[Bug]: Some matplotlib functions do not work anymore with pandas and numpy 1.24.0

[tomMoral]

Bug summary

The new release of numpy introduces a change in np.ma.masked_invalid which makes it not compatible with pandas Series anymore. This breaks some functionality of matplotlib like plt.fill_betweenx.

Reported this in numpy/numpy#22829. Not sure where this should be fixed.

Code for reproduction

import matplotlib.pyplot as plt
import pandas as pd

a = pd.Series([1, 2, 3])
plt.fill_betweenx(a, a, a)

Actual outcome

---

TypeError Traceback (most recent call last)
Cell In[4], line 1
----> 1 plt.fill_betweenx(a, a, a)

File ~/.local/miniconda/envs/test_benchopt/lib/python3.11/site-packages/matplotlib/pyplot.py:2536, in fill_betweenx(y, x1, x2, where, step, interpolate, data, **kwargs)
2532 @_copy_docstring_and_deprecators(Axes.fill_betweenx)
2533 def fill_betweenx(
2534 y, x1, x2=0, where=None, step=None, interpolate=False, *,
2535 data=None, **kwargs):
-> 2536 return gca().fill_betweenx(
2537 y, x1, x2=x2, where=where, step=step, interpolate=interpolate,
2538 **({"data": data} if data is not None else {}), **kwargs)

File ~/.local/miniconda/envs/test_benchopt/lib/python3.11/site-packages/matplotlib/init.py:1423, in _preprocess_data..inner(ax, data, *args, **kwargs)
1420 @functools.wraps(func)
1421 def inner(ax, *args, data=None, **kwargs):
1422 if data is None:
-> 1423 return func(ax, *map(sanitize_sequence, args), **kwargs)
1425 bound = new_sig.bind(ax, *args, **kwargs)
1426 auto_label = (bound.arguments.get(label_namer)
1427 or bound.kwargs.get(label_namer))

File ~/.local/miniconda/envs/test_benchopt/lib/python3.11/site-packages/matplotlib/axes/_axes.py:5381, in Axes.fill_betweenx(self, y, x1, x2, where, step, interpolate, **kwargs)
5379 def fill_betweenx(self, y, x1, x2=0, where=None,
5380 step=None, interpolate=False, **kwargs):
-> 5381 return self._fill_between_x_or_y(
5382 "y", y, x1, x2,
5383 where=where, interpolate=interpolate, step=step, **kwargs)

File ~/.local/miniconda/envs/test_benchopt/lib/python3.11/site-packages/matplotlib/axes/_axes.py:5272, in Axes._fill_between_x_or_y(self, ind_dir, ind, dep1, dep2, where, interpolate, step, **kwargs)
5268 kwargs["facecolor"] =
5269 self._get_patches_for_fill.get_next_color()
5271 # Handle united data, such as dates
-> 5272 ind, dep1, dep2 = map(
5273 ma.masked_invalid, self._process_unit_info(
5274 [(ind_dir, ind), (dep_dir, dep1), (dep_dir, dep2)], kwargs))
5276 for name, array in [
5277 (ind_dir, ind), (f"{dep_dir}1", dep1), (f"{dep_dir}2", dep2)]:
5278 if array.ndim > 1:

File /.local/miniconda/envs/test_benchopt/lib/python3.11/site-packages/numpy/ma/core.py:2360, in masked_invalid(a, copy)
2332 def masked_invalid(a, copy=True):
2333 """
2334 Mask an array where invalid values occur (NaNs or infs).
2335
(...)
2357
2358 """
-> 2360 return masked_where((np.isfinite(getdata(a))), a, copy=copy)

TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

Expected outcome

No error and a figure :)

Additional information

This issue was introduced by numpy/numpy#22046, shipped starting version 1.24.0 of numpy.

Operating system

linux

Matplotlib Version

3.6.2

Matplotlib Backend

TkAgg

Python version

3.11.0

Jupyter version

No response

Installation

pip

[oscargus]

This seems to work in the current main branch. (As in no error.)

[rcomer]

It seems you can reproduce the error without Matplotlib:
numpy/numpy#22826

[rcomer]

There is now a fix in numpy ready for the first patch release: numpy/numpy#22839

@tomMoral do you think the numpy patch will solve your issue or is there more to do here? I’m afraid I’m not familiar with pandas.

[tomMoral]

The fix in numpy is enough, thanks a lot for the answer.

Closing as this is not a bug but an incompatible numpy version.