Description
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
Join today and get immediate, lifetime access to the following:
- 7.5 hours of high-quality video
- Matplotlib & Seaborn PDF ebook (150+ pages)
- Downloadable project files & solutions
- Expert support and Q&A forum
- 30-day Udemy satisfaction guarantee
If you’re a data scientist, BI analyst or data engineer looking to add Matplotlib & Seaborn to your Python skill set, this is the course for you!
Happy learning!
-Chris Bruehl (Python Expert & Lead Python Instructor, Maven Analytics)
Who this course is for:
- Analysts or BI professionals looking to learn data visualization with Matplotlib and Seaborn
- Aspiring data scientists who want to build or strengthen their Python data visualization skills
- Anyone interested in learning one of the most popular open source programming languages in the world
- Students looking to learn powerful, practical skills with unique, hands-on projects and course demos
Requirements
- We’ll use Anaconda & Jupyter Notebooks (a free, user-friendly coding environment)
- Familiarity with base Python is strongly recommended, but not a strict prerequisite
Last Updated 10/2022
Download Links
Direct Download
Python Data Visualization: Matplotlib & Seaborn Masterclass.zip (2.6 GB) | Mirror
