R for Data Science
Hadley Wickham is a Rice University Assistant Professor and the Dobelman Family Junior Chair in Statistics. He is an active member of the R community, having written and contributed to over 30 R packages. He was awarded the John Chambers Award for Statistical Computing for his work developing data reshaping and visualization tools. Garrett Grolemund is a R developer, statistician, and teacher who presently works at RStudio. Data analysis, he believes, is a largely untapped source of value for both industry and science.
Learn how to use R to transform raw data into insight, knowledge, and comprehension. This book will teach you to R, RStudio, and the tidyverse, a set of R programs that work together to make data science quick, fluent, and enjoyable. R for Data Science is intended for readers with no prior programming expertise and is intended to get you started with data science as soon as possible.
Hadley Wickham and Garrett Grolemund walk you through the steps of importing, wrangling, examining, modeling, and communicating the outcomes of your data. You'll receive a comprehensive, big-picture grasp of the data science cycle, as well as the fundamental tools you'll need to manage the specifics. Each section of the book is accompanied by exercises to help you put what you've learned into practice. R for Data Science is regarded as one of the best books on databases and big data.
You'll discover how to:
- Wrangle: transform your datasets into an analysis-friendly format.
- Program: Learn how to use sophisticated R tools to solve data problems more clearly and easily.
- Explore: Examine your data, make hypotheses, and test them quickly.
- Model: create a low-dimensional description of your dataset's true "signals."
- Communicate: Learn how to use R Markdown to integrate prose, code, and results.
Author: Hadley Wickham and Garrett Grolemund
Link to buy: https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399/
Ratings: 4.7 out of 5 stars (from 1307 reviews)
Best Sellers Rank: #11,743 in Books
#2 in Mathematical & Statistical Software
#3 in Statistics (Books)
#7 in Data Processing
