For those looking for a modern take on improving on the CSV format, I'd recommend Frictionless Data's Datapackage specification[1] which basically consists of a json file of metadata that accompanies a CSV file that describes column types, versions, sources, and how to validate correctness of the CSV's data. This allows for quite a lot of tooling and workflow improvements to CSV files without mucking with the CSV itself
Another hack to improve CSV workflows is OCHA's HXL[2] that is used by humanitarian organizations. Basically adding a row of hashtags in addition to column names, which is surprisingly useful considering the ease of adding these to a file.
Another hack to improve CSV workflows is OCHA's HXL[2] that is used by humanitarian organizations. Basically adding a row of hashtags in addition to column names, which is surprisingly useful considering the ease of adding these to a file.
[1] https://frictionlessdata.io/docs/tabular-data-package/ [2] http://hxlstandard.org/