Iterating functions w/ nested data - case study: transform excel workbooks & worksheets to tidy data
Channel: John Little
Date: 2022-10-25

Iterating functions with nested data - case study: transform excel workbooks and worksheets to tidy data
code available at https://github.com/libjohn/workshop_rfun_iterate 
nest data frames: https://youtu.be/kZf11zbVpr0
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 final individual video (# 6) in the series presents iterating custom functions as a case study and ties all the previous tips and tricks together.  The challenge is importing select worksheet data found in multiple excel workbooks.  Each workbook contains over fifty worksheets.  I want to ingest only two of the worksheets, and I want to import the select data from each workbook into a single tidy data  frame.  This video episode is the final video in the #iterateFunctionsR series in which I demonstrate iterating via purrr::map over nested data.  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
0:40 - code repository
1:15 - coding begins

Materials available at https://github.com/libjohn/workshop_rfun_iterate 
More Rfun at https://Rfun.library.duke.edu/ 
Part of the CDVS Workshop Series: http://library.duke.edu/data/