number_noise_cleaner

Official

Clean text data by removing non-semantic numbers.

Authorcas-bigdatalab
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill addresses the issue of cleaning text data by removing non-semantic numbers from structured text fields.

Core Features & Use Cases

  • Non-Semantic Number Removal: Removes numbers that do not contribute meaning to the text.
  • Text Field Cleaning: Cleans specified or all text fields based on user input.
  • Use Case: Ideal for cleaning data from text fields in CSV, TSV, Excel, and SPSS files, ensuring that only meaningful information remains.

Quick Start

Run the number_noise_cleaner skill with the following command: number_noise_cleaner --input_path path/to/input.csv --output_path path/to/output.csv

Dependency Matrix

Required Modules

pandas

Components

scripts

💻 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: number_noise_cleaner
Download link: https://github.com/cas-bigdatalab/piflow/archive/main.zip#number-noise-cleaner

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