GroupBy and save each Occurence in Columns

Question

I have the following problem :

df

Key1     Key2      Value1     Value2     FixedValue
A        A         12         32         15
A        A         40         25         15
A        A         13         12         15
A        A         80         100        15
B        A         0          1          20
B        A         0          12         20
A        B         50         50         40
B        B         7          8          30

What I want is to create a new Dataframe, with only one line for each (Key1, Key2) couple, but creating new columns to keep the different values taken by Value1 and Value2 (see Output Example to understand better).
FixedValue directly depends to (Key1, Key2) so won’t change in time.
I’d like to limit to a certain number of new columns created, so my output doesn’t explode

Output wanted if I limit number of "new column by Value" to 3 :

Key1     Key2      Value1_1   Value1_2   Value1_3     Value2_1   Value2_2   Value2_3     FixedValue
A        A         12         40         13           32         25         12           15
B        A         0          0                       1          12                      20
A        B         50                                 50                                 40
B        B         7                                  8                                  30

I don’t mind the type of the blank going to non-existant values (they can be NaN, ”, … whatever)

Thanks in advance for your help

Asked By: Adept

||

Source

Answer 1

Use a pivot after filtering the number of rows to keep per group:

N = 3 # rows to keep per group

out = (df
 .assign(col=lambda d: d.groupby(['Key1', 'Key2']).cumcount().add(1))
 .query('col <= @N')
 .pivot(index=['Key1', 'Key2', 'FixedValue'],
        columns='col', values=['Value1', 'Value2']
       )
)

out.columns = out.columns.map(lambda x: f'{x[0]}_{x[1]}')
out = out.reset_index()

Output:

  Key1 Key2  FixedValue  Value1_1  Value1_2  Value1_3  Value2_1  Value2_2  Value2_3
0    A    A          15      12.0      40.0      13.0      32.0      25.0      12.0
1    A    B          40      50.0       NaN       NaN      50.0       NaN       NaN
2    B    A          20       0.0       0.0       NaN       1.0      12.0       NaN
3    B    B          30       7.0       NaN       NaN       8.0       NaN       NaN

Answered By: mozway

GroupBy and save each Occurence in Columns

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