Description
Code Sample
df = pd.DataFrame({
'x': pd.Series([-np.inf, np.inf]),
'y': pd.Series(["a", "b"], dtype="category")
})
df.replace([-np.inf, np.inf], np.nan)results in
...
~/anaconda/envs/grapy/lib/python3.7/site-packages/pandas/core/indexes/base.py in __contains__(self, key)
3898 @Appender(_index_shared_docs["contains"] % _index_doc_kwargs)
3899 def __contains__(self, key) -> bool:
-> 3900 hash(key)
3901 try:
3902 return key in self._engine
TypeError: unhashable type: 'list'
Problem description
When a DF contains a categorical column, and when to_replace argument is a list, replace() throws TypeError: unhashable type: 'list'.
Expected Output
When the to_replace argument is a tuple rather than a list (which is not a documented option), all seems good:
df.replace((-np.inf, np.inf), np.nan) x y
0 NaN a
1 NaN b
Output of pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.7.6.final.0
python-bits : 64
OS : Darwin
OS-release : 19.2.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.0
pip : 20.0.2
setuptools : 45.2.0.post20200209
Cython : None
pytest : 5.3.5
hypothesis : None
sphinx : 2.4.3
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.12.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pytest : 5.3.5
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : None
numba : 0.48.0