Categorical.replace returns unexpected dimensions for length 1 Series

[jseabold]

The shapes and types of the first two are unexpected. Should they be? Just upgraded to pandas 0.24.0.

pd.Series(pd.Categorical('A', categories=['A', 'B'])).replace({'A': 1, 'B': 2})
# Out[30]:
# 0    [1]
# dtype: object

pd.Series(pd.Categorical(('A', ), categories=['A', 'B'])).replace({'A': 1, 'B': 2})
# Out[31]:
# 0    [1]
# dtype: object

pd.Series(pd.Categorical(('A', 'B'), categories=['A', 'B'])).replace({'A': 1, 'B': 2})
# Out[32]:
# 0    1
# 1    2
# dtype: int64

I expect the first to be an int64 dtype with a shape of (1,). They return a Series with shape (1, 1) and dtype object.

INSTALLED VERSIONS ------------------ commit: None python: 3.7.0.final.0 python-bits: 64 OS: Linux OS-release: 4.4.0-116-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8

pandas: 0.24.0
pytest: 4.1.1
pip: 18.1
setuptools: 40.2.0
Cython: None
numpy: 1.15.4
scipy: 1.2.0
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2018.7
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: 1.2.15
pymysql: None
psycopg2: 2.7.6.1 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

[jorisvandenbossche]

@jseabold Thanks for the report!

What version were you using before upgrading? I see this buggy behaviour in 0.23.4 as well.

[jseabold]

What version were you using before upgrading?

I was using 0.23.4. I upgraded to see if another bug was fixed (it was), which revealed this one for me. Don't know anything about whether this code would have worked in an older version.

[jorisvandenbossche]

OK, just to know whether it was a regression or not. Of course it is still a clear bug, but if it was a regression compared to 0.23.4, we should have tried to give it priority.