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invisible_char_cleaner

Official

Efficiently remove invisible characters for cleaner text processing.

Data & Analytics#text processing#data preprocessing#data formatting#text cleaning#character removal
Authorcas-bigdatalab
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill addresses the issue of invisible and disruptive characters in text data, ensuring more accurate processing and analysis.

Core Features & Use Cases

  • Invisible Character Removal: Removes a comprehensive set of 63 invisible characters, including BOM, zero-width spaces, control characters, and others.
  • Customizable Column Selection: Allows users to specify which text columns to process, improving efficiency.
  • Formatting Retention: Option to keep formatting characters like ZWJ/ZWNJ for specific languages.
  • Use Case: Ideal for preprocessing multi-source data, before analysis or before importing into databases.

Quick Start

Run the invisible_char_cleaner skill with the input file path and output file path: python scripts/invisible_char_cleaner.py --input_path input.csv --output_path output.csv

Dependency Matrix

Required Modules

None required

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: invisible_char_cleaner
Download link: https://github.com/cas-bigdatalab/piflow/archive/main.zip#invisible-char-cleaner

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