This is the final part for the R Jump Start series! After this session you should walk away with a deep understanding of a few different visualization libraries, advantages, disadvantages as well as having gotten hands on with those libraries. We will al
Today, Dr. Riche shares her passion for the art of data driven storytelling, reveals the two superpowers of data visualization, gives us an inside look at some innovative projects designed to help us th(ink) with digital ink, and tells the story of how a young woman with an artist’s h...
Some of the best and most beautiful examples of data visualisations are hundreds of years old (like Florence Nightingale's Crimean War Mortality chart) and some are being made today by talented storyteller-analysts.
I love beautifully visualised data and I wanted share some tricks on how to create beautiful visualizations with R. 1. Choose fitting colors. you can choose specific colors for your visualization with millions of color palettes online and use it for the data background and fonts. 2. Create st...
《R语言数据可视化之美》配套代码. Contribute to github-gs/Beautiful-Visualization-with-R development by creating an account on GitHub.
She is passionate about data visualization and design, and fell in love with the online R community via #TidyTuesday. When she’s not working on data projects, you can find her cycling or exploring downtown St. Petersburg, Florida. Description: When we think about data visualization, bar ...
《R语言数据可视化之美》配套代码. Contribute to github-gs/Beautiful-Visualization-with-R development by creating an account on GitHub.
Beautiful Visualization is useful for readers from laypersons with no data graphics software experience to experienced people with data visualization and who want to read a variety of examples of data interpreted visually. Julie Steele and Noah Iliinsky have commissioned authors, mostly academics and ...
GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia) Network Analysis and Visualization in R by A. Kassambara (Datanovia) Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia) Inter-Rater Reliability Essentials: Practical Gui...
A new data processing workflow for R: dplyr, magrittr, tidyr and ggplot2 We start with the the quick setup and a default plot followed by a range of adjustments below. Quick-setup: The dataset We’re using data from the National Morbidity and Mortality Air Pollution Study (NMMAPS). To...