A version of the Titanic survival data tailored for people analytics demonstrations and practice. While another package, 'titanic', reproduces the Kaggle competition files with minimal preprocessing, 'tidytitanic' combines the train and test datasets into the single dataset, 'passengers', for exploration and summary across all passengers. It also extracts personal identifiers—such as first names, last names, and titles from the raw 'name' field, enabling demographic analysis. The 'passengers' data does not cover the crew, but this package also provides the more bare-bones, crew-containing datasets 'tidy_titanic' and 'flat_titanic' based on the 'Titanic' data set from 'datasets' for further exploration. This human-centered data package is designed to support exploratory data analysis, feature engineering, and pedagogical use cases.

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.

Phylogenetic trees contain components such as nodes, edges,
    branches, and associated data. As the core data manipulation tool in the
    'ggtree' ecosystem, 'tidytree' provides tools for converting tree objects
    to tidy data frames and tidy interfaces for manipulating, analyzing, and
    visualizing tree data.