Neo4j create nodes and relationships from pandas dataframe with py2neo

Question

Getting results on a pandas dataframe from a cypher query on a Neo4j database with py2neo is really straightforward, as:

>>> from pandas import DataFram         


        

Answer 1

You can use DataFrame.iterrows() to iterate through the DataFrame and execute a query for each row, passing in the values from the row as parameters.

for index, row in df.iterrows():
    graph.run('''
      MATCH (a:Label1 {property:$label1})
      MERGE (a)-[r:R_TYPE]->(b:Label2 {property:$label2})
    ''', parameters = {'label1': row['label1'], 'label2': row['label2']})

That will execute one transaction per row. We can batch multiple queries into one transaction for better performance.

tx = graph.begin()
for index, row in df.iterrows():
    tx.evaluate('''
      MATCH (a:Label1 {property:$label1})
      MERGE (a)-[r:R_TYPE]->(b:Label2 {property:$label2})
    ''', parameters = {'label1': row['label1'], 'label2': row['label2']})
tx.commit()

Typically we can batch ~20k database operations in a single transaction.