Pulls together a collection of datasets from Miguel de Carvalho research articles and books. Including, for example:
    - de Carvalho (2012) <doi:10.1016/j.jspi.2011.08.016>;
    - de Carvalho et al (2012) <doi:10.1080/03610926.2012.709905>;
    - de Carvalho et al (2012) <doi:10.1016/j.econlet.2011.09.007>);
    - de Carvalho and Davison (2014) <doi:10.1080/01621459.2013.872651>;
    - de Carvalho and Rua (2017) <doi:10.1016/j.ijforecast.2015.09.004>;
    - de Carvalho et al (2023) <doi:10.1002/sta4.560>;
    - de Carvalho et al (2022) <doi:10.1007/s13253-021-00469-9>;
    - Palacios et al (2025) <doi:10.1214/24-BA1420>.

Summarizes data frames by calculating various statistics including central tendency, dispersion, shape, and normality diagnostics. Handles numeric, character, and factor columns with NA-aware computations.

Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.

Assists in finding the most suitable thread count for the various
             'data.table' routines that support parallel processing.

Create tree structures from hierarchical data, and traverse the
    tree in various orders. Aggregate, cumulate, print, plot, convert to and from
    data.frame and more. Useful for decision trees, machine learning, finance,
    conversion from and to JSON, and many other applications.

Validate dataset by columns and rows using convenient predicates inspired by 'assertr' package.
             Generate good looking HTML report or print console output to display in logs of your data processing pipeline.

Allows you to define rules which can be used to verify a given
    dataset.
    The package acts as a thin wrapper around more powerful data packages such
    as 'dplyr', 'data.table', 'arrow', and 'DBI' ('SQL'), which do the heavy lifting.

Provides access to Dataverse APIs <https://dataverse.org/> (versions 4-5),
    enabling data search, retrieval, and deposit. For Dataverse versions <= 3.0,
    use the archived 'dvn' package <https://cran.r-project.org/package=dvn>.