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BUG: uint32 is not being preserved while round-tripping through parquet file #37327

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@galipremsagar

Description

@galipremsagar
  • I have checked that this issue has not already been reported.

  • I have confirmed this bug exists on the latest version of pandas.

  • (optional) I have confirmed this bug exists on the master branch of pandas.


Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

In[42]: df = pd.DataFrame({'a':pd.Series([1, 2, 3], dtype="uint64")})
In[43]: df.to_parquet('a')
In[44]: pd.read_parquet('a').dtypes
Out[44]: 
a    uint64
dtype: object
In[45]: df = pd.DataFrame({'a':pd.Series([1, 2, 3], dtype="uint32")})
In[46]: df.to_parquet('a')
In[47]: pd.read_parquet('a').dtypes
Out[47]: 
a    int64
dtype: object

Problem description

It appears to be that uint32 is not being preserved like uint64 is being preserved while round-tripping through a parquet file.

Expected Output

Preserve the uint32 dtype.

Output of pd.show_versions()

INSTALLED VERSIONS

commit : db08276
python : 3.7.8.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-52-generic
Version : #57-Ubuntu SMP Thu Oct 15 10:57:00 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.3
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.4
setuptools : 49.6.0.post20201009
Cython : 0.29.21
pytest : 6.1.1
hypothesis : 5.37.3
sphinx : 3.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.4
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.1
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.51.2

Crosslinking to cudf fuzz-testing for tracking purpose: rapidsai/cudf#6001

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