# Adjusted from  https://github.com/pandas-dev/pandas/issues/54875
# that has been solved for row MultiIndex.
# Would like it to work for column MultiIndex as well.
import pandas as pd
import numpy as np

# * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
# This part is just to create the example dataframes. It could be more elegant.

Lev1L = ["1A", "1B"]
Lev2L = ["2A", "2B"]
rix1 = pd.MultiIndex.from_product([Lev1L, Lev2L], names=["Lev1", "Lev2"])
rix2 = pd.MultiIndex.from_product([Lev1L], names=["Lev1"])
ColL = ["C1", "C2"]
df1 = pd.DataFrame(data=100, index=rix1, columns=ColL)
df2 = pd.DataFrame(data=np.array([[0.1, 0.2], [0.25, 0.45]]), index=rix2, columns=ColL)
df1.columns.name = "Lev10"
df2.columns.name = "Lev10"
df1t = df1.T
df2t = df2.T

# * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
# ROW alignment .. works

print("\n" + "-" * 10 + " ROW MultiIndex\n")
print(df1)
print()
print(df2)
df3 = df1.mul(df2)
print()
print(df3)

# * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
# COL alignment .. fails

print("\n" + "-" * 10 + " COL MultiIndex\n")
print(df1t)
print()
print(df2t)

df3t = df1t.mul(df2t)  #  AssertionError: Length of new_levels (2) must be <= self.nlevels (1)
print()
print(df3t)

"""
---------- ROW MultiIndex

Lev10       C1   C2
Lev1 Lev2
1A   2A    100  100
     2B    100  100
1B   2A    100  100
     2B    100  100

Lev10    C1    C2
Lev1
1A     0.10  0.20
1B     0.25  0.45

Lev10        C1    C2
Lev1 Lev2
1A   2A    10.0  20.0
     2B    10.0  20.0
1B   2A    25.0  45.0
     2B    25.0  45.0

---------- COL MultiIndex

Lev1    1A        1B
Lev2    2A   2B   2A   2B
Lev10
C1     100  100  100  100
C2     100  100  100  100

Lev1    1A    1B
Lev10
C1     0.1  0.25
C2     0.2  0.45
"""

"""
Lev1    1A          1B
Lev2    2A   2B     2A    2B
Lev10
C1     10.0  10.0   25.0  25.0
C2     20.0  20.0   45.0  45.0
"""