Use groupby
and agg
, and aggregate only unique values by calling Series.unique
:
df.astype(str).groupby('prop1').agg(lambda x: ','.join(x.unique()))
prop2 prop3 prop4
prop1
K20 12,1,66 travis,leo 10.0,4.0
L30 3,54,11,10 bob,john 11.2,10.0
df.astype(str).groupby('prop1', sort=False).agg(lambda x: ','.join(x.unique()))
prop2 prop3 prop4
prop1
L30 3,54,11,10 bob,john 11.2,10.0
K20 12,1,66 travis,leo 10.0,4.0
If handling NaNs is important, call fillna
in advance:
import re
df.fillna('').astype(str).groupby('prop1').agg(
lambda x: re.sub(',+', ',', ','.join(x.unique()))
)
prop2 prop3 prop4
prop1
K20 12,1,66 travis,leo 10.0,4.0
L30 3,54,11,10 bob,john 11.2,10.0
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