
"Few tools are more indispensable to my work than Unix. Manipulating data into different formats, performing transformations, and conducting exploratory data analysis (EDA) is the lingua franca of data science.1 The coffers of Unix hold many simple tools, which by themselves are powerful, but when chained together facilitate complex data manipulations. Unix's use of functional composition eliminates much of the tedious boilerplate of I/0 and text parsing found in scripting languages. This design creates a simple and succinct interface for manipulating data and a foundation upon which custom tools can be built. Although languages like R and Python are invaluable for data analysis, I find Unix to be superior in many scenarios for quick and simple data cleaning, idea prototyping, and understanding data. This post is about
how I use Unix for EDA."
Member since:
2007-03-26
That is where Perl and Python (depending on your camp) come into play. However the point of those tutorials is to show that basic data EDA can be done from the command line.
Though stuff like that comes into it's own if you're a sys admin and need to quickly churn through log files. I love working in a CLI but even I wouldn't advocate using Bash et al for analysing large, complex, datasets.
Edited 2012-12-04 00:57 UTC