将Excel中已修改的行更新为SQL Server表

import pandas as pd

# 读取Excel文件
excel_data = pd.read_excel('path_to_excel_file.xlsx')

# 将数据存储在DataFrame对象中
df = pd.DataFrame(excel_data)

import pyodbc

# 连接到SQL Server数据库
conn = pyodbc.connect('DRIVER={SQL Server};SERVER=server_name;DATABASE=database_name;UID=username;PWD=password')

# 执行SQL查询语句，获取表数据
cursor = conn.cursor()
cursor.execute('SELECT * FROM table_name')
sql_data = cursor.fetchall()

# 将数据存储在另一个DataFrame对象中
sql_df = pd.DataFrame(sql_data, columns=[column_name1, column_name2, ...])

# 合并Excel数据和SQL Server表数据
merged_df = pd.merge(df, sql_df, on='id', how='inner')

# 找出已修改的行
modified_rows = merged_df[merged_df['column_name'] != merged_df['column_name']]

# 更新已修改的行
for index, row in modified_rows.iterrows():
    cursor.execute("UPDATE table_name SET column_name1 = ?, column_name2 = ? WHERE id = ?", row['column_name1'], row['column_name2'], row['id'])

# 提交事务
conn.commit()