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Support str param type for partition_cols in to_parquet function #27984

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Support str param type for partition_cols in to_parquet function #27984

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3995d5a
Added check for string in partition_cols
Aug 17, 2019
93c4613
Added unit tests for PyArrow and FastParquet where partition_cols is …
Aug 18, 2019
afd10c4
Added docstring to to_parquet function
Aug 18, 2019
ec927c3
Deleted misadded code
Aug 18, 2019
dde77c3
Merge pull request #1 from JeanRoca/issue-27117
unchecked9 Aug 18, 2019
209eb7e
format with black pandas
Aug 18, 2019
270e2c5
Fix issue from flake8
Aug 18, 2019
d200305
Fix issue with earlier commit
Aug 18, 2019
84ae85b
Add partition_cols_list variable
Aug 18, 2019
22075e7
Add whatsnew entry
Aug 18, 2019
1d4c3d0
Move to 1.0.0 whtsnew and add a versionchanged to docstring
Aug 20, 2019
c30029e
Update doc/source/whatsnew/v0.25.1.rst
unchecked9 Aug 27, 2019
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7 changes: 4 additions & 3 deletions pandas/core/frame.py
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Expand Up @@ -2156,9 +2156,10 @@ def to_parquet(

.. versionadded:: 0.24.0

partition_cols : list, optional, default None
Column names by which to partition the dataset
Columns are partitioned in the order they are given
partition_cols : list or string, optional, default None
Column names by which to partition the dataset.
Columns are partitioned in the order they are given.
String identifies a single column to be partitioned.

.. versionadded:: 0.24.0
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Can you add a .. versionchanged:: 1.0.0 explaining that passing a single string was added in 1.0?

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I think I added it correctly. This is my first contribution so bear with me please :)

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You can put the .. versionchanged:: ... right below the parameter explanation (so since there is already a ..versionadded:: 0.24.0, it would go just below that


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9 changes: 6 additions & 3 deletions pandas/io/parquet.py
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Expand Up @@ -235,15 +235,18 @@ def to_parquet(

.. versionadded:: 0.24.0

partition_cols : list, optional, default None
Column names by which to partition the dataset
Columns are partitioned in the order they are given
partition_cols : list or string, optional, default None
Column names by which to partition the dataset.
Columns are partitioned in the order they are given.
String identifies a single column to be partitioned.

.. versionadded:: 0.24.0

kwargs
Additional keyword arguments passed to the engine
"""
if isinstance(partition_cols, str):
partition_cols = [partition_cols]
impl = get_engine(engine)
return impl.write(
df,
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29 changes: 29 additions & 0 deletions pandas/tests/io/test_parquet.py
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Expand Up @@ -473,6 +473,18 @@ def test_partition_cols_supported(self, pa, df_full):
assert len(dataset.partitions.partition_names) == 2
assert dataset.partitions.partition_names == set(partition_cols)

def test_partition_cols_string(self, pa, df_full):
# GH #23283
partition_cols = "bool"
df = df_full
with tm.ensure_clean_dir() as path:
df.to_parquet(path, partition_cols=partition_cols, compression=None)
import pyarrow.parquet as pq

dataset = pq.ParquetDataset(path, validate_schema=False)
assert len(dataset.partitions.partition_names) == 1
assert dataset.partitions.partition_names == set([partition_cols])

def test_empty_dataframe(self, pa):
# GH #27339
df = pd.DataFrame()
Expand Down Expand Up @@ -543,6 +555,23 @@ def test_partition_cols_supported(self, fp, df_full):
actual_partition_cols = fastparquet.ParquetFile(path, False).cats
assert len(actual_partition_cols) == 2

def test_partition_cols_string(self, fp, df_full):
# GH #23283
partition_cols = "bool"
df = df_full
with tm.ensure_clean_dir() as path:
df.to_parquet(
path,
engine="fastparquet",
partition_cols=partition_cols,
compression=None,
)
assert os.path.exists(path)
import fastparquet # noqa: F811

actual_partition_cols = fastparquet.ParquetFile(path, False).cats
assert len(actual_partition_cols) == 1

def test_partition_on_supported(self, fp, df_full):
# GH #23283
partition_cols = ["bool", "int"]
Expand Down