Matplotlib is a popular Python library used for data visualization and making 2D plots from data. It provides an object-oriented API that allows plots to be embedded in Python applications. Matplotlib has a MATLAB-like procedural interface called Pylab and can be considered an open source alternative to MATLAB. It is written in Python and relies on NumPy for numerical computations. Examples shown how to generate simple plots by importing Matplotlib and NumPy, preparing data, and using Matplotlib functions to plot and display the results.

1. PYTHON FOR MACHINE
LEARNING(MATPLOTLIB)
Dr. Amanpreet Kaur​
Associate Professor,
Chitkara University,
Punjab

2. MATPLOTLIB
2
• Matplotlib is one of the most popular Python packages used for data
visualization.
• It is a cross-platform library for making 2D plots from data in arrays.
• Matplotlib is written in Python and makes use of NumPy, the numerical
mathematics extension of Python.
• It provides an object-oriented API that helps in embedding plots in
applications using Python GUI toolkits such as PyQt, WxPythonot Tkinter.
• It can be used in Python and IPython shells, Jupyter notebook and web
application servers also.

3. 3
• Matplotlib has a procedural interface named the Pylab, which is
designed to resemble MATLAB, a proprietary programming
language developed by MathWorks.
• Matplotlib along with NumPy can be considered as the open
source equivalent of MATLAB.
• Matplotlib was originally written by John D. Hunter in 2003. The
current stable version is 2.2.0 released in January 2018.
• Below command in used to install Matplotlib
pip3 install matplotlib
MATPLOTLIB

4. 4
# importing the necessary packages and modules
import matplotlib.pyplot as plt
import numpy as np
# Prepare the data
x = np.linspace(0, 10, 100)
# Plot the data
plt.plot(x, x, label ='linear')
# Add a legend
plt.legend()
# Show the plot
plt.show()
MATPLOTLIB - EXAMPLE

5. 5
MATPLOTLIB - EXAMPLE
# importing the necessary packages and modules
import matplotlib.pyplot as plt
import numpy as np
plt.plot([1, 2, 3, 4], [1, 4, 9, 16], ‘ro’)
plt.axis([0, 6, 0, 20])
plt.show()

6. 6
MATPLOTLIB - EXAMPLE
import matplotlib.pyplot as plt
import numpy as np
data =np.random.randint(400,size=25)
# Return random integers from the “discrete uniform”
distribution of the specified dtype in the “half-open”
interval [low, high). If high is None (the default), then
results are from [0, low).
label = np.array(range(1,26))
plt.plot(label,data,'.')

7. PYTHON PROGRAMMING
7
Online Compiler:-
https://dataplatform.cloud.ibm.com/
https://jupyter.org/

8. PYTHON PROGRAMMING
8
E Books-
• Peter Harrington “Machine Learning In Action”, DreamTech
Press
• Ethem Alpaydın, “Introduction to Machine Learning”, MIT Press
Video Links-
• https://www.youtube.com/watch?v=BRMS3T11Cdw&list=PL3pGy4HtqwD2a
57wl7Cl7tmfxfk7JWJ9Y
• https://www.youtube.com/watch?v=EWmCkVfPnJ8&list=PL3pGy4HtqwD2a
57wl7Cl7tmfxfk7JWJ9Y&index=3

9. THANK YOU
aman_preet_k@yahoo.co.in