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DC2_SpaceCleaning

Official

Efficiently remove extra spaces from strings in structured data files

Data & Analytics#structured data#data cleaning#data preprocessing#text normalization#CSV processing
Authorcas-bigdatalab
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill addresses the common issue of extraneous spaces in data fields within structured files like CSV, TSV, Excel, and SPSS, which can disrupt data analysis and reporting.

Core Features & Use Cases

  • Space Removal: Strip leading and trailing spaces from string fields across various structured file formats.
  • File Format Support: Works with CSV, TSV, Excel, and SPSS files, ensuring compatibility with various data sources.
  • Use Case: For instance, when importing data for analysis and noticing inconsistent spacing in textual fields, this skill can quickly clean up the data, ensuring accurate processing.

Quick Start

To clean extra spaces from a CSV file named 'sales_data.csv', you would run:

python scripts/DC2_SpaceCleaning.py --input_path sales_data.csv --output_path cleaned_sales_data.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: DC2_SpaceCleaning
Download link: https://github.com/cas-bigdatalab/piflow/archive/main.zip#dc2-spacecleaning

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