[jira] [Assigned] (BEAM-12169) Allow non-deferred column operations on categorical columns

["Andy Ye (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-12169?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andy Ye reassigned BEAM-12169:
------------------------------

    Assignee: Andy Ye

> 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
>          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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