The world of time series and financial analysis in R has diverged in terms of the tooling used in day to day work. xts and quantmod currently reign supreme with a powerful arsenal of tools available to analyze time-based data. However, this data often requires manipulation and visualization using the tools of the Tidyverse. Moreover, the grouped analysis capabilities of dplyr are powerful features that are not available to the xts world. To reconcile these differences, we propose a “time-aware tibble” that builds off of tibble and the Tidyverse as a whole, but with a knowledge of the column to be used as the index for time-based subsetting, rolling analysis, period-based summaries, and endless other applications. The tibbletime package is the first step towards this. Eventually, this package will serve as the foundational data structure for a number of other packages focused on performance analysis, portfolio construction, and forecasting. Currently, combined with the tidyquant package, the two allow for a more seamless transition between xts and the Tidyverse, but the eventual goal is to perform time series analysis completely in the Tidyverse.
Davis is a software engineer at RStudio working on modeling in the tidyverse. He maintains a number of R packages, including furrr for parallelizing purrr code. Mostly, he enjoys creating tools that are intuitive to use and make the lives of others more productive. Outside of R, his hobbies include reading and hiking.
