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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2022/01/26 00:20:00 UTC
[jira] [Work logged] (BEAM-12169) Allow non-deferred column operations on categorical columns
[ https://issues.apache.org/jira/browse/BEAM-12169?focusedWorklogId=715370&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-715370 ]
ASF GitHub Bot logged work on BEAM-12169:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 26/Jan/22 00:19
Start Date: 26/Jan/22 00:19
Worklog Time Spent: 10m
Work Description: yeandy opened a new pull request #16615:
URL: https://github.com/apache/beam/pull/16615
Adding non-deferred operations. i.e. operations that produce a variable set of columns based on the intrinsic nature of the data.
[WIP] This PR includes functions:
- `get_dummies`
------------------------
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`ValidatesRunner` compliance status (on master branch)
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<th>Lang</th>
<th>ULR</th>
<th>Dataflow</th>
<th>Flink</th>
<th>Samza</th>
<th>Spark</th>
<th>Twister2</th>
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<td>XLang</td>
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Examples testing status on various runners
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<th>Spark</th>
<th>Twister2</th>
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<td>Go</td>
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<a href="https://ci-beam.apache.org/job/beam_PreCommit_Java_Examples_Dataflow_Cron/lastCompletedBuild/">
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</table>
Post-Commit SDK/Transform Integration Tests Status (on master branch)
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<th>Java</th>
<th>Python</th>
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<a href="https://ci-beam.apache.org/job/beam_PostCommit_Go/lastCompletedBuild/">
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Pre-Commit Tests Status (on master branch)
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<th>Website</th>
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<td>Non-portable</td>
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</table>
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Issue Time Tracking
-------------------
Worklog Id: (was: 715370)
Remaining Estimate: 0h
Time Spent: 10m
> Allow non-deferred column operations on categorical columns
> -----------------------------------------------------------
>
> Key: BEAM-12169
> URL: https://issues.apache.org/jira/browse/BEAM-12169
> Project: Beam
> Issue Type: Improvement
> Components: dsl-dataframe, sdk-py-core
> Reporter: Brian Hulette
> Priority: P3
> Labels: dataframe-api
> Time Spent: 10m
> Remaining Estimate: 0h
>
> There are several operations that we currently disallow because they produce a variable set of columns in the output based on the data (non-deferred-columns). However, for some dtypes (categorical, boolean) we can easily enumerate all the possible values that will be seen at execution time, so we can predict the columns that will be seen.
> Note we still can't implement these operations 100% correctly, as pandas will typically only create columns for the values that are _observed_, while we'd have to create a column for every possible value.
> We should allow these operations in these special cases.
> Operations in this category:
> - DataFrame.unstack (can work if unstacked level is a categorical or boolean column)
> - Series.str.get_dummies
> - Series.str.split
> - Series.str.rsplit
> - DataFrame.pivot
> - DataFrame.pivot_table
> - len(GroupBy) and ngroups
> ** if groupers are all categorical _and_ observed=False or all boolean
> ** Note these two may not actually be equivalent in all cases: [https://github.com/pandas-dev/pandas/issues/26326]
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