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Mastering Data Visualization with R

Matthew Renze

Learn how to create advanced data visualizations with R in order to transform your data into actionable insight.

R is a popular open-source programming language for data analysis. Its interactive programming environment and data visualization capabilities make R an ideal tool for creating a wide variety of data visualizations. In this course, Mastering Data Visualization with R, you will learn how to answer questions about your data by creating advanced data visualizations with R. First, you'll learn how to create and interpret data visualizations that involve spatial data, hierarchical data, graph and network data, and textual data. Then, you'll learn how to create animated data visualizations. Finally, you'll learn how to create web-based interactive data visualizations using a framework called Shiny. By the end of this course, you'll have the skills necessary to create and interpret a variety of data visualizations using R.

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What's inside

Syllabus

Course Overview

Introduction

Visualizing Spatial Data

Visualizing Hierarchical Data

Visualizing Graph and Network Data

Visualizing Textual Data

Animating Data Visualizations

Creating Interactive Data Visualizations

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers data visualizations, which are common in the field of data analysis

Taught by Matthew Renze, who authored the book 'R for Data Science'

Uses R, which is an industry-standard tool for data visualization

Covers advanced data visualization techniques, which can be used to create more insightful and engaging visualizations

Includes hands-on exercises and projects, which allows learners to apply their knowledge

Can help learners advance their careers in data analysis, data visualization, and related fields

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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 Mastering Data Visualization with R with these activities:

Review R basics

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Reviewing the basics of R will help you refresh your knowledge and prepare you for the more advanced concepts covered in this course.

Browse courses on R Programming

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Go through your notes or study materials from previous R courses or tutorials.
Complete practice questions or exercises to test your understanding of R syntax and data manipulation techniques.

Participate in peer study groups or online forums

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Participating in peer study groups or online forums will allow you to connect with other learners, ask questions, and share knowledge.

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Join online forums or discussion groups related to R and data visualization.
Participate in discussions, ask questions, and share your knowledge and experiences.
Attend or host virtual study sessions with other learners to review course materials and practice data visualization techniques.

Follow tutorials on advanced data visualization techniques in R

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Following tutorials will provide you with practical examples and step-by-step instructions to help you master advanced data visualization techniques in R.

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Search for tutorials on specific data visualization techniques that you want to learn or improve upon.
Follow the tutorials carefully, taking notes and practicing the techniques shown.
Experiment with different data sets and visualization parameters to see how they affect the final visualizations.

Four other activities

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Create data visualizations for different types of data

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Creating data visualizations for different types of data will help you develop a deeper understanding of how to represent and communicate data effectively.

Browse courses on Data Visualization

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Gather different types of data sets, such as spatial data, hierarchical data, network data, and textual data.
Explore the data and identify the key insights that you want to communicate.
Choose appropriate data visualization techniques to represent the insights effectively.
Create the visualizations using R and evaluate their effectiveness.

Develop an interactive data visualization using Shiny

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Developing an interactive data visualization using Shiny will allow you to create dynamic and engaging visualizations that can be shared with others.

Browse courses on Interactive Data Visualization

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Choose a data set and identify the insights that you want to communicate.
Design the layout and interface of your Shiny app.
Write the R code to create the visualizations and make them interactive.
Deploy your Shiny app and share it with others.

Contribute to open-source data visualization projects

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Contributing to open-source data visualization projects will allow you to learn from and collaborate with others in the community.

Browse courses on R Packages

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Identify open-source data visualization projects that align with your interests or skills.
Review the project documentation and identify areas where you can contribute.
Submit pull requests with your contributions and provide clear explanations of your changes.

Develop a data visualization project for a real-world problem

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Developing a data visualization project for a real-world problem will allow you to apply your skills to solve a practical problem and create a valuable portfolio piece.

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Identify a real-world problem that you can solve using data visualization.
Gather and prepare the necessary data.
Analyze the data and identify the key insights.
Create a data visualization that effectively communicates the insights.
Present your project and explain how it addresses the real-world problem.

Career center

Learners who complete Mastering Data Visualization with R will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist will gather, manage, and synthesize data so that it can be used to create models. Mastering Data Visualization with R can help build a foundation for data interpretation and creating visual representations for data analysis that is persuasive and clear. Any of the topics taught in this course may be used in the work of a Data Scientist, but particularly important is the section covering visualizing spatial data, hierarchical data, and graph and network data, as these often occur in a Data Scientist's workflow.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst cleans, processes, and mines data to help drive a company's business strategy. This course will help you to build skills necessary to prepare and visualize data in a way that can lead to data-driven decisions. The course includes several sections covering advanced data visualization, including visualizing spatial data, hierarchical data, graph and network data, textual data, and animating data visualizations. Creating these advanced data visualizations will help a Data Analyst make their work more persuasive and impactful.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

A Business Intelligence Analyst transforms data into actionable insights for an organization. This course will teach you how to use R to create advanced data visualizations, which is an essential tool for a Business Intelligence Analyst. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data. These techniques can be used to create insights that can help an organization make better decisions.

See salaries and explore the career path for Business Intelligence Analyst

Market Research Analyst

A Market Research Analyst gathers and interprets data about customers, competitors, and the market. This course can teach you how to visualize data in a way that can help you understand market trends and make better decisions. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data. These techniques can be used to create insights that can help you develop more effective marketing campaigns.

See salaries and explore the career path for Market Research Analyst

Quantitative Analyst

A Quantitative Analyst develops and uses mathematical and statistical models to analyze data and make predictions. This course can teach you how to use R to create advanced data visualizations, which can be used to communicate your findings to clients and stakeholders. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Quantitative Analyst

Risk Analyst

A Risk Analyst identifies and assesses financial risks. This course can teach you how to use R to create advanced data visualizations, which are essential for communicating your findings to clients and stakeholders. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Risk Analyst

Product Analyst

A Product Analyst gathers and analyzes data to help improve products. This course can teach you how to use R to create advanced data visualizations, which can help you communicate your findings to clients and stakeholders. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Product Analyst

Financial Analyst

A Financial Analyst analyzes financial data to make investment recommendations. This course can teach you how to use R to create advanced data visualizations, which can be used to communicate your findings to clients and stakeholders. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

An Operations Research Analyst develops and uses mathematical and statistical models to solve business problems. This course can teach you how to use R to create advanced data visualizations, which can be used to communicate your findings to clients and stakeholders. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Operations Research Analyst

Statistician

A Statistician gathers, analyzes, and interprets data. This course can teach you how to use R to create advanced data visualizations, which can be used to communicate your findings to clients and stakeholders. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Statistician

Software Developer

A Software Developer designs, develops, and maintains software systems. This course may be useful for a Software Developer who wants to learn how to use R to create advanced data visualizations. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Software Developer

Web Developer

A Web Developer designs and develops websites. This course may be useful for a Web Developer who wants to learn how to create interactive data visualizations for the web. The course covers how to create web-based interactive data visualizations using a framework called Shiny.

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Data Engineer

A Data Engineer builds and maintains data pipelines. This course may be useful for a Data Engineer who wants to learn how to use R to create advanced data visualizations. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models. This course may be useful for a Machine Learning Engineer who wants to learn how to use R to create advanced data visualizations. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Machine Learning Engineer

Data Science Manager

A Data Science Manager leads a team of data scientists. This course may be useful for a Data Science Manager who wants to learn how to use R to create advanced data visualizations. The course covers a variety of data visualization techniques, including visualizing spatial data, hierarchical data, graph and network data, and textual data.

See salaries and explore the career path for Data Science Manager

Reading list

We've selected 14 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 Mastering Data Visualization with R.

Modern Data Visualization with R

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Practical guide to creating data visualizations with R. It covers a wide range of topics, from basic visualizations to advanced techniques, such as creating interactive visualizations and working with spatial data. It valuable resource for anyone who wants to learn how to use R for data visualization.

Modern Data Visualization with R (Chapman &...

Kindle Edition

$$$

R for Data Science

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Comprehensive guide to ggplot2, a popular R package for data visualization. It provides a detailed overview of the ggplot2 grammar, and shows how to use it to create a wide variety of data visualizations. It is an essential resource for anyone who wants to learn how to use ggplot2.

Mastering Data Visualization with R

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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