When renaming some values in one of the levels of an index, any CategoricalIndex on other unrelated levels are suddenly no longer categorical.
Code Sample, a copy-pastable example if possible
import pandas as pd
mi = pd.MultiIndex.from_tuples([[2,2],[2,1],[1,2],[1,1]], names=list('AB'))
mi = mi.set_levels(pd.CategoricalIndex(mi.levels[0], categories=[2,1]), level='A')
a = pd.Series([1,2,3,4], index=mi)
b = a.rename({1:5}, level='B')
b.index.get_level_values('A')
returns
Int64Index([2, 2, 1, 1], dtype='int64', name='A')
Problem description
Index level 'A' should remain a CategoricalIndex after renaming values on index level 'B'.
Expected Output
The same as what we get when displaying a.index.get_level_values('A') (before renaming):
CategoricalIndex([2, 2, 1, 1], categories=[2, 1], ordered=False, name='A', dtype='category')
Output of pd.show_versions()
INSTALLED VERSIONS
------------------
commit : None
python : 3.6.6.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 : 1.17.1
pytz : 2019.2
dateutil : 2.8.0
pip : 19.2.3
setuptools : 39.0.1
Cython : 0.29.4
pytest : 4.2.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.1.2
lxml.etree : 4.3.4
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.1
IPython : 5.8.0
pandas_datareader: None
bs4 : 4.6.1
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.3.4
matplotlib : 2.2.4
numexpr : 2.6.9
odfpy : None
openpyxl : 2.5.12
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : 1.2.18
tables : None
xarray : 0.12.3
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.1.2
Comment From: theavey
Found this same issue. Any progress on a fix or workaround?