DataFrame.replace doesn't work with categorical data

[lovasoa]

Code Sample

import pandas as pd
df = pd.DataFrame(["x", "y", "z"], dtype='category')
df.replace({"x": "y"})

Problem description

Current output

~/.local/lib/python3.6/site-packages/pandas/core/internals.py in __init__(self, values, placement, ndim, fastpath)
    109             ndim = values.ndim
    110         elif values.ndim != ndim:
--> 111             raise ValueError('Wrong number of dimensions')
    112         self.ndim = ndim
    113 

ValueError: Wrong number of dimensions

Expected output

The following DataFrame:

   0
0  y
1  y
2  z

Explanation

At the very least, the error message is confusing. But I think this is a bug in the replace method, that should just work with categorical data.

This problem has confused other people before: https://stackoverflow.com/questions/48807344/how-to-replace-values-in-multiple-categoricals-in-a-pandas-dataframe

Output of pd.show_versions()

commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Linux
OS-release: 4.17.3-200.fc28.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8

pandas: 0.22.0
pytest: 3.3.2
pip: 9.0.3
setuptools: 39.2.0
Cython: 0.27.3
numpy: 1.14.1
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2018.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.9999999
sqlalchemy: 1.2.7
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[TomAugspurger]

Duplicate of #18250

As of 0.23 or master (not sure which) the categorical is coerced to objects and the replacement happens. Ideally it wouldn't coerce to object.