3 - R and RStudio Basics

Objectives

  • Introduction to RStudio
  • Introduction to Core R Data Types
  • Introduction to R Control Flow
  • Overview of R Data Input and Output
  • R Data Wrangling: Transformation using Base R

Topics

  • Basic RStudio tour: console, editor, environment/build/git, help/packages
  • How to run RStudio: Application, Server, Cloud
  • Basic Data Types
    • Vector, Matrix, … of int, double, char, logical, …
    • Date, Datetime, factors, …
    • NA, NaN, NULL
    • If time: More on types, dispatch, classes, …
  • Compound Types
    • DataFrame
    • List
  • Not Covered
    • Closure
    • Environment
    • Language Object
  • Getting Data In is part of just about any analysis!
    • R excels at this
      • truly broad coverage of file formats
      • as well as ‘backends’ such as databases
      • or different web-based APIs
    • Our focus: read/write of csv data
    • Mention other formats: json, xml, …
    • Efficient R-specific storage: rds
    • Mention protobuf, msgpack, feather, fst, …
  • Data wrangling topics
    • data.frame manipulations
    • modifying by adding columns
    • subsetting and summaries
    • conditional operation by groups
    • merging (and its relationship to SQL joins)
    • functional programming approaches

Core Material

Lecture Slides

Lecture Videos

Extras

Additional Resources