• [x] Closes #4783
• [ ] Tests added
• [x] Passes pre-commit run --all-files
• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

<sub>

Overriding CI behaviors

By default, the upstream dev CI is disabled on pull request and push events. You can override this behavior per commit by adding a [test-upstream] tag to the first line of the commit message. For documentation-only commits, you can skip the CI per commit by adding a [skip-ci] tag to the first line of the commit message </sub>

What happened:

Hi. Perhaps a trivially minor issue, but I have noticed that open_dataset and to_netcdf expand user directories (~), while open_mfdataset does so on file lists, but not on patterns or single files.

What you expected to happen:

I would expect consistent behaviour across all file reading and writing methods.

Minimal Complete Verifiable Example:

```python

import xarray as xr xr.Dataset().to_netcdf('~/dataset.nc') # works xr.open_dataset('~/dataset.nc') # works xr.open_mfdataset(['~/dataset.nc']) # works xr.open_mfdataset('~/dataset.nc') # error Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/lib/python3.9/site-packages/xarray/backends/api.py", line 891, in open_mfdataset raise OSError("no files to open") OSError: no files to open ```

Anything else we need to know?:

This is done by private method _normalize_paths, which is called in open_dataset and to_netcdf but not open_mfdataset.

https://github.com/pydata/xarray/blob/1525fb0b23b8e92420ab428dc3d918a658e92dd4/xarray/backends/api.py#L170-L177

Environment:

MCVE Code Sample

python import numpy as np import xarray as xr import matplotlib as mpl data = xr.DataArray(np.arange(24).reshape(4, 6)) data.plot.contour(norm=mpl.colors.Normalize(vmin=5, vmax=10))

Yields:

python Traceback (most recent call last): File "<stdin>", line 1, in <module> File ".../xarray/xarray/plot/plot.py", line 816, in plotmethod return newplotfunc(**allargs) File ".../xarray/xarray/plot/plot.py", line 694, in newplotfunc cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs( File ".../xarray/xarray/plot/utils.py", line 772, in _process_cmap_cbar_kwargs cmap_params = _determine_cmap_params(**cmap_kwargs) File ".../xarray/xarray/plot/utils.py", line 278, in _determine_cmap_params cmap, newnorm = _build_discrete_cmap(cmap, levels, extend, filled) File ".../xarray/xarray/plot/utils.py", line 94, in _build_discrete_cmap n_colors = len(levels) + ext_n - 1

Expected Output

A plot.

Problem Description

I think this has to do with:

https://github.com/pydata/xarray/blob/95e4f6c7a636878c94b892ee8d49866823d0748f/xarray/plot/utils.py#L744

And the line where the code fails:

https://github.com/pydata/xarray/blob/95e4f6c7a636878c94b892ee8d49866823d0748f/xarray/plot/utils.py#L94

There should be an easy fix, I think.

Output of xr.show_versions()

Add a master_file keyword arguments to open_mfdataset to choose the source of global attributes in a multi-file dataset.

• [x] Closes #2382
• [x] Tests added
• [x] Passes black . && mypy . && flake8
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Currently 1D plot functions only allow binned coordinates (of pd.Interval type, produced with groupby_bins) on the y-axis (issue #3571). This pull request enables plotting intervals on either or both axes of 1D plots.

• [x] Closes #3571
• [x] Tests added
• [x] Passes black . && mypy . && flake8
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Minimal Code Sample

```python import numpy as np import xarray as xr import matplotlib.pyplot as plt

create fake data

data = xr.DataArray(np.random.rand(101)).rename('data')

group by bins and compute sum

bins = np.linspace(0, 1, 11) data = data.groupby_bins(data, bins).sum()

plot group means

data.plot() # works data.plot(x='data_bins') # works plt.plot((bins[:-1]+bins[1:])/2, data) # works

plot with axes transposed

data.plot(y='data_bins') # TypeError data.plot.line(y='data_bins') # TypeError plt.plot(data, (bins[:-1]+bins[1:])/2) # workaround ```

Expected Output

I would like to plot binned data (produced with groupby_bins) with transposed axes, i.e. data on the x-axis, and bins on the y-axis.

Problem Description

Attempting to plot using an array of pd.Interval on the y-axis yields the following TypeError. The error message reports data should be numeric, dates or pd.Interval, which they are.

Traceback (most recent call last): File "./groupbybug.py", line 19, in <module> data.plot(y='data_bins') # TypeError File "~/.local/lib/python3.7/site-packages/xarray/plot/plot.py", line 465, in __call__ return plot(self._da, **kwargs) File "~/.local/lib/python3.7/site-packages/xarray/plot/plot.py", line 202, in plot return plotfunc(darray, **kwargs) File "~/.local/lib/python3.7/site-packages/xarray/plot/plot.py", line 323, in line _ensure_plottable(xplt_val, yplt_val) File "~/.local/lib/python3.7/site-packages/xarray/plot/utils.py", line 512, in _ensure_plottable "Plotting requires coordinates to be numeric " TypeError: Plotting requires coordinates to be numeric or dates of type np.datetime64, datetime.datetime, cftime.datetime or pd.Interval.

Output of xr.show_versions()

Code Sample

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

prepare fake data

time = np.arange(1000) data = time**2

write to multiple netcdf files

for i in range(10): filename = 'ds{:d}.nc'.format(i) ds = xr.Dataset({'data': (['time'], data[100i:100i+100])}, coords={'time': time[100i:100i+100]}, attrs={'history': 'Created ' + filename + '.'}) ds.to_netcdf(filename)

open as mfdataset

with xr.open_mfdataset('ds?.nc') as ds: print ds.history ```

Problem description

Currently, global attributes of multi-file datasets are taken from the first file in the list.

https://github.com/pydata/xarray/blob/b87b684b36cf5adbe4dca208aed0c69c44fc44c4/xarray/backends/api.py#L649

I think this is a problem in the context of consecutive model runs where history is appended in each subsequent run. When opening the results as mfdataset, history is taken from the first run file all subsequent history is lost.

NetCDF4 has a new keyword argument to set the master_file in a MFDataset (Unidata/netcdf4-python#835). Would it be possible to add a similar option in xarray?

Output of xr.show_versions()

Code Sample

```python import numpy as np import xarray as xr import matplotlib.pyplot as plt import matplotlib.colors as mcolors

prepare array with values between 1e0 and 1e3

da = xr.DataArray(np.logspace(0, 3, 24).reshape(4, 6), dims=('x', 'y'))

but we want to log-normalize between 1e0 and 1e2

norm = mcolors.LogNorm(1e1, 1e2)

plot with log norm

da.plot.imshow(norm=norm) # log norm is applied but bounds are replaced

da.plot.imshow(norm=norm, vmin=norm.vmin, vmax=norm.vmax) # works, but redundant

show results

plt.show()

```

Problem description

When passing a norm argument to imshow etc, the norm is forwarded to matplotlib but its data bounds are replaced with those calculated by xarray.

Expected Output

I think that the norm's vmin and vmax should take precedence over xarray-generated vmin and vmax.

Output of xr.show_versions()