Pandas, create new column if previous column(s) are not in [None, '', np.nan]
codewizard at gmail.com
codewizard at gmail.com
Wed Apr 11 16:30:24 EDT 2018
On Wednesday, April 11, 2018 at 2:49:01 PM UTC-4, zlju... at gmail.com wrote:
> I have a dataframe:
>
> import pandas as pd
> import numpy as np
>
> df = pd.DataFrame( { 'A' : ['a', 'b', '', None, np.nan],
> 'B' : [None, np.nan, 'a', 'b', '']})
>
> A B
> 0 a None
> 1 b NaN
> 2 a
> 3 None b
> 4 NaN
>
>
> I would like to create column C in the following way:
> column C = column B if column B is not in [None, '', np.nan]
> else column A
>
> How to do that?
>
> I tried:
>
> df['C'] = df[['A', 'B']].apply(lambda x: x[1] if x[1] in [None, '', np.nan] else x[0])
>
> but I got all np.nan's.
>
> Where am I wrong?
>
> I am expecting to get column C as ['a', 'b', 'a', 'b', NaN]
>
> Regards.
Try this:
df['C'] = df['B'].where(df['B'], other=df['A'])
Regards,
Igor.
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