BUG: PyArrow-backed DataFrame not exportable to Stata format

[maharris77]

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Reproducible Example

import pandas as pd
import pyarrow as pa
df = pd.DataFrame(data=[[1, 'a'], [2, 'b']],
                  index=[0, 1],
                  columns=['one', 'two'],
                  )
df = df.astype({'one': pd.ArrowDtype(pa.int64()),
                'two': pd.ArrowDtype(pa.string())})
df.to_stata('test_stata.dta', version=118)

Issue Description

The ArrowDtype columns are not recognized by the if/else logic of pandas.io.stata._dtype_to_default_stata_fmt, resulting in error with output:

"NotImplementedError: Data type int64[pyarrow] not supported."

I suspect this is true for all the PyArrow data types.

Note that fixing PyArrow issues in DataFrame.to_stata will also require recognizing PyArrow datetimes and dates in pandas.io.stata._prepare_pandas, for example replacing the line if lib.is_np_dtype(data[col].dtype, "M"): with if lib.is_np_dtype(data[col].dtype, "M") or is_datetime64_any_dtype(data[col].dtype): after importing the function is_datetime64_any_dtype from pandas.core.dtypes.common. However, I'm not sure that workaround handles all cases, including dates that are not datetimes (and maybe there is a faster C implementation?). I do not yet have a workaround for the dtype conversion logic that is the main issue.

Expected Behavior

Should run without error and output a Stata format (.dta) file.

Installed Versions

INSTALLED VERSIONS

commit : 6e194cf
python : 3.11.4.final.0
python-bits : 64
OS : Darwin
OS-release : 23.0.0
Version : Darwin Kernel Version 23.0.0: Tue Aug 1 03:24:46 PDT 2023; root:xnu-10002.0.242.0.6~31/RELEASE_ARM64_T8112
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 2.1.0rc0
numpy : 1.25.1
pytz : 2023.3
dateutil : 2.8.2
setuptools : 68.0.0
pip : 23.2.1
Cython : None
pytest : 7.4.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.3
html5lib : None
pymysql : None
psycopg2 : 2.9.6
jinja2 : 3.1.2
IPython : 8.7.0
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
brotli :
dataframe-api-compat: None
fastparquet : 2023.7.0
fsspec : 2023.6.0
gcsfs : None
matplotlib : 3.7.1
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 12.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.1
snappy : None
sqlalchemy : 1.4.47
tables : None
tabulate : None
xarray : 2023.7.0
xlrd : 2.0.1
zstandard : 0.19.0
tzdata : 2023.3
qtpy : None
pyqt5 : None

[mroeschke]

This is an issue for any extension type current as it appears the stata code always assumes numpy types

[chris-vecchio]

I'm having a similar issue with string columns converted from object to StringDType. The code below raises: NotImplementedError: Data type string not supported. I'm guessing StringDType is also an extension type? Any idea on if/when support for these types will be added? Thanks!

df = pd.DataFrame({'col1': ['a', 'b'], 'col2': [3, 4]})

df.dtypes
# col1    object
# col2     int64
# dtype: object
df = df.convert_dtypes()

df.dtypes
# col1    string[python]
# col2             Int64
# dtype: object

df.to_stata('test.dta', version=118)

Installed Versions

INSTALLED VERSIONS ------------------ commit : 2a953cf python : 3.11.5.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19045 machine : AMD64 processor : Intel64 Family 6 Model 154 Stepping 3, GenuineIntel byteorder : little LC_ALL : None LANG : en LOCALE : English_United States.1252

pandas : 2.1.3
numpy : 1.25.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.1.2
pip : 23.2.1
Cython : None
pytest : None
hypothesis : None
sphinx : 7.2.5
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.15.0
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.9.2
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.20
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
zstandard : None
tzdata : 2023.3
qtpy : 2.4.0
pyqt5 : None