It resonated with me when the author mentions that the book’s goal is to help produce readable, reusable, reproducible work flows using a variety of R packages and functions.
I found the “Three Universes” interesting as it refers to xts, tidyverse, and tidyquant. It was fascinating to learn that xts includes a ‘column number zero’ which are the dates as part of the time series, the observations and times at which they occurred. I learned that the dplyr package serves the common purpose and use of data wrangling, transformation, and organizing. I also did not know that a data frame is called a “tibble”.
I now understand that the “tidy” part of tidyverse relates to tidy data; (1) each variable has its own column, (2) each observation is a row, and (3) each value is a cell.
Additionally, I learned that tidyquant consists of the tidyquant, timetk, and tibbletime packages which take some of the best features of xts, PerformanceAnalytics and the tidyverse and enables them to work together efficiently.
Lastly, I learned about Shiny applications which are all performance metrics that I have learned in my finance classes and I was happy to see that I’ll be able to apply them without the tedious task of doing them manually.