timestamp_as_object support for pa.Table.to_pandas in pyarrow

[joetl]

pyarrow (Issue with timestamp conversion from arrow to pandas)

pyarrow Table.to_pandas has option date_as_object but does not have similar option for timestamp. When a timestamp column in arrow table is converted to pandas the target datetype is pd.Timestamp and pd.Timestamp does not handle time > 2262-04-11 23:47:16.854775807 and hence in the below scenario the date is transformed to incorrect value. Adding timestamp_as_object option in pa.Table.to_pandas will help in this scenario.

#Python(3.6.8)

import pandas as pd

import pyarrow as pa

pd.version
'0.24.1'

pa.version
'0.13.0'

import datetime

df = pd.DataFrame({"test_date": [datetime.datetime(3000,12,31,12,0),datetime.datetime(3100,12,31,12,0)]})

df
test_date
0 3000-12-31 12:00:00
1 3100-12-31 12:00:00

pa_table = pa.Table.from_pandas(df)

pa_table[0]
Column name='test_date' type=TimestampType(timestamp[us])
[
[
32535172800000000,
35690846400000000
]
]

pa_table.to_pandas()
test_date
0 1831-11-22 12:50:52.580896768
1 1931-11-22 12:50:52.580896768

[xhochy]

@joetl Can you open an issue in JIRA about this?

[wesm]

@joetl can you open a JIRA issue?

[joetl]

Create Jira issue https://issues.apache.org/jira/browse/ARROW-5359