badger VS DataScienceR

Compare badger vs DataScienceR 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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badger DataScienceR
1 1
188 1,959
- -
4.7 0.0
3 months ago about 1 year 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.

badger

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

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.

What are some alternatives?

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

r4ds - R for data science: a book

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

rmarkdown - Dynamic Documents for R

design - Tidyverse design principles

ggplot2 - An implementation of the Grammar of Graphics in R

lab02_R_intro - Vežbe 2: Uvod u R

dplyr - dplyr: A grammar of data manipulation

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

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

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.

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)