In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.read_csv('data/src/titanic_train.csv', index_col=0).drop(['Name', 'Ticket', 'SibSp', 'Parch'], axis=1)


    

In [3]:

    

print(df.head())


    

    




             Survived  Pclass     Sex   Age     Fare Cabin Embarked
PassengerId                                                        
1                   0       3    male  22.0   7.2500   NaN        S
2                   1       1  female  38.0  71.2833   C85        C
3                   1       3  female  26.0   7.9250   NaN        S
4                   1       1  female  35.0  53.1000  C123        S
5                   0       3    male  35.0   8.0500   NaN        S

In [4]:

    

print(pd.crosstab(df['Sex'], df['Pclass']))


    

    




Pclass    1    2    3
Sex                  
female   94   76  144
male    122  108  347

In [5]:

    

print(type(pd.crosstab(df['Sex'], df['Pclass'])))


    

    




<class 'pandas.core.frame.DataFrame'>

In [6]:

    

print(pd.crosstab([df['Sex'], df['Survived']], [df['Pclass'], df['Embarked']]))


    

    




Pclass            1         2          3         
Embarked          C  Q   S  C  Q   S   C   Q    S
Sex    Survived                                  
female 0          1  0   2  0  0   6   8   9   55
       1         42  1  46  7  2  61  15  24   33
male   0         25  1  51  8  1  82  33  36  231
       1         17  0  28  2  0  15  10   3   34

In [7]:

    

print(pd.crosstab([df['Sex'], df['Survived']], [df['Pclass'], df['Embarked']],
                  margins=True))


    

    




Pclass            1           2           3           All
Embarked          C  Q    S   C  Q    S   C   Q    S     
Sex    Survived                                          
female 0          1  0    2   0  0    6   8   9   55   81
       1         42  1   46   7  2   61  15  24   33  231
male   0         25  1   51   8  1   82  33  36  231  468
       1         17  0   28   2  0   15  10   3   34  109
All              85  2  127  17  3  164  66  72  353  889

In [8]:

    

print(pd.crosstab([df['Sex'], df['Survived']], [df['Pclass'], df['Embarked']],
                  margins=True, margins_name='Total'))


    

    




Pclass            1           2           3          Total
Embarked          C  Q    S   C  Q    S   C   Q    S      
Sex    Survived                                           
female 0          1  0    2   0  0    6   8   9   55    81
       1         42  1   46   7  2   61  15  24   33   231
male   0         25  1   51   8  1   82  33  36  231   468
       1         17  0   28   2  0   15  10   3   34   109
Total            85  2  127  17  3  164  66  72  353   889

In [9]:

    

print(pd.crosstab(df['Sex'], df['Pclass'], margins=True, normalize=True))


    

    




Pclass         1         2         3       All
Sex                                           
female  0.105499  0.085297  0.161616  0.352413
male    0.136925  0.121212  0.389450  0.647587
All     0.242424  0.206510  0.551066  1.000000

In [10]:

    

print(pd.crosstab(df['Sex'], df['Pclass'], margins=True, normalize='index'))


    

    




Pclass         1         2         3
Sex                                 
female  0.299363  0.242038  0.458599
male    0.211438  0.187175  0.601386
All     0.242424  0.206510  0.551066

In [11]:

    

print(pd.crosstab(df['Sex'], df['Pclass'], margins=True, normalize='columns'))


    

    




Pclass         1         2         3       All
Sex                                           
female  0.435185  0.413043  0.293279  0.352413
male    0.564815  0.586957  0.706721  0.647587

In [12]:

    

# print(pd.crosstab(df['Sex'], [df['Pclass'], df['Embarked']],
#                   margins=True, normalize=True))
# TypeError: Expected tuple, got str


    

In [13]:

    

print(pd.crosstab(df['Sex'], [df['Pclass'], df['Embarked']],
                  margins=True, normalize='index'))


    

    




Pclass           1                             2                      \
Embarked         C         Q         S         C         Q         S   
Sex                                                                    
female    0.137821  0.003205  0.153846  0.022436  0.006410  0.214744   
male      0.072790  0.001733  0.136915  0.017331  0.001733  0.168111   
All       0.095613  0.002250  0.142857  0.019123  0.003375  0.184477   

Pclass           3                      
Embarked         C         Q         S  
Sex                                     
female    0.073718  0.105769  0.282051  
male      0.074523  0.067591  0.459272  
All       0.074241  0.080990  0.397075  

In [14]:

    

# print(pd.crosstab(df['Sex'], [df['Pclass'], df['Embarked']],
#                   margins=True, normalize='columns'))
# ValueError: Length of new names must be 1, got 2


    

In [15]:

    

print(pd.crosstab(df['Sex'], [df['Pclass'], df['Embarked']], normalize=True))


    

    




Pclass           1                             2                      \
Embarked         C         Q         S         C         Q         S   
Sex                                                                    
female    0.048369  0.001125  0.053993  0.007874  0.002250  0.075366   
male      0.047244  0.001125  0.088864  0.011249  0.001125  0.109111   

Pclass           3                     
Embarked         C        Q         S  
Sex                                    
female    0.025872  0.03712  0.098988  
male      0.048369  0.04387  0.298088  

In [16]:

    

print(pd.crosstab(df['Sex'], [df['Pclass'], df['Embarked']], normalize='index'))


    

    




Pclass           1                             2                      \
Embarked         C         Q         S         C         Q         S   
Sex                                                                    
female    0.137821  0.003205  0.153846  0.022436  0.006410  0.214744   
male      0.072790  0.001733  0.136915  0.017331  0.001733  0.168111   

Pclass           3                      
Embarked         C         Q         S  
Sex                                     
female    0.073718  0.105769  0.282051  
male      0.074523  0.067591  0.459272  

In [17]:

    

print(pd.crosstab(df['Sex'], [df['Pclass'], df['Embarked']], normalize='columns'))


    

    




Pclass           1                        2                             3  \
Embarked         C    Q         S         C         Q         S         C   
Sex                                                                         
female    0.505882  0.5  0.377953  0.411765  0.666667  0.408537  0.348485   
male      0.494118  0.5  0.622047  0.588235  0.333333  0.591463  0.651515   

Pclass                        
Embarked         Q         S  
Sex                           
female    0.458333  0.249292  
male      0.541667  0.750708