Python | Matplotlib Graph plotting using object oriented API
In object-oriented API, first, we create a canvas on which we have to plot the graph and then we plot the graph. Many people prefer object-oriented API because it is easy to use as compared to functional API.
Let’s try to understand this with some examples.
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# importing matplotlib libraryimport matplotlib.pyplot as plt # x axis valuesx =[0, 5, 3, 6, 8, 4, 5, 7] # y axis valuesy =[5, 3, 6, 3, 7, 5, 6, 8] # creating the canvasfig = plt.figure() # setting the size of canvasaxes = fig.add_axes([0, 0, 1, 1]) # plotting the graphaxes.plot(x, y, 'mo--') # displaying the graphplt.show() |
Output:
Everything is pretty much clear in the first example but there is a thing that needs to be focused on, “Setting size of the canvas”, what this basically means is to set the size of the figure on which you want to plot the graph, the syntax is like this.
add_axes([left, bottom, width, height])
The values of left, bottom, height and width lies between 0 to 1. Another example will make you more clear about this concept.
Example #2:
# importing matplotlib libraryimport matplotlib.pyplot as plt # x-axis valuesx =[0, 1, 2, 3, 4, 5, 6] # y-axis valuesy =[0, 1, 3, 6, 9, 12, 17] # creating the canvasfig = plt.figure() # setting size of first canvasaxes1 = fig.add_axes([0, 0, 0.7, 1]) # plotting graph of first canvasaxes1.plot(x, y, 'mo--') # setting size of second canvasaxes2 = fig.add_axes([0.1, 0.5, 0.3, 0.3]) # plotting graph of second canvasaxes2.plot(x, y, 'go--') # displaying both graphsplt.show() |
Output:
