INNTEAMUTILS

Introduction

The innteamUtils offers a collection of functions, themes and datasets to enhance productivity on daily coding and reproducibility throughout the organization.

It is light on dependencies (and will be in the future), for better performance and ease of maintenance. It also, as part of the same philosophy, adopts “fully integrated end-to-end platform” production pipeline thanks to the following packages and frameworks:

• General Framework: data.table is completely written in base R and is blazing fast.
• Visualization:
  • ggplot2 for static graphics and production-ready plots (the only tidyverse package).
  • plotly for interactive graphics as is well-adopted with rmarkdown and shiny.
  • highcharter for advanced interactive graphics (coming soon).
  • reactable: for interactive and static production-ready tables.
  • reactablefmtr: for interactive tables and infografics (Coming soon).
  • bslib for Shiny apps productiong-grade UI features..
• Reporting:
  • pagedown: unique framework for PDF + HTML documentation. Fast rendering thanks to chrome browsing instead of LaTeX.
  • In a near future we plan to migrate .Rmd templates to Quarto as soon as it is a mature technology.
• Machine Learning: mlr3verse which seeks a production-ready approach like python for R and is fully built upon data.table and uses R6 objects (for stability and speed).

License and Permissions

No license, for Internal Use only. It is strictly forbidden to replicate or distribute the code outside the organization.

Installation

The development version can be installed from GitHub with:

# install.packages("remotes")
remotes::install_github("aba-innovationteam/innteamUtils", build_vignettes = TRUE)

Stable versions contacting by email. The latest stable version is 1.0.0.

Elements

The main components present in the latest stable version are:

• rmarkdown Report Templates: - HTML Doc for quick and light documents in HTML format.
• Paged Report for professional looking PDF and HTML reports (lightweight and fast rendering).
• RStudio Project Templates: standardized templates for reproducibility and optimal workflow by specific task.
• Shiny Theme Templates: standardized CSS and JS structures for production-grade Apps.
• ggplot2 theme: calling plot(...) + theme_innteam()
• reactable theme: calling reactable(..., theme = react_format)
• plotly theme: calling df %>% plot_ly(...) %>% plotly_innteam()
• Datasets: tables useful for common issues regarding data cleaning activities (e.g. codice_ateco or decodifica_comuni).
• Operators: expansions operators to improve readability of code. (%notin%, %contains%).

It also possible and probably more convenient to set the themes in the session options to avoid verbose code and enable easier reproducibility, especially on documents:

ggplot2::theme_set(theme_innteam())
options(reactable.theme = react_format)

Next elements under construction are ad-hoc functions in data.table for data wrangling and manipulation and mlr3 specific procedures.

Main Functions

• clean_names: transforms into snake_case column names: Nome.1 = nome_1.
• rounder: helper function to round vectors to the desired closest number: rounder(93, 5, 'up") = 95.
• diff_years: calculates the distance in years between to dates.
• is.error, is.interger64: helper function that evaluates to boolean.

Vignettes

(Comin soon) Each functionality and element information and usage can be found in their respective vignette.

• vignette("Datasets") explore Innovation Team Standard R Theming kit.
• vignette("theme_innteam") Datasets for Daily Activities.

To access them you may also type vignette("innteamUtils") in RStudio for a quick-start guide.

Claims and Issues

For any doubt, idea or issue please contact us via email to: [email protected]