Reference

Data Types

Vectors, factors, data frames, tibbles, and other structures.

1. data.frame()

   Create a data frame — a tabular data structure with rows and columns of potentially different types.

   data.frame(..., row.names = NULL, check.rows = FALSE, check.names = TRUE, stringsAsFactors = FALSE)
2. environment()

   Environments are key-value stores that form the backbone of R's scoping system, storing objects and managing variable lookup through parent chains.

3. factor()

   Create categorical variables with discrete levels in R. Factors store nominal or ordinal data efficiently and are essential for statistical modeling.

   factor(x = character(), levels, labels = levels, exclude = NA, ordered = FALSE, nmax = NA)
4. list()

   Lists are ordered collections of objects in R, allowing you to store heterogeneous data of different types and lengths in a single structure.

5. matrix()

   Create and manipulate matrices in R — two-dimensional arrays of atomic vectors.

   matrix(data, nrow, ncol, byrow, dimnames)
6. tibble::tibble()

   A tibble is a modern reimagining of the data.frame that provides better printing, subsetting, and type consistency for data analysis in R.

   tibble(..., .rows = NULL, .name_repair = c("unique", "universal", "minimal", "check_unique", "check_unique", "check_names"))