Data science is an exciting discipline that allows you to transform raw data into understanding, insight, and knowledge. The goals of R for Data Science are to help you learn the most important tools in R that will allow you to do data science efficiently and reproducibly and to have some fun along the way! After reading this book, you’ll have the tools to tackle a wide variety of data science challenges using the best parts of R.
[Xem chi tiết]📚📚 I. THÔNG TIN SẢN PHẨM
📒 Mã sản phẩm : STT950
📒 Nhà xuất bản : O'Reilly Media; 2nd edition (July 18, 2023)
📒 Tác giả : Hadley Wickham, Mine Çetinkaya-Rundel
📒 Ngôn ngữ : Tiếng Anh
📒 ISBN : 1492097403
📒 Số trang : 579 trang
📒 Hình thức : Bìa Mềm, IN ĐEN TRẮNG
📒 Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
📒 Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
📒 Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.
📚📚 II. MÔ TẢ SẢN PHẨM
📒 1.Mô tả sản phẩm
Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverseâ??a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly.
You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way.
You'll understand how to:
📒 2. Tác giả
Hadley Wickham is Chief Scientist at RStudio and a member of the R Foundation. He builds tools (both computational and cognitive) that make data science easier, faster, and more fun. His work includes packages for data science (ggplot2, dplyr, tidyr), data ingest (readr, readxl, haven), and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and frequent speaker promoting the use of R for data science. Learn more on his homepage, http://hadley.nz.
Mine Çetinkaya-Rundel is Professor of the Practice and the Director of Undergraduate Studies at the Department of Statistical Science and an affiliated faculty in the Computational Media, Arts, and Cultures program at Duke University as well as Educator at RStudio.
Garrett Grolemund is the author of Hands-On Programming with R and co-author of R for Data Science and R Markdown: The Definitive Guide. He is Director of Learning at RStudio and holds a Ph.D. in Statistics, but specializes in teaching.
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