Feature Construction _ Feature Splitting.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7bbb9cd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "66f575eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.linear_model import LogisticRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "36638014",
   "metadata": {
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   },
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Survived</th>\n",
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       "      <td>0</td>\n",
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       "      <th>120</th>\n",
       "      <td>21.0</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>30.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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      "text/plain": [
       "      Age  Pclass  SibSp  Parch  Survived\n",
       "481   NaN       2      0      0         0\n",
       "120  21.0       2      2      0         0\n",
       "668  43.0       3      0      0         0\n",
       "614  35.0       3      0      0         0\n",
       "798  30.0       3      0      0         0"
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     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"(Titanic)train.csv\")[['Age','Pclass','SibSp','Parch','Survived']]\n",
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0e80c969",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(inplace=True)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d05f7f58",
   "metadata": {
    "scrolled": true
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       "      <th>Pclass</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Survived</th>\n",
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       "      <th>827</th>\n",
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       "      <td>36.0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>9.0</td>\n",
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       "      <td>1</td>\n",
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       "      <th>756</th>\n",
       "      <td>28.0</td>\n",
       "      <td>3</td>\n",
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      "text/plain": [
       "      Age  Pclass  SibSp  Parch  Survived\n",
       "827   1.0       2      0      2         1\n",
       "265  36.0       2      0      0         0\n",
       "147   9.0       3      2      2         0\n",
       "489   9.0       3      1      1         1\n",
       "756  28.0       3      0      0         0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bc9e8b44",
   "metadata": {},
   "outputs": [],
   "source": [
    "X= df.iloc[:,0:4]\n",
    "y= df.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5ad48869",
   "metadata": {},
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
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       "  </thead>\n",
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       "      <th>203</th>\n",
       "      <td>45.5</td>\n",
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       "      <td>0</td>\n",
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       "      <th>434</th>\n",
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       "      <th>56</th>\n",
       "      <td>21.0</td>\n",
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       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>5.0</td>\n",
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      "text/plain": [
       "      Age  Pclass  SibSp  Parch\n",
       "203  45.5       3      0      0\n",
       "434  50.0       1      1      0\n",
       "56   21.0       2      0      0\n",
       "448   5.0       3      2      1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
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   ],
   "source": [
    "X.sample(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9f2f237d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6933333333333332"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(cross_val_score(LogisticRegression(),X,y,scoring='accuracy',cv=20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3019b0d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# from sklearn.model_selection import train_test_split\n",
    "# X_train,X_test,Y_train,Y_test =  train_test_split(X,y,test_size=0.2,random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a7f5b6c",
   "metadata": {},
   "source": [
    "## Applying feature construction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d6188dc2",
   "metadata": {},
   "outputs": [],
   "source": [
    "X['Family_size'] = X['SibSp']+X['Parch'] + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "30d2b275",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Family_size</th>\n",
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       "      <th>474</th>\n",
       "      <td>22.0</td>\n",
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       "      <td>1</td>\n",
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       "      <th>236</th>\n",
       "      <td>44.0</td>\n",
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       "      <td>0</td>\n",
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       "      <th>519</th>\n",
       "      <td>32.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>698</th>\n",
       "      <td>49.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>16.0</td>\n",
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       "      <th>483</th>\n",
       "      <td>63.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "      Age  Pclass  SibSp  Parch  Family_size\n",
       "474  22.0       3      0      0            1\n",
       "713  29.0       3      0      0            1\n",
       "236  44.0       2      1      0            2\n",
       "519  32.0       3      0      0            1\n",
       "698  49.0       1      1      1            3\n",
       "504  16.0       1      0      0            1\n",
       "483  63.0       3      0      0            1"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.sample(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cfb6302a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def myFunc(num):\n",
    "    if num == 1:\n",
    "        #alone\n",
    "        return 0\n",
    "    elif num == 2:\n",
    "        #small family\n",
    "        return 1\n",
    "    else:\n",
    "        #large family\n",
    "        return 2\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d75f0ccc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
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     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myFunc(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b19a6fc8",
   "metadata": {},
   "outputs": [],
   "source": [
    "X['Family_type'] = X['Family_size'].apply(myFunc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "05477b76",
   "metadata": {},
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       "      <th>794</th>\n",
       "      <td>25.0</td>\n",
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       "      <td>18.0</td>\n",
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       "      <th>663</th>\n",
       "      <td>36.0</td>\n",
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       "      <td>0</td>\n",
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      "text/plain": [
       "      Age  Pclass  SibSp  Parch  Family_size  Family_type\n",
       "794  25.0       3      0      0            1            0\n",
       "675  18.0       3      0      0            1            0\n",
       "400  39.0       3      0      0            1            0\n",
       "203  45.5       3      0      0            1            0\n",
       "663  36.0       3      0      0            1            0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "58a6f0d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "X.drop(columns=['SibSp','Parch','Family_size'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "67f65856",
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>34.0</td>\n",
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       "      <th>489</th>\n",
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       "      <th>50</th>\n",
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      "text/plain": [
       "      Age  Pclass  Family_type\n",
       "390  36.0       1            2\n",
       "516  34.0       2            0\n",
       "489   9.0       3            2\n",
       "400  39.0       3            0\n",
       "50    7.0       3            2"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "41faf5ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7088492063492063"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(cross_val_score(LogisticRegression(),X,y,scoring='accuracy',cv=20))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "720da818",
   "metadata": {},
   "source": [
    "## Feature Splitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0a6b5d71",
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>356</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Vanden Steen, Mr. Leo Peter</td>\n",
       "      <td>male</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>345783</td>\n",
       "      <td>9.500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>537</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Butt, Major. Archibald Willingham</td>\n",
       "      <td>male</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113050</td>\n",
       "      <td>26.550</td>\n",
       "      <td>B38</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>117</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Connors, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>70.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370369</td>\n",
       "      <td>7.750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>487</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>19943</td>\n",
       "      <td>90.000</td>\n",
       "      <td>C93</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>509</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Olsen, Mr. Henry Margido</td>\n",
       "      <td>male</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>C 4001</td>\n",
       "      <td>22.525</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "355          356         0       3   \n",
       "536          537         0       1   \n",
       "116          117         0       3   \n",
       "486          487         1       1   \n",
       "508          509         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "355                      Vanden Steen, Mr. Leo Peter    male  28.0      0   \n",
       "536                Butt, Major. Archibald Willingham    male  45.0      0   \n",
       "116                             Connors, Mr. Patrick    male  70.5      0   \n",
       "486  Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)  female  35.0      1   \n",
       "508                         Olsen, Mr. Henry Margido    male  28.0      0   \n",
       "\n",
       "     Parch  Ticket    Fare Cabin Embarked  \n",
       "355      0  345783   9.500   NaN        S  \n",
       "536      0  113050  26.550   B38        S  \n",
       "116      0  370369   7.750   NaN        Q  \n",
       "486      0   19943  90.000   C93        S  \n",
       "508      0  C 4001  22.525   NaN        S  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"(Titanic)train.csv\")\n",
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b944e9e2",
   "metadata": {
    "scrolled": true
   },
   "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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "66678a29",
   "metadata": {
    "scrolled": true
   },
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Braund</td>\n",
       "      <td>Mr. Owen Harris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cumings</td>\n",
       "      <td>Mrs. John Bradley (Florence Briggs Thayer)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Heikkinen</td>\n",
       "      <td>Miss. Laina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Futrelle</td>\n",
       "      <td>Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Allen</td>\n",
       "      <td>Mr. William Henry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>Montvila</td>\n",
       "      <td>Rev. Juozas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>Graham</td>\n",
       "      <td>Miss. Margaret Edith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>Johnston</td>\n",
       "      <td>Miss. Catherine Helen \"Carrie\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>Behr</td>\n",
       "      <td>Mr. Karl Howell</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>Dooley</td>\n",
       "      <td>Mr. Patrick</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             0                                            1\n",
       "0       Braund                              Mr. Owen Harris\n",
       "1      Cumings   Mrs. John Bradley (Florence Briggs Thayer)\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",
       "\n",
       "[891 rows x 2 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Name'].str.split(',',expand =True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "78592315",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                  Mr. Owen Harris\n",
       "1       Mrs. John Bradley (Florence Briggs Thayer)\n",
       "2                                      Miss. Laina\n",
       "3               Mrs. Jacques Heath (Lily May Peel)\n",
       "4                                Mr. William Henry\n",
       "                          ...                     \n",
       "886                                    Rev. Juozas\n",
       "887                           Miss. Margaret Edith\n",
       "888                 Miss. Catherine Helen \"Carrie\"\n",
       "889                                Mr. Karl Howell\n",
       "890                                    Mr. Patrick\n",
       "Name: 1, Length: 891, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Name'].str.split(',',expand =True)[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "14237066",
   "metadata": {
    "scrolled": true
   },
   "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",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mr</td>\n",
       "      <td>Owen Harris</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mrs</td>\n",
       "      <td>John Bradley (Florence Briggs Thayer)</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Miss</td>\n",
       "      <td>Laina</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mrs</td>\n",
       "      <td>Jacques Heath (Lily May Peel)</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mr</td>\n",
       "      <td>William Henry</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>Rev</td>\n",
       "      <td>Juozas</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>Miss</td>\n",
       "      <td>Margaret Edith</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>Miss</td>\n",
       "      <td>Catherine Helen \"Carrie\"</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>Mr</td>\n",
       "      <td>Karl Howell</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>Mr</td>\n",
       "      <td>Patrick</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         0                                       1     2\n",
       "0       Mr                             Owen Harris  None\n",
       "1      Mrs   John Bradley (Florence Briggs Thayer)  None\n",
       "2     Miss                                   Laina  None\n",
       "3      Mrs           Jacques Heath (Lily May Peel)  None\n",
       "4       Mr                           William Henry  None\n",
       "..     ...                                     ...   ...\n",
       "886    Rev                                  Juozas  None\n",
       "887   Miss                          Margaret Edith  None\n",
       "888   Miss                Catherine Helen \"Carrie\"  None\n",
       "889     Mr                             Karl Howell  None\n",
       "890     Mr                                 Patrick  None\n",
       "\n",
       "[891 rows x 3 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Name'].str.split(',',expand =True)[1].str.split('.',expand = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f5c9bba2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         Mr\n",
       "1        Mrs\n",
       "2       Miss\n",
       "3        Mrs\n",
       "4         Mr\n",
       "       ...  \n",
       "886      Rev\n",
       "887     Miss\n",
       "888     Miss\n",
       "889       Mr\n",
       "890       Mr\n",
       "Name: 0, Length: 891, dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Name'].str.split(',',expand =True)[1].str.split('.',expand = True)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d596dcb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Title'] = df['Name'].str.split(',',expand =True)[1].str.split('.',expand = True)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "276cf09a",
   "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>Title</th>\n",
       "      <th>Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mr</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mrs</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Miss</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mrs</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mr</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>Rev</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>Miss</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>Miss</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>Mr</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>Mr</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>891 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Title                                               Name\n",
       "0       Mr                            Braund, Mr. Owen Harris\n",
       "1      Mrs  Cumings, Mrs. John Bradley (Florence Briggs Th...\n",
       "2     Miss                             Heikkinen, Miss. Laina\n",
       "3      Mrs       Futrelle, Mrs. Jacques Heath (Lily May Peel)\n",
       "4       Mr                           Allen, Mr. William Henry\n",
       "..     ...                                                ...\n",
       "886    Rev                              Montvila, Rev. Juozas\n",
       "887   Miss                       Graham, Miss. Margaret Edith\n",
       "888   Miss           Johnston, Miss. Catherine Helen \"Carrie\"\n",
       "889     Mr                              Behr, Mr. Karl Howell\n",
       "890     Mr                                Dooley, Mr. Patrick\n",
       "\n",
       "[891 rows x 2 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Title','Name']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a08557e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Title\n",
       " the Countess    1.000000\n",
       " Mlle            1.000000\n",
       " Sir             1.000000\n",
       " Ms              1.000000\n",
       " Lady            1.000000\n",
       " Mme             1.000000\n",
       " Mrs             0.792000\n",
       " Miss            0.697802\n",
       " Master          0.575000\n",
       " Col             0.500000\n",
       " Major           0.500000\n",
       " Dr              0.428571\n",
       " Mr              0.156673\n",
       " Jonkheer        0.000000\n",
       " Rev             0.000000\n",
       " Don             0.000000\n",
       " Capt            0.000000\n",
       "Name: Survived, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.groupby('Title').mean()['Survived']).sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "bac96dfe",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\nagam\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:1732: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_single_block(indexer, value, name)\n"
     ]
    }
   ],
   "source": [
    "df['Is_married']=0\n",
    "df['Is_married'].loc[df['Title'] == 'Mrs'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "780f17f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      0\n",
       "1      0\n",
       "2      0\n",
       "3      0\n",
       "4      0\n",
       "      ..\n",
       "886    0\n",
       "887    0\n",
       "888    0\n",
       "889    0\n",
       "890    0\n",
       "Name: Is_married, Length: 891, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Is_married']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20bcecf0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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