Create clickable legends.
Description:
This code creates a plot with clickable legends, allowing users to toggle the visibility of each data series by clicking on the legend items.
Code Explanation:
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First, we import matplotlib for plotting.
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We create sample data for multiple lines (like product A, B, C).
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Then we plot each line with a label, which will show in the legend.
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We use
legend = ax.legend()to create a legend and store it in a variable. -
We make each legend item clickable using
legend.set_picker(True)and assign a pick event handler. -
When a legend item is clicked:
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The corresponding line's visibility is toggled.
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The legend item's appearance (like fading out) is also updated to reflect its visibility.
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This is useful for interactive dashboards or when analyzing multiple data series.
Program:
import matplotlib.pyplot as plt
import numpy as np
# Create sample data
x = np.linspace(0, 10, 100)
y1 = np.sin(x)
y2 = np.cos(x)
y3 = np.sin(x + np.pi / 4)
# Create the plot
fig, ax = plt.subplots()
line1, = ax.plot(x, y1, label='Product A')
line2, = ax.plot(x, y2, label='Product B')
line3, = ax.plot(x, y3, label='Product C')
# Add the legend and make it clickable
legend = ax.legend(loc='upper right')
lines = [line1, line2, line3]
lined = dict()
# Link each legend item to its corresponding line
for legline, origline in zip(legend.get_lines(), lines):
legline.set_picker(True)
lined[legline] = origline
# Define what happens when legend is clicked
def on_pick(event):
legline = event.artist
origline = lined[legline]
visible = not origline.get_visible()
origline.set_visible(visible)
legline.set_alpha(1.0 if visible else 0.2)
fig.canvas.draw()
# Connect the pick event to the handler
fig.canvas.mpl_connect('pick_event', on_pick)
# Show the plot
plt.title("Interactive Clickable Legends")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.grid(True)
plt.show()
Output:
