Pandas, Create Columns After Groupby

Regarding the Pandas DataFrame 'test_df': id_customer id_order product_name 3 78 product1 3 79 product2 3 80

Solution 1:

Note: I recommend using head to do this rather than using multiple columns:

In [11]: g = df.groupby('id_customer')

In [12]: g.head(2)
Out[12]:
   id_customer  id_order product_name
0378     product1
1379     product2
37100     product4
49109     product5

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You can combine the 0th and 1st using nth and then concat these:

In [21]: g = df.groupby('id_customer')

In [22]: g[['id_order', 'product_name']].nth(0)
Out[22]:
             id_order product_name
id_customer
378     product1
7100     product4
9109     product5

In [23]: g[['id_order', 'product_name']].nth(1)
Out[23]:
             id_order product_name
id_customer
379     product2

In [24]: a = g[['id_order', 'product_name']].nth(0)
         b = g[['id_order', 'product_name']].nth(1)

In [25]: pd.concat([a, b], axis=1)
Out[25]:
             id_order product_name  id_order product_name
id_customer
378     product1        79     product2
7100     product4       NaN          NaN
9109     product5       NaN          NaN