DataFrame.hist() does not get along with matplotlib.pyplot.tight_layout()

[vfilimonov]

When tight_layout() is called after DataFrame.hist() it raises AttributeError: 'NoneType' object has no attribute 'is_bbox if any of subplots is empty (number of charts with histograms is smaller than number os subplots).

I.e. the following code:

pd.DataFrame({'a':np.random.randn(100),
              'b':np.random.randn(100),
              }).hist()
plt.tight_layout()

works fine, but this code:

pd.DataFrame({'a':np.random.randn(100),
              'b':np.random.randn(100),
              'c':np.random.randn(100),
              }).hist()
plt.tight_layout()

raises AttributeError.

My versions:
pandas: 0.15.2
numpy: 1.9.1
scipy: 0.14.1
IPython: 2.3.1
matplotlib: 1.4.2

[ericmjl]

Ditto here, I can't seem to figure out what's going on.

[TomAugspurger]

Would either of you want to dig into what's causing the problem?

It seems that

    129         tight_bbox_raw = union([ax.get_tightbbox(renderer) for ax in subplots])

in matplotlib.tight_layout.auto_adjust_subplotpars returns None when it's expected to return a BBox.

[goyodiaz]

Actually, just before the error is raised, subplots is a list of one AxesSubplot instance for which get_visible() returns False. ax.get_tightbbox() returns None for invisible axes and auto_adjust_subplotpars() pass this None to TransformedBbox(), which expects a real Bbox and raises the exception.

Looks like a matplotlib issue to me, or maybe pandas should not be creating that invisible Axes.

A quick workaround would be to add something like this:

if tight_bbox_raw is None:
    continue

But it might have side effects.

[miraculixx]

+1

[ResidentMario]

As of matplotlib 2.0 this now works as expected.

[jreback]

@ResidentMario can you add a test to confirm this behavior (that skips if mpl < 2.0)?