titanic_data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('titanic_data_set.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pclass  Survived\n",
       "1       1           136\n",
       "        0            80\n",
       "2       0            97\n",
       "        1            87\n",
       "3       0           372\n",
       "        1           119\n",
       "Name: Survived, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Pclass').Survived.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sex     Survived\n",
       "female  1           233\n",
       "        0            81\n",
       "male    0           468\n",
       "        1           109\n",
       "Name: Survived, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Sex').Survived.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pclass  Sex     Survived\n",
       "1       female  1            91\n",
       "                0             3\n",
       "        male    0            77\n",
       "                1            45\n",
       "2       female  1            70\n",
       "                0             6\n",
       "        male    0            91\n",
       "                1            17\n",
       "3       female  0            72\n",
       "                1            72\n",
       "        male    0           300\n",
       "                1            47\n",
       "Name: Survived, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['Pclass', 'Sex']).Survived.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f811554bf28>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe8AAAFYCAYAAAB6RnQAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwDCUNwAAhqG8AQAwzP8DOEzEGRuwSzUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8115089fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x = 'Pclass', y = 'Survived', data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f81117743c8>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe8AAAFYCAYAAAB6RnQAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAGAYyhsAAMP8f3JipfZ8kV78AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f81534eeef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x = 'Sex', y = 'Survived', data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8111750f60>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe8AAAFYCAYAAAB6RnQAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f81116ccda0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x = 'Embarked', y = 'Survived', data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f81116ec080>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAFYCAYAAAB+s6Q9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBgDAEEQbAABD/D+I9teb9suMngAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f811166b160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x = 'Survived', y = 'Age', data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8111618668>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAFYCAYAAAB+s6Q9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f81115835f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x = 'Survived',y = 'Fare', data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f81116060f0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAFYCAYAAAB+s6Q9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8111642748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x = 'Pclass', y = 'Age', hue = 'Survived', data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f810e34c2e8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAFYCAYAAAB+s6Q9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f810e417320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x = 'Pclass', y = 'Age', hue = 'Survived', data = df, split = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f810e30e5c0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAf8AAAFYCAYAAABd6PXoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmWH4ExERyQzDn4iISGb+fy0cg/hIODlVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f810e314a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x = 'Pclass', y = 'Sex', hue = 'Survived', data = df, split = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f810e26c240>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe8AAAFYCAYAAAB6RnQAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nbwVs/MwoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f810e3b3d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x = 'Embarked', y = 'Pclass', hue = 'Survived', data = df, split = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f810e0d80b8>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAFYCAYAAAB+s6Q9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f81115ae160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x = 'Sex', y = 'Age', hue = 'Survived', data = df, split = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "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",
       "Cabin          687\n",
       "Embarked         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import Imputer\n",
    "imputer = Imputer(missing_values = 'NaN', strategy = 'mean')\n",
    "imputer = imputer.fit(df.iloc[:, 5:6])\n",
    "df.iloc[:, 5:6] = imputer.transform(df.iloc[:, 5:6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['Embarked'] = df['Embarked'].fillna('S')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "encoder = LabelEncoder()\n",
    "df['Sex'] = encoder.fit_transform(df['Sex'])\n",
    "encoder_embarked = LabelEncoder()\n",
    "df['Embarked'] = encoder_embarked.fit_transform(df['Embarked'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.get_dummies(df, columns = ['Pclass', 'Embarked'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['FamilySize'] = df['Parch'] + df['SibSp'] + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>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>Pclass_1</th>\n",
       "      <th>Pclass_2</th>\n",
       "      <th>Pclass_3</th>\n",
       "      <th>Embarked_0</th>\n",
       "      <th>Embarked_1</th>\n",
       "      <th>Embarked_2</th>\n",
       "      <th>FamilySize</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>1</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>0</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>0</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>1</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived                                               Name  \\\n",
       "0            1         0                            Braund, Mr. Owen Harris   \n",
       "1            2         1  Cumings, Mrs. John Bradley (Florence Briggs Th...   \n",
       "2            3         1                             Heikkinen, Miss. Laina   \n",
       "3            4         1       Futrelle, Mrs. Jacques Heath (Lily May Peel)   \n",
       "4            5         0                           Allen, Mr. William Henry   \n",
       "\n",
       "   Sex   Age  SibSp  Parch            Ticket     Fare Cabin  Pclass_1  \\\n",
       "0    1  22.0      1      0         A/5 21171   7.2500   NaN         0   \n",
       "1    0  38.0      1      0          PC 17599  71.2833   C85         1   \n",
       "2    0  26.0      0      0  STON/O2. 3101282   7.9250   NaN         0   \n",
       "3    0  35.0      1      0            113803  53.1000  C123         1   \n",
       "4    1  35.0      0      0            373450   8.0500   NaN         0   \n",
       "\n",
       "   Pclass_2  Pclass_3  Embarked_0  Embarked_1  Embarked_2  FamilySize  \n",
       "0         0         1           0           0           1           2  \n",
       "1         0         0           1           0           0           2  \n",
       "2         0         1           0           0           1           1  \n",
       "3         0         0           0           0           1           2  \n",
       "4         0         1           0           0           1           1  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(['PassengerId', 'Name', 'Ticket', 'Cabin', 'SibSp', 'Parch', ], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.to_csv('titanic_processed_data.csv', index = 0)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}