Gain insights into visually representing data with Matplotlib in Python. Explore plotting techniques, control axes, create complex layouts, and draw various plots, enhancing your data science skills.

For data science, Matplotlib is one of the most popular tools for representing data in a visual manner. There are many other tools, but for the Python user, Matplotlib is a must-know.

In this course, you will learn how to visually represent data in several different ways. You will learn how to use figures and axes to plot a chart, as well as how to plot from multiple types of objects and modules.

You will also discover ways to control the spine of an axes and how to create complex layouts for a figure using GridSpec so you can create visually stunning charts.

In the latter half of the course, you will focus on how to draw various types of plots, whether it be a line plot, a stem plot, or a heatmap plot. Overall, this is your no-fuss introduction to creating impactful data charts.

By the end, you will have an important new skill to add to your resume. As any data scientist knows, it is necessary that you be able to show insights found from analyzing data.

Matplotlib for Python: Visually Represent Data with Plots

Thank you very much for completing this course. Hopefully, this course will help you solve some problems with data visualization at work.

As we mentioned at the beginning of this course, we did not cover every aspect of **Matplotlib**. Instead, we focused on some of the most important features, as well as some basic concepts that will help you better understand the library. If you want to develop a greater understanding of Matplotlib, please refer to the official Matplotlib website. 

We hope that you now have an understanding of how to:

- Plot charts, individually and in multiples.
- Set the Tick, Text, Legend, and Annotate elements of a plot.
- Customize the Grid and Spine displays of a plot.
- Set the colors for different elements of a plot
- Customize the style and appearance of different plot components.
- Choose different chart types based on data type and requirement.
- Show the distribution of data.
- Show the relationship between different variables.
- Plot data in 2D and 3D.

We would greatly appreciate it if you would provide any feedback for this course. Please feel free to send us an email, or post a comment on the community forum.

Introduction

How to Draw Various Plot Elements

How to Draw Different Types of Plots

Final Remarks