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At times, we might want to display more than one chart at a time. We can achieve this by using subplots.
First, import Pyplot
import matplotlib.<< your code goes here >> as plt
Now we will create a sample plot
We did this to demonstrate that creating a subplot will delete any pre-existing subplot that overlaps with it beyond sharing a boundary.
Now, in the same cell as before, we will create a subplot using the
subplot() function with top plot of a grid with 2 rows and 1 column. Since this subplot will overlap the first, the plot (and its axes) previously created, will be removed
plt.<< your code goes here >>(2,1,1) plt.plot(range(12)) plt.subplot(2,1,2, facecolor='red') plt.plot(range(12)) plt.show()
The third line creates a second subplot with red background.
You can add an insert plot in the same figure by adding another axes object in the same figure canvas. The
matplotlib.figure module contains the Figure class. It is a top-level container for all plot elements. The
Figure object is instantiated by calling the
figure() function of the
pyplot module. You can create it as follows:
import matplotlib.pyplot as plt import numpy as np import math x = np.arange(0, math.pi*2, 0.09) fig=plt.figure() axes1 = fig.add_axes([0.1, 0.1, 0.9, 0.9]) axes2 = fig.add_axes([0.62, 0.62, 0.3, 0.3]) y = np.sin(x) axes1.plot(x, y, 'b') axes2.plot(x,np.cos(x),'r') axes1.set_title('sine') axes2.set_title("cosine") plt.show()
Here, axes1 is the main axes, and axes2 is the inset axes. You can test with different values to move and resize the charts.
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