Gentleman's set of packages R for automation of business tasks

    Continuation of previous publications “DataScience Tools as an Alternative to Classical Integration of IT Systems” and
    “Ecosystem R as a Tool for Automating Business Tasks” .
    This article is an answer to the questions about R packages that are useful for implementing the described approaches. I consider it solely as reference information, and the starting point for the subsequent detailed study by those who are interested, since each package hides a huge space with its own philosophy and ideology, mathematics and development paths.


    As a rule, all packages (9109 pieces as of September 7, 2016) are in the CRAN repository . Those that, for one reason or another, have not yet been published to the repository, can be found on GitHub. So, a short list:


    Hadley Wickham Packages ( Hadleyverse )


    Details on packages can be found on the GitHub repository.


    • dplyr- extensions of grammatical constructions for data manipulation. As an introductory article, I would recommend "dplyr and pipes: the basics" , despite the fact that it was published in 2014
    • ggplot2- extensions of grammatical constructions for visualization. You can get an idea of ​​the possibilities in the book "Cookbook for R", chapter "Graphs"
    • scales - ggplot2 extension for scaling chart axes
    • ggmap - ggplot2 extension for working with cartography
    • lubridate- The "magic" of working with dates and times. The ideology is described in the article "Dates and Times Made Easy with lubridate"
    • readr - improved text data import to R
    • forcats - improved work with categorical variables
    • tibble - modern rethinking of the standard data.frame data structure
    • readxl - import excel data into R
    • purrr - extensions of grammatical constructions for functional programming
    • tidyr- Improved work with "dirty" source data. The ideology is described in the article "Tidy Data"
    • reshape2- Improved data transformation. The ideology is described in the article "Reshaping Data with the reshape Package"
    • stringr - improved work with text strings
    • curl - improved approach for working with data over HTTP
    • httr - a simplified approach to working with data protocol http
    • xml2 - improved XML support

    Programming and Data Elements


    • futile.logger - developed logging system
    • iterators - iterator support
    • foreach - improved support for cyclic designs
    • magrittr - grammar of work with data routing (pipe)
    • jsonlite - simplified JSON support
    • sp - support for working with geodata
    • data.table - extension of the standard data.frame data model for working with big data
    • broom- data conversion stat. functions in the tidy data format (see above). For details, see broom: An R Package for Converting Statistical Analysis Objects Into Tidy Data Frames
    • knitr- Preparation of documents of various formats (static and interactive, more detailed here ) from a single format R Markdown . In general, this is generally a separate world.

    Shiny and web forms


    • shiny - the framework itself
    • shinythemes - additional themes (shiny built on bootstrap)
    • highcharter - wrapper for highcharts
    • googleVis- Connector to Google Charts charts. More here and here
    • shinydashboard - sets of functions for building dashboards (a little outdated)
    • flexdashboard- A modern approach to the construction of dashboards. Details can be found here
    • shinyjs - optional JS interactive
    • htmlwidgets- support for html widgets, gallery here
    • plotly- interface to the interactive visualization system Plot.ly. Details can be found here
    • leaflet- wrapper for interactive cards JS leaflet. Details can be found here
    • DT- wrapper for interactive tables JS DataTable. Details can be found here
    • rbokeh- R interface to the Bokeh visualization library. Details can be found here

    Colors and Themes


    • RColorBrewer - a package for flexible work with colors
    • viridis- Virdis color palette. Details here
    • wesanderson - another palette
    • ggthemes- themes for ggplot2. Details here

    In my work, I still use 2-3 dozens of other packages, but they have a narrower specificity, or simply provide connections to external sources (ODBC, No-SQL, git, dropbox, etc.)


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