我的数据是这样的:

list_data = [{'id': '1', 'city': 'Tokyo', 'country': 'Japan'},
             {'id': '2', 'city': 'Noida', 'country': 'India'},
             {'id': '3', 'city': 'Seoul', 'country': 'South korea'}]

df_data = pd.Dataframe(list_data)

数据库表:

这是一个例子。通常会有更多行要更新。
我想为 ID 为 1、2、3 的行更新列“城市”和“国家/地区”。

一次更新数据库表的代码是什么？

最佳答案

如果您将使用 pandas 写入数据库，那么您会发现使用 SQLAlchemy 而不是原始 DBAPI 连接是有利的。在这种情况下:

from pprint import pprint

import pandas as pd
import sqlalchemy as sa

engine = sa.create_engine("mysql+mysqldb://scott:tiger@localhost:3307/mydb")

# create the test environment
#
with engine.begin() as conn:
    conn.exec_driver_sql("DROP TABLE IF EXISTS table1")
    conn.exec_driver_sql(
        """
        CREATE TABLE table1 (
        id int primary key,
        colour varchar(50),
        city varchar(50),
        code varchar(50),
        country varchar(50)
        )
        """
    )
    conn.exec_driver_sql(
        """
        INSERT INTO table1 (id, colour, code) VALUES 
        (1, 'white', '125'),
        (2, 'red', '48'),
        (3, 'pink', '56'),
        (4, 'yellow', '456'),
        (5, 'white', '213')
        """
    )

list_data = [
    {"id": "1", "city": "Tokyo", "country": "Japan"},
    {"id": "2", "city": "Noida", "country": "India"},
    {"id": "3", "city": "Seoul", "country": "South korea"},
]
df_data = pd.DataFrame(list_data)

# run the test
#
with engine.begin() as conn:
    sql = """
    UPDATE table1 SET city = :city, country = :country
    WHERE id = :id
    """
    params = df_data.to_dict("records")
    conn.execute(sa.text(sql), params)

    pprint(conn.exec_driver_sql("SELECT * FROM table1").fetchall())
    """
    [(1, 'white', 'Tokyo', '125', 'Japan'),
     (2, 'red', 'Noida', '48', 'India'),
     (3, 'pink', 'Seoul', '56', 'South korea'),
     (4, 'yellow', None, '456', None),
     (5, 'white', None, '213', None)]
    """

https://stackoverflow.com/questions/70435792/