pandas: multiple row conditions based on different row values

Question

import pandas as pd
import numpy as np

colors = np.array(['blue','white', 'black', 'blue','white', 'black'])
money = np.array(['666', '777', '888','100', '300', '200'])

df = pd.DataFrame({'AAA': colors, 'BBB': money})
print(df)

output

hello,

what i want basically: where the row equals black, multiply the values on column BBB by 5, where the row equals white, multiply the values on column BBB by 10, and where the row equals blue, divide the values on column BBB by 7

thank you

What is your attempt to solve it? Please don't expect free answers here. — Mayank Porwal, May 01 '20 at 10:34
Does this answer your question? [Numpy "where" with multiple conditions](https://stackoverflow.com/questions/39109045/numpy-where-with-multiple-conditions) — Mayank Porwal, May 01 '20 at 13:15

score 0 · Accepted Answer · answered May 01 '20 at 10:33

0

df['BBB']= df['BBB'].astype('int')
df.loc[df.AAA=='black', 'BBB'] = df['BBB']*5
df.loc[df.AAA=='white', 'BBB'] = df['BBB']*10
df.loc[df.AAA=='blue', 'BBB'] = df['BBB']/7

answered May 01 '20 at 10:33

arpitrathi

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pandas: multiple row conditions based on different row values

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