Matplotlib Subplot And Subplots Examples

When drawing with Matplotlib, in most cases, we need to divide a canvas into several sub-areas, and then we can draw different graphics on these areas. In this section, we will learn how to draw multiple subgraphs on the same canvas.

1. Matplotlib subplot() Function.

1. The matplotlib.pyplot module provides a subplot() function, which can divide the canvas equally. The parameter format of this function is as follows.

   plt.subplot(nrows, ncols, index)
   
   nrows, ncols: Denotes the number of rows and columns to be divided into subregions (nrows*nclos denotes the number of subgraphs).
   
   index: The initial value is 1, which is used to select a specific sub region.

2. For example, the subplot(3, 6, 9) will divide the current canvas into 3 rows and 6 columns, at the same time, select the 9th sub-area to draw the subgraph.
3. Below is an example, it will divide the current canvas twice.
4. The first time it will divide the current canvas into 3 rows and 3 columns and draw a figure on the 9th sub-area.
5. The second time it will divide the current canvas into 2 rows and 3 columns and draw a figure on the second sub-area.
6. The 2 figures will override each other because they are on different sub-areas of the current canvas.
7. Below is the source code.

   # import the matplotlib.pyplot module.
   import matplotlib.pyplot as plt
   
   def subplot_example():
          
       # divide the current canvas into 3 rows and 3 columns, and draw the figure on the 9the sub area.
       plt.subplot(3, 3, 9)
       # plot the below figure on the 9th sub area.
       plt.plot(range(12))
       
       # divide the current canvas into 2 rows and  3 columns, and draw the figure on the second sub area.
       plt.subplot(232, facecolor='y')
       # plot the below figure on the second sub area.
       plt.plot(range(6))
       
       # the above 2 figures will not override each other, because they are on different sub area of the same canvas.
       
       # show the above 2 figures.
       plt.show()
   
   
   if __name__ == '__main__':
       
       subplot_example()

8. When you run the above example source code, you will get the below figure.
   

2. Matplotlib subplots() Function.

1. The matplotlib.pyplot module provides a subplots() function, which is similar to the subplot() function.
2. The difference is that subplots() create both a canvas containing subgraph areas and a figure graphic object, while subplot() only creates a canvas containing subgraph areas.

2.1 Syntax Of subplots() Function.

1. (fig , ax) = plt.subplots(nrows, ncols): nrows and ncols represent two integer parameters, which specify the number of rows and columns occupied by the subgraph.
2. The return value of the function is a tuple, including a graphic object and all axes objects.
3. The number of axes objects is equal to nrows * ncols, and each axes object can be accessed through the index value (starting from 1).

2.2 Matplotlib subplots() Example.

1. Next, we create a subgraph with 2 rows and 2 columns and display 4 different images in each subgraph.
2. Below is the example source code.

   # import the matplotlib.pyplot module.
   import matplotlib.pyplot as plt
   # import the numpy module.
   import numpy as np
   
   def subplots_example():
       
       # invoke the subplots function to create 4 axes objects and a figure object.
       (fig,a) =  plt.subplots(2,2)
   
       # create an array that contain number 1 to 100.
       x = np.arange(1,100)
       
       # draw exponential function image.
       a[0][0].plot(x,np.exp(x))
       a[0][0].set_title('exp')
   
       # draw logarithmic function image.
       a[0][1].plot(x,np.log10(x))
       a[0][1].set_title('log')
   
       # draw square function image.
       a[1][0].plot(x,x*x)
       a[1][0].set_title('square')
   
       # draw square root function image.
       a[1][1].plot(x,np.sqrt(x))
       a[1][1].set_title('square root')
   
       plt.show()
   
   if __name__ == '__main__':
       
       subplots_example()
   

3. When you run the above example source code, you will get the below figure.