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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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