Python Data Visualization: Matplotlib & Seaborn Masterclass

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 94 lectures (7h 30m) | 2.67 GB

Bring your data to LIFE and master Python’s most popular data analytics & visualization libraries: Matplotlib & Seaborn

This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data visualization: Matplotlib & Seaborn.

We’ll start with a quick introduction to data visualization frameworks and best practices, and review essential visuals, common errors, and tips for effective communication and storytelling.

From there we’ll dive into Matplotlib fundamentals, and practice building and customizing line charts, bar charts, pies & donuts, scatterplots, histograms and more. We’ll break down the components of a Matplotlib figure and introduce common chart formatting techniques, then explore advanced customization options like subplots, GridSpec, style sheets and parameters.

Finally we’ll introduce Python’s Seaborn library. We’ll start by building some basic charts, then dive into more advanced visuals like box & violin plots, PairPlots, heat maps, FacetGrids, and more.

Throughout the course you’ll play the role of a Consultant at Maven Consulting Group, a firm that provides strategic advice to companies around the world. You’ll practice applying your skills to a range of real-world projects and case studies, from hotel customer demographics to diamond ratings, coffee prices and automotive sales.

COURSE OUTLINE:

Intro to Data Visualization

Learn data visualization frameworks and best practices for choosing the right charts, applying effective formatting, and communicating clear, data-driven stories and insights

Matplotlib Fundamentals

Explore Python’s Matplotlib library and use it to build and customize several essential chart types, including line charts, bar charts, pie/donut charts, scatterplots and histograms

PROJECT #1: Analyzing the Global Coffee Market

Read data into Python from CSV files provided by a major global coffee trader, and use Matplotlib to visualize volume and price data by country

Advanced Customization

Apply advanced customization techniques in Matplotlib, including multi-chart figures, custom layout and colors, style sheets, gridspec, parameters and more

PROJECT #2: Visualizing Global Coffee Production

Continue your analysis of the global coffee market, and leverage advanced data visualization and formatting techniques to build a comprehensive report to communicate key insights

Data Visualization with Seaborn

Visualize data with Python’s Seaborn library, and build custom visuals using additional chart types like box plots, violin plots, joint plots, pair plots, heatmaps and more

PROJECT #3: Analyzing Used Car Sales

Use Seaborn and Matplotlib to explore, analyze and visualize automotive auction data to help your client identify the best deals on used service vehicles for the business

What you’ll learn

• Master the essentials of Matplotlib & Seaborn, two of Python’s most powerful data visualization packages
• Design and format 20+ chart types using Matplotlib & Seaborn, including line charts, bar charts, scatter plots, histograms, violin plots, heatmaps and more
• Learn advanced customization options like subplots, gridspec, style sheets and parameters
• Apply best practices for data visualization, storytelling, formatting and visual design
• Build powerful, practical skills for modern analytics and business intelligence