FriendsDontLetFriends VS wesanderson

Compare FriendsDontLetFriends vs wesanderson and see what are their differences.

FriendsDontLetFriends

Friends don't let friends make certain types of data visualization - What are they and why are they bad. (by cxli233)
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FriendsDontLetFriends wesanderson
4 4
5,968 1,865
- -
7.3 5.4
2 months ago 6 months ago
R R
MIT License 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.

FriendsDontLetFriends

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

wesanderson

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

What are some alternatives?

When comparing FriendsDontLetFriends and wesanderson you can also consider the following projects:

tanya-data-viz - Personal data visualization side projects.

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

purrr - A functional programming toolkit for R

sjPlot - sjPlot - Data Visualization for Statistics in Social Science

llr - Lisp-like-R: A clojure inspired lisp that compiles to R in R

quanteda - An R package for the Quantitative Analysis of Textual Data

tidyr - Tidy Messy Data

c3plot - R Package for Interactive Plotting via C3.js with a Base Graphics-like Interface

chess - An R package to read, write, create and explore chess games

tyecon - Assembling functions and results with ease

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.