Summer_Olympics_Data_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a508b568",
   "metadata": {},
   "source": [
    "# Summer Olympics Data Analysis Assignment"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87c3a161",
   "metadata": {},
   "source": [
    "### Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8d8b867f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb79c8cb",
   "metadata": {},
   "source": [
    "### Reading Summer Olympics Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d5c805ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Discipline</th>\n",
       "      <th>Athlete</th>\n",
       "      <th>Country</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1896</td>\n",
       "      <td>Athens</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>HAJOS, Alfred</td>\n",
       "      <td>HUN</td>\n",
       "      <td>Men</td>\n",
       "      <td>100M Freestyle</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1896</td>\n",
       "      <td>Athens</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>HERSCHMANN, Otto</td>\n",
       "      <td>AUT</td>\n",
       "      <td>Men</td>\n",
       "      <td>100M Freestyle</td>\n",
       "      <td>Silver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1896</td>\n",
       "      <td>Athens</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>DRIVAS, Dimitrios</td>\n",
       "      <td>GRE</td>\n",
       "      <td>Men</td>\n",
       "      <td>100M Freestyle For Sailors</td>\n",
       "      <td>Bronze</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1896</td>\n",
       "      <td>Athens</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>MALOKINIS, Ioannis</td>\n",
       "      <td>GRE</td>\n",
       "      <td>Men</td>\n",
       "      <td>100M Freestyle For Sailors</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1896</td>\n",
       "      <td>Athens</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>CHASAPIS, Spiridon</td>\n",
       "      <td>GRE</td>\n",
       "      <td>Men</td>\n",
       "      <td>100M Freestyle For Sailors</td>\n",
       "      <td>Silver</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year    City     Sport Discipline             Athlete Country Gender  \\\n",
       "0  1896  Athens  Aquatics   Swimming       HAJOS, Alfred     HUN    Men   \n",
       "1  1896  Athens  Aquatics   Swimming    HERSCHMANN, Otto     AUT    Men   \n",
       "2  1896  Athens  Aquatics   Swimming   DRIVAS, Dimitrios     GRE    Men   \n",
       "3  1896  Athens  Aquatics   Swimming  MALOKINIS, Ioannis     GRE    Men   \n",
       "4  1896  Athens  Aquatics   Swimming  CHASAPIS, Spiridon     GRE    Men   \n",
       "\n",
       "                        Event   Medal  \n",
       "0              100M Freestyle    Gold  \n",
       "1              100M Freestyle  Silver  \n",
       "2  100M Freestyle For Sailors  Bronze  \n",
       "3  100M Freestyle For Sailors    Gold  \n",
       "4  100M Freestyle For Sailors  Silver  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"summer.csv\", index_col = 0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21e836ce",
   "metadata": {},
   "source": [
    "## 1. In how many cities Summer Olympics is held so far?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4a43d25d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Summer Olympics has been held at \"22\" different countries so far!!\n"
     ]
    }
   ],
   "source": [
    "print(\"Summer Olympics has been held at \\\"\", df.City.nunique(), \"\\\" different countries so far!!\", sep='')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0235dbe6",
   "metadata": {},
   "source": [
    "## 2. Which sport is having most number of Gold Medals so far? (Top 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f8375781",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The sport having the highest number of Gold Medals is \"Aquatics\" with a total of 1421 medals so far!!\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a dataframe based on how many Gold Medals are won w.r.t Sports\n",
    "df1 = pd.DataFrame(df[df.Medal  == 'Gold'].groupby('Sport')['Medal'].agg('count').sort_values(ascending=False).reset_index())\n",
    "\n",
    "# Printing the sport having most number of Gold Medals\n",
    "print(\"\\nThe sport having the highest number of Gold Medals is \\\"\", df1.Sport[0], \"\\\" with a total of \", \n",
    "      df1.Medal[0], \" medals so far!!\", sep='')\n",
    "\n",
    "# Plotting Top 5 Sports which have most number of Gold Medals\n",
    "plt.figure(figsize=(10,7))\n",
    "plots = sns.barplot(x='Sport',y='Medal',data=df1.head(), palette='Spectral_r', edgecolor='black', lw=2)\n",
    "plt.xlabel('Top 5 Sports',size=15)\n",
    "plt.ylabel('Total Number of Gold Medals',size=15)\n",
    "plt.title('Top 5 Sports with highest number of Gold Medals',size=15)\n",
    "for bar in plots.patches:\n",
    "    plt.annotate(format(bar.get_height(), '.0f'), (bar.get_x() + bar.get_width() / 2, bar.get_height()), \n",
    "                 ha='center', va='center', size=12, xytext=(0, 8), textcoords='offset points')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03ecd3d0",
   "metadata": {},
   "source": [
    "## 3. Which sport is having most number of medals so far? (Top 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9f5b8b60",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The sport having the highest number of medals so far is \"Aquatics\"!\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a dataframe based on how many Medals are won w.r.t Sports\n",
    "df2 = pd.DataFrame(df.groupby('Sport')['Medal'].agg('count').sort_values(ascending=False)).reset_index()\n",
    "\n",
    "# Printing the Sport having the most number of medals\n",
    "print(\"\\nThe sport having the highest number of medals so far is \\\"\", df2.Sport[0], \"\\\"!\", sep='')\n",
    "\n",
    "# Plotting the Top 5 Sports having the most number of medals\n",
    "plt.figure(figsize=(10,7))\n",
    "plots = sns.barplot(x='Sport',y='Medal',data=df2.head(), palette='hot', edgecolor='black', lw=2)\n",
    "plt.xlabel('Top 5 Sports',size=15)\n",
    "plt.ylabel('Total Number of Medals',size=15)\n",
    "plt.title('Top 5 Sports with highest number of Medals',size=15)\n",
    "for bar in plots.patches:\n",
    "    plt.annotate(format(bar.get_height(), '.0f'), (bar.get_x() + bar.get_width() / 2, bar.get_height()), \n",
    "                 ha='center', va='center', size=12, xytext=(0, 8), textcoords='offset points')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a7b30cc",
   "metadata": {},
   "source": [
    "## 4. Which player has won most number of medals? (Top 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1aeba272",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\"Michael Phelps\" has won the most number of medals so far in Summer Olympics!\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a dataframe based on how many Medals are won by an individual Player\n",
    "df3 = pd.DataFrame(df.groupby('Athlete')['Medal'].agg('count').sort_values(ascending=False)).reset_index()\n",
    "\n",
    "# Printing the player name who won the most number of medals\n",
    "name = df3.Athlete[0]\n",
    "name = name.split(', ')\n",
    "print(\"\\n\\\"\", name[1], \" \", name[0].capitalize() , \"\\\" has won the most number of medals so far in Summer Olympics!\", sep='')\n",
    "\n",
    "# Plotting the Top 5 players who won the highest number of medals\n",
    "plt.figure(figsize=(11,7))\n",
    "plots = sns.barplot(x='Athlete',y='Medal',data=df3.head(), palette='coolwarm_r', edgecolor='black', lw=2)\n",
    "plt.xlabel('Top 5 Sportsperson',size=15)\n",
    "plt.ylabel('Total Number of Medals',size=15)\n",
    "plt.title('Top 5 Sportsperson with highest number of Medals',size=15)\n",
    "for bar in plots.patches:\n",
    "    plt.annotate(format(bar.get_height(), '.0f'), (bar.get_x() + bar.get_width() / 2, bar.get_height()), \n",
    "                 ha='center', va='center', size=12, xytext=(0, 8), textcoords='offset points')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cf53461",
   "metadata": {},
   "source": [
    "## 5. Which player has won most number Gold Medals of medals? (Top 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2c0bace6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\"Michael Phelps\" has won the most number of medals so far in Summer Olympics!\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a dataframe based on how many Gold Medals are won by an individual player\n",
    "df4 = pd.DataFrame(df[df.Medal == 'Gold'].groupby('Athlete')['Medal'].agg('count').sort_values(ascending=False)).reset_index()\n",
    "\n",
    "# Printing the player name who has won the most number of Gold Medals\n",
    "name1 = df4.Athlete[0]\n",
    "name1 = name1.split(', ')\n",
    "print(\"\\n\\\"\", name1[1], \" \", name1[0].capitalize() , \"\\\" has won the most number of medals so far in Summer Olympics!\", sep='')\n",
    "\n",
    "# Plotting the Top 5 players who has won the highest number of Gold Medals\n",
    "plt.figure(figsize=(10,7))\n",
    "plots = sns.barplot(x='Athlete',y='Medal',data=df4.head(), palette='autumn', edgecolor='black', lw=2)\n",
    "plt.xlabel('Top 5 Sportsperson',size=15)\n",
    "plt.ylabel('Total Number of Gold Medals',size=15)\n",
    "plt.title('Top 5 Sportsperson with highest number of Gold Medals',size=15)\n",
    "for bar in plots.patches:\n",
    "    plt.annotate(format(bar.get_height(), '.0f'), (bar.get_x() + bar.get_width() / 2, bar.get_height()), \n",
    "                 ha='center', va='center', size=12, xytext=(0, 8), textcoords='offset points')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1b203e0",
   "metadata": {},
   "source": [
    "## 6. In which year India won first Gold Medal in Summer Olympics?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "edc740d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "India won the first Gold Medal in Summer Olympics in the year \"1928\".\n"
     ]
    },
    {
     "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>Year</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Discipline</th>\n",
       "      <th>Athlete</th>\n",
       "      <th>Country</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5512</th>\n",
       "      <td>1928</td>\n",
       "      <td>Amsterdam</td>\n",
       "      <td>Hockey</td>\n",
       "      <td>Hockey</td>\n",
       "      <td>ALLEN, Richard James</td>\n",
       "      <td>IND</td>\n",
       "      <td>Men</td>\n",
       "      <td>Hockey</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year       City   Sport Discipline               Athlete Country Gender  \\\n",
       "5512  1928  Amsterdam  Hockey     Hockey  ALLEN, Richard James     IND    Men   \n",
       "\n",
       "       Event Medal  \n",
       "5512  Hockey  Gold  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a dataframe based on how many Gold Medals have been won by India\n",
    "yr = list(df.loc[(df.Country == 'IND') & (df.Medal == 'Gold')]['Year'].values)\n",
    "\n",
    "# Printing the year in which India won it's first Summer Olympics Gold Medal\n",
    "print(\"India won the first Gold Medal in Summer Olympics in the year \\\"\", yr[0], \"\\\".\", sep='')\n",
    "\n",
    "df.loc[(df.Country == 'IND') & (df.Medal == 'Gold')].head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88b2679a",
   "metadata": {},
   "source": [
    "## 7. Which event is most popular in terms on number of players? (Top 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7a3024b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The event that is most popular in terms of number of players is \"Football\".\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a dataframe based on how many Events are most popular w.r.t number of players\n",
    "df5 = pd.DataFrame(df.groupby('Event')['Athlete'].agg('count').sort_values(ascending=False)).reset_index()\n",
    "\n",
    "# Printing the Event name which is most popular in terms of numer of players\n",
    "print(\"\\nThe event that is most popular in terms of number of players is \\\"\", df5.Event[0], \"\\\".\", sep='')\n",
    "\n",
    "# Plotting the Top 5 most popular Events in terms of number of players\n",
    "plt.figure(figsize=(10,7))\n",
    "plots = sns.barplot(x='Event',y='Athlete',data=df5.head(), palette='vlag_r', edgecolor='black', lw=2)\n",
    "plt.xlabel('Top 5 Event',size=15)\n",
    "plt.ylabel('Total Number of Players',size=15)\n",
    "plt.title('Top 5 most popular Events in terms of number of players',size=15)\n",
    "for bar in plots.patches:\n",
    "    plt.annotate(format(bar.get_height(), '.0f'), (bar.get_x() + bar.get_width() / 2, bar.get_height()), \n",
    "                 ha='center', va='center', size=12, xytext=(0, 8), textcoords='offset points')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da152f03",
   "metadata": {},
   "source": [
    "## 8. Which sport is having most female Gold Medalists? (Top 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d0aee18a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The sport having the highest number of female Gold Medalists is \"Aquatics\"!\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a dataframe of Sports which have the most female Gold Medalists\n",
    "df6 = pd.DataFrame(df[(df.Medal == 'Gold') & (df.Gender == 'Women')].groupby('Sport')['Gender'].agg('count').sort_values(ascending=False)).reset_index()\n",
    "\n",
    "# Printing the Sport having the highest number of female Gold Medalists\n",
    "print(\"The sport having the highest number of female Gold Medalists is \\\"\", df6.Sport[0], \"\\\"!\", sep='')\n",
    "\n",
    "# Plotting the Top 5 Sports having the highest number of female Gold Medalists\n",
    "plt.figure(figsize=(10,7))\n",
    "plots = sns.barplot(x='Sport',y='Gender',data=df6.head(), palette='flare_r', edgecolor='black', lw=2)\n",
    "plt.xlabel('Top 5 Sports',size=15)\n",
    "plt.ylabel('Total Number of female Gold Medalists',size=15)\n",
    "plt.title('Top 5 Sports having the highest number of female Gold Medalists',size=15)\n",
    "for bar in plots.patches:\n",
    "    plt.annotate(format(bar.get_height(), '.0f'), (bar.get_x() + bar.get_width() / 2, bar.get_height()), \n",
    "                 ha='center', va='center', size=12, xytext=(0, 8), textcoords='offset points')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}