Feature proposal: xarray.interactive module

I've been experimenting with ipython widgets in jupyter notebooks, and I've been working on how we might use them to make xarray more interactive.

Motivation:

For most users who are exploring their data, it will be common to find themselves rerunning the same cells repeatedly but with slightly different values. In xarray's case that will often be in an .isel() or .sel() call, or selecting variables from a dataset. IPython widgets allow you to interact with your functions in a very intuitive way, which we could exploit. There are lots of tutorials on how to interact with pandas data (e.g. this great one), but I haven't seen any for interacting with xarray objects.

Relationship to other libraries:

Some downstream plotting libaries (such as @hvplot) already use widgets when interactively plotting xarray-derived data structures, but they don't seem to go the full N dimensions. This also isn't something that should be confined to plotting functions - you often choose slices or variables at the start of analysis, not just at the end. I'll come back to this idea later.

The default ipython widgets are pretty good, but we could write an xarray.interactive module in such a way that downstream developers can easily replace them with their own widgets.

Usage examples:

```python

imports

import ipywidgets as widgets import xarray.plot as xplot import xarray.interactive as interactive

Load tutorial data

ds = xr.tutorial.open_dataset('air_temperature')['air'] ```

Plotting against multiple dimensions interactively python interactive.isel(da, xplot.plot, lat=10, lon=50)

Interactively select a range from a dimension python def plot_mean_over_time(da): da.mean(dim=time) interactive.isel(da, plot_mean_over_time, time=slice(100, 500))

Animate over one dimension python from ipywidgets import Play interactive.isel(da, xplot.plot, time=Play())

API ideas:

We can write a function like this

python interactive.isel(da, func=xplot.plot, time=10)

which could also be used as a decorator something like this python @interactive.isel(da, time=10) def plot(da) return xplot.plot(da)

It would be nicer to be able to do this python @Interactive(da).isel(time=10) def plot(da) return xplot.plot(da) but Guido forbade it.

But we can attach these functions to an accessor to get python da.interactive.isel(xplot.plot, time=10)

Other ideas

Select variables from datasets ```python @interactive.data_vars(da1=ds['n'], da2=ds['T'], ...) def correlation(da1, da2, ...) ...

Would produce a dropdown list of variables for each dataset

```

Choose dimensions to apply functions over ```python @interactive.dims(dim='time') def mean(da, dim) ...

Would produce a dropdown list of dimensions in the dataarray

```

General interactive.explore() method to see variation over any number of dimensions, the default being all of them.

What do people think about this? Is it something that makes sense to include within xarray itself? (Dependencies aren't a problem because it's fine to have ipywidgets as an optional dependency just for this module.)