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text-normalization-and-large-file-processing

Normalize Chinese text and numeric fields in Excel files using pandas and openpyxl.

4.9k|347|Updated Apr 14, 2026
Search Tags:#python#excel#data cleaning#large files#text normalization#Excel data
One-click install
npx skills add https://github.com/OpenSenseNova/SenseNova-Skills --skill text-normalization-and-large-file-processing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: text-normalization-and-large-file-processing
Source: https://github.com/OpenSenseNova/SenseNova-Skills/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/text-normalization
Command: npx skills add https://github.com/OpenSenseNova/SenseNova-Skills --skill text-normalization-and-large-file-processing

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the standardization and cleaning of text data within Excel files, reducing manual efforts in data preprocessing.

Core Features & Use Cases

  • Text Standardization: Cleans and normalizes Chinese text by removing extraneous characters and prefixes.
  • Numeric Conversion: Converts inconsistent textual numeric fields into integers for analysis.
  • Large File Handling: Efficiently processes big Excel files and outputs cleaned data ready for downstream applications.
  • Use Case: Prepare raw data export from a Chinese e-commerce platform by removing prefixes and extracting Chinese names to ensure consistent data analysis.

Quick Start

Use the text-normalization skill to clean and normalize Chinese names and numeric fields in your Excel file, then download the processed file for your analysis.

Frequently Asked Questions about text-normalization-and-large-file-processing

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

FAQPage Schema
How do I clean and normalize Chinese text in Excel files for data analysis?▼

Text normalization for Excel data is achieved by removing extraneous characters and prefixes from Chinese text. This Skill automates the standardization process, outputting cleaned data ready for downstream analysis.

Can pandas handle large Excel files for text normalization and numeric conversion?▼

Yes, pandas handles large Excel files by utilizing openpyxl for file operations to process big datasets efficiently. This Skill automates numeric conversion, turning inconsistent textual numeric fields into integers for consistent analysis.

What is the best way to remove prefixes from Chinese names in an e-commerce data export?▼

Removing prefixes from Chinese names in an e-commerce data export is best handled by automated text standardization. This Skill focuses on Chinese text processing to extract names and ensure data consistency validation.

Do I need Python and openpyxl to process Excel data for numeric cleaning?▼

You need Python with pandas and openpyxl installed to process Excel data for numeric cleaning. These dependencies handle file operations and convert inconsistent textual numeric fields into integers for analysis.

How do I convert inconsistent textual numeric fields into integers in Excel?▼

Converting inconsistent textual numeric fields into integers in Excel is automated by this Skill during the text normalization process. It ensures data consistency validation for large dataset processing.

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