skills.rest
cas-bigdatalab
cas-bigdatalabOFFICIAL
Explore all skills by this author →
WebsiteGitHub

abbrev_expander

Expand abbreviations in structured text columns using custom dictionaries.

541|171|Updated May 3, 2018
Search Tags:#pandas#data normalization#text expansion#text cleaning#abbreviation expansion
One-click install
npx skills add https://github.com/cas-bigdatalab/piflow --skill abbrev-expander
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: abbrev_expander
Source: https://github.com/cas-bigdatalab/piflow/tree/main/workspace/skills/abbrev_expander
Command: npx skills add https://github.com/cas-bigdatalab/piflow --skill abbrev-expander

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, and includes scripts (resource) components.

What problem does it solve?

This Skill simplifies the task of converting abbreviated terms to their full names within structured text files, streamlining data cleaning and normalization processes.

Core Features & Use Cases

  • Expand Abbreviations: Automatically expands abbreviations present in text columns according to an internal dictionary or an external custom dictionary.
  • Selective Column Processing: Allows processing only specific text columns in the input file, making it adaptable for different data formats and needs.
  • Custom Dictionary Support: Integrates with JSON, CSV, or TSV dictionaries for defining additional abbreviation-to-full-name mappings.
  • Keep Abbreviations: Offers the option to retain the original abbreviation after the expanded term for better readability.

Quick Start

Expand abbreviations in 'input.csv' to 'output.csv' while processing all columns using the default dictionary and retaining abbreviations: python scripts/abbrev_expander.py --input_path input.csv --output_path output.csv --keep_abbr

Frequently Asked Questions about abbrev_expander

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I expand abbreviations to full terms in structured text data?▼

You can expand abbreviations in structured text using pandas by running a script that maps abbreviated terms to their full names. This normalizes text data for readability and integration across systems.

Can I use a custom dictionary for abbreviation expansion in pandas?▼

Yes, you can use a custom dictionary for abbreviation expansion by loading external JSON, CSV, or TSV files. This maps specific abbreviated terms to their full names during data preprocessing.

Does the text expansion tool support selective column processing?▼

Yes, the text expansion tool supports selective column processing. You can target specific text columns in your input file, making it adaptable for different data formats and normalization needs.

What is the best way to retain original abbreviations after text normalization?▼

To retain original abbreviations after text normalization, use the keep abbreviation option. This appends the original shortened term after the expanded full name for better contextual readability.

Do I need pandas to automate abbreviation expansion in CSV files?▼

Yes, you need pandas installed to automate abbreviation expansion in CSV files. The script relies on pandas to process structured text data and write the normalized output.

When do I need abbreviation expansion for data preprocessing?▼

You need abbreviation expansion for data preprocessing when normalizing text for content analysis or document conversion. It streamlines data cleaning by standardizing abbreviated terms across systems.

Related Skills

Explore More Data & Analytics Skills→
treasure-datatreasure-data
21

pytd

Query Treasure Data via Presto or Hive and load pandas DataFrames.

Official
Intermediate
mkurmanmkurman
321

flowio

Parse FCS files to extract event data and metadata into NumPy arrays or DataFrames.

Community
Intermediate
cas-bigdatalabcas-bigdatalab
541

en_text_cleaner

Clean English research text by expanding abbreviations and correcting spelling.

Official
Intermediate
alangebalangeb

search-replace

Perform bulk text substitution and pattern matching across local file systems using grep and Python.

Community
Intermediate