BUG: pd.Series.replace(to_replace=...) does not preserve the original dtype of the series · Issue #33484 · pandas-dev/pandas (original) (raw)

Code Sample, a copy-pastable example

s = pd.Series(["one", "two"], dtype="string") expected = pd.Series(["1", "2"], dtype="string") result = s.replace(to_replace={"one": "1", "two": "2"}) expected 0 1 1 2 dtype: string result 0 1 1 2 dtype: object

Problem description

The pandas.Series.replace does not return a series with the same dtype as the the original series. This behaviour is produced only when the replace function is called using the argument to_replace.

Notice: Similar behaviour is produced with other dtypes as well, this issue is not limited to string dtype.

The investigation should probably start here: /pandas/core/generic.py

Expected Output

We would expect the pandas.Series.replace(to_replace=...) to preserve the dtype of the series.
In the above code sample, both of the series should have a dtype of string.

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None python : 3.8.2.final.0 python-bits : 64 OS : Darwin OS-release : 19.4.0 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : None LOCALE : None.UTF-8

pandas : 1.0.3
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 46.1.3.post20200330
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : None