Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
RStudio Projects and Working Directories: A Beginner's Guide
This blog post provides a basic introduction on how to use RStudio Projects and structure your working directories. It explains why RStudio projects are important and the advantages of using them over setwd(). The post also covers how RStudio projects make file paths relative, making it easier to reference files within the project. It includes practical examples and personal advice for beginners in R programming.
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RStudio Shortcuts and Settings
Albert Rapp provides a guide for maximizing productivity in RStudio with shortcuts and settings. This post covers visual adjustments like themes, legibility improvements, and editor configurations, alongside tips for efficient code execution, debugging, and navigation. Rapp emphasizes starting with a clean environment, highlights key shortcuts for coding basics, file searching, command palette, and session management. The aim is to enhance user experience, reduce reliance on the mouse, and improve coding workflow. Ideal for R users looking to streamline their RStudio setup.
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rtweet
rtweet is an R package that allows for interacting with Twitter's APIs to collect and analyze Twitter data.
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RVerbalExpressions
RVerbalExpressions is an R package that makes it easier to construct regular expressions using grammar and functionality inspired by VerbalExpressions.
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rvest
rvest is an R package that helps you scrape (or harvest) data from web pages. It is designed to work with magrittr to make it easy to express common web scraping tasks.
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savonliquide
GitHub repository for the savonliquide R package, which provides a toolbox for implementing accessibility-related concepts.
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Second edition of Geocomputation with R is complete – geocompx
The blog post announces the near-completion of the second edition of 'Geocomputation with R.' It showcases the three-year journey of updating and enhancing the content, discussing improvements and pending tasks. This edition integrates changes in the R ecosystem, such as the introduction of the terra package for raster data and sf package's support for spherical geometries. It revises content on spatial vector and raster data manipulation, connects R with GIS/cloud services, and addresses real-world geocomputation applications like transportation and ecology. The second edition aligns with new library standards, emphasizing the practical, hands-on nature of the open-source book.
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sf
Simple Features for R is a package that provides simple features access for R. It represents simple features as records in a data.frame or tibble with a geometry list-column, and interfaces with GEOS for geometrical operations on projected coordinates. It also interfaces with GDAL, supporting all driver options, and PRØJ for coordinate reference system conversion and transformation. Additionally, it supports reading from and writing to spatial databases such as PostGIS using DBI.
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sf cheatsheet
A cheatsheet for the 'sf' package in R that provides a concise summary of spatial data manipulation and visualization functions.
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sf: A Tutorial
A tutorial introduction to the sf R package, which provides a powerful interface for working with geospatial data stored in vector formats.
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Sh*tty R help from sh*tty AI
The blog post from rostrum.blog critiques the proliferation of R help websites that use low-quality AI-generated content to exploit vulnerable learners for profit. The author observes these sites featuring predatory practices such as affiliate marketing without providing valuable help, producing numerous pages with slightly altered content for SEO gains, and dishonestly attributing authorship to non-existent human writers. The post warns readers to be cautious and recognize that these sites offer poor advice, often including incorrect or non-functional code, and may feature content pirated from legitimate creators without consent.
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shiny
Shiny is a web application framework for building interactive web apps without web development skills. It is used for data science and allows users to interact with data and analysis using R or Python.
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