Remember that pandas is not just a commandline tool. It was started in 2008 in an already strong ecosystem (Numpy, Scipy ...) by someone working full-time on it for his daily work.
My suggestion is, if you're familiar with pandas, and it's the best tool for your job, use it! There is no need to have one tool/language/framework to rule them all in my opinion. Now if you have time, you are more than welcome to contribute (it can be code, documentation, tests, examples). Several people see the potential in Nim for scientific and numerical computing and expressed interest in that ecosystem so you're not alone in that. (Disclaimer: I am building a Numpy/Torch like library in Nim)
