Before we Start

  • Navigate round RStudio and create an Rproj file.
  • Use RStudio to write and run R programs.
  • Install packages using the Packages tab or the install.packages() command.

Introduction to R

  • Assign values to object using the assignment operator <-. Remove existing objects using the rm() function.
  • Add comments in R scripts using the # operator.
  • Define and use R functions and arguments.
  • Getting help with the ?, ?? and help() functions.
  • Define the following terms as they relate to R: object, vector, assign, call, function.
  • Create or add new objects to a vector using the c() function. Subset vectors using [].
  • Deal with missing data in vectors using the is.na(), na.omit(), and complete.cases() functions.

Starting with Data

  • Use read.csv to read tabular data in R.
  • Use factors to represent categorical data in R.

Data cleaning & transformation 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 mutate() to create new variables.

Data Visualisation with ggplot2

  • ggplot2 is a flexible and useful tool for creating plots in R.
  • The data set and coordinate system can be defined using the ggplot function.
  • Additional layers, including geoms, are added using the + operator.
  • Boxplots are useful for visualizing the distribution of a continuous variable.
  • Barplot are useful for visualizing categorical data.
  • Faceting allows you to generate multiple plots based on a categorical variable.