其实就是按行解析csv文件,并将其中数据分为“结点”、“关系”两种类型,构建利用Node()方法构建节点;Relationship()方法构建关系
csv结构
entity1,relation1,entity2,relation2,info,relation3,keyword 人格纠纷权,包含,一般人格权纠纷,描述,一般人格权纠纷是指因侵害他人的一般人格权,使他人的人格利益受损而引起的纠纷。,关键词,人格权、纠纷、指因、人格、利益
from py2neo import Graph, Node, Relationship import pandas as pd df = pd.read_csv('crime.csv', error_bad_lines=False, encoding='utf-8') df = df.fillna('unknown') #填充缺失值 new = df['entity1'].str.strip() df['entity1'] = new new = df['entity2'].str.strip() df['entity2'] = new new = df['info'].str.strip() df['info'] = new new = df['keyword'].str.strip() df['keyword'] = new new = df['relation1'].str.strip() df['relation1'] = new new = df['relation2'].str.strip() df['relation2'] = new new = df['relation3'].str.strip() df['relation3'] = new # 连接neo4j数据库,输入地址、用户名、密码 graph = Graph("http://localhost:7474", username="neo4j", password='password') graph.delete_all() graph.begin() # 创建结点 for i in range(len(df['entity1'])): #设置node node1 = Node('entity1', name=df['entity1'][i]) graph.merge(node1, 'entity1', 'name') node2 = Node('entity2', name=df['entity2'][i]) graph.merge(node2, 'entity2', 'name') node3 = Node('info', name=df['info'][i]) graph.merge(node3, 'info', 'name') node4 = Node('keyword', name=df['keyword'][i]) graph.merge(node4, 'keyword', 'name') #设置relation rel1 = Relationship(node1, df['relation1'][i], node2) rel2 = Relationship(node2, df['relation2'][i], node3) rel3 = Relationship(node3, df['relation3'][i], node4) graph.merge(rel1) graph.merge(rel2) graph.merge(rel3) print("success")
原创文章,作者:端木书台,如若转载,请注明出处:https://blog.ytso.com/tech/database/267345.html