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clean-data-xls

clean-data-xls

github.com/anthropicsData & databases40.9k2.1k installsUpdated today
Repository

About clean-data-xls

A spreadsheet-cleaning skill for tidying data in an active sheet or specified range. It profiles columns, proposes fixes before editing, and favors auditable helper formulas for transformations.

Key features

  1. 01Profile column types and outliers
  2. 02Detect formatting and data errors
  3. 03Present proposed fixes before changes
  4. 04Use helper formulas for cleaning
  5. 05Confirm destructive edits

Use cases

  1. 01Standardize whitespace and text casing
  2. 02Convert text-formatted numbers and dates
  3. 03Find duplicates, blanks, and spreadsheet errors

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/anthropics/financial-services --skill clean-data-xls

After installing, type/clean-data-xlsin Claude Code to confirm it loaded.

Details

From the project README

Clean Data

Clean messy data in the active sheet or a specified range.

Environment

  • If running inside Excel (Office Add-in / Office JS): Use Office JS directly (Excel.run(async (context) => {...})). Read via range.values, write helper-column formulas via range.formulas = [["=TRIM(A2)"]]. The in-place vs helper-column decision still applies.
  • If operating on a standalone .xlsx file: Use Python/openpyxl.

Workflow

Step 1: Scope
  • If a range is given (e.g. A1:F200), use it
  • Otherwise use the full used range of the active sheet
  • Profile each column: detect its dominant type (text / number / date) and identify outliers
Step 2: Detect issues
IssueWhat to look for
Whitespaceleading/trailing spaces, double spaces
Casinginconsistent casing in categorical columns (usa / USA / Usa)
Number-as-textnumeric values stored as text; stray $, ,, % in number cells
Datesmixed formats in the same column (3/8/26, 2026-03-08, March 8 2026)
Duplicatesexact-duplicate rows and near-duplicates (case/whitespace differences)
Blanksempty cells in otherwise-populated columns
Mixed typesa column that's 98% numbers but has 3 text entries
Encodingmojibake (é, ’), non-printing characters
Errors#REF!, #N/A, #VALUE!, #DIV/0!
Step 3: Propose fixes

Show a summary table before changing anything:

ColumnIssueCountProposed Fix
Step 4: Apply
  • Prefer formulas over hardcoded cleaned values — where the cleaned output can be expressed as a formula (e.g. =TRIM(A2), =VALUE(SUBSTITUTE(B2,"$","")), =UPPER(C2), =DATEVALUE(D2)), write the formula in an adjacent helper column rather than computing the result in Python and overwriting the original. This keeps the transformation transparent and auditable.
  • Only overwrite in place with computed values when the user explicitly asks for it, or when no sensible formula equivalent exists (e.g. encoding/mojibake repair)
  • For destructive operations (removing duplicates, filling blanks, overwriting originals), confirm with the user first
  • After each category of fix (whitespace → casing → number conversion → dates → dedup), show the user a sample of what changed and get confirmation before moving to the next category
  • Report a before/after summary of what changed

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