Export Data Frames to Excel 'xlsx' Format

Zero-dependency data frame to xlsx exporter based on 'libxlsxwriter' < https://libxlsxwriter.github.io>. Fast and no Java or Excel required.

Track R Package Downloads from RStudio's CRAN Mirror

Allows to get and cache R package download log files from RStudio's CRAN mirror for analyzing package usage.

Enhance Reproducibility of R Code

A collection of high-level, machine- and OS-independent tools for making reproducible and reusable content in R. The two workhorse functions are 'Cache()' and 'prepInputs()'. 'Cache()' allows for nested caching, is robust to environments and objects with environments (like functions), and deals with some classes of file-backed R objects e.g., from 'terra' and 'raster' packages. Both functions have been developed to be foundational components of data retrieval and processing in continuous workflow situations. In both functions, efforts are made to make the first and subsequent calls of functions have the same result, but faster at subsequent times by way of checksums and digesting. Several features are still under development, including cloud storage of cached objects allowing for sharing between users. Several advanced options are available, see '?reproducibleOptions()'.

Reproducible Data Embedding

Allows caching of raw data directly in R code. This allows R scripts and R Notebooks to be shared and re-run on a machine without access to the original data. Cached data is encoded into an ASCII string that can be pasted into R code. When the code is run, the data is automatically loaded from the cached version if the original data file is unavailable. Works best for small datasets (a few hundred observations).

Download Sea Ice Concentration Data from the NSIDC Climate Data Record

Programmatic access to NSIDC's sea ice concentration CDR < https://nsidc.org/data/g02202> via ERDAPP server and Sea Ice index < https://nsidc.org/data/g02135>. Supports caching results and optional fixes for some inconsistencies of the raw files.

Nonlinear Root Finding, Equilibrium and Steady-State Analysis of Ordinary Differential Equations

Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). Includes routines that: (1) generate gradient and jacobian matrices (full and banded), (2) find roots of non-linear equations by the 'Newton-Raphson' method, (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the 'Newton-Raphson' method, or by dynamically running, (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations by numerical differencing (using the method-of-lines approach). Includes fortran code.

Create, Stow, and Read Data Packages

Data frame, tibble, or tbl objects are converted to data package objects using specific metadata labels (name, version, title, homepage, description). A data package object ('dpkg') can be written to disk as a 'parquet' file or released to a 'GitHub' repository. Data package objects can be read into R from online repositories and downloaded files are cached locally across R sessions.

'Memoisation' of Functions

Cache the results of a function so that when you call it again with the same arguments it returns the previously computed value.

SEC 'EDGAR' APIs

Simple and efficient access to the SEC's 'EDGAR' APIs < https://www.sec.gov/search-filings> for querying and retrieving filings. The 'secfile' package abstracts the complexities of interacting with SEC EDGAR APIs, such as session management, user agent declaration, rate limiting, index parsing, pagination of filing metadata, URL construction, document caching, and inline XBRL parsing. This abstraction allows users to focus on retrieving data rather than managing API details. Use cases include retrieving filings across a range of workflows such as indexes, tenures, submissions, and facts. The package supports flexible query capabilities, including customizable form types, date ranges, and dimensions, and automatic data validation. It handles the SEC's fair access requirements automatically, such as user agent declaration and rate limiting between requests, and caches downloaded documents for efficient retrieval of large datasets. The implementation uses standard HTTP libraries to handle API interactions efficiently and is available in both R and 'Python' for accessibility to a broad audience.

Update and Manipulate Rd Documentation Objects

Functions for manipulation of R documentation objects, including functions reprompt() and ereprompt() for updating 'Rd' documentation for functions, methods and classes; 'Rd' macros for citations and import of references from 'bibtex' files for use in 'Rd' files and 'roxygen2' comments; 'Rd' macros for evaluating and inserting snippets of 'R' code and the results of its evaluation or creating graphics on the fly; and many functions for manipulation of references and Rd files.