I'm a college student who has recently learned pandas, and I'm planning to start freelancing with pandas, NumPy, and openpyxl. I'm interested in gigs involving data cleaning, Excel automation, and report generation. While researching openpyxl, I saw descriptions saying it works with Excel 2010 files, which made me wonder whether the library is outdated. Is openpyxl still relevant for modern Excel work, and is it a useful skill to learn for freelance projects?
4 Answers
Excel is still deeply embedded in business, especially in finance, HR, operations, and reporting. For freelance automation, the ability to manipulate the actual workbook—not just export a plain table—is valuable. Many clients want a finished spreadsheet with specific formatting, formulas, multiple sheets, and a familiar workflow. Openpyxl is a practical choice for that kind of work and is easy to deploy when the client doesn’t have Excel or Python installed.
Yes, it’s still very relevant. The “Excel 2010” wording mostly refers to the XLSX format introduced around that time. That format is still widely used, and openpyxl remains useful for reading and writing workbooks, editing cells, applying styles, setting column widths, freezing panes, adding formulas, and generating polished reports. Pandas also commonly relies on it when working with modern .xlsx files.
Also consider the client’s environment before choosing the technology. Power Query or VBA can sometimes be easier for Excel users to maintain, while Python is better suited to backend automation and repeatable data pipelines. If you need Excel itself to calculate features or preserve more of the application’s behavior, xlwings can be useful, but it requires Windows and an installed copy of Excel. For portable .xlsx file manipulation, openpyxl is usually the simpler option.
That makes sense. I’ll start with pandas and openpyxl, then learn the other tools as I run into projects where they’re a better fit.
Learn it, but understand its limits. It’s a good fit for ordinary-sized files and workbooks where you need to inspect or modify individual cells, ranges, formulas, styles, named ranges, or worksheet structure. For very large files or performance-sensitive ingestion, tools such as Polars, DuckDB, fastexcel, or calamine may be faster. Those are alternatives for specific workloads, not evidence that openpyxl is obsolete.
That’s the important distinction: pandas is great for transforming tabular data, while openpyxl lets you control the workbook itself. You’ll often use both in the same project.