R for Data Science

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R for Data Science

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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. Learn how to use R to transform raw data into insights, knowledge, and understanding. This book introduces you to R, RStudio, and the Tidyverse, a collection of R packages designed to work together to make data science fast, fluid, and fun. R for Data Science is suitable for readers with no prior programming experience and is designed to get you started with data science as soon as possible.

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R for Data Science PDF book author

Hadley Wickham is Assistant Professor and Dobelman Family Junior Chair of Statistics at Rice University. He is an active member of the R community, has written and contributed to over 30 R packages, and won the John Chambers Award for Statistical Computing for his work developing tools for remodeling and visualizing data. His research focuses on how to make data analysis better, faster, and easier, with a particular focus on using visualizations to better understand data and models.

Garrett Grolemund is an R statistician, teacher, and developer who currently works for RStudio. She sees data analysis as a largely untapped source of value for industry and science. Garrett received his PhD from Rice University in Hadley Wickham's laboratory, where his research traced the origins of data analysis as a cognitive process and discovered how attention and epistemological concerns drive all data analysis.

Garrett is passionate about helping people avoid the frustration and unnecessary learning he went through while mastering data analysis. Before completing his dissertation, he began teaching business trainings in R and data analytics for Revolutions Analytics. He has taught at Google, eBay, Axciom and many other companies and is currently developing a training curriculum for RStudio that will make useful know-how even more accessible.

Outside of teaching, Garrett spends his time researching clinical trials, legal research, and financial analysis. He also develops R software, is co-author of the lubridate R package, which provides methods to analyze, manipulate and calculate with date and time, and wrote the ggsubplot package, which extends the ggplot2 package.

R for Data Science PDF

Authors Hadley Wickham and Garrett Grolemund walk you through the steps of importing, wrapping, exploring, and modeling your data and communicating the results. You will have a thorough and thorough understanding of the data science cycle, as well as the basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you have learned.