README.md

In brendan-newlon/df2neo4j: What the Package Does (One Line, Title Case)

df2neo4j

An R package that lets you load data from a data.frame into a Neo4j graph database with a single line of code. Expanded to include other helpful functions.

Installation

library(devtools)
install_github("brendan-newlon/df2neo4j")
library(df2neo4j)

load_df_to_neo4j

This function allows you to write a data.frame directly to nodes in Neo4j.

Note: The column names of the df will be used to name the properties. Eg. "Name", "Phone", "Email", "Client_ID"

The function writes a .csv file in your Neo4j database import directory, then loads the data to Neo4j. Once done, the .csv file is no longer needed, and it will be overwritten the next time the function is used.

ARGUMENTS

• df The data.frame with data about your nodes and their properties
• label Use label to indicate what type of node is represented in your df. You can assign one or more labels.

• Unique_ID_col Indicate one column that provides a unique ID for each unique node. This could be an ID number or something else that should be unique, such as a personal email address or phone number.

• other_constrain_col Identify any other columns that contain values that should be unique to one node, such as a personal email address.

NOTE: If you've accidentally assigned two different IDs where the person's email address is the same, this will throw an error so you can locate the problem row.

EXAMPLE

load_df_to_neo4j(   
df, 
label = c("Person", "Client"), 
Unique_ID_col = "Client_ID", 
other_constrain_col = c("Email", "Phone")
)

If one df contains data about your individual clients while another holds data about your corporate clients, you can label both as Client while also labeling one set as Person and the other as Organization:

load_df_to_neo4j(
 individual_clients,
 label = c("Person", "Client"),
 Unique_ID_col = "Client_ID",
 other_constrain_col = c("Email", "Phone")
 )

load_df_to_neo4j(
 corporate_clients,
 label = c("Organization", "Client"),
 Unique_ID_col = "Client_ID",
 other_constrain_col = c("Client_Contact_Email", "Client_Contact_Phone")
 )

load_edges_to_neo4j

This function allows you to write a data.frame of relationships between nodes in Neo4j.

The function writes a .csv file in your Neo4j database import directory, then loads the data to Neo4j. Once done, the .csv file is no longer needed, and it will be overwritten the next time the function is used.

Note: The column names of the df must identify the label(s) for the type(s) of nodes you are connecting, but the contents of the columns are unique ID values.

For exammple, the first column might be named "Person" and the values in that column are the value you defined using Unique_ID_col when creating the nodes (See: ?load_df_to_neo4j).

ARGUMENTS

• df.with.labels.as.colnames A data.frame of two columns, with node labels as column names. Eg. "Client". It's ok for both columns to have the same name if they are the same kind of node. If a column is unnamed, I think it will match a node of any label with the unique property value you define.

• a.unique.property The name of a unique property for nodes in the first column. Eg. "Client_ID". Use the name of the unique property exactly as you defined it when you created the nodes.

• b.unique.property The name of a unique property for nodes in the second column. Eg. "Client_ID"

• relationship_in_cypher The relationship to create between the nodes in the first and second columns, written in Cypher code. Relationships can be directed or undirected, and they can be labeled or unlabeled. Cypher is not case-sensitive.

For directed relationships, the head of the arrow indicates direction: * if A likes B, use "-[:Likes]->" * if B likes A, use "<-[:Likes]-" * to define an unlabeled directed relationship from A towards B, use "-->"

For mutual or undirected relationships, no arrow is needed. * if A and B have met, use "-[:Has_Met]-"

NOTE: Only one relationship label can be defined at a time. * If everyone in columns A and B have met and each pair likes the other, run the function once with "-[:Has_Met]-" and run it a second time with "-[:Likes]-"

I hope to add a column for edge weights or other variable properties in the next version.

EXAMPLE:

load_edges_to_neo4j(
df,    
a.unique.property = "Customer_ID", 
b.unique.property = "Item_SKU", 
relationship_in_cypher = "-[:PURCHASED]->"
)

In this example, the df might be two columns named "Customer" and "Product" if those are your node labels

delete_all_neo4j

WARNING: This function deletes all nodes and relationships in your current Neo4j database. The function does not take any arguments.

This function comes in handy if you're developing a repeatable process to build your graph database and you want to repeatedly experiment and return to a blank slate.

EXAMPLE:

delete_all_neo4j() # WARNING - This will delete EVERYTHING in your graph database!

Undocumented functions & shortcuts:

The package contains the following functions as well, but I haven't yet documented their use here. However, some have documentation incorporated into the code itself as comments.

Additional ETL functions for various scenarios:

neo_df

neo_named_nodes

no_na_cols

nodify_col

nodify_cols

edgify_cols

enhance_from_keys

neo.rel

unique_sep_values_of_col

Search functions using the CONTAINS Cypher argument:

neo.search

neo.find.nodes

Shortcuts:

%notin%

as.df

neo

brendan-newlon/df2neo4j documentation built on Sept. 19, 2020, 5:44 a.m.