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100 lines
3.1 KiB
100 lines
3.1 KiB
3 months ago
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import pandas as pd
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from neo4j import GraphDatabase
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import numpy as np
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# === 配置 ===
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EXCEL_PATH = r"C:\Users\hanyuqing\Desktop\最新国家医保ICD编码\最新国家医保ICD编码\ICD-10医保版数据.xlsx"
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NEO4J_URI = "bolt://localhost:7687"
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NEO4J_USER = "neo4j"
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NEO4J_PASSWORD = "12345678"
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# === 读取 Excel ===
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df = pd.read_excel(
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EXCEL_PATH,
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header=1,
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dtype=str, # 关键：防止 A00.0 变成 A00
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engine='openpyxl'
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)
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# 清理列名
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df.columns = df.columns.astype(str).str.strip()
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# 必需列
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required_cols = [
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"条目（诊断）名称", "条目（诊断）代码",
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"亚目名称", "亚目代码",
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"章代码范围", "节代码范围", "类目代码"
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]
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# 检查列是否存在
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missing = [col for col in required_cols if col not in df.columns]
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if missing:
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raise ValueError(f"缺少必要列: {missing}")
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# 替换 NaN 为 None（便于后续判断）
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df = df.replace({np.nan: None})
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# === 构造 name 和 code 字段（按你的逻辑）===
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def get_disease_name(row):
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diag_name = row["条目（诊断）名称"]
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subcat_name = row["亚目名称"]
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# 如果诊断名称为空（None 或 空白），用亚目名称
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if not diag_name or str(diag_name).strip() == "":
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return str(subcat_name).strip() if subcat_name else None
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return str(diag_name).strip()
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def get_diagnosis_code(row):
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code = row["条目（诊断）代码"]
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# 如果为空，返回空字符串 ""
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if not code or str(code).strip() == "":
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return ""
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return str(code).strip()
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# 应用逻辑
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df["_disease_name"] = df.apply(get_disease_name, axis=1)
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df["_diagnosis_code"] = df.apply(get_diagnosis_code, axis=1)
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# 过滤掉 name 仍为 None 的行（即 诊断名 + 亚目名 都为空）
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df = df[df["_disease_name"].notna() & (df["_disease_name"] != "")]
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print(f"✅ 共准备 {len(df)} 条疾病记录用于导入")
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# === Neo4j 连接 ===
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driver = GraphDatabase.driver(NEO4J_URI, auth=(NEO4J_USER, NEO4J_PASSWORD))
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def upsert_disease(tx, record):
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cypher = """
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MERGE (d:Disease {name: $name})
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ON CREATE SET
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d.diagnosisCode = $diagnosisCode,
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d.chapterRange = $chapterRange,
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d.sectionRange = $sectionRange,
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d.categoryCode = $categoryCode,
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d.subcategoryCode = $subcategoryCode
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ON MATCH SET
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d.diagnosisCode = $diagnosisCode,
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d.chapterRange = $chapterRange,
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d.sectionRange = $sectionRange,
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d.categoryCode = $categoryCode,
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d.subcategoryCode = $subcategoryCode
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"""
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tx.run(cypher, {
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"name": record["_disease_name"],
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"diagnosisCode": record["_diagnosis_code"],
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"chapterRange": record.get("章代码范围") or "",
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"sectionRange": record.get("节代码范围") or "",
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"categoryCode": record.get("类目代码") or "",
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"subcategoryCode": record.get("亚目代码") or ""
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})
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# === 批量导入 ===
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with driver.session() as session:
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for idx, row in df.iterrows():
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try:
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session.execute_write(upsert_disease, row.to_dict())
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except Exception as e:
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print(f"❌ 第 {idx + 2} 行失败: {e}")
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continue
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print("✅ 数据导入完成！")
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driver.close()
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