数据中台与智慧：构建高效的数据处理体系

        import pandas as pd
        # 读取销售系统的CSV文件
        sales_data = pd.read_csv('sales_data.csv')
        
        # 从CRM系统获取数据
        import requests
        response = requests.get('https://crm.example.com/api/customers')
        crm_data = response.json()
        
        # 将JSON转换为DataFrame
        crm_df = pd.DataFrame(crm_data)
        
        # 合并两个数据集
        combined_data = pd.merge(sales_data, crm_df, on='customer_id')
        
        # 输出结果
        print(combined_data.head())
      

        from sklearn.model_selection import train_test_split
        from sklearn.linear_model import LinearRegression
        
        # 准备特征和标签
        X = combined_data[['product_type', 'region']]
        y = combined_data['sales']
        
        # 划分训练集和测试集
        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
        
        # 训练模型
        model = LinearRegression()
        model.fit(X_train, y_train)
        
        # 预测
        predictions = model.predict(X_test)
        print(predictions)