How to create a new column with values ​​selected based on an existing column?

Question content

How to add the color column to the following dataframe so that color='green' If set == 'z', otherwise color='red'?

Type  Set
1     A    Z
2     B    Z           
3     B    X
4     C    Y

Correct Answer

If you only have two choices, use np.where:

df['color'] = np.where(df['set']=='z', 'green', 'red')

For example,

import pandas as pd
import numpy as np

df = pd.dataframe({'type':list('abbc'), 'set':list('zzxy')})
df['color'] = np.where(df['set']=='z', 'green', 'red')
print(df)

Yield

set type  color
0   z    a  green
1   z    b  green
2   x    b    red
3   y    c    red

If you have more than two conditions, use np.select. For example, if you want color to be

• yellow When (df['set'] == 'z') & (df['type'] == 'a')
• Otherwise blue When (df['set'] == 'z') & (df['type'] == 'b')
• Otherwise purple when (df['type'] == 'b')
• Otherwise black,

Then use

df = pd.dataframe({'type':list('abbc'), 'set':list('zzxy')})
conditions = [
    (df['set'] == 'z') & (df['type'] == 'a'),
    (df['set'] == 'z') & (df['type'] == 'b'),
    (df['type'] == 'b')]
choices = ['yellow', 'blue', 'purple']
df['color'] = np.select(conditions, choices, default='black')
print(df)

produce

Set Type   color
0   Z    A  yellow
1   Z    B    blue
2   X    B  purple
3   Y    C   black

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