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scientific-data-preprocessing

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Reproducible data preprocessing for science

Data & Analytics#pipeline#encoding#scaling#reproducible#imputation#outliers#data-preprocessing
Authornahisaho
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill provides a structured, reproducible template for scientific data preprocessing, covering data cleaning, transformation, and normalization to ensure consistent experiment results.

Core Features & Use Cases

  • Data quality checks and reporting
  • Missing value imputation (median/KNNImputer/SimpleImputer)
  • Outlier detection and handling
  • Encoding of categorical variables
  • Scaling and transformation options
  • Pipeline integration across CSV/DataFrame workflows (Exp-01〜13)

Quick Start

Apply the preprocessing_pipeline to your DataFrame with a config and save the outputs to results/preprocessed_data.csv and results/preprocessing_summary.json.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: scientific-data-preprocessing
Download link: https://github.com/nahisaho/satori/archive/main.zip#scientific-data-preprocessing

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