csvkit

csvkit (https://github.com/wireservice/csvkit) has a "csvlook" command, and yq (https://github.com/mikefarah/yq) supports CSV as an input format.

The problem with TSV is what are you going to do about quotes. Some fields might contain them [1] or they might be needed to store fields with tabs inside them. Because of this in order to read a plain simple TSV (fields separated by tabs, nothing more) with the Python csv module [2] you need to set the quote character to an improbable value, say € (using the euro sign because HN won't let me use U+1F40D), or just parse it by hand, e.g. row.split('\t'). [1]: https://github.com/wireservice/csvkit/issues/1194 [2]: https://docs.python.org/3/library/csv.html

Everyone is out here making fancy AI projects and talking about high tech stuff. In the mean time, I wrote this plain bash script to convert .ics files (a format from 1998) to CSV files. This lets you explore your calendar data without needing to setup API access and deal with authorization to your calendar software's API. (common ones all have .ics exports readily available) Combine this with CSV tooling and you got yourself some quick and easy calendar data analysis / exploration setup. Hope you like it! CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller

Csvkit [0] has been my go-to for a while now. I never heard of XSV before, but I will try just about anything with BurntSushi's name on it. Ripgrep is an amazing tool. [0]: https://github.com/wireservice/csvkit

Also csvkit. in2csv data.xls > data.csv in2csv data.json > data.csv csvcut -c column_a,column_c data.csv > new.csv csvcut -c column_c,column_a data.csv > new.csv csvgrep -c phone_number -r 555-555-\d{4}" data.csv > matching.csv csvjson data.csv > data.json csvsql --query "select name from data where age > 30" data.csv > old_folks.csv csvsql --db postgresql:///database --insert data.csv sql2csv --db postgresql:///database --query "select * from data" > extract.csv https://github.com/wireservice/csvkit (Submitted a pull request.)

I love csvkit[0] for this purpose [0] https://github.com/onyxfish/csvkit

CSVKit: https://github.com/onyxfish/csvkit and The R Project for Statistical Computing: http://www.r-project.org/

Cool stuff, and it's written in go! I made a simple ruby version of this a while back: https://github.com/dergachev/csv2sqlite Subsequently also I discovered CSVKIT, a python implementation which is probably more robust: https://github.com/onyxfish/csvkit

I can't speak for this lib, but I've had a lot of success with csvkit [0], json2csv [1] and json directly with jq [2]. [0] https://github.com/onyxfish/csvkit [1] https://github.com/jehiah/json2csv [2] https://github.com/stedolan/jq

Which is why, in similar fashion to awk, we have utilities to deal with JSON [0] and CSV [1] output. [0] https://github.com/stedolan/jq [1] https://github.com/onyxfish/csvkit