Pandas Pivot Titanic: Find survival rate by gender, age of the different categories of various classes and fare

Pandas: Pivot Titanic Exercise-10 with Solution

Write a Pandas program to create a Pivot table and find survival rate by gender, age of the different categories of various classes. Add the fare as a dimension of columns and partition fare column into 2 categories based on the values present in fare columns. Go to Editor

Sample Solution:

Python Code :

import pandas as pd
import numpy as np
df = pd.read_csv('titanic.csv')
fare = pd.qcut(df['fare'], 2)
age = pd.cut(df['age'], [0, 10, 30, 60, 80])
result = df.pivot_table('survived', index=['sex', age], columns=[fare, 'pclass'])
print(result)

Sample Output:

fare            (-0.001, 14.454]              ...    (14.454, 512.329]          
pclass                         1         2    ...                    2         3
sex    age                                    ...                               
female (0, 10]               NaN       NaN    ...             1.000000  0.411765
       (10, 30]              NaN  0.933333    ...             0.904762  0.307692
       (30, 60]              NaN  0.846154    ...             0.941176  0.333333
       (60, 80]              NaN       NaN    ...                  NaN       NaN
male   (0, 10]               NaN       NaN    ...             1.000000  0.263158
       (10, 30]              NaN  0.034483    ...             0.000000  0.130435
       (30, 60]              0.0  0.130435    ...             0.047619  0.166667
       (60, 80]              NaN  0.333333    ...                  NaN       NaN

[8 rows x 6 columns]            

Python Code Editor:

Pivot Titanic.csv:

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