R is a software environment for statistical computing and graphics. R is commonly used for Data Analysis, Statistical Computing, Machine Learning algorithms & scientific research.
This competency area includes fundamentals of the R programming language, understanding Data Frames, Packages, and Data Reshaping, using Data interfaces, among others.
Explore the basics - Fundamentals of R programming language (strings, vectors, lists, factors, etc).
Understanding Data Frames, Packages, and Data Reshaping - Data frames are tables or a two-dimensional array-like structure in which each column contains values of one variable and each row contains one set of values from each column. Understand the usage of storing data tables - a list of vectors of equal length, packages, and reshaping data in R.
Using Data interfaces (CSV, JSON, XML, and other files) - R can read and write into various file formats like CSV, Excel, XML, etc. R allows us to read data from files stored outside the R environment. It supports writing data into files that can be stored. Explore the usage of data interfaces.
Statistical analysis tool - Learn and use Statistical concepts in R (Regression, Distribution, etc).