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.

Miscellaneous Tools for Reproducible Research

Tools to load 'R' packages and automatically generate BibTeX files citing them as well as load and cache plain-text and 'Excel' formatted data stored on 'GitHub', and from other sources.

A Simpler Way to Find Your Files

Constructs paths to your project's files. Declare the relative path of a file within your project with 'i_am()'. Use the 'here()' function as a drop-in replacement for 'file.path()', it will always locate the files relative to your project root.

Read, Write and Edit xlsx Files

Simplifies the creation of Excel .xlsx files by providing a high level interface to writing, styling and editing worksheets. Through the use of 'Rcpp', read/write times are comparable to the 'xlsx' and 'XLConnect' packages with the added benefit of removing the dependency on Java.

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.

Download Datasets from the Swiss National Science Foundation (SNF, FNS, SNSF)

Download and read datasets from the Swiss National Science Foundation (SNF, FNS, SNSF; < https://snf.ch>). The package is lightweight and without dependencies. Downloaded data can optionally be cached, to avoid repeated downloads of the same files. There are also utilities for comparing different versions of datasets, i.e. to report added, removed and changed entries.

'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.

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.

Download Data from the Swiss National Bank (SNB)

Download data (tables and datasets) from the Swiss National Bank (SNB; < https://www.snb.ch/en>), the Swiss central bank. The package is lightweight and comes with few dependencies; suggested packages are used only if data is to be transformed into particular data structures, for instance into 'zoo' objects. Downloaded data can optionally be cached, to avoid repeated downloads of the same files.

Harrell Miscellaneous

Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.