Configuring a subnet layout using pandas

Question

I realized that matplotlib tight_layout() cannot be applied to charts generated by pandas .

This is the code I'm 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 get the following error:

AttributeError: 'NoneType' object has no attribute 'is_bbox'

I also believe this is due 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 tried to configure the parameter hspace. However, these keyword arguments are not accepted when calling the plot pandas function .

Any suggestions?

Answer 1

tight_layout() pandas!

tight_layout()

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

---

tight_layout()

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

Answer 2

piRSquared, , tight_layout() . .

Pandas , , , , .

. , .

plt.subplots_adjust(), .