Titlebook: R 4 Data Science Quick Reference; A Pocket Guide to AP Thomas Mailund Book 2022Latest edition Thomas Mailund 2022 Programming Language.R 4.

尾巴

Working with Factors: ,,stake can easily go undiscovered. If you want your categories ordered, then the lexicographical order on strings will not always be the order you need. As an alternative to strings for categories is factors. In this chapter, we look at the functionality that the . package provides for creating and manipulating factors.

通情達(dá)理

Working with Models: , and ,, of R packages that support this is well beyond the scope of this book. The main concerns when choosing and fitting models is not the syntax, and this book is, after all, a syntax reference. We will look at two packages that aim at making a tidy interface to models.

HUMP

Myelin

https://doi.org/10.1007/978-1-4842-8780-4Programming Language; R 4; R; data science; tidyr; analytics; purrr; ggplot; modelr; markdown; knitr; shiny; tid

光亮

陳腐的人

苦笑

oblique

山崩

Functional Programming: ,,A pipeline-based approach to data processing necessitates a functional programming approach. After all, pipelines are compositions of functions, and loops and variable assignment do not work well with pipelines. You are not precluded from imperative programming, but you need to wrap it in functions.

Digest