A thin wrapper around the 'Datorama' API.
    Ideal for analyzing marketing data from <https://datorama.com>.

Provee una versión traducida de los siguientes
    conjuntos de datos: 'airlines', 'airports', 'AwardsManagers',
    'babynames', 'Batting', 'credit_data', 'diamonds', 'faithful', 'fueleconomy',
    'Fielding', 'flights', 'gapminder', 'gss_cat', 'iris', 'Managers',
    'mpg', 'mtcars', 'atmos', 'palmerpenguins', 'People, 'Pitching', 'planes',
    'presidential', 'table1', 'table2', 'table3', 'table4a', 'table4b',
    'table5', 'vehicles', 'weather', 'who'.  English: It provides a
    Spanish translated version of the datasets listed above.

Converting date ranges into dating 'steps' eases the
    visualization of changes in e.g. pottery consumption, style and other
    variables over time. This package provides tools to process and
    prepare data for visualization and employs the concept of aoristic
    analysis.

Interface with the 'Dat' p2p network protocol <https://datproject.org>. Clone archives from the network, share your own files, and install packages from the network.

Profiles datasets (collecting statistics and informative summaries 
    about that data) on data frames and 'ODBC' tables: maximum, minimum, mean, standard deviation, nulls,
    distinct values, data patterns, data/format frequencies.

Phone numbers are often represented as strings because there
    is no obvious and suitable native representation for them.  This leads
    to high memory use and a lack of standard representation.  The package
    provides integer representation of Australian phone numbers with optional
    raw vector calling code. The package name is an extension of 'au' and 'ph'.

Provides several datasets used throughout the book 
    "Sampling and Data Analysis Using R: Theory and Practice" by 
    Islam (2025, ISBN:978-984-35-8644-5). 
    The datasets support teaching and learning of statistical concepts 
    such as sampling methods, descriptive analysis, estimation and 
    basic data handling. These curated data objects allow instructors, 
    students and researchers to reproduce examples, practice data 
    manipulation and perform hands-on analysis using R.