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Matplotlib.pyplot.thetagrids() in Python

  • Last Updated : 29 Jul, 2021

Matplotlib is a plotting library of Python programming language and its numerical mathematics module is NumPy. matplotlib.pyplot is a collection of command style functions that make matplotlib work like the MATLAB Tool. Each of the pyplot functions makes certain changes to a figure: e.g., creating a figure, creating a plot area in a figure, plots some lines in a plotting area or decorate the plot with labels, etc.
Note: For more information, refer to Pyplot in Matplotlib



Set the theta locations of the gridlines in the polar plot. If no arguments are passed, it returns a tuple (lines, labels) where lines are an array of radial gridlines (Line2D instances) and labels is an array of tick labels (Text instances):


Syntax: lines, labels = thetagrids(angles, labels=None, fmt=’%d’, frac = 1.5)

  • Angles:

set the angles to the place of theta grids (these gridlines are equal along the theta dimension)

  • labels:

if not None, then it is len(angles) or list of strings of the labels to use at each angle. If labels are None, the labels will be fmt%angle.

  • frac: It is the fraction of the polar axes radius at the place of label (1 is the edge). e.g., 1.25 is outside the axes and 0.75 is inside the axes. 

    Return Type: Return value is a list of tuples (lines, labels)
    Note: lines are Line2D instances, labels are Text instances.

  • Example:


    import matplotlib.pyplot as plt
    import numpy as np
    employee = ["Rahul", "Joy", "Abhishek",
                "Tina", "Sneha"]
    actual = [41, 57, 59, 63, 52, 41]
    expected = [40, 59, 58, 64, 55, 40]
    # Initialing the spiderplot by 
    # setting figure size and polar
    # projection
    plt.figure(figsize =(10, 6))
    plt.subplot(polar = True)
    theta = np.linspace(0, 2 * np.pi, len(actual))
    # Arranging the grid into number 
    # of sales into equal parts in
    # degrees
    lines, labels = plt.thetagrids(range(0, 360, int(360/len(employee))),
    # Plot actual sales graph
    plt.plot(theta, actual)
    plt.fill(theta, actual, 'b', alpha = 0.1)
    # Plot expected sales graph
    plt.plot(theta, expected)
    # Add legend and title for the plot
    plt.legend(labels =('Actual', 'Expected'),
               loc = 1)
    plt.title("Actual vs Expected sales by Employee")
    # Display the plot on the screen




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