[jira] [Created] (ARROW-3651) [Python] Datetimes from non-DateTimeIndex cannot be deserialized

["Armin Berres (JIRA)" <ji...@apache.org>]

Armin Berres created ARROW-3651:
-----------------------------------

             Summary: [Python] Datetimes from non-DateTimeIndex cannot be deserialized
                 Key: ARROW-3651
                 URL: https://issues.apache.org/jira/browse/ARROW-3651
             Project: Apache Arrow
          Issue Type: Bug
          Components: Python
    Affects Versions: 0.11.1
            Reporter: Armin Berres


Given an index which contains datetimes but is no DateTimeIndex writing the file works but reading back fails.
{code:python}
df = pd.DataFrame(1, index=pd.MultiIndex.from_arrays([[1,2],[3,4]]), columns=[pd.to_datetime("2018/01/01")])

# columns index is no DateTimeIndex anymore
df = df.reset_index().set_index(['level_0', 'level_1'])

table = pa.Table.from_pandas(df)
pq.write_table(table, 'test.parquet')

pq.read_pandas('test.parquet').to_pandas()
{code}

results in 
{code}
KeyError                                  Traceback (most recent call last)
~/venv/mpptool/lib/python3.7/site-packages/pyarrow/pandas_compat.py in _pandas_type_to_numpy_type(pandas_type)
    676     try:
--> 677         return _pandas_logical_type_map[pandas_type]
    678     except KeyError:

KeyError: 'datetime'
{code}

The created schema:

{code}
2018-01-01 00:00:00: int64
level_0: int64
level_1: int64
metadata
--------
{b'pandas': b'{"index_columns": ["level_0", "level_1"], "column_indexes": [{"n'
            b'ame": null, "field_name": null, "pandas_type": "datetime", "nump'
            b'y_type": "object", "metadata": null}], "columns": [{"name": "201'
            b'8-01-01 00:00:00", "field_name": "2018-01-01 00:00:00", "pandas_'
            b'type": "int64", "numpy_type": "int64", "metadata": null}, {"name'
            b'": "level_0", "field_name": "level_0", "pandas_type": "int64", "'
            b'numpy_type": "int64", "metadata": null}, {"name": "level_1", "fi'
            b'eld_name": "level_1", "pandas_type": "int64", "numpy_type": "int'
            b'64", "metadata": null}], "pandas_version": "0.23.4"}'}
{code}



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