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https://issues.apache.org/jira/browse/ARROW-7591?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joris Van den Bossche updated ARROW-7591:
-----------------------------------------
Fix Version/s: 0.16.0
> [Python] DictionaryArray.to_numpy returns dict of parts instead of numpy array
> ------------------------------------------------------------------------------
>
> Key: ARROW-7591
> URL: https://issues.apache.org/jira/browse/ARROW-7591
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Reporter: Joris Van den Bossche
> Assignee: Joris Van den Bossche
> Priority: Major
> Fix For: 0.16.0
>
>
> Currently, the {{to_numpy}} method doesn't return an ndarray incase of
> dictionaryd type data:
> {code}
> In [54]: a = pa.array(pd.Categorical(["a", "b", "a"]))
>
>
> In [55]: a
>
>
> Out[55]:
> <pyarrow.lib.DictionaryArray object at 0x7f5c63d98f28>
> -- dictionary:
> [
> "a",
> "b"
> ]
> -- indices:
> [
> 0,
> 1,
> 0
> ]
> In [57]: a.to_numpy(zero_copy_only=False)
>
>
> Out[57]:
> {'indices': array([0, 1, 0], dtype=int8),
> 'dictionary': array(['a', 'b'], dtype=object),
> 'ordered': False}
> {code}
> This is actually just an internal representation that is passed from C++ to
> Python so on the Python side a {{pd.Categorical}} / {{CategoricalBlock}} can
> be constructed, but it's not something we should return as such to the user.
> Rather, I think we should return a decoded / dense numpy array (or at least
> error instead of returning this dict)
> (also, if the user wants those parts, they are already available from the
> dictionary array as {{a.indices}}, {{a.dictionary}} and {{a.type.ordered}})
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