DataScienceR VS badger

Compare DataScienceR vs badger and see what are their differences.

DataScienceR

a curated list of R tutorials for Data Science, NLP and Machine Learning (by ujjwalkarn)
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DataScienceR badger
1 1
1,959 187
- -
0.0 4.7
about 1 year ago 3 months ago
R R
MIT License -
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.

DataScienceR

Posts with mentions or reviews of DataScienceR. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-12.

badger

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

What are some alternatives?

When comparing DataScienceR and badger you can also consider the following projects:

aor - 🎄📦 Advent of R: Utility Functions for the Advent of Code in R

r4ds - R for data science: a book

design - Tidyverse design principles

rmarkdown - Dynamic Documents for R

lab02_R_intro - Vežbe 2: Uvod u R

ggplot2 - An implementation of the Grammar of Graphics in R

awesome-computational-social-science - A list of awesome resources for Computational Social Science

dplyr - dplyr: A grammar of data manipulation

R-Fundamentals - D-Lab's 4 part, 8 hour introduction to R Fundamentals. Learn how to create variables and functions, manipulate data frames, make visualizations, use control flow structures, and more, using R in RStudio.

awesome-R - A curated list of awesome R packages, frameworks and software.

rlang - Low-level API for programming with R

seminr - Natural feeling domain-specific language for building structural equation models in R for estimation by covariance-based methods (like LISREL/Lavaan) or partial least squares (like SmartPLS)