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https://issues.apache.org/jira/browse/ARROW-2295?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Lawrence Chan updated ARROW-2295:
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Description:
There are `to_pandas()` functions, but no `to_numpy()` functions. I'd like to
propose that we include both.
Also, `pyarrow.lib.Array.to_pandas()` returns a `numpy.ndarray`, which imho is
very confusing :). I think it would be more intuitive for the `to_pandas()`
functions to return `pandas.Series` and `pandas.DataFrame` objects, and the
`to_numpy()` functions to return `numpy.ndarray` and either a dict of
`numpy.ndarray` or a structured `numpy.ndarray` depending on a flag, for
example. The `to_pandas()` function is of course welcome to use the
`to_numpy()` func to avoid the additional index and whatnot of the
`pandas.Series`.
was:
There are `to_pandas()` functions, but no `to_numpy()` functions. I'd like to
propose that we include both.
Also, `pyarrow.lib.Array.to_pandas()` returns a `numpy.ndarray`, which imho is
very confusing :). I think it would be more intuitive for the `to_pandas()`
functions to return `pandas.Series` and `pandas.DataFrame` objects, and the
`to_numpy()` functions to return `numpy.ndarray` and either a dict of
`numpy.ndarray` or a structured `numpy.ndarray` depending on a flag, for
example. The `to_pandas()` function is of course welcome to use the
`to_numpy()` func to avoid the additional indexes and whatnot of the
`pandas.Series`.
> Add to_numpy functions
> ----------------------
>
> Key: ARROW-2295
> URL: https://issues.apache.org/jira/browse/ARROW-2295
> Project: Apache Arrow
> Issue Type: Improvement
> Components: Python
> Reporter: Lawrence Chan
> Priority: Minor
>
> There are `to_pandas()` functions, but no `to_numpy()` functions. I'd like to
> propose that we include both.
> Also, `pyarrow.lib.Array.to_pandas()` returns a `numpy.ndarray`, which imho
> is very confusing :). I think it would be more intuitive for the
> `to_pandas()` functions to return `pandas.Series` and `pandas.DataFrame`
> objects, and the `to_numpy()` functions to return `numpy.ndarray` and either
> a dict of `numpy.ndarray` or a structured `numpy.ndarray` depending on a
> flag, for example. The `to_pandas()` function is of course welcome to use the
> `to_numpy()` func to avoid the additional index and whatnot of the
> `pandas.Series`.
>
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