Pandas2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "24e22b53",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3c6228ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic = pd.read_csv(r'titanic.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c0aeceb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Owen Harris Braund</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. John Bradley (Florence Briggs Thayer) Cum...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Laina Heikkinen</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. Jacques Heath (Lily May Peel) Futrelle</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. William Henry Allen</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Rev. Juozas Montvila</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Miss. Margaret Edith Graham</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Catherine Helen Johnston</td>\n",
       "      <td>female</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>23.4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Karl Howell Behr</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Patrick Dooley</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>887 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass                                               Name  \\\n",
       "0           0       3                             Mr. Owen Harris Braund   \n",
       "1           1       1  Mrs. John Bradley (Florence Briggs Thayer) Cum...   \n",
       "2           1       3                              Miss. Laina Heikkinen   \n",
       "3           1       1        Mrs. Jacques Heath (Lily May Peel) Futrelle   \n",
       "4           0       3                            Mr. William Henry Allen   \n",
       "..        ...     ...                                                ...   \n",
       "882         0       2                               Rev. Juozas Montvila   \n",
       "883         1       1                        Miss. Margaret Edith Graham   \n",
       "884         0       3                     Miss. Catherine Helen Johnston   \n",
       "885         1       1                               Mr. Karl Howell Behr   \n",
       "886         0       3                                 Mr. Patrick Dooley   \n",
       "\n",
       "        Sex   Age  Siblings/Spouses Aboard  Parents/Children Aboard     Fare  \n",
       "0      male  22.0                        1                        0   7.2500  \n",
       "1    female  38.0                        1                        0  71.2833  \n",
       "2    female  26.0                        0                        0   7.9250  \n",
       "3    female  35.0                        1                        0  53.1000  \n",
       "4      male  35.0                        0                        0   8.0500  \n",
       "..      ...   ...                      ...                      ...      ...  \n",
       "882    male  27.0                        0                        0  13.0000  \n",
       "883  female  19.0                        0                        0  30.0000  \n",
       "884  female   7.0                        1                        2  23.4500  \n",
       "885    male  26.0                        0                        0  30.0000  \n",
       "886    male  32.0                        0                        0   7.7500  \n",
       "\n",
       "[887 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "78204d5b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 887 entries, 0 to 886\n",
      "Data columns (total 8 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   Survived                 887 non-null    int64  \n",
      " 1   Pclass                   887 non-null    int64  \n",
      " 2   Name                     887 non-null    object \n",
      " 3   Sex                      887 non-null    object \n",
      " 4   Age                      887 non-null    float64\n",
      " 5   Siblings/Spouses Aboard  887 non-null    int64  \n",
      " 6   Parents/Children Aboard  887 non-null    int64  \n",
      " 7   Fare                     887 non-null    float64\n",
      "dtypes: float64(2), int64(4), object(2)\n",
      "memory usage: 55.6+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b00aec80",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.385569</td>\n",
       "      <td>2.305524</td>\n",
       "      <td>29.471443</td>\n",
       "      <td>0.525366</td>\n",
       "      <td>0.383315</td>\n",
       "      <td>32.30542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.487004</td>\n",
       "      <td>0.836662</td>\n",
       "      <td>14.121908</td>\n",
       "      <td>1.104669</td>\n",
       "      <td>0.807466</td>\n",
       "      <td>49.78204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.92500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.45420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.13750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.32920</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Survived      Pclass         Age  Siblings/Spouses Aboard  \\\n",
       "count  887.000000  887.000000  887.000000               887.000000   \n",
       "mean     0.385569    2.305524   29.471443                 0.525366   \n",
       "std      0.487004    0.836662   14.121908                 1.104669   \n",
       "min      0.000000    1.000000    0.420000                 0.000000   \n",
       "25%      0.000000    2.000000   20.250000                 0.000000   \n",
       "50%      0.000000    3.000000   28.000000                 0.000000   \n",
       "75%      1.000000    3.000000   38.000000                 1.000000   \n",
       "max      1.000000    3.000000   80.000000                 8.000000   \n",
       "\n",
       "       Parents/Children Aboard       Fare  \n",
       "count               887.000000  887.00000  \n",
       "mean                  0.383315   32.30542  \n",
       "std                   0.807466   49.78204  \n",
       "min                   0.000000    0.00000  \n",
       "25%                   0.000000    7.92500  \n",
       "50%                   0.000000   14.45420  \n",
       "75%                   0.000000   31.13750  \n",
       "max                   6.000000  512.32920  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "29735913",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>887</td>\n",
       "      <td>887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>887</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Mlle. Emma Sagesser</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>573</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Name   Sex\n",
       "count                   887   887\n",
       "unique                  887     2\n",
       "top     Mlle. Emma Sagesser  male\n",
       "freq                      1   573"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to desctibe just non numeric value use O in include\n",
    "titanic.describe(include='O')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "abd2cd45",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887</td>\n",
       "      <td>887</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.000000</td>\n",
       "      <td>887.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>887</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mlle. Emma Sagesser</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>573</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.385569</td>\n",
       "      <td>2.305524</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.471443</td>\n",
       "      <td>0.525366</td>\n",
       "      <td>0.383315</td>\n",
       "      <td>32.30542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.487004</td>\n",
       "      <td>0.836662</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.121908</td>\n",
       "      <td>1.104669</td>\n",
       "      <td>0.807466</td>\n",
       "      <td>49.78204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.92500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.45420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.13750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.32920</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Survived      Pclass                 Name   Sex         Age  \\\n",
       "count   887.000000  887.000000                  887   887  887.000000   \n",
       "unique         NaN         NaN                  887     2         NaN   \n",
       "top            NaN         NaN  Mlle. Emma Sagesser  male         NaN   \n",
       "freq           NaN         NaN                    1   573         NaN   \n",
       "mean      0.385569    2.305524                  NaN   NaN   29.471443   \n",
       "std       0.487004    0.836662                  NaN   NaN   14.121908   \n",
       "min       0.000000    1.000000                  NaN   NaN    0.420000   \n",
       "25%       0.000000    2.000000                  NaN   NaN   20.250000   \n",
       "50%       0.000000    3.000000                  NaN   NaN   28.000000   \n",
       "75%       1.000000    3.000000                  NaN   NaN   38.000000   \n",
       "max       1.000000    3.000000                  NaN   NaN   80.000000   \n",
       "\n",
       "        Siblings/Spouses Aboard  Parents/Children Aboard       Fare  \n",
       "count                887.000000               887.000000  887.00000  \n",
       "unique                      NaN                      NaN        NaN  \n",
       "top                         NaN                      NaN        NaN  \n",
       "freq                        NaN                      NaN        NaN  \n",
       "mean                   0.525366                 0.383315   32.30542  \n",
       "std                    1.104669                 0.807466   49.78204  \n",
       "min                    0.000000                 0.000000    0.00000  \n",
       "25%                    0.000000                 0.000000    7.92500  \n",
       "50%                    0.000000                 0.000000   14.45420  \n",
       "75%                    1.000000                 0.000000   31.13750  \n",
       "max                    8.000000                 6.000000  512.32920  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.describe(include = 'all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "473e66f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ee86cb0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "887"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ed9736e2",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Owen Harris Braund</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. John Bradley (Florence Briggs Thayer) Cum...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Laina Heikkinen</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. Jacques Heath (Lily May Peel) Futrelle</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. William Henry Allen</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Rev. Juozas Montvila</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Miss. Margaret Edith Graham</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Catherine Helen Johnston</td>\n",
       "      <td>female</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Karl Howell Behr</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Patrick Dooley</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>887 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass                                               Name  \\\n",
       "0           0       3                             Mr. Owen Harris Braund   \n",
       "1           1       1  Mrs. John Bradley (Florence Briggs Thayer) Cum...   \n",
       "2           1       3                              Miss. Laina Heikkinen   \n",
       "3           1       1        Mrs. Jacques Heath (Lily May Peel) Futrelle   \n",
       "4           0       3                            Mr. William Henry Allen   \n",
       "..        ...     ...                                                ...   \n",
       "882         0       2                               Rev. Juozas Montvila   \n",
       "883         1       1                        Miss. Margaret Edith Graham   \n",
       "884         0       3                     Miss. Catherine Helen Johnston   \n",
       "885         1       1                               Mr. Karl Howell Behr   \n",
       "886         0       3                                 Mr. Patrick Dooley   \n",
       "\n",
       "        Sex   Age  Siblings/Spouses Aboard  Parents/Children Aboard  Fare  \n",
       "0      male  22.0                        1                        0   7.0  \n",
       "1    female  38.0                        1                        0  71.0  \n",
       "2    female  26.0                        0                        0   8.0  \n",
       "3    female  35.0                        1                        0  53.0  \n",
       "4      male  35.0                        0                        0   8.0  \n",
       "..      ...   ...                      ...                      ...   ...  \n",
       "882    male  27.0                        0                        0  13.0  \n",
       "883  female  19.0                        0                        0  30.0  \n",
       "884  female   7.0                        1                        2  23.0  \n",
       "885    male  26.0                        0                        0  30.0  \n",
       "886    male  32.0                        0                        0   8.0  \n",
       "\n",
       "[887 rows x 8 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(titanic,0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8294c31a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(887, 8)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1d63cc76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7096"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "28498278",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=887, step=1)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6525d913",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Survived', 'Pclass', 'Name', 'Sex', 'Age', 'Siblings/Spouses Aboard',\n",
       "       'Parents/Children Aboard', 'Fare'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8d930db8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived                                             0\n",
       "Pclass                                               1\n",
       "Name                       Capt. Edward Gifford Crosby\n",
       "Sex                                             female\n",
       "Age                                               0.42\n",
       "Siblings/Spouses Aboard                              0\n",
       "Parents/Children Aboard                              0\n",
       "Fare                                               0.0\n",
       "dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#return min values from each columns\n",
    "titanic.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2d285ac0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived                                                                   1\n",
       "Pclass                                                                     3\n",
       "Name                       the Countess. of (Lucy Noel Martha Dyer-Edward...\n",
       "Sex                                                                     male\n",
       "Age                                                                     80.0\n",
       "Siblings/Spouses Aboard                                                    8\n",
       "Parents/Children Aboard                                                    6\n",
       "Fare                                                                512.3292\n",
       "dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ce714b83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived                    0.385569\n",
       "Pclass                      2.305524\n",
       "Age                        29.471443\n",
       "Siblings/Spouses Aboard     0.525366\n",
       "Parents/Children Aboard     0.383315\n",
       "Fare                       32.305420\n",
       "dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#mean values of each columns\n",
    "titanic.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "59105225",
   "metadata": {},
   "outputs": [
    {
     "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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Algernon Henry Wilson Barkworth</td>\n",
       "      <td>male</td>\n",
       "      <td>80.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Johan Svensson</td>\n",
       "      <td>male</td>\n",
       "      <td>74.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Ramon Artagaveytia</td>\n",
       "      <td>male</td>\n",
       "      <td>71.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>49.5042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. George B Goldschmidt</td>\n",
       "      <td>male</td>\n",
       "      <td>71.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34.6542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Patrick Connors</td>\n",
       "      <td>male</td>\n",
       "      <td>70.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Master. Alden Gates Caldwell</td>\n",
       "      <td>male</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>29.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Helene Barbara Baclini</td>\n",
       "      <td>female</td>\n",
       "      <td>0.75</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>19.2583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>641</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Eugenie Baclini</td>\n",
       "      <td>female</td>\n",
       "      <td>0.75</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>19.2583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Master. Viljo Hamalainen</td>\n",
       "      <td>male</td>\n",
       "      <td>0.67</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14.5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Master. Assad Alexander Thomas</td>\n",
       "      <td>male</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.5167</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>887 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass                                 Name     Sex    Age  \\\n",
       "627         1       1  Mr. Algernon Henry Wilson Barkworth    male  80.00   \n",
       "847         0       3                   Mr. Johan Svensson    male  74.00   \n",
       "490         0       1               Mr. Ramon Artagaveytia    male  71.00   \n",
       "95          0       1             Mr. George B Goldschmidt    male  71.00   \n",
       "115         0       3                  Mr. Patrick Connors    male  70.50   \n",
       "..        ...     ...                                  ...     ...    ...   \n",
       "77          1       2         Master. Alden Gates Caldwell    male   0.83   \n",
       "466         1       3         Miss. Helene Barbara Baclini  female   0.75   \n",
       "641         1       3                Miss. Eugenie Baclini  female   0.75   \n",
       "751         1       2             Master. Viljo Hamalainen    male   0.67   \n",
       "799         1       3       Master. Assad Alexander Thomas    male   0.42   \n",
       "\n",
       "     Siblings/Spouses Aboard  Parents/Children Aboard     Fare  \n",
       "627                        0                        0  30.0000  \n",
       "847                        0                        0   7.7750  \n",
       "490                        0                        0  49.5042  \n",
       "95                         0                        0  34.6542  \n",
       "115                        0                        0   7.7500  \n",
       "..                       ...                      ...      ...  \n",
       "77                         0                        2  29.0000  \n",
       "466                        2                        1  19.2583  \n",
       "641                        2                        1  19.2583  \n",
       "751                        1                        1  14.5000  \n",
       "799                        0                        1   8.5167  \n",
       "\n",
       "[887 rows x 8 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.sort_values(by='Age',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "35dc13e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(titanic['Age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e7b40263",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(titanic[['Age']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2f759e7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#if you want to select one column \n",
    "#from data frame you should decide which output is benefical, data frame or data seires."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "105069d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      22.0\n",
       "1      38.0\n",
       "2      26.0\n",
       "3      35.0\n",
       "4      35.0\n",
       "       ... \n",
       "882    27.0\n",
       "883    19.0\n",
       "884     7.0\n",
       "885    26.0\n",
       "886    32.0\n",
       "Name: Age, Length: 887, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#also you can use dot notation\n",
    "titanic.Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0d617d75",
   "metadata": {},
   "outputs": [],
   "source": [
    "olympics = pd.read_csv(r'athlete_events.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6e23a100",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 271116 entries, 0 to 271115\n",
      "Data columns (total 15 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   ID      271116 non-null  int64  \n",
      " 1   Name    271116 non-null  object \n",
      " 2   Sex     271116 non-null  object \n",
      " 3   Age     261642 non-null  float64\n",
      " 4   Height  210945 non-null  float64\n",
      " 5   Weight  208241 non-null  float64\n",
      " 6   Team    271116 non-null  object \n",
      " 7   NOC     271116 non-null  object \n",
      " 8   Games   271116 non-null  object \n",
      " 9   Year    271116 non-null  int64  \n",
      " 10  Season  271116 non-null  object \n",
      " 11  City    271116 non-null  object \n",
      " 12  Sport   271116 non-null  object \n",
      " 13  Event   271116 non-null  object \n",
      " 14  Medal   39783 non-null   object \n",
      "dtypes: float64(3), int64(2), object(10)\n",
      "memory usage: 31.0+ MB\n"
     ]
    }
   ],
   "source": [
    "olympics.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "918a4457",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .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>ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>271116.000000</td>\n",
       "      <td>261642.000000</td>\n",
       "      <td>210945.000000</td>\n",
       "      <td>208241.000000</td>\n",
       "      <td>271116.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>68248.954396</td>\n",
       "      <td>25.556898</td>\n",
       "      <td>175.338970</td>\n",
       "      <td>70.702393</td>\n",
       "      <td>1978.378480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>39022.286345</td>\n",
       "      <td>6.393561</td>\n",
       "      <td>10.518462</td>\n",
       "      <td>14.348020</td>\n",
       "      <td>29.877632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>1896.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>34643.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>1960.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>68205.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>175.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>1988.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>102097.250000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>2002.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>135571.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>226.000000</td>\n",
       "      <td>214.000000</td>\n",
       "      <td>2016.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  ID            Age         Height         Weight  \\\n",
       "count  271116.000000  261642.000000  210945.000000  208241.000000   \n",
       "mean    68248.954396      25.556898     175.338970      70.702393   \n",
       "std     39022.286345       6.393561      10.518462      14.348020   \n",
       "min         1.000000      10.000000     127.000000      25.000000   \n",
       "25%     34643.000000      21.000000     168.000000      60.000000   \n",
       "50%     68205.000000      24.000000     175.000000      70.000000   \n",
       "75%    102097.250000      28.000000     183.000000      79.000000   \n",
       "max    135571.000000      97.000000     226.000000     214.000000   \n",
       "\n",
       "                Year  \n",
       "count  271116.000000  \n",
       "mean     1978.378480  \n",
       "std        29.877632  \n",
       "min      1896.000000  \n",
       "25%      1960.000000  \n",
       "50%      1988.000000  \n",
       "75%      2002.000000  \n",
       "max      2016.000000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "088255c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID                      Name Sex   Age  Height  Weight            Team  \\\n",
       "0   1                 A Dijiang   M  24.0   180.0    80.0           China   \n",
       "1   2                  A Lamusi   M  23.0   170.0    60.0           China   \n",
       "2   3       Gunnar Nielsen Aaby   M  24.0     NaN     NaN         Denmark   \n",
       "3   4      Edgar Lindenau Aabye   M  34.0     NaN     NaN  Denmark/Sweden   \n",
       "4   5  Christine Jacoba Aaftink   F  21.0   185.0    82.0     Netherlands   \n",
       "\n",
       "   NOC        Games  Year  Season       City          Sport  \\\n",
       "0  CHN  1992 Summer  1992  Summer  Barcelona     Basketball   \n",
       "1  CHN  2012 Summer  2012  Summer     London           Judo   \n",
       "2  DEN  1920 Summer  1920  Summer  Antwerpen       Football   \n",
       "3  DEN  1900 Summer  1900  Summer      Paris     Tug-Of-War   \n",
       "4  NED  1988 Winter  1988  Winter    Calgary  Speed Skating   \n",
       "\n",
       "                              Event Medal  \n",
       "0       Basketball Men's Basketball   NaN  \n",
       "1      Judo Men's Extra-Lightweight   NaN  \n",
       "2           Football Men's Football   NaN  \n",
       "3       Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "4  Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "dc0ad624",
   "metadata": {},
   "outputs": [],
   "source": [
    "olympics = pd.read_csv(r'athlete_events.csv',index_col = 'ID')\n",
    "#index_col:Column(s) to use as the row labels of the DataFrame, either given as string name or column index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eb1826db",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ID</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135569</th>\n",
       "      <td>Andrzej ya</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Poland-1</td>\n",
       "      <td>POL</td>\n",
       "      <td>1976 Winter</td>\n",
       "      <td>1976</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Innsbruck</td>\n",
       "      <td>Luge</td>\n",
       "      <td>Luge Mixed (Men)'s Doubles</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Individual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Team</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2002 Winter</td>\n",
       "      <td>2002</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>271116 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Name Sex   Age  Height  Weight            Team  \\\n",
       "ID                                                                           \n",
       "1                      A Dijiang   M  24.0   180.0    80.0           China   \n",
       "2                       A Lamusi   M  23.0   170.0    60.0           China   \n",
       "3            Gunnar Nielsen Aaby   M  24.0     NaN     NaN         Denmark   \n",
       "4           Edgar Lindenau Aabye   M  34.0     NaN     NaN  Denmark/Sweden   \n",
       "5       Christine Jacoba Aaftink   F  21.0   185.0    82.0     Netherlands   \n",
       "...                          ...  ..   ...     ...     ...             ...   \n",
       "135569                Andrzej ya   M  29.0   179.0    89.0        Poland-1   \n",
       "135570                  Piotr ya   M  27.0   176.0    59.0          Poland   \n",
       "135570                  Piotr ya   M  27.0   176.0    59.0          Poland   \n",
       "135571        Tomasz Ireneusz ya   M  30.0   185.0    96.0          Poland   \n",
       "135571        Tomasz Ireneusz ya   M  34.0   185.0    96.0          Poland   \n",
       "\n",
       "        NOC        Games  Year  Season            City          Sport  \\\n",
       "ID                                                                      \n",
       "1       CHN  1992 Summer  1992  Summer       Barcelona     Basketball   \n",
       "2       CHN  2012 Summer  2012  Summer          London           Judo   \n",
       "3       DEN  1920 Summer  1920  Summer       Antwerpen       Football   \n",
       "4       DEN  1900 Summer  1900  Summer           Paris     Tug-Of-War   \n",
       "5       NED  1988 Winter  1988  Winter         Calgary  Speed Skating   \n",
       "...     ...          ...   ...     ...             ...            ...   \n",
       "135569  POL  1976 Winter  1976  Winter       Innsbruck           Luge   \n",
       "135570  POL  2014 Winter  2014  Winter           Sochi    Ski Jumping   \n",
       "135570  POL  2014 Winter  2014  Winter           Sochi    Ski Jumping   \n",
       "135571  POL  1998 Winter  1998  Winter          Nagano      Bobsleigh   \n",
       "135571  POL  2002 Winter  2002  Winter  Salt Lake City      Bobsleigh   \n",
       "\n",
       "                                           Event Medal  \n",
       "ID                                                      \n",
       "1                    Basketball Men's Basketball   NaN  \n",
       "2                   Judo Men's Extra-Lightweight   NaN  \n",
       "3                        Football Men's Football   NaN  \n",
       "4                    Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "5               Speed Skating Women's 500 metres   NaN  \n",
       "...                                          ...   ...  \n",
       "135569                Luge Mixed (Men)'s Doubles   NaN  \n",
       "135570  Ski Jumping Men's Large Hill, Individual   NaN  \n",
       "135570        Ski Jumping Men's Large Hill, Team   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  \n",
       "\n",
       "[271116 rows x 14 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "olympics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5c14ebdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name                        A Dijiang\n",
       "Sex                                 M\n",
       "Age                              24.0\n",
       "Height                          180.0\n",
       "Weight                           80.0\n",
       "Team                            China\n",
       "NOC                               CHN\n",
       "Games                     1992 Summer\n",
       "Year                             1992\n",
       "Season                         Summer\n",
       "City                        Barcelona\n",
       "Sport                      Basketball\n",
       "Event     Basketball Men's Basketball\n",
       "Medal                             NaN\n",
       "Name: 1, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ab893363",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
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   ]
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  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cc694dc8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name        Tomasz Ireneusz ya\n",
       "Sex                          M\n",
       "Age                       34.0\n",
       "Height                   185.0\n",
       "Weight                    96.0\n",
       "Team                    Poland\n",
       "NOC                        POL\n",
       "Games              2002 Winter\n",
       "Year                      2002\n",
       "Season                  Winter\n",
       "City            Salt Lake City\n",
       "Sport                Bobsleigh\n",
       "Event     Bobsleigh Men's Four\n",
       "Medal                      NaN\n",
       "Name: 135571, dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.iloc[-1]"
   ]
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  {
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   "execution_count": 23,
   "id": "ed44fdfd",
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   "outputs": [
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
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       "                   Name Sex   Age  Height  Weight     Team  NOC        Games  \\\n",
       "ID                                                                             \n",
       "1             A Dijiang   M  24.0   180.0    80.0    China  CHN  1992 Summer   \n",
       "2              A Lamusi   M  23.0   170.0    60.0    China  CHN  2012 Summer   \n",
       "3   Gunnar Nielsen Aaby   M  24.0     NaN     NaN  Denmark  DEN  1920 Summer   \n",
       "\n",
       "    Year  Season       City       Sport                         Event Medal  \n",
       "ID                                                                           \n",
       "1   1992  Summer  Barcelona  Basketball   Basketball Men's Basketball   NaN  \n",
       "2   2012  Summer     London        Judo  Judo Men's Extra-Lightweight   NaN  \n",
       "3   1920  Summer  Antwerpen    Football       Football Men's Football   NaN  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "olympics.iloc[[0,1,2]]"
   ]
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   "execution_count": 24,
   "id": "7d38f0a6",
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   "outputs": [
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       "      <td>80.0</td>\n",
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       "      <td>A Lamusi</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
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       "      <th>3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>M</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
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       "      <td>1920 Summer</td>\n",
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       "      <td>Antwerpen</td>\n",
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       "      <td>Football Men's Football</td>\n",
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       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Name Sex   Age  Height  Weight            Team  NOC  \\\n",
       "ID                                                                            \n",
       "1                  A Dijiang   M  24.0   180.0    80.0           China  CHN   \n",
       "2                   A Lamusi   M  23.0   170.0    60.0           China  CHN   \n",
       "3        Gunnar Nielsen Aaby   M  24.0     NaN     NaN         Denmark  DEN   \n",
       "4       Edgar Lindenau Aabye   M  34.0     NaN     NaN  Denmark/Sweden  DEN   \n",
       "5   Christine Jacoba Aaftink   F  21.0   185.0    82.0     Netherlands  NED   \n",
       "\n",
       "          Games  Year  Season       City          Sport  \\\n",
       "ID                                                        \n",
       "1   1992 Summer  1992  Summer  Barcelona     Basketball   \n",
       "2   2012 Summer  2012  Summer     London           Judo   \n",
       "3   1920 Summer  1920  Summer  Antwerpen       Football   \n",
       "4   1900 Summer  1900  Summer      Paris     Tug-Of-War   \n",
       "5   1988 Winter  1988  Winter    Calgary  Speed Skating   \n",
       "\n",
       "                               Event Medal  \n",
       "ID                                          \n",
       "1        Basketball Men's Basketball   NaN  \n",
       "2       Judo Men's Extra-Lightweight   NaN  \n",
       "3            Football Men's Football   NaN  \n",
       "4        Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "5   Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.iloc[0:5]"
   ]
  },
  {
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   "execution_count": 25,
   "id": "cf6a085a",
   "metadata": {},
   "outputs": [
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       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>135569</th>\n",
       "      <td>Andrzej ya</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Poland-1</td>\n",
       "      <td>POL</td>\n",
       "      <td>1976 Winter</td>\n",
       "      <td>1976</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Innsbruck</td>\n",
       "      <td>Luge</td>\n",
       "      <td>Luge Mixed (Men)'s Doubles</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Individual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Team</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2002 Winter</td>\n",
       "      <td>2002</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Name Sex   Age  Height  Weight      Team  NOC  \\\n",
       "ID                                                                    \n",
       "135569          Andrzej ya   M  29.0   179.0    89.0  Poland-1  POL   \n",
       "135570            Piotr ya   M  27.0   176.0    59.0    Poland  POL   \n",
       "135570            Piotr ya   M  27.0   176.0    59.0    Poland  POL   \n",
       "135571  Tomasz Ireneusz ya   M  30.0   185.0    96.0    Poland  POL   \n",
       "135571  Tomasz Ireneusz ya   M  34.0   185.0    96.0    Poland  POL   \n",
       "\n",
       "              Games  Year  Season            City        Sport  \\\n",
       "ID                                                               \n",
       "135569  1976 Winter  1976  Winter       Innsbruck         Luge   \n",
       "135570  2014 Winter  2014  Winter           Sochi  Ski Jumping   \n",
       "135570  2014 Winter  2014  Winter           Sochi  Ski Jumping   \n",
       "135571  1998 Winter  1998  Winter          Nagano    Bobsleigh   \n",
       "135571  2002 Winter  2002  Winter  Salt Lake City    Bobsleigh   \n",
       "\n",
       "                                           Event Medal  \n",
       "ID                                                      \n",
       "135569                Luge Mixed (Men)'s Doubles   NaN  \n",
       "135570  Ski Jumping Men's Large Hill, Individual   NaN  \n",
       "135570        Ski Jumping Men's Large Hill, Team   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.iloc[-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8b91abf3",
   "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>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Kjetil Andr Aamodt</td>\n",
       "      <td>M</td>\n",
       "      <td>22.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>Norway</td>\n",
       "      <td>NOR</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Alpine Skiing</td>\n",
       "      <td>Alpine Skiing Men's Combined</td>\n",
       "      <td>Silver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Meelis Aasme</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>Estonia</td>\n",
       "      <td>EST</td>\n",
       "      <td>2002 Winter</td>\n",
       "      <td>2002</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Cross Country Skiing</td>\n",
       "      <td>Cross Country Skiing Men's 4 x 10 kilometres R...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Name Sex   Age  Height  Weight         Team  NOC  \\\n",
       "ID                                                                         \n",
       "5   Christine Jacoba Aaftink   F  21.0   185.0    82.0  Netherlands  NED   \n",
       "20        Kjetil Andr Aamodt   M  22.0   176.0    85.0       Norway  NOR   \n",
       "44              Meelis Aasme   M  29.0   182.0    73.0      Estonia  EST   \n",
       "\n",
       "          Games  Year  Season            City                 Sport  \\\n",
       "ID                                                                    \n",
       "5   1988 Winter  1988  Winter         Calgary         Speed Skating   \n",
       "20  1994 Winter  1994  Winter     Lillehammer         Alpine Skiing   \n",
       "44  2002 Winter  2002  Winter  Salt Lake City  Cross Country Skiing   \n",
       "\n",
       "                                                Event   Medal  \n",
       "ID                                                             \n",
       "5                    Speed Skating Women's 500 metres     NaN  \n",
       "20                       Alpine Skiing Men's Combined  Silver  \n",
       "44  Cross Country Skiing Men's 4 x 10 kilometres R...     NaN  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.iloc[[4,67,123]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0969212e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'M'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#with iloc, you can get two index and return the cell of data frame\n",
    "olympics.iloc[0,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b37f221f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name      A Dijiang\n",
       "Sex               M\n",
       "Age            24.0\n",
       "Height        180.0\n",
       "Weight         80.0\n",
       "Name: 1, dtype: object"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.iloc[0,0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5193844e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Name Sex   Age  Height  Weight\n",
       "ID                                               \n",
       "1             A Dijiang   M  24.0   180.0    80.0\n",
       "2              A Lamusi   M  23.0   170.0    60.0\n",
       "3   Gunnar Nielsen Aaby   M  24.0     NaN     NaN"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.iloc[0:3,0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "335fb215",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name          Gunnar Nielsen Aaby\n",
       "Sex                             M\n",
       "Age                          24.0\n",
       "Height                        NaN\n",
       "Weight                        NaN\n",
       "Team                      Denmark\n",
       "NOC                           DEN\n",
       "Games                 1920 Summer\n",
       "Year                         1920\n",
       "Season                     Summer\n",
       "City                    Antwerpen\n",
       "Sport                    Football\n",
       "Event     Football Men's Football\n",
       "Medal                         NaN\n",
       "Name: 3, dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#.loc[] is primarily label based, but may also be used with a boolean array.\n",
    "olympics.loc[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ff3391f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[3,'Medal']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a1cc1427",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Medal     NaN\n",
       "Year     1920\n",
       "Name: 3, dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[3,['Medal','Year']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "78deecac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th></th>\n",
       "      <th>Medal</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gold</td>\n",
       "      <td>1900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Medal  Year\n",
       "ID            \n",
       "3    NaN  1920\n",
       "4   Gold  1900"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[[3,4],['Medal','Year']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ffa857a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>1</th>\n",
       "      <td>A Dijiang</td>\n",
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       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
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       "      <th>2</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>M</td>\n",
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       "      <th>3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Name Sex   Age  Height  Weight            Team\n",
       "ID                                                                    \n",
       "1                  A Dijiang   M  24.0   180.0    80.0           China\n",
       "2                   A Lamusi   M  23.0   170.0    60.0           China\n",
       "3        Gunnar Nielsen Aaby   M  24.0     NaN     NaN         Denmark\n",
       "4       Edgar Lindenau Aabye   M  34.0     NaN     NaN  Denmark/Sweden\n",
       "5   Christine Jacoba Aaftink   F  21.0   185.0    82.0     Netherlands\n",
       "5   Christine Jacoba Aaftink   F  21.0   185.0    82.0     Netherlands\n",
       "5   Christine Jacoba Aaftink   F  25.0   185.0    82.0     Netherlands\n",
       "5   Christine Jacoba Aaftink   F  25.0   185.0    82.0     Netherlands\n",
       "5   Christine Jacoba Aaftink   F  27.0   185.0    82.0     Netherlands\n",
       "5   Christine Jacoba Aaftink   F  27.0   185.0    82.0     Netherlands"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[1:5,'Name':'Team']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "d9395d4a",
   "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>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1992 Winter</td>\n",
       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1992 Winter</td>\n",
       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Name Sex   Age  Height  Weight         Team  NOC  \\\n",
       "ID                                                                         \n",
       "5   Christine Jacoba Aaftink   F  21.0   185.0    82.0  Netherlands  NED   \n",
       "5   Christine Jacoba Aaftink   F  21.0   185.0    82.0  Netherlands  NED   \n",
       "5   Christine Jacoba Aaftink   F  25.0   185.0    82.0  Netherlands  NED   \n",
       "5   Christine Jacoba Aaftink   F  25.0   185.0    82.0  Netherlands  NED   \n",
       "5   Christine Jacoba Aaftink   F  27.0   185.0    82.0  Netherlands  NED   \n",
       "5   Christine Jacoba Aaftink   F  27.0   185.0    82.0  Netherlands  NED   \n",
       "\n",
       "          Games  Year  Season         City          Sport  \\\n",
       "ID                                                          \n",
       "5   1988 Winter  1988  Winter      Calgary  Speed Skating   \n",
       "5   1988 Winter  1988  Winter      Calgary  Speed Skating   \n",
       "5   1992 Winter  1992  Winter  Albertville  Speed Skating   \n",
       "5   1992 Winter  1992  Winter  Albertville  Speed Skating   \n",
       "5   1994 Winter  1994  Winter  Lillehammer  Speed Skating   \n",
       "5   1994 Winter  1994  Winter  Lillehammer  Speed Skating   \n",
       "\n",
       "                                 Event Medal  \n",
       "ID                                            \n",
       "5     Speed Skating Women's 500 metres   NaN  \n",
       "5   Speed Skating Women's 1,000 metres   NaN  \n",
       "5     Speed Skating Women's 500 metres   NaN  \n",
       "5   Speed Skating Women's 1,000 metres   NaN  \n",
       "5     Speed Skating Women's 500 metres   NaN  \n",
       "5   Speed Skating Women's 1,000 metres   NaN  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "df10737e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Data Series\n",
    "age = olympics['Age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e429641c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID\n",
       "1         24.0\n",
       "2         23.0\n",
       "3         24.0\n",
       "4         34.0\n",
       "5         21.0\n",
       "          ... \n",
       "135569    29.0\n",
       "135570    27.0\n",
       "135570    27.0\n",
       "135571    30.0\n",
       "135571    34.0\n",
       "Name: Age, Length: 271116, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "957176ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    261642.000000\n",
       "mean         25.556898\n",
       "std           6.393561\n",
       "min          10.000000\n",
       "25%          21.000000\n",
       "50%          24.000000\n",
       "75%          28.000000\n",
       "max          97.000000\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1012547c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "261642"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "526aa28c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "271116"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "466e0918",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "271116"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(age)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "045e438c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sum function can't handle nan values\n",
    "sum(age)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b8cc8ae5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6686758.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a0d94461",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6686758.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#skipna is a prameter in sum method to ignore the nan values\n",
    "age.sum(skipna=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "45aabd49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.sum(skipna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ff8ca63f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.556898357297374"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f5ffcec6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f8aede80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.393560847032701"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "72c30f0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ede826dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "97.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "706c97c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([24., 23., 34., 21., 25., 27., 31., 33., 18., 26., 22., 30., 32.,\n",
       "       28., 54., 20., 17., 43., 47., 29., 41., 45., 49., 53., 57., nan,\n",
       "       19., 38., 35., 16., 37., 15., 42., 46., 40., 36., 14., 39., 48.,\n",
       "       52., 44., 55., 50., 71., 63., 51., 58., 13., 60., 75., 65., 56.,\n",
       "       64., 68., 84., 12., 72., 59., 61., 70., 74., 62., 67., 69., 73.,\n",
       "       66., 11., 76., 88., 96., 80., 10., 81., 77., 97.])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#return unique values\n",
    "age.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "af769d5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to count number of unique element, use len function\n",
    "len(age.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "25595e8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "74"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#also this method return number of unique values\n",
    "age.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ebd378de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#you can see, there is a differente, nunique method has parameteres for NAN\n",
    "age.nunique(dropna=False)\n",
    "#dropna is True by defualt, so didn't count NAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7a9619f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.0    21875\n",
       "24.0    21720\n",
       "22.0    20814\n",
       "25.0    19707\n",
       "21.0    19164\n",
       "        ...  \n",
       "77.0        2\n",
       "84.0        1\n",
       "96.0        1\n",
       "97.0        1\n",
       "10.0        1\n",
       "Name: Age, Length: 74, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to frequency of each element, use this method\n",
    "age.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "95a9caf4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28.0    14043\n",
       "42.0      866\n",
       "41.0      953\n",
       "63.0       56\n",
       "96.0        1\n",
       "        ...  \n",
       "35.0     3133\n",
       "30.0     9488\n",
       "37.0     1953\n",
       "74.0       12\n",
       "32.0     6246\n",
       "Name: Age, Length: 74, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you set sort by false, the data show by apperiance\n",
    "age.value_counts(sort = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "56422a0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.0    21875\n",
       "24.0    21720\n",
       "22.0    20814\n",
       "25.0    19707\n",
       "21.0    19164\n",
       "        ...  \n",
       "77.0        2\n",
       "84.0        1\n",
       "96.0        1\n",
       "97.0        1\n",
       "10.0        1\n",
       "Name: Age, Length: 74, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#this parameter ignore NaN\n",
    "age.value_counts(dropna=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e5ab5d83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "84.0        1\n",
       "97.0        1\n",
       "96.0        1\n",
       "10.0        1\n",
       "81.0        2\n",
       "        ...  \n",
       "21.0    19164\n",
       "25.0    19707\n",
       "22.0    20814\n",
       "24.0    21720\n",
       "23.0    21875\n",
       "Name: Age, Length: 74, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.value_counts(ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "008fe70f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.0    0.083607\n",
       "24.0    0.083014\n",
       "22.0    0.079551\n",
       "25.0    0.075320\n",
       "21.0    0.073245\n",
       "          ...   \n",
       "77.0    0.000008\n",
       "84.0    0.000004\n",
       "96.0    0.000004\n",
       "97.0    0.000004\n",
       "10.0    0.000004\n",
       "Name: Age, Length: 74, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.value_counts(normalize=True)\n",
    "# If True then the object returned will contain the relative\n",
    "    #frequencies of the unique values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5ee2f267",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9.912, 27.4]    184541\n",
       "(27.4, 44.8]      72695\n",
       "(44.8, 62.2]       3966\n",
       "(62.2, 79.6]        429\n",
       "(79.6, 97.0]         11\n",
       "Name: Age, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Rather than count values, group them into half-open bins\n",
    "age.value_counts(bins=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4ff737c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = olympics['Name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e23e4c76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID\n",
       "1                   A Dijiang\n",
       "2                    A Lamusi\n",
       "3         Gunnar Nielsen Aaby\n",
       "4        Edgar Lindenau Aabye\n",
       "5    Christine Jacoba Aaftink\n",
       "Name: Name, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8000d417",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID\n",
       "135569            Andrzej ya\n",
       "135570              Piotr ya\n",
       "135570              Piotr ya\n",
       "135571    Tomasz Ireneusz ya\n",
       "135571    Tomasz Ireneusz ya\n",
       "Name: Name, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "aa89fd24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                   271116\n",
       "unique                  134732\n",
       "top       Robert Tait McKenzie\n",
       "freq                        58\n",
       "Name: Name, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6cbc72d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(271116,)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2ce6e42d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "271116"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0f0d0479",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "271116"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7b9c6f16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'  Gabrielle Marie \"Gabby\" Adcock (White-)'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "aea3e07a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['A Dijiang', 'A Lamusi', 'Gunnar Nielsen Aaby', ..., 'Andrzej ya',\n",
       "       'Piotr ya', 'Tomasz Ireneusz ya'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "da6e4195",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "134732"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(name.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c4bd777d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "134732"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b63da28a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "134732"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.nunique(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "db5d2cee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "134732"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.nunique(dropna=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4cb056e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Robert Tait McKenzie           58\n",
       "Heikki Ilmari Savolainen       39\n",
       "Joseph \"Josy\" Stoffel          38\n",
       "Ioannis Theofilakis            36\n",
       "Takashi Ono                    33\n",
       "                               ..\n",
       "Nina Hemmer                     1\n",
       "Peter G. Luck                   1\n",
       "Stephen \"Steve\" Breheny         1\n",
       "Hugo Barth                      1\n",
       "Alphonse \"Fons\" Huylebroeck     1\n",
       "Name: Name, Length: 134732, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d7b9d5f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Robert Tait McKenzie           0.000214\n",
       "Heikki Ilmari Savolainen       0.000144\n",
       "Joseph \"Josy\" Stoffel          0.000140\n",
       "Ioannis Theofilakis            0.000133\n",
       "Takashi Ono                    0.000122\n",
       "                                 ...   \n",
       "Nina Hemmer                    0.000004\n",
       "Peter G. Luck                  0.000004\n",
       "Stephen \"Steve\" Breheny        0.000004\n",
       "Hugo Barth                     0.000004\n",
       "Alphonse \"Fons\" Huylebroeck    0.000004\n",
       "Name: Name, Length: 134732, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "55793d1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Robert Tait McKenzie        0.000214\n",
       "Heikki Ilmari Savolainen    0.000144\n",
       "Joseph \"Josy\" Stoffel       0.000140\n",
       "Ioannis Theofilakis         0.000133\n",
       "Takashi Ono                 0.000122\n",
       "Name: Name, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name.value_counts(normalize=True).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "eff39086",
   "metadata": {},
   "outputs": [],
   "source": [
    "summer = pd.read_csv(r'Summer-Olympic-medals-1976-to-2008.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ee6f9db6",
   "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>City</th>\n",
       "      <th>Year</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Discipline</th>\n",
       "      <th>Event</th>\n",
       "      <th>Athlete</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country_Code</th>\n",
       "      <th>Country</th>\n",
       "      <th>Event_gender</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Montreal</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Diving</td>\n",
       "      <td>3m springboard</td>\n",
       "      <td>K�HLER, Christa</td>\n",
       "      <td>Women</td>\n",
       "      <td>GDR</td>\n",
       "      <td>East Germany</td>\n",
       "      <td>W</td>\n",
       "      <td>Silver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Montreal</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Diving</td>\n",
       "      <td>3m springboard</td>\n",
       "      <td>KOSENKOV, Aleksandr</td>\n",
       "      <td>Men</td>\n",
       "      <td>URS</td>\n",
       "      <td>Soviet Union</td>\n",
       "      <td>M</td>\n",
       "      <td>Bronze</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Montreal</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Diving</td>\n",
       "      <td>3m springboard</td>\n",
       "      <td>BOGGS, Philip George</td>\n",
       "      <td>Men</td>\n",
       "      <td>USA</td>\n",
       "      <td>United States</td>\n",
       "      <td>M</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Montreal</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Diving</td>\n",
       "      <td>3m springboard</td>\n",
       "      <td>CAGNOTTO, Giorgio Franco</td>\n",
       "      <td>Men</td>\n",
       "      <td>ITA</td>\n",
       "      <td>Italy</td>\n",
       "      <td>M</td>\n",
       "      <td>Silver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Montreal</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>Aquatics</td>\n",
       "      <td>Diving</td>\n",
       "      <td>10m platform</td>\n",
       "      <td>WILSON, Deborah Keplar</td>\n",
       "      <td>Women</td>\n",
       "      <td>USA</td>\n",
       "      <td>United States</td>\n",
       "      <td>W</td>\n",
       "      <td>Bronze</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       City    Year     Sport Discipline           Event  \\\n",
       "0  Montreal  1976.0  Aquatics     Diving  3m springboard   \n",
       "1  Montreal  1976.0  Aquatics     Diving  3m springboard   \n",
       "2  Montreal  1976.0  Aquatics     Diving  3m springboard   \n",
       "3  Montreal  1976.0  Aquatics     Diving  3m springboard   \n",
       "4  Montreal  1976.0  Aquatics     Diving    10m platform   \n",
       "\n",
       "                    Athlete Gender Country_Code        Country Event_gender  \\\n",
       "0           K�HLER, Christa  Women          GDR   East Germany            W   \n",
       "1       KOSENKOV, Aleksandr    Men          URS   Soviet Union            M   \n",
       "2      BOGGS, Philip George    Men          USA  United States            M   \n",
       "3  CAGNOTTO, Giorgio Franco    Men          ITA          Italy            M   \n",
       "4    WILSON, Deborah Keplar  Women          USA  United States            W   \n",
       "\n",
       "    Medal  \n",
       "0  Silver  \n",
       "1  Bronze  \n",
       "2    Gold  \n",
       "3  Silver  \n",
       "4  Bronze  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summer.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7e514347",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City                   Montreal\n",
       "Year                     1976.0\n",
       "Sport                  Aquatics\n",
       "Discipline               Diving\n",
       "Event            3m springboard\n",
       "Athlete         K�HLER, Christa\n",
       "Gender                    Women\n",
       "Country_Code                GDR\n",
       "Country            East Germany\n",
       "Event_gender                  W\n",
       "Medal                    Silver\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summer.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "02deeabe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                 K�HLER, Christa\n",
       "1             KOSENKOV, Aleksandr\n",
       "2            BOGGS, Philip George\n",
       "3        CAGNOTTO, Giorgio Franco\n",
       "4          WILSON, Deborah Keplar\n",
       "                   ...           \n",
       "15428          GUENOT, Christophe\n",
       "15429         KVIRKELIA, Manuchar\n",
       "15430            RAHIMOV, Vitaliy\n",
       "15431              GUENOT, Steeve\n",
       "15432               LOPEZ, Mijain\n",
       "Name: Athlete, Length: 15433, dtype: object"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#for creating data series, you can use column for importing data\n",
    "pd.read_csv(r'Summer-Olympic-medals-1976-to-2008.csv',squeeze=True,usecols=['Athlete'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "17207dfa",
   "metadata": {},
   "outputs": [],
   "source": [
    "athlete = pd.read_csv(r'Summer-Olympic-medals-1976-to-2008.csv',squeeze=True,usecols=['Athlete'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b6ed013a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             K�HLER, Christa\n",
       "1         KOSENKOV, Aleksandr\n",
       "2        BOGGS, Philip George\n",
       "3    CAGNOTTO, Giorgio Franco\n",
       "4      WILSON, Deborah Keplar\n",
       "Name: Athlete, dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "athlete.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "f4cf32e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15428     GUENOT, Christophe\n",
       "15429    KVIRKELIA, Manuchar\n",
       "15430       RAHIMOV, Vitaliy\n",
       "15431         GUENOT, Steeve\n",
       "15432          LOPEZ, Mijain\n",
       "Name: Athlete, dtype: object"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "athlete.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "fbcfb1a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14641         AAMODT, Ragnhild\n",
       "5300     AARDENBURG, Willemien\n",
       "8892         AARDEWIJN, Pepijn\n",
       "8495      AARONES, Ann Kristin\n",
       "14412         ABAJO, Jose Luis\n",
       "                 ...          \n",
       "882                        NaN\n",
       "883                        NaN\n",
       "884                        NaN\n",
       "885                        NaN\n",
       "886                        NaN\n",
       "Name: Athlete, Length: 15433, dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "athlete.sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f5b530e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#if you want sort the values of data series\n",
    "athlete.sort_values(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4f316c94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14641         AAMODT, Ragnhild\n",
       "5300     AARDENBURG, Willemien\n",
       "8892         AARDEWIJN, Pepijn\n",
       "8495      AARONES, Ann Kristin\n",
       "14412         ABAJO, Jose Luis\n",
       "                 ...          \n",
       "882                        NaN\n",
       "883                        NaN\n",
       "884                        NaN\n",
       "885                        NaN\n",
       "886                        NaN\n",
       "Name: Athlete, Length: 15433, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "athlete"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "fed11d77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID\n",
       "128719    97.0\n",
       "49663     96.0\n",
       "31173     88.0\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want 3th largest age\n",
    "age.sort_values(ascending=False).head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "0442cb32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID\n",
       "128719    97.0\n",
       "49663     96.0\n",
       "31173     88.0\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#also you can use nlargest\n",
    "age.nlargest(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "e4539b94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID\n",
       "71691     10.0\n",
       "126307    11.0\n",
       "51268     11.0\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.sort_values(ascending=True).iloc[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "5e66dfd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID\n",
       "71691    10.0\n",
       "22411    11.0\n",
       "37333    11.0\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age.nsmallest(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "0ff91adf",
   "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>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135569</th>\n",
       "      <td>Andrzej ya</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Poland-1</td>\n",
       "      <td>POL</td>\n",
       "      <td>1976 Winter</td>\n",
       "      <td>1976</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Innsbruck</td>\n",
       "      <td>Luge</td>\n",
       "      <td>Luge Mixed (Men)'s Doubles</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Individual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Team</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2002 Winter</td>\n",
       "      <td>2002</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>271116 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Name Sex   Age  Height  Weight            Team  \\\n",
       "ID                                                                           \n",
       "1                      A Dijiang   M  24.0   180.0    80.0           China   \n",
       "2                       A Lamusi   M  23.0   170.0    60.0           China   \n",
       "3            Gunnar Nielsen Aaby   M  24.0     NaN     NaN         Denmark   \n",
       "4           Edgar Lindenau Aabye   M  34.0     NaN     NaN  Denmark/Sweden   \n",
       "5       Christine Jacoba Aaftink   F  21.0   185.0    82.0     Netherlands   \n",
       "...                          ...  ..   ...     ...     ...             ...   \n",
       "135569                Andrzej ya   M  29.0   179.0    89.0        Poland-1   \n",
       "135570                  Piotr ya   M  27.0   176.0    59.0          Poland   \n",
       "135570                  Piotr ya   M  27.0   176.0    59.0          Poland   \n",
       "135571        Tomasz Ireneusz ya   M  30.0   185.0    96.0          Poland   \n",
       "135571        Tomasz Ireneusz ya   M  34.0   185.0    96.0          Poland   \n",
       "\n",
       "        NOC        Games  Year  Season            City          Sport  \\\n",
       "ID                                                                      \n",
       "1       CHN  1992 Summer  1992  Summer       Barcelona     Basketball   \n",
       "2       CHN  2012 Summer  2012  Summer          London           Judo   \n",
       "3       DEN  1920 Summer  1920  Summer       Antwerpen       Football   \n",
       "4       DEN  1900 Summer  1900  Summer           Paris     Tug-Of-War   \n",
       "5       NED  1988 Winter  1988  Winter         Calgary  Speed Skating   \n",
       "...     ...          ...   ...     ...             ...            ...   \n",
       "135569  POL  1976 Winter  1976  Winter       Innsbruck           Luge   \n",
       "135570  POL  2014 Winter  2014  Winter           Sochi    Ski Jumping   \n",
       "135570  POL  2014 Winter  2014  Winter           Sochi    Ski Jumping   \n",
       "135571  POL  1998 Winter  1998  Winter          Nagano      Bobsleigh   \n",
       "135571  POL  2002 Winter  2002  Winter  Salt Lake City      Bobsleigh   \n",
       "\n",
       "                                           Event Medal  \n",
       "ID                                                      \n",
       "1                    Basketball Men's Basketball   NaN  \n",
       "2                   Judo Men's Extra-Lightweight   NaN  \n",
       "3                        Football Men's Football   NaN  \n",
       "4                    Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "5               Speed Skating Women's 500 metres   NaN  \n",
       "...                                          ...   ...  \n",
       "135569                Luge Mixed (Men)'s Doubles   NaN  \n",
       "135570  Ski Jumping Men's Large Hill, Individual   NaN  \n",
       "135570        Ski Jumping Men's Large Hill, Team   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  \n",
       "\n",
       "[271116 rows x 14 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "0b74ef51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "128719"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.Age.idxmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "b42791d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "71691"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.Age.idxmin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "cfe6df96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name                         Dimitrios Loundras\n",
       "Sex                                           M\n",
       "Age                                        10.0\n",
       "Height                                      NaN\n",
       "Weight                                      NaN\n",
       "Team              Ethnikos Gymnastikos Syllogos\n",
       "NOC                                         GRE\n",
       "Games                               1896 Summer\n",
       "Year                                       1896\n",
       "Season                                   Summer\n",
       "City                                     Athina\n",
       "Sport                                Gymnastics\n",
       "Event     Gymnastics Men's Parallel Bars, Teams\n",
       "Medal                                    Bronze\n",
       "Name: 71691, dtype: object"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[71691]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "40558c30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name                           John Quincy Adams Ward\n",
       "Sex                                                 M\n",
       "Age                                              97.0\n",
       "Height                                            NaN\n",
       "Weight                                            NaN\n",
       "Team                                    United States\n",
       "NOC                                               USA\n",
       "Games                                     1928 Summer\n",
       "Year                                             1928\n",
       "Season                                         Summer\n",
       "City                                        Amsterdam\n",
       "Sport                                Art Competitions\n",
       "Event     Art Competitions Mixed Sculpturing, Statues\n",
       "Medal                                             NaN\n",
       "Name: 128719, dtype: object"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[128719]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "561715d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 271116 entries, 1 to 135571\n",
      "Data columns (total 14 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   Name    271116 non-null  object \n",
      " 1   Sex     271116 non-null  object \n",
      " 2   Age     261642 non-null  float64\n",
      " 3   Height  210945 non-null  float64\n",
      " 4   Weight  208241 non-null  float64\n",
      " 5   Team    271116 non-null  object \n",
      " 6   NOC     271116 non-null  object \n",
      " 7   Games   271116 non-null  object \n",
      " 8   Year    271116 non-null  int64  \n",
      " 9   Season  271116 non-null  object \n",
      " 10  City    271116 non-null  object \n",
      " 11  Sport   271116 non-null  object \n",
      " 12  Event   271116 non-null  object \n",
      " 13  Medal   39783 non-null   object \n",
      "dtypes: float64(3), int64(1), object(10)\n",
      "memory usage: 39.1+ MB\n"
     ]
    }
   ],
   "source": [
    "olympics.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "8acd0837",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([     1,      2,      3,      4,      5,      5,      5,      5,\n",
       "                 5,      5,\n",
       "            ...\n",
       "            135565, 135566, 135567, 135567, 135568, 135569, 135570, 135570,\n",
       "            135571, 135571],\n",
       "           dtype='int64', name='ID', length=271116)"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "cf64d72a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.numeric.Int64Index"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(olympics.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "5e86c292",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Name', 'Sex', 'Age', 'Height', 'Weight', 'Team', 'NOC', 'Games',\n",
       "       'Year', 'Season', 'City', 'Sport', 'Event', 'Medal'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "107d6a04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.base.Index"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(olympics.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "42c3fe95",
   "metadata": {},
   "outputs": [],
   "source": [
    "olympics = pd.read_csv(r'athlete_events.csv',index_col='Name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "f55039b7",
   "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>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A Dijiang</th>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Lamusi</th>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gunnar Nielsen Aaby</th>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edgar Lindenau Aabye</th>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          ID Sex   Age  Height  Weight            Team  NOC  \\\n",
       "Name                                                                          \n",
       "A Dijiang                  1   M  24.0   180.0    80.0           China  CHN   \n",
       "A Lamusi                   2   M  23.0   170.0    60.0           China  CHN   \n",
       "Gunnar Nielsen Aaby        3   M  24.0     NaN     NaN         Denmark  DEN   \n",
       "Edgar Lindenau Aabye       4   M  34.0     NaN     NaN  Denmark/Sweden  DEN   \n",
       "Christine Jacoba Aaftink   5   F  21.0   185.0    82.0     Netherlands  NED   \n",
       "\n",
       "                                Games  Year  Season       City          Sport  \\\n",
       "Name                                                                            \n",
       "A Dijiang                 1992 Summer  1992  Summer  Barcelona     Basketball   \n",
       "A Lamusi                  2012 Summer  2012  Summer     London           Judo   \n",
       "Gunnar Nielsen Aaby       1920 Summer  1920  Summer  Antwerpen       Football   \n",
       "Edgar Lindenau Aabye      1900 Summer  1900  Summer      Paris     Tug-Of-War   \n",
       "Christine Jacoba Aaftink  1988 Winter  1988  Winter    Calgary  Speed Skating   \n",
       "\n",
       "                                                     Event Medal  \n",
       "Name                                                              \n",
       "A Dijiang                      Basketball Men's Basketball   NaN  \n",
       "A Lamusi                      Judo Men's Extra-Lightweight   NaN  \n",
       "Gunnar Nielsen Aaby                Football Men's Football   NaN  \n",
       "Edgar Lindenau Aabye           Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "Christine Jacoba Aaftink  Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "b1da27f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['A Dijiang', 'A Lamusi', 'Gunnar Nielsen Aaby', 'Edgar Lindenau Aabye',\n",
       "       'Christine Jacoba Aaftink', 'Christine Jacoba Aaftink',\n",
       "       'Christine Jacoba Aaftink', 'Christine Jacoba Aaftink',\n",
       "       'Christine Jacoba Aaftink', 'Christine Jacoba Aaftink',\n",
       "       ...\n",
       "       'Fernando scar Zylberberg', 'James Francis \"Jim\" Zylker',\n",
       "       'Aleksandr Viktorovich Zyuzin', 'Aleksandr Viktorovich Zyuzin',\n",
       "       'Olga Igorevna Zyuzkova', 'Andrzej ya', 'Piotr ya', 'Piotr ya',\n",
       "       'Tomasz Ireneusz ya', 'Tomasz Ireneusz ya'],\n",
       "      dtype='object', name='Name', length=271116)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "4a30e356",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.base.Index"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(olympics.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "43fb7373",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'A Dijiang'"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "ed9ff455",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to know column values are unique, use is_unique attribute\n",
    "olympics.index.is_unique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "716705d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#get_loc method, get label and retrun location\n",
    "olympics.index.get_loc('A Dijiang')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "5d393841",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['A Dijiang', 'A Lamusi', 'Gunnar Nielsen Aaby', 'Edgar Lindenau Aabye',\n",
       "       'Christine Jacoba Aaftink', 'Christine Jacoba Aaftink',\n",
       "       'Christine Jacoba Aaftink', 'Christine Jacoba Aaftink',\n",
       "       'Christine Jacoba Aaftink', 'Christine Jacoba Aaftink',\n",
       "       ...\n",
       "       'Fernando scar Zylberberg', 'James Francis \"Jim\" Zylker',\n",
       "       'Aleksandr Viktorovich Zyuzin', 'Aleksandr Viktorovich Zyuzin',\n",
       "       'Olga Igorevna Zyuzkova', 'Andrzej ya', 'Piotr ya', 'Piotr ya',\n",
       "       'Tomasz Ireneusz ya', 'Tomasz Ireneusz ya'],\n",
       "      dtype='object', name='Name', length=271116)"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "d1d455ed",
   "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>Name</th>\n",
       "      <th>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271111</th>\n",
       "      <td>Andrzej ya</td>\n",
       "      <td>135569</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Poland-1</td>\n",
       "      <td>POL</td>\n",
       "      <td>1976 Winter</td>\n",
       "      <td>1976</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Innsbruck</td>\n",
       "      <td>Luge</td>\n",
       "      <td>Luge Mixed (Men)'s Doubles</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271112</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>135570</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Individual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271113</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>135570</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Team</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271114</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>135571</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271115</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>135571</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2002 Winter</td>\n",
       "      <td>2002</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>271116 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Name      ID Sex   Age  Height  Weight  \\\n",
       "0                      A Dijiang       1   M  24.0   180.0    80.0   \n",
       "1                       A Lamusi       2   M  23.0   170.0    60.0   \n",
       "2            Gunnar Nielsen Aaby       3   M  24.0     NaN     NaN   \n",
       "3           Edgar Lindenau Aabye       4   M  34.0     NaN     NaN   \n",
       "4       Christine Jacoba Aaftink       5   F  21.0   185.0    82.0   \n",
       "...                          ...     ...  ..   ...     ...     ...   \n",
       "271111                Andrzej ya  135569   M  29.0   179.0    89.0   \n",
       "271112                  Piotr ya  135570   M  27.0   176.0    59.0   \n",
       "271113                  Piotr ya  135570   M  27.0   176.0    59.0   \n",
       "271114        Tomasz Ireneusz ya  135571   M  30.0   185.0    96.0   \n",
       "271115        Tomasz Ireneusz ya  135571   M  34.0   185.0    96.0   \n",
       "\n",
       "                  Team  NOC        Games  Year  Season            City  \\\n",
       "0                China  CHN  1992 Summer  1992  Summer       Barcelona   \n",
       "1                China  CHN  2012 Summer  2012  Summer          London   \n",
       "2              Denmark  DEN  1920 Summer  1920  Summer       Antwerpen   \n",
       "3       Denmark/Sweden  DEN  1900 Summer  1900  Summer           Paris   \n",
       "4          Netherlands  NED  1988 Winter  1988  Winter         Calgary   \n",
       "...                ...  ...          ...   ...     ...             ...   \n",
       "271111        Poland-1  POL  1976 Winter  1976  Winter       Innsbruck   \n",
       "271112          Poland  POL  2014 Winter  2014  Winter           Sochi   \n",
       "271113          Poland  POL  2014 Winter  2014  Winter           Sochi   \n",
       "271114          Poland  POL  1998 Winter  1998  Winter          Nagano   \n",
       "271115          Poland  POL  2002 Winter  2002  Winter  Salt Lake City   \n",
       "\n",
       "                Sport                                     Event Medal  \n",
       "0          Basketball               Basketball Men's Basketball   NaN  \n",
       "1                Judo              Judo Men's Extra-Lightweight   NaN  \n",
       "2            Football                   Football Men's Football   NaN  \n",
       "3          Tug-Of-War               Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "4       Speed Skating          Speed Skating Women's 500 metres   NaN  \n",
       "...               ...                                       ...   ...  \n",
       "271111           Luge                Luge Mixed (Men)'s Doubles   NaN  \n",
       "271112    Ski Jumping  Ski Jumping Men's Large Hill, Individual   NaN  \n",
       "271113    Ski Jumping        Ski Jumping Men's Large Hill, Team   NaN  \n",
       "271114      Bobsleigh                      Bobsleigh Men's Four   NaN  \n",
       "271115      Bobsleigh                      Bobsleigh Men's Four   NaN  \n",
       "\n",
       "[271116 rows x 15 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sometime you should reset the index on data frame. use reset_index\n",
    "olympics.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "d5a65170",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A Dijiang</th>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Lamusi</th>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gunnar Nielsen Aaby</th>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edgar Lindenau Aabye</th>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          ID Sex   Age  Height  Weight            Team  NOC  \\\n",
       "Name                                                                          \n",
       "A Dijiang                  1   M  24.0   180.0    80.0           China  CHN   \n",
       "A Lamusi                   2   M  23.0   170.0    60.0           China  CHN   \n",
       "Gunnar Nielsen Aaby        3   M  24.0     NaN     NaN         Denmark  DEN   \n",
       "Edgar Lindenau Aabye       4   M  34.0     NaN     NaN  Denmark/Sweden  DEN   \n",
       "Christine Jacoba Aaftink   5   F  21.0   185.0    82.0     Netherlands  NED   \n",
       "\n",
       "                                Games  Year  Season       City          Sport  \\\n",
       "Name                                                                            \n",
       "A Dijiang                 1992 Summer  1992  Summer  Barcelona     Basketball   \n",
       "A Lamusi                  2012 Summer  2012  Summer     London           Judo   \n",
       "Gunnar Nielsen Aaby       1920 Summer  1920  Summer  Antwerpen       Football   \n",
       "Edgar Lindenau Aabye      1900 Summer  1900  Summer      Paris     Tug-Of-War   \n",
       "Christine Jacoba Aaftink  1988 Winter  1988  Winter    Calgary  Speed Skating   \n",
       "\n",
       "                                                     Event Medal  \n",
       "Name                                                              \n",
       "A Dijiang                      Basketball Men's Basketball   NaN  \n",
       "A Lamusi                      Judo Men's Extra-Lightweight   NaN  \n",
       "Gunnar Nielsen Aaby                Football Men's Football   NaN  \n",
       "Edgar Lindenau Aabye           Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "Christine Jacoba Aaftink  Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "56947374",
   "metadata": {},
   "outputs": [],
   "source": [
    "#be sure use inplace parameter\n",
    "olympics.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "48a1f583",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Sex</th>\n",
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       "      <th>Height</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Name  ID Sex   Age  Height  Weight            Team  \\\n",
       "0                 A Dijiang   1   M  24.0   180.0    80.0           China   \n",
       "1                  A Lamusi   2   M  23.0   170.0    60.0           China   \n",
       "2       Gunnar Nielsen Aaby   3   M  24.0     NaN     NaN         Denmark   \n",
       "3      Edgar Lindenau Aabye   4   M  34.0     NaN     NaN  Denmark/Sweden   \n",
       "4  Christine Jacoba Aaftink   5   F  21.0   185.0    82.0     Netherlands   \n",
       "\n",
       "   NOC        Games  Year  Season       City          Sport  \\\n",
       "0  CHN  1992 Summer  1992  Summer  Barcelona     Basketball   \n",
       "1  CHN  2012 Summer  2012  Summer     London           Judo   \n",
       "2  DEN  1920 Summer  1920  Summer  Antwerpen       Football   \n",
       "3  DEN  1900 Summer  1900  Summer      Paris     Tug-Of-War   \n",
       "4  NED  1988 Winter  1988  Winter    Calgary  Speed Skating   \n",
       "\n",
       "                              Event Medal  \n",
       "0       Basketball Men's Basketball   NaN  \n",
       "1      Judo Men's Extra-Lightweight   NaN  \n",
       "2           Football Men's Football   NaN  \n",
       "3       Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "4  Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "71b4a312",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>135569</th>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Poland-1</td>\n",
       "      <td>POL</td>\n",
       "      <td>1976 Winter</td>\n",
       "      <td>1976</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Innsbruck</td>\n",
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       "      <td>Luge Mixed (Men)'s Doubles</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Individual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135570</th>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Team</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135571</th>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2002 Winter</td>\n",
       "      <td>2002</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>271116 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sex   Age  Height  Weight            Team  NOC        Games  Year  \\\n",
       "ID                                                                         \n",
       "1        M  24.0   180.0    80.0           China  CHN  1992 Summer  1992   \n",
       "2        M  23.0   170.0    60.0           China  CHN  2012 Summer  2012   \n",
       "3        M  24.0     NaN     NaN         Denmark  DEN  1920 Summer  1920   \n",
       "4        M  34.0     NaN     NaN  Denmark/Sweden  DEN  1900 Summer  1900   \n",
       "5        F  21.0   185.0    82.0     Netherlands  NED  1988 Winter  1988   \n",
       "...     ..   ...     ...     ...             ...  ...          ...   ...   \n",
       "135569   M  29.0   179.0    89.0        Poland-1  POL  1976 Winter  1976   \n",
       "135570   M  27.0   176.0    59.0          Poland  POL  2014 Winter  2014   \n",
       "135570   M  27.0   176.0    59.0          Poland  POL  2014 Winter  2014   \n",
       "135571   M  30.0   185.0    96.0          Poland  POL  1998 Winter  1998   \n",
       "135571   M  34.0   185.0    96.0          Poland  POL  2002 Winter  2002   \n",
       "\n",
       "        Season            City          Sport  \\\n",
       "ID                                              \n",
       "1       Summer       Barcelona     Basketball   \n",
       "2       Summer          London           Judo   \n",
       "3       Summer       Antwerpen       Football   \n",
       "4       Summer           Paris     Tug-Of-War   \n",
       "5       Winter         Calgary  Speed Skating   \n",
       "...        ...             ...            ...   \n",
       "135569  Winter       Innsbruck           Luge   \n",
       "135570  Winter           Sochi    Ski Jumping   \n",
       "135570  Winter           Sochi    Ski Jumping   \n",
       "135571  Winter          Nagano      Bobsleigh   \n",
       "135571  Winter  Salt Lake City      Bobsleigh   \n",
       "\n",
       "                                           Event Medal  \n",
       "ID                                                      \n",
       "1                    Basketball Men's Basketball   NaN  \n",
       "2                   Judo Men's Extra-Lightweight   NaN  \n",
       "3                        Football Men's Football   NaN  \n",
       "4                    Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "5               Speed Skating Women's 500 metres   NaN  \n",
       "...                                          ...   ...  \n",
       "135569                Luge Mixed (Men)'s Doubles   NaN  \n",
       "135570  Ski Jumping Men's Large Hill, Individual   NaN  \n",
       "135570        Ski Jumping Men's Large Hill, Team   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  \n",
       "135571                      Bobsleigh Men's Four   NaN  \n",
       "\n",
       "[271116 rows x 13 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to set index, use set_index\n",
    "olympics.set_index('ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "fa87c04a",
   "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>Name</th>\n",
       "      <th>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Name  ID Sex   Age  Height  Weight            Team  \\\n",
       "0                 A Dijiang   1   M  24.0   180.0    80.0           China   \n",
       "1                  A Lamusi   2   M  23.0   170.0    60.0           China   \n",
       "2       Gunnar Nielsen Aaby   3   M  24.0     NaN     NaN         Denmark   \n",
       "3      Edgar Lindenau Aabye   4   M  34.0     NaN     NaN  Denmark/Sweden   \n",
       "4  Christine Jacoba Aaftink   5   F  21.0   185.0    82.0     Netherlands   \n",
       "\n",
       "   NOC        Games  Year  Season       City          Sport  \\\n",
       "0  CHN  1992 Summer  1992  Summer  Barcelona     Basketball   \n",
       "1  CHN  2012 Summer  2012  Summer     London           Judo   \n",
       "2  DEN  1920 Summer  1920  Summer  Antwerpen       Football   \n",
       "3  DEN  1900 Summer  1900  Summer      Paris     Tug-Of-War   \n",
       "4  NED  1988 Winter  1988  Winter    Calgary  Speed Skating   \n",
       "\n",
       "                              Event Medal  \n",
       "0       Basketball Men's Basketball   NaN  \n",
       "1      Judo Men's Extra-Lightweight   NaN  \n",
       "2           Football Men's Football   NaN  \n",
       "3       Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "4  Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you set index column, the index_column remove from list of column, so use\n",
    "#drop parameter to don't do that\n",
    "#olympics.reset_index(inplace=True)\n",
    "olympics.set_index('ID',drop=False)\n",
    "olympics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "f8747c44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=271116, step=1)"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "47c5cc97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.index.is_unique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "5bd5a5cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#if you want to create uniqu index, use this technique\n",
    "new_index = ['Athlete_{}'.format(i) for i in range(1,olympics.index.size+1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "4c7eb885",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Athlete_1',\n",
       " 'Athlete_2',\n",
       " 'Athlete_3',\n",
       " 'Athlete_4',\n",
       " 'Athlete_5',\n",
       " 'Athlete_6',\n",
       " 'Athlete_7',\n",
       " 'Athlete_8',\n",
       " 'Athlete_9',\n",
       " 'Athlete_10',\n",
       " 'Athlete_11',\n",
       " 'Athlete_12',\n",
       " 'Athlete_13',\n",
       " 'Athlete_14',\n",
       " 'Athlete_15',\n",
       " 'Athlete_16',\n",
       " 'Athlete_17',\n",
       " 'Athlete_18',\n",
       " 'Athlete_19',\n",
       " 'Athlete_20',\n",
       " 'Athlete_21',\n",
       " 'Athlete_22',\n",
       " 'Athlete_23',\n",
       " 'Athlete_24',\n",
       " 'Athlete_25',\n",
       " 'Athlete_26',\n",
       " 'Athlete_27',\n",
       " 'Athlete_28',\n",
       " 'Athlete_29',\n",
       " 'Athlete_30',\n",
       " 'Athlete_31',\n",
       " 'Athlete_32',\n",
       " 'Athlete_33',\n",
       " 'Athlete_34',\n",
       " 'Athlete_35',\n",
       " 'Athlete_36',\n",
       " 'Athlete_37',\n",
       " 'Athlete_38',\n",
       " 'Athlete_39',\n",
       " 'Athlete_40',\n",
       " 'Athlete_41',\n",
       " 'Athlete_42',\n",
       " 'Athlete_43',\n",
       " 'Athlete_44',\n",
       " 'Athlete_45',\n",
       " 'Athlete_46',\n",
       " 'Athlete_47',\n",
       " 'Athlete_48',\n",
       " 'Athlete_49',\n",
       " 'Athlete_50',\n",
       " 'Athlete_51',\n",
       " 'Athlete_52',\n",
       " 'Athlete_53',\n",
       " 'Athlete_54',\n",
       " 'Athlete_55',\n",
       " 'Athlete_56',\n",
       " 'Athlete_57',\n",
       " 'Athlete_58',\n",
       " 'Athlete_59',\n",
       " 'Athlete_60',\n",
       " 'Athlete_61',\n",
       " 'Athlete_62',\n",
       " 'Athlete_63',\n",
       " 'Athlete_64',\n",
       " 'Athlete_65',\n",
       " 'Athlete_66',\n",
       " 'Athlete_67',\n",
       " 'Athlete_68',\n",
       " 'Athlete_69',\n",
       " 'Athlete_70',\n",
       " 'Athlete_71',\n",
       " 'Athlete_72',\n",
       " 'Athlete_73',\n",
       " 'Athlete_74',\n",
       " 'Athlete_75',\n",
       " 'Athlete_76',\n",
       " 'Athlete_77',\n",
       " 'Athlete_78',\n",
       " 'Athlete_79',\n",
       " 'Athlete_80',\n",
       " 'Athlete_81',\n",
       " 'Athlete_82',\n",
       " 'Athlete_83',\n",
       " 'Athlete_84',\n",
       " 'Athlete_85',\n",
       " 'Athlete_86',\n",
       " 'Athlete_87',\n",
       " 'Athlete_88',\n",
       " 'Athlete_89',\n",
       " 'Athlete_90',\n",
       " 'Athlete_91',\n",
       " 'Athlete_92',\n",
       " 'Athlete_93',\n",
       " 'Athlete_94',\n",
       " 'Athlete_95',\n",
       " 'Athlete_96',\n",
       " 'Athlete_97',\n",
       " 'Athlete_98',\n",
       " 'Athlete_99',\n",
       " 'Athlete_100',\n",
       " 'Athlete_101',\n",
       " 'Athlete_102',\n",
       " 'Athlete_103',\n",
       " 'Athlete_104',\n",
       " 'Athlete_105',\n",
       " 'Athlete_106',\n",
       " 'Athlete_107',\n",
       " 'Athlete_108',\n",
       " 'Athlete_109',\n",
       " 'Athlete_110',\n",
       " 'Athlete_111',\n",
       " 'Athlete_112',\n",
       " 'Athlete_113',\n",
       " 'Athlete_114',\n",
       " 'Athlete_115',\n",
       " 'Athlete_116',\n",
       " 'Athlete_117',\n",
       " 'Athlete_118',\n",
       " 'Athlete_119',\n",
       " 'Athlete_120',\n",
       " 'Athlete_121',\n",
       " 'Athlete_122',\n",
       " 'Athlete_123',\n",
       " 'Athlete_124',\n",
       " 'Athlete_125',\n",
       " 'Athlete_126',\n",
       " 'Athlete_127',\n",
       " 'Athlete_128',\n",
       " 'Athlete_129',\n",
       " 'Athlete_130',\n",
       " 'Athlete_131',\n",
       " 'Athlete_132',\n",
       " 'Athlete_133',\n",
       " 'Athlete_134',\n",
       " 'Athlete_135',\n",
       " 'Athlete_136',\n",
       " 'Athlete_137',\n",
       " 'Athlete_138',\n",
       " 'Athlete_139',\n",
       " 'Athlete_140',\n",
       " 'Athlete_141',\n",
       " 'Athlete_142',\n",
       " 'Athlete_143',\n",
       " 'Athlete_144',\n",
       " 'Athlete_145',\n",
       " 'Athlete_146',\n",
       " 'Athlete_147',\n",
       " 'Athlete_148',\n",
       " 'Athlete_149',\n",
       " 'Athlete_150',\n",
       " 'Athlete_151',\n",
       " 'Athlete_152',\n",
       " 'Athlete_153',\n",
       " 'Athlete_154',\n",
       " 'Athlete_155',\n",
       " 'Athlete_156',\n",
       " 'Athlete_157',\n",
       " 'Athlete_158',\n",
       " 'Athlete_159',\n",
       " 'Athlete_160',\n",
       " 'Athlete_161',\n",
       " 'Athlete_162',\n",
       " 'Athlete_163',\n",
       " 'Athlete_164',\n",
       " 'Athlete_165',\n",
       " 'Athlete_166',\n",
       " 'Athlete_167',\n",
       " 'Athlete_168',\n",
       " 'Athlete_169',\n",
       " 'Athlete_170',\n",
       " 'Athlete_171',\n",
       " 'Athlete_172',\n",
       " 'Athlete_173',\n",
       " 'Athlete_174',\n",
       " 'Athlete_175',\n",
       " 'Athlete_176',\n",
       " 'Athlete_177',\n",
       " 'Athlete_178',\n",
       " 'Athlete_179',\n",
       " 'Athlete_180',\n",
       " 'Athlete_181',\n",
       " 'Athlete_182',\n",
       " 'Athlete_183',\n",
       " 'Athlete_184',\n",
       " 'Athlete_185',\n",
       " 'Athlete_186',\n",
       " 'Athlete_187',\n",
       " 'Athlete_188',\n",
       " 'Athlete_189',\n",
       " 'Athlete_190',\n",
       " 'Athlete_191',\n",
       " 'Athlete_192',\n",
       " 'Athlete_193',\n",
       " 'Athlete_194',\n",
       " 'Athlete_195',\n",
       " 'Athlete_196',\n",
       " 'Athlete_197',\n",
       " 'Athlete_198',\n",
       " 'Athlete_199',\n",
       " 'Athlete_200',\n",
       " 'Athlete_201',\n",
       " 'Athlete_202',\n",
       " 'Athlete_203',\n",
       " 'Athlete_204',\n",
       " 'Athlete_205',\n",
       " 'Athlete_206',\n",
       " 'Athlete_207',\n",
       " 'Athlete_208',\n",
       " 'Athlete_209',\n",
       " 'Athlete_210',\n",
       " 'Athlete_211',\n",
       " 'Athlete_212',\n",
       " 'Athlete_213',\n",
       " 'Athlete_214',\n",
       " 'Athlete_215',\n",
       " 'Athlete_216',\n",
       " 'Athlete_217',\n",
       " 'Athlete_218',\n",
       " 'Athlete_219',\n",
       " 'Athlete_220',\n",
       " 'Athlete_221',\n",
       " 'Athlete_222',\n",
       " 'Athlete_223',\n",
       " 'Athlete_224',\n",
       " 'Athlete_225',\n",
       " 'Athlete_226',\n",
       " 'Athlete_227',\n",
       " 'Athlete_228',\n",
       " 'Athlete_229',\n",
       " 'Athlete_230',\n",
       " 'Athlete_231',\n",
       " 'Athlete_232',\n",
       " 'Athlete_233',\n",
       " 'Athlete_234',\n",
       " 'Athlete_235',\n",
       " 'Athlete_236',\n",
       " 'Athlete_237',\n",
       " 'Athlete_238',\n",
       " 'Athlete_239',\n",
       " 'Athlete_240',\n",
       " 'Athlete_241',\n",
       " 'Athlete_242',\n",
       " 'Athlete_243',\n",
       " 'Athlete_244',\n",
       " 'Athlete_245',\n",
       " 'Athlete_246',\n",
       " 'Athlete_247',\n",
       " 'Athlete_248',\n",
       " 'Athlete_249',\n",
       " 'Athlete_250',\n",
       " 'Athlete_251',\n",
       " 'Athlete_252',\n",
       " 'Athlete_253',\n",
       " 'Athlete_254',\n",
       " 'Athlete_255',\n",
       " 'Athlete_256',\n",
       " 'Athlete_257',\n",
       " 'Athlete_258',\n",
       " 'Athlete_259',\n",
       " 'Athlete_260',\n",
       " 'Athlete_261',\n",
       " 'Athlete_262',\n",
       " 'Athlete_263',\n",
       " 'Athlete_264',\n",
       " 'Athlete_265',\n",
       " 'Athlete_266',\n",
       " 'Athlete_267',\n",
       " 'Athlete_268',\n",
       " 'Athlete_269',\n",
       " 'Athlete_270',\n",
       " 'Athlete_271',\n",
       " 'Athlete_272',\n",
       " 'Athlete_273',\n",
       " 'Athlete_274',\n",
       " 'Athlete_275',\n",
       " 'Athlete_276',\n",
       " 'Athlete_277',\n",
       " 'Athlete_278',\n",
       " 'Athlete_279',\n",
       " 'Athlete_280',\n",
       " 'Athlete_281',\n",
       " 'Athlete_282',\n",
       " 'Athlete_283',\n",
       " 'Athlete_284',\n",
       " 'Athlete_285',\n",
       " 'Athlete_286',\n",
       " 'Athlete_287',\n",
       " 'Athlete_288',\n",
       " 'Athlete_289',\n",
       " 'Athlete_290',\n",
       " 'Athlete_291',\n",
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       " 'Athlete_963',\n",
       " 'Athlete_964',\n",
       " 'Athlete_965',\n",
       " 'Athlete_966',\n",
       " 'Athlete_967',\n",
       " 'Athlete_968',\n",
       " 'Athlete_969',\n",
       " 'Athlete_970',\n",
       " 'Athlete_971',\n",
       " 'Athlete_972',\n",
       " 'Athlete_973',\n",
       " 'Athlete_974',\n",
       " 'Athlete_975',\n",
       " 'Athlete_976',\n",
       " 'Athlete_977',\n",
       " 'Athlete_978',\n",
       " 'Athlete_979',\n",
       " 'Athlete_980',\n",
       " 'Athlete_981',\n",
       " 'Athlete_982',\n",
       " 'Athlete_983',\n",
       " 'Athlete_984',\n",
       " 'Athlete_985',\n",
       " 'Athlete_986',\n",
       " 'Athlete_987',\n",
       " 'Athlete_988',\n",
       " 'Athlete_989',\n",
       " 'Athlete_990',\n",
       " 'Athlete_991',\n",
       " 'Athlete_992',\n",
       " 'Athlete_993',\n",
       " 'Athlete_994',\n",
       " 'Athlete_995',\n",
       " 'Athlete_996',\n",
       " 'Athlete_997',\n",
       " 'Athlete_998',\n",
       " 'Athlete_999',\n",
       " 'Athlete_1000',\n",
       " ...]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "6c505d78",
   "metadata": {},
   "outputs": [],
   "source": [
    "olympics.index = new_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "e420d715",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
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       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Athlete_1</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_2</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_4</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Name  ID Sex   Age  Height  Weight  \\\n",
       "Athlete_1                 A Dijiang   1   M  24.0   180.0    80.0   \n",
       "Athlete_2                  A Lamusi   2   M  23.0   170.0    60.0   \n",
       "Athlete_3       Gunnar Nielsen Aaby   3   M  24.0     NaN     NaN   \n",
       "Athlete_4      Edgar Lindenau Aabye   4   M  34.0     NaN     NaN   \n",
       "Athlete_5  Christine Jacoba Aaftink   5   F  21.0   185.0    82.0   \n",
       "\n",
       "                     Team  NOC        Games  Year  Season       City  \\\n",
       "Athlete_1           China  CHN  1992 Summer  1992  Summer  Barcelona   \n",
       "Athlete_2           China  CHN  2012 Summer  2012  Summer     London   \n",
       "Athlete_3         Denmark  DEN  1920 Summer  1920  Summer  Antwerpen   \n",
       "Athlete_4  Denmark/Sweden  DEN  1900 Summer  1900  Summer      Paris   \n",
       "Athlete_5     Netherlands  NED  1988 Winter  1988  Winter    Calgary   \n",
       "\n",
       "                   Sport                             Event Medal  \n",
       "Athlete_1     Basketball       Basketball Men's Basketball   NaN  \n",
       "Athlete_2           Judo      Judo Men's Extra-Lightweight   NaN  \n",
       "Athlete_3       Football           Football Men's Football   NaN  \n",
       "Athlete_4     Tug-Of-War       Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "Athlete_5  Speed Skating  Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "08152de6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Name</th>\n",
       "      <th>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
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       "      <th>City</th>\n",
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       "      <th>Medal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Athlete_271112</th>\n",
       "      <td>Andrzej ya</td>\n",
       "      <td>135569</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Poland-1</td>\n",
       "      <td>POL</td>\n",
       "      <td>1976 Winter</td>\n",
       "      <td>1976</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Innsbruck</td>\n",
       "      <td>Luge</td>\n",
       "      <td>Luge Mixed (Men)'s Doubles</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_271113</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>135570</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Individual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_271114</th>\n",
       "      <td>Piotr ya</td>\n",
       "      <td>135570</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2014 Winter</td>\n",
       "      <td>2014</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Sochi</td>\n",
       "      <td>Ski Jumping</td>\n",
       "      <td>Ski Jumping Men's Large Hill, Team</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_271115</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>135571</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_271116</th>\n",
       "      <td>Tomasz Ireneusz ya</td>\n",
       "      <td>135571</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2002 Winter</td>\n",
       "      <td>2002</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Name      ID Sex   Age  Height  Weight  \\\n",
       "Athlete_271112          Andrzej ya  135569   M  29.0   179.0    89.0   \n",
       "Athlete_271113            Piotr ya  135570   M  27.0   176.0    59.0   \n",
       "Athlete_271114            Piotr ya  135570   M  27.0   176.0    59.0   \n",
       "Athlete_271115  Tomasz Ireneusz ya  135571   M  30.0   185.0    96.0   \n",
       "Athlete_271116  Tomasz Ireneusz ya  135571   M  34.0   185.0    96.0   \n",
       "\n",
       "                    Team  NOC        Games  Year  Season            City  \\\n",
       "Athlete_271112  Poland-1  POL  1976 Winter  1976  Winter       Innsbruck   \n",
       "Athlete_271113    Poland  POL  2014 Winter  2014  Winter           Sochi   \n",
       "Athlete_271114    Poland  POL  2014 Winter  2014  Winter           Sochi   \n",
       "Athlete_271115    Poland  POL  1998 Winter  1998  Winter          Nagano   \n",
       "Athlete_271116    Poland  POL  2002 Winter  2002  Winter  Salt Lake City   \n",
       "\n",
       "                      Sport                                     Event Medal  \n",
       "Athlete_271112         Luge                Luge Mixed (Men)'s Doubles   NaN  \n",
       "Athlete_271113  Ski Jumping  Ski Jumping Men's Large Hill, Individual   NaN  \n",
       "Athlete_271114  Ski Jumping        Ski Jumping Men's Large Hill, Team   NaN  \n",
       "Athlete_271115    Bobsleigh                      Bobsleigh Men's Four   NaN  \n",
       "Athlete_271116    Bobsleigh                      Bobsleigh Men's Four   NaN  "
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "1d174d0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to change the name of columns\n",
    "olympics.rename(columns={'Sex':'Gender'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "b6b5810d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
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       "      <th>NOC</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Athlete_1</th>\n",
       "      <td>A Dijiang</td>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_2</th>\n",
       "      <td>A Lamusi</td>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_3</th>\n",
       "      <td>Gunnar Nielsen Aaby</td>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_4</th>\n",
       "      <td>Edgar Lindenau Aabye</td>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athlete_5</th>\n",
       "      <td>Christine Jacoba Aaftink</td>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Name  ID Gender   Age  Height  Weight  \\\n",
       "Athlete_1                 A Dijiang   1      M  24.0   180.0    80.0   \n",
       "Athlete_2                  A Lamusi   2      M  23.0   170.0    60.0   \n",
       "Athlete_3       Gunnar Nielsen Aaby   3      M  24.0     NaN     NaN   \n",
       "Athlete_4      Edgar Lindenau Aabye   4      M  34.0     NaN     NaN   \n",
       "Athlete_5  Christine Jacoba Aaftink   5      F  21.0   185.0    82.0   \n",
       "\n",
       "                     Team  NOC        Games  Year  Season       City  \\\n",
       "Athlete_1           China  CHN  1992 Summer  1992  Summer  Barcelona   \n",
       "Athlete_2           China  CHN  2012 Summer  2012  Summer     London   \n",
       "Athlete_3         Denmark  DEN  1920 Summer  1920  Summer  Antwerpen   \n",
       "Athlete_4  Denmark/Sweden  DEN  1900 Summer  1900  Summer      Paris   \n",
       "Athlete_5     Netherlands  NED  1988 Winter  1988  Winter    Calgary   \n",
       "\n",
       "                   Sport                             Event Medal  \n",
       "Athlete_1     Basketball       Basketball Men's Basketball   NaN  \n",
       "Athlete_2           Judo      Judo Men's Extra-Lightweight   NaN  \n",
       "Athlete_3       Football           Football Men's Football   NaN  \n",
       "Athlete_4     Tug-Of-War       Tug-Of-War Men's Tug-Of-War  Gold  \n",
       "Athlete_5  Speed Skating  Speed Skating Women's 500 metres   NaN  "
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "333faa61",
   "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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Owen Harris Braund</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. William Henry Allen</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. James Moran</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.4583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Timothy J McCarthy</td>\n",
       "      <td>male</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>51.8625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Master. Gosta Leonard Palsson</td>\n",
       "      <td>male</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>21.0750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Mr. Frederick James Banfield</td>\n",
       "      <td>male</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Henry Jr Sutehall</td>\n",
       "      <td>male</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Rev. Juozas Montvila</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Karl Howell Behr</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Patrick Dooley</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>573 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass                           Name   Sex   Age  \\\n",
       "0           0       3         Mr. Owen Harris Braund  male  22.0   \n",
       "4           0       3        Mr. William Henry Allen  male  35.0   \n",
       "5           0       3                Mr. James Moran  male  27.0   \n",
       "6           0       1         Mr. Timothy J McCarthy  male  54.0   \n",
       "7           0       3  Master. Gosta Leonard Palsson  male   2.0   \n",
       "..        ...     ...                            ...   ...   ...   \n",
       "879         0       2   Mr. Frederick James Banfield  male  28.0   \n",
       "880         0       3          Mr. Henry Jr Sutehall  male  25.0   \n",
       "882         0       2           Rev. Juozas Montvila  male  27.0   \n",
       "885         1       1           Mr. Karl Howell Behr  male  26.0   \n",
       "886         0       3             Mr. Patrick Dooley  male  32.0   \n",
       "\n",
       "     Siblings/Spouses Aboard  Parents/Children Aboard     Fare  \n",
       "0                          1                        0   7.2500  \n",
       "4                          0                        0   8.0500  \n",
       "5                          0                        0   8.4583  \n",
       "6                          0                        0  51.8625  \n",
       "7                          3                        1  21.0750  \n",
       "..                       ...                      ...      ...  \n",
       "879                        0                        0  10.5000  \n",
       "880                        0                        0   7.0500  \n",
       "882                        0                        0  13.0000  \n",
       "885                        0                        0  30.0000  \n",
       "886                        0                        0   7.7500  \n",
       "\n",
       "[573 rows x 8 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[titanic.Sex == 'male']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "60347c5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       7.2500\n",
       "4       8.0500\n",
       "5       8.4583\n",
       "6      51.8625\n",
       "7      21.0750\n",
       "        ...   \n",
       "879    10.5000\n",
       "880     7.0500\n",
       "882    13.0000\n",
       "885    30.0000\n",
       "886     7.7500\n",
       "Name: Fare, Length: 573, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Fare[titanic.Sex == 'male']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fdbf11b9",
   "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>Age</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22.0</td>\n",
       "      <td>7.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>35.0</td>\n",
       "      <td>8.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>27.0</td>\n",
       "      <td>8.4583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>54.0</td>\n",
       "      <td>51.8625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2.0</td>\n",
       "      <td>21.0750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879</th>\n",
       "      <td>28.0</td>\n",
       "      <td>10.5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>25.0</td>\n",
       "      <td>7.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>27.0</td>\n",
       "      <td>13.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>26.0</td>\n",
       "      <td>30.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>32.0</td>\n",
       "      <td>7.7500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>573 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Age     Fare\n",
       "0    22.0   7.2500\n",
       "4    35.0   8.0500\n",
       "5    27.0   8.4583\n",
       "6    54.0  51.8625\n",
       "7     2.0  21.0750\n",
       "..    ...      ...\n",
       "879  28.0  10.5000\n",
       "880  25.0   7.0500\n",
       "882  27.0  13.0000\n",
       "885  26.0  30.0000\n",
       "886  32.0   7.7500\n",
       "\n",
       "[573 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#we recomend this method, because this format can use for more than one columns\n",
    "titanic.loc[titanic.Sex == 'male',['Age','Fare']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b3b51f58",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>23.4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>887 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass   Age  Siblings/Spouses Aboard  Parents/Children Aboard  \\\n",
       "0           0       3  22.0                        1                        0   \n",
       "1           1       1  38.0                        1                        0   \n",
       "2           1       3  26.0                        0                        0   \n",
       "3           1       1  35.0                        1                        0   \n",
       "4           0       3  35.0                        0                        0   \n",
       "..        ...     ...   ...                      ...                      ...   \n",
       "882         0       2  27.0                        0                        0   \n",
       "883         1       1  19.0                        0                        0   \n",
       "884         0       3   7.0                        1                        2   \n",
       "885         1       1  26.0                        0                        0   \n",
       "886         0       3  32.0                        0                        0   \n",
       "\n",
       "        Fare  \n",
       "0     7.2500  \n",
       "1    71.2833  \n",
       "2     7.9250  \n",
       "3    53.1000  \n",
       "4     8.0500  \n",
       "..       ...  \n",
       "882  13.0000  \n",
       "883  30.0000  \n",
       "884  23.4500  \n",
       "885  30.0000  \n",
       "886   7.7500  \n",
       "\n",
       "[887 rows x 6 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to show all numeric data. use this techniqu\n",
    "mask = titanic.dtypes != object\n",
    "titanic.loc[:,mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dc0a1c19",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .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>Sex</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mr. Owen Harris Braund</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mrs. John Bradley (Florence Briggs Thayer) Cum...</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Miss. Laina Heikkinen</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mrs. Jacques Heath (Lily May Peel) Futrelle</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mr. William Henry Allen</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>Rev. Juozas Montvila</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>Miss. Margaret Edith Graham</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>Miss. Catherine Helen Johnston</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>Mr. Karl Howell Behr</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>Mr. Patrick Dooley</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>887 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Name     Sex\n",
       "0                               Mr. Owen Harris Braund    male\n",
       "1    Mrs. John Bradley (Florence Briggs Thayer) Cum...  female\n",
       "2                                Miss. Laina Heikkinen  female\n",
       "3          Mrs. Jacques Heath (Lily May Peel) Futrelle  female\n",
       "4                              Mr. William Henry Allen    male\n",
       "..                                                 ...     ...\n",
       "882                               Rev. Juozas Montvila    male\n",
       "883                        Miss. Margaret Edith Graham  female\n",
       "884                     Miss. Catherine Helen Johnston  female\n",
       "885                               Mr. Karl Howell Behr    male\n",
       "886                                 Mr. Patrick Dooley    male\n",
       "\n",
       "[887 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[:,~mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7ab11454",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 271116 entries, A Dijiang to Tomasz Ireneusz ya\n",
      "Data columns (total 14 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   ID      271116 non-null  int64  \n",
      " 1   Sex     271116 non-null  object \n",
      " 2   Age     261642 non-null  float64\n",
      " 3   Height  210945 non-null  float64\n",
      " 4   Weight  208241 non-null  float64\n",
      " 5   Team    271116 non-null  object \n",
      " 6   NOC     271116 non-null  object \n",
      " 7   Games   271116 non-null  object \n",
      " 8   Year    271116 non-null  int64  \n",
      " 9   Season  271116 non-null  object \n",
      " 10  City    271116 non-null  object \n",
      " 11  Sport   271116 non-null  object \n",
      " 12  Event   271116 non-null  object \n",
      " 13  Medal   39783 non-null   object \n",
      "dtypes: float64(3), int64(2), object(9)\n",
      "memory usage: 31.0+ MB\n"
     ]
    }
   ],
   "source": [
    "olympics.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2df621dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
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       "      <th>NOC</th>\n",
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       "      <th>Season</th>\n",
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       "      <th>Medal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A Dijiang</th>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
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       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
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       "      <td>NED</td>\n",
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       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
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       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
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       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 1,500 metres</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
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       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 5,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 1,500 metres</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 5,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tomasz Ireneusz ya</th>\n",
       "      <td>135571</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36958 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              ID Sex   Age  Height  Weight         Team  NOC  \\\n",
       "Name                                                                           \n",
       "A Dijiang                      1   M  24.0   180.0    80.0        China  CHN   \n",
       "Christine Jacoba Aaftink       5   F  25.0   185.0    82.0  Netherlands  NED   \n",
       "Christine Jacoba Aaftink       5   F  25.0   185.0    82.0  Netherlands  NED   \n",
       "Christine Jacoba Aaftink       5   F  27.0   185.0    82.0  Netherlands  NED   \n",
       "Christine Jacoba Aaftink       5   F  27.0   185.0    82.0  Netherlands  NED   \n",
       "...                          ...  ..   ...     ...     ...          ...  ...   \n",
       "Pawe Jan Zygmunt          135559   M  21.0   182.0    79.0       Poland  POL   \n",
       "Pawe Jan Zygmunt          135559   M  21.0   182.0    79.0       Poland  POL   \n",
       "Pawe Jan Zygmunt          135559   M  25.0   182.0    79.0       Poland  POL   \n",
       "Pawe Jan Zygmunt          135559   M  25.0   182.0    79.0       Poland  POL   \n",
       "Tomasz Ireneusz ya        135571   M  30.0   185.0    96.0       Poland  POL   \n",
       "\n",
       "                                Games  Year  Season         City  \\\n",
       "Name                                                               \n",
       "A Dijiang                 1992 Summer  1992  Summer    Barcelona   \n",
       "Christine Jacoba Aaftink  1992 Winter  1992  Winter  Albertville   \n",
       "Christine Jacoba Aaftink  1992 Winter  1992  Winter  Albertville   \n",
       "Christine Jacoba Aaftink  1994 Winter  1994  Winter  Lillehammer   \n",
       "Christine Jacoba Aaftink  1994 Winter  1994  Winter  Lillehammer   \n",
       "...                               ...   ...     ...          ...   \n",
       "Pawe Jan Zygmunt          1994 Winter  1994  Winter  Lillehammer   \n",
       "Pawe Jan Zygmunt          1994 Winter  1994  Winter  Lillehammer   \n",
       "Pawe Jan Zygmunt          1998 Winter  1998  Winter       Nagano   \n",
       "Pawe Jan Zygmunt          1998 Winter  1998  Winter       Nagano   \n",
       "Tomasz Ireneusz ya        1998 Winter  1998  Winter       Nagano   \n",
       "\n",
       "                                  Sport                               Event  \\\n",
       "Name                                                                          \n",
       "A Dijiang                    Basketball         Basketball Men's Basketball   \n",
       "Christine Jacoba Aaftink  Speed Skating    Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating  Speed Skating Women's 1,000 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating    Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating  Speed Skating Women's 1,000 metres   \n",
       "...                                 ...                                 ...   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 1,500 metres   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 5,000 metres   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 1,500 metres   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 5,000 metres   \n",
       "Tomasz Ireneusz ya            Bobsleigh                Bobsleigh Men's Four   \n",
       "\n",
       "                         Medal  \n",
       "Name                            \n",
       "A Dijiang                  NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "...                        ...  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Tomasz Ireneusz ya         NaN  \n",
       "\n",
       "[36958 rows x 14 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#between is usefull filter\n",
    "olympics[olympics.Year.between(1990,1999)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1b81501c",
   "metadata": {},
   "outputs": [
    {
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       "      <th>A Dijiang</th>\n",
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       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
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       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
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       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 1,500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 5,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 1,500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pawe Jan Zygmunt</th>\n",
       "      <td>135559</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Men's 5,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tomasz Ireneusz ya</th>\n",
       "      <td>135571</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1998 Winter</td>\n",
       "      <td>1998</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Nagano</td>\n",
       "      <td>Bobsleigh</td>\n",
       "      <td>Bobsleigh Men's Four</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36958 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              ID Sex   Age  Height  Weight         Team  NOC  \\\n",
       "Name                                                                           \n",
       "A Dijiang                      1   M  24.0   180.0    80.0        China  CHN   \n",
       "Christine Jacoba Aaftink       5   F  25.0   185.0    82.0  Netherlands  NED   \n",
       "Christine Jacoba Aaftink       5   F  25.0   185.0    82.0  Netherlands  NED   \n",
       "Christine Jacoba Aaftink       5   F  27.0   185.0    82.0  Netherlands  NED   \n",
       "Christine Jacoba Aaftink       5   F  27.0   185.0    82.0  Netherlands  NED   \n",
       "...                          ...  ..   ...     ...     ...          ...  ...   \n",
       "Pawe Jan Zygmunt          135559   M  21.0   182.0    79.0       Poland  POL   \n",
       "Pawe Jan Zygmunt          135559   M  21.0   182.0    79.0       Poland  POL   \n",
       "Pawe Jan Zygmunt          135559   M  25.0   182.0    79.0       Poland  POL   \n",
       "Pawe Jan Zygmunt          135559   M  25.0   182.0    79.0       Poland  POL   \n",
       "Tomasz Ireneusz ya        135571   M  30.0   185.0    96.0       Poland  POL   \n",
       "\n",
       "                                Games  Year  Season         City  \\\n",
       "Name                                                               \n",
       "A Dijiang                 1992 Summer  1992  Summer    Barcelona   \n",
       "Christine Jacoba Aaftink  1992 Winter  1992  Winter  Albertville   \n",
       "Christine Jacoba Aaftink  1992 Winter  1992  Winter  Albertville   \n",
       "Christine Jacoba Aaftink  1994 Winter  1994  Winter  Lillehammer   \n",
       "Christine Jacoba Aaftink  1994 Winter  1994  Winter  Lillehammer   \n",
       "...                               ...   ...     ...          ...   \n",
       "Pawe Jan Zygmunt          1994 Winter  1994  Winter  Lillehammer   \n",
       "Pawe Jan Zygmunt          1994 Winter  1994  Winter  Lillehammer   \n",
       "Pawe Jan Zygmunt          1998 Winter  1998  Winter       Nagano   \n",
       "Pawe Jan Zygmunt          1998 Winter  1998  Winter       Nagano   \n",
       "Tomasz Ireneusz ya        1998 Winter  1998  Winter       Nagano   \n",
       "\n",
       "                                  Sport                               Event  \\\n",
       "Name                                                                          \n",
       "A Dijiang                    Basketball         Basketball Men's Basketball   \n",
       "Christine Jacoba Aaftink  Speed Skating    Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating  Speed Skating Women's 1,000 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating    Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating  Speed Skating Women's 1,000 metres   \n",
       "...                                 ...                                 ...   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 1,500 metres   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 5,000 metres   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 1,500 metres   \n",
       "Pawe Jan Zygmunt          Speed Skating    Speed Skating Men's 5,000 metres   \n",
       "Tomasz Ireneusz ya            Bobsleigh                Bobsleigh Men's Four   \n",
       "\n",
       "                         Medal  \n",
       "Name                            \n",
       "A Dijiang                  NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "...                        ...  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Pawe Jan Zygmunt           NaN  \n",
       "Tomasz Ireneusz ya         NaN  \n",
       "\n",
       "[36958 rows x 14 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics[olympics.Year.between(1990,1999,inclusive=True)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f1260ce7",
   "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>ID</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Team</th>\n",
       "      <th>NOC</th>\n",
       "      <th>Games</th>\n",
       "      <th>Year</th>\n",
       "      <th>Season</th>\n",
       "      <th>City</th>\n",
       "      <th>Sport</th>\n",
       "      <th>Event</th>\n",
       "      <th>Medal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A Dijiang</th>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Lamusi</th>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1992 Winter</td>\n",
       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1992 Winter</td>\n",
       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Per Knut Aaland</th>\n",
       "      <td>6</td>\n",
       "      <td>M</td>\n",
       "      <td>31.0</td>\n",
       "      <td>188.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>United States</td>\n",
       "      <td>USA</td>\n",
       "      <td>1992 Winter</td>\n",
       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Cross Country Skiing</td>\n",
       "      <td>Cross Country Skiing Men's 10 kilometres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sawomir Andrzej Zwierzyski</th>\n",
       "      <td>135537</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Fencing</td>\n",
       "      <td>Fencing Men's epee, Team</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henk Jan Zwolle</th>\n",
       "      <td>135545</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Rowing</td>\n",
       "      <td>Rowing Men's Double Sculls</td>\n",
       "      <td>Bronze</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Viktoriya Viktorovna Zyabkina</th>\n",
       "      <td>135547</td>\n",
       "      <td>F</td>\n",
       "      <td>19.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>Kazakhstan</td>\n",
       "      <td>KAZ</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Athletics</td>\n",
       "      <td>Athletics Women's 200 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dominik ycki</th>\n",
       "      <td>135557</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Sailing</td>\n",
       "      <td>Sailing Men's Two Person Keelboat</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ukasz Tomasz ygado</th>\n",
       "      <td>135558</td>\n",
       "      <td>M</td>\n",
       "      <td>32.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>POL</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Volleyball</td>\n",
       "      <td>Volleyball Men's Volleyball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29333 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   ID Sex   Age  Height  Weight  \\\n",
       "Name                                                              \n",
       "A Dijiang                           1   M  24.0   180.0    80.0   \n",
       "A Lamusi                            2   M  23.0   170.0    60.0   \n",
       "Christine Jacoba Aaftink            5   F  25.0   185.0    82.0   \n",
       "Christine Jacoba Aaftink            5   F  25.0   185.0    82.0   \n",
       "Per Knut Aaland                     6   M  31.0   188.0    75.0   \n",
       "...                               ...  ..   ...     ...     ...   \n",
       "Sawomir Andrzej Zwierzyski     135537   M  25.0   175.0    72.0   \n",
       "Henk Jan Zwolle                135545   M  27.0   197.0    93.0   \n",
       "Viktoriya Viktorovna Zyabkina  135547   F  19.0   174.0    62.0   \n",
       "Dominik ycki                   135557   M  38.0   192.0    95.0   \n",
       "ukasz Tomasz ygado             135558   M  32.0   200.0    89.0   \n",
       "\n",
       "                                        Team  NOC        Games  Year  Season  \\\n",
       "Name                                                                           \n",
       "A Dijiang                              China  CHN  1992 Summer  1992  Summer   \n",
       "A Lamusi                               China  CHN  2012 Summer  2012  Summer   \n",
       "Christine Jacoba Aaftink         Netherlands  NED  1992 Winter  1992  Winter   \n",
       "Christine Jacoba Aaftink         Netherlands  NED  1992 Winter  1992  Winter   \n",
       "Per Knut Aaland                United States  USA  1992 Winter  1992  Winter   \n",
       "...                                      ...  ...          ...   ...     ...   \n",
       "Sawomir Andrzej Zwierzyski            Poland  POL  1992 Summer  1992  Summer   \n",
       "Henk Jan Zwolle                  Netherlands  NED  1992 Summer  1992  Summer   \n",
       "Viktoriya Viktorovna Zyabkina     Kazakhstan  KAZ  2012 Summer  2012  Summer   \n",
       "Dominik ycki                          Poland  POL  2012 Summer  2012  Summer   \n",
       "ukasz Tomasz ygado                    Poland  POL  2012 Summer  2012  Summer   \n",
       "\n",
       "                                      City                 Sport  \\\n",
       "Name                                                               \n",
       "A Dijiang                        Barcelona            Basketball   \n",
       "A Lamusi                            London                  Judo   \n",
       "Christine Jacoba Aaftink       Albertville         Speed Skating   \n",
       "Christine Jacoba Aaftink       Albertville         Speed Skating   \n",
       "Per Knut Aaland                Albertville  Cross Country Skiing   \n",
       "...                                    ...                   ...   \n",
       "Sawomir Andrzej Zwierzyski       Barcelona               Fencing   \n",
       "Henk Jan Zwolle                  Barcelona                Rowing   \n",
       "Viktoriya Viktorovna Zyabkina       London             Athletics   \n",
       "Dominik ycki                        London               Sailing   \n",
       "ukasz Tomasz ygado                  London            Volleyball   \n",
       "\n",
       "                                                                  Event  \\\n",
       "Name                                                                      \n",
       "A Dijiang                                   Basketball Men's Basketball   \n",
       "A Lamusi                                   Judo Men's Extra-Lightweight   \n",
       "Christine Jacoba Aaftink               Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink             Speed Skating Women's 1,000 metres   \n",
       "Per Knut Aaland                Cross Country Skiing Men's 10 kilometres   \n",
       "...                                                                 ...   \n",
       "Sawomir Andrzej Zwierzyski                     Fencing Men's epee, Team   \n",
       "Henk Jan Zwolle                              Rowing Men's Double Sculls   \n",
       "Viktoriya Viktorovna Zyabkina              Athletics Women's 200 metres   \n",
       "Dominik ycki                          Sailing Men's Two Person Keelboat   \n",
       "ukasz Tomasz ygado                          Volleyball Men's Volleyball   \n",
       "\n",
       "                                Medal  \n",
       "Name                                   \n",
       "A Dijiang                         NaN  \n",
       "A Lamusi                          NaN  \n",
       "Christine Jacoba Aaftink          NaN  \n",
       "Christine Jacoba Aaftink          NaN  \n",
       "Per Knut Aaland                   NaN  \n",
       "...                               ...  \n",
       "Sawomir Andrzej Zwierzyski        NaN  \n",
       "Henk Jan Zwolle                Bronze  \n",
       "Viktoriya Viktorovna Zyabkina     NaN  \n",
       "Dominik ycki                      NaN  \n",
       "ukasz Tomasz ygado                NaN  \n",
       "\n",
       "[29333 rows x 14 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to check something within a set use isin\n",
    "mask1 = [1992,2012]\n",
    "olympics.loc[olympics.Year.isin(mask1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "462f6490",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1920, 1900, 1988, 1994, 1932, 2002, 1952, 1980, 2000, 1996, 1912,\n",
       "       1924, 2014, 1948, 1998, 2006, 2008, 2016, 2004, 1960, 1964, 1984,\n",
       "       1968, 1972, 1936, 1956, 1928, 1976, 2010, 1906, 1904, 1908, 1896],\n",
       "      dtype=int64)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.loc[~olympics.Year.isin(mask1)]['Year'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "54537fe4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 887 entries, 0 to 886\n",
      "Data columns (total 8 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   Survived                 887 non-null    int64  \n",
      " 1   Pclass                   887 non-null    int64  \n",
      " 2   Name                     887 non-null    object \n",
      " 3   Sex                      887 non-null    object \n",
      " 4   Age                      887 non-null    float64\n",
      " 5   Siblings/Spouses Aboard  887 non-null    int64  \n",
      " 6   Parents/Children Aboard  887 non-null    int64  \n",
      " 7   Fare                     887 non-null    float64\n",
      "dtypes: float64(2), int64(4), object(2)\n",
      "memory usage: 55.6+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c7952ed9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Return whether any element is True, potentially over an axis.\n",
    "(titanic.Sex == 'Male').any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "f9bac564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Return whether all elements are True, potentially over an axis.\n",
    "(titanic.Sex != 'Male').all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "74989f73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Survived, Pclass, Name, Sex, Age, Siblings/Spouses Aboard, Parents/Children Aboard, Fare]\n",
       "Index: []"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[titanic.Sex == 'Male']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "762de9ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29.471443066516347"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Age.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "4e576922",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(titanic.Age >= 90).any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "2413cb86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
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       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Owen Harris Braund</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. John Bradley (Florence Briggs Thayer) Cum...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Laina Heikkinen</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. Jacques Heath (Lily May Peel) Futrelle</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. William Henry Allen</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Survived  Pclass                                               Name  \\\n",
       "0         0       3                             Mr. Owen Harris Braund   \n",
       "1         1       1  Mrs. John Bradley (Florence Briggs Thayer) Cum...   \n",
       "2         1       3                              Miss. Laina Heikkinen   \n",
       "3         1       1        Mrs. Jacques Heath (Lily May Peel) Futrelle   \n",
       "4         0       3                            Mr. William Henry Allen   \n",
       "\n",
       "      Sex   Age  Siblings/Spouses Aboard  Parents/Children Aboard     Fare  \n",
       "0    male  22.0                        1                        0   7.2500  \n",
       "1  female  38.0                        1                        0  71.2833  \n",
       "2  female  26.0                        0                        0   7.9250  \n",
       "3  female  35.0                        1                        0  53.1000  \n",
       "4    male  35.0                        0                        0   8.0500  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b20b11d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic.drop(index=0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "dc002ecc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>Mrs. John Bradley (Florence Briggs Thayer) Cum...</td>\n",
       "      <td>female</td>\n",
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       "      <td>71.2833</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Laina Heikkinen</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. Jacques Heath (Lily May Peel) Futrelle</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. William Henry Allen</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. James Moran</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.4583</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Survived  Pclass                                               Name  \\\n",
       "1         1       1  Mrs. John Bradley (Florence Briggs Thayer) Cum...   \n",
       "2         1       3                              Miss. Laina Heikkinen   \n",
       "3         1       1        Mrs. Jacques Heath (Lily May Peel) Futrelle   \n",
       "4         0       3                            Mr. William Henry Allen   \n",
       "5         0       3                                    Mr. James Moran   \n",
       "\n",
       "      Sex   Age  Siblings/Spouses Aboard  Parents/Children Aboard     Fare  \n",
       "1  female  38.0                        1                        0  71.2833  \n",
       "2  female  26.0                        0                        0   7.9250  \n",
       "3  female  35.0                        1                        0  53.1000  \n",
       "4    male  35.0                        0                        0   8.0500  \n",
       "5    male  27.0                        0                        0   8.4583  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "e3703aba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    885\n",
       "True       1\n",
       "Name: Age, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(titanic.Age >=80).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3cfe1e4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Algernon Henry Wilson Barkworth</td>\n",
       "      <td>male</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Survived  Pclass                                 Name   Sex   Age  \\\n",
       "627         1       1  Mr. Algernon Henry Wilson Barkworth  male  80.0   \n",
       "\n",
       "     Siblings/Spouses Aboard  Parents/Children Aboard  Fare  \n",
       "627                        0                        0  30.0  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[titanic.Age>=80]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "94d22667",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 271116 entries, A Dijiang to Tomasz Ireneusz ya\n",
      "Data columns (total 14 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   ID      271116 non-null  int64  \n",
      " 1   Sex     271116 non-null  object \n",
      " 2   Age     261642 non-null  float64\n",
      " 3   Height  210945 non-null  float64\n",
      " 4   Weight  208241 non-null  float64\n",
      " 5   Team    271116 non-null  object \n",
      " 6   NOC     271116 non-null  object \n",
      " 7   Games   271116 non-null  object \n",
      " 8   Year    271116 non-null  int64  \n",
      " 9   Season  271116 non-null  object \n",
      " 10  City    271116 non-null  object \n",
      " 11  Sport   271116 non-null  object \n",
      " 12  Event   271116 non-null  object \n",
      " 13  Medal   39783 non-null   object \n",
      "dtypes: float64(3), int64(2), object(9)\n",
      "memory usage: 39.1+ MB\n"
     ]
    }
   ],
   "source": [
    "olympics.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "24578d8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to know is a value in the data frame\n",
    "1996 in olympics.Year.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "7ad7eeb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Medal</th>\n",
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       "      <th>Name</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A Dijiang</th>\n",
       "      <td>1</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>1992 Summer</td>\n",
       "      <td>1992</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Basketball</td>\n",
       "      <td>Basketball Men's Basketball</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Lamusi</th>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>23.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>China</td>\n",
       "      <td>CHN</td>\n",
       "      <td>2012 Summer</td>\n",
       "      <td>2012</td>\n",
       "      <td>Summer</td>\n",
       "      <td>London</td>\n",
       "      <td>Judo</td>\n",
       "      <td>Judo Men's Extra-Lightweight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gunnar Nielsen Aaby</th>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1920 Summer</td>\n",
       "      <td>1920</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Football</td>\n",
       "      <td>Football Men's Football</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edgar Lindenau Aabye</th>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Denmark/Sweden</td>\n",
       "      <td>DEN</td>\n",
       "      <td>1900 Summer</td>\n",
       "      <td>1900</td>\n",
       "      <td>Summer</td>\n",
       "      <td>Paris</td>\n",
       "      <td>Tug-Of-War</td>\n",
       "      <td>Tug-Of-War Men's Tug-Of-War</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1988 Winter</td>\n",
       "      <td>1988</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1992 Winter</td>\n",
       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1992 Winter</td>\n",
       "      <td>1992</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Albertville</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 500 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christine Jacoba Aaftink</th>\n",
       "      <td>5</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NED</td>\n",
       "      <td>1994 Winter</td>\n",
       "      <td>1994</td>\n",
       "      <td>Winter</td>\n",
       "      <td>Lillehammer</td>\n",
       "      <td>Speed Skating</td>\n",
       "      <td>Speed Skating Women's 1,000 metres</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          ID Sex   Age  Height  Weight            Team  NOC  \\\n",
       "Name                                                                          \n",
       "A Dijiang                  1   M  24.0   180.0    80.0           China  CHN   \n",
       "A Lamusi                   2   M  23.0   170.0    60.0           China  CHN   \n",
       "Gunnar Nielsen Aaby        3   M  24.0     NaN     NaN         Denmark  DEN   \n",
       "Edgar Lindenau Aabye       4   M  34.0     NaN     NaN  Denmark/Sweden  DEN   \n",
       "Christine Jacoba Aaftink   5   F  21.0   185.0    82.0     Netherlands  NED   \n",
       "Christine Jacoba Aaftink   5   F  21.0   185.0    82.0     Netherlands  NED   \n",
       "Christine Jacoba Aaftink   5   F  25.0   185.0    82.0     Netherlands  NED   \n",
       "Christine Jacoba Aaftink   5   F  25.0   185.0    82.0     Netherlands  NED   \n",
       "Christine Jacoba Aaftink   5   F  27.0   185.0    82.0     Netherlands  NED   \n",
       "Christine Jacoba Aaftink   5   F  27.0   185.0    82.0     Netherlands  NED   \n",
       "\n",
       "                                Games  Year  Season         City  \\\n",
       "Name                                                               \n",
       "A Dijiang                 1992 Summer  1992  Summer    Barcelona   \n",
       "A Lamusi                  2012 Summer  2012  Summer       London   \n",
       "Gunnar Nielsen Aaby       1920 Summer  1920  Summer    Antwerpen   \n",
       "Edgar Lindenau Aabye      1900 Summer  1900  Summer        Paris   \n",
       "Christine Jacoba Aaftink  1988 Winter  1988  Winter      Calgary   \n",
       "Christine Jacoba Aaftink  1988 Winter  1988  Winter      Calgary   \n",
       "Christine Jacoba Aaftink  1992 Winter  1992  Winter  Albertville   \n",
       "Christine Jacoba Aaftink  1992 Winter  1992  Winter  Albertville   \n",
       "Christine Jacoba Aaftink  1994 Winter  1994  Winter  Lillehammer   \n",
       "Christine Jacoba Aaftink  1994 Winter  1994  Winter  Lillehammer   \n",
       "\n",
       "                                  Sport                               Event  \\\n",
       "Name                                                                          \n",
       "A Dijiang                    Basketball         Basketball Men's Basketball   \n",
       "A Lamusi                           Judo        Judo Men's Extra-Lightweight   \n",
       "Gunnar Nielsen Aaby            Football             Football Men's Football   \n",
       "Edgar Lindenau Aabye         Tug-Of-War         Tug-Of-War Men's Tug-Of-War   \n",
       "Christine Jacoba Aaftink  Speed Skating    Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating  Speed Skating Women's 1,000 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating    Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating  Speed Skating Women's 1,000 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating    Speed Skating Women's 500 metres   \n",
       "Christine Jacoba Aaftink  Speed Skating  Speed Skating Women's 1,000 metres   \n",
       "\n",
       "                         Medal  \n",
       "Name                            \n",
       "A Dijiang                  NaN  \n",
       "A Lamusi                   NaN  \n",
       "Gunnar Nielsen Aaby        NaN  \n",
       "Edgar Lindenau Aabye      Gold  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  \n",
       "Christine Jacoba Aaftink   NaN  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olympics.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7a08536c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(titanic.Age <=1).any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1597186a",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic.loc[titanic.Age <=1,'Age']=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "104558f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(titanic.Age <1).any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd0f98c1",
   "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>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Siblings/Spouses Aboard</th>\n",
       "      <th>Parents/Children Aboard</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Zero</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Owen Harris Braund</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Zero</td>\n",
       "      <td>7.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. John Bradley (Florence Briggs Thayer) Cum...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Zero</td>\n",
       "      <td>71.2833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Laina Heikkinen</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Zero</td>\n",
       "      <td>Zero</td>\n",
       "      <td>7.925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs. Jacques Heath (Lily May Peel) Futrelle</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Zero</td>\n",
       "      <td>53.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Zero</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. William Henry Allen</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Zero</td>\n",
       "      <td>Zero</td>\n",
       "      <td>8.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>Zero</td>\n",
       "      <td>2</td>\n",
       "      <td>Rev. Juozas Montvila</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Zero</td>\n",
       "      <td>Zero</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Miss. Margaret Edith Graham</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Zero</td>\n",
       "      <td>Zero</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>Zero</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss. Catherine Helen Johnston</td>\n",
       "      <td>female</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>23.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mr. Karl Howell Behr</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Zero</td>\n",
       "      <td>Zero</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>Zero</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr. Patrick Dooley</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>Zero</td>\n",
       "      <td>Zero</td>\n",
       "      <td>7.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>887 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Survived  Pclass                                               Name  \\\n",
       "0       Zero       3                             Mr. Owen Harris Braund   \n",
       "1          1       1  Mrs. John Bradley (Florence Briggs Thayer) Cum...   \n",
       "2          1       3                              Miss. Laina Heikkinen   \n",
       "3          1       1        Mrs. Jacques Heath (Lily May Peel) Futrelle   \n",
       "4       Zero       3                            Mr. William Henry Allen   \n",
       "..       ...     ...                                                ...   \n",
       "882     Zero       2                               Rev. Juozas Montvila   \n",
       "883        1       1                        Miss. Margaret Edith Graham   \n",
       "884     Zero       3                     Miss. Catherine Helen Johnston   \n",
       "885        1       1                               Mr. Karl Howell Behr   \n",
       "886     Zero       3                                 Mr. Patrick Dooley   \n",
       "\n",
       "        Sex   Age Siblings/Spouses Aboard Parents/Children Aboard     Fare  \n",
       "0      male  22.0                       1                    Zero     7.25  \n",
       "1    female  38.0                       1                    Zero  71.2833  \n",
       "2    female  26.0                    Zero                    Zero    7.925  \n",
       "3    female  35.0                       1                    Zero     53.1  \n",
       "4      male  35.0                    Zero                    Zero     8.05  \n",
       "..      ...   ...                     ...                     ...      ...  \n",
       "882    male  27.0                    Zero                    Zero     13.0  \n",
       "883  female  19.0                    Zero                    Zero     30.0  \n",
       "884  female   7.0                       1                       2    23.45  \n",
       "885    male  26.0                    Zero                    Zero     30.0  \n",
       "886    male  32.0                    Zero                    Zero     7.75  \n",
       "\n",
       "[887 rows x 8 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you want to replace one value to new value, use replace method\n",
    "titanic.replace(0,'Zero')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5b8088d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "age = titanic.Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bda9f5a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age._is_view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4a715e8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bb56f6aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp._is_view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "084cdffa",
   "metadata": {},
   "outputs": [],
   "source": [
    "age = titanic.Age.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "69674724",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age._is_view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7f8e3758",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "survived     0.383838\n",
       "pclass       2.308642\n",
       "age         29.699118\n",
       "sibsp        0.523008\n",
       "parch        0.381594\n",
       "fare        32.204208\n",
       "dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.agg('mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a389d3e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "survived     0.383838\n",
       "pclass       2.308642\n",
       "age         29.699118\n",
       "sibsp        0.523008\n",
       "parch        0.381594\n",
       "fare        32.204208\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ca996692",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "survived           1\n",
       "pclass             3\n",
       "sex             male\n",
       "age             80.0\n",
       "sibsp              8\n",
       "parch              6\n",
       "fare        512.3292\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "961dc3ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "survived           1\n",
       "pclass             3\n",
       "sex             male\n",
       "age             80.0\n",
       "sibsp              8\n",
       "parch              6\n",
       "fare        512.3292\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.agg('max')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "61c3f6c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      survived    pclass        age     sibsp     parch       fare\n",
       "mean  0.383838  2.308642  29.699118  0.523008  0.381594  32.204208\n",
       "std   0.486592  0.836071  14.526497  1.102743  0.806057  49.693429"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.agg(['mean','std'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6c0f6145",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.383838</td>\n",
       "      <td>29.699118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.420000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      survived        age\n",
       "mean  0.383838  29.699118\n",
       "max        NaN  80.000000\n",
       "min        NaN   0.420000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.agg({'survived':'mean','age':['mean','max','min']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bd4570d8",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>28.34369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>80.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.42000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median</th>\n",
       "      <td>28.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             age\n",
       "mean    28.34369\n",
       "max     80.00000\n",
       "min      0.42000\n",
       "median  28.00000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[titanic.survived==1].agg({'age':['mean','max','min','median']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "150be3a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Mon</th>\n",
       "      <th>Tue</th>\n",
       "      <th>Wed</th>\n",
       "      <th>Thu</th>\n",
       "      <th>Fri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Steven</td>\n",
       "      <td>34</td>\n",
       "      <td>27</td>\n",
       "      <td>15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mike</td>\n",
       "      <td>45</td>\n",
       "      <td>9</td>\n",
       "      <td>74</td>\n",
       "      <td>87.0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Andi</td>\n",
       "      <td>17</td>\n",
       "      <td>33</td>\n",
       "      <td>54</td>\n",
       "      <td>8.0</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Paul</td>\n",
       "      <td>87</td>\n",
       "      <td>67</td>\n",
       "      <td>27</td>\n",
       "      <td>45.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Unnamed: 0  Mon  Tue  Wed   Thu  Fri\n",
       "0     Steven   34   27   15   NaN   33\n",
       "1       Mike   45    9   74  87.0   12\n",
       "2       Andi   17   33   54   8.0   29\n",
       "3       Paul   87   67   27  45.0    7"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales = pd.read_csv(r'sales.csv')\n",
    "sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "26ca6ec5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0    Andi\n",
       "Mon             17\n",
       "Tue              9\n",
       "Wed             15\n",
       "Thu            8.0\n",
       "Fri              7\n",
       "dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.min(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f51462c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    15.0\n",
       "1     9.0\n",
       "2     8.0\n",
       "3     7.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.min(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2a6a7fcb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def range(series):\n",
    "    return series.max() - series.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f49ffb35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0    Steven\n",
       "Mon               87\n",
       "Tue               67\n",
       "Wed               74\n",
       "Thu             87.0\n",
       "Fri               33\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.apply(lambda x:x.max(),axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e42706a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0    Andi\n",
       "Mon             17\n",
       "Tue              9\n",
       "Wed             15\n",
       "Thu            8.0\n",
       "Fri              7\n",
       "dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales.apply(lambda x : x.min(),axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "796afcdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "summer = pd.read_csv(r'summer.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ed7a2803",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\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": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summer.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e0ec6b03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         HAJOS, Alfred\n",
       "1      HERSCHMANN, Otto\n",
       "2     DRIVAS, Dimitrios\n",
       "3    MALOKINIS, Ioannis\n",
       "4    CHASAPIS, Spiridon\n",
       "Name: Athlete, dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summer.Athlete.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "603edbd6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def findComma(s):\n",
    "    index = 1\n",
    "    for i in s:\n",
    "        if i != ',':\n",
    "            index+=1\n",
    "        else:\n",
    "            break\n",
    "    return index-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b756bbb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             HAJOS\n",
       "1        HERSCHMANN\n",
       "2            DRIVAS\n",
       "3         MALOKINIS\n",
       "4          CHASAPIS\n",
       "            ...    \n",
       "31160    JANIKOWSKI\n",
       "31161        REZAEI\n",
       "31162        TOTROV\n",
       "31163    ALEKSANYAN\n",
       "31164       LIDBERG\n",
       "Name: Athlete, Length: 31165, dtype: object"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summer.Athlete.apply(lambda x : x[0:findComma(x)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "2fa72545",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             HAJOS\n",
       "1        HERSCHMANN\n",
       "2            DRIVAS\n",
       "3         MALOKINIS\n",
       "4          CHASAPIS\n",
       "            ...    \n",
       "31160    JANIKOWSKI\n",
       "31161        REZAEI\n",
       "31162        TOTROV\n",
       "31163    ALEKSANYAN\n",
       "31164       LIDBERG\n",
       "Name: Athlete, Length: 31165, dtype: object"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summer.Athlete.map(lambda x : x[0:findComma(x)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "774f6fc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                    [HAJOS,  Alfred]\n",
       "1                 [HERSCHMANN,  Otto]\n",
       "2                [DRIVAS,  Dimitrios]\n",
       "3               [MALOKINIS,  Ioannis]\n",
       "4               [CHASAPIS,  Spiridon]\n",
       "                     ...             \n",
       "31160           [JANIKOWSKI,  Damian]\n",
       "31161    [REZAEI,  Ghasem Gholamreza]\n",
       "31162               [TOTROV,  Rustam]\n",
       "31163            [ALEKSANYAN,  Artur]\n",
       "31164               [LIDBERG,  Jimmy]\n",
       "Name: Athlete, Length: 31165, dtype: object"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summer.Athlete.apply(lambda x : x.split(',') )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "8b2932e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "names = summer.Athlete.loc[:10].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "50a5a313",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             HAJOS, Alfred\n",
       "1          HERSCHMANN, Otto\n",
       "2         DRIVAS, Dimitrios\n",
       "3        MALOKINIS, Ioannis\n",
       "4        CHASAPIS, Spiridon\n",
       "5     CHOROPHAS, Efstathios\n",
       "6             HAJOS, Alfred\n",
       "7          ANDREOU, Joannis\n",
       "8     CHOROPHAS, Efstathios\n",
       "9             NEUMANN, Paul\n",
       "10        PEPANOS, Antonios\n",
       "Name: Athlete, dtype: object"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "5a4f1398",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             hajos, alfred\n",
       "1          herschmann, otto\n",
       "2         drivas, dimitrios\n",
       "3        malokinis, ioannis\n",
       "4        chasapis, spiridon\n",
       "5     chorophas, efstathios\n",
       "6             hajos, alfred\n",
       "7          andreou, joannis\n",
       "8     chorophas, efstathios\n",
       "9             neumann, paul\n",
       "10        pepanos, antonios\n",
       "Name: Athlete, dtype: object"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#in pandas, you can use strig method with str\n",
    "names.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "4f5837f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     13\n",
       "1     16\n",
       "2     17\n",
       "3     18\n",
       "4     18\n",
       "5     21\n",
       "6     13\n",
       "7     16\n",
       "8     21\n",
       "9     13\n",
       "10    17\n",
       "Name: Athlete, dtype: int64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names.str.len()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "b8fd6a55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             [HAJOS,  Alfred]\n",
       "1          [HERSCHMANN,  Otto]\n",
       "2         [DRIVAS,  Dimitrios]\n",
       "3        [MALOKINIS,  Ioannis]\n",
       "4        [CHASAPIS,  Spiridon]\n",
       "5     [CHOROPHAS,  Efstathios]\n",
       "6             [HAJOS,  Alfred]\n",
       "7          [ANDREOU,  Joannis]\n",
       "8     [CHOROPHAS,  Efstathios]\n",
       "9             [NEUMANN,  Paul]\n",
       "10        [PEPANOS,  Antonios]\n",
       "Name: Athlete, dtype: object"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names.str.split(',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "70f6ce45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    -1\n",
       "1    -1\n",
       "2    -1\n",
       "3    -1\n",
       "4    -1\n",
       "5    -1\n",
       "6    -1\n",
       "7     0\n",
       "8    -1\n",
       "9    -1\n",
       "10   -1\n",
       "Name: Athlete, dtype: int64"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names.str.find('AND')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "de2d903d",
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HAJOS</td>\n",
       "      <td>Alfred</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HERSCHMANN</td>\n",
       "      <td>Otto</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DRIVAS</td>\n",
       "      <td>Dimitrios</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MALOKINIS</td>\n",
       "      <td>Ioannis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHASAPIS</td>\n",
       "      <td>Spiridon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CHOROPHAS</td>\n",
       "      <td>Efstathios</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>HAJOS</td>\n",
       "      <td>Alfred</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ANDREOU</td>\n",
       "      <td>Joannis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CHOROPHAS</td>\n",
       "      <td>Efstathios</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NEUMANN</td>\n",
       "      <td>Paul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PEPANOS</td>\n",
       "      <td>Antonios</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             0            1\n",
       "0        HAJOS       Alfred\n",
       "1   HERSCHMANN         Otto\n",
       "2       DRIVAS    Dimitrios\n",
       "3    MALOKINIS      Ioannis\n",
       "4     CHASAPIS     Spiridon\n",
       "5    CHOROPHAS   Efstathios\n",
       "6        HAJOS       Alfred\n",
       "7      ANDREOU      Joannis\n",
       "8    CHOROPHAS   Efstathios\n",
       "9      NEUMANN         Paul\n",
       "10     PEPANOS     Antonios"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names.str.split(',',n=2,expand=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "f9579dd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic = titanic.iloc[0:50,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "15b39af4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 50 entries, 0 to 49\n",
      "Data columns (total 9 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   survived  50 non-null     int64  \n",
      " 1   pclass    50 non-null     int64  \n",
      " 2   sex       50 non-null     object \n",
      " 3   age       36 non-null     float64\n",
      " 4   sibsp     50 non-null     int64  \n",
      " 5   parch     50 non-null     int64  \n",
      " 6   fare      50 non-null     float64\n",
      " 7   embarked  50 non-null     object \n",
      " 8   deck      9 non-null      object \n",
      "dtypes: float64(2), int64(4), object(3)\n",
      "memory usage: 3.6+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "ec77be72",
   "metadata": {},
   "outputs": [],
   "source": [
    "#if you use list of columns to set index, you define heirachical indexing\n",
    "titanic.set_index(['pclass','sex'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "4f42c6bd",
   "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></th>\n",
       "      <th>survived</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>deck</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">1</th>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>146.5208</td>\n",
       "      <td>C</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>S</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>263.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27.7208</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>82.1708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">2</th>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>41.5792</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"32\" valign=\"top\">3</th>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>11.1333</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>16.7000</td>\n",
       "      <td>S</td>\n",
       "      <td>G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8542</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0292</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>31.3875</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8792</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>11.2417</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9.4750</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8792</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7500</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>17.8000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.4583</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>21.0750</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>31.2750</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>29.1250</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2250</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2292</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>15.5000</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>21.6792</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               survived   age  sibsp  parch      fare embarked deck\n",
       "pclass sex                                                         \n",
       "1      female         1  38.0      1      0   71.2833        C    C\n",
       "       female         1  35.0      1      0   53.1000        S    C\n",
       "       female         1  58.0      0      0   26.5500        S    C\n",
       "       female         1   NaN      1      0  146.5208        C    B\n",
       "       male           0  54.0      0      0   51.8625        S    E\n",
       "       male           1  28.0      0      0   35.5000        S    A\n",
       "       male           0  19.0      3      2  263.0000        S    C\n",
       "       male           0  40.0      0      0   27.7208        C  NaN\n",
       "       male           0  28.0      1      0   82.1708        C  NaN\n",
       "       male           0  42.0      1      0   52.0000        S  NaN\n",
       "2      female         1  14.0      1      0   30.0708        C  NaN\n",
       "       female         1  55.0      0      0   16.0000        S  NaN\n",
       "       female         0  27.0      1      0   21.0000        S  NaN\n",
       "       female         1   3.0      1      2   41.5792        C  NaN\n",
       "       male           1   NaN      0      0   13.0000        S  NaN\n",
       "       male           0  35.0      0      0   26.0000        S  NaN\n",
       "       male           1  34.0      0      0   13.0000        S    D\n",
       "       male           0  66.0      0      0   10.5000        S  NaN\n",
       "3      female         1  26.0      0      0    7.9250        S  NaN\n",
       "       female         1  27.0      0      2   11.1333        S  NaN\n",
       "       female         1   4.0      1      1   16.7000        S    G\n",
       "       female         0  14.0      0      0    7.8542        S  NaN\n",
       "       female         0  31.0      1      0   18.0000        S  NaN\n",
       "       female         1   NaN      0      0    7.2250        C  NaN\n",
       "       female         1  15.0      0      0    8.0292        Q  NaN\n",
       "       female         0   8.0      3      1   21.0750        S  NaN\n",
       "       female         1  38.0      1      5   31.3875        S  NaN\n",
       "       female         1   NaN      0      0    7.8792        Q  NaN\n",
       "       female         1   NaN      0      0    7.7500        Q  NaN\n",
       "       female         0  18.0      2      0   18.0000        S  NaN\n",
       "       female         1  14.0      1      0   11.2417        C  NaN\n",
       "       female         0  40.0      1      0    9.4750        S  NaN\n",
       "       female         1  19.0      0      0    7.8792        Q  NaN\n",
       "       female         1   NaN      0      0    7.7500        Q  NaN\n",
       "       female         0  18.0      1      0   17.8000        S  NaN\n",
       "       male           0  22.0      1      0    7.2500        S  NaN\n",
       "       male           0  35.0      0      0    8.0500        S  NaN\n",
       "       male           0   NaN      0      0    8.4583        Q  NaN\n",
       "       male           0   2.0      3      1   21.0750        S  NaN\n",
       "       male           0  20.0      0      0    8.0500        S  NaN\n",
       "       male           0  39.0      1      5   31.2750        S  NaN\n",
       "       male           0   2.0      4      1   29.1250        Q  NaN\n",
       "       male           0   NaN      0      0    7.2250        C  NaN\n",
       "       male           0   NaN      0      0    7.8958        S  NaN\n",
       "       male           1   NaN      0      0    7.2292        C  NaN\n",
       "       male           0  21.0      0      0    8.0500        S  NaN\n",
       "       male           0   NaN      0      0    7.8958        C  NaN\n",
       "       male           0   NaN      0      0    8.0500        S  NaN\n",
       "       male           0   NaN      1      0   15.5000        Q  NaN\n",
       "       male           0   NaN      2      0   21.6792        C  NaN"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "ea36f436",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic.sort_index(ascending=[False,True],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "93ecd9db",
   "metadata": {},
   "outputs": [
    {
     "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",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>deck</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th>pclass</th>\n",
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       "      <th></th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"17\" valign=\"top\">female</th>\n",
       "      <th>3</th>\n",
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       "      <td>S</td>\n",
       "      <td>G</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>31.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>8.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>21.0750</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th rowspan=\"15\" valign=\"top\">male</th>\n",
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       "      <td>0</td>\n",
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       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8958</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>15.5000</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>21.6792</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">female</th>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>41.5792</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">male</th>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">female</th>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>146.5208</td>\n",
       "      <td>C</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">male</th>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>S</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>263.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27.7208</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>82.1708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               survived   age  sibsp  parch      fare embarked deck\n",
       "sex    pclass                                                      \n",
       "female 3              1  26.0      0      0    7.9250        S  NaN\n",
       "       3              1  27.0      0      2   11.1333        S  NaN\n",
       "       3              1   4.0      1      1   16.7000        S    G\n",
       "       3              0  14.0      0      0    7.8542        S  NaN\n",
       "       3              0  31.0      1      0   18.0000        S  NaN\n",
       "       3              1   NaN      0      0    7.2250        C  NaN\n",
       "       3              1  15.0      0      0    8.0292        Q  NaN\n",
       "       3              0   8.0      3      1   21.0750        S  NaN\n",
       "       3              1  38.0      1      5   31.3875        S  NaN\n",
       "       3              1   NaN      0      0    7.8792        Q  NaN\n",
       "       3              1   NaN      0      0    7.7500        Q  NaN\n",
       "       3              0  18.0      2      0   18.0000        S  NaN\n",
       "       3              1  14.0      1      0   11.2417        C  NaN\n",
       "       3              0  40.0      1      0    9.4750        S  NaN\n",
       "       3              1  19.0      0      0    7.8792        Q  NaN\n",
       "       3              1   NaN      0      0    7.7500        Q  NaN\n",
       "       3              0  18.0      1      0   17.8000        S  NaN\n",
       "male   3              0  22.0      1      0    7.2500        S  NaN\n",
       "       3              0  35.0      0      0    8.0500        S  NaN\n",
       "       3              0   NaN      0      0    8.4583        Q  NaN\n",
       "       3              0   2.0      3      1   21.0750        S  NaN\n",
       "       3              0  20.0      0      0    8.0500        S  NaN\n",
       "       3              0  39.0      1      5   31.2750        S  NaN\n",
       "       3              0   2.0      4      1   29.1250        Q  NaN\n",
       "       3              0   NaN      0      0    7.2250        C  NaN\n",
       "       3              0   NaN      0      0    7.8958        S  NaN\n",
       "       3              1   NaN      0      0    7.2292        C  NaN\n",
       "       3              0  21.0      0      0    8.0500        S  NaN\n",
       "       3              0   NaN      0      0    7.8958        C  NaN\n",
       "       3              0   NaN      0      0    8.0500        S  NaN\n",
       "       3              0   NaN      1      0   15.5000        Q  NaN\n",
       "       3              0   NaN      2      0   21.6792        C  NaN\n",
       "female 2              1  14.0      1      0   30.0708        C  NaN\n",
       "       2              1  55.0      0      0   16.0000        S  NaN\n",
       "       2              0  27.0      1      0   21.0000        S  NaN\n",
       "       2              1   3.0      1      2   41.5792        C  NaN\n",
       "male   2              1   NaN      0      0   13.0000        S  NaN\n",
       "       2              0  35.0      0      0   26.0000        S  NaN\n",
       "       2              1  34.0      0      0   13.0000        S    D\n",
       "       2              0  66.0      0      0   10.5000        S  NaN\n",
       "female 1              1  38.0      1      0   71.2833        C    C\n",
       "       1              1  35.0      1      0   53.1000        S    C\n",
       "       1              1  58.0      0      0   26.5500        S    C\n",
       "       1              1   NaN      1      0  146.5208        C    B\n",
       "male   1              0  54.0      0      0   51.8625        S    E\n",
       "       1              1  28.0      0      0   35.5000        S    A\n",
       "       1              0  19.0      3      2  263.0000        S    C\n",
       "       1              0  40.0      0      0   27.7208        C  NaN\n",
       "       1              0  28.0      1      0   82.1708        C  NaN\n",
       "       1              0  42.0      1      0   52.0000        S  NaN"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you have heirachical index and want to swap between them\n",
    "titanic.swaplevel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "92b38fce",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "d1022b00",
   "metadata": {},
   "outputs": [
    {
     "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",
       "    .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>survived</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>deck</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>146.5208</td>\n",
       "      <td>C</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>S</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>263.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27.7208</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>82.1708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        survived   age  sibsp  parch      fare embarked deck\n",
       "sex                                                         \n",
       "female         1  38.0      1      0   71.2833        C    C\n",
       "female         1  35.0      1      0   53.1000        S    C\n",
       "female         1  58.0      0      0   26.5500        S    C\n",
       "female         1   NaN      1      0  146.5208        C    B\n",
       "male           0  54.0      0      0   51.8625        S    E\n",
       "male           1  28.0      0      0   35.5000        S    A\n",
       "male           0  19.0      3      2  263.0000        S    C\n",
       "male           0  40.0      0      0   27.7208        C  NaN\n",
       "male           0  28.0      1      0   82.1708        C  NaN\n",
       "male           0  42.0      1      0   52.0000        S  NaN"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#if you have heirachical index, loc can slice you data base on index\n",
    "titanic.loc[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "609d3b0d",
   "metadata": {},
   "outputs": [
    {
     "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",
       "        vertical-align: top;\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>deck</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">1</th>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.5500</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>146.5208</td>\n",
       "      <td>C</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>51.8625</td>\n",
       "      <td>S</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>263.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27.7208</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>82.1708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">2</th>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>30.0708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>41.5792</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0000</td>\n",
       "      <td>S</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.5000</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               survived   age  sibsp  parch      fare embarked deck\n",
       "pclass sex                                                         \n",
       "1      female         1  38.0      1      0   71.2833        C    C\n",
       "       female         1  35.0      1      0   53.1000        S    C\n",
       "       female         1  58.0      0      0   26.5500        S    C\n",
       "       female         1   NaN      1      0  146.5208        C    B\n",
       "       male           0  54.0      0      0   51.8625        S    E\n",
       "       male           1  28.0      0      0   35.5000        S    A\n",
       "       male           0  19.0      3      2  263.0000        S    C\n",
       "       male           0  40.0      0      0   27.7208        C  NaN\n",
       "       male           0  28.0      1      0   82.1708        C  NaN\n",
       "       male           0  42.0      1      0   52.0000        S  NaN\n",
       "2      female         1  14.0      1      0   30.0708        C  NaN\n",
       "       female         1  55.0      0      0   16.0000        S  NaN\n",
       "       female         0  27.0      1      0   21.0000        S  NaN\n",
       "       female         1   3.0      1      2   41.5792        C  NaN\n",
       "       male           1   NaN      0      0   13.0000        S  NaN\n",
       "       male           0  35.0      0      0   26.0000        S  NaN\n",
       "       male           1  34.0      0      0   13.0000        S    D\n",
       "       male           0  66.0      0      0   10.5000        S  NaN"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[[1,2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "e87f13b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-73-d240fdae71ba>:1: PerformanceWarning: indexing past lexsort depth may impact performance.\n",
      "  titanic.loc[(1,'male')]\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">1</th>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>54.0</td>\n",
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       "    <tr>\n",
       "      <th>male</th>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
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       "      <td>S</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27.7208</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>82.1708</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0</td>\n",
       "      <td>42.0</td>\n",
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       "      <td>NaN</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "             survived   age  sibsp  parch      fare embarked deck\n",
       "pclass sex                                                       \n",
       "1      male         0  54.0      0      0   51.8625        S    E\n",
       "       male         1  28.0      0      0   35.5000        S    A\n",
       "       male         0  19.0      3      2  263.0000        S    C\n",
       "       male         0  40.0      0      0   27.7208        C  NaN\n",
       "       male         0  28.0      1      0   82.1708        C  NaN\n",
       "       male         0  42.0      1      0   52.0000        S  NaN"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[(1,'male')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "a41ba664",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:889: PerformanceWarning: indexing past lexsort depth may impact performance.\n",
      "  return self._getitem_tuple(key)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "pclass  sex \n",
       "1       male    54.0\n",
       "        male    28.0\n",
       "        male    19.0\n",
       "        male    40.0\n",
       "        male    28.0\n",
       "        male    42.0\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[(1,'male'),'age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec8bf26f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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