R FOR DATA SCIENCE 2nd edition

Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as the tidyverse-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. Each section in this edition includes exercises to help you practice what you've learned along the way.Updated for the latest tidyverse best practices, new chapters dive deeper into visualization and data wrangling, show you how to get data from spreadsheets, databases, and websites, and help you make the most of new programming tools.You'll learn how to:Visualize-create plots for data exploration and communication of resultsTransform-discover types of variables and the tools you can use to work with themImport-get data into R and in a form convenient for analysisProgram-learn R tools for solving data problems with greater clarity and easeCommunicate-integrate prose, code, and results with Quarto

Détails du produit

• Auteurs: Garrett Grolemund, Hadley Wickham, Grolemund Garrett, Mine Cetinkaya-Rundel, Mine Cetinkaya–rundel, Wickham Hadley, Garreth Grolemund
• Edition: O'Reilly UK Ltd.
• Contenu: Livre
• Forme du produit: Livre de poche
• Date de parution: 30.06.2023
• Catégorie: Ecole et pédagogie > Préparation de l'enseignement > Formation professionnelle; Sciences naturelles, médecine, it, technique > Informatique, ordinateurs > Informatique
• EAN: 9781492097402
• ISBN: 978-1-4920-9740-2
• Nombre de pages: 548
• Catégories: COMPUTERS / Data Science / Data Visualization; COMPUTERS / Database Administration & Management; Data capture and analysis; Data Capture & Analysis; r data ggvis rmarkdown shiny dplyr tidyr statistics visualization data analysis data modelling data prediction shiny r packages packages