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Data processing command line-style

Very often I jump to using Python for any sort of data processing. And I totally forget about the powerful tools available on pretty much every Linux/Mac box1.

Jeroen Janssens’s 7 command-line tools for data science presents 6 command line tools for fetching, filtering and transforming data: jq, json2csv, csvkit, scrape, xml2json, sample.

Then Leonardo Trabuco’s Working with data on the command line gives a quick roundup of the standard Linux tools: head, tail, less, awk, cut, sort, uniq, wc, grep, shuf.

If you understand the philosophy of Linux tools and get familiar with some of the tools listed above — I’ve never got too deep into awk and sed almost always tricks me, you’ll be able to do some nice data processing experimentation directly from the command line.

  1. The one excuse I usually find for myself when doing this is that debugging command line tools behavior is not as pleasant as debugging some Python scripts. _Sort of an OK argument, but still an excuse._ 

Original title and link: Data processing command line-style (NoSQL database©myNoSQL)