By Matt Brousil The goal of this walkthrough is to look over some methods for cleaning and maintaining data and scripts. This will not be comprehensive for either topic, but contains some tips I've collected. Data Cleaned data is a wonderful thing. There are resources like Data Carpentry to provide crash courses in how …

By Nicholas Potter Resources: A list of best practices Ropensci's rrrpkg suggestions An official using GIT with Rstudio A better GIT and Rstudio article Why R projects? Because setwd() is evil (source). here: an R packages to manage the working directory and file locations A scenario: A new project on water …

By Alli Cramer Spatial analysis in R For one of my primary experiences of spatial analysis in R, we used a number of existing data bases to determine the average yearly temperature and precipitation for over 1.3 million lakes. One of my duties in this project was to combine multiple raster layers from a reanalysis of …

By Alli Cramer 1library(astsa) Lynx Data set For this example, we will be using a Lynx population dataset. You can find the dataset here: the "Annual Number of Lynx Trapped on the Mackenzie River from 1821-1934. From: …

By Michael F. Meyer For the reader: This document is to serve as a tutorial for the R Working Group at Washington State University. For more information, please contact Michael F. Meyer For BeginneRs There are three main takeaways from this tutorial. You will have learned: How to read in a text file and convert a …

Things to Look for as a Beginner These are the three functions that are used during this presentation for webscraping. These are the only functions that are used from the "rvest" package. Everything else in this presentation is base R. read_html() html_nodes() html_table() What is Web Scraping? Web scraping …

By Julia Piaskowski Sources Thomas Lumley, Github repo useRfasteR Hadley Wickham, Profiling, Advanced R Dirk Eddelbuettel, Rcpp The Process for Improving Code: (quote from Advanced R) Find the biggest bottleneck (the slowest part of your code). Try to eliminate it (you may not succeed but that's ok). Repeat …

By Matt Brousil Making our first shiny app: Shiny is a package developed by RStudio. It allows you to build interactive apps online, displaying data, figures, etc. It's very flexible and only requires that you know how to use R in order to build an app. Once you have an app written, it can be hosted online or even …

Post by Dominik Schneider A couple things to note. Spatial/gis functions in R are undergoing a massive change right now. The old stalwart sp has been succeeded by sf (simple features), which is compatible with the open geospatial consortium standards. When you are looking for solutions online, make sure you know which …