issues: 130753818

Firstly, I think xarray is great and for the type of physics simulations I run n-dimensional labelled arrays is exactly what I need. But, and I may be missing something, is there a way to merge (or concatenate/update) DataArrays with different domains on the same coordinates?

For example consider this setup:

``` python import xarray as xr

x1 = [100] y1 = [1, 2, 3, 4, 5] dat1 = [[101, 102, 103, 104, 105]]

x2 = [200] y2 = [3, 4, 5, 6] # different size and domain dat2 = [[203, 204, 205, 206]]

da1 = xr.DataArray(dat1, dims=['x', 'y'], coords={'x': x1, 'y': y1}) da2 = xr.DataArray(dat2, dims=['x', 'y'], coords={'x': x2, 'y': y2}) ```

I would like to aggregate such DataArrays into a new, single DataArray with nan padding such that:

``` python

merge(da1, da2, align=True) # made up syntax <xarray.DataArray (x: 2, y: 6)> array([[ 101., 102., 103., 104., 105., nan], [ nan, nan, 203., 204., 205., 206.]]) Coordinates: * x (x) int64 100 200 * y (y) int64 1 2 3 4 5 6 ```

Here is a quick function I wrote to do such but I would worried about the performance of 'expanding' the new data to the old data's size every iteration (i.e. supposing that the first argument is a large DataArray that you are adding to but doesn't necessarily contain the dimensions already).

python def xrmerge(*das, accept_new=True): da = das[0] for new_da in das[1:]: # Expand both to have same dimensions, padding with NaN da, new_da = xr.align(da, new_da, join='outer') # Fill NaNs one way or the other re. accept_new da = new_da.fillna(da) if accept_new else da.fillna(new_da) return da

Might this be (or is this already!) possible in simpler form in xarray? I know Datasets have merge and update methods but I couldn't make them work as above. I also notice there are possible plans ( #417 ) to introduce a merge function for DataArrays.