Renaming columns in pandas dataframe during groupby operation

Question

I tried to rename the column that has been obtained as the result of groupby & count operation like below:

dfa = df.groupby('Product_ID').Product_ID.count().rename(columns={0: "Product",1:"Sale_count"}).reset_index()
print(dfa[:1])

the output obtained is

 Product_ID     0
0  P00000142  1130

The column names are not what I specified. So I changed it again using the below command

dfa.columns =['product','sales']
print(dfa[:1])

 product  sales
0  P00000142   1130

Then I got the expected column names. However I believe it shall be obtained during the first method dataframe.rename itself. What is wrong in the 1st code snippet dfa = df.groupby('Product_ID').Product_ID.count().rename(columns={0: "Product",1:"Sale_count"}).reset_index()that I did not get the expected output.

do you need df.groupby('Product_ID').size().reset_index(name='sales_count') ? — anky
– anky, Commented May 29, 2019 at 5:18
df.groupby('Product_ID').Product_ID.count() will result in a series, not a dataframe. Your output, however, is a dataframe. It seems that your code is not quite correct, or else the output looks to be inconsistent. — Alexander
– Alexander, Commented May 29, 2019 at 5:24

anky · Accepted Answer · 2019-05-29 05:25:59Z

2

As mentioned in comments, you need:

df.groupby('Product_ID').size().reset_index(name='sales_count')

answered May 29, 2019 at 5:25

anky

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