How to make custom legend in matplotlib

How to make custom legend in matplotlib

You can create a custom legend in Matplotlib by using the legend function along with the Line2D class from the matplotlib.lines module to define custom legend entries. Here's an example of how to create a custom legend:

import matplotlib.pyplot as plt from matplotlib.lines import Line2D # Create some example data x = [1, 2, 3, 4, 5] y1 = [1, 2, 3, 4, 5] y2 = [5, 4, 3, 2, 1] # Create a figure and axis fig, ax = plt.subplots() # Plot the data and customize the line styles line1, = ax.plot(x, y1, label='Line 1', linestyle='-', color='blue', marker='o') line2, = ax.plot(x, y2, label='Line 2', linestyle='--', color='red', marker='s') # Define custom legend entries using Line2D legend_elements = [ Line2D([0], [0], color='blue', lw=1, label='Line 1', marker='o'), Line2D([0], [0], color='red', lw=1, label='Line 2', linestyle='--', marker='s') ] # Add the custom legend to the plot ax.legend(handles=legend_elements, loc='upper right') # Show the plot plt.show()

In this example:

  1. We create a figure and axis using plt.subplots().

  2. We plot two lines (line1 and line2) with different styles (line style, color, marker).

  3. We define custom legend entries using the Line2D class. Each Line2D instance represents an entry in the legend and specifies its appearance.

  4. We add the custom legend to the plot using ax.legend(), passing the legend_elements list and specifying the location for the legend.

  5. Finally, we display the plot using plt.show().

This results in a custom legend with the specified line styles, colors, and markers for each entry. You can customize the legend entries further by adjusting the Line2D properties to match your desired appearance.

Examples

  1. "Matplotlib custom legend with labels"

    • Description: This query seeks information on how to create a custom legend in Matplotlib with specific labels for each element.
    • Code Implementation:
      import matplotlib.pyplot as plt # Create some data for demonstration x = range(10) y1 = [i**2 for i in x] y2 = [i**1.5 for i in x] # Plot the data plt.plot(x, y1, label='Squared') plt.plot(x, y2, label='Square root') # Create a custom legend with labels custom_legend = plt.legend(title='Functions', labels=['Squared', 'Square root']) # Show the plot plt.show()

  2. "Matplotlib custom legend position"

    • Description: Developers may want to customize the position of the legend in a Matplotlib plot to improve visualization.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data plt.plot([1, 2, 3], label='Line 1') plt.plot([3, 2, 1], label='Line 2') # Customize legend position plt.legend(loc='upper left') # Show the plot plt.show()

  3. "Matplotlib custom legend colors"

    • Description: This query involves customizing the colors of the legend elements in a Matplotlib plot.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data plt.plot([1, 2, 3], color='blue', label='Line 1') plt.plot([3, 2, 1], color='red', label='Line 2') # Customize legend colors plt.legend(facecolor='lightgray') # Show the plot plt.show()

  4. "Matplotlib custom legend markers"

    • Description: Developers may want to customize the markers in the legend to match the plot markers in a Matplotlib plot.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data with markers plt.plot([1, 2, 3], 'bo-', label='Line 1') plt.plot([3, 2, 1], 'r^--', label='Line 2') # Customize legend markers plt.legend(markerfirst=False) # Show the plot plt.show()

  5. "Matplotlib custom legend title"

    • Description: This query focuses on adding a title to the legend in a Matplotlib plot for better understanding.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data plt.plot([1, 2, 3], label='Line 1') plt.plot([3, 2, 1], label='Line 2') # Add a title to the legend plt.legend(title='Lines') # Show the plot plt.show()

  6. "Matplotlib custom legend font size"

    • Description: Developers might want to adjust the font size of the legend in a Matplotlib plot for better readability.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data plt.plot([1, 2, 3], label='Line 1') plt.plot([3, 2, 1], label='Line 2') # Customize legend font size plt.legend(fontsize='large') # Show the plot plt.show()

  7. "Matplotlib custom legend background color"

    • Description: This query pertains to changing the background color of the legend box in a Matplotlib plot.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data plt.plot([1, 2, 3], label='Line 1') plt.plot([3, 2, 1], label='Line 2') # Customize legend background color plt.legend(facecolor='lightgray') # Show the plot plt.show()

  8. "Matplotlib custom legend with line styles"

    • Description: Developers may want to include line styles in the legend along with labels in a Matplotlib plot.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data with line styles plt.plot([1, 2, 3], 'r-', label='Line 1') plt.plot([3, 2, 1], 'g--', label='Line 2') # Customize legend with line styles plt.legend(handlelength=2) # Show the plot plt.show()

  9. "Matplotlib custom legend with markers"

    • Description: This query involves including markers along with labels in the legend of a Matplotlib plot.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot some data with markers plt.plot([1, 2, 3], 'ro-', label='Line 1') plt.plot([3, 2, 1], 'gs--', label='Line 2') # Customize legend with markers plt.legend(markerfirst=False) # Show the plot plt.show()

  10. "Matplotlib custom legend for multiple plots"

    • Description: Developers may want to create a custom legend for multiple plots in a single Matplotlib figure.
    • Code Implementation:
      import matplotlib.pyplot as plt # Plot multiple datasets plt.plot([1, 2, 3], label='Line 1') plt.scatter([1, 2, 3], [4, 5, 6], color='red', label='Scatter 1') # Customize legend for multiple plots plt.legend(loc='upper right') # Show the plot plt.show()

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