R crash-course materials

Course scheme

Day 1

1.1. R-basics

  • Course presentation;
  • How to prepare a working directory (rules of good data science);
  • File names and type of data files;
  • The R studio IDE;
  • Reading and Writing Data;
  • Scripting;
  • Packages (and GitHub);
  • Ask for help;

1.2. Workflow basics

  • Using the console
  • Practice
  • Using the scripts
  • Practice

Day 2

2. Data wrangling

  • Welcome to the Tidyverse;
  • filter() #Pick observations by their values
  • arrange() #Reorder the rows
  • select() #Pick variables by their names
  • mutate() #Create new variables with functions of existing variables
  • summarise() #Collapse many values down to a single summary
  • group_by() #which changes the scope of each function from the entire dataset to a group
  • saving data

2.1. Fishing effort exercise 1

3. Data visualization

  • Welcome to ggplot2
  • Exploratory data analysis
  • Data visualization

3.1. Fishing effort exercise 2

Day 3

4. R-functions and iterations

  • R-functions and shortcuts;
  • The purrr package;

5. Knitting


Weblinks

Basics

Advanced

Visualization

Documents creation

Miscellaneous tutorials

Written on February 17, 2021