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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
Explores core concepts in data visualization with Python
Taught by Ryan Ahmed, an expert in data visualization and data analysis
Utilizes Python libraries Matplotlib and Seaborn, which are widely used in industry
Covers various types of data visualization, including line plots, scatterplots, and histograms
Offers hands-on exercises and interactive materials for active learning
Suited for beginners seeking a foundation in data visualization with Python

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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 for Data Visualization:Matplotlib & Seaborn(Enhanced) with these activities:
Review Statistics
Brush up on your statistics skills to get a solid footing for this course.
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  • Review probability distributions and their properties.
  • Practice calculating descriptive statistics (mean, median, mode, etc.).
  • Refresh your knowledge of hypothesis testing and confidence intervals.
Review Python Basics
Ensure you have a solid understanding of Python before diving into data visualization.
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  • Review variables, data types, and operators.
  • Practice writing simple functions and loops.
  • Refresh your knowledge of object-oriented programming concepts.
Explore Matplotlib and Seaborn Tutorials
Enhance your understanding of these Python libraries by following some tutorials to reinforce what's covered in the course.
Browse courses on Matplotlib
Show steps
  • Find a tutorial that covers the basics of Matplotlib.
  • Follow a tutorial that demonstrates how to create visualizations with Seaborn.
  • Try out the examples and experiment with different data sets.
Three other activities
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Show all six activities
Join a Study Group for Python Visualization
Collaborate with peers to enhance your understanding of Python visualization techniques.
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Show steps
  • Find a study group or create one with classmates.
  • Meet regularly to discuss course concepts, share code snippets, and work on projects together.
  • Provide feedback and support to your peers.
Create a Variety of Plots with Matplotlib
Solidify your grasp of Matplotlib by practicing creating different types of plots.
Browse courses on Matplotlib
Show steps
  • Create a line plot to visualize a time series.
  • Plot a scatterplot to show the relationship between two variables.
  • Generate a histogram to display the distribution of data.
  • Create a pie chart to represent proportions.
Develop a Dashboard with Seaborn
Deepen your understanding of Seaborn by building a dashboard to visualize data comprehensively.
Browse courses on Seaborn
Show steps
  • Choose a dataset and import it into your Python environment.
  • Use Seaborn to create multiple visualizations (e.g., line charts, scatterplots, histograms).
  • Arrange the visualizations on a dashboard using a framework like Plotly or Dash.
  • Share your dashboard with others for feedback and insights.

Career center

Learners who complete Python for Data Visualization:Matplotlib & Seaborn(Enhanced) will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make better decisions. The ability to visualize data is an essential skill for Data Analysts, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Data Analyst.
Data Scientist
Data Scientists analyze large amounts of data to find patterns and trends that can help businesses make better decisions. The ability to visualize data is an essential skill for Data Scientists, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Data Scientist.
Market Research Analyst
Market Research Analysts collect and analyze data on consumer behavior to help businesses develop new products and services. The ability to visualize data is an essential skill for Market Research Analysts, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Market Research Analyst.
Business Analyst
Business Analysts help businesses improve their performance by analyzing data and identifying opportunities for improvement. The ability to visualize data is an essential skill for Business Analysts, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Business Analyst.
Financial Analyst
Financial Analysts help businesses make sound financial decisions by analyzing financial data. The ability to visualize data is an essential skill for Financial Analysts, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Financial Analyst.
Statistician
Statisticians collect, analyze, and interpret data to help businesses make better decisions. The ability to visualize data is an essential skill for Statisticians, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Statistician.
Data Engineer
Data Engineers design and build systems to manage and process data. The ability to visualize data is an essential skill for Data Engineers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Data Engineer.
Machine Learning Engineer
Machine Learning Engineers design and build machine learning models to solve business problems. The ability to visualize data is an essential skill for Machine Learning Engineers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Machine Learning Engineer.
Software Engineer
Software Engineers design, develop, and maintain software applications. The ability to visualize data is an essential skill for Software Engineers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Software Engineer.
Data Visualization Specialist
Data Visualization Specialists design and create visualizations to help businesses communicate data insights. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Data Visualization Specialist.
Graphic designer
Graphic Designers create visual concepts, using computer software or by hand, to communicate ideas that inspire, inform, and captivate consumers. The ability to visualize data is an essential skill for Graphic Designers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Graphic Designer.
UX Designer
UX Designers create user interfaces for websites and applications. The ability to visualize data is an essential skill for UX Designers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a UX Designer.
Sales Manager
Sales Managers are responsible for the development and execution of sales strategies. The ability to visualize data is an essential skill for Sales Managers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Sales Manager.
Marketing Manager
Marketing Managers are responsible for the development and execution of marketing campaigns. The ability to visualize data is an essential skill for Marketing Managers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Marketing Manager.
Product Manager
Product Managers are responsible for the development and launch of new products. The ability to visualize data is an essential skill for Product Managers, as it allows them to quickly and easily identify patterns and trends in data. This course will help you build a strong foundation in data visualization using Python libraries such as Matplotlib and seaborn. These skills will be invaluable to you if you are interested in a career as a Product Manager.

Reading list

We've selected 13 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(Enhanced).
Classic text on data visualization. It covers a wide range of topics, including data visualization principles, chart selection, and design principles. This book would be a valuable resource for anyone looking to learn more about data visualization best practices.
Provides a comprehensive overview of data science, from data collection to data visualization. It covers a wide range of topics, including data exploration, data cleaning, and data modeling. This book would be a valuable resource for anyone looking to learn more about data science.
Provides a comprehensive overview of data visualization principles and best practices. It covers a wide range of topics, including data visualization theory, chart selection, and design principles. This book would be a valuable resource for anyone looking to learn more about data visualization best practices.
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including deep learning algorithms, model training, and model evaluation. This book would be a valuable resource for anyone looking to learn more about deep learning.
Provides a theoretical foundation for data visualization. It covers a wide range of topics, including data representation, visual perception, and interaction design. This book would be a valuable resource for anyone looking to learn more about the theoretical foundations of data visualization.
Provides a comprehensive overview of data visualization. It covers a wide range of topics, including data visualization principles, chart selection, and design principles. This book would be a valuable resource for anyone looking to learn more about data visualization.
Provides a comprehensive overview of data analysis using Python. It covers a wide range of topics, including data exploration, data cleaning, and data visualization. This book would be a valuable resource for anyone looking to learn more about data analysis with Python.
Provides a comprehensive overview of data visualization. It covers a wide range of topics, including data visualization principles, chart selection, and design principles. This book would be a valuable resource for anyone looking to learn more about data visualization.
Provides a comprehensive overview of data visualization techniques, with a focus on using Python and JavaScript. It covers a wide range of topics, including data preparation, chart creation, and interactive visualizations. This book would be a valuable resource for anyone looking to learn more about data visualization with Python and JavaScript.
Provides a comprehensive overview of data visualization. It covers a wide range of topics, including data visualization principles, chart selection, and design principles. This book would be a valuable resource for anyone looking to learn more about data visualization.
Provides a comprehensive overview of data visualization. It covers a wide range of topics, including data visualization principles, chart selection, and design principles. This book would be a valuable resource for anyone looking to learn more about data visualization.
Provides a comprehensive overview of the ggplot2 package for data visualization in R. It covers a wide range of topics, including data preparation, chart creation, and interactive visualizations. This book would be a valuable resource for anyone looking to learn more about data visualization with R.
Provides a collection of recipes for creating visualizations in R. It covers a wide range of topics, including data preparation, chart creation, and interactive visualizations. This book would be a valuable resource for anyone looking for a quick and easy way to create visualizations in R.

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