Data Wrangling in R Parts I & II

Online workshop series: October 10 & 17, 2025. 1:00 - 3:00 pm

Overview

Data Wrangling in R

"Data wrangling" refers to all the manipulations commonly needed to prepare tabular data for visualization or analysis. This could include subsetting the data, manipulating rows and columns, changing data types, going from long-to-wide formats or vice-versa, parsing text, dealing with missing values, joining, stacking, or splitting tables, and aggregating rows for higher level units of analysis.

In the real-world, data wrangling is frequently a pain point for researchers. It is often said that up to 80% of the time spent on data analysis is spent preparing the data, the so-called 80/20 rule.

R is an outstanding platform for wrangling data. This two-part workshop series will cover data wrangling methods using the tidyverse family of R packages, including dplyr, tidyr, lubridate, stringr, ggplot, and others. The topics in this workshop are part of the foundation for doing data analysis in R, including spatial data.

Agenda

Part 1. Friday October 10. 1:00 - 3:00p

  • Introduction
  • Tidy data
  • Planning your strategy
  • Better ways to import data
  • Understanding your data
  • Subsetting rows and columns
  • Column manipulations
  • Joining and stacking tables

Part 2. Friday October 17. 1:00 - 3:00p

  • Dealing with missing values
  • Reshaping data
  • Time series data
  • Grouping and summarizing rows

Instructor

Audience

  • UC Cooperative Extension
  • UC students & faculty
  • AIFS affiliates (including Davis, Berkeley, Cornell, U. Illinois, & USDA)

Cost

This is a free workshop

Requirements

This workshop presumes some experience with R (at least enough to run prepared Notebooks in RStudio). See also the video Fundamentals of Coding with R that reviews some of the basic concepts, terminology, and programming techniques that we'll be using in the workshop.

This hands-on exercises (recommended but not required) will use RStudio running in a virtual machine from Posit Cloud (i.e., in a browser). Participants wishing to complete the hands-on exercises will therefore need a free account on Posit Cloud. Experienced R users are welcome to run the exercises in RStudio Desktop or Positron, but support will be limited.


Fundamentals of Coding with R

Parts of the workshop will require you to follow along as the instructor demonstrates code to solve a problem. It is therefore highly recommended that you have a computer with two monitors, so you can view the instructor's screen on one monitor, and work in RStudio in the other. Participants who only have a small laptop with no external monitor may find it challenging to complete the hands-on exercises, and may just want to watch.

Registration

Registration is closed. The recordings are available below and on the IGIS YouTube Channel.

Recordings

 

This course content is the result of a collaborative effort between UC ANR IGIS Statewide Program, and the USDA-NIFA/NSF AI Institute for Next Generation Food Systems (AIFS).

IGIS logo
AIFS logo

 

Source URL: https://ucanr.edu/program/informatics-and-gis-program/data-wrangling-f25