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DOC: Update parquet metadata format description around index levels #18201

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Dec 7, 2018
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DOC: Update parquet metadata format description around index levels #18201

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DOC: Update pyarrow format description around index levels
cpcloud Nov 9, 2017
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cpcloud Dec 7, 2017
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cpcloud Dec 7, 2017
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37 changes: 33 additions & 4 deletions doc/source/developer.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -50,15 +50,37 @@ So that a ``pandas.DataFrame`` can be faithfully reconstructed, we store a
'pandas_version': $VERSION}

Here, ``<c0>``/``<ci0>`` and so forth are dictionaries containing the metadata
for each column. This has JSON form:
for each column, *including the index columns*. This has JSON form:

.. code-block:: text

{'name': column_name,
'field_name': parquet_column_name,
'pandas_type': pandas_type,
'numpy_type': numpy_type,
'metadata': metadata}

.. note::

Every index column is stored with a name matching the pattern
``__index_level_\d+__`` and its corresponding column information is can be
found with the following code snippet.

Following this naming convention isn't strictly necessary, but strongly
suggested for compatibility with Arrow.

Here's an example of how the index metadata is structured in pyarrow:

.. code-block:: python
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Suggested change
.. code-block:: python
.. ipython:: python


# assuming there's at least 3 levels in the index
index_columns = metadata['index_columns']
columns = metadata['columns']
ith_index = 2
assert index_columns[ith_index] == '__index_level_2__'
ith_index_info = columns[-len(index_columns):][ith_index]
ith_index_level_name = ith_index_info['name']

``pandas_type`` is the logical type of the column, and is one of:

* Boolean: ``'bool'``
Expand Down Expand Up @@ -109,32 +131,39 @@ As an example of fully-formed metadata:
{'index_columns': ['__index_level_0__'],
'column_indexes': [
{'name': None,
'pandas_type': 'string',
'field_name': 'None',
'pandas_type': 'unicode',
'numpy_type': 'object',
'metadata': None}
'metadata': {'encoding': 'UTF-8'}}
],
'columns': [
{'name': 'c0',
'field_name': 'c0',
'pandas_type': 'int8',
'numpy_type': 'int8',
'metadata': None},
{'name': 'c1',
'field_name': 'c1',
'pandas_type': 'bytes',
'numpy_type': 'object',
'metadata': None},
{'name': 'c2',
'field_name': 'c2',
'pandas_type': 'categorical',
'numpy_type': 'int16',
'metadata': {'num_categories': 1000, 'ordered': False}},
{'name': 'c3',
'field_name': 'c3',
'pandas_type': 'datetimetz',
'numpy_type': 'datetime64[ns]',
'metadata': {'timezone': 'America/Los_Angeles'}},
{'name': 'c4',
'field_name': 'c4',
'pandas_type': 'object',
'numpy_type': 'object',
'metadata': {'encoding': 'pickle'}},
{'name': '__index_level_0__',
{'name': None,
'field_name': '__index_level_0__',
'pandas_type': 'int64',
'numpy_type': 'int64',
'metadata': None}
Expand Down