Unable to get the groupby column of same numeric column-CodePudding

Below is the dataframe

df = pd.DataFrame({'Cust_Pincode':[487551,487551,639207,452001,484661,484661],
                   'REGIONAL_GROUPING':['WEST I','WEST II','TN II','WEST I','WEST I','WEST II'],
                   'C_LATITUDE':[22.89831,23.74881,10.72208,22.69875,23.88280,23.88280],
                   'C_LONGITUDE':[78.75441,79.48472,77.94168,75.88575,80.98250,80.98250],
                   'Region_dist_lim':[33.577743,33.577743,36.812093,33.577743,33.577743,33.577743]})


Cust_Pincode    REGIONAL_GROUPING   C_LATITUDE  C_LONGITUDE Region_dist_lim
0   487551  WEST I  22.89831    78.75441    33.577743
1   487551  WEST II 23.74881    79.48472    33.577743
2   639207  TN II   10.72208    77.94168    36.812093
3   452001  WEST I  22.69875    75.88575    33.577743
4   484661  WEST I  23.88280    80.98250    33.577743
5   484661  WEST II 23.88280    80.98250    33.577743

I'm trying to write a code which will return unique Cust_Pincode has different REGIONAL_GROUPING. groupby on cust_pincode, regional_grouping and return the dataframe where cust_pincode has multiple regional grouping value. Below is the expected output dataframe

    Cust_Pincode   REGIONAL_GROUPING
                   WEST I
0    487551               
                   WEST II
                   WEST I
1    484661
                   WEST II

The code which i've written is below

df.groupby(['Cust_Pincode','REGIONAL_GROUPING']).filter(lambda x: len(x) > 1)

The above code is not giving any output

CodePudding user response：

You can try this solution

df = df.groupby(['Cust_Pincode']).filter(lambda x: len(x) > 1)
print(df.groupby(['Cust_Pincode', 'REGIONAL_GROUPING']).first())

CodePudding user response：

Why use filter()? You can just use first() like this:

df.groupby(['Cust_Pincode','REGIONAL_GROUPING']).first()