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https://issues.apache.org/jira/browse/ARROW-5359?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joris Van den Bossche updated ARROW-5359:
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Summary: [Python] timestamp_as_object support for pa.Table.to_pandas in
pyarrow (was: timestamp_as_object support for pa.Table.to_pandas in pyarrow)
> [Python] timestamp_as_object support for pa.Table.to_pandas in pyarrow
> ----------------------------------------------------------------------
>
> Key: ARROW-5359
> URL: https://issues.apache.org/jira/browse/ARROW-5359
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.13.0
> Environment: Ubuntu
> Reporter: Joe Muruganandam
> Priority: Major
>
> Creating ticket for issue reported in
> github([https://github.com/apache/arrow/issues/4284])
> h2. 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
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