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numpy-masked

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Handle missing data robustly.

Data & Analytics#data cleaning#missing data#numpy#masked array#robust statistics#numpy.ma
Authorcuba6112
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill addresses the challenge of handling missing or invalid data points within numerical arrays, ensuring that these problematic values do not skew calculations or cause errors.

Core Features & Use Cases

  • Masked Arrays: Integrates with NumPy's masked array functionality to selectively ignore data.
  • Robust Computations: Enables statistical and mathematical operations that automatically exclude masked values.
  • Use Case: When analyzing sensor readings that may contain "no-data" flags (e.g., -999), this Skill ensures that only valid readings contribute to the average or sum.

Quick Start

Use the numpy-masked skill to calculate the mean of an array, ignoring any values equal to -999.

Dependency Matrix

Required Modules

numpy

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: numpy-masked
Download link: https://github.com/cuba6112/skillfactory/archive/main.zip#numpy-masked

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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