Have you ever had two #chromosome 9's? Well today I have.

One more reason that I prefer #R Dataframes to #Python Dataframes (#pandas). In R, there is rarely any uncertainty when it comes to loading in genomic data.

Image1 shows a 140k row table generated with Pandas containing just "9" or "X" for the chromosome.

Image2 shows how that dataset is read easily by R, but misinterpreted by pandas unless you set the datatypes yourself.

I've heard of #chromosome_duplication but this is pushing it

I've wasted literal years dabbling in beautiful looking shells (#fish / #zsh), or trying to enhance my #bash with needlessly bloated decoration frameworks (oh-my-bash/starship), I've decided to roll my own bash prompt in 20 lines.

It shows everything I need: user and host only over ssh, active environments (#conda, venv, or #guix), and the #git branch if I'm in a project.

That's it. Runs quick and easy.

Just add the code (see the alt/hover text in the code image) to your #bashrc, and voila!