Adjusting subplot layout with pandas

matplotlib, pandas, python, subplot

Solution

`tight_layout()` definitely works with pandas!

without `tight_layout()`

df.T.plot(kind='bar', subplots=True, width=0.7, legend=False, 
                             layout=(3, 2), sharex=True, sharey=True)
# plt.tight_layout()

with `tight_layout()`

df.T.plot(kind='bar', subplots=True, width=0.7, legend=False, 
                             layout=(3, 2), sharex=True, sharey=True)
plt.tight_layout()

Problem

I came to realize that matplotlib's `tight_layout()` cannot be applied to plots generated by pandas. This is the code I am running: ``` 0 1 2 3 4 A 0.039895 0.960105 NaN NaN NaN D 0.030418 0.969582 NaN NaN NaN E 0.037345 0.962655 NaN NaN NaN F 0.061522 0.938478 NaN NaN NaN G 0.047163 0.952837 NaN NaN NaN H 0.026423 0.000000 0.000000 0.973577 NaN df.T.plot(kind='bar', subplots=True, width=0.7, legend=False, layout=(2,4), sharex=True, sharey=True) plt.tight_layout() ``` I end up with the following error: ``` AttributeError: 'NoneType' object has no attribute 'is_bbox' ``` I also believe that this is related to a similar issue posted on github: DataFrame.hist() does not get along with matplotlib.pyplot.tight_layout() #9351 Therefore, I am looking for a workaround based on `subplots_adjust(*args, **kwargs)`. Most importantly, I was trying to adjust the `hspace` parameter. However, these keyword arguments are not accepted when calling the `plot` function of pandas. Any suggestions?

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