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This article mainly introduces the Matplotlib subplot and subplots how to use the relevant knowledge, the content is detailed and easy to understand, the operation is simple and fast, has a certain reference value, I believe you will have something to gain after reading this Matplotlib subplot and subplots article, let's take a look at it.

The comparison begins:

Requirements: draw two subgraphs and display them on one line. The contents of the subgraphs are exactly the same.

Subplot Code:

Ax1 = plt.subplot ax1.scatter (positive ['X1'], positive [' X2'], sword50, marker='x', label='Positive') ax1.scatter (negative ['X1'], negative [' X2'], scurvie 50, marker='o', label='Negative') ax1.legend () # adding the image column is the top right-hand corner, indicating that ax2 = plt.subplot (1mezzo 2) ax2.scatter (positive ['X1'], positive [' X2'], slot50, marker='x') Label='Positive') ax2.scatter (negative ['X1'], negative [' X2'], saw50, marker='o', label='Negative') ax2.legend () # add the column is the point description in the upper right corner

Subplots Code:

Fig, ax = plt.subplots (figsize= (12Power8), ncols=2,nrows=1) # this method returns the drawing object and coordinate object ax,figsize is to set the length and width of the subimage (1200 Ax [0] .audter (positive ['X1'], positive [' X2'], sprinter 50, marker='x', label='Positive') ax [0] .accounter (negative ['X1'], negative [' X2'], slot50, marker='o', label='Negative') ax [0] .explanation () # adding the image column is the dot description in the upper right corner ax [1] .roomter (positive ['X1'], positive [' X2'], sprinter 50, marker='x' Label='Positive') ax [1] .roomter (negative ['X1'], negative [' X2'], saw50, marker='o', label='Negative') ax [1] .adding the figure column is the comparison result in the upper right corner:

You can see that both of them can achieve the function of drawing sub-images, but subplots helps us plan the artboard and returns an array of coordinate objects, while subplot can only return one coordinate object at a time. Subplots can directly specify the size of the artboard.

This is the end of the article on "how to use Matplotlib's subplot and subplots". Thank you for reading! I believe you all have a certain understanding of the knowledge of "how to use Matplotlib's subplot and subplots". If you want to learn more, you are welcome to follow the industry information channel.

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