BUG: is_string_dtype(pd.Index([], dtype='O')) returns False

[flying-sheep]

Pandas version checks

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Reproducible Example

import pandas as pd
from pandas.api.types import is_string_dtype

assert is_string_dtype(pd.Index([], dtype='O'))

Issue Description

For object arrays it tests if all objects are strings. That test should be successful when 0 items are tested.

Expected Behavior

The assertion succeeds.

Installed Versions

INSTALLED VERSIONS

commit : 6e194cf
python : 3.10.12.final.0
python-bits : 64
OS : Linux
OS-release : 6.4.10-zen2-1-zen
Version : #1 ZEN SMP PREEMPT_DYNAMIC Sun, 13 Aug 2023 01:33:59 +0000
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : de_DE.UTF-8
LOCALE : de_DE.UTF-8

pandas : 2.1.0rc0
numpy : 1.24.4
pytz : 2023.3
dateutil : 2.8.2
setuptools : 68.1.0
pip : 23.2.1
Cython : None
pytest : 7.4.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : None
pandas_datareader : None
bs4 : None
bottleneck : None
brotli : None
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.6.0
gcsfs : None
matplotlib : 3.7.2
numba : 0.57.1
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.2
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[jesse-sealand]

Referring to:

pandas/pandas/core/dtypes/common.py

Line 137 in 61e54c2

def is_object_dtype(arr_or_dtype) -> bool:

is_object_dtype(np.array([], dtype=object))
True

The Object dtype can be a mix of other dtypes. It's not exclusive to strings. "All strings are objects but not all objects are strings."

[flying-sheep]

I’m aware. As I said:

For object arrays it tests if all objects are strings. That test should be successful when 0 items are tested.

[flying-sheep]

Only in that both are about is_string_dtype. I think the bug you linked is invalid. The issue author just didn’t realize that passing an actual string to it causes it to be interpreted as a dtype specification (like the argument passed to dtype('O')).

[natmokval]

I would like to work on this.

[Jamshaid1988]

df_temp['UsageBand'] = df_temp['UsageBand'].astype("string")
pd.api.types.is_string_dtype(df_temp['UsageBand'])

Hello, I am a student of data science.
Will this effect our model if we replace the object with the string?