CougRstats Blog

Raster parallel process in R

May 10, 2021 · 5 min read · raster parallel snow foreach ·

By Fidel Maureira Sotomayor Install libraries if there are no already in your computer. 1packages = c('raster','terra', 'snow', 'parallel', 'foreach','doParallel','rasterVis', 'mapview','ggplot2', 'lubridate','pryr') 2out = …

Using Python in R Studio with Reticulate

Apr 21, 2021 · 6 min read · R Python reticulate ·

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By Sarah Murphy Download all code used below from the GitHub repository! There are four ways to use Python code in your R workflow: Python code blocks in R Markdown Interactively in the console Importing Python packages and using the commands within your R scripts Importing Python scripts and using user-defined …

Feature Engineering with Sliding Windows and Lagged Inputs

Feb 18, 2021 · 1 min read · time series ·

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This week Bryan Shalloway presented a talk about feature engineering with sliding windows and lagged inputs. You can find a post on his personal blog about the topic here, and the link to the corresponding GitHub repository here.

Introduction to mapping in R

Feb 10, 2021 · 15 min read · ggplot2 mapping sf ·

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By Matt Brousil In this post I'll walk through some of the basics for getting started importing, formatting, and creating maps with spatial data in R. Many students and researchers I know (myself included) have taken GIS coursework and are familiar with tools like ArcMap, but want to work with their data in R. R …

Research profiles with Shiny Dashboard: A case study in a community survey for antimicrobial resistance in Guatemala

Dec 2, 2020 · 2 min read · Research Profiles shiny ·

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October 28th, 2020. By Juan Carlos Romero (jromero@ces.uvg.edu.gt), Juan Pablo Alvis (jalvis@ces.uvg.edu.gt), Laura María Grajeda (lgrajeda@ces.uvg.edu.gt) from Centro de Estudios en Salud, Universidad del Valle de Guatemala. The successful implementation of community surveys requires close and timely monitoring of …

Formatting data for use with R

Oct 21, 2020 · 8 min read · data formatting janitor ·

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By Matt Brousil This post walks through some best practices for formatting and preparing your data for use with R. Some of the suggestions here are drawn from Data Carpentry, Broman and Woo (2018), and the BES Guide to Reproducible Code. The required dataset is available here. A previous version of this post that deals …

ggplot2 tutorial

Oct 16, 2020 · 9 min read · ggplot2 ·

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By Mikala Meize Libraries used 1library(tidyverse) 2library(ggthemes) The ggplot() function, which is used in this tutorial is housed within the tidyverse library. The ggthemes library is something we'll use later on in the tutorial. There are several ways to set up a plot using ggplot(). The first is to simply run: …

Tidyverse Data Wrangling

Sep 30, 2020 · 15 min read · data wrangling tidyverse ·

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By Ben Leonard What is Data Wrangling? Most of the time datasets will not come "out of the box" ready to use for analysis. Summarizing data and presenting audience friendly tables and figures requires quite a bit of data manipulation. A data wrangling task is performed anytime a dataset is cleaned, tweaked, …

An introduction to linear models with R

Sep 25, 2020 · 18 min read · linear regression multiple regression ·

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By Mikala Meize Libraries used 1library(QuantPsyc) 2library(lmtest) 3library(palmerpenguins) Linear model information Linear models are generally coded in this format: model.name <- modeltype(outcome ~ predictor, data, specifications) The following code will apply specifically to Ordinary Least Squares (OLS) …

An Introduction to data.table using sythetic lat/lon data

Apr 15, 2020 · 11 min read · data.table ·

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By Nicholas A. Potter This is a short introduction to using data.table based on my work with climate data. Initial setup Let's begin by generating some data to work with. We'll use the following packages: 1# If you don't have the packages below, install with: 2#install.packages(c("data.table", …