Fix inconsistent results for pd.api.types.is_string_dtype #62112
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…th Categorical series vs dtype
## Description
This PR fixes an inconsistency in `pd.api.types.is_string_dtype()` when passed a Categorical series directly versus the dtype of that series.
Currently:
```python
import pandas as pd
series = pd.Categorical(['A', 'B', 'C'])
print(f"is_string_dtype(series): {pd.api.types.is_string_dtype(series)}") # True
print(f"is_string_dtype(series.dtype): {pd.api.types.is_string_dtype(series.dtype)}") # False
```
The issue is that when a Categorical series is passed, the function correctly checks if the categories are strings, but when a Categorical dtype is passed directly, it doesn't handle it properly.
## Fix
The fix adds explicit handling for CategoricalDtype in both cases (series and dtype) to ensure consistent behavior.
## Test Plan
Added a new test file `test_categorical_string_dtype.py` with tests that verify the consistent behavior for both Categorical series and their dtypes.
Fixes pandas-dev#62109
MengAiDev
changed the title
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Description
This PR fixes an inconsistency in
pd.api.types.is_string_dtype()when passed a Categorical series directly versus the dtype of that series.Currently:
The issue is that when a Categorical series is passed, the function correctly checks if the categories are strings, but when a Categorical dtype is passed directly, it doesn't handle it properly.
Fix
The fix adds explicit handling for CategoricalDtype in both cases (series and dtype) to ensure consistent behavior.
Test Plan
Added a new test file
test_categorical_string_dtype.pywith tests that verify the consistent behavior for both Categorical series and their dtypes.Fixes #62109