titanic-prediction.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/drsanj/titanic-prediction?scriptVersionId=127362345\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown"},{"cell_type":"code","execution_count":1,"id":"1bd3d58a","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2023-04-26T19:11:56.070345Z","iopub.status.busy":"2023-04-26T19:11:56.069308Z","iopub.status.idle":"2023-04-26T19:11:56.087254Z","shell.execute_reply":"2023-04-26T19:11:56.085898Z"},"papermill":{"duration":0.037134,"end_time":"2023-04-26T19:11:56.089982","exception":false,"start_time":"2023-04-26T19:11:56.052848","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["/kaggle/input/titanic/train.csv\n","/kaggle/input/titanic/test.csv\n","/kaggle/input/titanic/gender_submission.csv\n"]}],"source":["# This Python 3 environment comes with many helpful analytics libraries installed\n","# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n","# For example, here's several helpful packages to load\n","\n","import numpy as np # linear algebra\n","import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n","\n","# Input data files are available in the read-only \"../input/\" directory\n","# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n","\n","import os\n","for dirname, _, filenames in os.walk('/kaggle/input'):\n","    for filename in filenames:\n","        print(os.path.join(dirname, filename))\n","\n","# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n","# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"]},{"cell_type":"code","execution_count":2,"id":"bdfa7259","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.117938Z","iopub.status.busy":"2023-04-26T19:11:56.116991Z","iopub.status.idle":"2023-04-26T19:11:56.176677Z","shell.execute_reply":"2023-04-26T19:11:56.175294Z"},"papermill":{"duration":0.076745,"end_time":"2023-04-26T19:11:56.179513","exception":false,"start_time":"2023-04-26T19:11:56.102768","status":"completed"},"tags":[]},"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>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","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>886</th>\n","      <td>887</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>Montvila, Rev. Juozas</td>\n","      <td>male</td>\n","      <td>27.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>211536</td>\n","      <td>13.0000</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>887</th>\n","      <td>888</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Graham, Miss. Margaret Edith</td>\n","      <td>female</td>\n","      <td>19.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>112053</td>\n","      <td>30.0000</td>\n","      <td>B42</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>888</th>\n","      <td>889</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n","      <td>female</td>\n","      <td>NaN</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>W./C. 6607</td>\n","      <td>23.4500</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>889</th>\n","      <td>890</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Behr, Mr. Karl Howell</td>\n","      <td>male</td>\n","      <td>26.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>111369</td>\n","      <td>30.0000</td>\n","      <td>C148</td>\n","      <td>C</td>\n","    </tr>\n","    <tr>\n","      <th>890</th>\n","      <td>891</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Dooley, Mr. Patrick</td>\n","      <td>male</td>\n","      <td>32.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>370376</td>\n","      <td>7.7500</td>\n","      <td>NaN</td>\n","      <td>Q</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>891 rows × 12 columns</p>\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","886          887         0       2   \n","887          888         1       1   \n","888          889         0       3   \n","889          890         1       1   \n","890          891         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","886                              Montvila, Rev. Juozas    male  27.0      0   \n","887                       Graham, Miss. Margaret Edith  female  19.0      0   \n","888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n","889                              Behr, Mr. Karl Howell    male  26.0      0   \n","890                                Dooley, Mr. Patrick    male  32.0      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  \n","..     ...               ...      ...   ...      ...  \n","886      0            211536  13.0000   NaN        S  \n","887      0            112053  30.0000   B42        S  \n","888      2        W./C. 6607  23.4500   NaN        S  \n","889      0            111369  30.0000  C148        C  \n","890      0            370376   7.7500   NaN        Q  \n","\n","[891 rows x 12 columns]"]},"execution_count":2,"metadata":{},"output_type":"execute_result"}],"source":["train=pd.read_csv('/kaggle/input/titanic/train.csv')\n","train"]},{"cell_type":"code","execution_count":3,"id":"fca115db","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.208485Z","iopub.status.busy":"2023-04-26T19:11:56.207316Z","iopub.status.idle":"2023-04-26T19:11:56.241143Z","shell.execute_reply":"2023-04-26T19:11:56.240122Z"},"papermill":{"duration":0.050962,"end_time":"2023-04-26T19:11:56.243663","exception":false,"start_time":"2023-04-26T19:11:56.192701","status":"completed"},"tags":[]},"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>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>892</td>\n","      <td>3</td>\n","      <td>Kelly, Mr. James</td>\n","      <td>male</td>\n","      <td>34.5</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>330911</td>\n","      <td>7.8292</td>\n","      <td>NaN</td>\n","      <td>Q</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>893</td>\n","      <td>3</td>\n","      <td>Wilkes, Mrs. James (Ellen Needs)</td>\n","      <td>female</td>\n","      <td>47.0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>363272</td>\n","      <td>7.0000</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>894</td>\n","      <td>2</td>\n","      <td>Myles, Mr. Thomas Francis</td>\n","      <td>male</td>\n","      <td>62.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>240276</td>\n","      <td>9.6875</td>\n","      <td>NaN</td>\n","      <td>Q</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>895</td>\n","      <td>3</td>\n","      <td>Wirz, Mr. Albert</td>\n","      <td>male</td>\n","      <td>27.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>315154</td>\n","      <td>8.6625</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>896</td>\n","      <td>3</td>\n","      <td>Hirvonen, Mrs. Alexander (Helga E Lindqvist)</td>\n","      <td>female</td>\n","      <td>22.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>3101298</td>\n","      <td>12.2875</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>413</th>\n","      <td>1305</td>\n","      <td>3</td>\n","      <td>Spector, Mr. Woolf</td>\n","      <td>male</td>\n","      <td>NaN</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>A.5. 3236</td>\n","      <td>8.0500</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>414</th>\n","      <td>1306</td>\n","      <td>1</td>\n","      <td>Oliva y Ocana, Dona. Fermina</td>\n","      <td>female</td>\n","      <td>39.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>PC 17758</td>\n","      <td>108.9000</td>\n","      <td>C105</td>\n","      <td>C</td>\n","    </tr>\n","    <tr>\n","      <th>415</th>\n","      <td>1307</td>\n","      <td>3</td>\n","      <td>Saether, Mr. Simon Sivertsen</td>\n","      <td>male</td>\n","      <td>38.5</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>SOTON/O.Q. 3101262</td>\n","      <td>7.2500</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>416</th>\n","      <td>1308</td>\n","      <td>3</td>\n","      <td>Ware, Mr. Frederick</td>\n","      <td>male</td>\n","      <td>NaN</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>359309</td>\n","      <td>8.0500</td>\n","      <td>NaN</td>\n","      <td>S</td>\n","    </tr>\n","    <tr>\n","      <th>417</th>\n","      <td>1309</td>\n","      <td>3</td>\n","      <td>Peter, Master. Michael J</td>\n","      <td>male</td>\n","      <td>NaN</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>2668</td>\n","      <td>22.3583</td>\n","      <td>NaN</td>\n","      <td>C</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>418 rows × 11 columns</p>\n","</div>"],"text/plain":["     PassengerId  Pclass                                          Name  \\\n","0            892       3                              Kelly, Mr. James   \n","1            893       3              Wilkes, Mrs. James (Ellen Needs)   \n","2            894       2                     Myles, Mr. Thomas Francis   \n","3            895       3                              Wirz, Mr. Albert   \n","4            896       3  Hirvonen, Mrs. Alexander (Helga E Lindqvist)   \n","..           ...     ...                                           ...   \n","413         1305       3                            Spector, Mr. Woolf   \n","414         1306       1                  Oliva y Ocana, Dona. Fermina   \n","415         1307       3                  Saether, Mr. Simon Sivertsen   \n","416         1308       3                           Ware, Mr. Frederick   \n","417         1309       3                      Peter, Master. Michael J   \n","\n","        Sex   Age  SibSp  Parch              Ticket      Fare Cabin Embarked  \n","0      male  34.5      0      0              330911    7.8292   NaN        Q  \n","1    female  47.0      1      0              363272    7.0000   NaN        S  \n","2      male  62.0      0      0              240276    9.6875   NaN        Q  \n","3      male  27.0      0      0              315154    8.6625   NaN        S  \n","4    female  22.0      1      1             3101298   12.2875   NaN        S  \n","..      ...   ...    ...    ...                 ...       ...   ...      ...  \n","413    male   NaN      0      0           A.5. 3236    8.0500   NaN        S  \n","414  female  39.0      0      0            PC 17758  108.9000  C105        C  \n","415    male  38.5      0      0  SOTON/O.Q. 3101262    7.2500   NaN        S  \n","416    male   NaN      0      0              359309    8.0500   NaN        S  \n","417    male   NaN      1      1                2668   22.3583   NaN        C  \n","\n","[418 rows x 11 columns]"]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"source":["test=pd.read_csv('/kaggle/input/titanic/test.csv')\n","test"]},{"cell_type":"code","execution_count":4,"id":"9fc0c950","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.274555Z","iopub.status.busy":"2023-04-26T19:11:56.274046Z","iopub.status.idle":"2023-04-26T19:11:56.29208Z","shell.execute_reply":"2023-04-26T19:11:56.291103Z"},"papermill":{"duration":0.035957,"end_time":"2023-04-26T19:11:56.294522","exception":false,"start_time":"2023-04-26T19:11:56.258565","status":"completed"},"tags":[]},"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","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>892</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>893</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>894</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>895</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>896</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>413</th>\n","      <td>1305</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>414</th>\n","      <td>1306</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>415</th>\n","      <td>1307</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>416</th>\n","      <td>1308</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>417</th>\n","      <td>1309</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>418 rows × 2 columns</p>\n","</div>"],"text/plain":["     PassengerId  Survived\n","0            892         0\n","1            893         1\n","2            894         0\n","3            895         0\n","4            896         1\n","..           ...       ...\n","413         1305         0\n","414         1306         1\n","415         1307         0\n","416         1308         0\n","417         1309         0\n","\n","[418 rows x 2 columns]"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["gender_submission=pd.read_csv('/kaggle/input/titanic/gender_submission.csv')\n","gender_submission"]},{"cell_type":"code","execution_count":5,"id":"870083bc","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.324377Z","iopub.status.busy":"2023-04-26T19:11:56.323918Z","iopub.status.idle":"2023-04-26T19:11:56.333103Z","shell.execute_reply":"2023-04-26T19:11:56.332128Z"},"papermill":{"duration":0.027098,"end_time":"2023-04-26T19:11:56.335501","exception":false,"start_time":"2023-04-26T19:11:56.308403","status":"completed"},"tags":[]},"outputs":[],"source":["train.drop(columns=['Cabin'],inplace=True)\n","test.drop(columns=['Cabin'],inplace=True)"]},{"cell_type":"code","execution_count":6,"id":"55581e16","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.36599Z","iopub.status.busy":"2023-04-26T19:11:56.364752Z","iopub.status.idle":"2023-04-26T19:11:56.376739Z","shell.execute_reply":"2023-04-26T19:11:56.375508Z"},"papermill":{"duration":0.030019,"end_time":"2023-04-26T19:11:56.379435","exception":false,"start_time":"2023-04-26T19:11:56.349416","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["PassengerId      0\n","Survived         0\n","Pclass           0\n","Name             0\n","Sex              0\n","Age            177\n","SibSp            0\n","Parch            0\n","Ticket           0\n","Fare             0\n","Embarked         2\n","dtype: int64"]},"execution_count":6,"metadata":{},"output_type":"execute_result"}],"source":["train.isnull().sum()"]},{"cell_type":"code","execution_count":7,"id":"1bc88aa6","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.409245Z","iopub.status.busy":"2023-04-26T19:11:56.408745Z","iopub.status.idle":"2023-04-26T19:11:56.419533Z","shell.execute_reply":"2023-04-26T19:11:56.418538Z"},"papermill":{"duration":0.028555,"end_time":"2023-04-26T19:11:56.421761","exception":false,"start_time":"2023-04-26T19:11:56.393206","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["PassengerId     0\n","Pclass          0\n","Name            0\n","Sex             0\n","Age            86\n","SibSp           0\n","Parch           0\n","Ticket          0\n","Fare            1\n","Embarked        0\n","dtype: int64"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["test.isnull().sum()"]},{"cell_type":"code","execution_count":8,"id":"360b7f06","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.451517Z","iopub.status.busy":"2023-04-26T19:11:56.45107Z","iopub.status.idle":"2023-04-26T19:11:56.46626Z","shell.execute_reply":"2023-04-26T19:11:56.464938Z"},"papermill":{"duration":0.033418,"end_time":"2023-04-26T19:11:56.469049","exception":false,"start_time":"2023-04-26T19:11:56.435631","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["S    644\n","C    168\n","Q     77\n","Name: Embarked, dtype: int64"]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["train['Embarked'].value_counts()"]},{"cell_type":"code","execution_count":9,"id":"023bad55","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.498971Z","iopub.status.busy":"2023-04-26T19:11:56.498465Z","iopub.status.idle":"2023-04-26T19:11:56.505723Z","shell.execute_reply":"2023-04-26T19:11:56.504407Z"},"papermill":{"duration":0.025645,"end_time":"2023-04-26T19:11:56.508496","exception":false,"start_time":"2023-04-26T19:11:56.482851","status":"completed"},"tags":[]},"outputs":[],"source":["train['Embarked'].fillna('S',inplace=True)"]},{"cell_type":"code","execution_count":10,"id":"8e0436fa","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.539838Z","iopub.status.busy":"2023-04-26T19:11:56.539335Z","iopub.status.idle":"2023-04-26T19:11:56.547282Z","shell.execute_reply":"2023-04-26T19:11:56.54585Z"},"papermill":{"duration":0.026726,"end_time":"2023-04-26T19:11:56.550082","exception":false,"start_time":"2023-04-26T19:11:56.523356","status":"completed"},"tags":[]},"outputs":[],"source":["test['Fare'].fillna(test['Fare'].mean(),inplace=True)"]},{"cell_type":"code","execution_count":11,"id":"85866873","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:56.580685Z","iopub.status.busy":"2023-04-26T19:11:56.580176Z","iopub.status.idle":"2023-04-26T19:11:58.15628Z","shell.execute_reply":"2023-04-26T19:11:58.15482Z"},"papermill":{"duration":1.59473,"end_time":"2023-04-26T19:11:58.159011","exception":false,"start_time":"2023-04-26T19:11:56.564281","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:xlabel='Age', ylabel='Count'>"]},"execution_count":11,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import seaborn as sns\n","sns.histplot(train['Age'])"]},{"cell_type":"code","execution_count":12,"id":"cb713de6","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.191271Z","iopub.status.busy":"2023-04-26T19:11:58.190095Z","iopub.status.idle":"2023-04-26T19:11:58.200084Z","shell.execute_reply":"2023-04-26T19:11:58.198743Z"},"papermill":{"duration":0.028789,"end_time":"2023-04-26T19:11:58.202847","exception":false,"start_time":"2023-04-26T19:11:58.174058","status":"completed"},"tags":[]},"outputs":[],"source":["train_age=np.random.randint(train['Age'].mean()-train['Age'].std(),train['Age'].mean()+train['Age'].std(),177)"]},{"cell_type":"code","execution_count":13,"id":"6ec4fdd4","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.235746Z","iopub.status.busy":"2023-04-26T19:11:58.234736Z","iopub.status.idle":"2023-04-26T19:11:58.245488Z","shell.execute_reply":"2023-04-26T19:11:58.243988Z"},"papermill":{"duration":0.030533,"end_time":"2023-04-26T19:11:58.248487","exception":false,"start_time":"2023-04-26T19:11:58.217954","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["array([20, 25, 16, 36, 36, 18, 25, 23, 43, 33, 28, 43, 32, 38, 32, 24, 24,\n","       37, 17, 43, 23, 41, 43, 20, 20, 17, 28, 19, 32, 20, 23, 33, 35, 16,\n","       18, 27, 32, 29, 32, 33, 16, 39, 18, 43, 24, 21, 43, 34, 16, 43, 16,\n","       33, 18, 40, 28, 27, 26, 16, 21, 23, 28, 28, 23, 22, 20, 19, 35, 34,\n","       42, 32, 36, 38, 36, 26, 42, 21, 36, 42, 30, 18, 39, 23, 22, 25, 26,\n","       28])"]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["test_age=np.random.randint(test['Age'].mean()-test['Age'].std(),test['Age'].mean()+test['Age'].std(),86)\n","test_age"]},{"cell_type":"code","execution_count":14,"id":"88a584d1","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.282293Z","iopub.status.busy":"2023-04-26T19:11:58.281103Z","iopub.status.idle":"2023-04-26T19:11:58.292489Z","shell.execute_reply":"2023-04-26T19:11:58.291025Z"},"papermill":{"duration":0.031568,"end_time":"2023-04-26T19:11:58.295134","exception":false,"start_time":"2023-04-26T19:11:58.263566","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: 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","  \"\"\"Entry point for launching an IPython kernel.\n"]}],"source":["train['Age'][train['Age'].isnull()]=train_age"]},{"cell_type":"code","execution_count":15,"id":"23b6696b","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.328506Z","iopub.status.busy":"2023-04-26T19:11:58.327638Z","iopub.status.idle":"2023-04-26T19:11:58.33845Z","shell.execute_reply":"2023-04-26T19:11:58.336481Z"},"papermill":{"duration":0.03061,"end_time":"2023-04-26T19:11:58.340983","exception":false,"start_time":"2023-04-26T19:11:58.310373","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: 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","  \"\"\"Entry point for launching an IPython kernel.\n"]}],"source":["test['Age'][test['Age'].isnull()]=test_age"]},{"cell_type":"code","execution_count":16,"id":"d3003f7a","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.373101Z","iopub.status.busy":"2023-04-26T19:11:58.372119Z","iopub.status.idle":"2023-04-26T19:11:58.38544Z","shell.execute_reply":"2023-04-26T19:11:58.384077Z"},"papermill":{"duration":0.032254,"end_time":"2023-04-26T19:11:58.388066","exception":false,"start_time":"2023-04-26T19:11:58.355812","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Pclass\n","1    0.629630\n","2    0.472826\n","3    0.242363\n","Name: Survived, dtype: float64"]},"execution_count":16,"metadata":{},"output_type":"execute_result"}],"source":["train.groupby(['Pclass'])['Survived'].mean()"]},{"cell_type":"markdown","id":"0dcbc71f","metadata":{"papermill":{"duration":0.01437,"end_time":"2023-04-26T19:11:58.417242","exception":false,"start_time":"2023-04-26T19:11:58.402872","status":"completed"},"tags":[]},"source":[]},{"cell_type":"code","execution_count":17,"id":"566434be","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.450346Z","iopub.status.busy":"2023-04-26T19:11:58.449327Z","iopub.status.idle":"2023-04-26T19:11:58.460495Z","shell.execute_reply":"2023-04-26T19:11:58.459266Z"},"papermill":{"duration":0.030252,"end_time":"2023-04-26T19:11:58.463106","exception":false,"start_time":"2023-04-26T19:11:58.432854","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Sex\n","female    0.742038\n","male      0.188908\n","Name: Survived, dtype: float64"]},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":["train.groupby(['Sex'])['Survived'].mean()"]},{"cell_type":"code","execution_count":18,"id":"bc24a036","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.495236Z","iopub.status.busy":"2023-04-26T19:11:58.494772Z","iopub.status.idle":"2023-04-26T19:11:58.505507Z","shell.execute_reply":"2023-04-26T19:11:58.504064Z"},"papermill":{"duration":0.030099,"end_time":"2023-04-26T19:11:58.508075","exception":false,"start_time":"2023-04-26T19:11:58.477976","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Embarked\n","C    0.553571\n","Q    0.389610\n","S    0.339009\n","Name: Survived, dtype: float64"]},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":["train.groupby(['Embarked'])['Survived'].mean()"]},{"cell_type":"code","execution_count":19,"id":"eba9200c","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.540611Z","iopub.status.busy":"2023-04-26T19:11:58.540129Z","iopub.status.idle":"2023-04-26T19:11:58.866389Z","shell.execute_reply":"2023-04-26T19:11:58.865019Z"},"papermill":{"duration":0.346411,"end_time":"2023-04-26T19:11:58.869455","exception":false,"start_time":"2023-04-26T19:11:58.523044","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: UserWarning: \n","\n","`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n","\n","Please adapt your code to use either `displot` (a figure-level function with\n","similar flexibility) or `histplot` (an axes-level function for histograms).\n","\n","For a guide to updating your code to use the new functions, please see\n","https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n","\n","  \"\"\"Entry point for launching an IPython kernel.\n","/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:2: UserWarning: \n","\n","`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n","\n","Please adapt your code to use either `displot` (a figure-level function with\n","similar flexibility) or `histplot` (an axes-level function for histograms).\n","\n","For a guide to updating your code to use the new functions, please see\n","https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n","\n","  \n"]},{"data":{"text/plain":["<AxesSubplot:xlabel='Age', ylabel='Density'>"]},"execution_count":19,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["sns.distplot(train['Age'][train['Survived']==0])\n","sns.distplot(train['Age'][train['Survived']==1])"]},{"cell_type":"code","execution_count":20,"id":"364e6088","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:58.903909Z","iopub.status.busy":"2023-04-26T19:11:58.903384Z","iopub.status.idle":"2023-04-26T19:11:59.301283Z","shell.execute_reply":"2023-04-26T19:11:59.300217Z"},"papermill":{"duration":0.418198,"end_time":"2023-04-26T19:11:59.303893","exception":false,"start_time":"2023-04-26T19:11:58.885695","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: UserWarning: \n","\n","`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n","\n","Please adapt your code to use either `displot` (a figure-level function with\n","similar flexibility) or `histplot` (an axes-level function for histograms).\n","\n","For a guide to updating your code to use the new functions, please see\n","https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n","\n","  \"\"\"Entry point for launching an IPython kernel.\n","/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:2: UserWarning: \n","\n","`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n","\n","Please adapt your code to use either `displot` (a figure-level function with\n","similar flexibility) or `histplot` (an axes-level function for histograms).\n","\n","For a guide to updating your code to use the new functions, please see\n","https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n","\n","  \n"]},{"data":{"text/plain":["<AxesSubplot:xlabel='Fare', ylabel='Density'>"]},"execution_count":20,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["sns.distplot(train['Fare'][train['Survived']==0])\n","sns.distplot(train['Fare'][train['Survived']==1])"]},{"cell_type":"code","execution_count":21,"id":"f5654c7f","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.339781Z","iopub.status.busy":"2023-04-26T19:11:59.338493Z","iopub.status.idle":"2023-04-26T19:11:59.346824Z","shell.execute_reply":"2023-04-26T19:11:59.345697Z"},"papermill":{"duration":0.028986,"end_time":"2023-04-26T19:11:59.349412","exception":false,"start_time":"2023-04-26T19:11:59.320426","status":"completed"},"tags":[]},"outputs":[],"source":["train.drop(columns=['Ticket'], inplace=True)\n","test.drop(columns=['Ticket'], inplace=True)"]},{"cell_type":"code","execution_count":22,"id":"24bc58f8","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.384626Z","iopub.status.busy":"2023-04-26T19:11:59.384113Z","iopub.status.idle":"2023-04-26T19:11:59.392285Z","shell.execute_reply":"2023-04-26T19:11:59.391225Z"},"papermill":{"duration":0.028801,"end_time":"2023-04-26T19:11:59.394724","exception":false,"start_time":"2023-04-26T19:11:59.365923","status":"completed"},"tags":[]},"outputs":[],"source":["train['Family']=train['SibSp']+train['Parch']+1"]},{"cell_type":"code","execution_count":23,"id":"e73acbd0","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.431161Z","iopub.status.busy":"2023-04-26T19:11:59.429977Z","iopub.status.idle":"2023-04-26T19:11:59.438067Z","shell.execute_reply":"2023-04-26T19:11:59.436784Z"},"papermill":{"duration":0.029008,"end_time":"2023-04-26T19:11:59.440534","exception":false,"start_time":"2023-04-26T19:11:59.411526","status":"completed"},"tags":[]},"outputs":[],"source":["test['Family']=test['SibSp']+test['Parch']+1"]},{"cell_type":"code","execution_count":24,"id":"626b6281","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.476792Z","iopub.status.busy":"2023-04-26T19:11:59.475961Z","iopub.status.idle":"2023-04-26T19:11:59.485642Z","shell.execute_reply":"2023-04-26T19:11:59.484251Z"},"papermill":{"duration":0.030547,"end_time":"2023-04-26T19:11:59.488072","exception":false,"start_time":"2023-04-26T19:11:59.457525","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["SibSp\n","0    0.345395\n","1    0.535885\n","2    0.464286\n","3    0.250000\n","4    0.166667\n","5    0.000000\n","8    0.000000\n","Name: Survived, dtype: float64"]},"execution_count":24,"metadata":{},"output_type":"execute_result"}],"source":["train.groupby(['SibSp'])['Survived'].mean()"]},{"cell_type":"code","execution_count":25,"id":"93876e65","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.524742Z","iopub.status.busy":"2023-04-26T19:11:59.523926Z","iopub.status.idle":"2023-04-26T19:11:59.533027Z","shell.execute_reply":"2023-04-26T19:11:59.532091Z"},"papermill":{"duration":0.030614,"end_time":"2023-04-26T19:11:59.535429","exception":false,"start_time":"2023-04-26T19:11:59.504815","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Parch\n","0    0.343658\n","1    0.550847\n","2    0.500000\n","3    0.600000\n","4    0.000000\n","5    0.200000\n","6    0.000000\n","Name: Survived, dtype: float64"]},"execution_count":25,"metadata":{},"output_type":"execute_result"}],"source":["train.groupby(['Parch'])['Survived'].mean()"]},{"cell_type":"code","execution_count":26,"id":"90bcbc74","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.571652Z","iopub.status.busy":"2023-04-26T19:11:59.570821Z","iopub.status.idle":"2023-04-26T19:11:59.590249Z","shell.execute_reply":"2023-04-26T19:11:59.588874Z"},"papermill":{"duration":0.040715,"end_time":"2023-04-26T19:11:59.592955","exception":false,"start_time":"2023-04-26T19:11:59.55224","status":"completed"},"tags":[]},"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>Age</th>\n","      <th>SibSp</th>\n","      <th>Parch</th>\n","      <th>Fare</th>\n","    </tr>\n","    <tr>\n","      <th>Family</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>1</th>\n","      <td>458.000000</td>\n","      <td>0.303538</td>\n","      <td>2.400372</td>\n","      <td>31.290503</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>21.242689</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>412.838509</td>\n","      <td>0.552795</td>\n","      <td>1.919255</td>\n","      <td>30.983975</td>\n","      <td>0.763975</td>\n","      <td>0.236025</td>\n","      <td>49.894129</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>448.352941</td>\n","      <td>0.578431</td>\n","      <td>2.225490</td>\n","      <td>26.307157</td>\n","      <td>0.872549</td>\n","      <td>1.127451</td>\n","      <td>39.692482</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>514.344828</td>\n","      <td>0.724138</td>\n","      <td>2.068966</td>\n","      <td>19.324828</td>\n","      <td>1.344828</td>\n","      <td>1.655172</td>\n","      <td>54.864510</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>367.866667</td>\n","      <td>0.200000</td>\n","      <td>2.666667</td>\n","      <td>21.600000</td>\n","      <td>2.133333</td>\n","      <td>1.866667</td>\n","      <td>58.094453</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>400.136364</td>\n","      <td>0.136364</td>\n","      <td>2.590909</td>\n","      <td>18.409091</td>\n","      <td>2.818182</td>\n","      <td>2.181818</td>\n","      <td>73.722727</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>355.750000</td>\n","      <td>0.333333</td>\n","      <td>3.000000</td>\n","      <td>15.166667</td>\n","      <td>3.250000</td>\n","      <td>2.750000</td>\n","      <td>29.366667</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>393.833333</td>\n","      <td>0.000000</td>\n","      <td>3.000000</td>\n","      <td>15.666667</td>\n","      <td>4.333333</td>\n","      <td>2.666667</td>\n","      <td>46.900000</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>481.714286</td>\n","      <td>0.000000</td>\n","      <td>3.000000</td>\n","      <td>30.571429</td>\n","      <td>8.000000</td>\n","      <td>2.000000</td>\n","      <td>69.550000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        PassengerId  Survived    Pclass        Age     SibSp     Parch  \\\n","Family                                                                   \n","1        458.000000  0.303538  2.400372  31.290503  0.000000  0.000000   \n","2        412.838509  0.552795  1.919255  30.983975  0.763975  0.236025   \n","3        448.352941  0.578431  2.225490  26.307157  0.872549  1.127451   \n","4        514.344828  0.724138  2.068966  19.324828  1.344828  1.655172   \n","5        367.866667  0.200000  2.666667  21.600000  2.133333  1.866667   \n","6        400.136364  0.136364  2.590909  18.409091  2.818182  2.181818   \n","7        355.750000  0.333333  3.000000  15.166667  3.250000  2.750000   \n","8        393.833333  0.000000  3.000000  15.666667  4.333333  2.666667   \n","11       481.714286  0.000000  3.000000  30.571429  8.000000  2.000000   \n","\n","             Fare  \n","Family             \n","1       21.242689  \n","2       49.894129  \n","3       39.692482  \n","4       54.864510  \n","5       58.094453  \n","6       73.722727  \n","7       29.366667  \n","8       46.900000  \n","11      69.550000  "]},"execution_count":26,"metadata":{},"output_type":"execute_result"}],"source":["train.groupby(['Family']).mean()"]},{"cell_type":"code","execution_count":27,"id":"f4c63d31","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.63015Z","iopub.status.busy":"2023-04-26T19:11:59.629665Z","iopub.status.idle":"2023-04-26T19:11:59.635547Z","shell.execute_reply":"2023-04-26T19:11:59.634371Z"},"papermill":{"duration":0.027952,"end_time":"2023-04-26T19:11:59.638122","exception":false,"start_time":"2023-04-26T19:11:59.61017","status":"completed"},"tags":[]},"outputs":[],"source":["def cal(number):\n","    if number==1:\n","        return 'Alone'\n","    elif number>1 and number<5:\n","        return 'Medium'\n","    else:\n","        return 'Large'"]},{"cell_type":"code","execution_count":28,"id":"426d92fc","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.675271Z","iopub.status.busy":"2023-04-26T19:11:59.674788Z","iopub.status.idle":"2023-04-26T19:11:59.682344Z","shell.execute_reply":"2023-04-26T19:11:59.68077Z"},"papermill":{"duration":0.0299,"end_time":"2023-04-26T19:11:59.685071","exception":false,"start_time":"2023-04-26T19:11:59.655171","status":"completed"},"tags":[]},"outputs":[],"source":["train['Family_Size']=train['Family'].apply(cal)"]},{"cell_type":"code","execution_count":29,"id":"0ec19cec","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.722374Z","iopub.status.busy":"2023-04-26T19:11:59.72185Z","iopub.status.idle":"2023-04-26T19:11:59.730001Z","shell.execute_reply":"2023-04-26T19:11:59.728712Z"},"papermill":{"duration":0.03029,"end_time":"2023-04-26T19:11:59.732726","exception":false,"start_time":"2023-04-26T19:11:59.702436","status":"completed"},"tags":[]},"outputs":[],"source":["test['Family_Size']=test['Family'].apply(cal)"]},{"cell_type":"code","execution_count":30,"id":"13c76b9f","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.769737Z","iopub.status.busy":"2023-04-26T19:11:59.768491Z","iopub.status.idle":"2023-04-26T19:11:59.796052Z","shell.execute_reply":"2023-04-26T19:11:59.794672Z"},"papermill":{"duration":0.049281,"end_time":"2023-04-26T19:11:59.799059","exception":false,"start_time":"2023-04-26T19:11:59.749778","status":"completed"},"tags":[]},"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>Fare</th>\n","      <th>Embarked</th>\n","      <th>Family</th>\n","      <th>Family_Size</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>7.2500</td>\n","      <td>S</td>\n","      <td>2</td>\n","      <td>Medium</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>71.2833</td>\n","      <td>C</td>\n","      <td>2</td>\n","      <td>Medium</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>7.9250</td>\n","      <td>S</td>\n","      <td>1</td>\n","      <td>Alone</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>53.1000</td>\n","      <td>S</td>\n","      <td>2</td>\n","      <td>Medium</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>8.0500</td>\n","      <td>S</td>\n","      <td>1</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>886</th>\n","      <td>887</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>Montvila, Rev. Juozas</td>\n","      <td>male</td>\n","      <td>27.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>13.0000</td>\n","      <td>S</td>\n","      <td>1</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>887</th>\n","      <td>888</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Graham, Miss. Margaret Edith</td>\n","      <td>female</td>\n","      <td>19.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>30.0000</td>\n","      <td>S</td>\n","      <td>1</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>888</th>\n","      <td>889</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n","      <td>female</td>\n","      <td>36.0</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>23.4500</td>\n","      <td>S</td>\n","      <td>4</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>889</th>\n","      <td>890</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Behr, Mr. Karl Howell</td>\n","      <td>male</td>\n","      <td>26.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>30.0000</td>\n","      <td>C</td>\n","      <td>1</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>890</th>\n","      <td>891</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Dooley, Mr. Patrick</td>\n","      <td>male</td>\n","      <td>32.0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>7.7500</td>\n","      <td>Q</td>\n","      <td>1</td>\n","      <td>Alone</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>891 rows × 12 columns</p>\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","886          887         0       2   \n","887          888         1       1   \n","888          889         0       3   \n","889          890         1       1   \n","890          891         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","886                              Montvila, Rev. Juozas    male  27.0      0   \n","887                       Graham, Miss. Margaret Edith  female  19.0      0   \n","888           Johnston, Miss. Catherine Helen \"Carrie\"  female  36.0      1   \n","889                              Behr, Mr. Karl Howell    male  26.0      0   \n","890                                Dooley, Mr. Patrick    male  32.0      0   \n","\n","     Parch     Fare Embarked  Family Family_Size  \n","0        0   7.2500        S       2      Medium  \n","1        0  71.2833        C       2      Medium  \n","2        0   7.9250        S       1       Alone  \n","3        0  53.1000        S       2      Medium  \n","4        0   8.0500        S       1       Alone  \n","..     ...      ...      ...     ...         ...  \n","886      0  13.0000        S       1       Alone  \n","887      0  30.0000        S       1       Alone  \n","888      2  23.4500        S       4      Medium  \n","889      0  30.0000        C       1       Alone  \n","890      0   7.7500        Q       1       Alone  \n","\n","[891 rows x 12 columns]"]},"execution_count":30,"metadata":{},"output_type":"execute_result"}],"source":["train"]},{"cell_type":"code","execution_count":31,"id":"3842b851","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.836513Z","iopub.status.busy":"2023-04-26T19:11:59.836035Z","iopub.status.idle":"2023-04-26T19:11:59.846225Z","shell.execute_reply":"2023-04-26T19:11:59.844778Z"},"papermill":{"duration":0.031847,"end_time":"2023-04-26T19:11:59.848671","exception":false,"start_time":"2023-04-26T19:11:59.816824","status":"completed"},"tags":[]},"outputs":[],"source":["train.drop(columns=['SibSp','Parch','Family'], inplace=True)\n","test.drop(columns=['SibSp','Parch','Family'], inplace=True)"]},{"cell_type":"code","execution_count":32,"id":"484e41f6","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.88644Z","iopub.status.busy":"2023-04-26T19:11:59.885215Z","iopub.status.idle":"2023-04-26T19:11:59.90962Z","shell.execute_reply":"2023-04-26T19:11:59.908159Z"},"papermill":{"duration":0.0463,"end_time":"2023-04-26T19:11:59.912309","exception":false,"start_time":"2023-04-26T19:11:59.866009","status":"completed"},"tags":[]},"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>Fare</th>\n","      <th>Embarked</th>\n","      <th>Family_Size</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>7.2500</td>\n","      <td>S</td>\n","      <td>Medium</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>71.2833</td>\n","      <td>C</td>\n","      <td>Medium</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>7.9250</td>\n","      <td>S</td>\n","      <td>Alone</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>53.1000</td>\n","      <td>S</td>\n","      <td>Medium</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>8.0500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>886</th>\n","      <td>887</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>Montvila, Rev. Juozas</td>\n","      <td>male</td>\n","      <td>27.0</td>\n","      <td>13.0000</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>887</th>\n","      <td>888</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Graham, Miss. Margaret Edith</td>\n","      <td>female</td>\n","      <td>19.0</td>\n","      <td>30.0000</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>888</th>\n","      <td>889</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n","      <td>female</td>\n","      <td>36.0</td>\n","      <td>23.4500</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>889</th>\n","      <td>890</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Behr, Mr. Karl Howell</td>\n","      <td>male</td>\n","      <td>26.0</td>\n","      <td>30.0000</td>\n","      <td>C</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>890</th>\n","      <td>891</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>Dooley, Mr. Patrick</td>\n","      <td>male</td>\n","      <td>32.0</td>\n","      <td>7.7500</td>\n","      <td>Q</td>\n","      <td>Alone</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>891 rows × 9 columns</p>\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","886          887         0       2   \n","887          888         1       1   \n","888          889         0       3   \n","889          890         1       1   \n","890          891         0       3   \n","\n","                                                  Name     Sex   Age     Fare  \\\n","0                              Braund, Mr. Owen Harris    male  22.0   7.2500   \n","1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0  71.2833   \n","2                               Heikkinen, Miss. Laina  female  26.0   7.9250   \n","3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0  53.1000   \n","4                             Allen, Mr. William Henry    male  35.0   8.0500   \n","..                                                 ...     ...   ...      ...   \n","886                              Montvila, Rev. Juozas    male  27.0  13.0000   \n","887                       Graham, Miss. Margaret Edith  female  19.0  30.0000   \n","888           Johnston, Miss. Catherine Helen \"Carrie\"  female  36.0  23.4500   \n","889                              Behr, Mr. Karl Howell    male  26.0  30.0000   \n","890                                Dooley, Mr. Patrick    male  32.0   7.7500   \n","\n","    Embarked Family_Size  \n","0          S      Medium  \n","1          C      Medium  \n","2          S       Alone  \n","3          S      Medium  \n","4          S       Alone  \n","..       ...         ...  \n","886        S       Alone  \n","887        S       Alone  \n","888        S      Medium  \n","889        C       Alone  \n","890        Q       Alone  \n","\n","[891 rows x 9 columns]"]},"execution_count":32,"metadata":{},"output_type":"execute_result"}],"source":["train"]},{"cell_type":"code","execution_count":33,"id":"cf38932d","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:11:59.950921Z","iopub.status.busy":"2023-04-26T19:11:59.949482Z","iopub.status.idle":"2023-04-26T19:11:59.973406Z","shell.execute_reply":"2023-04-26T19:11:59.972089Z"},"papermill":{"duration":0.04589,"end_time":"2023-04-26T19:11:59.976023","exception":false,"start_time":"2023-04-26T19:11:59.930133","status":"completed"},"tags":[]},"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>Pclass</th>\n","      <th>Name</th>\n","      <th>Sex</th>\n","      <th>Age</th>\n","      <th>Fare</th>\n","      <th>Embarked</th>\n","      <th>Family_Size</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>892</td>\n","      <td>3</td>\n","      <td>Kelly, Mr. James</td>\n","      <td>male</td>\n","      <td>34.5</td>\n","      <td>7.8292</td>\n","      <td>Q</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>893</td>\n","      <td>3</td>\n","      <td>Wilkes, Mrs. James (Ellen Needs)</td>\n","      <td>female</td>\n","      <td>47.0</td>\n","      <td>7.0000</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>894</td>\n","      <td>2</td>\n","      <td>Myles, Mr. Thomas Francis</td>\n","      <td>male</td>\n","      <td>62.0</td>\n","      <td>9.6875</td>\n","      <td>Q</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>895</td>\n","      <td>3</td>\n","      <td>Wirz, Mr. Albert</td>\n","      <td>male</td>\n","      <td>27.0</td>\n","      <td>8.6625</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>896</td>\n","      <td>3</td>\n","      <td>Hirvonen, Mrs. Alexander (Helga E Lindqvist)</td>\n","      <td>female</td>\n","      <td>22.0</td>\n","      <td>12.2875</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>413</th>\n","      <td>1305</td>\n","      <td>3</td>\n","      <td>Spector, Mr. Woolf</td>\n","      <td>male</td>\n","      <td>25.0</td>\n","      <td>8.0500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>414</th>\n","      <td>1306</td>\n","      <td>1</td>\n","      <td>Oliva y Ocana, Dona. Fermina</td>\n","      <td>female</td>\n","      <td>39.0</td>\n","      <td>108.9000</td>\n","      <td>C</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>415</th>\n","      <td>1307</td>\n","      <td>3</td>\n","      <td>Saether, Mr. Simon Sivertsen</td>\n","      <td>male</td>\n","      <td>38.5</td>\n","      <td>7.2500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>416</th>\n","      <td>1308</td>\n","      <td>3</td>\n","      <td>Ware, Mr. Frederick</td>\n","      <td>male</td>\n","      <td>26.0</td>\n","      <td>8.0500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>417</th>\n","      <td>1309</td>\n","      <td>3</td>\n","      <td>Peter, Master. Michael J</td>\n","      <td>male</td>\n","      <td>28.0</td>\n","      <td>22.3583</td>\n","      <td>C</td>\n","      <td>Medium</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>418 rows × 8 columns</p>\n","</div>"],"text/plain":["     PassengerId  Pclass                                          Name  \\\n","0            892       3                              Kelly, Mr. James   \n","1            893       3              Wilkes, Mrs. James (Ellen Needs)   \n","2            894       2                     Myles, Mr. Thomas Francis   \n","3            895       3                              Wirz, Mr. Albert   \n","4            896       3  Hirvonen, Mrs. Alexander (Helga E Lindqvist)   \n","..           ...     ...                                           ...   \n","413         1305       3                            Spector, Mr. Woolf   \n","414         1306       1                  Oliva y Ocana, Dona. Fermina   \n","415         1307       3                  Saether, Mr. Simon Sivertsen   \n","416         1308       3                           Ware, Mr. Frederick   \n","417         1309       3                      Peter, Master. Michael J   \n","\n","        Sex   Age      Fare Embarked Family_Size  \n","0      male  34.5    7.8292        Q       Alone  \n","1    female  47.0    7.0000        S      Medium  \n","2      male  62.0    9.6875        Q       Alone  \n","3      male  27.0    8.6625        S       Alone  \n","4    female  22.0   12.2875        S      Medium  \n","..      ...   ...       ...      ...         ...  \n","413    male  25.0    8.0500        S       Alone  \n","414  female  39.0  108.9000        C       Alone  \n","415    male  38.5    7.2500        S       Alone  \n","416    male  26.0    8.0500        S       Alone  \n","417    male  28.0   22.3583        C      Medium  \n","\n","[418 rows x 8 columns]"]},"execution_count":33,"metadata":{},"output_type":"execute_result"}],"source":["test"]},{"cell_type":"code","execution_count":34,"id":"924f4030","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.014792Z","iopub.status.busy":"2023-04-26T19:12:00.013877Z","iopub.status.idle":"2023-04-26T19:12:00.020689Z","shell.execute_reply":"2023-04-26T19:12:00.019011Z"},"papermill":{"duration":0.029001,"end_time":"2023-04-26T19:12:00.023186","exception":false,"start_time":"2023-04-26T19:11:59.994185","status":"completed"},"tags":[]},"outputs":[],"source":["PassengerId=test['PassengerId'].values"]},{"cell_type":"code","execution_count":35,"id":"68ceb42f","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.061866Z","iopub.status.busy":"2023-04-26T19:12:00.060884Z","iopub.status.idle":"2023-04-26T19:12:00.069483Z","shell.execute_reply":"2023-04-26T19:12:00.068161Z"},"papermill":{"duration":0.030898,"end_time":"2023-04-26T19:12:00.072101","exception":false,"start_time":"2023-04-26T19:12:00.041203","status":"completed"},"tags":[]},"outputs":[],"source":["train.drop(columns=['Name','PassengerId'], inplace=True)\n","test.drop(columns=['Name','PassengerId'], inplace=True)"]},{"cell_type":"code","execution_count":36,"id":"51650c30","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.110514Z","iopub.status.busy":"2023-04-26T19:12:00.109999Z","iopub.status.idle":"2023-04-26T19:12:00.130283Z","shell.execute_reply":"2023-04-26T19:12:00.128924Z"},"papermill":{"duration":0.04292,"end_time":"2023-04-26T19:12:00.132907","exception":false,"start_time":"2023-04-26T19:12:00.089987","status":"completed"},"tags":[]},"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>Pclass</th>\n","      <th>Sex</th>\n","      <th>Age</th>\n","      <th>Fare</th>\n","      <th>Embarked</th>\n","      <th>Family_Size</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>34.5</td>\n","      <td>7.8292</td>\n","      <td>Q</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>3</td>\n","      <td>female</td>\n","      <td>47.0</td>\n","      <td>7.0000</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>male</td>\n","      <td>62.0</td>\n","      <td>9.6875</td>\n","      <td>Q</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>27.0</td>\n","      <td>8.6625</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>3</td>\n","      <td>female</td>\n","      <td>22.0</td>\n","      <td>12.2875</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>413</th>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>25.0</td>\n","      <td>8.0500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>414</th>\n","      <td>1</td>\n","      <td>female</td>\n","      <td>39.0</td>\n","      <td>108.9000</td>\n","      <td>C</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>415</th>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>38.5</td>\n","      <td>7.2500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>416</th>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>26.0</td>\n","      <td>8.0500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>417</th>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>28.0</td>\n","      <td>22.3583</td>\n","      <td>C</td>\n","      <td>Medium</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>418 rows × 6 columns</p>\n","</div>"],"text/plain":["     Pclass     Sex   Age      Fare Embarked Family_Size\n","0         3    male  34.5    7.8292        Q       Alone\n","1         3  female  47.0    7.0000        S      Medium\n","2         2    male  62.0    9.6875        Q       Alone\n","3         3    male  27.0    8.6625        S       Alone\n","4         3  female  22.0   12.2875        S      Medium\n","..      ...     ...   ...       ...      ...         ...\n","413       3    male  25.0    8.0500        S       Alone\n","414       1  female  39.0  108.9000        C       Alone\n","415       3    male  38.5    7.2500        S       Alone\n","416       3    male  26.0    8.0500        S       Alone\n","417       3    male  28.0   22.3583        C      Medium\n","\n","[418 rows x 6 columns]"]},"execution_count":36,"metadata":{},"output_type":"execute_result"}],"source":["test"]},{"cell_type":"code","execution_count":37,"id":"2832f160","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.173111Z","iopub.status.busy":"2023-04-26T19:12:00.172568Z","iopub.status.idle":"2023-04-26T19:12:00.195751Z","shell.execute_reply":"2023-04-26T19:12:00.194212Z"},"papermill":{"duration":0.04653,"end_time":"2023-04-26T19:12:00.198505","exception":false,"start_time":"2023-04-26T19:12:00.151975","status":"completed"},"tags":[]},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Survived</th>\n","      <th>Pclass</th>\n","      <th>Sex</th>\n","      <th>Age</th>\n","      <th>Fare</th>\n","      <th>Embarked</th>\n","      <th>Family_Size</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>22.0</td>\n","      <td>7.2500</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>female</td>\n","      <td>38.0</td>\n","      <td>71.2833</td>\n","      <td>C</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>3</td>\n","      <td>female</td>\n","      <td>26.0</td>\n","      <td>7.9250</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>female</td>\n","      <td>35.0</td>\n","      <td>53.1000</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>35.0</td>\n","      <td>8.0500</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>886</th>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>male</td>\n","      <td>27.0</td>\n","      <td>13.0000</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>887</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>female</td>\n","      <td>19.0</td>\n","      <td>30.0000</td>\n","      <td>S</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>888</th>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>female</td>\n","      <td>36.0</td>\n","      <td>23.4500</td>\n","      <td>S</td>\n","      <td>Medium</td>\n","    </tr>\n","    <tr>\n","      <th>889</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>male</td>\n","      <td>26.0</td>\n","      <td>30.0000</td>\n","      <td>C</td>\n","      <td>Alone</td>\n","    </tr>\n","    <tr>\n","      <th>890</th>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>male</td>\n","      <td>32.0</td>\n","      <td>7.7500</td>\n","      <td>Q</td>\n","      <td>Alone</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>891 rows × 7 columns</p>\n","</div>"],"text/plain":["     Survived  Pclass     Sex   Age     Fare Embarked Family_Size\n","0           0       3    male  22.0   7.2500        S      Medium\n","1           1       1  female  38.0  71.2833        C      Medium\n","2           1       3  female  26.0   7.9250        S       Alone\n","3           1       1  female  35.0  53.1000        S      Medium\n","4           0       3    male  35.0   8.0500        S       Alone\n","..        ...     ...     ...   ...      ...      ...         ...\n","886         0       2    male  27.0  13.0000        S       Alone\n","887         1       1  female  19.0  30.0000        S       Alone\n","888         0       3  female  36.0  23.4500        S      Medium\n","889         1       1    male  26.0  30.0000        C       Alone\n","890         0       3    male  32.0   7.7500        Q       Alone\n","\n","[891 rows x 7 columns]"]},"execution_count":37,"metadata":{},"output_type":"execute_result"}],"source":["train"]},{"cell_type":"code","execution_count":38,"id":"ea0fa42f","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.239798Z","iopub.status.busy":"2023-04-26T19:12:00.23892Z","iopub.status.idle":"2023-04-26T19:12:00.252996Z","shell.execute_reply":"2023-04-26T19:12:00.251672Z"},"papermill":{"duration":0.03796,"end_time":"2023-04-26T19:12:00.255496","exception":false,"start_time":"2023-04-26T19:12:00.217536","status":"completed"},"tags":[]},"outputs":[],"source":["train=pd.get_dummies(train, columns=['Pclass','Sex','Embarked','Family_Size'], drop_first=True)\n"]},{"cell_type":"code","execution_count":39,"id":"d2ec700c","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.294699Z","iopub.status.busy":"2023-04-26T19:12:00.294238Z","iopub.status.idle":"2023-04-26T19:12:00.306841Z","shell.execute_reply":"2023-04-26T19:12:00.305711Z"},"papermill":{"duration":0.035419,"end_time":"2023-04-26T19:12:00.309463","exception":false,"start_time":"2023-04-26T19:12:00.274044","status":"completed"},"tags":[]},"outputs":[],"source":["test=pd.get_dummies(test, columns=['Pclass','Sex','Embarked','Family_Size'], drop_first=True)"]},{"cell_type":"code","execution_count":40,"id":"b792be3d","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.349129Z","iopub.status.busy":"2023-04-26T19:12:00.348665Z","iopub.status.idle":"2023-04-26T19:12:00.369376Z","shell.execute_reply":"2023-04-26T19:12:00.367978Z"},"papermill":{"duration":0.043939,"end_time":"2023-04-26T19:12:00.372059","exception":false,"start_time":"2023-04-26T19:12:00.32812","status":"completed"},"tags":[]},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Survived</th>\n","      <th>Age</th>\n","      <th>Fare</th>\n","      <th>Pclass_2</th>\n","      <th>Pclass_3</th>\n","      <th>Sex_male</th>\n","      <th>Embarked_Q</th>\n","      <th>Embarked_S</th>\n","      <th>Family_Size_Large</th>\n","      <th>Family_Size_Medium</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>22.0</td>\n","      <td>7.2500</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>38.0</td>\n","      <td>71.2833</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>26.0</td>\n","      <td>7.9250</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>35.0</td>\n","      <td>53.1000</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0</td>\n","      <td>35.0</td>\n","      <td>8.0500</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>886</th>\n","      <td>0</td>\n","      <td>27.0</td>\n","      <td>13.0000</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>887</th>\n","      <td>1</td>\n","      <td>19.0</td>\n","      <td>30.0000</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>888</th>\n","      <td>0</td>\n","      <td>36.0</td>\n","      <td>23.4500</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>889</th>\n","      <td>1</td>\n","      <td>26.0</td>\n","      <td>30.0000</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>890</th>\n","      <td>0</td>\n","      <td>32.0</td>\n","      <td>7.7500</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>891 rows × 10 columns</p>\n","</div>"],"text/plain":["     Survived   Age     Fare  Pclass_2  Pclass_3  Sex_male  Embarked_Q  \\\n","0           0  22.0   7.2500         0         1         1           0   \n","1           1  38.0  71.2833         0         0         0           0   \n","2           1  26.0   7.9250         0         1         0           0   \n","3           1  35.0  53.1000         0         0         0           0   \n","4           0  35.0   8.0500         0         1         1           0   \n","..        ...   ...      ...       ...       ...       ...         ...   \n","886         0  27.0  13.0000         1         0         1           0   \n","887         1  19.0  30.0000         0         0         0           0   \n","888         0  36.0  23.4500         0         1         0           0   \n","889         1  26.0  30.0000         0         0         1           0   \n","890         0  32.0   7.7500         0         1         1           1   \n","\n","     Embarked_S  Family_Size_Large  Family_Size_Medium  \n","0             1                  0                   1  \n","1             0                  0                   1  \n","2             1                  0                   0  \n","3             1                  0                   1  \n","4             1                  0                   0  \n","..          ...                ...                 ...  \n","886           1                  0                   0  \n","887           1                  0                   0  \n","888           1                  0                   1  \n","889           0                  0                   0  \n","890           0                  0                   0  \n","\n","[891 rows x 10 columns]"]},"execution_count":40,"metadata":{},"output_type":"execute_result"}],"source":["train"]},{"cell_type":"code","execution_count":41,"id":"d9d98f40","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.412627Z","iopub.status.busy":"2023-04-26T19:12:00.411693Z","iopub.status.idle":"2023-04-26T19:12:00.431424Z","shell.execute_reply":"2023-04-26T19:12:00.429914Z"},"papermill":{"duration":0.043456,"end_time":"2023-04-26T19:12:00.434398","exception":false,"start_time":"2023-04-26T19:12:00.390942","status":"completed"},"tags":[]},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Age</th>\n","      <th>Fare</th>\n","      <th>Pclass_2</th>\n","      <th>Pclass_3</th>\n","      <th>Sex_male</th>\n","      <th>Embarked_Q</th>\n","      <th>Embarked_S</th>\n","      <th>Family_Size_Large</th>\n","      <th>Family_Size_Medium</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>34.5</td>\n","      <td>7.8292</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>47.0</td>\n","      <td>7.0000</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>62.0</td>\n","      <td>9.6875</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>27.0</td>\n","      <td>8.6625</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>22.0</td>\n","      <td>12.2875</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</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","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>413</th>\n","      <td>25.0</td>\n","      <td>8.0500</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>414</th>\n","      <td>39.0</td>\n","      <td>108.9000</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>415</th>\n","      <td>38.5</td>\n","      <td>7.2500</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>416</th>\n","      <td>26.0</td>\n","      <td>8.0500</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>417</th>\n","      <td>28.0</td>\n","      <td>22.3583</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>418 rows × 9 columns</p>\n","</div>"],"text/plain":["      Age      Fare  Pclass_2  Pclass_3  Sex_male  Embarked_Q  Embarked_S  \\\n","0    34.5    7.8292         0         1         1           1           0   \n","1    47.0    7.0000         0         1         0           0           1   \n","2    62.0    9.6875         1         0         1           1           0   \n","3    27.0    8.6625         0         1         1           0           1   \n","4    22.0   12.2875         0         1         0           0           1   \n","..    ...       ...       ...       ...       ...         ...         ...   \n","413  25.0    8.0500         0         1         1           0           1   \n","414  39.0  108.9000         0         0         0           0           0   \n","415  38.5    7.2500         0         1         1           0           1   \n","416  26.0    8.0500         0         1         1           0           1   \n","417  28.0   22.3583         0         1         1           0           0   \n","\n","     Family_Size_Large  Family_Size_Medium  \n","0                    0                   0  \n","1                    0                   1  \n","2                    0                   0  \n","3                    0                   0  \n","4                    0                   1  \n","..                 ...                 ...  \n","413                  0                   0  \n","414                  0                   0  \n","415                  0                   0  \n","416                  0                   0  \n","417                  0                   1  \n","\n","[418 rows x 9 columns]"]},"execution_count":41,"metadata":{},"output_type":"execute_result"}],"source":["test"]},{"cell_type":"code","execution_count":42,"id":"96876a3f","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.477094Z","iopub.status.busy":"2023-04-26T19:12:00.47614Z","iopub.status.idle":"2023-04-26T19:12:00.483384Z","shell.execute_reply":"2023-04-26T19:12:00.48237Z"},"papermill":{"duration":0.031531,"end_time":"2023-04-26T19:12:00.486265","exception":false,"start_time":"2023-04-26T19:12:00.454734","status":"completed"},"tags":[]},"outputs":[],"source":["X=train.iloc[:,1:].values\n"]},{"cell_type":"code","execution_count":43,"id":"1e0ad4d4","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.526577Z","iopub.status.busy":"2023-04-26T19:12:00.526089Z","iopub.status.idle":"2023-04-26T19:12:00.532405Z","shell.execute_reply":"2023-04-26T19:12:00.531094Z"},"papermill":{"duration":0.029475,"end_time":"2023-04-26T19:12:00.534905","exception":false,"start_time":"2023-04-26T19:12:00.50543","status":"completed"},"tags":[]},"outputs":[],"source":["y=train.iloc[:,0].values"]},{"cell_type":"code","execution_count":44,"id":"e3a4d8a0","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.575439Z","iopub.status.busy":"2023-04-26T19:12:00.574937Z","iopub.status.idle":"2023-04-26T19:12:00.822165Z","shell.execute_reply":"2023-04-26T19:12:00.821078Z"},"papermill":{"duration":0.270915,"end_time":"2023-04-26T19:12:00.825015","exception":false,"start_time":"2023-04-26T19:12:00.5541","status":"completed"},"tags":[]},"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=0.3)"]},{"cell_type":"code","execution_count":45,"id":"217dd793","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:00.866226Z","iopub.status.busy":"2023-04-26T19:12:00.865348Z","iopub.status.idle":"2023-04-26T19:12:01.116358Z","shell.execute_reply":"2023-04-26T19:12:01.115035Z"},"papermill":{"duration":0.275387,"end_time":"2023-04-26T19:12:01.119652","exception":false,"start_time":"2023-04-26T19:12:00.844265","status":"completed"},"tags":[]},"outputs":[],"source":["from sklearn.tree import DecisionTreeClassifier\n","classifier=DecisionTreeClassifier()"]},{"cell_type":"code","execution_count":46,"id":"ea2740f9","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.161946Z","iopub.status.busy":"2023-04-26T19:12:01.161296Z","iopub.status.idle":"2023-04-26T19:12:01.17703Z","shell.execute_reply":"2023-04-26T19:12:01.17556Z"},"papermill":{"duration":0.04026,"end_time":"2023-04-26T19:12:01.179686","exception":false,"start_time":"2023-04-26T19:12:01.139426","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["DecisionTreeClassifier()"]},"execution_count":46,"metadata":{},"output_type":"execute_result"}],"source":["classifier.fit(X_train,y_train)"]},{"cell_type":"code","execution_count":47,"id":"4c723a49","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.221851Z","iopub.status.busy":"2023-04-26T19:12:01.221204Z","iopub.status.idle":"2023-04-26T19:12:01.228226Z","shell.execute_reply":"2023-04-26T19:12:01.22679Z"},"papermill":{"duration":0.032085,"end_time":"2023-04-26T19:12:01.231342","exception":false,"start_time":"2023-04-26T19:12:01.199257","status":"completed"},"tags":[]},"outputs":[],"source":["y_pred=classifier.predict(X_test)"]},{"cell_type":"code","execution_count":48,"id":"79d35897","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.273455Z","iopub.status.busy":"2023-04-26T19:12:01.272927Z","iopub.status.idle":"2023-04-26T19:12:01.283128Z","shell.execute_reply":"2023-04-26T19:12:01.281849Z"},"papermill":{"duration":0.034708,"end_time":"2023-04-26T19:12:01.285716","exception":false,"start_time":"2023-04-26T19:12:01.251008","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["0.7761194029850746"]},"execution_count":48,"metadata":{},"output_type":"execute_result"}],"source":["from sklearn.metrics import accuracy_score\n","accuracy_score(y_pred, y_test)"]},{"cell_type":"code","execution_count":49,"id":"9d7b599a","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.329714Z","iopub.status.busy":"2023-04-26T19:12:01.328159Z","iopub.status.idle":"2023-04-26T19:12:01.335667Z","shell.execute_reply":"2023-04-26T19:12:01.334482Z"},"papermill":{"duration":0.032565,"end_time":"2023-04-26T19:12:01.338415","exception":false,"start_time":"2023-04-26T19:12:01.30585","status":"completed"},"tags":[]},"outputs":[],"source":["Xf=test.iloc[:,:].values"]},{"cell_type":"code","execution_count":50,"id":"c0a4433d","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.381546Z","iopub.status.busy":"2023-04-26T19:12:01.380752Z","iopub.status.idle":"2023-04-26T19:12:01.386035Z","shell.execute_reply":"2023-04-26T19:12:01.385033Z"},"papermill":{"duration":0.030271,"end_time":"2023-04-26T19:12:01.388698","exception":false,"start_time":"2023-04-26T19:12:01.358427","status":"completed"},"tags":[]},"outputs":[],"source":["y_final=classifier.predict(Xf)"]},{"cell_type":"code","execution_count":51,"id":"6dce01b4","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.432798Z","iopub.status.busy":"2023-04-26T19:12:01.432224Z","iopub.status.idle":"2023-04-26T19:12:01.439279Z","shell.execute_reply":"2023-04-26T19:12:01.43789Z"},"papermill":{"duration":0.032552,"end_time":"2023-04-26T19:12:01.442426","exception":false,"start_time":"2023-04-26T19:12:01.409874","status":"completed"},"tags":[]},"outputs":[],"source":["final=pd.DataFrame()"]},{"cell_type":"code","execution_count":52,"id":"b65bceab","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.485502Z","iopub.status.busy":"2023-04-26T19:12:01.485035Z","iopub.status.idle":"2023-04-26T19:12:01.500586Z","shell.execute_reply":"2023-04-26T19:12:01.499277Z"},"papermill":{"duration":0.040643,"end_time":"2023-04-26T19:12:01.50341","exception":false,"start_time":"2023-04-26T19:12:01.462767","status":"completed"},"tags":[]},"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","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>892</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>893</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>894</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>895</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>896</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>413</th>\n","      <td>1305</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>414</th>\n","      <td>1306</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>415</th>\n","      <td>1307</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>416</th>\n","      <td>1308</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>417</th>\n","      <td>1309</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>418 rows × 2 columns</p>\n","</div>"],"text/plain":["     PassengerId  Survived\n","0            892         0\n","1            893         1\n","2            894         0\n","3            895         0\n","4            896         0\n","..           ...       ...\n","413         1305         0\n","414         1306         1\n","415         1307         0\n","416         1308         0\n","417         1309         1\n","\n","[418 rows x 2 columns]"]},"execution_count":52,"metadata":{},"output_type":"execute_result"}],"source":["final['PassengerId']=PassengerId\n","final['Survived']=y_final\n","final"]},{"cell_type":"code","execution_count":53,"id":"49671adc","metadata":{"execution":{"iopub.execute_input":"2023-04-26T19:12:01.546574Z","iopub.status.busy":"2023-04-26T19:12:01.545074Z","iopub.status.idle":"2023-04-26T19:12:01.559126Z","shell.execute_reply":"2023-04-26T19:12:01.557528Z"},"papermill":{"duration":0.039168,"end_time":"2023-04-26T19:12:01.56252","exception":false,"start_time":"2023-04-26T19:12:01.523352","status":"completed"},"tags":[]},"outputs":[],"source":["final.to_csv('submission.csv', index=False)"]}],"metadata":{"kernelspec":{"display_name":"Python 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