Extension of the 'tidyverse' for 'SpatRaster' and
    'SpatVector' objects of the 'terra' package. It includes also new
    'geom_' functions that provide a convenient way of visualizing 'terra'
    objects with 'ggplot2'.

Using tidy data principles can make many text mining tasks
    easier, more effective, and consistent with tools already in wide use.
    Much of the infrastructure needed for text mining with tidy data
    frames already exists in packages like 'dplyr', 'broom', 'tidyr', and
    'ggplot2'. In this package, we provide functions and supporting data
    sets to allow conversion of text to and from tidy formats, and to
    switch seamlessly between tidy tools and existing text mining
    packages.

A selection of various tools to extend a data analysis workflow based on the 'tidyverse' packages.
  This includes high-level data frame editing methods (in the style of 'mutate'/'mutate_at'), some methods in the style of
  'purrr' and 'forcats', 'lookup' methods for dict-like lists, a generic method for lumping a data frame by a given count,
  various low-level methods for special treatment of 'NA' values, 'python'-style tuple-assignment and 'truthy'/'falsy' checks,
  saving to PDF and PNG from a pipe and various small utilities.

Generate tables, listings, and graphs (TLG) using 'tidyverse.'
  Tables can be created functionally, using a standard TLG process, or by
  specifying table and column metadata to create generic analysis summaries.
  The 'envsetup' package can also be leveraged to create environments for table
  creation.

Read General Transit Feed Specification (GTFS) zipfiles into a list of R dataframes. Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. Please see the GTFS documentation here for more detail: <https://gtfs.org/>.

Functions for extracting tidy data from Bayesian treatment effect models, in particular BART, but extensions are possible. Functionality includes extracting tidy posterior summaries as in 'tidybayes' <https://github.com/mjskay/tidybayes>, estimating (average) treatment effects, common support calculations, and plotting useful summaries of these.