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The concept of "tidy data" offers a powerful framework for structuring datato ease manipulation, modeling and visualization. However, most R functions,both those built-in and those found in third-party packages, produce outputthat is not tidy, and that is therefore difficult to reshape, recombine, andotherwise manipulate. Here I introduce the broom package, which turns theoutput of model objects into tidy data frames that are suited to furtheranalysis, manipulation, and visualization with input-tidy tools. Broom definesthe "tidy", "augment" and "glance" generics, which arrange a model into threelevels of tidy output respectively: the component level, the observation level,and the model level. I provide examples to demonstrate how these generics workwith tidy tools to allow analysis and modeling of data that is divided intosubsets, to recombine results from bootstrap replicates, and to performsimulations that investigate the effect of varying input parameters.

broom: An R Package for Converting Statistical Analysis Objects Into Tidy Data Frames