Goals If you are an R developer or data scientist, this guide provides an overview of options for connecting from R to Neo4j and even using Neo4j from within R-Studio. Prerequisites You should be familiar with graph database concepts and… Read more →

Goals
If you are an R developer or data scientist, this guide provides an overview of options for connecting from R to Neo4j and even using Neo4j from within R-Studio.
Prerequisites
You should be familiar with graph database concepts and the property graph model. You should have installed Neo4j and made yourself familiar with our Cypher Query language.
Intermediate


Neo4j for R Developers and Data Scientists

Rlogo

Neo4R

The goal of {neo4r} is to provide a modern and flexible Neo4J driver for R.

It’s modern in the sense that the results are returned as tibbles whenever possible, it relies on modern tools, and it is designed to work with pipes. Our goal is to provide a driver that can be easily integrated in a data analysis workflow, especially by providing an API working smoothly with other data analysis ({dplyr} or {purrr}) and graph packages ({igraph}, {ggraph}, {visNetwork}…).

It was developed by ThinkR, led by Colin Fay.

Currently it connects to Neo4j via Http but we plan to integrate it with the C-connector for Bolt, Seabolt.

Author

Colin Fay

Package

Source

https://github.com/neo4j-rstats/neo4r

Neo4j-Rstats

https://github.com/neo4j-rstats/

Neo4j Online Community

https://community.neo4j.com/c/drivers-stacks/r

Docs

https://neo4j-rstats.github.io/user-guide/

Protocols

Http