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电子商务交易数据集

发布时间：2026-03-17 14:31:42资源ID：2031896442913067009资源类型：免费

该数据集《E - Commerce Transactions Dataset》主要用于二分类任务，数据形态以表格为主，应用场景偏向金融风控。 题目说明：A synthetic dataset of 50K e - commerce transactions with user and purchase detail 任务类型：表格二分类。 建议流程：先做缺失值/异常值处理与特征编码，再比较逻辑回归、随机森林、XGBoost。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：ecommerce_transactions.csv。 Overview This dataset contains 50,000 fictional e - commerce transaction records, making it ideal for data analysis, visualization, and machine learning experiments. It includes user demographics, product categories, purchase amounts, payment methods, and transaction dates to help understand consumer behavior and sales trends. Columns Transaction_ID – Unique identifier for each transaction User_Name – Randomly generated user name Age – Age of the user (18 to 70) Country – Country where the transaction took place (randomly chosen from 10 countries) Product_Category – Category of the purchased item (e.g., Electronics, Clothing, Books) Purchase_Amount – Total amount spent on the transaction (randomly generated between $5 and $1000) Payment_Method – Method used for payment (e.g., Credit Card, PayPal, UPI) Transaction_Date – Date of the purchase (randomly selected within the past two years)

电子商务交易数据集

摘要概览

该数据集《E - Commerce Transactions Dataset》主要用于二分类任务，数据形态以表格为主，应用场景偏向金融风控。 题目说明：A synthetic dataset of 50K e - commerce transactions with user and purchase detail

任务类型：表格二分类。

建议流程：先做缺失值/异常值处理与特征编码，再比较逻辑回归、随机森林、XGBoost。

评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。

可用文件：ecommerce_transactions.csv。

Overview

This dataset contains 50,000 fictional e - commerce transaction records, making it ideal for data analysis, visualization, and machine learning experiments. It includes user demographics, product categories, purchase amounts, payment methods, and transaction dates to help understand consumer behavior and sales trends.

Columns

Transaction_ID – Unique identifier for each transaction User_Name – Randomly generated user name Age – Age of the user (18 to 70) Country – Country where the transaction took place (randomly chosen from 10 countries) Product_Category – Category of the purchased item (e.g., Electronics, Clothing, Books) Purchase_Amount – Total amount spent on the transaction

(randomly generated between $5 and $1000) Payment_Method – Method used for payment (e.g., Credit Card, PayPal, UPI) Transaction_Date – Date of the purchase (randomly selected within the past two years)