Customization in Matplotlib
This lesson will guide you through all the possible techniques that are used to visualize data using the Matplotlib Python library.
In this lesson, we will explore the main functionalities of Matplotlib: we will look at how to customize Matplotlib objects, how to use various plotting techniques, and finally, we will focus on how to communicate results.
If you have any feedback related to this lesson, feel free to contact us at support@cloudacademy.com.
Learning Objectives
- Learn the fundamentals of Python's Matplotlib library and its main features
- Customize objects in Matplotlib
- Create multiple plots in Matplotlib
- Customize plots in Matplotlib (annotations, labels, linestyles, colors, etc)
- Understand the different plot types available
Intended Audience
- Data scientists
- Anyone looking to create plots and visualize data in Matplotlib
Prerequisites
To get the most out of this lesson, you should already be familiar with using Python, for which you can take our Introduction to Python course. Knowledge of Python's Pandas library would also be beneficial and you might want to take our lessons Working with Pandas and Data Wrangling with Pandas before embarking on this Matplotlib lesson.
Resources
The data used in this lesson can be found in the following GitHub repository: https://github.com/cloudacademy/data-visualization-with-python-using-matplotlib
Andrea is a Data Scientist at Cloud Academy. He is passionate about statistical modeling and machine learning algorithms, especially for solving business tasks.
He holds a PhD in Statistics, and he has published in several peer-reviewed academic journals. He is also the author of the book Applied Machine Learning with Python.