[ARROW-6114] [Python] Datatypes not preserved for partition fields in roundtrip to partitioned parquet dataset

• Type: Bug
• Status: Open
• Priority: Major
• Resolution: Unresolved
• Affects Version/s: 0.14.1
• Component/s: Python
• Labels: dataset dataset-parquet-read parquet
• Environment: Python 3.7.3 ; pyarrow 0.14.1
• External issue URL: https://github.com/apache/arrow/issues/22510
• Assignee: Unassigned
• Reporter: Naga
• Created: 02/Aug/19 04:32
• Updated: 11/Jan/23 07:44

Description

Datatypes are not preserved when a pandas data frame is partitioned and saved as parquet file using pyarrow but that's not the case when the data frame is not partitioned.

Case 1: Saving a partitioned dataset - Data Types are NOT preserved

# Saving a Pandas Dataframe to Local as a partioned parquet file using pyarrow
import pandas as pd
df = pd.DataFrame( {'age': [77,32,234],'name':['agan','bbobby','test'] }
)
path = 'test'
partition_cols=['age']
print('Datatypes before saving the dataset')
print(df.dtypes)
table = pa.Table.from_pandas(df)
pq.write_to_dataset(table, path, partition_cols=partition_cols, preserve_index=False)

 # Loading a dataset partioned parquet dataset from local
df = pq.ParquetDataset(path, filesystem=None).read_pandas().to_pandas()
print('\nDatatypes after loading the dataset')
print(df.dtypes)

Output:

Datatypes before saving the dataset
age int64
name object
dtype: object

Datatypes after loading the dataset
name object
age category
dtype: object

From the above output, we could see that the data type for age is int64 in the original pandas data frame but it got changed to category when we saved to local and loaded back.

Case 2: Non-partitioned dataset - Data types are preserved

import pandas as pd
print('Saving a Pandas Dataframe to Local as a parquet file without partitioning using pyarrow')
df = pd.DataFrame(

{'age': [77,32,234],'name':['agan','bbobby','test'] }

)
path = 'test_without_partition'
print('Datatypes before saving the dataset')
print(df.dtypes)
table = pa.Table.from_pandas(df)
pq.write_to_dataset(table, path, preserve_index=False)
 # Loading a non-partioned parquet file from local
df = pq.ParquetDataset(path, filesystem=None).read_pandas().to_pandas()
print('\nDatatypes after loading the dataset')
print(df.dtypes)

Output:

Saving a Pandas Dataframe to Local as a parquet file without partitioning using pyarrow
Datatypes before saving the dataset
age int64
name object
dtype: object

Datatypes after loading the dataset
age int64
name object
dtype: object

Versions

• Python 3.7.3
• pyarrow 0.14.1

Issue Links

• depends upon: ARROW-8039 [Python][Dataset] Support using dataset API in pyarrow.parquet with a minimal ParquetDataset shim
• is related to: ARROW-5666 [Python] Underscores in partition (string) values are dropped when reading dataset
• is related to: ARROW-3388 [C++][Dataset] Automatically detect boolean partition columns