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portada Learn Rstudio Ide: Quick, Effective, and Productive Data Science
Type
Physical Book
Publisher
Language
Inglés
Pages
153
Format
Paperback
Dimensions
23.4 x 15.6 x 0.9 cm
Weight
0.24 kg.
ISBN13
9781484245101

Learn Rstudio Ide: Quick, Effective, and Productive Data Science

Matthew Campbell (Author) · Apress · Paperback

Learn Rstudio Ide: Quick, Effective, and Productive Data Science - Campbell, Matthew

Physical Book

£ 35.30

  • Condition: New
Origin: U.S.A. (Import costs included in the price)
It will be shipped from our warehouse between Friday, July 19 and Friday, July 26.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.

Synopsis "Learn Rstudio Ide: Quick, Effective, and Productive Data Science"

Discover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration. This book gives you a tour of RStudio and shows you how it helps you do exploratory data analysis; build data visualizations with ggplot; and create custom R packages and web-based interactive visualizations with Shiny. In addition, you will cover common data analysis tasks including importing data from diverse sources such as SAS files, CSV files, and JSON. You will map out the features in RStudio so that you will be able to customize RStudio to fit your own style of coding.Finally, you will see how to save a ton of time by adopting best practices and using packages to extend RStudio. Learn RStudio IDE is a quick, no-nonsense tutorial of RStudio that will give you a head start to develop the insights you need in your data science projects. What YouWill LearnQuickly, effectively, and productively use RStudio IDE for building data science applicationsInstall RStudio and program your first Hello World applicationAdopt the RStudio workflow Make your code reusable using RStudioUse RStudio and Shiny for data visualization projectsDebug your code with RStudio Import CSV, SPSS, SAS, JSON, and other dataWho This Book Is ForProgrammers who want to start doing data science, but don't know what tools to focus on to get up to speed quickly.

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