python operation neo4j creating knowledge map template

Data: Name of purchaserName of selleramount of moneyElectr...

Data:

Name of purchaser

Name of seller

amount of money

Electronic toll center of Shandong Expressway Group Co., Ltd

Harbin told the company

2000W level transaction

Hunan daoyue expressway industry Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

2000W level transaction

Hunan daoyue expressway industry Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

100W level transaction

Hunan daoyue expressway industry Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

2000W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

2000W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

2000W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hubei a Shen Nan Expressway Development Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hubei CCCC Jiatong Expressway Development Co., Ltd

2000W level transaction

Hubei a Shen Nan Expressway Development Co., Ltd

Hunan daoyue expressway industry Co., Ltd

100W level transaction

Hubei a Shen Nan Expressway Development Co., Ltd

Hunan daoyue expressway industry Co., Ltd

500W level transaction

Hubei a Shen Nan Expressway Development Co., Ltd

Hunan daoyue expressway industry Co., Ltd

100W level transaction

Hubei a Shen Nan Expressway Development Co., Ltd

Hunan daoyue expressway industry Co., Ltd

500W level transaction

Hubei CCCC Jiatong Expressway Development Co., Ltd

Hunan daoyue expressway industry Co., Ltd

2000W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hunan daoyue expressway industry Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hunan daoyue expressway industry Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hunan daoyue expressway industry Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Hunan daoyue expressway industry Co., Ltd

2000W level transaction

Hunan daoyue expressway industry Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

8000W level transaction

Hunan daoyue expressway industry Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

8000W level transaction

Hunan daoyue expressway industry Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

2000W level transaction

Hunan daoyue expressway industry Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

2000W level transaction

Modern Investment Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

8000W level transaction

Modern Investment Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

8000W level transaction

Modern Investment Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

2000W level transaction

Modern Investment Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

2000W level transaction

Modern Investment Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

2000W level transaction

Modern Investment Co., Ltd

Electronic toll center of Shandong Expressway Group Co., Ltd

2000W level transaction

Hunan daoyue expressway industry Co., Ltd

Modern Investment Co., Ltd

8000W level transaction

Hunan daoyue expressway industry Co., Ltd

Modern Investment Co., Ltd

8000W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Modern Investment Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Modern Investment Co., Ltd

500W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Modern Investment Co., Ltd

2000W level transaction

Electronic toll center of Shandong Expressway Group Co., Ltd

Modern Investment Co., Ltd

100W level transaction

from py2neo import Node, Graph, Relationship, NodeMatcher import pandas as pd class DataToNeo4j: def __init__(self): # Connect to database link = Graph("http:localhost:7474", username="neo4j", password="rhino1qaz@wsx") self.graph = link # Establish node self.buy = "buy" self.sell = "sell" self.graph.delete_all() # Empty the database first self.matcher = NodeMatcher(link) # Then define a matcher def create_node(self, node_buy_key, node_sell_key): """Establish node""" for name in node_buy_key: buy_node = Node(self.buy, name=name) self.graph.create(buy_node) for name in node_sell_key: sell_node = Node(self.sell, name=name) self.graph.create(sell_node) def create_relation(self, df_data): """Establish contact""" for m in range(0, len(df_data)): # print(df_data['buy'][m], df_data['money'][m], df_data['sell'][m]) rel = Relationship(self.matcher.match(self.buy).where("_.name=" + "'" + df_data['buy'][m] + "'").first(), df_data['money'][m], self.matcher.match(self.sell).where("_.name=" + "'" + df_data['sell'][m] + "'").first()) self.graph.create(rel) class Processor: def __init__(self, path): self.invoice_data = pd.read_excel(path, header=0) def node_extraction(self): # Take the buyer's name to the list node_buy_key = self.invoice_data['Name of purchaser'].tolist() node_sell_key = self.invoice_data['Name of seller'].tolist() # Remove duplicate invoice names node_buy_key = list(set(node_buy_key)) node_sell_key = list(set(node_sell_key)) return node_buy_key, node_sell_key def relation_extraction(self): """Contact data extraction""" links_dict = {} sell_list = [] money_list = [] buy_list = [] for i in range(0, len(self.invoice_data)): money_list.append(self.invoice_data[self.invoice_data.columns[19]][i]) # amount of money sell_list.append(self.invoice_data[self.invoice_data.columns[10]][i]) # Name of seller buy_list.append(self.invoice_data[self.invoice_data.columns[6]][i]) # Name of purchaser # Convert all int types in the data to string sell_list = [str(i) for i in sell_list] buy_list = [str(i) for i in buy_list] money_list = [str(i) for i in money_list] # Integrate the data and integrate the three list s into a dict links_dict['buy'] = buy_list links_dict['money'] = money_list links_dict['sell'] = sell_list # Convert data to DataFrame df_data = pd.DataFrame(links_dict) return df_data if __name__ == '__main__': # dataToNeo4j = DataToNeo4j() path = './Invoice_data_Demo.xls' processor = Processor(path) node_buy_key, node_sell_key = processor.node_extraction() print(node_buy_key) print(node_sell_key) df_data = processor.relation_extraction() dataToNeo4j = DataToNeo4j() dataToNeo4j.create_node(node_buy_key, node_sell_key) dataToNeo4j.create_relation(df_data)

result:

24 November 2021, 01:17 | Views: 8625

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