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Titlebook: Learn RStudio IDE; Quick, Effective, an Matthew Campbell Book 2019 Matthew Campbell 2019 RStudio.R.data science.tool.IDE.Integrated.program

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發(fā)表于 2025-3-21 18:35:47 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Learn RStudio IDE
副標(biāo)題Quick, Effective, an
編輯Matthew Campbell
視頻videohttp://file.papertrans.cn/583/582626/582626.mp4
概述An accelerated tutorial on learning to use RStudio IDE.Covers the leading tool for R programming quickly, effectively and productively.Shows the power of RStudio for data visualization and other data
圖書封面Titlebook: Learn RStudio IDE; Quick, Effective, an Matthew Campbell Book 2019 Matthew Campbell 2019 RStudio.R.data science.tool.IDE.Integrated.program
描述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 Learn.Quickly, effectively, and productively use RStudio IDE for building data science applications.Install RStudio and program your first Hello World application.Adopt the RStudio workflow?.Make your code reusable using RStudio.Use RStudio and Shiny for data visualization proj
出版日期Book 2019
關(guān)鍵詞RStudio; R; data science; tool; IDE; Integrated; programming; big data; analytics; statistics; analysis; code
版次1
doihttps://doi.org/10.1007/978-1-4842-4511-8
isbn_softcover978-1-4842-4510-1
isbn_ebook978-1-4842-4511-8
copyrightMatthew Campbell 2019
The information of publication is updating

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RStudio Projects,What we have learned so far adds a great deal of integration to R programming. But we are missing a way to bring all of that together in a format that we can reuse. This is where RStudio projects come into play.
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R Markdown,You use R Markdown to create reports that incorporate the features discussed in the previous chapters. R Markdown leverages freely available open source technology like HTML, CSS, and Markdown to create rich reports in a variety of formats.
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Data Visualization, to highlight major graphic tools that will inform most of your daily work. Of course, in the R ecosystem we have hundreds of additional libraries and specialized packages that may be used for visualization.
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發(fā)表于 2025-3-23 06:34:55 | 只看該作者
Shiny R Dashboards,at these types of static tools can provide. For instance, you may need to ask users to supply parameters that will be used in an analysis, connect to a backend database, or execute new R scripts as the user explores your analysis.
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