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Pretty much every programming language in existence has a utility for parsing CSVs into tabular data while handling commas sanely. (using awk for processing is not a typical pipeline)

More importantly, CSVs are handled natively by statistical programs such as Excel and R (you can change the expected delimiter while importing, but in my experience that leads to unexpected results)




Microsoft often fails with CSVs actually. I've found I can't copy/paste from Sql Server Management Studio into Excel if you have a mismatched double-quote in a cell - it fails silently and garbles your data.

That was embarrassing.

The CSV format is so messy that even big corporate implementations will have subtle bugs like that. Do not trust it.


Microsoft excel has the worst CSV defaults. The separating character is even locale-specific! Many locales use semicolon ";" instead of "," as a separator. Great stuff when creating web app exporters.


> using awk for processing is not a typical pipeline

except it is. (g)awk is more often part of the pipe(d)line than other programming langueage(s) interpreter(s).


>More importantly, CSVs are handled natively by statistical programs such as Excel and R

in excel or R? Because I've never encountered problems with tsv files with excel


R can also read both CSV and TSV just fine. Just use read.csv() or read.table() as you want. Same goes for Pandas.


Excel can handle TSV's if you name them .txt




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