Pandas Pivot Titanic: Partition each of the passengers into four categories based on their age
7. Partition Passengers into Age Categories
Write a Pandas program to partition each of the passengers into four categories based on their age. Go to Editor
Note: Age categories (0, 10), (10, 30), (30, 60), (60, 80)
Sample Solution:
Python Code :
import pandas as pd
import numpy as np
df = pd.read_csv('titanic.csv')
result = pd.cut(df['age'], [0, 10, 30, 60, 80])
print(result)
Sample Output:
0 (10, 30]
1 (30, 60]
2 (10, 30]
3 (30, 60]
4 (30, 60]
5 NaN
6 (30, 60]
7 (0, 10]
8 (10, 30]
9 (10, 30]
10 (0, 10]
11 (30, 60]
12 (10, 30]
13 (30, 60]
14 (10, 30]
15 (30, 60]
16 (0, 10]
17 NaN
18 (30, 60]
19 NaN
20 (30, 60]
21 (30, 60]
22 (10, 30]
23 (10, 30]
24 (0, 10]
25 (30, 60]
26 NaN
27 (10, 30]
28 NaN
29 NaN
...
861 (10, 30]
862 (30, 60]
863 NaN
864 (10, 30]
865 (30, 60]
866 (10, 30]
867 (30, 60]
868 NaN
869 (0, 10]
870 (10, 30]
871 (30, 60]
872 (30, 60]
873 (30, 60]
874 (10, 30]
875 (10, 30]
876 (10, 30]
877 (10, 30]
878 NaN
879 (30, 60]
880 (10, 30]
881 (30, 60]
882 (10, 30]
883 (10, 30]
884 (10, 30]
885 (30, 60]
886 (10, 30]
887 (10, 30]
888 NaN
889 (10, 30]
890 (30, 60]
Name: age, Length: 891, dtype: category
Categories (4, interval[int64]): [(0, 10] < (10, 30] < (30, 60] < (60, 80]]
For more Practice: Solve these Related Problems:
- Write a Pandas program to import titanic.csv and partition passengers into four age groups: (0,10), (10,30), (30,60), (60,80).
- Write a Pandas program to create an age category column in titanic.csv using cut() with the specified age intervals.
- Write a Pandas program to add a new column to titanic.csv that labels passengers according to the four specified age categories.
- Write a Pandas program to partition the passenger ages into the defined groups and then count the number of passengers in each group.
Python Code Editor:
Pivot Titanic.csv:
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