I want to group by one column (tag) and sum up the corresponding quantites (qty). The related reference no. column should be separated by commas
import pandas as pd
tag = ['PO_001045M100960','PO_001045M100960','PO_001045MSP2526','PO_001045M870191', 'PO_001045M870191', 'PO_001045M870191']
reference= ['PA_000003', 'PA_000005', 'PA_000001', 'PA_000002', 'PA_000004', 'PA_000009']
qty=[4,2,2,1,1,1]
df = pd.DataFrame({'tag' : tag, 'reference':reference, 'qty':qty})
tag reference qty
PO_001045M100960 PA_000003 4
PO_001045M100960 PA_000005 2
PO_001045MSP2526 PA_000001 2
PO_001045M870191 PA_000002 1
PO_001045M870191 PA_000004 1
PO_001045M870191 PA_000009 1
If I use df.groupby('tag')['qty'].sum().reset_index(), I am getting the following result.
tag qty
ASL_PO_000001045M100960 6
ASL_PO_000001045M870191 3
ASL_PO_000001045MSP2526 2
I need an additional column where the reference no. are added under the respective tags like,
tag qty refrence
ASL_PO_000001045M100960 6 PA_000003, PA_000005
ASL_PO_000001045M870191 3 PA_000002, PA_000004, PA_000009
ASL_PO_000001045MSP2526 2 PA_000001
How can I achieve this?
Thanks.
Use pandas.DataFrame.groupby.agg
:
df.groupby('tag').agg({'qty': 'sum', 'reference': ', '.join})
Output:
reference qty
tag
PO_001045M100960 PA_000003, PA_000005 6
PO_001045M870191 PA_000002, PA_000004, PA_000009 3
PO_001045MSP2526 PA_000001 2
Note: if reference
column is numeric, ', '.join
will not work. In such case, use lambda x: ', '.join(str(i) for i in x)
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