Separate multivalue fields

Separate multivalue fields code available at https://github.com/libjohn/workshop_rfun_iterate regex video - https://youtu.be/UCrYhpGT_B0 pivot_longer / pivot_wider - https://youtu.be/sspFC2m8fog full video series -- playlist -- https://www.youtube.com/watch?v=PrUnbYlC1kY&list=PLIUcX1JrVUNWW7RgPh9ysmJM3mBpIAlYG Using the case-study of data cleaning, this modular video series will demonstrate iteration with purrr::map() and custom functions while also showing several Tidyverse tips and tricks. This individual video (# 1-F) in the series presents the multivalue fields and how to easily separate those fields into taller or wider dataframes. In the Tidyverse, tall data is often easier to code for iteration. Each #IterateFunctionsR video will become progressively more fluent, using building-blocks to present intermediate data manipulation techniques in R and the Tidyverse. By the end of the series you'll learn how to use the purrr package, a very convenient package in support of iterating over list-columns and nested data frames. purrr::map() iteration is often more convenient and efficient than a For-loop. You'll also learn how to compose custom functions in R. since R is a functional programming language, composing your own custom functions can increase your fluency as an R coder. Contents: 0:00 - introduction 0:56 - separate_rows() - transform data to tall data format, easier for iteration 1:19 - multivalue fields 2:53 - separate() - transform data to a wider format Materials available at https://github.com/libjohn/workshop_rfun_iterate stringr cheatsheet - https://stringr..tidyverse.org More Rfun at https://Rfun.library.duke.edu/ Part of the CDVS Workshop Series: http://library.duke.edu/data/