- Pandas is interwoven into downstream projects. So it will be here to stay for a long time. This is good for maintenance and stability. Advantage: Pandas.
- OTOH, the Pandas experience is awful; this was obvious to many from the outset, and yet it persisted. I haven't tracked the history. But my guess would be the competition from Polars was a key pressure for improvement. Edge: Polars.
- Lots of Python projects are moving to Rust-backed tooling: uv, Polars, etc. Front-end users get the convenience of Python and tool-developers get the confidence & capabilities of Rust. Edge: Polars.
- Pandas has a governance structure not tied to one company. Polars does not. (comment above said this) Advantage: Pandas.
But this could change. Polars users could (and may already be?) pressing for company-independent governance.
Wes came to my local PUG in like 2011 or 2012 and did a talk showing it off. It was also the first time I saw jupyter, which was the ipython notebook at the time. I remember being blown away by both, but I so rarely need dataframes that im sure i don’t know what im missing. I mostly only ever use it for manipulating time series data.
Pandas on the other hand has been open source for almost two decades, and is supported by many companies. They have a governance board, and an active community. The risk of it going off the rails into corporate nonsense is much lower.