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Course website for CSSS508: Introduction to R for Social Scientists

University of Washington

Charles Lanfear
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Function Reference

This page serves as a quick reference for key functions taught in each lecture of the course. Under each numbered lecture, you can find a list of the key functions covered in that lecture with a short description. For more information, use R’s built in help (?) or browse the relevant lecture.

Functions listed like dplyr::filter() indicate that the function is named filter() and it comes from the dplyr package. You can actually call a function this way from a package without loading it using library(). This is good when you want to use a function that has the same name as one you’ve already loaded (e.g. MASS::select() when you already have dplyr loaded).

Lectures

  1. RStudio and Markdown
    • <-: The assignment operator, for creating objects.
    • $: The extract operator, for extracting or replacing parts of objects.
    • c(): Combine elements into a vector.
    • data(): Load data objects from R packages.
    • head(): Displays the first few elements of an object.
    • hist(): Draws a histogram of a numeric vector.
    • pairs(): Draws pairwise scatterplots of a dataframe.
    • install.packages(): Install a package when given a package name as a string (that is, a name in quotes).
    • library(): Loads a package when given the package name (doesn’t need to be in quotes).
    • pander::pander(): Creates a table in an R Markdown doc out of an object.
    • plot(): Draws a default plot (scatterplot for two variables).
    • str(): Displays the structure of an object such as data types and dimensions.
    • summary(): Summarize an object. This function does different things for different types of objects!
    • View(): Opens up a data viewer window.
  2. Visualizing Data
    • getwd(): Returns the path of the current working directory as a text string.
    • setwd(): Sets a new working directory when given a path as a text string.
    • save(): Writes an R object to disk as a .RData or .Rds file.
    • load(): Opens .RData and .Rds files.
    • dplyr::filter(): Subsets data to specific rows based on logical expressions.
    • ggplot2::ggplot(): Initiates a ggplot2 plot.
    • ggplot2::aes(): Sets aesthetics inside a ggplot2 call.
    • ggplot2::geom_point(): Draws a points layer (scatterplot).
    • ggplot2::geom_line(): Draws a lines layer (line plot).
    • ggplot2::facet_wrap(): Splits a plot into a series of plots by levels of a factor.
    • ggplot2::facet_grid(): Splits a plot into a grid of plots by levels of multiple factors.
    • ggplot2::theme(): A function with many arguments for setting the appearance of a ggplot2 plot.
    • ggplot2::ggsave(): Saves a plot as a PDF or image file.
  3. Manipulating and Summarizing Data
  4. Understanding R Data Structures
  5. Importing, Exporting, Cleaning Data
  6. Using Loops
  7. Writing Functions
  8. Working with Text Data
  9. Working with Geographical Data
  10. Reproducibility and Best Practices
  11. Working with Model Results
  12. Working with Social Media Data