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https://issues.apache.org/jira/browse/BEAM-9547?focusedWorklogId=601969&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-601969
]
ASF GitHub Bot logged work on BEAM-9547:
----------------------------------------
Author: ASF GitHub Bot
Created on: 25/May/21 22:12
Start Date: 25/May/21 22:12
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on a change in pull request
#14850:
URL: https://github.com/apache/beam/pull/14850#discussion_r639242557
##########
File path: sdks/python/apache_beam/dataframe/frames.py
##########
@@ -1677,10 +1643,46 @@ def aggregate(self, func, axis=0, *args, **kwargs):
[self._expr],
requires_partition_by=partitionings.Singleton()))
else:
- # In the general case, compute the aggregation of each column separately,
- # then recombine.
+ # In the general case, we will compute the aggregation of each column
+ # separately, then recombine.
+
+ # First, handle any kwargs that cause a projection, by eagerly generating
+ # the proxy, and only including the columns that are in the output.
+ PROJECT_KWARGS = ('numeric_only', 'bool_only', 'include', 'exclude')
+ proxy = self._expr.proxy().agg(func, axis, *args, **kwargs)
+
+ if isinstance(proxy, pd.DataFrame):
+ projected = self[list(proxy.columns)]
+ elif isinstance(proxy, pd.Series):
+ projected = self[list(proxy.index)]
+ else:
+ projected = self
+
+ nonnumeric_columns = [name for (name, dtype) in projected.dtypes.items()
+ if not
+ pd.core.dtypes.common.is_numeric_dtype(dtype)]
+
+ if _is_numeric(func) and len(nonnumeric_columns):
Review comment:
Done
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Issue Time Tracking
-------------------
Worklog Id: (was: 601969)
Time Spent: 87h 40m (was: 87.5h)
> Implement all pandas operations (or raise WontImplementError)
> -------------------------------------------------------------
>
> Key: BEAM-9547
> URL: https://issues.apache.org/jira/browse/BEAM-9547
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Brian Hulette
> Assignee: Robert Bradshaw
> Priority: P2
> Labels: dataframe-api
> Time Spent: 87h 40m
> Remaining Estimate: 0h
>
> We should have an implementation for every DataFrame, Series, and GroupBy
> method. Everything that's not possible to implement should get a default
> implementation that raises WontImplementError
> See https://github.com/apache/beam/pull/10757#discussion_r389132292
> Progress at the individual operation level is tracked in a
> [spreadsheet|https://docs.google.com/spreadsheets/d/1hHAaJ0n0k2tw465ORs5tfdy4Lg0DnGWIQ53cLjAhel0/edit],
> consider requesting edit access if you'd like to help out.
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