1 Getting started

Slides

  • Introduction to R and RStudio environment
  • Setting up Projects
  • Libraries and packages
  • File naming conventions

Packages

here

2 Exploratory Data Analysis

Slides

  • Reading and writing data
  • Visualizing distributions
  • Patterns in data
  • Missing values

Packages

tidyverse

3 Data Wrangling

Slides

  • Introduction to tidyverse
  • Data transformation
  • Cleaning data for analysis
  • Summarizing datasets

Packages

tidyverse
gapminder

4 Data Visualization

Slides

  • Introduction to ggplot package
  • Theory of grammar of graphics
  • Customizable and publication ready plots
  • Common problems with plotting

Packages

tidyverse

5 Relational Data

Slides

  • Working with multiple datasets
  • Different kinds of data joins
  • Join problems and pitfalls
  • Set operations with datasets

Packages

tidyverse

6 Date and Time

Slides

  • Creating date/times
  • Introduction lubridate package
  • Manipulating timestamps
  • Arithmetic with date-time data

7 Iterations & Functions

Slides

  • Introduction to functions
  • for loops
  • Introduction to purrr package
  • Best practices for efficient code

Packages

tidyverse
gapminder

8 Statistics & Modelling

Slides

Packages (new)

gtsummary
flextable
broom

  • Summary statistics
  • Linear Regression
  • Working with multiple models
  • Brief introduction to Machine Learning

9 Spatial Analysis

Slides

  • Introduction to coordinate systems
  • Introduction to sf and raster packages
  • Making maps in R
  • Spatial data analysis in R

10 Reporting with RMarkdown

Slides

  • Creating reproducible reports
  • Themes and formatting
  • Automated reports using parameters
  • Introduction to Xaringan package