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Posted to issues@beam.apache.org by "Beam JIRA Bot (Jira)" <ji...@apache.org> on 2022/04/15 16:59:00 UTC
[jira] [Updated] (BEAM-12169) Allow non-deferred column operations on categorical columns
[ https://issues.apache.org/jira/browse/BEAM-12169?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Beam JIRA Bot updated BEAM-12169:
---------------------------------
Labels: dataframe-api stale-assigned (was: dataframe-api)
> 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
> Assignee: Andy Ye
> Priority: P3
> Labels: dataframe-api, stale-assigned
> Time Spent: 6h 50m
> 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, Series.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
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