Consistent way of getting labels from plot, bar and other drawings with matplotlib-CodePudding

With line plots, I can get all labels like this and build a legend:

p1 = ax1.plot(x, 'P1', data=df)
p2 = ax1.plot(x, 'P2', data=df)
p3 = ax1.plot(x, 'P3', data=df)
p4 = ax1.plot(x, 'P4', data=df)

p = p1 p2 p3 p4
labs = [l.get_label() for l in p]
ax1.legend(p, labs, loc=0, frameon=False)

When I have bar plots, this does not work anymore. E.g.:

b1 = ax1.bar(x-2*w, 'B1', data=df, width=w, label="TP")
b2 = ax1.bar(x-w, 'B2', data=df, width=w, label="FN")
b3 = ax1.bar(x, 'B3', data=df, width=w, label="FP")
b4 = ax2.bar(x w, 'B4', data=df, width=w, label="AP")
b5 = ax2.bar(x 2*w, 'B5', data=df, width=w, label="AR")

b1.get_label() returns a string similar to a __str__ method:

'0    87
Name: TP, dtype: object'

Why does .get_label() not behave identically?

CodePudding user response：

ax1.plot(...) returns a

The same can be written as follows, making it easier to combine handles from different functions:

p1, = ax1.plot(x, 'P1', data=df)
p2, = ax1.plot(x, 'P2', data=df)
p3, = ax1.plot(x, 'P3', data=df)
p4, = ax1.plot(x, 'P4', data=df)

p = [p1, p2, p3, p4]
ax1.legend(handles=p, frameon=False)
plt.show()

That makes it similar to how you would work with bars:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

x = np.arange(5)
df = pd.DataFrame({f'B{i}': np.random.rand(5).cumsum() for i in range(1, 6)})
fig, ax1 = plt.subplots()
w = 0.19
b1 = ax1.bar(x - 2 * w, 'B1', data=df, width=w, label="TP")
b2 = ax1.bar(x - w, 'B2', data=df, width=w, label="FN")
b3 = ax1.bar(x, 'B3', data=df, width=w, label="FP")
b4 = ax1.bar(x   w, 'B4', data=df, width=w, label="AP")
b5 = ax1.bar(x   2 * w, 'B5', data=df, width=w, label="AR")

ax1.legend(handles=[b1, b2, b3, b4, b5], frameon=False)
plt.show()

Of course, in these cases, the legend can also be created automatically. However, explicit working with these handles can be interesting if you need finetuning the legend, or you want to combine two handles into one.