Welcome to the Nice R code module. This module is targeted at researchers who are already using R and want to write nicer code. By ‘nicer’ we mean code that is easy to write, is easy to read, runs fast, gives reliable results, is easy to reuse in …

By ‘nicer’ we mean code that is easy to write, is easy to read, runs fast, gives reliable results, is easy to reuse in new projects, and is easy to share with collaborators. At the nice R code site, we are trying to help researchers (mostly biologists) get the most out of their code by communicating the elements of work flow and good coding ...

The Nice R code guides to.... We have put together the following guides on writing niceR code. A general introduction to R; Version control in R with git; Using functions to simplify your scripts; Different ways of repeating things. Plotting. Writing reports with knitr and markdown; We have also put together a list of

A nicer replacement for PHP's print_r (). Works with (at least) PHP 5.2 (tested). Following a recent rewrite, this library has been converted into a class. However, an adapter is available for …

Explore many nice R examples and examples, working samples and examples using the R packages. How to do this and that after downloading and installing the package.

Welcome the R graph gallery, a collection of charts made with the R programming language. Hundreds of charts are displayed in several sections, always with their reproducible code available. The gallery makes a focus on the tidyverse and ggplot2. Feel free to suggest a chart or report a bug; any feedback is highly welcome!

This repository contains the functions of the niceRplots package, which provides functions to create graphics in the NICE style, inspired by the similar bbplot package. These functions can be used to style static charts created using ggplot2, or interactive charts created using plotly.

In this section, we’ll delve into the fundamental aspects and key features of the package. The nice package in R provides a convenient method for non-parametric interval estimation and hypothesis testing. It features a variety of functions for confidence intervals, bootstrap intervals, and permutation tests.

Our recommendation for writing nice R code is that in most cases, you should put your functions into a file with an intuitive name, like analysis-fun.R and read these into memory by calling:

2024年2月27日 · NICER Data Analysis. This page contains links to documents and information on the NICER software (NICERDAS) necessary to calibrate and analyse the NICER data. The current NICERDAS software version 12 is distributed with HEAsoft version 6.33 (Feb 2024).