Matplotlib 3.3 compatibility fixups #35393
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TomAugspurger
added
Visualization
| @@ -299,6 +300,11 @@ def plot_group(keys, values, ax): | |||
| if fontsize is not None: | |||
| ax.tick_params(axis="both", labelsize=fontsize) | |||
| if kwds.get("vert", 1): | |||
| ticks = ax.get_xticks() | |||
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This comes from a change in MPL being stricter about set_xticks. This worked for matplotlib 3.2
import pandas as pd
import matplotlib.pyplot as plt
import string
import numpy as np
fig, (ax1, ax2) = plt.subplots(ncols=2, sharex=True)
ax1.boxplot([
np.array([1, 2, 3, 4]),
np.array([1, 2, 3, 4])
])
ax2.boxplot([
np.array([1, 2, 2, 3]),
np.array([1, 2, 3, 4])
])
ax1.set_xticklabels(['A', 'B'])We set 2 x ticklabels despite there being 4.
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Yes, this was a deliberate change... matplotlib/matplotlib#17266 The obvious problem if you only give us 2 tick labels is that its ambiguous which of the 4 ticks you wanted labeled.
MPL now has categorical axes which I think were added because pandas has them. Probably too big a project to homogenize, but....
| @@ -411,8 +391,8 @@ def __call__(self): | |||
| interval = self._get_interval() | |||
| freq = f"{interval}L" | |||
| tz = self.tz.tzname(None) | |||
| st = _from_ordinal(dates.date2num(dmin)) # strip tz | |||
| ed = _from_ordinal(dates.date2num(dmax)) | |||
| st = dmin.replace(tzinfo=None) | |||
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If the comment is correct that this is really about stripping the tz, then this is cleaner since it doesn't rely on matplotlib's Datetime <-> numeric conversion.
| @@ -331,7 +332,7 @@ def test_freq_with_no_period_alias(self): | |||
| bts = tm.makeTimeSeries(5).asfreq(freq) | |||
| _, ax = self.plt.subplots() | |||
| bts.plot(ax=ax) | |||
| assert ax.get_lines()[0].get_xydata()[0, 0] == bts.index[0].toordinal() | |||
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This test, and some similar, are invalid now. The relationship between the plotted xy data and ordinals isn't necessarily stable / valuable.
| for kind in kinds: | ||
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| _, ax = self.plt.subplots() |
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Some strange interaction / issue when plotting on existing axes. IIRC it's from MPL being stricter about things. I didn't investigate too much.
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Its preferable to keep the reference to the figure and axes and then reuse, rather than depend on the implicit ability of plt.subplots() to pick up the same axes...
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cc @jklymak. The only change I'm uncertain about being a bug vs. deliberate is #35393 (comment). |
Matplotlib has supported datetime64 since v2.2.0, though there have been some bug fixed along the way.... |
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2.2.0 is our minimum right now, so I think we're good. |
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thanks @TomAugspurger |
Closes #34850
Closes #35350
Haven't tested with matplotlib's older than 3.2 yet. We'll see what CI says.