PeterL PeterL - 1 year ago 289
Python Question

Using lambda if condition on different columns in Pandas dataframe

I have simple dataframe:

import pandas as pd
frame = pd.DataFrame(np.random.randn(4, 3), columns=list('abc'))

Thus for example:

a b c
0 -0.813530 -1.291862 1.330320
1 -1.066475 0.624504 1.690770
2 1.330330 -0.675750 -1.123389
3 0.400109 -1.224936 -1.704173

And then I want to create column “d” that contains value from “c” if c is positive. Else value from “b”.

I am trying:

frame['d']=frame.apply(lambda x: frame['c'] if frame['c']>0 else frame['b'],axis=0)

But getting “ValueError: ('The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().', 'occurred at index a')

I was trying to google how to solve this, but did not succeed. Any tip please?

Answer Source

is that what you want?

In [300]: frame[['b','c']].apply(lambda x: x['c'] if x['c']>0 else x['b'], axis=1)
0   -1.099891
1    0.582815
2    0.901591
3    0.900856
dtype: float64
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