Pandas 具有多索引列的数据框 - 更改级别
Pandas dataframe with multiindex column - change levels
源数据:
pd.pivot_table(ceshi, values=['num1', 'num2'], index=['date'],
columns=['c'], aggfunc={'num1': np.sum,'num2': np.sum}, fill_value=0)
如何转化为:
使用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)
然后:
df = df.swaplevel(1,0, axis=1).sort_index(axis=1)
源数据:
pd.pivot_table(ceshi, values=['num1', 'num2'], index=['date'],
columns=['c'], aggfunc={'num1': np.sum,'num2': np.sum}, fill_value=0)
如何转化为:
使用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)
然后:
df = df.swaplevel(1,0, axis=1).sort_index(axis=1)