This post describes a project from rOpenSci unconf18. In the spirit of exploration and experimentation at our unconferences, projects are not necessarily finished products or in scope for rOpenSci packages.
Data == knowledge! Much of the data we use, whether it be from government repositories, social media, GitHub, or e-commerce sites comes from public-facing APIs. The quantity of data available is truly staggering, but munging JSON output into a format that is easily analyzable in R is an equally staggering undertaking. When JSON is turned into an R object, it usually becomes a deeply nested list riddled with missing values that is difficult to untangle into a tidy format. Moreover, every API presents its own challenges; code you’ve written to clean up data from GitHub isn’t necessarily going to work on Twitter data, as each API spews data out in its own unique, headache-inducing nested list structure. To ease and generalize this process, Amanda Dobbyn proposed an unconf18 project for a general API response tidier! Welcome roomba, our first stab at easing the process of tidying nested lists!
Read the full post here: https://ropensci.org/blog/2018/06/26/roomba/