Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
Open Case Studies | Bloomberg American Health Initiative
The Open Case Studies project showcases the possibilities of what can be achieved when working with real-world data. It provides insights about gathering and working with data for students, instructors, and those with experience in data science or statistical methods at nonprofit organizations and public sector agencies. Each case study focuses on an important public health topic and introduces methods to provide users with the skills and knowledge for greater legibility, reproducibility, rigor, and flexibility in their own data analyses.
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Optimising VS Code and Positron for Quarto
This content presents a comprehensive guide to optimizing the editing experience of Quarto documents within VS Code and Positron platforms. It details specific editor settings adjustments aimed at improving document editing by addressing common issues such as code formatting, readability, and workspace performance. The settings enhance visual assistance, reduce visual clutter, manage markdown table rendering, and refine Git diffs. Essential configurations such as defining language-specific settings, modifying word wrapping, and utilizing bracket pair guides are discussed. Additionally, recommendations for visual line length guides, workspace performance optimization, and GitHub Copilot integration for AI assistance are provided to streamline the Quarto document editing workflow.
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Ordering images of toast from least toasted to most toasted...
The GitHub repository 'toast' by cj-holmes is a unique project that involves organizing images of toast based on their level of toasting, from least to most toasted. It provides an analytical approach to the humorous question of the best way to 'toast a toast' using R and ImageMagick. The repository includes code to read and analyze an image of toast, select pixel values, and visualize them to identify the level of toasting. It leverages packages from the tidyverse and uses ggplot for visualization and magick for image processing to create a greyscale intensity from RGB values of pixels.
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Origin and development of a Snowflake Map
This blog post describes the origin and development of a snowflake map, a data visualization technique for representing snow cover. The author explains the concept, the data used, and the steps involved in creating the map. The post also mentions the use of various packages like ggimage and magick. The final result is a snowflake hex map of the contiguous U.S. that shows average snow cover.
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Outliers in Data Analysis: Detecting Extreme Values Before Modeling in R
This content provides a comprehensive guide on detecting outliers in data analysis before modeling using R, with a specific focus on Airbnb listings data from Istanbul. It emphasizes the importance of understanding the statistical implications of outliers and how they can distort statistical analysis and modeling efforts. The guide demonstrates practical outlier detection methods and includes R code for loading and pre-processing the Airbnb dataset, while also discussing relevant statistical concepts and the importance of making informed preprocessing decisions. Example variables such as price, minimum_nights, and room_type are used for illustration.
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Overriding {ggplot2} Legend Keys · Jindra Lacko
This content describes a method to achieve visual consistency in {ggplot2} legends across different plot types by overriding the legend keys. Specifically, it addresses aligning legend keys between a choropleth map and a point map in R, with the choropleth map using square keys and the point map using round points. The article provides an example using North Carolina shapefiles and demonstrates how to use the key_glyph argument in geom_sf() to customize legend glyphs, thereby maintaining a consistent legend appearance across multiple plots. It also explores alternative glyphs like timeseries and boxplot in the context of maps.
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Parameterized Reporting with RMarkdown
Parameterized Reporting with RMarkdown is a tutorial that explains how to use parameterized reporting in RMarkdown to generate multiple reports at the same time.
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patchwork 1.3.0
patchwork 1.3.0 introduces exciting new features for creating multifigure plot compositions, adding support for beautifully formatted tables alongside figures with native support for gt objects. Enhanced by Teun Van den Brand's contributions, it allows users to seamlessly integrate tables using the wrap_elements() method or with table-specific formatting via wrap_table(). This version optimizes the space utilization of tables within plots, aligning components perfectly and providing formatting options for an improved aesthetic and functional integration of data visualizations and tabular presentations.
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Patterns and anti-patterns of data analysis reuse
The blog post titled 'Before I Sleep: Patterns and anti-patterns of data analysis reuse' by Miles McBain discusses the common themes in data analysis roles pertaining to the repeated nature of certain analyses across various industries. McBain highlights the need for reusing code and strategies efficiently to maintain productivity amidst this recurring challenge. The text delves into different stages of data analysis reuse, such as copy-pasting previous work, which may initially save time but lead to accruing technical debt. It stresses on setting up practices for swift reuse of work to build upon proven capabilities, assuming the work is code-based and document-like products are code-generated.
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Personal Art Map with R
Learn how to create personal art maps with R using data from Open Street Maps (OSM) and personal mobility data. This tutorial provides step-by-step instructions on downloading street maps, collecting highway and street data, and combining them to create personalized maps.
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PIPING HOT DATA: Getting started with unit testing in R
Getting started with unit testing in R. This blog post accompanies the R-Ladies Philly workshop on Nov 11, 2021, where they demonstrate how to automate R package testing using the usethis, devtools, testthat, and covr packages. The post highlights key points from the workshop, including strategies for writing tests, debugging techniques, and concepts in function writing that facilitate the testing process.
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