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Reproducible Example

import pandas as pd

df = pd.DataFrame({"x": [1, 2, 3, 4, 5], "y": list("caaab")})
df["y"] = df["y"].astype(pd.StringDtype("pyarrow"))
df["y"] = df["y"].astype("category")
df.to_parquet("test-arrow.parquet")

Issue Description

I have a dataframe with string[pyarrow]. I can convert it to category, but the resulting dataframe can't be written with to_parquet:

Traceback (most recent call last):
  File "/Users/jbennet/Library/Application Support/JetBrains/PyCharm2022.3/scratches/writeparquet_pyarrow.py", line 6, in <module>
    df.to_parquet("test-arrow.parquet")
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pandas/util/_decorators.py", line 211, in wrapper
    return func(*args, **kwargs)
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pandas/core/frame.py", line 2976, in to_parquet
    return to_parquet(
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pandas/io/parquet.py", line 430, in to_parquet
    impl.write(
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pandas/io/parquet.py", line 174, in write
    table = self.api.Table.from_pandas(df, **from_pandas_kwargs)
  File "pyarrow/table.pxi", line 3557, in pyarrow.lib.Table.from_pandas
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pyarrow/pandas_compat.py", line 611, in dataframe_to_arrays
    arrays = [convert_column(c, f)
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pyarrow/pandas_compat.py", line 611, in <listcomp>
    arrays = [convert_column(c, f)
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pyarrow/pandas_compat.py", line 598, in convert_column
    raise e
  File "/Users/jbennet/mambaforge/envs/pandas-dev/lib/python3.8/site-packages/pyarrow/pandas_compat.py", line 592, in convert_column
    result = pa.array(col, type=type_, from_pandas=True, safe=safe)
  File "pyarrow/array.pxi", line 310, in pyarrow.lib.array
  File "pyarrow/array.pxi", line 2608, in pyarrow.lib.DictionaryArray.from_arrays
  File "pyarrow/array.pxi", line 320, in pyarrow.lib.array
  File "pyarrow/array.pxi", line 39, in pyarrow.lib._sequence_to_array
  File "pyarrow/error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status
  File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: ("Could not convert <pyarrow.StringScalar: 'a'> with type pyarrow.lib.StringScalar: did not recognize Python value type when inferring an Arrow data type", 'Conversion failed for column y with type category')

Expected Behavior

Expected parquet file to be created.

Installed Versions

INSTALLED VERSIONS ------------------ commit : d9ba285ac159d4113f1990ecfd13eeb2dda0ad29 python : 3.8.16.final.0 python-bits : 64 OS : Darwin OS-release : 22.3.0 Version : Darwin Kernel Version 22.3.0: Thu Jan 5 20:50:36 PST 2023; root:xnu-8792.81.2~2/RELEASE_ARM64_T6020 machine : arm64 processor : arm byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.1.0.dev0+112.gd9ba285ac1 numpy : 1.23.5 pytz : 2022.7.1 dateutil : 2.8.2 setuptools : 67.4.0 pip : 23.0.1 Cython : 0.29.33 pytest : 7.2.1 hypothesis : 6.68.2 sphinx : 4.5.0 blosc : None feather : None xlsxwriter : 3.0.8 lxml.etree : 4.9.2 html5lib : 1.1 pymysql : 1.0.2 psycopg2 : 2.9.3 jinja2 : 3.1.2 IPython : 8.11.0 pandas_datareader: None bs4 : 4.11.2 bottleneck : 1.3.6 brotli : fastparquet : 2023.2.0 fsspec : 2023.1.0 gcsfs : 2023.1.0 matplotlib : 3.6.3 numba : 0.56.4 numexpr : 2.8.3 odfpy : None openpyxl : 3.1.0 pandas_gbq : None pyarrow : 11.0.0 pyreadstat : 1.2.1 pyxlsb : 1.0.10 s3fs : 2023.1.0 scipy : 1.10.1 snappy : sqlalchemy : 2.0.4 tables : 3.7.0 tabulate : 0.9.0 xarray : 2023.1.0 xlrd : 2.0.1 zstandard : 0.19.0 tzdata : None qtpy : None pyqt5 : None

Comment From: phofl

Hi, thanks for your report. This looks like a bug in pyarrow. Their conversion routine for categoricals can't deal with categories backed by pyarrow arrays and chunked arrays

Comment From: j-bennet

Filed a corresponding issue in pyarrow: https://github.com/apache/arrow/issues/34449.

Comment From: phofl

Small side-note: This happens for any pd.ArrowDtype, e.g. int64[pyarrow] has the same problem. Not exclusive to strings

Comment From: j-bennet

The original issue in pyarrow: https://github.com/apache/arrow/issues/33727.

This is the one to keep an eye on. https://github.com/apache/arrow/issues/34449 is a duplicate and now closed.

Comment From: jrbourbeau

Just following up here. https://github.com/apache/arrow/issues/33727 has been resolved upstream in arrow 🎉 I just tried the original failing code snippet using the latest nightly pyarrow and it now runs successfully. Probably still worth adding a regression test for this case though

Comment From: jrbourbeau

Looking a bit closer, the dtype of the categories isn't preserved when roundtripping through parquet

In [1]: import pandas as pd
   ...:
   ...: df = pd.DataFrame({"x": [1, 2, 3, 4, 5], "y": list("caaab")})
   ...: df["y"] = df["y"].astype(pd.StringDtype("pyarrow"))
   ...: df["y"] = df["y"].astype("category")
   ...: df.to_parquet("test-arrow.parquet")

In [2]: df2 = pd.read_parquet("test-arrow.parquet")

In [3]: df.y.dtype.categories
Out[3]: Index(['a', 'b', 'c'], dtype='string')

In [4]: df2.y.dtype.categories
Out[4]: Index(['a', 'b', 'c'], dtype='object')

The original categories are pyarrow strings, but reading the parquet dataset in gives object categories. I'm not sure if this is coming from the pandas or pyarrow side though