Curate R Data

This and other lessons assume users already have some experience with R, for instance through a Data Carpentry workshop. See References for useful introductory and advanced material.

Learning Objectives

After completing this section, an individual will be able to curate data in R.

• read, manipulate and display data summaries in concise tables
• work with data frames using tidyverse tools
• use character string operations to clean data
• create functions to collapse repeated steps into one-line “verbs”
• save cleaned up data tables in external files

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Read, Manipulate and Display Data

• Working with data tables in R
• Examples using for and apply

Work with Data Frames using Tidyverse tools

• sub_lesson recasting data.frame examples
• Tidyverse split-apply-combine example
• purrr example using map & transpose
• more tidyverse on portal_mammals data

Character String Operations to Clean Cata

• characters and strings
• regular expressions (regex)

Create Functions to Collapse Steps

examples of functions

Save Cleaned up Data to External Files

read and write files

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Condensed Format

Learning Objectives: After completing this material, an individual will be able to curate data in R.

• read, manipulate and display data summaries in concise tables
• work with data frames using tidyverse tools
• write cleaned up data table out in CSV format

file	contents
data_tables	Working with data tables in R
applyExample	Examples using for and apply
intro_dplyr	sub_lesson recasting data.frame examples
tidyverse	Tidyverse split-apply-combine example
purrr	another example using map & transpose
species	dplyr, tidyr and purrr ideas with portal_mammals data
string	characters and strings
regex	regular expressions
file	read and write files