Provides a function tidy_source() to format R source code. Spaces
    and indent will be added to the code automatically, and comments will be
    preserved under certain conditions, so that R code will be more
    human-readable and tidy. There is also a Shiny app as a user interface in
    this package (see tidy_app()).

Provides functions to create formattable vectors and data frames.
    'Formattable' vectors are printed with text formatting, and formattable
    data frames are printed with multiple types of formatting in HTML
    to improve the readability of data presented in tabular form rendered in
    web pages.

We provide a framework for rendering complex tables to ASCII,
    and a set of formatters for transforming values or sets of values into
    ASCII-ready display strings.

'Shiny' apps can often make use of the same key elements, this package provides modules for common tasks (data upload, wrangling data, figure generation and saving the app state), and also a framework for developing. These modules can react and interact as well as generate code to create reproducible analyses.

Provides analytics directly from 'R'. It requires:
    'FormShare App': <https://github.com/qlands/FormShare >= 2.22.0> .
    Analytics plugin: <https://github.com/qlands/formshare_analytics_plugin> .
    Remote SQL plugin: <https://github.com/qlands/formshare_sql_plugin> .

Infrastructure for extended formulas with multiple parts on the
             right-hand side and/or multiple responses on the left-hand side
	     (see <doi:10.18637/jss.v034.i01>).

These utilities facilitate the programmatic manipulations of
    formulas, expressions, calls, assignments and other R language objects. 
    These objects all share the same structure: a left-hand side, operator and 
    right-hand side. This packages provides methods for accessing and 
    modifying this structures as well as extracting and replacing names and 
    symbols from these objects.

Many statistical models and analyses in R are implemented through formula objects. The formulaic package creates a unified approach for programmatically and dynamically generating formula objects. Users may specify the outcome and inputs of a model directly, search for variables to include based upon naming patterns, incorporate interactions, and identify variables to exclude. A wide range of quality checks are implemented to identify issues such as misspecified variables, duplication, a lack of contrast in the inputs, and a large number of levels in categorical data.  Variables that do not meet these quality checks can be automatically excluded from the model.  These issues are documented and reported in a manner that provides greater accountability and useful information to guide an investigation of the data.