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Joris Van den Bossche commented on ARROW-842: --------------------------------------------- {{pd.NaT}} is one that is not recognized, but, only in lists / object dtype: {code} In [25]: pa.array([pd.Timestamp("2012-01-01"), pd.NaT, None, np.nan, float('nan')]) Out[25]: <pyarrow.lib.TimestampArray object at 0x7f27703b82c8> [ 1325376000000000, -62135596800000000, null, null, null ] {code} If you actually pass a pandas Series object with the proper dtype such as datetime64[ns], then those missing values are handled correctly: {code} In [32]: pa.array(pd.Series([pd.Timestamp("2012-01-01"), pd.NaT])) Out[32]: <pyarrow.lib.TimestampArray object at 0x7f2752662b38> [ 1325376000000000000, null ] {code} > [Python] Handle more kinds of null sentinel objects from pandas 0.x > ------------------------------------------------------------------- > > Key: ARROW-842 > URL: https://issues.apache.org/jira/browse/ARROW-842 > Project: Apache Arrow > Issue Type: Improvement > Components: Python > Reporter: Wes McKinney > Priority: Major > > Follow-on work to ARROW-707. See > https://github.com/pandas-dev/pandas/blob/master/pandas/_libs/lib.pyx#L193 > and discussion in https://github.com/apache/arrow/pull/554 -- This message was sent by Atlassian JIRA (v7.6.3#76005)