issue_comments: 321461998

This data as json

html_url issue_url id node_id user created_at updated_at author_association body reactions performed_via_github_app issue
https://github.com/pydata/xarray/pull/1489#issuecomment-321461998 https://api.github.com/repos/pydata/xarray/issues/1489 321461998 MDEyOklzc3VlQ29tbWVudDMyMTQ2MTk5OA== 1217238 2017-08-10T06:22:02Z 2017-08-10T06:22:02Z MEMBER

@jmunroe This is great functionality -- thanks for your work on this!

One concern: if possible, I would like to avoid adding explicit dask graph building code in xarray. It looks like the canonical way to transform from a list of dask/numpy arrays to a dask dataframe is to make use of dask.dataframe.from_array along with dask.dataframe.concat: ``` In [34]: import numpy as np

In [35]: import dask.dataframe as dd

In [36]: import dask.array as da

In [37]: x = da.from_array(np.arange(5), 2)

In [38]: y = da.from_array(np.linspace(-np.pi, np.pi, 5), 2)

notice that dtype is preserved properly

In [39]: dd.concat([dd.from_array(x), dd.from_array(y)], axis=1) Out[39]: Dask DataFrame Structure: 0 1 npartitions=2 0 int64 float64 2 ... ... 4 ... ... Dask Name: concat-indexed, 26 tasks ```

Can you look into refactoring your code to make use of these?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   245624267