Visualization with Python- Matplotlib All In One

Visualization with Python: Matplotlib All In One, available at $64.99, has an average rating of 4.25, with 33 lectures, based on 13 reviews, and has 60 subscribers.

You will learn about Matplotlib Interfaces Learn and Understand pyplot Understanding Matplotlib Architecture Configuring Matplotlib Advanced use of Matplotlib This course is ideal for individuals who are Programmers or Anyone interested in Data Visualization It is particularly useful for Programmers or Anyone interested in Data Visualization.

Enroll now: Visualization with Python: Matplotlib All In One

Summary

Title: Visualization with Python: Matplotlib All In One

Price: $64.99

Average Rating: 4.25

Number of Lectures: 33

Number of Published Lectures: 33

Number of Curriculum Items: 33

Number of Published Curriculum Objects: 33

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Matplotlib Interfaces

Learn and Understand pyplot

Understanding Matplotlib Architecture

Configuring Matplotlib

Advanced use of Matplotlib

Who Should Attend

Programmers

Anyone interested in Data Visualization

Target Audiences

Programmers

Anyone interested in Data Visualization

Welcome aboard to the journey of creating good data visuals. Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. It provides a large library of customizable plots, along with a comprehensive set of backends. This is a practical course to help you visualize data with Python using the Matplotlib library.

This course will teach you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. With the help of this course, you’ll be able to tackle any problem you might come across while designing attractive, insightful data visualizations.  You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this course. Once you’ve familiarized yourself with the fundamentals, you’ll move on to developing professional dashboards with a wide variety of graphs and sophisticated grid layouts in 2D and 3D. You’ll annotate and add rich text to the plots, enabling the creation of a business storyline. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. In addition to this, you’ll learn how to save figures and animations in various formats for downstream deployment, followed by extending the functionality offered by various internal and third-party toolkits.

By the end of this course, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib and leveraging its power to build attractive, insightful, and powerful visualizations.

Course Curriculum

Chapter 1: Welcome

Lecture 1: Introduction

Chapter 2: Getting started

Lecture 1: Learn How to Install Matplotlib – 1

Lecture 2: Learn How to Install Matplotlib – 2

Lecture 3: Matplotlib – Exploring Data using Python

Lecture 4: Learn to Use Matplotlib with Jupyter

Lecture 5: Learning Pylab, pyplot & OO API

Chapter 3: Learn and Understand pyplot

Lecture 1: Introduction

Lecture 2: Understanding the Plot Function

Lecture 3: Learn More About Plotting

Lecture 4: Understanding Parallel Coordinates

Lecture 5: Understanding Subplots

Lecture 6: Learn How to Adjust Subplot Parameters

Lecture 7: Understanding Scatterplot Matrix

Lecture 8: Understanding Complex Subplots

Chapter 4: Learn and Understand Matplotlib Architecture

Lecture 1: Introduction

Lecture 2: Matplotlib – Anatomy of A Graphic

Lecture 3: Learn How to pyplot Works

Lecture 4: Troubleshooting pyplot Issues

Chapter 5: Learn How to Configure Matplotlib

Lecture 1: Introduction

Lecture 2: Learn About Style Sheets

Lecture 3: Learn About Custom Style Sheets

Chapter 6: Learn and Understand Interactivity

Lecture 1: Handling Event

Lecture 2: Learn How to Create An Interface With ipywidgets

Lecture 3: Learn How to Refine An ipywidgets Interface

Chapter 7: Maps In Matplotlib

Lecture 1: Introduction

Lecture 2: Learn About Basemap

Lecture 3: Learn How to Create a Choropleth With Matplotlib

Lecture 4: Learn How to Create a Dot Density Map

Chapter 8: Understanding the Matplotlib Ecosystem

Lecture 1: Learn About Seaborn

Lecture 2: Learn About Pandas

Lecture 3: Learn About the Web

Chapter 9: Course Summary

Lecture 1: Summary

Lecture 2: Course Material & Source Code

Instructors

Chris Jimerson
Passionate and Creative Software Engineer

Rating Distribution

1 stars: 1 votes

2 stars: 1 votes

3 stars: 0 votes

4 stars: 1 votes

5 stars: 10 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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