Beginning Data Visualization with R and ggplot2
- 3.3
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Brief Introduction
Learn to design and implement data from scratchDescription
Data analysis is crucial to accurately predict the performance of an application. When data is presented to you in a graphical or pictorial format, you can analyze it more effectively. This Learning Path introduces you to the tools for working with data. To start with, you'll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops.
Once you have grasped the basics, you'll move on to studying data visualization and graphics. You'll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you'll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values. You'll discover what layers, scales, coordinates, and themes are, and study how you can use them to transform your data into aesthetical graphs. Next, you'll study simple plots such as histograms and advanced plots such as superimposing and density plots. You'll also get to grips with plotting trends, correlations, and statistical summaries.
By the end of this Learning Path, you'll become master in data visualization techniques using the powerful R libraries.
About the Author
Samik Sen is currently working with R on machine learning. He has done his PhD in Theoretical Physics. He has tutored classes for high performance computing postgraduates and lecturer at international conferences. He has experience of using Perl on data, producing plots with gnuplot for visualization and latex to produce reports. He, then, moved to finance/football and online education with videos.
Chris DallaVilla is the founder and CEO of VALID., an independent marketing consulting practice specializing in providing data-driven solutions that help chief marketing officers and their teams strengthen their planning and execution, and drive results. Chris has expertise in digital and social media marketing, as well as certifications in Agile, Google AdWords, and Google Analytics. He studied computer science at Harvard University, design technology at Massachusetts College of Art and Design, and advertising and marketing communications at the Questrom School of Business at Boston University.
Requirements
- Requirements
- Prior knowledge of R programming would be beneficial. It is assumed that you know basic high school math and statistics.
Packt Publishing
3.3 Raiting
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