Format y axis as percent in Matplotlib

Format y axis as percent in Matplotlib

You can format the y-axis as a percentage in Matplotlib using the FuncFormatter from the matplotlib.ticker module. Here's how you can achieve that:

import matplotlib.pyplot as plt import matplotlib.ticker as mtick import numpy as np # Sample data x = np.arange(5) y = np.array([0.2, 0.35, 0.6, 0.8, 0.95]) # Create a figure and axis fig, ax = plt.subplots() # Plot the data ax.plot(x, y) # Format y-axis as percentage fmt = '%.0f%%' # Define the format (0 decimal places) yticks = mtick.FormatStrFormatter(fmt) # Create the formatter ax.yaxis.set_major_formatter(yticks) # Apply the formatter to the y-axis # Show the plot plt.show()

In this example, the mtick.FormatStrFormatter(fmt) function is used to create a custom formatter for the y-axis. The format string '%.0f%%' specifies that the y-axis values should be displayed with 0 decimal places and followed by a percentage sign. You can adjust the format string to display a different number of decimal places or customize the appearance as needed.

Make sure you have Matplotlib installed (pip install matplotlib) and customize the example with your own data as necessary.

Examples

  1. "Matplotlib format y axis as percent" Description: Learn how to format the y-axis as a percentage in Matplotlib to represent data in percentage form. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [0.1, 0.3, 0.5, 0.7, 0.9] # Plot plt.plot(x, y) # Format y-axis as percent plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.show()

  2. "Matplotlib y axis as percent with custom ticks" Description: Find out how to customize the ticks on the y-axis formatted as percentages in Matplotlib for better visualization. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [0.1, 0.3, 0.5, 0.7, 0.9] # Plot plt.plot(x, y) # Format y-axis as percent with custom ticks plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1, decimals=1)) plt.show()

  3. "Python Matplotlib format y axis as percentage" Description: Explore methods to format the y-axis as percentages in Python using Matplotlib for clear data representation. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [0.1, 0.3, 0.5, 0.7, 0.9] # Plot plt.plot(x, y) # Format y-axis as percentage plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.show()

  4. "Matplotlib y axis format as percent with grid" Description: Learn how to format the y-axis as percentages with a grid in Matplotlib for improved visualization of data. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [0.1, 0.3, 0.5, 0.7, 0.9] # Plot plt.plot(x, y) # Format y-axis as percent with grid plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.grid(True) plt.show()

  5. "Python Matplotlib format y axis as percent without ticks" Description: Find out how to format the y-axis as percentages in Matplotlib without displaying ticks for a cleaner plot. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [0.1, 0.3, 0.5, 0.7, 0.9] # Plot plt.plot(x, y) # Format y-axis as percent without ticks plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.gca().tick_params(axis='y', which='both', length=0) plt.show()

  6. "Matplotlib format y axis as percent with specific precision" Description: Learn how to format the y-axis as percentages with a specific precision in Matplotlib to control the number of decimal places. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [0.1, 0.3, 0.5, 0.7, 0.9] # Plot plt.plot(x, y) # Format y-axis as percent with specific precision plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1, decimals=2)) plt.show()

  7. "Python Matplotlib y axis as percent with log scale" Description: Find out how to format the y-axis as percentages with a logarithmic scale in Matplotlib for better visualization of data. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [0.1, 0.3, 0.5, 0.7, 0.9] # Plot plt.plot(x, y) # Format y-axis as percent with log scale plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.yscale('log') plt.show()

  8. "Matplotlib format y axis as percent with multiple subplots" Description: Learn how to format the y-axis as percentages in Matplotlib with multiple subplots for comparison of data. Code:

    import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y1 = [0.1, 0.3, 0.5, 0.7, 0.9] y2 = [0.2, 0.4, 0.6, 0.8, 1.0] # Create subplots fig, axs = plt.subplots(2) # Plot data on each subplot axs[0].plot(x, y1) axs[1].plot(x, y2) # Format y-axis as percent on each subplot for ax in axs: ax.yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.show()

  9. "Python Matplotlib format y axis as percent with bar plot" Description: Find out how to format the y-axis as percentages in Matplotlib when creating a bar plot for visualizing categorical data. Code:

    import matplotlib.pyplot as plt # Sample data categories = ['A', 'B', 'C', 'D'] values = [0.1, 0.3, 0.5, 0.7] # Create bar plot plt.bar(categories, values) # Format y-axis as percent plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.show()

  10. "Matplotlib format y axis as percent with heatmap" Description: Learn how to format the y-axis as percentages in Matplotlib when creating a heatmap for visualizing data distributions. Code:

    import matplotlib.pyplot as plt import numpy as np # Sample data data = np.random.rand(5, 5) # Create heatmap plt.imshow(data, cmap='viridis', interpolation='nearest') plt.colorbar() # Format y-axis as percent plt.gca().yaxis.set_major_formatter(plt.PercentFormatter(xmax=1)) plt.show()

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