[
https://issues.apache.org/jira/browse/ARROW-1664?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16932797#comment-16932797
]
Mitar commented on ARROW-1664:
------------------------------
It is like extension of DataFrame to multiple dimensions.
{quote}Xarray introduces labels in the form of dimensions, coordinates and
attributes on top of raw [NumPy|http://www.numpy.org/]-like arrays, which
allows for a more intuitive, more concise, and less error-prone developer
experience. The package includes a large and growing library of domain-agnostic
functions for advanced analytics and visualization with these data structures.
Xarray was inspired by and borrows heavily from
[pandas|http://pandas.pydata.org/], the popular data analysis package focused
on labelled tabular data.
{quote}
So internally it is ndarrays. This is why I think serialization could be
possible, similar to how Pandas DataFrames internally use ndarrays.
> [Python] Support for xarray.DataArray and xarray.Dataset
> --------------------------------------------------------
>
> Key: ARROW-1664
> URL: https://issues.apache.org/jira/browse/ARROW-1664
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Reporter: Mitar
> Priority: Minor
>
> DataArray and Dataset are efficient in-memory representations for multi
> dimensional data. It would be great if one could share them between processes
> using Arrow.
> http://xarray.pydata.org/en/stable/generated/xarray.DataArray.html#xarray.DataArray
> http://xarray.pydata.org/en/stable/generated/xarray.Dataset.html#xarray.Dataset
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
