Python Data Visualization for Beginners (CPD Accredited)

Python Data Visualization for Beginners (CPD Accredited), available at $49.99, has an average rating of 4.55, with 83 lectures, based on 29 reviews, and has 8865 subscribers.

You will learn about Review the python visualization landscape Explore core visualization concepts Use matplotlib to build and customize visualizations Build and customize simple plots with pandas Learn about seaborn and use it for statistical visualizations Create visualizations using Altair Generate interactive plots using the Plotly library Design interactive dashboards using Streamlit Construct highly custom and flexible dashboards using Plotly's Dash framework This course is ideal for individuals who are Data Analysts and Developers that have a bit of experience with python but have yet to develop a competency in a python visualization library. or Those feeling restricted by their current plotting tools and wish to explore other options. It is particularly useful for Data Analysts and Developers that have a bit of experience with python but have yet to develop a competency in a python visualization library. or Those feeling restricted by their current plotting tools and wish to explore other options.

Enroll now: Python Data Visualization for Beginners (CPD Accredited)

Summary

Title: Python Data Visualization for Beginners (CPD Accredited)

Price: $49.99

Average Rating: 4.55

Number of Lectures: 83

Number of Published Lectures: 83

Number of Curriculum Items: 83

Number of Published Curriculum Objects: 83

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Review the python visualization landscape
Explore core visualization concepts
Use matplotlib to build and customize visualizations
Build and customize simple plots with pandas
Learn about seaborn and use it for statistical visualizations
Create visualizations using Altair
Generate interactive plots using the Plotly library
Design interactive dashboards using Streamlit
Construct highly custom and flexible dashboards using Plotly's Dash framework

Who Should Attend

Data Analysts and Developers that have a bit of experience with python but have yet to develop a competency in a python visualization library.
Those feeling restricted by their current plotting tools and wish to explore other options.

Target Audiences

Data Analysts and Developers that have a bit of experience with python but have yet to develop a competency in a python visualization library.
Those feeling restricted by their current plotting tools and wish to explore other options.

Have you ever found yourself stuck and unable to move forward while creating a simple plot? Do you want to create sophisticated, interactive data visualizations in python? Have you ever needed clarification on all the different python plotting libraries? If your answer is yes, to any of these questions, this course is for you.

So what’s it about, and how is this course different?

There are many different libraries in the python data visualization landscape. They are all powerful and valuable, but is it obvious to determine what works best for you? You will discover many of the most popular python visualization libraries through this course. It starts by learning how to use each library to build simple visualizations.

You will be able to explore more complex usage and identify the scenarios where each library shines. At the end of the course, you will gain a basic working knowledge of using multiple libraries to visualize data in python.

You will also understand which library is more suitable for you and your coding style. You’ll also understand general visualization concepts to make your plots more practical.

And that’s what makes this course unique.

We will cover more complex, interactive visualization dashboard technologies in addition to the overview material.

All software used is 100% free and open source, including editors, Python language, etc. You don’t need to buy anything for this course.

Concepts backed by concise visuals whenever we hit a new topic.

The time to act is now.

Data science is one of the year’s hottest topics, and data visualization is a core skill set needed to communicate your results and discoveries properly. Take this course to get good at various modern Python-based visualization libraries.

Course Curriculum

Chapter 1: Welcome to the course

Lecture 1: Introduction

Lecture 2: Python Visualization Ecosystem

Chapter 2: Visualization Concepts

Lecture 1: Intro to Visualization concepts and the Aesthetics Concept

Lecture 2: Data Types and Visualization variables

Lecture 3: Colors and 6 Small multiple plots

Chapter 3: Matplotlib

Lecture 1: Matplotlib introduction, History and Landscape

Lecture 2: System setup

Lecture 3: Data set and Figure Overview

Lecture 4: Interface types & Launching notebooks

Lecture 5: Reading data

Lecture 6: Pylot Example

Lecture 7: Histograms

Lecture 8: Figures and Axes

Lecture 9: Saving images & Quick Reference

Lecture 10: Line plots

Lecture 11: Bar charts

Lecture 12: Scatter plots

Lecture 13: Styles

Lecture 14: Regression

Lecture 15: Customizing multiple plots

Lecture 16: References

Lecture 17: Summary

Chapter 4: Pandas

Lecture 1: Pandas Intro, Overview and API Overview

Lecture 2: Basic API examples

Lecture 3: API summary, Specialized hist and boxplot API

Lecture 4: Advanced specialized plots

Lecture 5: API Advanced Plot Summary and Pandas Conclusion

Chapter 5: Seaborn

Lecture 1: Introduction to Seaborn & Overview

Lecture 2: Getting started & Figure and axes level plots

Lecture 3: Data set changes

Lecture 4: Displot

Lecture 5: Catplot

Lecture 6: Relplot & Seaborn API Summary

Lecture 7: Displot relplot and facetting

Lecture 8: Catplot API summary & Specialized plots

Lecture 9: Heatmap

Lecture 10: Pair and jointplot

Lecture 11: Customizing Seaborn summary & Seaborn Summary

Chapter 6: Altair

Lecture 1: Introduction to Altair, Overview & Vega lite

Lecture 2: Installing & Shorthand API

Lecture 3: Basic shorthand API

Lecture 4: Additional examples of the basic API

Lecture 5: Longhand API

Lecture 6: Longhand overview

Lecture 7: Data type & Types viz alterations

Lecture 8: Concat charts

Lecture 9: Faceting & Layers

Lecture 10: Multiple chart summary & Amazon data set

Lecture 11: Amazon authors

Lecture 12: Reference example & Conclusion

Chapter 7: Plotly

Lecture 1: Introduction to Plotly, Overview, API Intro and Installing

Lecture 2: Basic plotting

Lecture 3: Customizing

Lecture 4: Additional plot types

Lecture 5: API overview & Scatter Plots

Lecture 6: Line bar area

Lecture 7: Regression treemap heatmap

Lecture 8: Facetting

Lecture 9: Annotations

Lecture 10: Annotation summary and Section Conclusion

Chapter 8: Streamlit

Lecture 1: Introduction, Background and Installation

Lecture 2: Basic app concepts and Simple App example

Lecture 3: Streamlit running overview & API Summary

Lecture 4: Widget Intro & Widget interactivity

Lecture 5: User input

Lecture 6: Show charts

Lecture 7: Sidebar intro

Lecture 8: Sidebar details

Lecture 9: Conclusion

Chapter 9: Dash

Lecture 1: Introduction, Overview, Why Dash, Getting started and Program structure

Lecture 2: First App

Lecture 3: Running App

Lecture 4: Component overview & HTML

Lecture 5: Interactive app

Lecture 6: Interactive app demo & Callback reference

Lecture 7: Final app overview & Full app part 1

Lecture 8: Full app data filtering

Lecture 9: Full app demo

Lecture 10: Advanced topics & Conclusion

Chapter 10: Course Conclusion

Lecture 1: Course review, Objectives & Data VS concepts

Lecture 2: Matplotlib, Pandas, Seaborn, Altair, Plotly, Streamlit & Dash Wrap-up

Lecture 3: My Workflow and Thank You!

Lecture 4: Bonus Lecture:

Instructors

OMG – Mastermind
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Kareem Mostafa
Management Consultant and Entrepreneurship Enthusiast!

Rating Distribution

1 stars: 0 votes
2 stars: 2 votes
3 stars: 5 votes
4 stars: 7 votes
5 stars: 15 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?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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