Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({'a': [1, 2, 3, 10, 11, 1, 2, 3, 4, 10, 11], 'b':['a']*11})
In [3]: mkdir "tmp_dir"
In [4]: df.to_parquet("tmp_dir", partition_cols=['a'])
In [5]: df.dtypes
Out[5]:
a int64
b object
dtype: object
In [6]: pd.read_parquet("tmp_dir")
Out[6]:
b a
0 a 1
1 a 1
2 a 10
3 a 10
4 a 11
5 a 11
6 a 2
7 a 2
8 a 3
9 a 3
10 a 4
In [7]: pd.read_parquet("tmp_dir").dtypes
Out[7]:
b object
a category
dtype: object
In [8]: pd.read_parquet("tmp_dir")['a']
Out[8]:
0 1
1 1
2 10
3 10
4 11
5 11
6 2
7 2
8 3
9 3
10 4
Name: a, dtype: category
Categories (6, int32): [1, 10, 11, 2, 3, 4]Issue Description
When we partition a dataframe into multiple files using a column(a) in this case, and we read it back, the partitioned column is converted to categorical type of the original type. This is expected, but with pandas-2.0, the categorical type seems to be modifying the underlying type from int64 to int32. See example above & expected behavior.
Expected Behavior
In [8]: pd.read_parquet("tmp_dir")['a']
Out[8]:
0 1
1 1
2 10
3 10
4 11
5 11
6 2
7 2
8 3
9 3
10 4
Name: a, dtype: category
Categories (6, int64): [1, 10, 11, 2, 3, 4]Installed Versions
In [9]: pd.show_versions()
warnings.warn("Setuptools is replacing distutils.")
INSTALLED VERSIONS
commit : 37ea63d
python : 3.10.11.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-76-generic
Version : #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.0.1
numpy : 1.23.5
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.7.2
pip : 23.1.2
Cython : 0.29.34
pytest : 7.3.1
hypothesis : 6.75.3
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.13.2
pandas_datareader: None
bs4 : 4.12.2
bottleneck : None
brotli :
fastparquet : None
fsspec : 2023.5.0
gcsfs : None
matplotlib : None
numba : 0.56.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2023.5.0
scipy : 1.10.1
snappy :
sqlalchemy : 2.0.15
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None