Programming Techniques in R


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level


Overview/Description
There are a variety of frequently used programming techniques you can apply to get the most out of the R language. This course covers a variety of techniques in R in order to increase the quality and performance of your R programs.

Target Audience
Individuals with some R and data science experience working toward a wider degree of knowledge in using R for data science

Prerequisites
None

Expected Duration (hours)
1.5

Lesson Objectives

Programming Techniques in R

  • start the course
  • use the R substitute, quote, and deparse functions
  • use the R ast function
  • use the R str function
  • work with lazy evaluation in R
  • use the R eval function
  • use the R paste family of functions
  • create a reference class in R
  • use the R class function
  • define a binary operator
  • simulate a unary operator using binary operator syntax
  • translate a SQL query to R syntax
  • use the tableHTML library to create HTML tables in R
  • use the xtable library to export a LaTeX document
  • use list2env in R
  • write C++ inline in an R program
  • use Rcpp to call C++ from R
  • use cfunction in R to call inline C
  • use xtable to output a table in LaTeX format

    • Course Number:
    df_dsur_a03_it_enus

    Expertise Level
    Intermediate