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.
- 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.
When you are still figuring out things step by step, pandas does a lot of heavy lifting for you so you don't have to think about it.
E.g. I don't have to think about timeseries alignment, pandas handles that for me implicitly because dataframes can be indexed by timestamps. Polars has timeseries support, but I need to write a paragraph of extra code to deal with it.
