id,node_id,number,state,locked,title,user,body,created_at,updated_at,closed_at,merged_at,merge_commit_sha,assignee,milestone,draft,head,base,author_association,auto_merge,repo,url,merged_by
31399492,MDExOlB1bGxSZXF1ZXN0MzEzOTk0OTI=,378,closed,0,"ENH: fillna method for Dataset, DataArray and GroupBy objects",1217238,"This is a new method for Dataset, DataArray and GroupBy objects. For the most part, it follows standard broadcasting and alignment rules for binary operations.
## Example usage

Setup:

```
In [1]: import xray

In [2]: import pandas as pd

In [3]: import numpy as np

In [4]: array = xray.DataArray(np.arange(75.0), [('time', pd.date_range('2000-01-01', periods=75, freq='5D'))])

In [5]: array[::3] = np.nan

In [6]: array
Out[6]:
<xray.DataArray (time: 75)>
array([ nan,   1.,   2.,  nan,   4.,   5.,  nan,   7.,   8.,  nan,  10.,
        11.,  nan,  13.,  14.,  nan,  16.,  17.,  nan,  19.,  20.,  nan,
        22.,  23.,  nan,  25.,  26.,  nan,  28.,  29.,  nan,  31.,  32.,
        nan,  34.,  35.,  nan,  37.,  38.,  nan,  40.,  41.,  nan,  43.,
        44.,  nan,  46.,  47.,  nan,  49.,  50.,  nan,  52.,  53.,  nan,
        55.,  56.,  nan,  58.,  59.,  nan,  61.,  62.,  nan,  64.,  65.,
        nan,  67.,  68.,  nan,  70.,  71.,  nan,  73.,  74.])
Coordinates:
  * time     (time) datetime64[ns] 2000-01-01 2000-01-06 2000-01-11 2000-01-16 ...
```

Simple example:

```
In [7]: array.fillna(0)
Out[7]:
<xray.DataArray (time: 75)>
array([  0.,   1.,   2.,   0.,   4.,   5.,   0.,   7.,   8.,   0.,  10.,
        11.,   0.,  13.,  14.,   0.,  16.,  17.,   0.,  19.,  20.,   0.,
        22.,  23.,   0.,  25.,  26.,   0.,  28.,  29.,   0.,  31.,  32.,
         0.,  34.,  35.,   0.,  37.,  38.,   0.,  40.,  41.,   0.,  43.,
        44.,   0.,  46.,  47.,   0.,  49.,  50.,   0.,  52.,  53.,   0.,
        55.,  56.,   0.,  58.,  59.,   0.,  61.,  62.,   0.,  64.,  65.,
         0.,  67.,  68.,   0.,  70.,  71.,   0.,  73.,  74.])
Coordinates:
  * time     (time) datetime64[ns] 2000-01-01 2000-01-06 2000-01-11 2000-01-16 ...
```

Fill missing values with average for that month:

```
In [8]: g = array.groupby('time.month')

In [9]: g.fillna(g.mean('time'))
Out[9]:
<xray.DataArray (time: 75)>
array([ 17.2,   1. ,   2. ,  17.2,   4. ,   5. ,  17.2,   7. ,   8. ,
         9. ,  10. ,  11. ,  15. ,  13. ,  14. ,  15. ,  16. ,  17. ,
        15. ,  19. ,  20. ,  21. ,  22. ,  23. ,  21. ,  25. ,  26. ,
        27. ,  28. ,  29. ,  27. ,  31. ,  32. ,  33. ,  34. ,  35. ,
        33. ,  37. ,  38. ,  39. ,  40. ,  41. ,  39. ,  43. ,  44. ,
        45. ,  46. ,  47. ,  45. ,  49. ,  50. ,  51. ,  52. ,  53. ,
        51. ,  55. ,  56. ,  57. ,  58. ,  59. ,  57. ,  61. ,  62. ,
        63. ,  64. ,  65. ,  63. ,  67. ,  68. ,  69.8,  70. ,  71. ,
        69.8,  73. ,  74. ])
Coordinates:
  * time     (time) datetime64[ns] 2000-01-01 2000-01-06 2000-01-11 2000-01-16 ...
    month    (time) int32 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 ...
```

CC @nicolasfauchereau
",2015-03-18T04:16:29Z,2015-03-20T23:00:42Z,2015-03-20T23:00:41Z,2015-03-20T23:00:41Z,2369df3199638ad665539523b5ff1de89c247bf5,,1028398,0,179b0b65c86400069ec25247a7c09d623966e6f6,aaf9067d794a655e52c7186ef9e1c3388573bde6,MEMBER,,13221727,https://github.com/pydata/xarray/pull/378,
31706895,MDExOlB1bGxSZXF1ZXN0MzE3MDY4OTU=,380,closed,0,ENH: Add Dataset.assign and .assign_coords,1217238,"Fixes #314

Based off the new pandas method of the same name.

An example:

```
In [3]: ds = xray.Dataset({'y': ('x', [1, 2, 3])})

In [4]: ds.assign(z = lambda x: x.y ** 2)
Out[4]:
<xray.Dataset>
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int64 0 1 2
Data variables:
    y        (x) int64 1 2 3
    z        (x) int64 1 4 9
```
",2015-03-23T06:04:13Z,2015-03-23T18:42:45Z,2015-03-23T18:42:43Z,2015-03-23T18:42:43Z,1766cfc428d024db2038a5ba470a043a91218652,,1028398,0,d7271cdcbbed3c6dba9136f2b91451e455f0fcfc,4798741a22cf24a1f132865c18e1f2320f2bc855,MEMBER,,13221727,https://github.com/pydata/xarray/pull/380,