How to extend pandas Dataframe by values in multiindex column?

Question

I have a table with Multiindex getting by groupby():

new_data=data.groupby(['id','category']).sum('amount')
new_data

Output looks like that (just a random table with the same form as mine):

#               amount
#id category
1   2           12
    3           1
2   1           45
    3           56

Unique Id has some amount in each category.

But I need to get a table where is amount presented for each 'id' for each category in the same columns.

Something like that:

#id amount_category_1 amount_category_2 amount_category_3
1   0                 12                1
2   45                0                 56

Answer 1

Assuming that you reset the index of your dataframe and have it in the form:

   id  category  amount
0   1         1      45
1   1         3      34
2   2         2      36
3   2         3      24

you can pivot your dataframe and rename your columns:

df = df.pivot_table(index='id',columns='category',values='amount').rename_axis(None, axis=1).reset_index() 
df = df.rename(columns={c: 'category_'+ str(c) for c in df.columns if c not in ['id']})

to get somethng like this:

   id  category_1  category_2  category_3
0   1        45.0         NaN        34.0
1   2         NaN        36.0        24.0

Change NaN using df.fillna(0) to get

   id  category_1  category_2  category_3
0   1        45.0         0.0        34.0
1   2         0.0        36.0        24.0