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DOC: update the parquet docstring #20129

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Merged
merged 8 commits into from
Mar 12, 2018
Merged

DOC: update the parquet docstring #20129

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6d25e6c
DOC: update the parquet docstring
benman1 Mar 10, 2018
14ed668
update order of sections; return type fixed
benman1 Mar 10, 2018
7b7f8bc
fix issues as suggested in discussion of pull request
benman1 Mar 10, 2018
7ec8537
ignore validation error for **kwargs argument as per jorisvandenbossche
benman1 Mar 10, 2018
39423cd
update links as per feedback on pull request
benman1 Mar 10, 2018
d08f6b2
fix pep8 long line
benman1 Mar 10, 2018
b5329d2
remove return section
jorisvandenbossche Mar 10, 2018
e65840c
Update frame.py
jorisvandenbossche Mar 12, 2018
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34 changes: 31 additions & 3 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1697,19 +1697,47 @@ def to_parquet(self, fname, engine='auto', compression='snappy',

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An extended summary is necessary.

.. versionadded:: 0.21.0

This function writes the dataframe as a `parquet file
<https://parquet.apache.org/>`_. You can choose different parquet
backends, and have the option of compression. See
:ref:`the user guide <io.parquet>` for more details.

Parameters
----------
fname : str
string file path
String file path.
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IIRC we use lower for these? @jorisvandenbossche

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Here it is fine as start of the sentence and not being the exact type

engine : {'auto', 'pyarrow', 'fastparquet'}, default 'auto'
Parquet library to use. If 'auto', then the option
``io.parquet.engine`` is used. The default ``io.parquet.engine``
behavior is to try 'pyarrow', falling back to 'fastparquet' if
'pyarrow' is unavailable.
compression : {'snappy', 'gzip', 'brotli', None}, default 'snappy'
Name of the compression to use. Use ``None`` for no compression.
kwargs
Additional keyword arguments passed to the engine
**kwargs
Additional arguments passed to the parquet library. See
:ref:`pandas io <io.parquet>` for more details.

See Also
--------
read_parquet : Read a parquet file.
DataFrame.to_csv : Write a csv file.
DataFrame.to_sql : Write to a sql table.
DataFrame.to_hdf : Write to hdf.

Notes
-----
This function requires either the `fastparquet
<https://pypi.python.org/pypi/fastparquet>`_ or `pyarrow
<https://arrow.apache.org/docs/python/>`_ library.

Examples
--------
>>> df = pd.DataFrame(data={'col1': [1, 2], 'col2': [3, 4]})
>>> df.to_parquet('df.parquet.gzip', compression='gzip')
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can you also show using read_parquet to read this back

>>> pd.read_parquet('df.parquet.gzip')
col1 col2
0 1 3
1 2 4
"""
from pandas.io.parquet import to_parquet
to_parquet(self, fname, engine,
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