Jeroen Janssens famously argued that the command line is a ‘hidden gem’ for data science. It’s not about avoiding Python or R—it’s about knowing when to use them.

When to stay in the Terminal:

  • When you are exploring raw data (head, tail, cut).
  • When you are cleaning messy CSVs (sed).
  • When you need a quick count or sum (awk).

When to move to Python:

  • When you need complex machine learning models.
  • When you need advanced visualization (plotting graphs).
  • When the data logic requires deep nesting that makes awk unreadable.

For the Textsmith, the terminal is the first stop. Most of the time, it’s the only stop you’ll need.

Forged in the terminal. Refined under the anvil.