crosstab sometimes erroneously handles dt operations

[Eric-Sommer]

Code Sample

import pandas as pd
df = pd.DataFrame({'date': ['2019-01-01', '2019-02-01', '2018-01-01', '2018-02-01']})
df["date"] = pd.to_datetime(df["date"])
pd.crosstab(df["date"].dt.month, df["date"].dt.year)

Problem description

This gives my a 2x2 table with the years 2018 and 2019 on both axes, thus wrongly treating the dt.month operation. The same thing happens if I replace dt.month with dt.day in my example. Interestingly, pd.crosstab(df["date"].dt.day, df["date"].dt.month) works as expected, while pd.crosstab(df["date"].dt.month, df["date"].dt.day) does not!

Expected Output

year	2018	2019
month
1	1	1
2	1	1

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None

pandas : 0.25.1
numpy : 1.16.4
pytz : 2019.2
dateutil : 2.8.0
pip : 19.2.2
setuptools : 41.0.1
Cython : None
pytest : 5.0.1
hypothesis : 4.32.2
sphinx : 2.1.2
blosc : None
feather : None
xlsxwriter : 1.1.8
lxml.etree : 4.4.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.1
IPython : 7.8.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 2.6.2
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : 3.5.2
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.1.8

[TomAugspurger]

The following is correct

In [6]: pd.crosstab(df["date"].dt.month.rename('month'), df["date"].dt.year.rename('year'))
   ...:
   ...:
Out[6]:
year   2018  2019
month
1         1     1
2         1     1

Can you investigate what crosstab is supposed to do when the arguments have the same name? I agree that the behavior you show is surprising.

[TomAugspurger]

I think this is a duplicate of #22529