Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
A Scientist's Guide to R: Step 2.2 - Joining Data with dplyr
This post is part of the Scientist's Guide to R series and focuses on using joins to combine data frames in R with the dplyr package. It covers different types of joins, such as inner, left, right, full, semi, and anti join, as well as using bind_rows() or bind_cols() to build data frames. The post also mentions the merge() function in base R for joining data frames.
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A Scientist's Guide to R: Step 2.3 - string manipulation and regex
A Scientist's Guide to R: Step 2.3 - string manipulation and regex
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A Scientist's Guide to R: Step 2.4 - forcats for factors
This post is part of a series called A Scientist's Guide to R and focuses on how to work with factors in R using the forcats package.
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A Scientist's Guide to R: Step 2.5 - dates & times
A Scientist's Guide to R: Step 2.5 - dates & times is a blog post that provides a guide on how to work with dates and times in R using the lubridate package. It covers topics such as date/time basics, reading dates, time zones, month names, extracting datetime components, custom date formats, date calculations, and planning a behavioural neuroscience experiment. The post aims to help readers handle dates and times effectively in R.
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A SIMPLE guide to create BUMP CHARTS with ggplot2 - YouTube
A YouTube tutorial on creating bump charts with ggplot2
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A timeline of R's first 30 years
This content celebrates the 30th anniversary of the R language with a timeline highlighting significant milestones, packages, and papers. Developed by Tim Brock, Colin Gillespie, and the Jumping Rivers Team, it showcases R's evolution and invites contributions through social media. The standalone timeline is inspired by a figure in a publication on R's role in bioinformatics and data science. Jumping Rivers offers related training and a newsletter.
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A Twitter bot with {rtweet} and GitHub Actions
A blog post about creating a Twitter bot using the R package rtweet and GitHub Actions
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A year with Visible Long-Covid Tracking
Dr. Mowinckel shares insights on a year-long journey of tracking Long Covid symptoms using the Visible app. The app monitors heart rate, HRV, daily symptoms, and functional capacity through the FUNCAP27 questionnaire. The post details the process of collecting and analyzing personal health data to understand recovery patterns, pacing strategies, and warning signs. The blog also offers a look at tools within Visible that help visualize progress, such as heart rate graphs and a functional capacity semi-circle, providing a valuable resource for individuals managing Long Covid.
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Access and Manipulate Comprehensive Country Level Data in Tidy Format • tidycountries
The tidycountries package in R provides a comprehensive interface for accessing and manipulating country-level data. It includes details such as names, regions, populations, currencies, and more in a tidy format that integrates with the tidyverse. It's useful for global research, visualizations, and querying country information. The package can be easily installed from CRAN or GitHub and integrates well with the tidyverse, making data manipulation straightforward.
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Access South Korean Data via Public APIs and Curated Datasets • SouthKoreAPIs
The SouthKoreAPIs package is a comprehensive R tool for accessing South Korean open data from various public APIs and curated datasets. It interfaces with the World Bank API, Nager.Date API, and REST Countries API to fetch a range of information, such as economic indicators and national holidays. Additionally, it boasts an extensive collection of datasets encompassing public health, demographics, social surveys, and more. Its utility functions facilitate the retrieval of specific data points, like mortality rates and GDP, while its organized datasets enable in-depth analysis of South Korean socioeconomic and cultural patterns.
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Add last rendered or modified time to Quarto
Garrick Aden-Buie's blog post introduces 'now,' a Quarto extension that allows the automatic update of time information in Quarto documents. This extension saves time by eliminating the need for manual updates of dates in documentation footers. By adding the extension using 'quarto add gadenbuie/quarto-now,' Quarto users can employ shortcodes like '{{< now >}}' and '{{< modified >}}' to display the current or last modified time. The extension supports customization of time output formats and may significantly streamline Quarto project maintenance by ensuring date accuracy without manual intervention.
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Adding a logo to images with {magick} and {purrr}
Jadey Ryan shared her experience with automating the process of adding logos to images using the R packages {magick} and {purrr}. She also highlighted new merchandise such as tote bags and embroidered hats on her Etsy shop. Additionally, she announced a free webinar series on soil health where she will demo the {soils} R package. Alongside, she informed about the Parameterized Quarto workshops she is giving, focusing on efficient report generation using R and Quarto, with the next one scheduled with R-Ladies Abuja.
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