[jira] [Commented] (ARROW-4032) [Python] New pyarrow.Table.from_pydict() function

["Wes McKinney (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-4032?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16721727#comment-16721727 ] 

Wes McKinney commented on ARROW-4032:
-------------------------------------

You can do {{pa.array(pylist)}} already. So if we had a function to convert StructArray to Table then this would mostly do what you're describing. This was partly the intent of ARROW-40

> [Python] New pyarrow.Table.from_pydict() function
> -------------------------------------------------
>
>                 Key: ARROW-4032
>                 URL: https://issues.apache.org/jira/browse/ARROW-4032
>             Project: Apache Arrow
>          Issue Type: Task
>          Components: Python
>            Reporter: David Lee
>            Priority: Minor
>
> Here's a proposal to create a pyarrow.Table.from_pydict() function.
> Right now only pyarrow.Table.from_pandas() exist and there are inherit problems using Pandas with NULL support for Int(s) and Boolean(s)
> [http://pandas.pydata.org/pandas-docs/version/0.23.4/gotchas.html]
> {{NaN}}, Integer {{NA}} values and {{NA}} type promotions:
> Sample python code on how this would work.
>  
> {code:java}
> import pyarrow as pa
> from datetime import datetime
> pylist = [
> {"name": "Tom", "age": 10},
> {"name": "Mark", "age": 5, "city": "San Francisco"},
> {"name": "Pam", "age": 7, "birthday": datetime.now()}
> ]
> def from_pydict(pylist, columns):
>     arrow_columns = list()
>     for column in columns:
>         arrow_columns.append(pa.array([v[column] if column in v else None for v in pylist]))
>     arrow_table = pa.Table.from_arrays(arrow_columns, columns)
>     return arrow_table
> test = from_pydict(pylist, ['name' , 'age', 'city', 'birthday', 'dummy'])
> {code}
>  



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