BUG: exponential moving window covariance fails for multiIndexed DataFrame

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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

import pandas as pd
import numpy as np 

columns = pd.MultiIndex.from_product([['a','b','c'],['x','y','w','z'], list(range(9))])
index = range(1000)
df = pd.DataFrame(
    np.random.normal(size=(len(index), len(columns))),
    index=index,
    columns=columns
    )
    
df.ewm(alpha=0.1).cov()  #Throws AssertionError: Length of order must be same as number of levels (4), got 3

Problem description

When calculating ewm covariance, pandas fails when the DataFrame has multiindex columns. However it works when columns are simple Index dataframes. It works for:

pd.DataFrame(df.values).ewm(alpha=0.1).cov()

Expected Output

The covariance, actually only the last matrix (last level of index)

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None python : 3.7.7.final.0 python-bits : 64 OS : Windows OS-release : 10 machine : AMD64 processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : None.None

pandas : 1.0.3 numpy : 1.18.1 pytz : 2019.3 dateutil : 2.8.1 pip : 20.0.2 setuptools : 46.1.3.post20200330 Cython : 0.29.15 pytest : 5.4.1 hypothesis : 5.8.3 sphinx : 2.4.4 blosc : None feather : None xlsxwriter : 1.2.8 lxml.etree : 4.5.0 html5lib : 1.0.1 pymysql : None psycopg2 : None jinja2 : 2.11.1 IPython : 7.13.0 pandas_datareader: None bs4 : 4.9.0 bottleneck : 1.3.2 fastparquet : None gcsfs : None lxml.etree : 4.5.0 matplotlib : 3.1.3 numexpr : 2.7.1 odfpy : None openpyxl : 3.0.3 pandas_gbq : None pyarrow : 0.15.1 pytables : None pytest : 5.4.1 pyxlsb : None s3fs : None scipy : 1.4.1 sqlalchemy : 1.3.16 tables : 3.6.1 tabulate : 0.8.3 xarray : None xlrd : 1.2.0 xlwt : 1.3.0 xlsxwriter : 1.2.8 numba : 0.49.0

[jorisvandenbossche]

@PablocFonseca thanks for the report, and @arw2019 thanks for the confirmation and simple reproducer!

It’s also failing on 0.25

[Dinkarkumar]

I want to work on this issue.