th>Female</th>\n",
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              "      <th>Highest Divide</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Athletics</td>\n",
              "      <td>969</td>\n",
              "      <td>1072</td>\n",
              "      <td>2041</td>\n",
              "      <td>103</td>\n",
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              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Wrestling</td>\n",
              "      <td>96</td>\n",
              "      <td>193</td>\n",
              "      <td>289</td>\n",
              "      <td>97</td>\n",
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              "      <td>Boxing</td>\n",
              "      <td>102</td>\n",
              "      <td>187</td>\n",
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              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Football</td>\n",
              "      <td>264</td>\n",
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              "      <td>608</td>\n",
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              "   Discipline  Female  Male  Total  Highest Divide\n",
              "4   Athletics     969  1072   2041             103\n",
              "45  Wrestling      96   193    289              97\n",
              "9      Boxing     102   187    289              85\n",
              "20   Football     264   344    608              80"
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