• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

@aulemahal would you be able to test against xclim's test suite. I imagine you're doing a bunch of grouped quantiles.

…roadcast=False`` (#8784)"

This reverts commit 11f89ecdd41226cf93da8d1e720d2710849cd23e.

Reverting #8784

Sadly that PR broke a lot of tests by breaking create_test_data with from xarray.tests import create_test_data create_test_data()

```

AssertionError Traceback (most recent call last) Cell In[3], line 2 1 from xarray.tests import create_test_data ----> 2 create_test_data()

File ~/repos/xarray/xarray/tests/init.py:329, in create_test_data(seed, add_attrs, dim_sizes) 327 obj.coords["numbers"] = ("dim3", numbers_values) 328 obj.encoding = {"foo": "bar"} --> 329 assert all(var.values.flags.writeable for var in obj.variables.values()) 330 return obj

AssertionError: ```

Somehow that code changes whether IndexVariable.values returns a writeable numpy array. I spent some time debugging but couldn't figure it out.

cc @etienneschalk

Builds on #8560

• [x] Closes #8409
• [x] Tests added
• [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst

cc @max-sixty

``` print(len(cloudpickle.dumps(da.chunk(lat=1, lon=1).map_blocks(lambda x: x))))

779354739 -> 47699827

print(len(cloudpickle.dumps(da.chunk(lat=1, lon=1).drop_vars(da.indexes).map_blocks(lambda x: x))))

15981508

```

This is a quick attempt. I think we can generalize this to minimize duplication.

The downside is that the graphs are not totally embarrassingly parallel any more. This PR:

vs main:

• [x] Tests added
• [x] Passes black . && mypy . && flake8
• [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API

This adds plotting methods to GroupBy objects so that it's easy to plot each group as a facet. I'm finding this super helpful in my current research project.

It's pretty self-contained, mostly just adding map_groupby* methods to FacetGrid. But that's because I make GroupBy mimic the underlying DataArray by adding coords, attrs and __getitem__.

This still needs more tests but I would like feedback on the feature and the implementation.

Example

``` python import numpy as np import xarray as xr

time = np.arange(80) da = xr.DataArray(5 * np.sin(2np.pitime/10), coords={"time": time}, dims="time") da["period"] = da.time.where((time % 10) == 0).ffill("time")/10 da.plot() ```

python da.groupby("period").plot(col="period", col_wrap=4)

python da = da.expand_dims(y=10) da.groupby("period").plot(col="period", col_wrap=4, sharex=False, sharey=True, robust=True)

• [x] Closes #2383
• [x] Tests added
• [x] Passes black . && mypy . && flake8
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Should merge after https://github.com/dask/dask/pull/7234 is merged

• [x] Closes #3277, closes #2531, closes #2532, closes #2514
• [x] Tests added
• [x] Passes pre-commit run --all-files
• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

• [x] Tests added
• [x] Passes isort -rc . && black . && mypy . && flake8
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

It parses args and breaks any xarray objects into appropriate blocks before passing them on to the user function.

e.g. ```python da1 = xr.DataArray( np.ones((10, 20)), dims=["x", "y"], coords={"x": np.arange(10), "y": np.arange(20)} ).chunk({"x": 5, "y": 4}) da1

def sumda(da1, da2): #print(da1.shape) #print(da2.shape) return da1 - da2

da3 = (da1 + 1).isel(x=1, drop=True).rename({"y": "k"}) mapped = xr.map_blocks(sumda, da1, args=[da3]) xr.testing.assert_equal(da1-da3, mapped) # passes ```

1. python 3.8 is not allowed on RTD (yet)
2. I pinned a few versions (based on the env solution obtained locally). This seems to have fixed the memory problem.

This adds join='override' which checks that indexes along a dimension are of the same size and overwrites those indices with indices from the first object.

Definitely need help, feedback.

• [x] With #3102 this partially helps with #2039, #2217
• [x] Tests added
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

partially addresses #1850 closes #946

I tried to make an "awesome xarray" list by doing a github search for 'xarray'. I only put packages that looked like they were intended for general use. Also, I moved the list from internals.rst to faq.rst.

Let me know if there are any I've missed or any that should be added.