An end-to-end framework that enables users to implement various descriptive studies for a given set of target and outcome cohorts for data mapped to the Observational Medical Outcomes Partnership Common Data Model.

Creates a new chars class which looks like a string but is actually 
    a vector of individual characters, making 'strings' iterable. This class 
    enables vector operations on 'strings' such as reverse, sort, head, and set 
    operations.

Provides a standardized and reproducible framework for characterizing
    and classifying discrete color classes from digital images of biological organisms.
    The package automatically determines the presence or absence of 10 human-visible
    color categories (black, blue, brown, green, grey, orange, purple, red, white, yellow)
    using a biologically-inspired Color Look-Up Table (CLUT) that partitions HSV color space.
    Supports both fully automated and semi-automated (interactive) workflows with complete
    provenance tracking for reproducibility. Pre-processes images using the 'recolorize'
    package (Weller et al. 2024 <doi:10.1111/ele.14378>) for spatial-color binning, and
    integrates with 'pavo' (Maia et al. 2019 <doi:10.1111/2041-210X.13174>) for color
    pattern geometry statistics. Designed for high-throughput analysis and seamless
    integration with downstream evolutionary analyses.

Make fake data that looks realistic, supporting addresses, 
    person names, dates,
    times, colors, coordinates, currencies, digital object identifiers
    ('DOIs'), jobs, phone numbers, 'DNA' sequences, doubles and integers
    from distributions and within a range.

For those wishing to interact with the 'Charles Schwab Individual Trader API' (<https://developer.schwab.com/products/trader-api--individual>) with R in a simplified manner, this package offers wrapper functions around authentication and the available API calls to streamline the process.

Provides a very simple syntax for the user to generate custom plot(s) without having to remember complicated 'ggplot2' syntax. The 'chartql' package uses 'ggplot2' and manages all the syntax complexities internally. As an example, to generate a bar chart of company sales faceted by product category further faceted by season of the year, we simply write: "CHART bar X category, season Y sales".