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. But before that make sure Python and PIP are already installed on a system :
To install pip you can refer to this article : Python PIP
After checking Python and PIP in your system, You need to run this command to install Matplotlib.
python -mpip install -U matplotlib
Importing matplotlib
After successfully installing matplotlib , You can run this command to import matplotlib on your system.
Import matplotlib
Basic plots in Matplotlib
Matplotlib comes with a wide variety of plots. Plots help to understand trends, and patterns, and to make correlations. They’re typically instruments for reasoning about quantitative information. Some of the sample plots are covered here.
Line plot using Matplotlib
By importing the matplotlib module, defines x and y values for a plots, plots the data using the plot() function and it helps to display the plot by using the show() function . The plot() creates a line plot by connecting the points defined by x and y values.
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()
|
Output :
Plots in Matplotlib
Bar plot using Matplotlib
By using matplotlib library in python , it allows us to access the functions and classes provided by the library for plotting. There are tow list x and y are defined . This function creates a bar plot by taking x-axis and y-axis values as arguments and generates the bar plot based on those values.
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()
|
Output:
Bar Plot
Histogram using Matplotlib
By using the matplotlib module defines the y-axis values for a histogram plot. Plots in histogram using the hist() function and displays the plot using the show() function. The hist() function creates a histogram plot based on the values in the y-axis list.
Python3
from matplotlib import pyplot as plt
y = [10, 5, 8, 4, 2]
plt.hist(y)
plt.show()
|
Output:
Histogram
Scatter Plot using Matplotlib
By imports the matplotlib module, defines x and y values for a scatter plot, plots the data using the scatter() function, and displays the plot using the show() function. The scatter() function creates a scatter plot by plotting individual data points defined by the x and y values.
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()
|
Output :
Scatter Plot
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()
|
Output:
Scatter Plot by using plot()