Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
brand.yml
The _brand.yml file allows for unified branding across various outputs by setting company brand guidelines in a YAML file. This file can be integrated with tools like Quarto and Python's Shiny to automatically apply brand themes to reports, dashboards, and presentations, ensuring a consistent brand identity in data science products. Support for _brand.yml is available in several formats and libraries, enabling easy theming with company logos, colors, and typography across different platforms. Examples and user stories illustrate its practical applications in data science workflows.
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Branding and automating your work with R Markdown
This video is about branding and automating work with R Markdown. It discusses how a team of data scientists uses advanced features in RStudio to brand reports and presentations for clients. The speaker highlights lessons learned in areas like version control and automation, including how a few lines of code allowed them to create a specialized report on crime for every county in Utah.
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breakerofchains
Break your chain at the cursor line. Run the first bit. See the output. Be free.
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bs4Dash
bs4Dash is a Bootstrap 4 version of shinydashboard, a package for creating dashboards with Shiny in R. This article provides information on how to upgrade from shinydashboard to bs4Dash.
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Build Advanced Charts in R
The LinkedIn Learning course 'Build Advanced Charts in R' by Rita Giordano is an advanced-level data visualization course. Over 1 hour and 43 minutes, students delve into creating sophisticated charts including lollipop plots, sparklines, dot charts, and slope charts. The course covers creating theme functions, combining plots, and ensuring accessibility with colorblind-friendly palettes and dyslexia-friendly fonts. Participants will learn when to use advanced charts, how to apply accessibility principles, and how to build a simple infographic. A downloadable certificate of completion enhances professional profiles, demonstrating data visualization proficiency in R.
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Build Advanced Charts in R Online Class | LinkedIn Learning, formerly Lynda.com
This online class on LinkedIn Learning (formerly Lynda.com) teaches users how to build advanced charts in R for data visualization. The course covers topics such as lollipop plots, sparklines, dot charts, slope charts, and chord diagrams. It also includes information on creating a theme function, combining multiple plots, and addressing accessibility and annotations. The instructor, Rita Giordano, is a data visualization consultant and LinkedIn Instructor.
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Building a Linkedin data visualisation template with Quarto and Typst
Aaron Schiff shares a method for sharing data visualizations on Linkedin using Quarto and Typst. He created a template that allows for the production of nicely formatted PDFs to circumvent Linkedin's subpar image handling. The template includes a topic heading, summary text, a ggplot chart, data source citation, optional two-column text, and a footer. Additionally, Schiff explains the synergy of Quarto, a publishing system, and Typst, a layout framework, to streamline the production of visually appealing PDFs. He provides guidance on creating a Quarto Typst template and how to use it with example code and the configuration process.
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Building R packages with devtools and usethis | RStudio - YouTube
This YouTube video provides a tutorial on building R packages using devtools and usethis in RStudio.
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Building Shiny apps - an interactive tutorial
An interactive tutorial on building Shiny apps, which are interactive web pages built using R.
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Building Stories With Data - Fixing awkward backgrounds in ggplot2
In this article, Cara Thompson shares a solution for fixing awkward backgrounds in ggplot2 when using fixed coordinate systems like coord_sf() or coord_polar(). The issue arises when the background color does not cover the entire export area. She offers several solutions, including one that she finds more elegant, involving the use of the {cowplot} package. By implementing a simple function, one can ensure the background color fills the full plotting area, enhancing the visual consistency of custom-themed graphs and maps within documents.
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