Download Data from the European Social Survey on the Fly

Download data from the European Social Survey directly from their website < http://www.europeansocialsurvey.org/>. There are two families of functions that allow you to download and interactively check all countries and rounds available.

Manage Data from Cardiopulmonary Exercise Testing

Import, process, summarize and visualize raw data from metabolic carts. See Robergs, Dwyer, and Astorino (2010) for more details on data processing.

A Unifying API for Calling the 'Unity' '3D' Video Game Engine

Functions for the creation and manipulation of scenes and objects within the 'Unity' '3D' video game engine (< https://unity.com/>). Specific focuses include the creation and import of terrain data and 'GameObjects' as well as scene management.

Landscape Visualizations in R and 'Unity'

Functions for the retrieval, manipulation, and visualization of 'geospatial' data, with an aim towards producing '3D' landscape visualizations in the 'Unity' '3D' rendering engine. Functions are also provided for retrieving elevation data and base map tiles from the 'USGS' National Map < https://apps.nationalmap.gov/services/>.

Print Maps, Draw on Them, Scan Them Back in

Enables preparation of maps to be printed and drawn on. Modified maps can then be scanned back in, and hand-drawn marks converted to spatial objects.

Deterministic Categorization of Items Based on External Code Data

Fast categorization of items based on external code data identified by regular expressions. A typical use case considers patient with medically coded data, such as codes from the International Classification of Diseases ('ICD') or the Anatomic Therapeutic Chemical ('ATC') classification system. Functions of the package relies on a triad of objects: (1) case data with unit id:s and possible dates of interest; (2) external code data for corresponding units in (1) and with optional dates of interest and; (3) a classification scheme ('classcodes' object) with regular expressions to identify and categorize relevant codes from (2). It is easy to introduce new classification schemes ('classcodes' objects) or to use default schemes included in the package. Use cases includes patient categorization based on 'comorbidity indices' such as 'Charlson', 'Elixhauser', 'RxRisk V', or the 'comorbidity-polypharmacy' score (CPS), as well as adverse events after hip and knee replacement surgery.

A Test Environment for Database Requests

Testing and documenting code that communicates with remote databases can be painful. Although the interaction with R is usually relatively simple (e.g. data(frames) passed to and from a database), because they rely on a separate service and the data there, testing them can be difficult to set up, unsustainable in a continuous integration environment, or impossible without replicating an entire production cluster. This package addresses that by allowing you to make recordings from your database interactions and then play them back while testing (or in other contexts) all without needing to spin up or have access to the database your code would typically connect to.

Interface with the United Nations Comtrade API

Interface with and extract data from the United Nations 'Comtrade' API < https://comtradeplus.un.org/>. 'Comtrade' provides country level shipping data for a variety of commodities, these functions allow for easy API query and data returned as a tidy data frame.

Build Reproducible Analytical Pipelines with 'Nix'

Streamlines the creation of reproducible analytical pipelines using 'default.nix' expressions generated via the 'rix' package for reproducibility. Define derivations in 'R', 'Python' or 'Julia', chain them into a composition of pure functions and build the resulting pipeline using 'Nix' as the underlying end-to-end build tool. Functions to plot the pipeline as a directed acyclic graph are included, as well as functions to load and inspect intermediary results for interactive analysis. User experience heavily inspired by the 'targets' package.

Efficiently Retrieve and Process Satellite Imagery

Downloads spatial data from spatiotemporal asset catalogs ('STAC'), computes standard spectral indices from the Awesome Spectral Indices project (Montero et al. (2023) ) against raster data, and glues the outputs together into predictor bricks. Methods focus on interoperability with the broader spatial ecosystem; function arguments and outputs use classes from 'sf' and 'terra', and data downloading functions support complex 'CQL2' queries using 'rstac'.