Data Processing

A comprehensive reference skill for the Polars DataFrame library, providing documentation on data operations, pandas migration patterns, I/O operations, and performance best practices. Designed for users working with in-memory data processing tasks.

FlowIO is a documentation skill that teaches Claude how to help users work with Flow Cytometry Standard (FCS) files. It provides guidance on parsing FCS metadata, extracting event data as NumPy arrays, creating new FCS files, and handling multi-dataset files for scientific flow cytometry data processing.

A comprehensive documentation skill for Dask, a Python library for parallel and distributed computing. It provides detailed reference guides for working with larger-than-memory datasets using DataFrames, Arrays, Bags, and Futures, along with scheduler selection and best practices for performance optimization.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.