Provides datasets used for analysis 
  and visualizations in the open-access Hello Data Science book.

A dummy package to demonstrate how to interface to a jar
        file that resides inside an R package.

Template R package with minimal setup to use Rust code in R without
    hacks or frameworks. Includes basic examples of importing cargo dependencies,
    spawning threads and passing numbers or strings from Rust to R. Cargo crates
    are automatically 'vendored' in the R source package to support offline
    installation. The GitHub repository for this package has more details and also 
    explains how to set up CI. This project was first presented at 'Erum2018' to 
    showcase R-Rust integration <https://jeroen.github.io/erum2018/>; for a real
    world use-case, see the 'gifski' package on 'CRAN'.

Contains miscellaneous functions useful for managing 'NetCDF' files (see <https://en.wikipedia.org/wiki/NetCDF>), get moon phase and time for sun rise and fall, tide level, analyse and reconstruct periodic time series of temperature with irregular sinusoidal pattern, show scales and wind rose in plot with change of color of text, Metropolis-Hastings algorithm for Bayesian MCMC analysis, plot graphs or boxplot with error bars, search files in disk by there names or their content, read the contents of all files from a folder at one time.

Tools for accessing various open data APIs in the Helsinki
    region in Finland. Current data sources include the Service Map API,
    Linked Events API, and Helsinki Region Infoshare statistics API.

Import and classify canopy fish-eye images, estimate angular gap fraction and derive canopy attributes like leaf area index and openness.  Additional information is provided in the study by Chianucci F., Macek M. (2023) <doi:10.1016/j.agrformet.2023.109470>.

A visualization suite primarily designed for single-cell
    RNA-sequencing data analysis applications, but adaptable to
    other purposes as well. It introduces novel plots to represent two-variable
    and frequency data and optimizes some commonly used plotting options
    (e.g., correlation, network, density and alluvial plots) for ease of usage
    and flexibility.