How to transform my grouped DataFrame column type rows into multiple columns

Question

I have the following DataFrame:

Id         Category        Amount
900000007  Schuur          8.0
900000009  Garage          24.0
           Dakkapel        5.0
900000015  Schuur          8.0
           Garage          20.0
           Dakkapel        5.0
900000019  Schuur          8.0
           Garage          18.0

So it's a list of Id's, a variable list of categories and an amount for each category that exists for that Id.

Now I want it to become like this:

Id         Schuur       Garage    Dakkapel
900000007  8.0          NaN       Nan
900000009  Nan          24.0      5.0
900000015  8.0          20.0      5.0
900000019  8.0          18.0      Nan

So the categories become the name of the columns, with one row for each Id and the amount filled in for each category. Please help me find the right function for this, thanks!

What is print (df.index) ?

jezrael
– jezrael

2022-10-14 09:35:02 +00:00
Commented Oct 14, 2022 at 9:35 — jezrael
– jezrael, Commented Oct 14, 2022 at 9:35
the index is 2000 x 1, so one column

Romy
– Romy

2022-10-14 09:39:56 +00:00
Commented Oct 14, 2022 at 9:39 — Romy
– Romy, Commented Oct 14, 2022 at 9:39

jezrael · Accepted Answer · 2022-10-14 09:46:49Z

1

If first 2 columns are levels of MultiIndex use Series.unstack with select column Amount:

df1 = df['Amount'].unstack()

edited Oct 14, 2022 at 9:46

answered Oct 14, 2022 at 9:34

jezrael

868k103 gold badges1.4k silver badges1.3k bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

How to transform my grouped DataFrame column type rows into multiple columns

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related