Читать книгу Computational Statistics in Data Science - Группа авторов - Страница 37

R is tailored to working with data and performing statistical analysis in a way that is more consistent and extensible than Python. The syntax for accessing data in lists and data frames is convenient with tab completion showing what elements are in an object. Creating documents, reports, notebooks, presentations, and web pages is possible through Rmarkdown/RStudio.

Through the use of the metapackage tidyverse or the library data.table, working with tabular data is direct, efficient, and intuitive. Because R is a scripted language, reproducible workflows are possible, and steps in the process of extracting and transforming data are easy to go back and modify without disrupting the analysis. While this is a virtue shared among all scripting languages, the nature of reproducible results and modular code saves time compared to a point‐and‐click interface like that of Excel or Minitab.