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https://issues.apache.org/jira/browse/BEAM-11628?focusedWorklogId=573643&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-573643
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ASF GitHub Bot logged work on BEAM-11628:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 29/Mar/21 18:29
Start Date: 29/Mar/21 18:29
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on a change in pull request
#13843:
URL: https://github.com/apache/beam/pull/13843#discussion_r603519215
##########
File path: sdks/python/apache_beam/dataframe/frames_test.py
##########
@@ -315,6 +314,40 @@ def test_dataframe_drop_ignore_errors(self):
self._run_test(
lambda df: df.drop(index='cow', columns='small', errors='ignore'), df)
+ def test_groupby_apply(self):
+ df = GROUPBY_DF
+
+ def median_sum_fn(x):
+ return (x.foo + x.bar).median()
+
+ describe = lambda df: df.describe()
Review comment:
er actually this is different, because it's producing summary statistics
per group. It is the same as
[`DataFrameGroupBy.describe`](https://pandas.pydata.org/docs/reference/api/pandas.core.groupby.DataFrameGroupBy.describe.html)
though.
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Issue Time Tracking
-------------------
Worklog Id: (was: 573643)
Time Spent: 8h 50m (was: 8h 40m)
> Implement GroupBy.apply
> -----------------------
>
> Key: BEAM-11628
> URL: https://issues.apache.org/jira/browse/BEAM-11628
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Brian Hulette
> Assignee: Brian Hulette
> Priority: P2
> Labels: dataframe-api
> Time Spent: 8h 50m
> Remaining Estimate: 0h
>
> https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.GroupBy.apply.html
> We can partition by key and then apply func on each key. It should be
> possible to create a proxy by passing a proxy to the function.
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