tidyverse
desctable
| tidyverse | desctable | |
|---|---|---|
| 2 | 2 | |
| 1,602 | 51 | |
| 0.9% | - | |
| 4.9 | 0.0 | |
| 5 months ago | about 2 years ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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.
tidyverse
-
Discrimination of R in companies
What’s the original? Tidyverse, as it exists now, had it’s initial release in 2016. Pandas initial release was in 2009. AFAIK, ggplot2 and reshape are the only individual Tidyverse packages older than that.
- R packages installation error
desctable
- New to R. Anyone have a go-to way to make a pretty descriptives table?
-
desctable has a website, and a new version!
The new API is not yet complete, but has feature parity with the old one, and will be further developed towards 1.0. (have a look at the roadmap on the github repo) desctable has now full support for purrr::map-like formulas when defining statistics and tests, and a easier to manipulate internal format. There's a new website at https://desctable.github.io, the repo has moved to it's own org (https://github.com/desctable/desctable), and new documentation and vignettes have been written!
What are some alternatives?
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IntRo - Introduction to R for health data
tidyqpcr - quantitative PCR analysis with the tidyverse
Practical-Applications-in-R-for-Psychologists - Lesson files for Practical Applications in R for Psychologists.
janitor - simple tools for data cleaning in R
tidytext - Text mining using tidy tools :sparkles::page_facing_up::sparkles:
drake - An R-focused pipeline toolkit for reproducibility and high-performance computing
tidylog - Tidylog provides feedback about dplyr and tidyr operations. It provides wrapper functions for the most common functions, such as filter, mutate, select, and group_by, and provides detailed output for joins.
tidyquery - Query R data frames with SQL
forcats - 🐈🐈🐈🐈: tools for working with categorical variables (factors)