Workshop on R Data Literacy

The lecture content from a 2-day workshop I delivered for individuals working at the Virginia Department of Environmental Quality tht focused on building a foundation of data analysis using R.

Venti Views Image from Unspalsh

Workshop Logistics

When: March 7-8, 2022
Where: 1111 East Main Street, Richmond Virginia 37.5367, -77.4350
Impetus: Build internal capacity at for using R as an analysis platform to increase efficiency of data management.
Instructor: Rodney Dyer
Data Sets:

Introduction to R and RStudio

Learning Objectives:
- Learning about the R environment,
- Understand differences between coding to the Console versus making scripts,
- Use a Project to organize code, data, analyses, & narratives,
- Personalize the RStudio GUI for success.

Character Data and Basic Function Usage

Learning Objectives:
- Learn about basic function structure,
- Explore the built-in help system,
- Practice operations using the fundamental data type character,
- Manipulate data in vector formats,
- Perform textual analyses using the stringr library.

stringr Cheatsheet

Numeric Data and Data Frames

Learning Objectives:
- Explore numeric data and mathematical operations.
- Create and manipulate data within data.frame objects.

Basic Data Manipulation - Tidyverse

Learning Objectives:
- Understand data manipulation verbs,
- Pipe data through several modifier functions to derive inferences,
- Filter and select subsets of a larger data set,
- Group and summarize measurements to derive summary parameters

Data Wrangling Cheatsheet

Non-Character Character Data

Learning Objectives:
- Apply the mutate operator to create derived data columns.
- Demonstrate the use of unordered and ordered factor data.
- Convert textual representations of dates and times into date objects.
- Derive temporal inferences from date objects

forcats Cheatsheet

lubridate Cheatsheet


Visualizing Data - Basic & GGPlot

Learning Objectives:
- Learn about joins to merge data from two or more data.frames. - Develop your first function for consistent data formatting prior to visualization.
- Understand and implement basic plotting routines provided in R::graphics
- Convert raw data into high-quality graphical output using a variety of ggplot2 routines.

visualization Cheatsheet

Interactive Mapping

Learning Objectives:
- Understand how to create a viable map display.
- Apply differential tile providers to an interactive map.
- Create markers on a map representing data found within the data frame.

leaflet Cheatsheet


Learning Objectives:
- Understand basic markup to represent common textual components.
- Insert graphical output (figures, maps, etc) into a markdown document.
- Inject components of statistical inferences into the text of a markdown document.

markdown Cheatsheet