Python Data Visualization: Matplotlib & Seaborn Masterclass from Udemy

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:

Intro to Python 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 Formatting & 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
Python 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 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.

What's inside

Syllabus

Getting Started

Course Structure & Outline

READ ME: Important Notes for New Students

DOWNLOAD: Course Resources

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides hands-on experience with Matplotlib and Seaborn, which are essential tools for data visualization and business intelligence in the Python ecosystem

Uses real-world projects and case studies, such as analyzing the global coffee market and used car sales, to provide practical experience

Covers a range of essential chart types, including line charts, bar charts, pie/donut charts, scatterplots, histograms, box plots, violin plots, and heatmaps

Explores advanced customization options in Matplotlib, such as subplots, GridSpec, style sheets, and parameters, which allows for creating highly tailored visualizations

Requires students to install and use Jupyter Notebooks, which may require some learners to spend time setting up their local environments

Reviews summary

Practical python data vis skills

According to learners, this course is a largely positive experience for mastering Python data visualization with Matplotlib and Seaborn. Students praise the instructor's clear and engaging teaching style and the well-structured content that covers essential techniques. The hands-on, project-based approach with practical projects is frequently cited as highly effective for applying concepts. While a small minority of advanced learners desired deeper coverage of niche topics, the course successfully builds a strong foundation in creating various chart types and customizations, making it highly recommended for those looking to add these skills to their toolkit.

Requires some prior Python/Pandas knowledge.

"While the course focuses on vis, having some Python/Pandas background helps."

"I felt the pace was good, likely because I already knew Python basics."

"Learners should be comfortable with basic Python before starting."

Content is organized logically and flows well.

"The course is very well organized and easy to follow."

"Content structure makes learning straightforward."

"The logical flow of the material builds skills effectively."

Covers essential Matplotlib and Seaborn features.

"Covers essential charts in Matplotlib and Seaborn."

"I feel like I have a solid understanding of the core concepts."

"The course goes from basics to advanced techniques like subplots and FacetGrid."

"A comprehensive introduction to both libraries."

Hands-on projects reinforce understanding.

"The projects were very relevant and really tied the concepts together."

"The real-world projects made the concepts much more tangible."

"I appreciated the hands-on projects with realistic data."

"The projects give you an opportunity to apply what you've learned immediately."

Instructor explains complex topics clearly.

"Chris is an incredible instructor - he is clear, concise, and extremely knowledgable."

"The instructor is very clear and thorough in his explanations."

"Chris is a phenomenal instructor. Explanations are clear, concise, and easy to follow."

"Excellent instruction, clear concise and easy to understand."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python Data Visualization: Matplotlib & Seaborn Masterclass with these activities:

Review Python Fundamentals

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Reinforce your understanding of Python fundamentals to ensure a smooth learning experience with Matplotlib and Seaborn.

Browse courses on Python Basics

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Review basic Python syntax and data types.
Practice writing simple Python functions.
Familiarize yourself with lists, dictionaries, and other data structures.

Review 'Python Data Science Handbook'

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Deepen your understanding of data science principles and Python libraries relevant to data visualization.

View Python Data Science Handbook: Essential Tools... on Amazon

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Read the chapters on Matplotlib and Seaborn.
Work through the examples provided in the book.
Experiment with different visualization techniques.

Recreate Matplotlib Gallery Examples

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Solidify your Matplotlib skills by replicating complex visualizations from the official Matplotlib gallery.

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Choose a visualization from the Matplotlib gallery.
Analyze the code and try to understand the logic.
Recreate the visualization from scratch.
Compare your result with the original.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Review 'Storytelling with Data'

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Improve your ability to communicate data-driven insights effectively through compelling visualizations.

View Storytelling with You: Plan, Create, and... on Amazon

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Read the book and take notes on key concepts.
Apply the principles to your own visualizations.
Practice presenting your visualizations to others.

Visualize Personal Data

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Apply your newly acquired skills by visualizing data from your personal life, such as fitness tracking data or financial transactions.

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Gather data from a personal source.
Clean and prepare the data for visualization.
Create visualizations using Matplotlib and Seaborn.
Analyze the visualizations and draw insights.

Create a Data Visualization Blog Post

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Reinforce your learning by creating a blog post explaining a specific data visualization technique or showcasing a project.

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Choose a topic related to data visualization.
Write a clear and concise explanation of the topic.
Include code examples and visualizations.
Publish the blog post online.

Contribute to Matplotlib or Seaborn

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Deepen your understanding of the libraries by contributing to their open-source development.

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Explore the Matplotlib or Seaborn GitHub repository.
Identify a bug or feature request.
Implement a solution or improvement.
Submit a pull request.

Career center

Learners who complete Python Data Visualization: Matplotlib & Seaborn Masterclass will develop knowledge and skills that may be useful to these careers:

Data Analyst

A data analyst examines data using various statistical tools and software. The data analyst identifies trends, develops charts, and creates reports. This "Python Data Visualization: Matplotlib & Seaborn Masterclass" helps data analysts create compelling visuals. As a data analyst, you will be working with stakeholders and communicating data insights. The course helps develop skills using Matplotlib and Seaborn. You will learn to customize charts and how to visualize data. These skills you need to present information and tell compelling stories to stakeholders.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

A business intelligence analyst examines data and market trends. They look to improve a company's profits and efficiency. This course, "Python Data Visualization: Matplotlib & Seaborn Masterclass," helps a business intelligence analyst communicate data insights and findings. The course is a source for learning frameworks and best practices for choosing the right charts. It is useful in learning how to apply effective formatting. The business intelligence analyst makes clear, data-driven stories and insights. This will help you develop your skill set.

See salaries and explore the career path for Business Intelligence Analyst

Data Scientist

A data scientist examines vast sources of data. They then seek to identify trends, make business predictions, and create easily digestible visualizations. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" directly supports the creation of those data visualizations. This course teaches how to leverage Python libraries like Matplotlib and Seaborn, which are essential tools in a data scientist's toolkit. You will be able to present findings with impact and clarity. Skills you will need as a data scientist.

See salaries and explore the career path for Data Scientist

Market Research Analyst

A market research analyst studies market conditions, consumer behaviors, and competitor activities. They look to advise companies on product development and marketing campaigns. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful for visualizing complex market data. This allows the analyst to present their insights to stakeholders in a clear and compelling manner. The course provides experience with Matplotlib and Seaborn. These are tools that help translate raw data into actionable intelligence.

See salaries and explore the career path for Market Research Analyst

Statistician

Statisticians collect, analyze, and interpret numerical data. They then apply statistical methodologies to solve problems in various fields. This "Python Data Visualization: Matplotlib & Seaborn Masterclass" is an asset. It may assist statisticians in presenting their research findings. They can use visualizations and graphical representations. This course will help you learn to communicate complex statistical concepts. You will use Matplotlib and Seaborn, tools that translate data into understandable formats.

See salaries and explore the career path for Statistician

Financial Analyst

A financial analyst analyzes financial data. They provide investment recommendations. They also prepare financial reports. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful for a financial analyst. It can help them to visualize financial trends and performance metrics. Through the course, financial analysts can learn to create informative charts and graphs. These can be used in presentations to stakeholders. This improves communication and supports data-driven decision-making.

See salaries and explore the career path for Financial Analyst

Data Engineer

A data engineer builds and maintains data pipelines and infrastructure. They ensure data is accessible, reliable, and optimized for analysis. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful for a data engineer. It will help them gain a better understanding of how the data they manage is ultimately used and visualized. The course provides insight into the data visualization process. You will understand the impact and utility of the data pipelines they create.

See salaries and explore the career path for Data Engineer

Healthcare Analyst

A healthcare analyst uses data to improve healthcare outcomes. They also help streamline processes. They identify trends and provide recommendations. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful for a healthcare analyst. It will help analysts display healthcare data. They can create visuals that communicate key insights to decision-makers. The course provides techniques. These techniques will help translate complex datasets into actionable information.

See salaries and explore the career path for Healthcare Analyst

Research Scientist

A research scientist designs and conducts experiments. They analyze data, and then publish findings. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful for research scientists. It will help them visualize data. They can create compelling figures for publications and presentations. The course offers a range of charting options. This includes formatting techniques. These will help research scientists tell a story with their data.

See salaries and explore the career path for Research Scientist

Quantitative Analyst

A quantitative analyst, often working in the finance sector, develops and implements mathematical models for pricing and risk management. While an advanced degree (master's or PhD) is typically required, "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful. It may help them visualize and present their model outputs and findings. It allows quantitative analysts to communicate insights effectively to stakeholders and decision-makers, even if their primary focus is on model development.

See salaries and explore the career path for Quantitative Analyst

Supply Chain Analyst

A supply chain analyst optimizes the flow of goods and information. They aim to improve efficiency and reduce costs. They may find the "Python Data Visualization: Matplotlib & Seaborn Masterclass" useful for visualizing supply chain data. The supply chain analyst will be able to create charts and dashboards that display key performance indicators. The course provides you with essential tools. These tools translate complex supply chain data into actionable insights.

See salaries and explore the career path for Supply Chain Analyst

Management Consultant

A management consultant advises organizations. They look to improve performance and efficiency. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful to create presentations and reports. These reports will communicate findings and recommendations. The course will teach you to visualize data. You will be able to present data to clients in meetings. These are skills that are helpful to your career as a management consultant.

See salaries and explore the career path for Management Consultant

Actuary

An actuary assesses and manages financial risks. They work primarily in the insurance industry. While an advanced degree is often needed, the "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful for an actuary. They can use it present complex actuarial models and predictions. The course enables an actuary to translate numerical results into visuals. Matplotlib and Seaborn are important tools. They will help communicate insights effectively to stakeholders.

See salaries and explore the career path for Actuary

Urban Planner

An urban planner develops plans and programs for land use. They create community growth and redevelopment. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" may be useful. Charts and maps will help visualize demographic data. It can also display transportation patterns. As an urban planner, you can use the course to enhance your visual communication. Seaborn is a tool that will help you create data driven images.

See salaries and explore the career path for Urban Planner

Digital Marketing Specialist

A digital marketing specialist develops and implements marketing campaigns. They use various digital channels. The "Python Data Visualization: Matplotlib & Seaborn Masterclass" helps a digital marketing specialist visualize campaign data and performance metrics. The digital marking specialist can use this course to learn visualization frameworks and best practices. It may be easier to present insights and data to stakeholders.

See salaries and explore the career path for Digital Marketing Specialist

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python Data Visualization: Matplotlib & Seaborn Masterclass.

Python Data Science Handbook

Save

Provides a comprehensive overview of essential Python data science tools, including Matplotlib and Seaborn. It covers data manipulation with Pandas, which is often used in conjunction with visualization libraries. The book valuable reference for understanding the underlying principles and advanced techniques for data analysis and visualization. It is commonly used as a textbook in data science courses.

Python Data Science Handbook: Essential Tools for...

Paperback

$$$

Storytelling with You

Save

Focuses on the art of communicating insights through data visualization. It provides practical guidance on choosing the right visuals, designing effective charts, and crafting compelling narratives. While not a technical guide to Matplotlib or Seaborn, it complements the course by teaching you how to present your visualizations in a clear and impactful way. This book is commonly used by business professionals.

Storytelling with You: Plan, Create, and Deliver a...

Paperback

Storytelling with You: Plan, Create, and Deliver a...

Kindle Edition

Python Data Visualization

Matplotlib & Seaborn Masterclass

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Practical python data vis skills

Activities

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