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Python Data Visualization: Create impactful visuals, animations and dashboards

Category: Tutorials



Python Data Visualization: Create impactful visuals, animations and dashboards
Python Data Visualization: Create impactful visuals, animations and dashboards
ISBN: 9780135426531 | .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 6h 36m | 1.5 GB
Instructor: Bruno Goncalves


The Sneak Peek program provides early access to Pearson video products and is exclusively available to subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing.

Python Data Visualization: Introduction

Lesson 1: Human Perception


Topics
1.1 Understanding Color Theory
1.2 Overview of Human Vision
1.3 Color Schemes

Lesson 2: Analytical Design

Topics
2.1 Understand the Fundamental Principles of Analytical Design
2.2 Describe the Fundamental Tools of Visualization
2.3 Advantages and Disadvantages of Different Chart Types

Lesson 3: Data Cleaning and Visualizion with Pandas

Topics
3.1 DataFrames and Series
3.2 GroupBy and Pivot Tables
3.3 Merge and Join
3.4 The Plot Function
3.5 Demo
3.6 Time Series
3.7 Bar Plot Demo

Lesson 4: Matplotlib

Topics
4.1 Fundamental Components of a matplotlib plot
4.2 Explore the matplotlib API
4.3 Demo
4.4 Stylesheets
4.5 Demo
4.6 Mapping
4.7 Demo

Lesson 5: Matploltib Animations

Topics
5.1 Matploltib Animation API
5.2 Func Animation
5.3 Animation Writers
5.4 Demo

Lesson 6: Jupyter Widgets

Topics
6.1 ipywidgets as Interactive Browser Controls
6.2 Simple Wdget Use
6.3 Widget Customization
6.4 Demo

Lesson 7: Seaborn

Topics
7.1 Understand the Structure of seaborn
7.2 Understand the Differences with matplotlib
7.3 Explore the Seaborn API
7.4 Demo

Lesson 8: Bokeh

Topics
8.1 Basic Plotting with Bokeh
8.2 Advanced Plotting
8.3 Networks
8.4 Demo

Lesson 9: Plotly

Topics
9.1 Basic Plotly
9.2 3D and Animated Plots
9.3 Demo

Summary

Python Data Visualization: Summary
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