Cudf Analytics

You get groupby aggregations, statistical summaries, and anomaly detection with the same API you already know, just faster on large datasets. The initialization block is actually useful since it includes a real GPU compute test and graceful pandas fallback, not just import checking. Best for CSV analysis where you're doing repeated aggregations or correlation work on millions of rows. The to_pandas() wrapper with Arrow fallback handles the common gotcha where GPU to host transfers fail. If your dataset fits in memory and you're doing one pass analysis, the speedup might not justify the GPU dependency.