design VS awesome-R

Compare design vs awesome-R and see what are their differences.

awesome-R

A curated list of awesome R packages, frameworks and software. (by qinwf)
InfluxDB - Power Real-Time Data Analytics at Scale
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SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
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design awesome-R
2 6
210 5,783
0.5% -
8.4 4.0
3 months ago 2 months ago
R R
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

design

Posts with mentions or reviews of design. We have used some of these posts to build our list of alternatives and similar projects.

awesome-R

Posts with mentions or reviews of awesome-R. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-13.

What are some alternatives?

When comparing design and awesome-R you can also consider the following projects:

ggstatsplot - Enhancing {ggplot2} plots with statistical analysis 📊📣

fontawesome - Easily insert FontAwesome icons into R Markdown docs and Shiny apps

DataScienceR - a curated list of R tutorials for Data Science, NLP and Machine Learning

easystats - :milky_way: The R easystats-project

ggplot2 - An implementation of the Grammar of Graphics in R

sf - Simple Features for R

dplyr - dplyr: A grammar of data manipulation

lab02_R_intro - Vežbe 2: Uvod u R

rmarkdown - Dynamic Documents for R

viridis - Colorblind-Friendly Color Maps for R

wesanderson - A Wes Anderson color palette for R

fastverse - An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R