技术博主Dr. Drang发表文章阐述了他对电子表格的使用态度[1]。他的核心原则是"不使用电子表格"[1]。基于十多年来处理工程师发来的复杂Excel文件的经验，作者解释了这一立场的原因，并列举了两个允许的例外情况[1]。
Excel的行数限制为1,048,576行，而Numbers的限制为1,000,000行[1]。作者以美国婴儿姓名数据集为例进行了工具对比，该数据集包含2,181,032条记录，已超过Excel的行数限制[1]。在这类场景下，使用电子表格显然不适合处理大规模数据。
作者认可的两个例外情况分别是：问题规模足够小且操作足够简单的情况，以及将电子表格作为编辑和传输数据的中转站[1]。对于更复杂的数据分析工作，Dr. Drang现已转向使用Python Pandas和SQLite等工具[1]。他还提到了Reinhart/Rogoff论文中的电子表格错误，以此说明电子表格使用不当带来的风险[1]。
Dr. Drang has published a technical essay outlining his philosophy on spreadsheet usage, rooted in over a decade of experience handling complex Excel files from engineers [1]. His primary rule is straightforward: avoid spreadsheets altogether [1]. However, he acknowledges two specific exceptions to this principle—when a problem is sufficiently small with straightforward operations, and when spreadsheets serve as a temporary intermediary for data editing [1].
The author illustrates the limitations of spreadsheet applications through practical examples, noting that Excel can accommodate up to 1,048,576 rows while Numbers supports 1,000,000 rows [1]. He references the U.S. baby names dataset, which contains 2,181,032 records, demonstrating how common data sources exceed these constraints [1]. To highlight the risks of relying on spreadsheets for complex analysis, he cites errors found in the Reinhart-Rogoff economic paper that were traced to spreadsheet mistakes [1].
Rather than defaulting to spreadsheets, Dr. Drang advocates for alternative tools suited to data-intensive work. He now employs Python Pandas and SQLite for data analysis tasks, tools he presents as more appropriate for handling substantial datasets and reducing the errors that can arise from spreadsheet manipulation [1].