bigrquery VS awesome-R

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

bigrquery

An interface to Google's BigQuery from R. (by r-dbi)

awesome-R

A curated list of awesome R packages, frameworks and software. (by qinwf)
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bigrquery awesome-R
2 6
504 5,792
0.2% -
8.4 4.0
18 days ago 2 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.

bigrquery

Posts with mentions or reviews of bigrquery. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-16.

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

DBI - A database interface (DBI) definition for communication between R and RDBMSs

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

BigQuery-Python - Simple Python client for interacting with Google BigQuery.

easystats - :milky_way: The R easystats-project

rmarkdown - Dynamic Documents for R

sf - Simple Features for R

dbplyr - Database (DBI) backend for dplyr

lab02_R_intro - Vežbe 2: Uvod u R

rudderstack-docs - Documentation repository for RudderStack - the Customer Data Platform for Developers.

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