Prerequisite: Matplotlib
Plots are an effective way of visually representing data and summarizing it in a beautiful manner. However, if not plotted efficiently it seems appears complicated. In python’s matplotlib provides several libraries for the purpose of data representation.
While making a plot it is important for us to optimize its size. Here are various ways to change the default plot size as per our required dimensions or resize a given plot.
Method 1: Using set_figheight() and set_figwidth()
For changing height and width of a plot set_figheight and set_figwidth are used
Python3
import matplotlib.pyplot as plt
x = [ 1 , 2 , 3 , 4 , 5 ]
y = [ 1 , 2 , 3 , 4 , 5 ]
plt.xlabel( 'x - axis' )
plt.ylabel( 'y - axis' )
print ( "Plot in it's default size: " )
plt.plot(x, y)
plt.show()
f = plt.figure()
f.set_figwidth( 4 )
f.set_figheight( 1 )
print ( "Plot after re-sizing: " )
plt.plot(x, y)
plt.show()
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Output:

Method 2: Using figsize
figsize() takes two parameters- width and height (in inches). By default the values for width and height are 6.4 and 4.8 respectively.
Syntax:
plt.figure(figsize=(x,y))
Where, x and y are width and height respectively in inches.
Python3
import matplotlib.pyplot as plt
x = [ 1 , 2 , 3 , 4 , 5 ]
y = [ 6 , 7 , 8 , 9 , 10 ]
display(plt.plot(x, y))
plt.figure(figsize = ( 2 , 2 ))
display(plt.plot(x, y))
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Output:

output screenshot
Method 3: Changing the default rcParams
We can permanently change the default size of a figure as per our needs by setting the figure.figsize.
Python3
import matplotlib.pyplot as plt
x = [ 1 , 2 , 3 , 4 , 5 ]
y = [ 1 , 2 , 3 , 4 , 5 ]
plt.xlabel( 'x - axis' )
plt.ylabel( 'y - axis' )
plt.plot(x, y)
plt.show()
plt.rcParams[ 'figure.figsize' ] = [ 2 , 2 ]
plt.plot(x, y)
plt.show()
plt.scatter(x, y)
plt.show()
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Output:

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Last Updated :
26 Nov, 2020
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