# Some basic tips on using the command line for data work

4 minute read

I’ve been challenging myself to write down the most common command line commands I use day to day to work with data. This post is about the list I came up with, it does not have any pretence to be exhaustive nor general/agreed by everyone. In fact, I don’t even think these are really all of the most common commands I use - I may have forgotten several.

Also, the commands I’m listing here are quite basics ones, they’re likely amongst the most common commands used overall, but that’s also why I use them all the time so I thought I’d share anyway - this can help people who are maybe at the start of their data science journey, or just work as a little cheatsheet. Note that J Janssens has written a fantastic book about using the command line for data science.

Note that these commands will refer to a Unix system.

# Explore what’s in directories, and how much it occupies

You’re somewhere and you don’t know where?

• pwd (print work directory) is your friend
• you can cd (change directory) to go somewhere
• ls (list) will show you what’s in there, ls -la will show you in long listing (-l) and including hidden files -a
• du (disk usage) will show you the occupancy of said material, flag -h will do that in human-readable form

# Manipulate things

• mv (move) is to move files and directories (you need a -r flag in that case), it’s also used for renaming
• rm will remove files (with flag -r will remove a directory)
• cp (copy) will copy data (files/directories)

# Simple stats on a file, or counting what’s in a directory

wc (word count) is great, it will allow you to count lines of a file as well as (as per the name) the tokens in it.

• wc -l is for when you quickly need to know how many lines are there in a file, it’s very useful e.g. for a CSV when running Python to do this or opening the file in an editor would be overkill
• wc -w will count the tokens (words) instead, where the separators used to determine what’s a word are spaces, tabs and newlines

There are other useful options to wc. I often use it in conjunction with ls to count the number of files in a folder, as

ls <directory_name> | wc -l


Note that the pipe (|) is what lets you concatenate commands such that you create a nested structure for instructions: in this case the output of ls, which is the list of files in my folder, gets fed to wc so that (given the use of the flag) lines are counts, and the overall result is the count of items in the folder.

# Various utilities

• history will show you the last (how many?) commands you’ve used - very useful
• man <command> will show you the command manual, I often skip overlook myself and go directly for googling, but it’s a good practice instead (and will possibly reinforce your memory more…)
• grep is used to fetch strings

# Monitor running programs

If I’ve run a Jupyter in the background (or anything else), I can fetch it easily.

• pgrep jupyter - this will search by pattern (in this case “jupyter”), looking for all running jobs matching what I wrote, and will return me the PID (process ID)
• kill <PID> allows me to kill the job, note that kill -9 will run the signal KILL (SIGKILL), which will force kill it - there are other signals
• killall is extreme, it’ll kill all processes

# Compressing data

I work with various machines and often need to move data from one to the other - if it’s a directory and it’s rather big I prefer to ZIP it up beforehand, using command zip. Then I unzip with unzip. Easy. But because I can never remember the syntax of these, I make great use of history to recall this, like history | grep zip, which will show all places in the history I wrote something contaning “zip”. Anyway, the syntaxes for my most common use cases are:

• zip -r <zipped_filename> <folder_to_zip>
• unzip <filename_to_unzip> -d <unzipped_folder_to_create>

# Quickly look at a file

When I have a CSV and I don’t know the header (so I don’t know the columns), a quick way is to head the file (again, to avoid having to call Python to do this, or to open it in a text editor) - head will show the first lines (you can also ask for a certain number of them). The polar opposite is tail - it shows the ending lines.

# Using text editors from the terminal

What’s your favourite text editor?

You can call them from the terminal of course, but more often then not when I need to quickly inspect the content of a file, or do some little edits (the king example is the bash profile) I use nano to open it directly from the terminal. vim is another one.

# References

1. J Janssens, Data Science at the Command Line, a wonderful O’Reilly book - note that as of now there is a second edition coming up

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