ZenithTA VS Panther

I have a technical analysis library written for Python using Rust and PyO3 called ZenithTA. A typical Dataframe for a stock has four columns: open, high, low, and close. Currently, I am converting each of the rows into lists to pass into Rust. It would be way easier if the end user could just pass in the dataframe, and I could just manipulate it in Rust. Does anyone have any tips or advice for doing this?

I recently started learning rust and decided to make a python library with PyO3 and NDArray as a first project. With the name Panther, the library was supposed to be an implementation of stock technical indicators (EMA, SMA, RSI, Ect). I added a few functions, and decided to do some speed tests with the pandas way of calculating these indicators. I was shocked to see that my code was about 9x faster on average than pandas calculations. I know this is expected when using a low level language like rust in python, but I'm amazed none the less. Especially as someone new to rust, the fact I could get these "advertised" results with rust in python without having to do crazy optimizations is crazy to me. Plus, something about writing low-level code and getting these results in python is very satisfying. The best part though? The process to get these results wasn't even hard! The cargo packages I used had great documentation and the compiler?! Actually helpful! With reference material on errors too! Officially done geeking out about Rust haha but love this language and love this community. Hoping to get more involved with OS stuff. What project is everyone working on? Anything cool?