numpy-sorting

What problem does it solve?

This Skill provides efficient methods for sorting, partitioning, and searching within NumPy arrays, optimizing data manipulation tasks.

Core Features & Use Cases

• Top-K Selection: Quickly find the k smallest or largest elements in an array without a full sort.
• Hierarchical Sorting: Sort data based on multiple criteria (e.g., by score, then by name).
• Vectorized Search: Efficiently find insertion points for values in sorted arrays.
• Use Case: When analyzing a large dataset, you can use this skill to quickly identify the top 10% of performers based on a specific metric, or to efficiently categorize data points into predefined bins.

Quick Start

Use the numpy-sorting skill to find the top 5 smallest elements in the array [10, 2, 8, 5, 1, 9, 3, 7, 4, 6].