How to make types in the rows of pandas dataframe to become the column header with result as row type?

Question

I have a df structured in following setting and would like to change it so that the types found in the column type are the the row readers with the original result as the row the new type column, condensing all ids into one row. For example, I would like to change the following table:

id	name	type	result
A	Apple	1	X
A	Apple	2	X
A	Apple	3	X
B	Banana	1	Y
B	Banana	2	Y
C	Cantaloupe	2	Z
C	Cantaloupe	3	Z
...	...	...	...

To:

id	name	1	2	3
A	Apple	X	X	X
B	Banana	Y	Y	None
C	Cantaloupe	None	Z	Z
...	...	...

Check out .pivot() in the docs – CreekGeek Aug 21 '21 at 01:30 — CreekGeek, Aug 21 '21 at 01:30
`df.pivot(['id','name'],'type','result')` – Anurag Dabas Aug 21 '21 at 02:03 — Anurag Dabas, Aug 21 '21 at 02:03

score 0 · Accepted Answer · answered Aug 21 '21 at 01:32

Try pivot_table with rename_axis:

>>> df.pivot_table('result', ['id', 'name'], 'type', aggfunc=''.join).reset_index().rename_axis(columns=None)
  id        name    1  2    3
0  A       Apple    X  X    X
1  B      Banana    Y  Y  NaN
2  C  Cantaloupe  NaN  Z    Z
>>>

How to make types in the rows of pandas dataframe to become the column header with result as row type?

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