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Course

Introduction to Data Visualization with Matplotlib

BasicSkill Level

4.8+

Updated 06/2025

Learn how to create, customize, and share data visualizations using Matplotlib.

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PythonData Visualization4 hr14 videos44 Exercises3,600 XP207,327Statement of Accomplishment

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Course Description

Visualizing data in plots and figures exposes the underlying patterns in the data and provides insights. Good visualizations also help you communicate your data to others, and are useful to data analysts and other consumers of the data. In this course, you will learn how to use Matplotlib, a powerful Python data visualization library. Matplotlib provides the building blocks to create rich visualizations of many different kinds of datasets. You will learn how to create visualizations for different kinds of data and how to customize, automate, and share these visualizations.

Prerequisites

Introduction to Python

1

Introduction to Matplotlib

Introduction to data visualization with Matplotlib

Using the matplotlib.pyplot interface

Adding data to an Axes object

Customizing your plots

Customizing data appearance

Customizing axis labels and adding titles

Small multiples

Creating a grid of subplots

Creating small multiples with plt.subplots

Small multiples with shared y axis

2

Plotting time-series

Plotting time-series data

Read data with a time index

Plot time-series data

Using a time index to zoom in

Plotting time-series with different variables

Plotting two variables

Defining a function that plots time-series data

Using a plotting function

Annotating time-series data

Annotating a plot of time-series data

Plotting time-series: putting it all together

3

Quantitative comparisons and statistical visualizations

Quantitative comparisons: bar-charts

Stacked bar chart

Quantitative comparisons: histograms

Creating histograms

"Step" histogram

Statistical plotting

Adding error-bars to a bar chart

Adding error-bars to a plot

Creating boxplots

Quantitative comparisons: scatter plots

Simple scatter plot

Encoding time by color

4

Sharing visualizations with others

Preparing your figures to share with others

Selecting a style for printing

Switching between styles

Saving your visualizations

Saving a file several times

Save a figure with different sizes

Automating figures from data

Unique values of a column

Automate your visualization

Where to go next

Introduction to Data Visualization with Matplotlib

Course
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*4.8

from 471 reviews

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Osman Mohamoud

about 4 hours

Practical, informative. But the problem is the exercises are just examples.

Nicholas

about 15 hours

Olayele

about 17 hours

Detailed lecture

Nsikan Sylvia

about 17 hours

Khalid

about 18 hours

kirti

about 20 hours

"Practical, informative. But the problem is the exercises are just examples."

Osman Mohamoud

Nicholas

"Detailed lecture"

Olayele

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