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clean-data-xls

Clean and standardize Excel data with whitespace, casing, and date fixes.

Updated May 10, 2026
Search Tags:#Excel#data cleaning#data standardization#spreadsheet analysis#data prep
One-click install
npx skills add https://github.com/rpoole-dev/comps-site --skill clean-data-xls-rpoole-dev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clean-data-xls
Source: https://github.com/rpoole-dev/comps-site/tree/main/financial-services-main/plugins/vertical-plugins/financial-analysis/skills/clean-data-xls
Command: npx skills add https://github.com/rpoole-dev/comps-site --skill clean-data-xls-rpoole-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the issue of dealing with inconsistent, unstructured, or incomplete data within spreadsheets, providing tools to normalize and prepare data for analysis.

Core Features & Use Cases

  • Whitespace and Casing Standardization: Trim spaces, correct inconsistent casing in text columns.
  • Number Conversion: Convert numbers stored as text to numeric format.
  • Date Standardization: Normalize different date formats within the same column.
  • Duplicate Removal: Eliminate exact and near-duplicate rows.
  • Mixed-Type Column Flagging: Identify columns with mixed data types.
  • Use Case: When you have a spreadsheet with multiple inconsistencies, such as numbers stored as text, varying date formats, and extra spaces, this Skill can quickly clean the data, making it ready for analysis.

Quick Start

Run the clean-data-xls skill to normalize the data in the current sheet.

Frequently Asked Questions about clean-data-xls

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

FAQPage Schema
How do I clean up messy Excel data and fix inconsistent formatting?▼

To clean up messy Excel data, you can trim extra whitespace, correct inconsistent text casing, convert numbers stored as text to numeric format, and eliminate duplicate rows. This standardizes your spreadsheet for reliable analysis.

What is the best way to standardize mixed date formats in a spreadsheet?▼

Standardizing mixed date formats involves normalizing different date entries within the same column to a consistent structure. This process also flags mixed-type columns so you can identify data inconsistencies before analysis.

Can I normalize spreadsheet data using Python without opening Excel?▼

Yes, you can normalize spreadsheet data using Python with the openpyxl library. This allows you to perform standalone data standardization, handling whitespace, casing, and duplicates without needing the Excel application open.

Does this data cleaning approach work with Office JS inside Excel?▼

Yes, the data cleaning approach works within the Excel environment using Office JS. This ensures compatibility for standardizing number formatting, removing duplicate rows, and correcting whitespace directly in your spreadsheet.

How do I remove near-duplicate rows and fix numbers stored as text in Excel?▼

You can remove exact and near-duplicate rows and convert numbers stored as text to numeric format by running a data standardization script. This automatically resolves formatting inconsistencies and eliminates redundant entries.

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