This lesson is UCSB Carpentry’s customized lesson of the Carpentries’ canonical lesson Data Analysis and Visualization in R for Ecologists. Main differences are in what data set is used, and to incorporate research data mgmt practices and data literacy points.
Prerequisites
No prior programming experience will be expected in this lesson.
| Setup | Download files required for the lesson | |
| 00:00 | 1. Before we Start |
How to find your way around RStudio?
How to interact with R? How to manage your environment? How to install packages? |
| 00:40 | 2. Introduction to R |
What data types are available in R?
What is an object? How can values be initially assigned to variables of different data types? What arithmetic and logical operators can be used? How can subsets be extracted from vectors? How does R treat missing values? How can we deal with missing values in R? |
| 01:20 | 3. Starting with Data |
What is a data.frame?
How can I read a complete csv file into R? How can I get basic summary information about my dataset? How are dates represented in R and how can I change the format? |
| 01:40 | 4. Manipulating, analyzing and exporting data with tidyverse |
What are dplyr and tidyr?
How can I select columns and filter rows? How can I use commands together How to export data? |
| 03:00 | 5. Data Visualisation with ggplot2 |
What are the components of a ggplot?
How do I create scatterplots, boxplots, histograms, and more? How can I change the aesthetics (ex. colour, transparency) of my plot? How can I create multiple plots at once? |
| 04:55 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.