Multi tool use

how to combine the data in dataframe

I am working with datasets having records in csv file as:

C_id C_Name S_Name Phone
97 [Bedsheet] Shree Collection 77422222
97 [Bedsheet] Shree Collection 77422222
105 [Jeans] Shree Collection 77422222
61 [Kurti] F Fashion 9040645
95 [Lehenga] Shree Collection 77422222
61 [Kurti] F Fashion 9040645
73 [Cotton Kurti] F Fashion 9040645
117 [Earring] Banti 90406459


I want to show the data the data as like :

C_id C_Name S_Name Phone
97,105,95 Bedsheet,Jeans,Lehenga Shree Collection 77422222
61,73 Kurti,Cotton Kurti F Fashion 9040645
117 Earring Banti 90406459


How can this be achieved

1 Answer
1

You can use groupby with agg and a couple of str.join functions. The parts where you need particular care:

groupby

agg

str.join

C_id

str.join

int

str

C_Name

itertools.chain

Here's a working example:

from itertools import chain

agg_funcs = {'C_id': lambda x: ','.join(map(str, x)),
'C_Name': lambda x: ','.join(chain.from_iterable(x))}

res = df.groupby(['S_Name', 'Phone']).agg(agg_funcs).reset_index()

print(res)

S_Name Phone C_id C_Name
0 Banti 90406459 117 Earring
1 F Fashion 9040645 61,61,73 Kurti,Kurti,Cotton Kurti
2 Shree Collection 77422222 97,97,105,95 Bedsheet,Bedsheet,Jeans,Lehenga


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