[
https://issues.apache.org/jira/browse/BEAM-12529?focusedWorklogId=616545&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-616545
]
ASF GitHub Bot logged work on BEAM-12529:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 29/Jun/21 15:20
Start Date: 29/Jun/21 15:20
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on a change in pull request
#15073:
URL: https://github.com/apache/beam/pull/15073#discussion_r660723890
##########
File path: sdks/python/apache_beam/dataframe/schemas_test.py
##########
@@ -290,6 +290,29 @@ def
test_unbatch_include_index_column_conflict_raises(self):
with self.assertRaisesRegex(ValueError, 'foo'):
_ = pc | schemas.UnbatchPandas(proxy, include_indexes=True)
+ def test_unbatch_datetime(self):
+
+ s = pd.Series(
+ pd.date_range(
+ '1/1/2000', periods=100, freq='m', tz='America/Los_Angeles'))
+ proxy = s[:0]
+
+ with TestPipeline() as p:
+ res = (
+ p | beam.Create([s[::2], s[1::2]])
+ | schemas.UnbatchPandas(proxy, include_indexes=True))
+
+ assert_that(
+ res,
+ equal_to(
+ list(
Review comment:
Good point, done
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Issue Time Tracking
-------------------
Worklog Id: (was: 616545)
Time Spent: 1h 40m (was: 1.5h)
> to_pcollection does not support timestamp types
> -----------------------------------------------
>
> Key: BEAM-12529
> URL: https://issues.apache.org/jira/browse/BEAM-12529
> Project: Beam
> Issue Type: Improvement
> Components: dsl-dataframe
> Reporter: Brian Hulette
> Assignee: Brian Hulette
> Priority: P2
> Fix For: 2.32.0
>
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
> We do not currently support converting timestamps directly from a deferred
> dataframe to a schema'd PCollection. It will raise an error like:
> {code}
> TypeError: Unsupported dtype in proxy: 'datetime64[ns]'
> {code}
> Note that pandas timestamps are nanosecond precision by default, while Beam's
> Timestamp type is microsecond precision.
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