Modifying values in a pandas dataframe column given a different column has a desired value

Question

So I have a dataframe that looks like this:

import pandas as pd
import numpy as np
df = pd.DataFrame({'A': 'foo bar foo bar foo bar foo foo'.split(),
               'B': 'one one two three two two one three'.split(),
               'C': np.arange(8), 'D': np.zeros(8)})

The output looks like this:

print(df)
     A      B  C    D
0  foo    one  0  0.0
1  bar    one  1  0.0
2  foo    two  2  0.0
3  bar  three  3  0.0
4  foo    two  4  0.0
5  bar    two  5  0.0
6  foo    one  6  0.0
7  foo  three  7  0.0

What I now want to do is consider column C and if its values are odd numbers, change the corresponding D value to 1 and if they are even, keep it 0.

How do I do that? I am very new to python and I am kind of confused. Any help would be appreciated.

Quang Hoang · Accepted Answer · 2020-09-30 18:00:36Z

2

Is it:

df['D'] = df['C'] % 2

Or if current 0 values in D are just representative, and you only want to change the specific rows, you can use loc:

df.loc[(df['C'] % 2)==1, 'D'] = 1

Output:

     A      B  C  D
0  foo    one  0  0
1  bar    one  1  1
2  foo    two  2  0
3  bar  three  3  1
4  foo    two  4  0
5  bar    two  5  1
6  foo    one  6  0
7  foo  three  7  1

answered Sep 30, 2020 at 18:00

Quang Hoang

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1 Comment

time12 Over a year ago

Did the job for me. Thanks a lot. :) I was looking for the second one.

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