Overview

"Data wrangling" refers to all the manipulations commonly needed to prepare tabular data for visualization or analysis. This may include subsetting the data, manipulating rows and columns, changing data types, going from long-to-wide formats and vice-versa, 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 workshop 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.

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).

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, but support will be limited.

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:

Click here to register.

 

Check back soon ----> Note - This event may reach capacity, after which a waiting list will be created.

 

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

For information regarding other upcoming IGIS workshops, please see IGIS training or contact Sean Hogan at sdhogan@ucanr.edu