Pandas:通过组合索引和列名称来透视和展平列

好吧,经过几个小时的紧张搜索,我找到了一个简单的解决方案:

df.columns = [col[0] + f"_r{col[1]}" for col in df.columns]

我相信你需要 add_prefix 对于“更改列名称”,然后删除 column.name 通过 rename_axis reset_index :

df1 = df.pivot(index='date', columns='variable', values='value')

df1 = df1.add_prefix(df1.columns.name + '_').rename_axis(None, axis=1).reset_index()
print (df1)
         date  variable_A  variable_B  variable_C  variable_D
0  2000-01-03    0.469112   -1.135632    0.119209   -2.104569
1  2000-01-04   -0.282863    1.212112   -1.044236   -0.494929
2  2000-01-05   -1.509059   -0.173215   -0.861849    1.071804

编辑:

list comprehension :

mux = pd.MultiIndex.from_product([["A", "B", "C", "D"], ["X", "Y"]])
df = pd.DataFrame([np.arange(8)], columns=mux)
print(df)
   A     B     C     D   
   X  Y  X  Y  X  Y  X  Y
0  0  1  2  3  4  5  6  7

df.columns = [f"{a}_r{b}" for a, b in df.columns]
print (df)
   A_rX  A_rY  B_rX  B_rY  C_rX  C_rY  D_rX  D_rY
0     0     1     2     3     4     5     6     7