ggplot2 VS worldfootballR

Compare ggplot2 vs worldfootballR and see what are their differences.

ggplot2

An implementation of the Grammar of Graphics in R (by tidyverse)

worldfootballR

A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob (by JaseZiv)
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ggplot2 worldfootballR
62 7
6,316 399
1.2% -
9.4 9.0
6 days ago 3 months 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.

ggplot2

Posts with mentions or reviews of ggplot2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-02.

worldfootballR

Posts with mentions or reviews of worldfootballR. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-12.

What are some alternatives?

When comparing ggplot2 and worldfootballR you can also consider the following projects:

Altair - Declarative statistical visualization library for Python

dplyr - dplyr: A grammar of data manipulation

tmap - R package for thematic maps

blogdown - Create Blogs and Websites with R Markdown

vega - A visualization grammar.

wesanderson - A Wes Anderson color palette for R

epanet2toolkit - An R package for calling the Epanet software for simulation of piping networks.

glue - Glue strings to data in R. Small, fast, dependency free interpreted string literals.

DontBlameTheData - Repository for the backend of dontblamethedata.com

deneb - Deneb is a custom visual for Microsoft Power BI, which allows developers to use the declarative JSON syntax of the Vega or Vega-Lite languages to create their own data visualizations.

soccerdata - ⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, FotMob, Sofascore, SoFIFA, Understat and WhoScored.