Recommendations: Part 1 Solutions¶

In this notebook you will learn how to make recommendations using Neo4j.

Execute the code to import the libraries (remember to unset Reset all runtimes before running):

In [1]:

from py2neo import Graph
import pandas as pd

import matplotlib 
import matplotlib.pyplot as plt

plt.style.use('fivethirtyeight')
pd.set_option('display.float_format', lambda x: '%.3f' % x)
pd.set_option('display.max_colwidth', 100)

Update the cell below to use the IP Address, Bolt Port, and Password, as you did previously.

In [ ]:

# Change the line of code below to use the Bolt URL,  and Password of your Neo4j database instance.
# graph = Graph("<Bolt URL>", auth=("neo4j", "<Password>")) 
 
graph = Graph("bolt://localhost:7687", auth=("neo4j", "letmein"))

Exercise¶

Can you find the top 20 suggested collaborators for 'Brian Fitzgerald'?

In [3]:

query = """
MATCH (author:Author {name: $authorName})<-[:AUTHOR]-(article)-[:AUTHOR]->(coauthor),
      (coauthor)<-[:AUTHOR]-()-[:AUTHOR]->(coc)
WHERE not((coc)<-[:AUTHOR]-()-[:AUTHOR]->(author)) AND coc <> author      
RETURN coc.name AS coauthor, count(*) AS collaborations
ORDER BY collaborations DESC
LIMIT 20
"""

params = {"authorName": "Brian Fitzgerald", "searchTerm": "open source"}
graph.run(query, params).to_data_frame()

Out[3]:

	coauthor	collaborations
0	Holger Giese	5
1	Grace A. Lewis	4
2	Robert C. Seacord	4
3	Gabriel A. Moreno	4
4	Kurt C. Wallnau	4
5	Chris Jensen	4
6	Judith A. Stafford	4
7	Thomas D. LaToza	3
8	Klaus Pohl	3
9	Gerald Bortis	3
10	Ivar Jacobson	3
11	Nicolás López	3
12	Salah Bendifallah	2
13	Thuan Q. Pham	2
14	Gregor Engels	2
15	Pankaj K. Garg	2
16	Gary Thunquest	2
17	Pavel Dmitriev	2
18	Peiwei Mi	2
19	Neil Smith	2

How many of these potential collaborators have collaborated with Brian's collaborators more than 3 times?

In [4]:

query = """
MATCH (author:Author {name: $authorName})<-[:AUTHOR]-(article)-[:AUTHOR]->(coauthor),
      (coauthor)<-[:AUTHOR]-()-[:AUTHOR]->(coc)
WHERE not((coc)<-[:AUTHOR]-()-[:AUTHOR]->(author)) AND coc <> author      
WITH coc, count(*) AS collaborations
WHERE collaborations > 3
RETURN count(*)
"""
graph.run(query, params).to_data_frame()

Out[4]:

	count(*)
0	7

In [ ]: