Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
Full-Stack Survey Research with SurveyMonkey • svmkR
This package provides a suite of tools to work with SurveyMonkey surveys in R.
Go to Resource
Full-Stack Survey Research with SurveyMonkey • svmkR
svmkR is an R package that provides a comprehensive toolkit for managing SurveyMonkey surveys within the R programming environment. It enables users to create, upload, download, and analyze surveys directly from R. Users can calculate margins of error, apply statistical survey weights through raking, and generate SurveyMonkey-style banner presentations for polls. The package is installed from GitHub and serves as a full-stack survey research solution. The source is available on GitHub, and the package was developed by a team of contributors, building on the surveymonkey package by enhancing and refactoring it.
Go to Resource
Functions and Themes for gt tables
A tutorial on using functions and themes for creating gt tables in R language.
Go to Resource
Gentelella Shiny
This is an R Shiny HTML Template version of the gentelella bootstrap theme. It provides a unique looking Shiny dashboard with features like login authentication, dynamic progress bar visualization, custom boxes for plots, and more.
Go to Resource
Geocomputation with R
Geocomputation with R is a book on geographic data analysis, visualization, and modeling. It covers various topics related to working with geographic data in R.
Go to Resource
Getting fonts to work in R
Getting fonts to work in R and RStudio can be tricky! This post walks through the different steps we need to follow to give ourselves the best chance of success.
Go to Resource
Getting more out of dplyr
Video presentation by Suzan Baert on getting more out of dplyr at SatRday 2018 Amsterdam.
Go to Resource
Getting started with theme()
This tutorial provides an introduction to the theme() function in ggplot2 and explains how to modify plot themes and elements using this function. It covers basic plot building, using built-in ggplot2 themes, modifying the legend position, and introduces the element_*() functions.
Go to Resource
Getting started with theme()
This blog post offers a beginner-friendly introduction to the theme() function in {ggplot2} for R, emphasizing its utility in customizing plot aesthetics like text and overall style. The author, Jack Kennedy, breaks down the overwhelming number of arguments into manageable, impactful components, providing a step-by-step guide to modifying plots using theme() and related element_*() functions. The content is approachable, combining practical examples with a touch of personal style advice, aiming to empower readers to tailor their {ggplot2} plots confidently.
Go to Resource
Getting started with theme()
This content is a tutorial on the theme() function in the ggplot2 package for R. It provides a practical guide to customizing the appearance of plots using theme(), starting from basic modifications to more advanced tweaks. The tutorial includes examples of modifying plot themes with pre-built ggplot2 themes and the use of the theme() function. It discusses altering legend positions, grid lines, and more nuanced theme elements for personalizing plots. The content is designed to help readers become comfortable and confident in adjusting plot aesthetics to match their preferred style or organizational standard.
Go to Resource