Create new column by grouping a single column in pandas dataframe

Question

I have a dataframe

df1 = pd.DataFrame({'value': [100, 100, 100, 200, 300, 300, 400], 'owner': list('aabbaba')}) value owner 100 a 100 a 100 b 200 b 300 a 300 b 400 a

I need to groupby the value column and produce a new output such that no duplicates exist in the value column. A value that is linked to both a and b should have an owner value of both while a value with only a single owner should just have that owner.

Output desired:

value owner 100 both 200 b 300 both 400 a

Thanks for the help

yatu · Accepted Answer · 2019-12-13 13:53:29Z

One approach is cheking the amount of unique values within each group, and use np.where to replace with either both or the unique value contained in a group:

import numpy as np out = df.groupby('value', as_index=False).agg({'owner':'nunique'}) out['owner'] = np.where(out.owner.eq(2), 'both', df.groupby('value').owner.first())

print(out) value owner 0 100 both 1 200 b 2 300 both 3 400 a

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