Unverified50% confidenceBenchmarkExact time
据CrowdFlower 2016年行业调查及后续研究，数据科学家约60%-80%的工作时间消耗在数据清洗与预处理阶段
1
Sources
50%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
Getting Started with Pandas: How to Choose Tutorials and Efficient Practice Resources
redditr/learnmachinelearning7/10/2026
Related Claims
UnverifiedIn real-world work, data scientists often need to spend 60% to 80% of their time on data collection, cleaning, and problem definition.82% similarVerifiedIn real industrial environments, data scientists typically spend 60%-80% of their time on data cleaning and feature engineering, rather than model tuning.82% similarVerifiedIn actual machine learning projects, data preprocessing typically accounts for 60%–80% of the workload.67% similarUnverified80% of the success or failure of fine-tuning depends on data quality, and data preparation typically accounts for 60%–70% of the total project workload.66% similarUnverified微调过程中，数据清洗、格式标准化、指令-回答对的质量控制往往占据整个微调流程70%以上的工作量65% similar
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