What is the difference between drawing plots using plot, axes or figure in matplotlib?

I'm kind of confused what is going at the backend when I draw plots in matplotlib, tbh, I'm not clear with the hierarchy of plot, axes and figure. I read the documentation and it was helpful but I'm still confused...

The below code draws the same plot in three different ways -

    #creating the arrays for testing
    x = np.arange(1, 100)
    y = np.sqrt(x)
    #1st way
    plt.plot(x, y)
    #2nd way
    ax = plt.subplot()
    ax.plot(x, y)
    #3rd way
    figure = plt.figure()
    new_plot = figure.add_subplot(111)
    new_plot.plot(x, y)

Now my question is -

  1. What is the difference between all the three, I mean what is going under the hood when any of the 3 methods are called?

  2. Which method should be used when and what are the pros and cons of using any on those?

Method 1

    plt.plot(x, y)

This lets you plot just one figure with (x,y) coordinates. If you just want to get one graphic, you can use this way.

Method 2

    ax = plt.subplot()
    ax.plot(x, y)

This lets you plot one or several figure(s) in the same window. As you write it, you will plot just one figure, but you can make something like this:

    fig1, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)

You will plot 4 figures which are named ax1, ax2, ax3 and ax4 each one but on the same window. This window will be just divided in 4 parts with my example.

Method 3

    fig = plt.figure()
    new_plot = fig.add_subplot(111)
    new_plot.plot(x, y)

I didn't use it, but you can find documentation.

Example:

    import numpy as np
    import matplotlib.pyplot as plt

    # Method 1 #

    x = np.random.rand(10)
    y = np.random.rand(10)

    figure1 = plt.plot(x,y)

    # Method 2 #

    x1 = np.random.rand(10)
    x2 = np.random.rand(10)
    x3 = np.random.rand(10)
    x4 = np.random.rand(10)
    y1 = np.random.rand(10)
    y2 = np.random.rand(10)
    y3 = np.random.rand(10)
    y4 = np.random.rand(10)

    figure2, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
    ax1.plot(x1,y1)
    ax2.plot(x2,y2)
    ax3.plot(x3,y3)
    ax4.plot(x4,y4)

    plt.show()

enter image description here enter image description here

Other example:

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From: stackoverflow.com/q/37970424