future VS shiny.i18n

Compare future vs shiny.i18n and see what are their differences.

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future shiny.i18n
2 1
932 166
- 0.0%
8.1 4.9
16 days ago 17 days 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.

future

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

shiny.i18n

Posts with mentions or reviews of shiny.i18n. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing future and shiny.i18n you can also consider the following projects:

seurat - R toolkit for single cell genomics

nflfastR - A Set of Functions to Efficiently Scrape NFL Play by Play Data

R-sharp - R# language is a kind of R liked vectorized language implements on .NET environment for the bioinformatics data analysis

huxtable - An R package to create styled tables in multiple output formats, with a friendly, modern interface.

HoRM - Supplemental Functions and Datasets for "Handbook of Regression Methods"

worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob

hts - Hierarchical and Grouped Time Series

mindr - an R package which converts markdown files (.md, .Rmd) into mindmaps (brainstorms)

r2u - CRAN as Ubuntu Binaries

openxlsx - openxlsx - a fast way to read and write complex xslx files

parsel - parallel execution of RSelenium

randomNames - Function to generate random gender and ethnicity correct first and/or last names. Names are chosen proportionally based upon their probability of appearing in a large scale data base of real names.