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ADVICE: Save yourself and colleagues loads of time, by taking a few suggestions into account before using Excel.

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Well-meaning people using Excel, are without realizing it, too often making analysts and coders cry for inefficiency reasons. This is very costly, both financially and emotionally, and must be improved:

  • I suggest to have everybody invest a few hours in "Data Organization in Spreadsheets ...", from the awesome carpentries.org, for which I am a certified instructor. "We teach foundational coding and data science skills to researchers worldwide."
  • Advertise that course, this page, or your own, widely in contexts, including in the default 'new Excel sheet'.
  • Try a pre-structured spreadsheet, like what I made a rough sketch for in the Excel file in this repo.
  • When the 'damage' is already done, and you have to figure out the (implicit and hidden?) structure of an already existing Excel spreadsheet, look at https://mobile.twitter.com/steltenpower/status/1330290665322934278
  • Questions will arise and Digital Competence Centers and the like should be great at answering them
  • It is not uncommon that finding and cleaning of data takes way more time than everything else in a project. Put that in your planning and make sure managers read it, to make sure they think about investing in data quality.
  • (Mental note: Excel's comma-delimited .csv is actually semi-colon (;) delimited. See if there are carpentries.org courses to explain this and maybe mention how to roundtrip from Python/R with Excel on CSV)
  • Why electronic notebooks make you work together faster and fewer errors
  • If datacarpentry and softwarecarpentry sound scary, try Library Carpentry

If you actually want or need further structuring of data:

Excel is not all bad if you know how to use it, plus there are nice extensions:

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ADVICE: Save yourself and colleagues loads of time, by taking a few suggestions into account before using Excel.

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