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Learn a wide variety of modern Python-based visualization libraries in no time | Python for Beginners

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

Description

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.


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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.

English
language

Content

Welcome to the course

Introduction
Python Visualization Ecosystem

Visualization Concepts

Intro to Visualization concepts and the Aesthetics Concept
Data Types and Visualization variables
Colors and 6 Small multiple plots

Matplotlib

Matplotlib introduction, History and Landscape
System setup
Data set and Figure Overview
Interface types & Launching notebooks
Reading data
Pylot Example
Histograms
Figures and Axes
Saving images & Quick Reference
Line plots
Bar charts
Scatter plots
Styles
Regression
Customizing multiple plots
References
Summary

Pandas

Pandas Intro, Overview and API Overview
Basic API examples
API summary, Specialized hist and boxplot API
Advanced specialized plots
API Advanced Plot Summary and Pandas Conclusion

Seaborn

Introduction to Seaborn & Overview
Getting started & Figure and axes level plots
Data set changes
Displot
Catplot
Relplot & Seaborn API Summary
Displot relplot and facetting
Catplot API summary & Specialized plots
Heatmap
Pair and jointplot
Customizing Seaborn summary & Seaborn Summary

Altair

Introduction to Altair, Overview & Vega lite
Installing & Shorthand API
Basic shorthand API
Additional examples of the basic API
Longhand API
Longhand overview
Data type & Types viz alterations
Concat charts
Faceting & Layers
Multiple chart summary & Amazon data set
Amazon authors
Reference example & Conclusion

Plotly

Introduction to Plotly, Overview, API Intro and Installing
Basic plotting
Customizing
Additional plot types
API overview & Scatter Plots
Line bar area
Regression treemap heatmap
Facetting
Annotations
Annotation summary and Section Conclusion

Streamlit

Introduction, Background and Installation
Basic app concepts and Simple App example
Streamlit running overview & API Summary
Widget Intro & Widget interactivity
User input
Show charts
Sidebar intro
Sidebar details
Conclusion

Dash

Introduction, Overview, Why Dash, Getting started and Program structure
First App
Running App
Component overview & HTML
Interactive app
Interactive app demo & Callback reference
Final app overview & Full app part 1
Full app data filtering
Full app demo
Advanced topics & Conclusion

Course Conclusion

Course review, Objectives & Data VS concepts
Matplotlib, Pandas, Seaborn, Altair, Plotly, Streamlit & Dash Wrap-up
My Workflow and Thank You!
Bonus Lecture: