Slow data loads, memory-intensive joins, and long-running operations—these are problems every Python practitioner has faced. They waste valuable time and make iterating on your ideas harder than it…
Use polars, or some framework that’s been built with performance from the start?
I have optimized pandas notebooks before, but it seems a bit like a foundation of sand.
plus a GPU-powered drop-in accelerator, cudf.pandas, that delivers order-of-magnitude speedups with no code changes.
Don’t have a GPU on your machine? No problem—you can use cudf.pandas for free in Google Colab, where GPUs are available and the library comes pre-installed.
Use polars, or some framework that’s been built with performance from the start?
I have optimized pandas notebooks before, but it seems a bit like a foundation of sand.
Ah, I see why NVIDIA is writing about it.