Introduction to R and RStudio

  • Use RStudio to write and run R programs.
  • R has the usual arithmetic operators.
  • Use <- to assign values to variables.
  • Use install.packages() to install packages (libraries).

Project Management With RStudio

  • Use RStudio to create and manage projects with consistent layout.
  • Treat raw data as read-only.
  • Treat generated output as disposable.

Data Structures

  • Use read.csv to read tabular data in R.
  • The basic data types in R are double, integer, complex, logical, and character.
  • Use factors to represent categories in R.

Exploring Data Frames

  • Use cbind() to add a new column to a data frame.
  • Use rbind() to add a new row to a data frame.
  • Remove rows from a data frame.
  • Use na.omit() to remove rows from a data frame with NA values.
  • Use levels() and as.character() to explore and manipulate factors.
  • Use str(), nrow(), ncol(), dim(), colnames(), rownames(), head(), and typeof() to understand the structure of a data frame.
  • Read in a csv file using read.csv().
  • Understand what length() of a data frame represents.

Subsetting Data

  • Indexing in R starts at 1, not 0.
  • Access individual values by location using [].
  • Access slices of data using [low:high].
  • Access arbitrary sets of data using [c(...)].
  • Use logical operations and logical vectors to access subsets of data.

Data frame Manipulation with dplyr

  • Use the dplyr package to manipulate dataframes.
  • Use select() to choose variables from a dataframe.
  • Use filter() to choose data based on values.
  • Use group_by() and summarize() to work with subsets of data.
  • Use count() and n() to obtain the number of observations in columns.
  • Use mutate() to create new variables.

Introduction to Visualization

  • Use ggplot2 to create plots.
  • Think about graphics in layers: aesthetics, geometry, etc.

Writing Data

  • Save plots using ggsave().
  • Use write.csv to save tabular data.