English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 6h 36m | 1.49 GB
Bruno Gonçalves is a senior data scientist in the area of complex systems, human behavior, and finance. He has been programming in Python since 2005. For more than ten years, his work has focused on analyzing large-scale social media datasets for the temporal analysis of social behavior.
Table of Contents
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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