Pandas_class5.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "26fd4d5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ed23e780",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 12 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   PassengerId  891 non-null    int64  \n",
      " 1   Survived     891 non-null    int64  \n",
      " 2   Pclass       891 non-null    int64  \n",
      " 3   Name         891 non-null    object \n",
      " 4   Sex          891 non-null    object \n",
      " 5   Age          714 non-null    float64\n",
      " 6   SibSp        891 non-null    int64  \n",
      " 7   Parch        891 non-null    int64  \n",
      " 8   Ticket       891 non-null    object \n",
      " 9   Fare         891 non-null    float64\n",
      " 10  Cabin        204 non-null    object \n",
      " 11  Embarked     889 non-null    object \n",
      "dtypes: float64(2), int64(5), object(5)\n",
      "memory usage: 83.7+ KB\n"
     ]
    }
   ],
   "source": [
    "titanic = pd.read_csv(\"https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv\")\n",
    "titanic.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4089a8b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "74151c4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                Braund, Mr. Owen Harris\n",
       "1      Cumings, Mrs. John Bradley (Florence Briggs Th...\n",
       "2                                 Heikkinen, Miss. Laina\n",
       "3           Futrelle, Mrs. Jacques Heath (Lily May Peel)\n",
       "4                               Allen, Mr. William Henry\n",
       "                             ...                        \n",
       "886                                Montvila, Rev. Juozas\n",
       "887                         Graham, Miss. Margaret Edith\n",
       "888             Johnston, Miss. Catherine Helen \"Carrie\"\n",
       "889                                Behr, Mr. Karl Howell\n",
       "890                                  Dooley, Mr. Patrick\n",
       "Name: Name, Length: 891, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic['Name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7d740586",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                braund, mr. owen harris\n",
       "1      cumings, mrs. john bradley (florence briggs th...\n",
       "2                                 heikkinen, miss. laina\n",
       "3           futrelle, mrs. jacques heath (lily may peel)\n",
       "4                               allen, mr. william henry\n",
       "                             ...                        \n",
       "886                                montvila, rev. juozas\n",
       "887                         graham, miss. margaret edith\n",
       "888             johnston, miss. catherine helen \"carrie\"\n",
       "889                                behr, mr. karl howell\n",
       "890                                  dooley, mr. patrick\n",
       "Name: Name, Length: 891, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Name.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3017fbc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                BRAUND, MR. OWEN HARRIS\n",
       "1      CUMINGS, MRS. JOHN BRADLEY (FLORENCE BRIGGS TH...\n",
       "2                                 HEIKKINEN, MISS. LAINA\n",
       "3           FUTRELLE, MRS. JACQUES HEATH (LILY MAY PEEL)\n",
       "4                               ALLEN, MR. WILLIAM HENRY\n",
       "                             ...                        \n",
       "886                                MONTVILA, REV. JUOZAS\n",
       "887                         GRAHAM, MISS. MARGARET EDITH\n",
       "888             JOHNSTON, MISS. CATHERINE HELEN \"CARRIE\"\n",
       "889                                BEHR, MR. KARL HOWELL\n",
       "890                                  DOOLEY, MR. PATRICK\n",
       "Name: Name, Length: 891, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Name.str.upper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4c608123",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                Braund, Mr. Owen Harris\n",
       "1      Cumings, Mrs. John Bradley (Florence Briggs Th...\n",
       "2                                 Heikkinen, Miss. Laina\n",
       "3           Futrelle, Mrs. Jacques Heath (Lily May Peel)\n",
       "4                               Allen, Mr. William Henry\n",
       "                             ...                        \n",
       "886                                Montvila, Rev. Juozas\n",
       "887                         Graham, Miss. Margaret Edith\n",
       "888             Johnston, Miss. Catherine Helen \"Carrie\"\n",
       "889                                Behr, Mr. Karl Howell\n",
       "890                                  Dooley, Mr. Patrick\n",
       "Name: Name, Length: 891, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Name.str.title()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "28a56c63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                             [Braund,  Mr. Owen Harris]\n",
       "1      [Cumings,  Mrs. John Bradley (Florence Briggs ...\n",
       "2                              [Heikkinen,  Miss. Laina]\n",
       "3        [Futrelle,  Mrs. Jacques Heath (Lily May Peel)]\n",
       "4                            [Allen,  Mr. William Henry]\n",
       "                             ...                        \n",
       "886                             [Montvila,  Rev. Juozas]\n",
       "887                      [Graham,  Miss. Margaret Edith]\n",
       "888          [Johnston,  Miss. Catherine Helen \"Carrie\"]\n",
       "889                             [Behr,  Mr. Karl Howell]\n",
       "890                               [Dooley,  Mr. Patrick]\n",
       "Name: Name, Length: 891, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[\"Name\"].str.split(\",\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b9efe0ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'pakistan, india, usa, japan'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"pakistan, india, usa, japan\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5b2234d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['pakistan', ' india', ' usa', ' japan']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"pakistan, india, usa, japan\".split(\",\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3b51a994",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         Braund\n",
       "1        Cumings\n",
       "2      Heikkinen\n",
       "3       Futrelle\n",
       "4          Allen\n",
       "         ...    \n",
       "886     Montvila\n",
       "887       Graham\n",
       "888     Johnston\n",
       "889         Behr\n",
       "890       Dooley\n",
       "Name: Surname, Length: 891, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[\"Surname\"] = titanic[\"Name\"].str.split(\",\").str.get(0)\n",
    "titanic[\"Surname\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "369274dc",
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Surname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Braund</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "      <td>Cumings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Heikkinen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "      <td>Futrelle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Allen</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked    Surname  \n",
       "0      0         A/5 21171   7.2500   NaN        S     Braund  \n",
       "1      0          PC 17599  71.2833   C85        C    Cumings  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  Heikkinen  \n",
       "3      0            113803  53.1000  C123        S   Futrelle  \n",
       "4      0            373450   8.0500   NaN        S      Allen  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a28c65de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Name.str.contains(\"Countess\").sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "55a45e83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      False\n",
       "1      False\n",
       "2      False\n",
       "3      False\n",
       "4      False\n",
       "       ...  \n",
       "886    False\n",
       "887    False\n",
       "888    False\n",
       "889    False\n",
       "890    False\n",
       "Name: Name, Length: 891, dtype: bool"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Name.str.contains(\"Countess\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b24b598d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Surname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>760</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Rothes, the Countess. of (Lucy Noel Martha Dye...</td>\n",
       "      <td>female</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>110152</td>\n",
       "      <td>86.5</td>\n",
       "      <td>B77</td>\n",
       "      <td>S</td>\n",
       "      <td>Rothes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "759          760         1       1   \n",
       "\n",
       "                                                  Name     Sex   Age  SibSp  \\\n",
       "759  Rothes, the Countess. of (Lucy Noel Martha Dye...  female  33.0      0   \n",
       "\n",
       "     Parch  Ticket  Fare Cabin Embarked Surname  \n",
       "759      0  110152  86.5   B77        S  Rothes  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[titanic.Name.str.contains(\"Countess\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "96706013",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      23\n",
       "1      51\n",
       "2      22\n",
       "3      44\n",
       "4      24\n",
       "       ..\n",
       "886    21\n",
       "887    28\n",
       "888    40\n",
       "889    21\n",
       "890    19\n",
       "Name: Name, Length: 891, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Name.str.len()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "fbd98354",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "82\n",
      "12\n"
     ]
    }
   ],
   "source": [
    "print(titanic.Name.str.len().max())\n",
    "print(titanic.Name.str.len().min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f6256d05",
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Surname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>308</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Penasco y Castellana, Mrs. Victor de Satode (M...</td>\n",
       "      <td>female</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17758</td>\n",
       "      <td>108.9</td>\n",
       "      <td>C65</td>\n",
       "      <td>C</td>\n",
       "      <td>Penasco y Castellana</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "307          308         1       1   \n",
       "\n",
       "                                                  Name     Sex   Age  SibSp  \\\n",
       "307  Penasco y Castellana, Mrs. Victor de Satode (M...  female  17.0      1   \n",
       "\n",
       "     Parch    Ticket   Fare Cabin Embarked               Surname  \n",
       "307      0  PC 17758  108.9   C65        C  Penasco y Castellana  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[titanic.Name.str.len() == 82]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ec97ae37",
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Surname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>693</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Lam, Mr. Ali</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1601</td>\n",
       "      <td>56.4958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Lam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>826</th>\n",
       "      <td>827</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Lam, Mr. Len</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1601</td>\n",
       "      <td>56.4958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Lam</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass          Name   Sex  Age  SibSp  Parch  \\\n",
       "692          693         1       3  Lam, Mr. Ali  male  NaN      0      0   \n",
       "826          827         0       3  Lam, Mr. Len  male  NaN      0      0   \n",
       "\n",
       "    Ticket     Fare Cabin Embarked Surname  \n",
       "692   1601  56.4958   NaN        S     Lam  \n",
       "826   1601  56.4958   NaN        S     Lam  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[titanic.Name.str.len() == 12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "22adbcdb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "307"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[\"Name\"].str.len().idxmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "390ffd14",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "444b6d70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "692"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[\"Name\"].str.len().idxmin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3beb936b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo)'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.loc[titanic[\"Name\"].str.len().idxmax(), \"Name\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d5e93d2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        male\n",
       "1      female\n",
       "2      female\n",
       "3      female\n",
       "4        male\n",
       "        ...  \n",
       "886      male\n",
       "887    female\n",
       "888    female\n",
       "889      male\n",
       "890      male\n",
       "Name: Sex, Length: 891, dtype: object"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[\"Sex\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b80b6892",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      M\n",
       "1      F\n",
       "2      F\n",
       "3      F\n",
       "4      M\n",
       "      ..\n",
       "886    M\n",
       "887    F\n",
       "888    F\n",
       "889    M\n",
       "890    M\n",
       "Name: Sex, Length: 891, dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[\"Sex\"].replace({\"male\": \"M\", \"female\": \"F\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "75411973",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      M\n",
       "1      F\n",
       "2      F\n",
       "3      F\n",
       "4      M\n",
       "      ..\n",
       "886    M\n",
       "887    F\n",
       "888    F\n",
       "889    M\n",
       "890    M\n",
       "Name: Sex, Length: 891, dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic[\"Sex\"].map({\"male\": \"M\", \"female\": \"F\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9a047c26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
       "       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked', 'Surname'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2b5ebdec",
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic[\"Sex_short\"] = titanic[\"Sex\"].replace({\"male\": \"M\", \"female\": \"F\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "c05e55be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
       "       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked', 'Surname', 'Sex_short'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "9113c10a",
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "      <th>Surname</th>\n",
       "      <th>Sex_short</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>Braund</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass                     Name   Sex   Age  SibSp  \\\n",
       "0            1         0       3  Braund, Mr. Owen Harris  male  22.0      1   \n",
       "\n",
       "   Parch     Ticket  Fare Cabin Embarked Surname Sex_short  \n",
       "0      0  A/5 21171  7.25   NaN        S  Braund         M  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6077ec9b",
   "metadata": {},
   "source": [
    "# apply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "ca0b3ebe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Pakistan zinda baD'"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def my_fun(x):\n",
    "\n",
    "    x = x[0].upper() + x[1:-1].lower() + x[-1].upper()\n",
    "    return x\n",
    "\n",
    "my_fun(\"Pakistan Zinda bad\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "f6819b85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                Braund, mr. owen harriS\n",
       "1      Cumings, mrs. john bradley (florence briggs th...\n",
       "2                                 Heikkinen, miss. lainA\n",
       "3           Futrelle, mrs. jacques heath (lily may peel)\n",
       "4                               Allen, mr. william henrY\n",
       "                             ...                        \n",
       "886                                Montvila, rev. juozaS\n",
       "887                         Graham, miss. margaret editH\n",
       "888             Johnston, miss. catherine helen \"carrie\"\n",
       "889                                Behr, mr. karl howelL\n",
       "890                                  Dooley, mr. patricK\n",
       "Name: Name, Length: 891, dtype: object"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.Name.apply(my_fun)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "7e374ab8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>roll</th>\n",
       "      <th>name</th>\n",
       "      <th>sub1</th>\n",
       "      <th>sub2</th>\n",
       "      <th>sub3</th>\n",
       "      <th>sub4</th>\n",
       "      <th>sub5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>94</td>\n",
       "      <td>20</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>B</td>\n",
       "      <td>8</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>46</td>\n",
       "      <td>95</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>56</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>E</td>\n",
       "      <td>85</td>\n",
       "      <td>46</td>\n",
       "      <td>21</td>\n",
       "      <td>75</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>F</td>\n",
       "      <td>86</td>\n",
       "      <td>68</td>\n",
       "      <td>78</td>\n",
       "      <td>99</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>G</td>\n",
       "      <td>53</td>\n",
       "      <td>44</td>\n",
       "      <td>35</td>\n",
       "      <td>58</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>H</td>\n",
       "      <td>38</td>\n",
       "      <td>8</td>\n",
       "      <td>85</td>\n",
       "      <td>39</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>I</td>\n",
       "      <td>87</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>44</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>J</td>\n",
       "      <td>92</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "      <td>11</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   roll name  sub1  sub2  sub3  sub4  sub5\n",
       "0     1    A    94    20    70    30    91\n",
       "1     2    B     8    72     1     5     8\n",
       "2     3    C    46    95    68    67    48\n",
       "3     4    D    56    11     4    16     1\n",
       "4     5    E    85    46    21    75    44\n",
       "5     6    F    86    68    78    99    56\n",
       "6     7    G    53    44    35    58    53\n",
       "7     8    H    38     8    85    39    62\n",
       "8     9    I    87    40     5    44    91\n",
       "9    10    J    92    41    40    11    51"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    \"roll\":[1,2,3,4,5,6,7,8,9,10],\n",
    "    'name':list('ABCDEFGHIJ'),\n",
    "    'sub1':np.random.randint(1,100, 10),\n",
    "    'sub2':np.random.randint(1,100, 10),\n",
    "    'sub3':np.random.randint(1,100, 10),\n",
    "    'sub4':np.random.randint(1,100, 10),\n",
    "    'sub5':np.random.randint(1,100, 10),\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "77f6aeff",
   "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",
       "    }\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>roll</th>\n",
       "      <th>name</th>\n",
       "      <th>sub1</th>\n",
       "      <th>sub2</th>\n",
       "      <th>sub3</th>\n",
       "      <th>sub4</th>\n",
       "      <th>sub5</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>94</td>\n",
       "      <td>20</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "      <td>91</td>\n",
       "      <td>305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>B</td>\n",
       "      <td>8</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>46</td>\n",
       "      <td>95</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>48</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>56</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>E</td>\n",
       "      <td>85</td>\n",
       "      <td>46</td>\n",
       "      <td>21</td>\n",
       "      <td>75</td>\n",
       "      <td>44</td>\n",
       "      <td>271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>F</td>\n",
       "      <td>86</td>\n",
       "      <td>68</td>\n",
       "      <td>78</td>\n",
       "      <td>99</td>\n",
       "      <td>56</td>\n",
       "      <td>387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>G</td>\n",
       "      <td>53</td>\n",
       "      <td>44</td>\n",
       "      <td>35</td>\n",
       "      <td>58</td>\n",
       "      <td>53</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>H</td>\n",
       "      <td>38</td>\n",
       "      <td>8</td>\n",
       "      <td>85</td>\n",
       "      <td>39</td>\n",
       "      <td>62</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>I</td>\n",
       "      <td>87</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>44</td>\n",
       "      <td>91</td>\n",
       "      <td>267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>J</td>\n",
       "      <td>92</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "      <td>11</td>\n",
       "      <td>51</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   roll name  sub1  sub2  sub3  sub4  sub5  total\n",
       "0     1    A    94    20    70    30    91    305\n",
       "1     2    B     8    72     1     5     8     94\n",
       "2     3    C    46    95    68    67    48    324\n",
       "3     4    D    56    11     4    16     1     88\n",
       "4     5    E    85    46    21    75    44    271\n",
       "5     6    F    86    68    78    99    56    387\n",
       "6     7    G    53    44    35    58    53    243\n",
       "7     8    H    38     8    85    39    62    232\n",
       "8     9    I    87    40     5    44    91    267\n",
       "9    10    J    92    41    40    11    51    235"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['total'] = df['sub1'] +  df['sub2'] +  df['sub3'] +  df['sub4'] + df['sub5']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "4875bf93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sub1    10\n",
       "sub2    10\n",
       "sub3    10\n",
       "sub4    10\n",
       "sub5    10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"sub1\",\"sub2\",\"sub3\",\"sub4\",\"sub5\"]].apply(len)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "4c935e45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5\n",
       "1    5\n",
       "2    5\n",
       "3    5\n",
       "4    5\n",
       "5    5\n",
       "6    5\n",
       "7    5\n",
       "8    5\n",
       "9    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"sub1\",\"sub2\",\"sub3\",\"sub4\",\"sub5\"]].apply(len, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "e9557c10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>roll</th>\n",
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       "      <th>sub4</th>\n",
       "      <th>sub5</th>\n",
       "      <th>total</th>\n",
       "      <th>toatl1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>30</td>\n",
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       "    </tr>\n",
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       "      <th>1</th>\n",
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       "      <td>B</td>\n",
       "      <td>8</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
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       "      <td>8</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>46</td>\n",
       "      <td>95</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>48</td>\n",
       "      <td>324</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>56</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>88</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>E</td>\n",
       "      <td>85</td>\n",
       "      <td>46</td>\n",
       "      <td>21</td>\n",
       "      <td>75</td>\n",
       "      <td>44</td>\n",
       "      <td>271</td>\n",
       "      <td>271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>F</td>\n",
       "      <td>86</td>\n",
       "      <td>68</td>\n",
       "      <td>78</td>\n",
       "      <td>99</td>\n",
       "      <td>56</td>\n",
       "      <td>387</td>\n",
       "      <td>387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>G</td>\n",
       "      <td>53</td>\n",
       "      <td>44</td>\n",
       "      <td>35</td>\n",
       "      <td>58</td>\n",
       "      <td>53</td>\n",
       "      <td>243</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>H</td>\n",
       "      <td>38</td>\n",
       "      <td>8</td>\n",
       "      <td>85</td>\n",
       "      <td>39</td>\n",
       "      <td>62</td>\n",
       "      <td>232</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>I</td>\n",
       "      <td>87</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>44</td>\n",
       "      <td>91</td>\n",
       "      <td>267</td>\n",
       "      <td>267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>J</td>\n",
       "      <td>92</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "      <td>11</td>\n",
       "      <td>51</td>\n",
       "      <td>235</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   roll name  sub1  sub2  sub3  sub4  sub5  total  toatl1\n",
       "0     1    A    94    20    70    30    91    305     305\n",
       "1     2    B     8    72     1     5     8     94      94\n",
       "2     3    C    46    95    68    67    48    324     324\n",
       "3     4    D    56    11     4    16     1     88      88\n",
       "4     5    E    85    46    21    75    44    271     271\n",
       "5     6    F    86    68    78    99    56    387     387\n",
       "6     7    G    53    44    35    58    53    243     243\n",
       "7     8    H    38     8    85    39    62    232     232\n",
       "8     9    I    87    40     5    44    91    267     267\n",
       "9    10    J    92    41    40    11    51    235     235"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['toatl1'] = df[[\"sub1\",\"sub2\",\"sub3\",\"sub4\",\"sub5\"]].apply(sum, axis=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "244ab1c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    61.0\n",
       "1    18.8\n",
       "2    64.8\n",
       "3    17.6\n",
       "4    54.2\n",
       "5    77.4\n",
       "6    48.6\n",
       "7    46.4\n",
       "8    53.4\n",
       "9    47.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"sub1\",\"sub2\",\"sub3\",\"sub4\",\"sub5\"]].apply(np.mean, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "c0555ef9",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "my_sum() missing 4 required positional arguments: 's2', 's3', 's4', and 's5'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mC:\\Users\\STUDEN~1\\AppData\\Local\\Temp/ipykernel_11416/2548322186.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0ms1\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0ms2\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0ms3\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0ms4\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0ms5\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'toatl1'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"sub1\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m\"sub2\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m\"sub3\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m\"sub4\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m\"sub5\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmy_sum\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36mapply\u001b[1;34m(self, func, axis, raw, result_type, args, **kwargs)\u001b[0m\n\u001b[0;32m   8738\u001b[0m             \u001b[0mkwargs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   8739\u001b[0m         )\n\u001b[1;32m-> 8740\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   8741\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   8742\u001b[0m     def applymap(\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\apply.py\u001b[0m in \u001b[0;36mapply\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    686\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_raw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    687\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 688\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_standard\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    689\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    690\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0magg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\apply.py\u001b[0m in \u001b[0;36mapply_standard\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    810\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    811\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mapply_standard\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 812\u001b[1;33m         \u001b[0mresults\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mres_index\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_series_generator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    813\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    814\u001b[0m         \u001b[1;31m# wrap results\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\apply.py\u001b[0m in \u001b[0;36mapply_series_generator\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    826\u001b[0m             \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mseries_gen\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    827\u001b[0m                 \u001b[1;31m# ignore SettingWithCopy here in case the user mutates\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 828\u001b[1;33m                 \u001b[0mresults\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    829\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresults\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mABCSeries\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    830\u001b[0m                     \u001b[1;31m# If we have a view on v, we need to make a copy because\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: my_sum() missing 4 required positional arguments: 's2', 's3', 's4', and 's5'"
     ]
    }
   ],
   "source": [
    "def my_sum(s1,s2,s3,s4,s5):\n",
    "    return s1 + s2 + s3 + s4 + s5\n",
    "\n",
    "df['toatl1'] = df[[\"sub1\",\"sub2\",\"sub3\",\"sub4\",\"sub5\"]].apply(my_sum, axis=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "5f2300b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3\n"
     ]
    }
   ],
   "source": [
    "s1,s2,s3 = (1,2,3)\n",
    "print(s1,s2,s3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "9d530828",
   "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>roll</th>\n",
       "      <th>name</th>\n",
       "      <th>sub1</th>\n",
       "      <th>sub2</th>\n",
       "      <th>sub3</th>\n",
       "      <th>sub4</th>\n",
       "      <th>sub5</th>\n",
       "      <th>total</th>\n",
       "      <th>toatl1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>94</td>\n",
       "      <td>20</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "      <td>91</td>\n",
       "      <td>305</td>\n",
       "      <td>305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>B</td>\n",
       "      <td>8</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>C</td>\n",
       "      <td>46</td>\n",
       "      <td>95</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>48</td>\n",
       "      <td>324</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>56</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>88</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>E</td>\n",
       "      <td>85</td>\n",
       "      <td>46</td>\n",
       "      <td>21</td>\n",
       "      <td>75</td>\n",
       "      <td>44</td>\n",
       "      <td>271</td>\n",
       "      <td>271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>F</td>\n",
       "      <td>86</td>\n",
       "      <td>68</td>\n",
       "      <td>78</td>\n",
       "      <td>99</td>\n",
       "      <td>56</td>\n",
       "      <td>387</td>\n",
       "      <td>387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>G</td>\n",
       "      <td>53</td>\n",
       "      <td>44</td>\n",
       "      <td>35</td>\n",
       "      <td>58</td>\n",
       "      <td>53</td>\n",
       "      <td>243</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>H</td>\n",
       "      <td>38</td>\n",
       "      <td>8</td>\n",
       "      <td>85</td>\n",
       "      <td>39</td>\n",
       "      <td>62</td>\n",
       "      <td>232</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>I</td>\n",
       "      <td>87</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>44</td>\n",
       "      <td>91</td>\n",
       "      <td>267</td>\n",
       "      <td>267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>J</td>\n",
       "      <td>92</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "      <td>11</td>\n",
       "      <td>51</td>\n",
       "      <td>235</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   roll name  sub1  sub2  sub3  sub4  sub5  total  toatl1\n",
       "0     1    A    94    20    70    30    91    305     305\n",
       "1     2    B     8    72     1     5     8     94      94\n",
       "2     3    C    46    95    68    67    48    324     324\n",
       "3     4    D    56    11     4    16     1     88      88\n",
       "4     5    E    85    46    21    75    44    271     271\n",
       "5     6    F    86    68    78    99    56    387     387\n",
       "6     7    G    53    44    35    58    53    243     243\n",
       "7     8    H    38     8    85    39    62    232     232\n",
       "8     9    I    87    40     5    44    91    267     267\n",
       "9    10    J    92    41    40    11    51    235     235"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['toatl1'] = df[[\"sub1\",\"sub2\",\"sub3\",\"sub4\",\"sub5\"]].apply(lambda x:my_sum(*x), axis=1)\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "03683b85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1    <NA>\n",
       "2       0\n",
       "dtype: Int64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series([\"a\", None, \"b\"], dtype=\"string\")\n",
    "s.str.count(\"a\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "3f298436",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "2    0\n",
       "dtype: Int64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.dropna().str.count(\"a\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "c3dc3e31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       a\n",
       "1    <NA>\n",
       "2       b\n",
       "dtype: string"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "2309c000",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'My name is St\\\\xe5le'\n",
      "b'My name is Stle'\n",
      "b'My name is St\\\\N{LATIN SMALL LETTER A WITH RING ABOVE}le'\n",
      "b'My name is St?le'\n",
      "b'My name is St&#229;le'\n"
     ]
    }
   ],
   "source": [
    "txt = \"My name is Ståle\"\n",
    "\n",
    "print(txt.encode(encoding=\"ascii\",errors=\"backslashreplace\"))\n",
    "print(txt.encode(encoding=\"ascii\",errors=\"ignore\"))\n",
    "print(txt.encode(encoding=\"ascii\",errors=\"namereplace\"))\n",
    "print(txt.encode(encoding=\"ascii\",errors=\"replace\"))\n",
    "print(txt.encode(encoding=\"ascii\",errors=\"xmlcharrefreplace\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c68782b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         12\n",
       "1       -$10\n",
       "2    $10,000\n",
       "dtype: string"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dollars = pd.Series([\"12\", \"-$10\", \"$10,000\"], dtype=\"string\")\n",
    "dollars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "95b69e86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         12\n",
       "1        -10\n",
       "2    $10,000\n",
       "dtype: string"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dollars.str.replace(r\"-\\$\", \"-\", regex=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "53aada33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         women 19\n",
       "1    abd  pakistan\n",
       "dtype: object"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = \"women 19\"\n",
    "y = r'\\bmen 1\\b'\n",
    "\n",
    "pd.Series([\"women 19\", \"abd men 1 pakistan\"]).str.replace(y,\"\", regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "2c187538",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    ajkdsf ak stage a1, roman, a3\n",
       "1               abd men 1 pakistan\n",
       "dtype: object"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg = r\"\\b[abc]([iv]+)\\b\"\n",
    "s = pd.Series([\"ajkdsf ak stage a1, aii, a3\", \"abd men 1 pakistan\"])\n",
    "\n",
    "s.replace(reg,'roman',regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "c65a425e",
   "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",
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <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>a</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0     1\n",
       "0     a     1\n",
       "1     b     2\n",
       "2  <NA>  <NA>\n",
       "3  <NA>  <NA>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(\n",
    "    [\"a1 hello\", \"b2 yy\", \"c3\",\"d4\"],\n",
    "    dtype=\"string\",\n",
    ").str.extract(r\"\\b([ab])(\\d)\\b\", expand=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "6b271562",
   "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>X</th>\n",
       "      <th>Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37</td>\n",
       "      <td>A</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>58</td>\n",
       "      <td>B</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23</td>\n",
       "      <td>B</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>59</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>88</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>45</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>96</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      X  Y\n",
       "0    37  A\n",
       "1    58  B\n",
       "2    23  B\n",
       "3     9  C\n",
       "4    59  C\n",
       "..   .. ..\n",
       "995  88  A\n",
       "996  45  C\n",
       "997  96  B\n",
       "998  10  A\n",
       "999   1  B\n",
       "\n",
       "[1000 rows x 2 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({\"X\":np.random.randint(1,100, 1000),\n",
    "                   \"Y\": [pd.Series([\"A\",\"B\",\"C\"]).sample(1).values[0] for i in range(1000)]\n",
    "                   })\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aaee20e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#   A B C\n",
    "#A  1 0 0\n",
    "#B  0 1 0\n",
    "#C  0 0 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "15b01dc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
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       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     A  B  C\n",
       "0    1  0  0\n",
       "1    0  1  0\n",
       "2    0  1  0\n",
       "3    0  0  1\n",
       "4    0  0  1\n",
       "..  .. .. ..\n",
       "995  1  0  0\n",
       "996  0  0  1\n",
       "997  0  1  0\n",
       "998  1  0  0\n",
       "999  0  1  0\n",
       "\n",
       "[1000 rows x 3 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.get_dummies(df1.Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "589743b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    B\n",
       "dtype: object"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " pd.Series([\"A\",\"B\",\"C\"]).sample(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaf7268d",
   "metadata": {},
   "source": [
    "# handle null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "02bdc5b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>one</th>\n",
       "      <th>two</th>\n",
       "      <th>three</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>1.143622</td>\n",
       "      <td>-0.819672</td>\n",
       "      <td>-0.155115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>-0.097118</td>\n",
       "      <td>1.159542</td>\n",
       "      <td>0.824832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>0.383128</td>\n",
       "      <td>-1.235158</td>\n",
       "      <td>0.982446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.523330</td>\n",
       "      <td>-0.021055</td>\n",
       "      <td>0.187879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.809041</td>\n",
       "      <td>0.776752</td>\n",
       "      <td>0.425965</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        one       two     three\n",
       "a  1.143622 -0.819672 -0.155115\n",
       "c -0.097118  1.159542  0.824832\n",
       "e  0.383128 -1.235158  0.982446\n",
       "f  0.523330 -0.021055  0.187879\n",
       "h  0.809041  0.776752  0.425965"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    np.random.randn(5, 3),\n",
    "    index=[\"a\", \"c\", \"e\", \"f\", \"h\"],\n",
    "    columns=[\"one\", \"two\", \"three\"],\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "ec409464",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"four\"] = \"bar\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "f6272db0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>four</th>\n",
       "      <th>five</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>1.143622</td>\n",
       "      <td>-0.819672</td>\n",
       "      <td>-0.155115</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>-0.097118</td>\n",
       "      <td>1.159542</td>\n",
       "      <td>0.824832</td>\n",
       "      <td>bar</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>0.383128</td>\n",
       "      <td>-1.235158</td>\n",
       "      <td>0.982446</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.523330</td>\n",
       "      <td>-0.021055</td>\n",
       "      <td>0.187879</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.809041</td>\n",
       "      <td>0.776752</td>\n",
       "      <td>0.425965</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        one       two     three four   five\n",
       "a  1.143622 -0.819672 -0.155115  bar   True\n",
       "c -0.097118  1.159542  0.824832  bar  False\n",
       "e  0.383128 -1.235158  0.982446  bar   True\n",
       "f  0.523330 -0.021055  0.187879  bar   True\n",
       "h  0.809041  0.776752  0.425965  bar   True"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"five\"] = df[\"one\"] > 0\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "1fd53cbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "      <td>-0.155115</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>-0.097118</td>\n",
       "      <td>1.159542</td>\n",
       "      <td>0.824832</td>\n",
       "      <td>bar</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>0.383128</td>\n",
       "      <td>-1.235158</td>\n",
       "      <td>0.982446</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.523330</td>\n",
       "      <td>-0.021055</td>\n",
       "      <td>0.187879</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.809041</td>\n",
       "      <td>0.776752</td>\n",
       "      <td>0.425965</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        one       two     three four   five\n",
       "a  1.143622 -0.819672 -0.155115  bar   True\n",
       "b       NaN       NaN       NaN  NaN    NaN\n",
       "c -0.097118  1.159542  0.824832  bar  False\n",
       "d       NaN       NaN       NaN  NaN    NaN\n",
       "e  0.383128 -1.235158  0.982446  bar   True\n",
       "f  0.523330 -0.021055  0.187879  bar   True\n",
       "g       NaN       NaN       NaN  NaN    NaN\n",
       "h  0.809041  0.776752  0.425965  bar   True"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df2 = df.reindex([\"a\", \"b\", \"c\", \"d\", \"e\", \"f\", \"g\", \"h\"])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "19e3538f",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
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   "execution_count": 127,
   "id": "de909ac0",
   "metadata": {},
   "outputs": [
    {
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       "a     True\n",
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       "g    False\n",
       "h     True\n",
       "Name: four, dtype: bool"
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     "execution_count": 127,
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  {
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   "execution_count": 131,
   "id": "a20a66b5",
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   "outputs": [
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  {
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       "      <td>bar</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>0.383128</td>\n",
       "      <td>-1.235158</td>\n",
       "      <td>0.982446</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.523330</td>\n",
       "      <td>-0.021055</td>\n",
       "      <td>0.187879</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.809041</td>\n",
       "      <td>0.776752</td>\n",
       "      <td>0.425965</td>\n",
       "      <td>bar</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        one       two     three four   five\n",
       "a  1.143622 -0.819672 -0.155115  bar   True\n",
       "b       NaN       NaN       NaN  NaN    NaN\n",
       "c -0.097118  1.159542  0.824832  bar  False\n",
       "d       NaN       NaN       NaN  NaN    NaN\n",
       "e  0.383128 -1.235158  0.982446  bar   True\n",
       "f  0.523330 -0.021055  0.187879  bar   True\n",
       "g       NaN       NaN       NaN  NaN    NaN\n",
       "h  0.809041  0.776752  0.425965  bar   True"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df2\n",
    "# df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ee8f752",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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