Matplotlib Plotting for Python Beginners

Introduction

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK. It also provides a procedural interface for non-interactive plotting.

In this lab, you will learn how to create a simple plot using Matplotlib.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL matplotlib(("`Matplotlib`")) -.-> matplotlib/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlottingDataGroup(["`Plotting Data`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlotCustomizationGroup(["`Plot Customization`"]) python(("`Python`")) -.-> python/DataStructuresGroup(["`Data Structures`"]) python(("`Python`")) -.-> python/ModulesandPackagesGroup(["`Modules and Packages`"]) python(("`Python`")) -.-> python/DataScienceandMachineLearningGroup(["`Data Science and Machine Learning`"]) matplotlib/BasicConceptsGroup -.-> matplotlib/importing_matplotlib("`Importing Matplotlib`") matplotlib/BasicConceptsGroup -.-> matplotlib/figures_axes("`Understanding Figures and Axes`") matplotlib/BasicConceptsGroup -.-> matplotlib/saving_figures("`Saving Figures to File`") matplotlib/PlottingDataGroup -.-> matplotlib/line_plots("`Line Plots`") matplotlib/PlotCustomizationGroup -.-> matplotlib/titles_labels("`Adding Titles and Labels`") python/DataStructuresGroup -.-> python/lists("`Lists`") python/DataStructuresGroup -.-> python/tuples("`Tuples`") python/ModulesandPackagesGroup -.-> python/importing_modules("`Importing Modules`") python/DataScienceandMachineLearningGroup -.-> python/data_visualization("`Data Visualization`") subgraph Lab Skills matplotlib/importing_matplotlib -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} matplotlib/figures_axes -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} matplotlib/saving_figures -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} matplotlib/line_plots -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} matplotlib/titles_labels -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} python/lists -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} python/tuples -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} python/importing_modules -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} python/data_visualization -.-> lab-48887{{"`Matplotlib Plotting for Python Beginners`"}} end

Import the Matplotlib Library

To use Matplotlib in Python, you need to import it first. Type the following code to import the Matplotlib library:

import matplotlib.pyplot as plt

Create a Simple Plot

To create a simple plot in Matplotlib, you need to provide a list of numbers that you want to plot. In this case, we will plot a list of numbers against their index resulting in a straight line. Use a format string (here, 'o-r') to set the markers (circles), linestyle (solid line) and color (red).

plt.plot([1, 2, 3, 4], 'o-r')
plt.ylabel('some numbers')
plt.show()

Customize the Plot

Matplotlib provides many options to customize the plot. You can change the color, linestyle, marker style, and many other options. Here is an example of how to change the color of the line to blue and the marker style to a plus sign:

plt.plot([1, 2, 3, 4], '+-b')
plt.ylabel('some numbers')
plt.show()

Add Labels and Titles

Adding labels and titles to the plot is essential to make it more informative. The following code adds a title to the plot and labels to the x and y-axis:

plt.plot([1, 2, 3, 4], 'o-r')
plt.title('Simple Plot')
plt.xlabel('Index')
plt.ylabel('Numbers')
plt.show()

Save the Plot

You can save the plot as an image file using the savefig method. The following code saves the plot as a PNG image:

plt.plot([1, 2, 3, 4], 'o-r')
plt.title('Simple Plot')
plt.xlabel('Index')
plt.ylabel('Numbers')
plt.savefig('simple_plot.png')

Summary

In this lab, you have learned how to create a simple plot using Matplotlib. You have also learned how to customize the plot, add labels and titles, and save the plot as an image file. Matplotlib provides many options to create informative and visually appealing plots.