Pandas dataframe 与多索引列 - 更改级别

Question

source data：

pd.pivot_table(ceshi, values=['num1', 'num2'], index=['date'],
            columns=['c'], aggfunc={'num1': np.sum,'num2': np.sum}, fill_value=0)

how to transform to?：

Answer 1

Use DataFrame.swaplevel with DataFrame.sort_index :

df = pd.pivot_table(ceshi, values=['num1', 'num2'], index=['date'],
                   columns=['c'], aggfunc={'num1': np.sum,'num2': np.sum}, fill_value=0)

And then:

df = df.swaplevel(1,0, axis=1).sort_index(axis=1)