Matplotlib: display legend keys for lines as patches by default

Making this appear by default probably wouldn’t work, as there are too many differences between lines and patches. Lines can have a line width, markes, line styles, … . Patches can have an outline, hatching, ….

For a simple situation with just a colored, you might use rectangles:

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

fig, ax = plt.subplots()
ax.plot(np.random.randn(100).cumsum(), color='tomato', label='red line')
ax.plot(np.random.randn(100).cumsum(), color='cornflowerblue', alpha=0.6, label='blue line')

handles, labels = ax.get_legend_handles_labels()
new_handles = [h if type(h) != matplotlib.lines.Line2D
               else plt.Rectangle((0, 0), 0, 0, lw=0, color=h.get_color(), alpha=h.get_alpha()) for h in handles]

ax.legend(new_handles, labels)
plt.show()

You can display legend as patches doing the following:

import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches

colors = [['#01FF4F','#00FFff'],
           ['#FFEB00','#FFFF00']]
categories = ['A','B']
# categories and colors inside a dict
legend_dict=dict(zip(categories,colors))
# setting up lines for the plot and list for patches
patchList = []
fig, ax = plt.subplots()
# assigning each inner color for each categories to their respective plot lines and legend/patches
for key in legend_dict:
        data_key = mpatches.Patch(facecolor=legend_dict[key][0],
                                  edgecolor=legend_dict[key][1], label=key)
        ax.plot(np.random.randn(100).cumsum(), color=legend_dict[key][0], label=legend_dict[key][1])
        patchList.append(data_key)

ax.legend(handles=patchList, ncol=len(categories), fontsize='small')
plt.show()

Which output:

I didn’t know matplotlib before making this answer, so I had to mix two or three SO post to get this far (and trying/failing for a bit). Here they are, in a non-special order:

• https://stackoverflow.com/a/57791790/12349101
• https://stackoverflow.com/a/73832036/12349101 (one line from answer of this post)
• https://stackoverflow.com/a/39500357/12349101

Since you mentioned Line2d:

import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from matplotlib.lines import Line2D

colors = [['#01FF4F','#00FFff'],
           ['#FFEB00','#FFFF00']]
categories = ['A','B']
# categories and colors inside a dict
legend_dict=dict(zip(categories,colors))
# setting up lines for the plot and list for patches
patchList = []
fig, ax = plt.subplots()
# assigning each inner color for each categories to their respective plot lines and legend/patches
for key in legend_dict:
        data_key = mpatches.Patch(facecolor=legend_dict[key][0],
                                  edgecolor=legend_dict[key][1], label=key)
        ax.plot(Line2D(np.random.randn(100).cumsum(), np.random.randn(100).cumsum()).get_data(), color=legend_dict[key][0], label=legend_dict[key][1])
        patchList.append(data_key)

ax.legend(handles=patchList, ncol=len(categories), fontsize='small')
plt.show()

Output:

One intriguing and related to patches as legend post that I can’t help but link to: Make patches bigger used as legend inside matplotlib

lastly, here is a decent excerpt related to customizing legend on matplotlib: https://jakevdp.github.io/PythonDataScienceHandbook/04.06-customizing-legends.html