As a data scientist, a lot of time is spent into parsing and processing data to transform it into a nicer format that can be easily fed to whichever algorithm is being used. This process is often known as ETL.

There are a number of tools for the job ranging from command line utils, language libraries, and even whole products that go all the way to Petabyte scale (e.g., Spark).

Here I will give one tip for a unix/linux command line util that is often forgotten but that has a lot of functionality, it is fast and memory efficient (can process tens of thousands of rows per second, scale to multiple cores by using unix pipelining), and it is available pretty much anywhere (while your preferred tool or library might not). The awesome AWK!

Now, AWK can do pretty much anything, but here are just 2 bits that are exceptionally useful as a starting point of our data processing.

1. Select by column (e.g, select a field of a csv file) is achieved by using the special variable $i where i is the column position we want to select, e.g., to print the second column
   #awk -F "\"*,\"*" '{print $2}' filename.csv
2. Select by row (e.g., iterate through a csv file) is achieved using the built-in variable FNR, e.g., to print the second row
   #awk 'FNR == 2 {print}' filename.csv

For a primer you can look HERE. Happy AWKing! 😎