How to transform Pandas df for stacked bargraph

Question

I have the following df resulting from:

plt_df = df.groupby(['Aufnahme_periode','Preisgruppe','Land']).count()


INDEX  Aufnahme_periode  Preisgruppe Land  Anzahl
1344       2021-11-01            1   NL       2
1345       2021-12-01            1   AT       8
1346       2021-12-01            1   BE       1
1347       2021-12-01            1   CH       1
1348       2021-12-01            1   DE     154
1349       2021-12-01            1   GB       3
1350       2021-12-01            1   JP       1
1351       2021-12-01            1   NL       2
1352       2022-01-01            1   AT       1
1353       2022-01-01            1   DE      19
1354       2022-01-01            1   IT       1
1355       2022-01-01            2   CH       1
1356       2022-01-01            2   DE       1
1357       2022-02-01            1   DE      16
1358       2022-02-01            1   FR       1
1359       2022-02-01            2   CH       1
1360       2022-03-01            1   DE      23

I would like to make two bar charts:

1:

Monthly signup by "Preisgruppe" so stack group 2 on top of group 1:

The df should probably have columns for group 1 and 2 and rows for each month.

2:
Monthly signup by country:

Same as above, one column for each country and rows for the months.

I think I know how to make the charts, I just need help transforming the df.

Asked By: Joan Arau

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Source

Answer 1

You need a pivot_table:

(plt_df
 .pivot_table(index='Aufnahme_periode', columns='Preisgruppe',
              values='Anzahl', aggfunc='sum')
 .plot.bar(stacked=True)
)

output:

Same thing for the countries, just use 'Land' in place of 'Preisgruppe':

output:

Answered By: mozway

How to transform Pandas df for stacked bargraph

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