地球资源数据云——数据资源详情
最新数据科学工作薪资 2020 - 2025
该数据集《Latest Data Science Job Salaries 2020 - 2025》主要用于监督学习任务，数据形态以表格为主，应用场景偏向交通/汽车。 题目说明：Exploring Salary Dynamics and Employment Trends in Data Science Careers 任务类型：表格监督学习。 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：DataScience_salaries_2025.csv。 This dataset provides insights into data science job salaries from 2020 to 2025, including information on experience levels, employment types, job titles, and company characteristics. It serves as a valuable resource for understanding salary trends and factors influencing compensation in the data science field. Features: | Feature | Description | | work_year | The year of the data related to the job salary. | | experience_level | The level of experience of the employee (e.g., entry - level, mid - level, senior - level). |
摘要概览
该数据集《Latest Data Science Job Salaries 2020 - 2025》主要用于监督学习任务，数据形态以表格为主，应用场景偏向交通/汽车。 题目说明：Exploring Salary Dynamics and Employment Trends in Data Science Careers
任务类型：表格监督学习。
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：DataScience_salaries_2025.csv。
This dataset provides insights into data science job salaries from 2020 to 2025, including information on experience levels, employment types, job titles, and company characteristics. It serves as a valuable resource for understanding salary trends and factors influencing compensation in the data science field.
Features:
| Feature | Description |
| work_year | The year of the data related to the job salary. |
| experience_level | The level of experience of the employee (e.g., entry - level, mid - level, senior - level). |