issue_comments

Thanks @shoyer: Is there a how to contribute guide? I basically look for how to write a test and run test to check if my adding this option did not break anything...

Cheers

I stand corrected. Misread the old issue. ☕️ 😪

Indeed, data_vars is a (somewhat confusingly named) argument to xarray.concat, and isn't deprecated. open_mfdataset could pass the argument on through to concat, but it doesn't do that yet.

~use of data_vars was deprecated in https://github.com/pydata/xarray/pull/473.~

This seems to be working, and no deprecation warning... (But probably I have to sort paths...)

```python In [8]: ds = xarray.concat([xarray.open_dataset(p, chunks={"time": 100}) for p in paths], data_vars="minimal", dim="time")

In [9]: ds Out[9]: <xarray.Dataset> Dimensions: (time: 13505, x: 782, y: 808) Coordinates: * x (x) float64 -4.556e+06 -4.546e+06 -4.536e+06 ... * y (y) float64 4.98e+06 4.97e+06 4.96e+06 4.95e+06 ... * time (time) datetime64[ns] 1993-01-01T12:00:09.140797440 ... Data variables: lon (y, x) float64 156.5 156.5 156.6 156.6 156.7 ... lat (y, x) float64 58.55 58.64 58.72 58.81 58.9 ... lambert_conformal_conic int16 -32767 tmin (time, y, x) float64 nan nan nan nan nan nan ...

In [10]: lon = ds["lon"]

In [11]: lon.ndim Out[11]: 2 ``` Cheers

Thanks @spencerahill : You are right, but the error message won't change, since the data_vars keyword is not known, and I am not able to change the dataset's attribute data_vars. I think I have to use concat explicitly...

Cheers

I think you've accidentally used "minimum" instead of "minimal"

Hi @shoyer:

where is this data_vars='minimal' set? or maybe I am using a wrong version of xarray? Here is what I get

```python

In [10]: ds = xarray.open_mfdataset("/snow3/huziy/Daymet_daily_derivatives/daymet_spatial_agg_tmin_10x10/daymet_v3_tmin_*.nc4", data_vars="minimum")

TypeError Traceback (most recent call last) <ipython-input-10-ba844206f74a> in <module>() ----> 1 ds = xarray.open_mfdataset("/snow3/huziy/Daymet_daily_derivatives/daymet_spatial_agg_tmin_10x10/daymet_v3_tmin_*.nc4", data_vars="minimum")

/snow3/huziy/Python/python_builds/anaconda3/envs/py3.6-a3/lib/python3.6/site-packages/xarray/backends/api.py in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, lock, **kwargs) 503 paths = sorted(glob(paths)) 504 else: --> 505 paths = [str(p) if isinstance(p, path_type) else p for p in paths] 506 507 if not paths:

/snow3/huziy/Python/python_builds/anaconda3/envs/py3.6-a3/lib/python3.6/site-packages/xarray/backends/api.py in <listcomp>(.0) 503 paths = sorted(glob(paths)) 504 else: --> 505 paths = [str(p) if isinstance(p, path_type) else p for p in paths] 506 507 if not paths:

TypeError: open_dataset() got an unexpected keyword argument 'data_vars'

In [11]: ds = xarray.open_mfdataset("/snow3/huziy/Daymet_daily_derivatives/daymet_spatial_agg_tmin_10x10/daymet_v3_tmin_*.nc4")

In [12]: ds.data_vars = "minimum"

AttributeError Traceback (most recent call last) <ipython-input-12-9026b067946d> in <module>() ----> 1 ds.data_vars = "minimum"

/snow3/huziy/Python/python_builds/anaconda3/envs/py3.6-a3/lib/python3.6/site-packages/xarray/core/common.py in setattr(self, name, value) 180 raise AttributeError( 181 "cannot set attribute %r on a %r object. Use setitem " --> 182 "style assignment (e.g., ds['name'] = ...) instead to " 183 "assign variables." % (name, type(self).name)) 184 object.setattr(self, name, value)

AttributeError: can't set attribute

In [13]: ds.data_vars Out[13]: Data variables: tmin (time, y, x) float64 nan nan nan nan nan nan ... lon (time, y, x) float64 156.5 156.5 156.6 156.6 ... lat (time, y, x) float64 58.55 58.64 58.72 58.81 ... lambert_conformal_conic (time) int64 -32767 -32767 -32767 -32767 -32767 ...

In [16]: xarray.version Out[16]: '0.9.6'

``` Cheers

With #473, you will be able to achieve your desired result by adjusting the data_vars argument. data_vars='minimal will probably do the trick.

But why not just exclude all that do not have a time dimension?

Yeah, this is probably a good idea.

concat also covers combining datasets along a new dimension (i.e., if time was not a dimension of any of the individual datasets), but that's not the case here.

netCDF4-python uses a dimension specified by the user or an unlimited dimension it finds in the dataset. Here is the corresponding code section.

Here is a print-out of the full dataset for POP ocean model output (see that gist in nbviewer).

I can see that the heuristics exclude variables from concatenation that are associated with dimensions of other variables. But why not just exclude all that do not have a time dimension?

Hmm, I'll have to think about this one. We use some heuristics to figure out what to concatenation but they aren't perfect. Could you print what the full datasets look like, not just this variable?