I have a data frame like shown below

If I pivot as shown below

df = pd.pivot_table(df, values=['runs', 'volume','revenue'],
                        index=['customer', 'organization', 'currency'],
                        columns=['Duration'],
                        aggfunc=sum,
                        fill_value=0
                  )

level = 0 becomes volume for all Duration (level 1) revenue for all Duration duration for all Duration.

I would like to pivot by Duration as level 0 and volume, revenue as level 2.

How to achieve it?

Current output:

I would like to have date as level 0 and volume, revenue and runs under it.

CodePudding user response：

You can use swaplevel like below in your current pivot code; try this;

df1 = df.pivot_table(index=['customer', 'organization', 'currency'],
                        columns=['Duration'],
                        aggfunc=sum,
                        fill_value=0).swaplevel(0,1, axis=1).sort_index(axis=1)

Hope this Helps...