BUG: `pandas.DataFrame.replace` silently fails to replace category type columns.

[corynezinstitchfix]

Pandas version checks

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• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

df = pd.DataFrame({"a": ["a", "b", float("nan")]})

df["a"] = df["a"].astype("category")

df = df.fillna(float("nan")).replace([float("nan")], [None])

print(df["a"].loc[2])

> nan

Issue Description

As of Pandas 2.0.0, pandas.DataFrame.replace now silently fails to replace math.nan with None on categorical type columns.

Expected Behavior

either:

1. nan should be replaced with None; or
2. an error should be raised.

Installed Versions

/Users/corynezin/.pyenv/versions/wearit/lib/python3.9/site-packages/_distutils_hack/init.py:33: UserWarning: Setuptools is replacing distutils.
warnings.warn("Setuptools is replacing distutils.")

INSTALLED VERSIONS

commit : 478d340
python : 3.9.10.final.0
python-bits : 64
OS : Darwin
OS-release : 21.6.0
Version : Darwin Kernel Version 21.6.0: Wed Aug 10 14:25:27 PDT 2022; root:xnu-8020.141.5~2/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.0.0
numpy : 1.23.5
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.6.1
pip : 23.0.1
Cython : None
pytest : 7.3.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.6
jinja2 : 3.1.2
IPython : 8.12.0
pandas_datareader: None
bs4 : 4.12.2
bottleneck : None
brotli : None
fastparquet : 2023.2.0
fsspec : 2023.4.0
gcsfs : None
matplotlib : 3.7.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
snappy : None
sqlalchemy : 2.0.9
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[phofl]

cc @lukemanley

Author: Luke Manley <lukemanley@gmail.com>
Date:   Tue Jan 24 14:02:33 2023 -0500

    BUG/PERF: Series(category).replace (#50857)

[lukemanley]

Thanks for the report @corynezinstitchfix.

The 1.5.3 behavior seems a bit odd to me (adjusting your example a bit):

import pandas as pd

df = pd.DataFrame({"a": ["a", "b", float("nan")]})

df["a"] = df["a"].astype("category")

# converts to object dtype (loses category) and replaces nan with None
df.replace([float("nan")], [None])

# no effect (does not replace nan with "c")
df.replace([float("nan")], ["c"])

In 2.0, both of those replace calls have no effect so I think 2.0 is a bit more consistent when replacing nan. I'm not a huge fan of the 1.5.3 behavior that loses the category dtype. If you want that behavior in 2.0, I think you could just do df.astype(object).replace(np.nan, None).

I'm not sure about raising an error either. At the moment, replacing a category that does not exist in the existing categorical dtype has no effect:

# no effect ("c" is not an existing category)
df.replace(["c], ["d"])

Since the nan is not actually one of the categories (it represents a missing value), I think you could argue it should also have no effect when trying to replace.

All of that said, I don't feel too strongly here. Open to other thoughts.

@phofl, any thoughts?

[lukemanley]

Looks like there is another open issue discussing replacing nan in a categorical: #40472

[phofl]

So we are avoiding losing the dtype now? This is a + imo. So sounds good. But should probably adjust whatsnew

[lukemanley]

So we are avoiding losing the dtype now? This is a + imo. So sounds good. But should probably adjust whatsnew

Correct, 2.0 no longer loses the dtype and casts to object. Replacing nan in a categorical now has no-effect regardless of replacement value. (1.5.3 had an edge case that would convert to object and replace if the replacement value was NA-like)

[phofl]

Sounds good to me.

@jbrockmendel any thoughts here?

[jbrockmendel]

There was an issue a while back (not specific to categorical) about replacing nan with None and the conclusion IIRC was to respect that the user specifically asked for that. If we want to raise and tell the user to explicitly case first I'd be OK with that, but I don't think silently ignoring what they specifically asked for is helpful.

Also note that trying to replace nan with non-na 4 or even a category "a" silently is a no-op. This is definitely a bug.