Remove Duplicates in Excel — Quick Start

Usage Steps:

1. Upload — Select an Excel (.xlsx) or CSV file. The tool analyzes headers, sample values, and row count locally.
2. Choose Columns — Tick one or more columns as the unique key for duplicate detection (e.g., Email + Phone).
3. Set Options — Choose 'Keep First' or 'Keep Last'; enable normalization like Trim/Lower-case/Punctuation/Full→Half Width.
4. Run — Start processing. View progress and summary: original rows, duplicates removed, unique rows retained.
5. Download — Export the cleaned dataset to Excel or CSV with a single click.

Features:

• Multi-Column Deduplication — Combine columns to define row uniqueness
• Keep Strategy — Choose to keep the first or last occurrence of duplicates
• Normalization — Trim whitespaces, convert to lower-case, normalize punctuation, full-width→half-width
• Local-first — All processing stays in the browser; no server upload
• Result Summary — See counts of original, duplicate, and unique rows
• Export — Download to .xlsx or .csv instantly

Use Cases:

• Email List Cleaning — Remove duplicate subscribers across merged lists
• Sales CRM Merging — Deduplicate leads by Email + Phone or Company + Name
• Event Registrations — Clean attendee sheets before badge printing
• Product Catalog — Collapse duplicate SKUs while keeping latest updates
• Academic Datasets — Ensure unique participants or records by ID
• Finance Exports — Normalize payee names and remove duplicate transactions

Common Questions (Q&A):

1. Q: How do I remove duplicates by multiple columns in Excel?
   A: Select all relevant columns as the unique key (e.g., Email + Phone). The tool treats rows with identical values across these columns as duplicates.
2. Q: What is the difference between 'Keep First' and 'Keep Last'?
   A: 'Keep First' preserves the first encountered row among duplicates; 'Keep Last' keeps the most recent occurrence if your data is time-ordered.
3. Q: Is my file uploaded to a server?
   A: No. All parsing, normalization, and deduplication happen locally in your browser for maximum privacy.
4. Q: Will normalization change my data permanently?
   A: Normalization affects how duplicates are detected. The exported result reflects the cleaned values so your dataset stays consistent.
5. Q: Which output format should I choose, Excel or CSV?
   A: Choose Excel (.xlsx) to preserve formatting and wide compatibility; choose CSV for lightweight interoperability and pipelines.