Matplotlib in Python: A Detailed Understanding on Functionalities and Installation

This is a matplotlib window, which allows us to navigate, observe, and modify our graph. You can usually see the coordinates in the bottom right corner of the graph if you hover over it. The buttons can also be used for interacting with the application. These buttons can be found in a variety of places, but in the image above, they’re in the lower-left corner.

Here, each icon is a separate entity and helps you explore the application further. 

Usage of Matplotlib Function

Relation with Numpy:

Numpy is a scientific computing software. Matplotlib requires Numpy, which employs NumPy functions for numerical data and multi-dimensional arrays, as illustrated in the following code snippet of a NumPy array

import numpy as nmp 

from matplotlib import pyplot as pplt 

# forming an ndarray on x axis using the numpy range() function:
x = nmp.arange(2,13)
# Store equation values on y axis:
y = 5*x-1 
pplt.title(“Plot of numpy array”)
# Plot values using x,y coordinates:
pplt.plot(x,y)
pplt.show()

Check our US - Data Science Programs

Line plots in Matplotlib+

A line plot is used to see how the x and y axes are related in the function provided to us by the user.

The plot() function in the Pyplot module of the Matplotlib package is used to plot the coordinates x and y in a 2D hexagonal plot. 

plot() accepts several arguments, including plot(x, y, scalex, scaley, data, kwargs). [kwargs specific properties such as line label, linewidth, marker, color, and so on.]

x, y are the horizontal and vertical axis coordinates, with x values being optional and range(len(y) being the default value.

The scalex and scaley options are used to autoscale the x- and y-axes, respectively, with the default value of true.

Code snippet for a line plot, as per analyticsvidhya.com

#this line will create array of numbers between 1 to 10 of length 100 
#np.linspace(start,stop,num) 
x1 = np.linspace(0, 10, 100)  #line plot 
pplt.plot(x1, np.sin(x1), ‘-‘,color=’orange’) 
pplt.plot(x1, np.cos(x1), ‘–‘,color=’b’)
#give the name of the x and y  axis 
pplt.xlabel(‘x label’)
pplt.ylabel(‘y label’) 
#also give the title of the plot 
pplt.title(“Title”) 
pplt.show() 

Line plot for the provided code snippet

Pie plot in Matplotlib

Here is an example of a pie plot code snippet on matplotlib:

import matplotlib.pyplot as pplt

# Data labels, sizes, and colors are defined:

labels = ‘Broccoli’, ‘Chocolate Cake’, ‘Blueberries’, ‘Raspberries’

sizes = [30, 330, 245, 210]

colors = [‘green’, ‘brown’, ‘blue’, ‘red’]

# Data is plotted:

pplt.pie(sizes, labels=labels, colors=colors)

pplt.axis(‘equal’)

pplt.title(“Pie Plot”)

pplt.show()

This code results in a pie chart like:

Multiple Plots

Multiple plots can also be created by using this library function. A code snippet from geeksforgeeks.org shows a proper example.

# Python program to show pyplot module
import matplotlib.pyplot as plt
from matplotlib.figure import Figure
# Creating a new figure with width = 5 inches
# and height = 4 inches
fig = plt.figure(figsize =(5, 4))
# Creating first axes for the figure
ax1 = fig.add_axes([1, 1, 1, 1])
# Creating second axes for the figure
ax2 = fig.add_axes([1, 0.5, 0.5, 0.5])
# Adding the data to be plotted
ax1.plot([2, 3, 4, 5, 5, 6, 6], [5, 7, 1, 3, 4, 6 ,8])
ax2.plot([1, 2, 3, 4, 5], [2, 3, 4, 5, 6])
plt.show()

The result of the above code is shown in the image above.

Read our Popular Data Science Articles

Conclusion

Matplotlib is an extremely valuable library function. It has all the facilities of turning small, easy code snippets into graphs of all types. You can try plotting different datasets and mathematical functions now that you know the basics of plotting and charting.

For someone who can code in Python or similar languages, matplotlib acts as a catalyst to enhance their knowledge. It broadens one’s understanding and helps prepare easily understandable graphs. These graphs help in the preparation of a conformed analysis of data. 

If you’d like to gain in-depth knowledge of Python, we recommend upGrad’s online Professional Certificate Program in Data Science and Business Analytics from the University of Maryland, which is one of the top 100 global universities in the world.

The 9-months program offers a certificate from Maryland Smith and You will also have the opportunity to learn from world class faculty members from the University of Maryland.

In addition to this, students also benefit from dedicated mentorship access and exposure to a global peer network of 40,000+ paid learners for collaborative opportunities.