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Bethemesh
Data & spreadsheets

Clean an Excel or CSV file

Import an Excel or CSV file, choose cleanup operations, preview the result and export it without uploading your data to a server.

  • Batch processing
  • Export
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Cleaning options

Result

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How does this tool work?

Spreadsheet exports can contain surrounding spaces, completely empty rows and repeated records. This cleaner applies three explicit operations before comparison, joining or conversion. All three options start enabled and can be switched off independently. Cleaning is deliberately limited: it does not correct spelling, infer business types or decide that similar records represent the same person. Keep the original so you can explain removed rows and check whether each selected operation fits the meaning of your source data.

Import CSV, TSV, XLSX, XLS or flat tabular JSON, up to 30 MiB per file through the drop zone. Processing and export stay in the browser. This interface uses a workbook’s first sheet without a sheet selector. Styles, macros, merged cells and live formulas are not retained as in an Excel editor. CSV cells are strings; scalar JSON values keep their types. Nested objects or arrays in JSON cells must be flattened first.

Operations run in a fixed order: trim surrounding spaces, remove empty rows, then remove duplicates. Trimming applies to text values and column names without collapsing internal spaces or changing case. Headings that collide after trimming are made unique to avoid overwriting cells. CSV import already normalizes empty or repeated headings; disabling cleaning does not undo that structural import preparation. When trimming is enabled, records differing only in surrounding spaces may become identical before deduplication.

A row is empty when every value is missing, null or whitespace after textual inspection. Zero and false are not empty. Duplicate matching uses the complete record, including field names and value types, while ignoring JSON property order. The first occurrence is retained. Preview and XLSX, CSV or JSON exports use the cleaned result. The interface reports retained row counts but does not provide a detailed deletion log identifying the reason for each removed record.

How to use this tool

  1. Select suitable operations

    Check the first sheet and disable unsuitable options. Surrounding spaces can matter in some identifiers, so inspect them before trimming.

  2. Clean known sample records

    Inspect an empty row, a duplicate and a spaced value after processing. Compare source and result counts to identify unexpected losses.

  3. Choose an export format

    Use XLSX, CSV or JSON for the destination. CSV makes values textual and cannot always distinguish null from an empty string; retain the source for later checks.

Use cases

Prepare a comparison

Remove accidental spaces before comparing list versions while keeping case differences significant.

Remove exact repetitions

Eliminate whole-record duplicates from an export without choosing between merely similar customer records.

Reduce empty data

Remove rows without content before conversion or joining while retaining rows containing zero or false.

Examples

Spaces, blanks and duplicates

All options enabled: trimming makes both records identical, the first is kept and the empty row is removed.

Input

name;city
 Ada ; Leeds 
Ada;Leeds
 ;

Result

[
  {
    "name": "Ada",
    "city": "Leeds"
  }
]

Distinct JSON types

All options enabled. Key order is ignored, numeric 1 differs from text 1, and zero and false are retained.

Input

[{"code":1,"active":false},{"active":false,"code":1},{"code":"1","active":false},{"code":0,"active":false}]

Result

[
  {
    "code": 1,
    "active": false
  },
  {
    "code": "1",
    "active": false
  },
  {
    "code": 0,
    "active": false
  }
]

Tips and best practices

  • Inspect identifiers before enabling trimming. It removes accidental spaces but cannot know your reference conventions or distinguish intentional spacing from a data-entry mistake.
  • Use CSV Deduplicator when you need selected key columns or the last occurrence. This spreadsheet cleaner compares complete records and keeps the first without fuzzy matching options.
  • Save before-and-after copies when traceability matters. The retained-row count summarizes the operation but is not a detailed explanation of why every individual record was removed.

Frequently asked questions

Must all three options be used?

No. They start enabled but are independent. Remove only empty rows or disable trimming to preserve cell spaces. Enabled operations keep their fixed order, which affects duplicate detection when values are normalized before comparison.

Can I deduplicate using one column?

Not in this interface. Matching uses the complete row and retains its first occurrence. Two records with the same identifier but different amounts remain separate. Use a key-column deduplication tool when your rule depends on only part of the table.

Are dates, accents and letter case normalized?

No. The tool removes surrounding spaces, empty rows and exact repetitions according to selected options. It does not standardize dates, currencies, case or accents. Similar-looking values may remain different and require domain-specific preparation.

Is the original workbook changed?

No. The browser reads values and creates a new export without rewriting the source or preserving its complete presentation. Prepare another sheet in a separate file if needed; this interface uses the first workbook sheet.

Recommended workflow

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