Free online tool • No signup required

Excel Clean Up & Data Cleaner Online:
Fix Formula Errors, Deduplicate & Free Dashboard Templates

Instantly clean up messy Excel spreadsheets in your browser. Remove duplicate rows, fix broken formula errors (#VALUE!, #REF!, #N/A), harmonize conflicting dates, eliminate rogue spaces, and download 28 free formula-driven dashboard templates — 100% private with zero server uploads.

What Gets Cleaned

Automated in-memory fixes

✓
Duplicate Rows & IDs Merge or drop exact & fuzzy duplicates
✓
Mixed Date Formats Harmonize ISO, US/UK & 5-digit serials
✓
Ghost Whitespaces Strip trailing, non-breaking & double spaces
✓
Text Stored as Numbers Clean currencies, commas & scientific notations
✓
Corrupt CSV Delimiters Fix rogue tabs, commas & quotes
⚡ 100% Non-Destructive

Drop your Excel or CSV file here

Supported: XLSX · XLS · CSV · TSV • Up to 50MB (100,000 rows)

Your file stays yours. Processed 100% locally in your browser. Review our privacy details.

Remove duplicates
Fix date formats
Clean CSV files

In-Browser Sandbox

Local security guarantees

🔒
Zero Cloud Uploads Spreadsheet rows never touch an external server
⚡
Sub-Second Speed Cleans 100,000 rows in <800ms
🛡️
No Account or Sign-Up Instant access without email or credit card
📊
Formula Safe Maintains SUM, VLOOKUP & references intact
💾
Clean Export Ready Download standardized .xlsx or clean .csv
🔒 Zero Data Retention
Or load specific messy test data:
Interactive Demonstration

See SheetFix AI in action

Toggle between deliberately messy sample data, the cleaned result, and side-by-side diff marking. All 14 issues auto-resolved in milliseconds without formulas.

Found 14 Issues (Duplicates, Dates, Spaces)
# A • ID B • Customer Name C • Email Address D • Signup Date E • Deal Value F • Status
100% Client-Side Sandbox • Instant in-browser cleaning
Fast 4-Step Flow

How SheetFix AI works

A straightforward in-browser flow engineered for speed, full preview transparency, and zero data leakage.

1

Upload your file

Drop your Excel (.xlsx, .xls) or CSV spreadsheet. Instant in-browser parsing with zero cloud upload.

2

Automated audit

Immediate client-side scan inspects every row and column, detecting duplicates, serial dates, and whitespace bugs.

3

Choose repairs

Select exactly which cleaning rules to apply using simple toggles, with live before/after diff highlighting.

4

Download clean file

Export your pristine workbook as XLSX, CSV, copy directly to clipboard, or download an audit trail report.

Section 4 • Capabilities

Core cleaning features

Eight specialized cleaning modules to resolve common spreadsheet formatting and integrity problems.

Duplicate Removal

Eliminate exact duplicate rows across all columns, or deduplicate by key columns like Email or Order ID while keeping the first occurrence.

Matches row 1 → Flagged & dropped

Date Repair

Harmonize mixed date formats (DD/MM/YYYY vs MM/DD/YYYY, timestamps, and Excel 5-digit serial integers) into standard ISO YYYY-MM-DD.

"45689" → "2025-02-14"

Whitespace Cleanup

Trim hidden leading and trailing spaces, condense double spaces, and purge non-breaking spaces (ASCII 160) that break lookups.

" Sarah Connor " → "Sarah Connor"

Number Formatting

Strip rogue currency symbols ($ € £), commas, and standardize European decimal separators so numbers calculate properly.

"$14,500.00" → 14500.00

Blank-Cell Handling

Identify null entries, delete entirely empty rows, and replace missing values with explicit defaults ("N/A", 0, or previous record).

Empty cell → filled with "N/A" or 0

Text Normalization

Convert chaotic ALL-CAPS names into proper Title Case, lowercase email addresses, and strip unprintable characters.

"JOHN@DOE.COM" → "john@doe.com"

CSV Repair

Auto-detect delimiters (semicolon, comma, tab), fix unescaped internal quotes, remove UTF-8 BOM, and preserve leading zeroes.

Zip "07030" preserved (not "7030")

Formula-Error Detection

Pinpoint and highlight broken formulas (#VALUE!, #N/A, #REF!, #DIV/0!) across all sheets before sharing with clients.

Flagged #VALUE! cell in Col E
Dedicated Resources & Guides

Knowledge base & specialized tools

Deep-dive tutorials, formula error troubleshooting, keyboard cheat sheets, and downloadable starter templates on dedicated standalone pages.

Deep-Dive Guide

Excel Formula Error Explainer

Diagnose and resolve #VALUE!, #REF!, #N/A, #DIV/0!, #NAME?, and #SPILL! errors with root cause breakdowns and formula fixes.

Open Formula Guide →
Complete Cheatsheet

100+ Excel Shortcuts & Formulas

Master speed navigation, selection tricks, and modern dynamic formulas including XLOOKUP, INDEX/MATCH, LET, and LAMBDA.

View Shortcuts Cheatsheet →
28 Free Templates

28 Free Dashboard Templates

Pre-built executive, marketing, financial, and operational dashboard workbooks with native charts and instant free downloads.

Browse 28 Dashboards →
Formatting Guide

Date Formats & Serial Number Fixer

Understand Excel's 5-digit serial date system (e.g. 45689 = 2025-02-14), flip international DD/MM vs MM/DD, and convert to ISO 8601.

Read Date Guide →
Troubleshooting

Whitespace & ASCII 160 Traps

Learn why standard TRIM fails on web-copied tables containing non-breaking spaces (&nbsp;) and how to cleanly sanitize strings.

Read Whitespace Guide →
Audit Engine

Spreadsheet Health & Quality Audit

Analyze total rows, columns, blank clusters, duplicate clusters, and schema inconsistencies with confirmed vs potential categorization.

Run Quality Audit →
Section 7 • Real Value

Why SheetFix AI?

Practical spreadsheet cleaning built on transparent previews, safe data handling, and deterministic rules.

Ease of Use

No need to memorize complex nested Excel formulas like `=INDEX(MATCH())` or write Python Pandas scripts. Clean datasets with intuitive toggles.

Transparent Previews

Review every single proposed change in a color-coded before/after grid. You have full visibility into what the engine will modify before saving.

Safe Data Handling

Your confidential spreadsheet rows are processed locally inside your web browser’s memory. Your data never leaves your computer or touches remote storage.

Time-Saving Automation

Turn hours of manual cell editing, date reformatting, and space trimming into a fast, repeatable 5-second workflow.

Accessible Tools

Direct access for first-time visitors with no forced registration, no paywalls on essential cleaning operations, and no software installation.

Deterministic Integrity

We apply deterministic, auditable rules rather than hallucinating AI changes, ensuring your critical financial and customer numbers remain exact.

Transparency First • Clear Boundaries

Free Anonymous Cleaning vs. Optional Accounts

We believe in complete transparency. Here is exactly what is free without an account, what an optional account adds, and how our optional AI assistant works.

No Sign-Up Required • Free Forever

Free Anonymous Cleaning

$0 / 100% Free Forever

Zero registration. Every core tool runs instantly inside your web browser’s memory with total client-side privacy.

  • Unlimited Local RAM Processing: Clean files up to 50MB and 100k+ rows.
  • All 10 Core Cleaning Rules: Deduplication, dates, spaces, casing, numbers & blank rows.
  • 100% Client-Side Privacy: Files never leave your device. Zero cloud storage.
  • Formula Preservation: Formulas (=SUM, =VLOOKUP) preserved by default.
  • Local Preset Storage: Save custom cleaning rules directly in your browser.
  • Full Export Suite: Instant download to XLSX, CSV, or TSV with audit certificate.
  • Templates & Guides: 28 Excel dashboards and 100+ shortcuts included.

Optional Free Account

$0 / No Credit Card Required

Convenience features for professionals and teams who clean spreadsheets across multiple laptops and desktops.

  • Everything in Free Anonymous, plus:
  • Cross-Device Cloud Sync: Access your saved cleaning recipes on any computer.
  • Persistent Audit Trail: Review historical cleaning metrics and past certificates.
  • Team Pipeline Sharing: Generate 1-click shareable URLs with preset cleaning rules.
  • Custom Engine Defaults: Pre-set your preferred date format (ISO 8601 vs US vs UK).
  • Never Required: You can clean unlimited sheets without ever signing in.
Optional Assistant • 25 Free Queries

AI Formula Explainer

25 Free / Session Quota

A specialized diagnostic tool to help you understand and repair cryptic Excel formula syntax and calculation errors.

  • Completely Optional: Core cleaning is 100% deterministic and never uses AI.
  • Formula Syntax Diagnosis: Instant plain-English explanation for #VALUE!, #REF!, #N/A.
  • Recommended Formula Fixes: Clear instructions to rewrite fragile lookups or missing cells.
  • 25 Free Queries / Session: Available to all visitors with zero account required.
  • Pro Multi-Seat Upgrade: 500+ monthly AI queries for enterprise data teams.
Explore Formula Explainer
Section 8 • Common Questions

Frequently Asked Questions

Clear answers about privacy, format handling, formulas, and repair behavior.

No. You can upload, inspect, clean, preview, and download your spreadsheets completely anonymously with zero sign-up. Creating an account is 100% optional and only exists for analysts who want to sync custom cleaning presets and audit certificates across multiple computers.
When you click "Save Rules as Preset" as an anonymous user, your custom cleaning recipe is stored immediately in your local web browser storage (localStorage). It remains available on your device every time you return. If you later choose to create a free account, your presets can be synchronized to the cloud.
Not at all. SheetFix AI’s core cleaning engine is 100% deterministic and runs in-browser mathematical algorithms to deduplicate rows, normalize dates, trim whitespace, and preserve formulas with zero AI dependencies. The AI Formula Explainer is a separate, modular tool solely used for explaining complex syntax errors (#VALUE!, #N/A) on demand.
SheetFix AI natively supports Microsoft Excel workbooks (.xlsx, legacy .xls), Comma Separated Values (.csv), and Tab Separated Values (.tsv).
Your data is processed 100% inside your web browser using client-side JavaScript. The file never leaves your computer, is not sent over the network to external servers, and is never stored in any database.
Yes. SheetFix AI preserves formulas by default where supported (including arithmetic, logical functions, multi-sheet references, and named ranges). If a formula contains unresolvable external workbook links, missing dependencies, or syntax errors (#REF!, #VALUE!), SheetFix AI clearly flags it during inspection and asks for your confirmation before converting any formula into a static calculated value.
When numbers exceed 12, our parser automatically knows it must be the day (e.g. 24/02/2025). For ambiguous values, our diagnosis highlights them under "Potential Issues" and lets you choose your target format (YYYY-MM-DD, MM/DD/YYYY, or DD/MM/YYYY).
Because processing runs in your browser's RAM, files up to 50MB and up to 100,000 rows can be cleaned smoothly. For larger multi-gigabyte databases, we recommend chunked CSV imports.
Yes. All standard cleaning operations (deduplication, date repairs, whitespace trimming, CSV fixes, and exports) are free with no registration required.
Yes, the interface is fully responsive. You can upload files from iOS Files, Android Downloads, or Google Drive directly in your mobile browser.
Our cleaning pipeline is strictly non-destructive. If an unreadable cell value cannot be safely parsed, the original text is preserved exactly as uploaded and flagged in the audit report so you never lose information.
100% Free • Private In-Browser

Start Cleaning Your Spreadsheet Right Now

No accounts, no credit cards, and zero data uploads to cloud servers. Simply drop your Excel or CSV file to begin.

No file selected
Drop an Excel/CSV file or choose a sample to begin
1 Upload
2 Inspect
3 Review
4 Clean
5 Export

Upload your spreadsheet for diagnosis

Drag & drop your .xlsx, .xls, or .csv workbook

Or test immediately with a ready sample:
Core Tool Pages

SEO Architecture: Turn the Tools into a Traffic Engine

The main title is an excellent starting point for the homepage, but you should not try to rank one page for every spreadsheet problem. Create a dedicated page for each important user need.

Main Tool /excel-data-cleaner

Excel Data Cleaner Online

Main tool page for spreadsheet cleanup. Auto-diagnose and sanitize messy spreadsheets with side-by-side diff previews.

  • Complete multi-pass cleaning pipeline
  • Side-by-side cell diff review
  • 100% in-browser RAM execution
Open Dedicated Page →
Deduplication /remove-duplicates-excel

Remove Duplicates from Excel

Exact duplicates, selected columns and safe previews. Never silently deletes ambiguous records.

  • Multi-column composite keys
  • Keep first or keep last controls
  • Near-duplicate candidate suggestions
Open Dedicated Page →
Date Repair /fix-excel-date-format

Fix Excel Date Formats

Mixed dates, text dates and ambiguous dates. Standardizes serial integers (45689) and timestamps to ISO 8601.

  • DD/MM vs MM/DD auto-detection
  • Resolves 5-digit Excel serial numbers
  • Native ISO YYYY-MM-DD output
Open Dedicated Page →
CSV Repair /clean-csv-online

Clean CSV Files Online

Delimiters, encoding and malformed rows. Fixes messy commas, escaped quotes, semicolons and UTF-8 BOMs.

  • Auto-detects comma, semicolon, tab, pipe
  • Preserves leading zeroes on zip codes
  • Sanitizes unescaped multi-line text
Open Dedicated Page →
Whitespace /remove-extra-spaces-excel

Remove Extra Spaces in Excel

Leading spaces, trailing spaces and repeated whitespace. Strips invisible ASCII 160 non-breaking spaces.

  • Removes web copy & paste nbsp (CHAR 160)
  • Collapses multiple consecutive spaces
  • Prevents failed VLOOKUP/XLOOKUP matches
Open Dedicated Page →
Numeric Repair /convert-text-to-numbers

Convert Text to Numbers

Locale-aware number parsing and safe conversions. Strips currency symbols, apostrophes and percentage signs.

  • Handles accounting parentheses ($1,200)
  • Distinguishes zip codes from integers
  • Converts green triangle text errors
Open Dedicated Page →
Missing Data /find-blank-cells-excel

Find Blank Cells in Excel

Missing data and empty-row analysis. Differentiate between empty strings ("") and true null values.

  • Discovers ghost whitespace cells
  • Fills missing with default or "N/A"
  • Safe deletion of 100% empty rows
Open Dedicated Page →
Diagnostics /excel-formula-error-explainer

Excel Formula Error Explainer

Explain common formula errors and suggest fixes. Pinpoints root causes for #VALUE!, #REF!, #N/A and #DIV/0!.

  • Generates modernized replacement syntax
  • Replaces broken VLOOKUP with XLOOKUP
  • Replaces error cells with fallback values
Open Dedicated Page →
Reconciliation /compare-excel-files

Compare Excel Files

Compare rows, columns and changed values. Reconcile monthly versions and spot differences with color-coded diffs.

  • Primary key or row-by-row alignment
  • Added, deleted & modified cell badges
  • Exportable change audit log
Open Dedicated Page →
Auditing /excel-data-quality-checker

Spreadsheet Data Quality Checker

Detect inconsistent types, missing values and suspicious records. Calculates an instant 0-100% Hygiene Score.

  • Executive Health Score (0-100%)
  • Confirmed vs potential issue breakdown
  • Pre-flight database import audit
Open Dedicated Page →

Search Architecture Standard: These dedicated URLs provide targeted search intent matching for high-demand spreadsheet problem queries. Each tool page includes a working client-side parser, sample dataset launcher, detailed usage steps, realistic before-and-after diffs, and privacy-preserving in-browser processing.

Main Tool

Excel Data Cleaner Online: Sanitize, Standardize & Repair Spreadsheets

Clean messy Excel and CSV spreadsheets online in seconds. Automatically detect duplicate rows, fix inconsistent date formats, and trim whitespace without complex formulas.

Interactive In-Browser Tool
100% Client-Side • Zero Data Upload

Drop your Excel or CSV file to start

Files are parsed instantly in your computer's memory. No registration or software install needed.

Supported formats & limits:
XLSX CSV XLS TSV Max 50MB Up to 100,000 Rows 100% In-Browser

Step-by-Step Usage Instructions

Clean and repair your data in four intuitive visual steps:

Realistic Before-and-After Example

Inspect how our client-side cleaning engine detects errors and produces pristine standardized output:

Raw Spreadsheet Input (With Defects) Before
Sanitized & Standardized Output Cleaned

Frequently Asked Questions

Addressing genuine user concerns about security, limits, formulas, and large files.

Related Spreadsheet Tools

Solve other data hygiene issues in your workflow:

Ready to Clean Your Spreadsheet?

Launch the SheetFix AI workspace now. Process your workbook with interactive side-by-side previews, custom keep strategies, and 100% in-browser privacy.

Workflow Architecture

How SheetFix AI Cleans Data Accurately

Designed to give spreadsheet users total transparency, speed, and confidence with an interactive audit trail.

1

Upload

Drag and drop any XLSX, XLS, or CSV file. Files are parsed locally in milliseconds with zero server upload.

2

Inspect

Our diagnosis engine scans every cell, scoring sheet health and isolating duplicates, bad formats, and missing values.

3

Review

Toggle specific cleaning rules and inspect proposed changes in a color-coded before/after spreadsheet grid.

4

Clean

Watch the automated batch execution with live progress feedback and automatic audit log generation.

5

Export

Save your clean workbook as XLSX, CSV, copy directly to your clipboard, or download the verification audit trail.

Free-First Architecture

Recommended Technology Stack & Application Architecture

Engineered for maximal performance, search discovery, and 100% client-side privacy without unnecessary cloud costs.

Frontend — Next.js + TypeScript Web Application & SEO

A strong choice for a public SEO website and interactive application in one codebase. Uses Tailwind CSS and an accessible component library for the white-and-green interface.

Spreadsheet processing — SheetJS or ExcelJS Zero-Knowledge Parsing

Evaluate SheetJS for parsing Excel and CSV data, and ExcelJS for workbook creation and supported formatting. Test the exact file types and workbook features you need; neither should be assumed to preserve every Excel feature.

Database and optional accounts — Supabase Optional Storage

Store user profiles, saved cleaning rules, preferences and usage metadata. Start without mandatory accounts and introduce cloud storage only when it adds clear value.

AI — optional, later Modular Intelligence

Start with deterministic cleaning rules. Add AI-assisted explanations and recommendations after validation. Keep API keys server-side, set usage limits and never make AI calls necessary for basic cleaning.

SEO and analytics Privacy Analytics

Use Google Search Console, lightweight privacy-conscious analytics where appropriate, and automated checks for broken links, page performance and indexing.

Suggested Application Architecture

Modular System Design

Clean separation of concerns ensuring that deterministic, zero-knowledge spreadsheet cleaning remains fast and private while allowing modular expansion.

1
Public Pages
Statically rendered wherever possible for instant page loads and optimal search engine crawlability.
2
Cleaning Engine
Pure, testable transformation functions with explicit inputs and outputs (no side-effects, deterministic logic).
3
Workbook Layer
Fast binary parser, multi-worksheet selection, encoding detection, and formatted XLSX/CSV export.
4
UI Layer
Dropzone upload, issue diagnostics cards, side-by-side cell diff review, and non-destructive Ctrl+Z history.
5
Optional Backend
User accounts, saved cleaning rule recipes, usage quotas, and paid features without mandatory login.
6
AI Layer
Recommendation and explanation service, completely separated from the deterministic cleaning engine.
Useful references for implementation:
Next.js ↗ SheetJS ↗ ExcelJS ↗ Supabase pricing ↗

Free hosting and database tiers have limits, and processing large files can consume significant memory. Check current quotas and terms before choosing a deployment.

Full Feature Catalogue

What SheetFix AI Can Clean & Repair

Practical spreadsheet repairs combined with granular human control over every transformation.

A

Duplicate and Repeated Data

Pinpoint identical records, repeated column values, and subtle spelling variations with non-destructive human review.

9 Practical Repairs
Important: Never silently delete near-duplicates. Two customers can share a name, and two legitimate transactions can have identical amounts. SheetFix AI displays matching rules, row indices, and side-by-side previews before any action.
Exact Duplicate Rows Exact Match

Detect fully identical records across all columns and highlight them in warning red.

Row 14 == Row 42 (100% column parity)
Duplicate Values Column Scope

Find repeated entries in selected columns such as Email, SKU, or Phone Number.

col("email").occurrences > 1
Multi-Column Duplicates Composite Key

Match records using composite combinations such as Customer Name + Phone or Invoice Number + Date.

compositeKey([name, phone])
Near-Duplicate Candidates Human Review

Suggest possible spelling variations and typo records using Levenshtein distance for human review.

"Sara Connor" ∼ "Sarah Conner" (score: 91%)
Case-Insensitive Matching Text Normalize

Treat text with differing capitalization as equal when requested.

"ACME INC" == "Acme Inc"
Whitespace-Aware Matching Space Clean

Identify duplicate values that differ only by leading, trailing, or internal extra spaces.

" John Doe " == "John Doe"
Keep-First / Keep-Last Strategy

Choose whether to preserve the earliest recorded entry or retain the most recent update.

strategy: "keep_first" | "keep_last"
Merge or Compare Records Interactive

Review conflicting cell values in candidate rows side-by-side before deciding which survives.

diff(recordA, recordB) → user choice
Duplicate Audit Report Audit Trail

Full transparency log showing exactly which rows were matched, why they matched, and which was kept.

exportAuditTrail() → audit.json
B

Date and Time Repair

Standardize mixed calendar notations, solve ambiguous day/month order, and translate Excel integer serials.

12 Practical Repairs
Text Dates to Real Dates Parsing

Convert plain string dates into real date entities recognized across all modern spreadsheet software.

"11-May-2026" → 2026-05-11
Format Normalization Harmonize

Normalize inconsistent representations like 11/05/2026, 2026-05-11, and 11-May-2026 into a single chosen standard.

ISO 8601 (YYYY-MM-DD), US, or European
Ambiguous Date Detection Interactive Prompt

Detect ambiguous dates like 03/04/2026 and ask whether the intended order is Day/Month or Month/Day.

03/04/2026: March 4 vs April 3 prompt
Mixed Date Format Fix Column Healing

Repair single columns populated from multiple CRM exports with conflicting format rules.

col.forEach(c → standardize(c, targetFormat))
Invalid Calendar Dates Validation

Flag impossible calendar entries like 2026-02-31 or 2026-13-45 and unparseable gibberish strings.

isValidDate(cell) === false → flagged
Time Value Normalization 12h / 24h

Convert and synchronize 12-hour AM/PM times with military 24-hour notation.

"02:30 PM" ↔ "14:30:00"
Timestamp Sanitization Separator Clean

Clean timestamps containing extra spaces, tabs, or non-standard colon/dot separators.

"2026-05-11 14:30 .00" → clean ISO
Separate Date & Time Column Splitting

Split composite datetime timestamps into separate dedicated Date and Time columns.

split("2026-05-11 14:30") → ["2026-05-11", "14:30"]
Combine Date & Time Column Merging

Merge independent date and time columns into a single unified ISO timestamp when requested.

combine(colDate, colTime) → colDateTime
Unix Timestamp Conversion Epoch Decoders

Translate epoch integers in seconds or milliseconds into human-readable date/time strings.

1778500000 → 2026-05-11T11:46:40Z
Excel Serial-Date Converter Serial Decoder

Detect Excel 5-digit serial numbers like 45689 caused by CSV misformatting and offer instant preview.

45689 → 2025-01-28 (1900 epoch decoded)
Export Standardization Export Ready

Output ISO 8601 or customized local formats guaranteed to open without corruption in Excel and Google Sheets.

XLSX date numFmt: "yyyy-mm-dd"
C

Text Cleanup and Normalization

Eradicate invisible non-printing characters, normalize capitalization, format phone numbers, and harmonize categories.

14 Practical Repairs
Trim Leading & Trailing Spaces Whitespace

Eliminate invisible margin spaces that cause failed VLOOKUP, XLOOKUP, and database foreign keys.

cell.trim() (removes ghost margin spaces)
Collapse Repeated Spaces Internal Space

Replace accidental double and triple spaces between words with a single clean space.

replace(/\s{2,}/g, ' ')
Non-Printing & Line Breaks Sanitization

Strip ASCII control characters (0-31), soft hyphens, and unwanted carriage returns inside single cells.

replace(/[\x00-\x1F\x7F-\x9F]/g, '')
Casing Normalization Letter Case

Intelligently switch between UPPERCASE, lowercase, Title Case (for names & cities), and sentence case.

"JOHN DOE" → "John Doe"
Phone Number Presentation Digit Preserved

Format telephone strings into consistent display masks (e.g. +1 555-019-2834) without altering underlying digits.

"5550192834" → "+1 (555) 019-2834"
Prefix & Suffix Stripping Pattern Trimming

Bulk remove unwanted prefixes (e.g., "ID_", "REF-") or suffixes across any selected column.

stripPrefix("INV-") → "00941"
Punctuation & Unicode Spaces Unicode

Standardize non-breaking spaces (&nbsp; / \u00A0), en-dashes, em-dashes, and smart curly quotes.

\u00A0 → standard ASCII space (0x20)
Inconsistent Category Spellings Taxonomy

Detect variants like "Technology", "Tech", and "Technolgy" and group them into a single canonical tag.

clusterSimilarCategories(column)
Search & Replace Rules Transformation

Target exact substrings or regex patterns across one or all columns with preview diffs.

regexReplace(pattern, replacement)
Column Splitter Splitting

Split combined columns by delimiter (comma, slash, space), fixed character width, or regex pattern.

"New York, NY" → ["New York", "NY"]
Column Combiner Merging

Join multiple columns (First Name + Last Name) using your preferred separator.

[First, Last].join(" ")
Entity & Pattern Extractor Regex Extraction

Extract email addresses, order IDs, ZIP codes, or numeric values from noisy unstructured text cells.

extractPattern(/[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}/)
Malformed Email / ID Detection Integrity

Flag strings missing @ signs, invalid top-level domains, or broken ID structures.

"user@@domain..com" → flagged invalid
Approved State/Country Mapping Mapping

Normalize geographic entries (e.g. "CA", "Calif.", "California") using a transparent user-approved dictionary.

mapLookup("Calif.", STATE_MAP) → "CA"
D

Numbers, Currencies and Percentages

Convert text numbers, harmonize thousands/decimal separators across locales, and strictly protect numeric identifiers.

12 Practical Repairs
Critical rule: An identifier such as 001245 must not be converted to 1245 automatically. SheetFix AI allows users to mark any column as an Identifier / Text to preserve leading zeros in ZIP codes, account numbers, and barcode SKUs.
Numbers Stored as Text Type Casting

Convert green-triangle text-formatted numbers into genuine numeric values that calculate in SUM and AVERAGE.

"142.50" → 142.50 (numeric)
Separator Normalization Thousands/Decimals

Clean irregular comma and period placements in large numerical values.

"1,000,250.00" → 1000250.00
Locale Handling (US vs EU) Locale Select

Handle 1,250.50 (US comma thousands) versus 1.250,50 (European comma decimal) using an explicitly chosen locale.

locale: "eu" | "us" explicit parse
Currency Symbol Stripping Clean Numeric

Remove currency marks ($, €, £, ¥, INR) while fully preserving the underlying numeric value and sign.

"$ 1,250.00" → 1250.00
Percentage Conversion Percent Parse

Convert percentages stored as text strings (e.g. "15.5%") into decimal fractions (0.155) or sanitized numbers.

"25%" → 0.25 | 25
Decimal Precision Audit Consistency

Detect inconsistent decimal lengths across currency columns (e.g. mixed 1, 2, and 4 decimal places).

flagMixedDecimals(column)
Accounting Negatives Negative Signs

Identify negative numbers enclosed in accounting parentheses and convert them to standard minus signs.

"(500.00)" → -500.00
Mixed Numeric/Text Columns Type Anomaly

Flag columns containing both numeric values and string text (e.g. "N/A", "TBD", "Free").

detectMixedTypeAnomalies(col)
Standardize Currency Display Formatting

Standardize currency formatting without implying an unrequested live currency rate conversion.

numFmt: "$#,##0.00"
Statistical Outlier Detection IQR / Z-Score

Highlight unusually large or small values using interquartile range (IQR) for analyst review.

val > Q3 + 1.5 * IQR → flagged outlier
Unexpected Signs / Magnitude Sign Audit

Identify numbers with unexpected negative quantities, negative ages, or impossible discount rates.

quantity < 0 → warning
Leading Zero Preservation Identifier Shield

Guarantee leading zeros are preserved for ZIP codes, PIN codes, phone numbers, and product barcodes.

"07030" remains string "07030"
E

Blank Cells, Missing Values & Incomplete Records

Distinguish true blanks from placeholders, remove entirely empty margins, and execute controlled imputation.

12 Practical Repairs
Missing data rule: Missing data should not be filled automatically just because a cell is blank. The correct treatment depends on what that field represents; SheetFix AI requires explicit user selection for any fill method.
Empty & Whitespace Detection Blank Audit

Detect truly empty cells and whitespace-only cells that look blank but contain spaces.

cell === "" || /^\s+$/.test(cell)
Placeholder Discrimination Placeholders

Distinguish true blanks from placeholder strings such as "N/A", "NULL", "-", "None", and "Unknown".

isPlaceholder(val) → user map choice
Missing Required Fields Completeness

Identify records missing mandatory columns such as Customer ID, Email Address, or Transaction Date.

checkRequiredFields(row, requiredCols)
Drop Empty Rows Row Hygiene

Safely remove rows where every single cell is completely blank without corrupting neighboring data.

row.every(c => c === "") → dropped
Drop Empty Columns Column Hygiene

Remove empty columns left behind by deleted software exports or blank spreadsheet margins.

col.every(c => c === "") → dropped
Fill with Constant Constant Fill

Fill blanks with a user-selected constant string or number (e.g. "N/A", 0, "Unassigned").

fillValue: "Not Specified"
Forward / Backward Fill Imputation

Propagate values downward or upward across merged-origin categories when explicitly requested.

ffill() | bfill()
Numeric Imputation Statistical Fill

Fill missing numeric values with mean, median, or zero using selectable statistical rules.

fillMissingWith(method: "median")
High Missing-Rate Warning Warning

Flag columns where more than 30% or 50% of records are absent before relying on them.

missingPct > 40% → High Missing Alert
Critical Key Audit Audit

Find records missing essential primary keys, IDs, or timestamps required for database ingestion.

row.id == null → marked critical
Missing Data Summary Reporting

Generate an interactive column-by-column breakdown of missing percentages and fill recommendations.

generateMissingDataSummary()
Fill Rule Preview Preview First

Preview exactly how many rows will be altered by any removal or imputation rule before execution.

previewAffectCount(rule)
F

Column Names and Table Structure

Standardize header conventions, detect headers buried under report titles, and remove repeat headers.

14 Practical Repairs
Trim Header Whitespace Header Clean

Remove leading, trailing, and internal double-spaces from column header strings.

" Customer ID " → "Customer ID"
Duplicate & Empty Headers Uniqueness

Automatically rename repeated headers ("Date", "Date_1") and name empty headers ("Column_3").

renameDuplicates(["ID", "ID"]) → ["ID", "ID_2"]
Header Casing Standard Naming

Standardize header capitalization across all columns (Title Case, UPPERCASE, lowercase).

header.toTitleCase()
snake_case Database Converter SQL Ready

Convert human headers like "Order Total ($ USD)" into clean SQL-ready "order_total_usd".

"First Name" → "first_name"
Cross-File Schema Audit Multi-File

Detect inconsistent column naming conventions when consolidating monthly or regional files.

"Client_Name" vs "CustomerName"
Column Reordering Arrangement

Drag and drop or select predefined column orders to match target ERP/CRM schemas.

reorderColumns([id, date, name, amount])
Split Multi-Part Column Structure

Split single composite columns into multiple distinct columns with custom target headers.

"City, State, Zip" → 3 columns
Combine Related Columns Concatenation

Combine Address Line 1 and Address Line 2 or Area Code + Local Number into one column.

mergeCols(addr1, addr2, ", ")
Mixed Data Types in Column Type Safety

Flag columns containing conflicting data types (e.g. numbers mixed with text notes or dates).

columnTypeProfile(col) → mixed warning
Title / Notes Header Offset Table Start

Identify the true header row when a spreadsheet has report titles or export timestamps above the table.

detectHeaderRow(sampleRows) → row 4
Remove Mid-Data Headers Pagination Clean

Detect and discard repeated header rows accidentally injected into the middle of data by legacy reports.

row == headers && rIdx > 0 → drop
Totals & Footer Row Detection Subtotals

Detect and isolate "Total:", "Subtotal:", and footer notes mixed into dataset rows.

isFooterOrTotalRow(row) → prompt separate
Inconsistent Column Counts Ragged Rows

Flag ragged CSV records where rows have fewer or more columns than the header definition.

row.length !== headers.length → align
Table Shape Normalization Rectangular Grid

Pad or trim records to output a strictly rectangular, database-ingestible data frame.

normalizeRectangularGrid(rows)
G

Formula & Spreadsheet Error Assistance

Detect spreadsheet errors (#REF!, #DIV/0!, #VALUE!), diagnose formula inconsistencies, and explain causes.

11 Practical Repairs
Technical distinction: Detecting an error is not the same as recalculating a workbook. SheetFix AI highlights broken formulas, explains errors in plain English, and suggests corrections without making unrealistic claims about running a full background Excel calculation engine.
Formula Error Detection Error Scan

Instantly locate standard spreadsheet errors: #REF!, #DIV/0!, #VALUE!, #N/A, #NAME?, and #NUM!.

['#REF!','#VALUE!','#DIV/0!','#N/A'].includes(c)
Hardcoded Value Overrides Formula Break

Identify formulas overwritten with manual hardcoded constants in an otherwise formula-driven column.

detectOverwrittenFormulas(column)
Adjacent Pattern Breaks Inconsistency

Highlight formulas whose relative cell references break expected patterns compared to surrounding rows.

flagFormulaPatternDeviation(range)
Missing Cell References Dangling Refs

Highlight formulas pointing to blank cells, out-of-range rows, or deleted worksheet columns.

checkReferenceIntegrity(formula)
External Workbook Links Broken Links

Identify external workbook dependencies (e.g. [Budget_2025.xlsx]Sheet1) that break when a file is emailed.

detectExternalReferences(workbook)
Plain English Error Explanations Clarity

Explain exactly why #VALUE! or #REF! occurred and what data input provoked it.

"#VALUE!: Text 'TBD' used in mathematical formula"
Suggested Corrected Formulas Assistance

Suggest working corrections with concrete examples (e.g. wrapping lookups in IFERROR).

suggest: "=IFERROR(VLOOKUP(...), 0)"
Suspicious Formula Results Sanity Check

Flag zero division, circular reference artifacts, and unexpected negative outputs for human inspection.

flagSuspiciousResults(calcSummary)
Inconsistent Range Formulas Uniformity

Detect formula cells that use different functions or arguments than the rest of the column range.

flagInconsistentFunctions(column)
Formula Preservation Non-Destructive

Preserve original formulas intact and display suggested repairs separately in audit previews.

preserveOriginal: true
Formula Validation on Samples Safe Test

Validate formula logic against sample rows before commiting bulk updates across thousands of rows.

testFormulaSample(formula, sampleRows)
H

CSV Repair and Import/Export

Auto-detect delimiters, fix UTF-8 BOM, resolve quoting issues, and configure pristine delimiter exports.

13 Practical Repairs
Delimiter Auto-Detection Auto Sniff

Sniff and detect common delimiters: comma (,), semicolon (;), tab (\t), and pipe (|).

sniffDelimiter(csvSample) → ";"
Manual Delimiter Override User Choice

Allow users to explicitly select the delimiter when automatic detection is uncertain or files are messy.

select: Comma | Semicolon | Tab | Pipe
Encoding Auto-Detection Encoding

Detect UTF-8, Windows-1252, and ISO-8859-1 encodings before parsing text strings.

detectEncoding(fileBuffer) → UTF-8
UTF-8 BOM Handling Byte Order

Strip or handle invisible UTF-8 Byte Order Marks (\uFEFF) that corrupt first column headers.

stripBOM(buffer) (removes \uFEFF)
Character Encoding Repair Mojibake

Repair common mojibake encoding corruption (e.g. "é" back to "é") when raw bytes permit.

repairMojibake("Café") → "Café"
Inconsistent Column Counts Ragged CSV

Detect ragged lines where commas inside unquoted text resulted in extra or missing columns.

flagRaggedLines(lineCounts)
Malformed Quoting Repair Quotes

Correct unescaped quotation marks and unbalanced double quotes inside cell contents.

healQuotes(rawCsvText)
Preserve Commas & Newlines RFC 4180

Strictly preserve commas and multi-line breaks contained within valid quoted text fields.

RFC 4180 compliant parsing
Inconsistent Line Endings CRLF / LF

Detect and normalize conflicting Windows CRLF (\r\n) and Unix LF (\n) line breaks.

normalizeLineEndings(text, "\r\n")
Pre-Parse Table Preview Preview First

Preview the parsed grid with column boundaries before initiating any cleaning operations.

renderParsedGridPreview()
Custom Export Parameters Export Config

Choose delimiter, encoding (UTF-8 with or without BOM), text qualifiers ("), and line endings on export.

exportCSV({ delimiter: ";", qualifier: '"' })
Locale Selection for Export Locale Export

Choose target date and numeric locale standards for downstream software compatibility.

exportLocale: "en-US" | "de-DE"
Export Loss Warnings Warning

Transparently alert users when exporting to CSV will discard formulas, multiple sheets, or cell colors.

warnCSVFeatureLoss()
I

Excel Workbook Integrity & Formatting

Parse XLSX and legacy XLS workbooks, handle multi-sheet selectors, detect merged cells, and warn of macro loss.

10 Practical Repairs
Integrity notice: Legacy .xls formats and modern .xlsx workbooks are fully supported for data extraction and repair. Transparent warnings notify users when macros, pivot caches, or external links cannot survive plain tabular re-export.
XLSX and XLS Parsing File Support

Client-side parsing of both modern .xlsx OpenXML workbooks and legacy Excel 97-2003 .xls binary files.

XLSX.read(arrayBuffer, { raw: true })
Worksheet Multi-Selector Sheet Nav

List all worksheets in multi-tab workbooks and let users choose which sheets to inspect and clean.

workbook.SheetNames.map(name => tab)
Merged Cell Detection Grid Alignment

Detect merged header or data cells that disrupt standard table filtering and offer clean unmerging options.

sheet['!merges'] → unmerge and ffill
Hidden Rows / Cols / Sheets Hidden Data

Identify hidden worksheets, rows, and columns that might conceal confidential records or duplicate totals.

detectHiddenElements(sheet)
Inconsistent Number Formats Cell Format

Flag inconsistent number display formats within a single column (e.g. General, Currency, Text mixed).

flagInconsistentFormats(col)
Text vs Date Format Check Type Scan

Detect text-formatted numbers and numbers stored as formatted dates.

detectFormatMismatch(cell)
Bloated Range De-inflation Size Reduction

Identify empty formatted ranges (e.g. millions of empty cells) that inflate workbook file size to 100MB+.

recalculateUsedRange(sheet) → shrink
Duplicate Worksheet Names Validation

Flag conflicting sheet structures or naming anomalies across workbooks.

validateSheetNames(workbook)
Header & Sheet Preservation Preservation

Retain sheet names, custom column titles, and supported data formats when exporting back to .xlsx.

exportXLSX({ preserveMetadata: true })
Feature Loss Warning Transparency

Transparently alert users when VBA macros, charts, or pivot tables will not survive pure table cleaning.

displayFeatureLossNotice()
J

Data Quality and Analysis

Transparent data health scoring, dataset diffing, primary key candidate detection, and exportable audit logs.

11 Practical Repairs
Transparent scoring note: The Spreadsheet Health Score is a product-defined indicator calculated from duplicate density, missing ratios, and type inconsistencies, not an objective legal certification.
Transparent Quality Score Health Score

Calculated score (0-100%) showing data readiness with an open breakdown of deductions.

Score = 100 - (dup% * 40 + blank% * 30 + format% * 30)
Issue Summarization Diagnostics

Categorized tally of exact duplicates, missing values, date format errors, and numeric outliers.

getInspectedIssues() → metric strip
Statistical Outlier Profiling Statistics

Detect statistical anomalies across numerical fields using user-selected thresholds.

detectOutliers(column, { method: 'IQR' })
Category Inconsistency Tally Distribution

Highlight category columns with too many near-identical unique values.

findInconsistentTaxonomies(col)
Candidate Primary Keys Primary Key

Analyze uniqueness and completeness to suggest which columns can serve as unique database keys.

uniqueRatio === 1.0 && missingRatio === 0 → PK
Conflicting Identifier Alerts ID Collision

Flag repeated IDs associated with conflicting customer names or contradictory billing addresses.

idCollisions(idCol, dataCols)
Unique-Value Distributions Profiling

View column distribution summaries and counts of distinct values for instant EDA.

getDistribution(column) → { unique: 48, top: 'Active' }
Dataset Version Diffing Version Compare

Compare two versions of a spreadsheet to visualize rows added, removed, or modified.

compareDatasets(fileA, fileB) → diff summary
Two-Sheet Comparison Sheet Diff

Compare two sheets in the same uploaded workbook to find discrepancies.

compareSheets(sheet1, sheet2)
Auditable Cleaning Log Compliance

Generate an auditable report documenting every rule executed, row count, and transformation reason.

auditTrail.push({ action, detail, count })
Independent Report Export JSON / Text

Download the audit report as an independent JSON or text file for compliance records.

exportAuditReport() → audit_report.json
K

AI-Assisted Cleanup

Describe spreadsheet problems in plain English, receive guided recommendations, and execute deterministically.

10 Practical Repairs
Deterministic principle: AI models recommend transformations and synthesize plain-English instructions, but deterministic browser code applies the approved operations. This makes changes 100% reproducible, verifiable, and safe from AI hallucinations.
Plain English Problem Summary Natural Language

Translates spreadsheet anomalies into concise, non-technical explanations of data risks.

"Found 14 duplicate rows and 3 different date styles in Column C."
Recommended Cleaning Actions Smart Pipeline

Proactively suggests the highest-impact fixes tailored to the uploaded file structure.

suggestRecommendations(inspectedIssues)
Category Mapping Suggestions Categorization

Suggests logical mappings between inconsistent category strings for user approval.

"N.Y.", "NYC", "New York City" → "New York"
Contextual Duplicate Match Context Match

Identifies candidate duplicate records using column semantic context without silent deletion.

contextualDuplicateDetection(rowA, rowB)
Explain Unfamiliar Errors Error Tutor

Explains mysterious formula failures (e.g. #SPILL!, #FIELD!, #CALC!) in simple steps.

explainFormulaError("#SPILL!")
Written Instruction to Rules Prompt to Rule

Type instructions like "Standardize dates to YYYY-MM-DD and remove duplicates by email" to configure rules automatically.

processAIInstruction(prompt) → appliedConfig
Formula Generation for Review Formula Builder

Generate verified Excel/Sheets formulas from plain English descriptions with syntax highlighting.

"Calculate 30-day rolling average" → =AVERAGEIFS(...)
Issue Causes & Origins Root Cause

Summarize likely software origin causes (e.g. Salesforce export encoding, legacy CSV truncation).

diagnoseProbableOrigin(fileAnomalies)
Safe Operation Order Sequencing

Suggests the optimal order of operations (e.g. trim whitespace before deduplication) to maximize clean rate.

Optimal: 1. Trim → 2. Casing → 3. Dedup → 4. Impute
Pre-Execution Impact Explanation Audit Confidence

Explains clearly what each selected operation will change before any data is altered.

explainOperationImpact(rule) → preview report
Tutorials & Troubleshooting

Excel & CSV Troubleshooting Guides

Practical formulas, troubleshooting steps, and step-by-step solutions for common data quality headaches.

Excel Guide

How to Fix Mixed Date Formats in Excel (DD/MM vs MM/DD)

When importing CSVs from different countries, dates often flip between European and American formats. Here is how to fix them with formulas or automatic detection.

=DATE(RIGHT(A2,4), MID(A2,4,2), LEFT(A2,2))

Tip: SheetFix AI auto-detects date columns and harmonizes them to YYYY-MM-DD in 1 click.

Excel Guide

Removing Duplicate Rows While Keeping the Most Recent Record

Excel's built-in "Remove Duplicates" tool always keeps the FIRST record and deletes the rest. If your file is not sorted by date, you could discard newer data.

=SORTBY(DataRange, DateColumn, -1)

Sort first, or use SheetFix AI to inspect duplicate clusters before deletion.

CSV Guide

How to Prevent Excel from Deleting Leading Zeroes in CSVs

Excel automatically interprets zip codes like "07030" or product SKUs like "00129" as numbers and strips the leading zeros into "7030".

=TEXT(A2, "00000")

SheetFix AI keeps original string representations intact during export.

CSV Guide

Why European Excel Uses Semicolons Instead of Commas in CSV

In many European countries, the comma is used as the decimal separator (e.g. 14,50 €). Consequently, Excel uses semicolons (;) as the list delimiter.

Regional settings → List separator → Change to ','

SheetFix AI automatically detects semicolon delimiters and normalizes files.

Traffic & Content Architecture

Blog and Tutorial Categories

Targeted knowledge hubs, syntax guides, and troubleshooting recipes for every spreadsheet dilemma.

Date formatting

Excel dates that won't change, mixed date formats, timestamps and locale errors.

  • Mixed DD/MM vs MM/DD dates
  • Excel 5-digit serial numbers (45689)
  • Locale mismatches (European vs US)
  • Date text string conversion
Open Date Standardizer →

Duplicates

Duplicate rows, duplicate IDs, repeated customers and fuzzy matching.

  • Exact duplicate row removal
  • Multi-column composite key deduplication
  • Near-duplicate candidate review
  • Keep-first vs keep-last strategies
Open Duplicate Remover →

Excel formulas

Common formula errors, inconsistent formulas and text-number problems.

  • Troubleshooting #VALUE! and #N/A
  • Resolving #SPILL! and dynamic arrays
  • VLOOKUP vs XLOOKUP best practices
  • IFERROR error handling wrappers
Open Formula Explainer →

CSV troubleshooting

Encoding, delimiters, broken imports and export settings.

  • Semicolon vs comma delimiter auto-detection
  • Preventing loss of leading zeros in zip codes
  • Stripping invisible UTF-8 BOM artifacts
  • RFC 4180 quotation escaping
Open CSV Cleaner →

Data quality

Missing values, inconsistent categories, outliers and validation.

  • Detecting hidden ghost rows and blank cells
  • Standardizing casing for customer names and emails
  • Trimming ASCII 160 non-breaking spaces
  • Calculating Spreadsheet Health Scores
Open Quality Checker →

Free templates

Data-cleaning checklists, inventory sheets and sample datasets.

  • Clean CRM Sales Leads Template (.xlsx)
  • E-Commerce Orders & SKU Template (.xlsx)
  • Financial Ledger & Journal Template (.xlsx)
  • Spreadsheet Pre-Flight Data Hygiene Checklist
Open Excel Cleaner →
Security Standard

Your Data Stays Yours. Period.

SheetFix AI is engineered with a Zero-Knowledge, 100% Client-Side Architecture.

100% Client-Side In-Browser Execution Guarantee

Unlike conventional web apps that send your sensitive spreadsheets to a remote server for processing, SheetFix AI runs entirely inside your web browser’s local sandbox using JavaScript and WebAssembly. Your rows, columns, customer data, and financial figures never leave your device.

Zero Cloud Storage

We do not store, log, cache, or maintain copies of your files. When you close the browser tab, the data in memory vanishes.

No Data Training

We never use your uploaded files or business spreadsheets to train AI models or machine learning algorithms.

HIPAA & GDPR Compliant

Because data never traverses our network, SheetFix AI aligns with internal corporate security policies and data residency laws.

Support & Mission

About SheetFix AI & Contact Us

Have a question or custom cleaning requirement? We are here to help.

Spreadsheet cleaning should be instant, safe, and pleasant.

We created SheetFix AI because spreadsheet users spend millions of hours every year debugging broken dates, searching for duplicate customer records, and reformatting corrupted CSVs.

By pairing local browser execution with modern spreadsheet diagnosis heuristics, our goal is to give every knowledge worker clean data in seconds.

Direct Online Support & Feature Feedback

All inquiries, bug reports, and custom cleaning requests are handled exclusively through this contact form. Messages are sent securely and directly to our engineering team.

Guaranteed response within 24 hours