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Python for Data Visualization

Matplotlib & Seaborn

Ryan Ahmed

In this hands-on project, we will understand the fundamentals of data visualization with Python and leverage the power of two important python libraries known as Matplotlib and seaborn. We will learn how to generate line plots, scatterplots, histograms, distribution plot, 3D plots, pie charts, pair plots, countplots and many more!

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In this hands-on project, we will understand the fundamentals of data visualization with Python and leverage the power of two important python libraries known as Matplotlib and seaborn. We will learn how to generate line plots, scatterplots, histograms, distribution plot, 3D plots, pie charts, pair plots, countplots and many more!

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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What's inside

Syllabus

Python for Data Visualization: Matplotlib & Seaborn
In this hands-on project, we will understand the fundamentals of data visualization with Python and leverage the power of two important python libraries known as Matplotlib and seaborn. We will learn how to generate line plots, scatterplots, histograms, distribution plot, 3D plots, pie charts, pair plots, countplots and many more!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for beginners exploring data visualization in Python
Leverages popular Python libraries Matplotlib and Seaborn
Covers various plot types, enhancing data visualization skills
Offers hands-on exercises for practical application
Best suited for learners based in North America due to regional restrictions

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Reviews summary

Python data visualization fundamentals

Learners say Python for Data Visualization: Matplotlib & Seaborn is an excellent course for beginners who want to learn the basics of data visualization with Python, Matplotlib, and Seaborn. The course is well-structured and easy to follow, with clear and concise explanations. The instructor is knowledgeable and engaging, and the mini-challenges are a great way to practice the concepts learned.
Hands-on mini-challenges reinforce learning.
"And I loved mini challenges idea."
Instructor is knowledgeable and engaging.
"The instructor and the videos are clear and concise."
"The instructor is good and has clear pronunciation."
Perfect for those new to data visualization.
"This course is too basic - but gives you a good idea of what to do."
"In one word superb overview and explanation."
"I wanted to understand how to make surface maps and contour maps - but these were hardly touched."
Course materials cannot be downloaded for offline use.
"Please know that this project does NOT have a resource section where you can download what you have done."
Covers basic concepts, may not be sufficient for advanced learners.
"T​his course is too basic - but gives you a good idea of what to do."
"Seaborn and 3D plot is just brushed at the surface."

Activities

Coming soon We're preparing activities for Python for Data Visualization: Matplotlib & Seaborn. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Python for Data Visualization: Matplotlib & Seaborn will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst uses data to help companies make better decisions. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be easily understood by stakeholders. This course can help you develop the skills you need to succeed as a Data Analyst by providing you with a strong foundation in data visualization.
Data Scientist
A Data Scientist uses data to solve business problems. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to make informed decisions. This course can help you develop the skills you need to succeed as a Data Scientist by providing you with a strong foundation in data visualization.
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models to solve business problems. They use their skills in Python, Matplotlib, and Seaborn to visualize data and create models that can be used to make predictions. This course can help you develop the skills you need to succeed as a Machine Learning Engineer by providing you with a strong foundation in data visualization.
Business Analyst
A Business Analyst uses data to help companies make better decisions. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to understand business trends and make informed decisions. This course can help you develop the skills you need to succeed as a Business Analyst by providing you with a strong foundation in data visualization.
Financial Analyst
A Financial Analyst uses data to make investment decisions. They use their skills in Python, Matplotlib, and Seaborn to analyze financial data and create visualizations that can be used to identify investment opportunities. This course can help you develop the skills you need to succeed as a Financial Analyst by providing you with a strong foundation in data visualization.
Market Analyst
A Market Analyst uses data to understand market trends and make marketing decisions. They use their skills in Python, Matplotlib, and Seaborn to analyze market data and create visualizations that can be used to identify opportunities and make informed decisions. This course can help you develop the skills you need to succeed as a Market Analyst by providing you with a strong foundation in data visualization.
Operations Research Analyst
An Operations Research Analyst uses data to improve the efficiency of business operations. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to identify inefficiencies and make improvements. This course can help you develop the skills you need to succeed as an Operations Research Analyst by providing you with a strong foundation in data visualization.
Program Manager
A Program Manager uses data to manage the implementation of programs and projects. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to track progress and make informed decisions. This course can help you develop the skills you need to succeed as a Program Manager by providing you with a strong foundation in data visualization.
Product Manager
A Product Manager uses data to develop and manage products. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to understand customer needs and make product decisions. This course can help you develop the skills you need to succeed as a Product Manager by providing you with a strong foundation in data visualization.
Project Manager
A Project Manager uses data to manage the implementation of projects. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to track progress and make informed decisions. This course can help you develop the skills you need to succeed as a Project Manager by providing you with a strong foundation in data visualization.
Risk Analyst
A Risk Analyst uses data to identify and manage risks. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to identify risks and make informed decisions. This course can help you develop the skills you need to succeed as a Risk Analyst by providing you with a strong foundation in data visualization.
Software Engineer
A Software Engineer uses data to develop and maintain software systems. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to understand user needs and make software design decisions. This course may help you develop the skills you need to succeed as a Software Engineer by providing you with a foundation in data visualization.
Statistician
A Statistician uses data to analyze data and draw conclusions. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to understand data patterns and make informed decisions. This course may help you develop the skills you need to succeed as a Statistician by providing you with a foundation in data visualization.
Data Visualization Engineer
A Data Visualization Engineer designs and develops data visualizations. They use their skills in Python, Matplotlib, and Seaborn to create visualizations that can be used to communicate data insights to stakeholders. This course may help you develop the skills you need to succeed as a Data Visualization Engineer by providing you with a foundation in data visualization.
User Experience Researcher
A User Experience Researcher conducts research to understand user needs and improve the user experience of products. They use their skills in Python, Matplotlib, and Seaborn to analyze data and create visualizations that can be used to understand user behavior and make design decisions. This course may help you develop the skills you need to succeed as a User Experience Researcher by providing you with a foundation in data visualization.

Reading list

We've selected 11 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 for Data Visualization: Matplotlib & Seaborn.
Provides a comprehensive introduction to data science using Python, covering data manipulation, visualization, and machine learning.
Provides a comprehensive guide to data science using R, covering topics such as data import, wrangling, visualization, and modeling.
Provides a comprehensive guide to data analysis using Python, covering topics such as data manipulation, cleaning, and visualization.
Features a collection of essays from experts in the field of data visualization, providing insights into the principles and techniques of effective data visualization.
Focuses on creating interactive data visualizations for the web using JavaScript and D3.js. It covers a range of topics, from the basics of D3.js to more advanced techniques such as data binding and animation.
Provides a comprehensive introduction to the ggplot2 package for data visualization in R. It covers a wide range of topics, from the basics of ggplot2 to more advanced techniques such as creating custom visualizations and working with large datasets.
Provides a comprehensive overview of the field of information visualization. It covers a wide range of topics, from the history of information visualization to the latest research in the field.
Provides a practical guide to data visualization. It covers a wide range of topics, from the basics of data visualization to more advanced techniques such as creating interactive visualizations and working with large datasets.
Classic work on data visualization. It provides a comprehensive overview of the field, covering topics such as the principles of data visualization, the different types of data visualizations, and how to create effective visualizations.

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