Python Data Visualization: Matplotlib & Seaborn Masterclass
Python Data Visualization: Matplotlib & Seaborn Masterclass, available at $84.99, has an average rating of 4.62, with 94 lectures, 4 quizzes, based on 509 reviews, and has 5317 subscribers.
You will learn about Master Python's Matplotlib & Seaborn libraries, 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 Python data visualization, storytelling, formatting and visual design Build powerful, practical skills for modern analytics, data science and business intelligence This course is ideal for individuals who are Analysts or business intelligence professionals looking to learn data visualization with Matplotlib and Seaborn or Aspiring data scientists who want to build or strengthen their Python data visualization skills or Anyone interested in learning one of the most popular open source programming languages in the world or Students looking to learn powerful, practical skills with unique, hands-on projects and course demos It is particularly useful for Analysts or business intelligence professionals looking to learn data visualization with Matplotlib and Seaborn or Aspiring data scientists who want to build or strengthen their Python data visualization skills or Anyone interested in learning one of the most popular open source programming languages in the world or Students looking to learn powerful, practical skills with unique, hands-on projects and course demos.
Enroll now: Python Data Visualization: Matplotlib & Seaborn Masterclass
Summary
Title: Python Data Visualization: Matplotlib & Seaborn Masterclass
Price: $84.99
Average Rating: 4.62
Number of Lectures: 94
Number of Quizzes: 4
Number of Published Lectures: 94
Number of Published Quizzes: 4
Number of Curriculum Items: 98
Number of Published Curriculum Objects: 98
Original Price: $129.99
Quality Status: approved
Status: Live
What You Will Learn
- Master Python's Matplotlib & Seaborn libraries, 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 Python data visualization, storytelling, formatting and visual design
- Build powerful, practical skills for modern analytics, data science and business intelligence
Who Should Attend
- Analysts or business intelligence 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
Target Audiences
- Analysts or business intelligence 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
This is a hands-on, project-based course designed to help you learn two of the most popular Python packages for data visualization and business intelligence: Matplotlib & Seaborn.
We’ll start with a quick introduction to Python 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:
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Intro to Python Data Visualization
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Learn data visualization frameworks and best practices for choosing the right charts, applying effective formatting, and communicating clear, data-driven stories and insights
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Matplotlib Fundamentals
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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
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PROJECT #1: Analyzing the Global Coffee Market
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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
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Advanced Formatting & Customization
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Apply advanced customization techniques in Matplotlib, including multi-chart figures, custom layout and colors, style sheets, gridspec, parameters and more
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PROJECT #2: Visualizing Global Coffee Production
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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
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Data Visualization with Seaborn
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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
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PROJECT #3: Analyzing Used Car Sales
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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
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Join today and get immediate, lifetime access to the following:
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7.5 hours of high-quality video
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Python Matplotlib & Seaborn PDF ebook (150+ pages)
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Downloadable project files & solutions
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Expert support and Q&A forum
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30-day Udemy satisfaction guarantee
If you’re a data analyst. data scientist, business intelligence professional or data engineer looking to add Matplotlib & Seaborn to your Python data analysis and visualization skill set, this is the course for you!
Happy learning!
-Chris Bruehl (Python Expert & Lead Python Instructor,Maven Analytics)
__________
Looking for our full business intelligence stack? Search for “Maven Analytics“ to browse our full course library, including Excel, Power BI, MySQL, Tableau and Machine Learning courses!
See why our courses are among the TOP-RATED on Udemy:
“Some of the BEST courses I’ve ever taken. I’ve studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I’ve seen!”Russ C.
“This is my fourth course from Maven Analytics and my fourth 5-star review, so I’m running out of things to say. I wish Maven was in my life earlier!”Tatsiana M.
“Maven Analytics should become the new standard for all courses taught on Udemy!”Jonah M.
Course Curriculum
Chapter 1: Getting Started
Lecture 1: Course Structure & Outline
Lecture 2: READ ME: Important Notes for New Students
Lecture 3: DOWNLOAD: Course Resources
Lecture 4: Introducing the Course Project
Lecture 5: Setting Expectations
Lecture 6: Jupyter Installation & Launch
Chapter 2: Intro to Data Visualization
Lecture 1: Why Visualize Data?
Lecture 2: 3 Key Questions
Lecture 3: Essential Visuals
Lecture 4: Chart Formatting & Storytelling
Lecture 5: Common Visualization Mistakes
Lecture 6: Key Takeaways
Chapter 3: Matplotlib Fundamentals
Lecture 1: Intro to Matplotlib
Lecture 2: Plotting Methods
Lecture 3: Plotting DataFrames
Lecture 4: ASSIGNMENT: Plotting DataFrames
Lecture 5: SOLUTION: Plotting DataFrames
Lecture 6: Anatomy of a Matplotlib Figure
Lecture 7: Chart Titles & Font Sizes
Lecture 8: Chart Legends
Lecture 9: Line Styles
Lecture 10: Axis Limits
Lecture 11: Figure Sizes
Lecture 12: Custom Axis Ticks
Lecture 13: Vertical Lines
Lecture 14: Adding Text
Lecture 15: PRO TIP: Text Annotations
Lecture 16: Removing Borders
Lecture 17: ASSIGNMENT: Formatting Charts
Lecture 18: SOLUTION: Formatting Charts
Lecture 19: Line Charts
Lecture 20: Stacked Line Charts
Lecture 21: Dual Axis Charts
Lecture 22: ASSIGNMENT: Dual Axis Line Charts
Lecture 23: SOLUTION: Dual Axis Line Charts
Lecture 24: Bar Charts
Lecture 25: ASSIGNMENT: Bar Charts
Lecture 26: SOLUTION: Bar Charts
Lecture 27: Stacked Bar Charts
Lecture 28: Grouped Bar Charts
Lecture 29: Combo Charts
Lecture 30: ASSIGNMENT: Advanced Bar Charts
Lecture 31: SOLUTION: Advanced Bar Charts
Lecture 32: Pie & Donut Charts
Lecture 33: ASSIGNMENT: Pie & Donut Charts
Lecture 34: SOLUTION: Pie & Donut Charts
Lecture 35: Scatterplots & Bubble Charts
Lecture 36: Histograms
Lecture 37: ASSIGNMENT: Scatterplots & Histograms
Lecture 38: SOLUTION: Scatterplots & Histograms
Lecture 39: Key Takeaways
Chapter 4: PROJECT #1: Analyzing the Global Coffee Market
Lecture 1: Project #1 Introduction
Lecture 2: Project #1 Solution Walkthrough
Chapter 5: Advanced Customization
Lecture 1: Intro to Advanced Customization
Lecture 2: Subplots
Lecture 3: ASSIGNMENT: Subplots
Lecture 4: SOLUTION: Subplots
Lecture 5: GridSpec
Lecture 6: ASSIGNMENT: GridSpec
Lecture 7: SOLUTION: GridSpec
Lecture 8: Color Options
Lecture 9: Color Palettes
Lecture 10: ASSIGNMENT: Colors
Lecture 11: SOLUTION: Colors
Lecture 12: Style Sheets
Lecture 13: ASSIGNMENT: Style Sheets
Lecture 14: SOLUTION: Style Sheets
Lecture 15: rcParameters
Lecture 16: Saving Figures & Images
Lecture 17: Key Takeaways
Chapter 6: PROJECT #2: Visualizing Global Coffee Production
Lecture 1: Project #2 Introduction
Lecture 2: Project #2 Solution Walkthrough
Chapter 7: Visualization with Seaborn
Lecture 1: Intro to Seaborn
Lecture 2: Basic Formatting Options
Lecture 3: Bar Charts & Histograms
Lecture 4: ASSIGNMENT: Bar Charts & Histograms
Lecture 5: SOLUTION: Bar Charts & Histograms
Lecture 6: Box & Violin Plots
Lecture 7: ASSIGNMENT: Box & Violin Plots
Lecture 8: SOLUTION: Box & Violin Plots
Lecture 9: Linear Relationship Charts
Lecture 10: Jointplots
Lecture 11: PairPlots
Lecture 12: ASSIGNMENT: Linear Relationship Charts
Lecture 13: SOLUTION: Linear Relationship Charts
Lecture 14: Heatmaps
Lecture 15: ASSIGNMENT: Heatmaps
Lecture 16: SOLUTION: Heatmaps
Lecture 17: FacetGrid
Lecture 18: Matplotlib Integration
Instructors
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Maven Analytics
Empowering everyday people with life-changing data skills -
Chris Bruehl
Lead Python Instructor at Maven Analytics
Rating Distribution
- 1 stars: 6 votes
- 2 stars: 8 votes
- 3 stars: 41 votes
- 4 stars: 133 votes
- 5 stars: 321 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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