pydata / xarray / 4762

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Rolling window with `as_strided` (#1837)

* Rolling_window for np.ndarray

* Add pad method to Variable

* Added rolling_window to DataArray and Dataset

* remove pad_value option. Support dask.rolling_window

* Refactor rolling.reduce

* add as_strided to npcompat. Tests added for reduce(np.nanmean)

* Support boolean in maybe_promote

* move rolling_window into duck_array_op. Make DataArray.rolling_window public.

* Added to_dataarray and to_dataset to rolling object.

* Use pad in rolling to make compatible to pandas. Expose pad_with_fill_value to public.

* Refactor rolling

* flake8

* Added a comment for dask's pad.

* Use fastpath in rolling.to_dataarray

* Doc added.

* Revert not to use fastpath

* Remove maybe_prompt for Boolean. Some improvements based on @shoyer's review.

* Update test.

* Bug fix in test_rolling_count_correct

* fill_value for boolean array

* rolling_window(array, axis, window) -> rolling_window(array, window, axis)

* support stride in rolling.to_dataarray

* flake8

* Improve doc. Add DataArrayRolling to api.rst

* Improve docs in common.rolling.

* Expose groupby docs to public

* Default fill_value=dtypes.NA, stride=1. Add comment for DataArrayRollig.

* Default fill_value=dtypes.NA, stride=1. Add comment for DataArrayRollig.

* Add fill_value option to rolling.to_dataarray

* Convert non-numeric array in reduce.

* Fill_value = False for boolean array in rolling.reduce

* Support old numpy plus bottleneck combination. Suppress warning for all-nan slice reduce.

* flake8

* Add benchmark

* Dataset.count. Benchmark

* Classize benchmark

* Decoratorize for asv benchmark

* Classize benchmarks/indexing.py

* Working with nanreduce

* Support .sum for object dtype.

* Remove unused if-statements.

* Default skipna for rolling.reduce

* Pass tests. Test added to make sure the consistency to pandas' behavior.

* Delete duplicate file. ... (continued)

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