quanteda VS awesome-R

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

quanteda

An R package for the Quantitative Analysis of Textual Data (by quanteda)

awesome-R

A curated list of awesome R packages, frameworks and software. (by qinwf)
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quanteda awesome-R
5 6
824 5,792
0.4% -
9.7 4.0
4 days ago 2 months ago
R R
GNU General Public License v3.0 only -
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.

quanteda

Posts with mentions or reviews of quanteda. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-05.

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 quanteda and awesome-R you can also consider the following projects:

dplyr - dplyr: A grammar of data manipulation

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

BTM - Biterm Topic Modelling for Short Text with R

easystats - :milky_way: The R easystats-project

empirist-corpus - A web and social media corpus based on the dataset of the EmpiriST 2015 shared task

sf - Simple Features for R

wesanderson - A Wes Anderson color palette for R

lab02_R_intro - Vežbe 2: Uvod u R

tidytext - Text mining using tidy tools :sparkles::page_facing_up::sparkles:

viridis - Colorblind-Friendly Color Maps for R

ggplot2 - An implementation of the Grammar of Graphics in R

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