Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. It was introduced by John Hunter in the year 2002. One of the greatest benefits of visualization is that it allows us visual access to huge amounts of data in easily digestible visuals. Matplotlib consists of several plots like line, bar, scatter, histogram etc. Installation : Windows, Linux and macOS distributions have matplotlib and most of its dependencies as wheel packages. Run the following command to install matplotlib package :
python -mpip install -U matplotlib
Importing matplotlib :
Basic plots in Matplotlib :
Matplotlib comes with a wide variety of plots. Plots helps to understand trends, patterns, and to make correlations. They’re typically instruments for reasoning about quantitative information. Some of the sample plots are covered here. Line plot :
Python3
from matplotlib import pyplot as plt
x = [ 5 , 2 , 9 , 4 , 7 ]
y = [ 10 , 5 , 8 , 4 , 2 ]
plt.plot(x,y)
plt.show()
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Output :
Bar plot :
Python3
from matplotlib import pyplot as plt
x = [ 5 , 2 , 9 , 4 , 7 ]
y = [ 10 , 5 , 8 , 4 , 2 ]
plt.bar(x,y)
plt.show()
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Output :
Histogram :
Python3
from matplotlib import pyplot as plt
y = [ 10 , 5 , 8 , 4 , 2 ]
plt.hist(y)
plt.show()
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Output :
Scatter Plot :
Python3
from matplotlib import pyplot as plt
x = [ 5 , 2 , 9 , 4 , 7 ]
y = [ 10 , 5 , 8 , 4 , 2 ]
plt.scatter(x, y)
plt.show()
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Output :
We can also plot a scatter plot using the plot() method by providing the marker style as ‘o’.
Python3
from matplotlib import pyplot as plt
x = [ 5 , 2 , 9 , 4 , 7 ]
y = [ 10 , 5 , 8 , 4 , 2 ]
plt.plot(x,y, 'o' )
plt.show()
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Output –
Reference : Matplotlib Documentation.