经过pd.to_sql()将DataFrame写入Mysql

import pandas as pd from sqlalchemy import create_engine from sqlalchemy.types import NVARCHAR, Float, Integer def pd2sql(): """ to_sql目前只支持两类mysql引擎一个是sqlalchemy和sqlliet3 :return: """
    # 初始化数据库链接，使用pymysql模块
    # MySQL的用户：root, 密码:147369, 端口：3306,数据库：mydb
    # ?charset=utf8 指定数据库编码
    engine = create_engine('mysql+pymysql://root:@localhost:3306/pandas2mysql?charset=utf8') conn = engine.connect() for i in range(1, 10): # 指定字段的数据类型
        dtypedict = { 'index_code': NVARCHAR(length=255), 'date': NVARCHAR(length=255), 'open': NVARCHAR(length=255), 'close': NVARCHAR(length=255), 'low': NVARCHAR(length=255), 'high': NVARCHAR(length=255), 'volume': NVARCHAR(length=255), 'money': NVARCHAR(length=255), 'change': NVARCHAR(length=255) } csv_path = r'E:\data\yucezhe\trading-data-push.20190201\2019-02-01 index data.csv'

        # 读取本地CSV文件
        df = pd.read_csv(csv_path).head() # 将DataFrame储存为MySQL中的数据表，不储存index列
        df.to_sql(f'csv_table{i}', engine, if_exists='replace', index=False, dtype=dtypedict) # 执行原生sql语句
        # 设置主键
        conn.execute(f"alter table csv_table{i} add constraint p_key primary key (index_code)") # 从表设置外键
        if i%2 == 0: conn.execute( f"alter table csv_table{i-1} add foreign key (index_code) references csv_table{i}(index_code)") print(f"Write to MySQL successfully! ---- csv_table{i}") engine.dispose() pd2sql() # 对已存在的表作主键：alter table csv_short1 add constraint p_key primary key (index_code);

# 对已存在的表作外键：alter table csv_short1 add foreign key (index_code) references csv_short2(index_code);

# 内链接查询：select * from a,b where a.x = b.x