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Use Python to read CSV data to generate a simple knowledge map

1. Environment construction

pandas==1.1.5
py2neo==2021.0.1

If py2neo installation fails, please upgrade pip

2. Use steps

1. Import library

import pandas as pd
from py2neo import Graph, Node, Relationship

2. Data display

Some data of accidents and disasters:
insert image description here
Bloggers provide 100 pieces of data for personal learning experiments
Link: https://pan.baidu.com/s/15fjkOMyaxZTVSocWeiRzuQ
Extraction code: qjbx

3. Read data

# 字段映射字典
mapping_dict = {
    
    "发生时间": "occurrence_time",
                "发布时间": "release_time",
                "发生地点": "scene",
                "死亡人数": "death_toll",
                "受伤人数": "injury_toll",
                "直接损失": "direct_loss",
                "事故主体单位": "accident_unit",
                "灾害事故类型": "accident_type",
                "防范与整改": "prevention_rectification",
                "处理建议": "treatment_recommendations",
                "应急措施": "emergency_measure",
                "直接原因": "immediate_cause",
                "严重程度": "order_severity",
                "应急响应": "emergency_response"}
# 读取文件
storage_df = pd.read_csv('database/new.csv', encoding='utf-8')
# 获取列标签
columns_list = storage_df.columns.tolist()
# 获取数据条数
nums = len(storage_df['title'])
# 删除title列标签
columns_list.remove('title')
# 逆转映射字典
new_dic = dict(zip(mapping_dict.values(), mapping_dict.keys()))

4. Connection graph database

# 连接数据库，输入个人配置
graph = Graph("http://localhost:7474//browser/", username='', password='', run="sub")
# 清空全部数据
graph.delete_all()
# 开启一个新的事务
graph.begin()

Refer to the official website for detailed parameters: https://py2neo.readthedocs.io/en/latest/

5. Create knowledge graph

 for i in range(nums):
     data_dict = {
    
    }
     title = storage_df['title'][i]
     for columns in columns_list:
         if str(storage_df[columns][i]) != 'nan':
             data_dict[columns] = storage_df[columns][i]
     # 创建事件节点（主节点），节点属性
     node1 = Node("case", name=title, **data_dict)
     graph.merge(node1, 'case', 'name')
     # 删除id列
     data_dict.pop('id')
     # 创建关系与副节点
     for key, value in data_dict.items():
     	 # 创建副节点
         node2 = Node(key, name=value)
         graph.merge(node2, key, 'name')
         # 创建关系
         rel = Relationship(node1, new_dic[key], node2, type=key)
         graph.merge(rel)

Node attribute data_dict:
insert image description here
Multiple attributes can be added to each node and relationship.

6. Knowledge map display

insert image description here

Summarize

Work essay, I hope it can help everyone!
If there are deficiencies, please advise!

Python creates a knowledge graph

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