Skip to main content
Bethemesh
Data & spreadsheets

Convert Excel, CSV and JSON

Convert a spreadsheet file between supported formats while preserving its tabular data, then download the generated result.

  • Batch processing
  • Export

Embed this widget

Customize the result, check the live preview, then copy the code.

Preview

Embed code type

Code to copy

Responsive and automatically resized by Bethemesh.

Your files are processed locally in your browser and are never sent to our servers.

Drop your file here

Recommended size: up to 30 MB

Result

Was this tool useful?

How does this tool work?

The spreadsheet converter changes a table of values into a format another application can use: CSV can become XLSX, a workbook can supply flat JSON, and tabular JSON can become CSV. It does not reproduce a complete Excel document. Its working unit is one sheet represented as records and columns. Use it when data matters more than presentation, and retain the original workbook when other sheets, calculations or formatting have value that a simple table export cannot preserve.

The drop zone accepts CSV, TSV, XLSX, XLS and JSON up to 30 MiB per file. Reading stays in your browser. CSV and TSV use the first record as headings; empty or repeated headings are normalized to preserve columns. JSON must contain a flat object or array of flat objects with scalar cells. Nested objects and arrays are rejected; flatten them first. A standalone scalar or array of numbers is not an accepted table here.

For XLSX and XLS, this interface uses the first sheet without a selector for others. The reader retrieves displayed values as text and does not run Excel’s calculation engine to refresh formulas. Styles, macros, charts, validation rules and merged cells are not rebuilt. Preview shows a sample of the imported table while export uses all read records. An empty first sheet does not trigger an automatic search through subsequent sheets for useful data.

Available outputs are XLSX, CSV and JSON, not XLS or TSV. CSV uses semicolons, UTF-8 with a BOM and quoting for delimiters, quotes and line breaks. It converts values into text and missing or null values into empty cells. JSON output is an array of objects; CSV cells remain strings without automatic number or date inference. XLSX creates a new sheet of values. Choose according to the receiving system rather than assuming a lossless conversion.

How to use this tool

  1. Check sheet and shape

    Put the intended sheet first or prepare a separate file. Inspect headings and flatten nested JSON before importing.

  2. Inspect sensitive values

    Check dates, leading zeros, long identifiers and formula results. Conversion cannot repair values already rounded or stale in the source.

  3. Choose and inspect output

    Select XLSX, CSV or JSON and open it in the receiving application. Confirm delimiter, encoding, types and record count before important processing.

Use cases

Open text exports in a spreadsheet

Turn CSV or TSV into a single-sheet XLSX after checking references and accented characters.

Prepare application records

Export a flat table as JSON, checking whether textual types match the receiving code’s expectations.

Provide compatible CSV

Extract first-sheet workbook values as semicolon-delimited CSV for software supporting that convention.

Examples

CSV into JSON objects

JSON output keeps both fields as strings, preserving reference leading zeros without guessing numeric types.

Input

reference;quantity
0012;42
0013;7

Result

[
  {
    "reference": "0012",
    "quantity": "42"
  },
  {
    "reference": "0013",
    "quantity": "7"
  }
]

JSON into semicolon CSV

The embedded semicolon requires quotes. Booleans become text, while null and empty strings look alike here. The downloaded file’s BOM is omitted from this display.

Input

[{"name":"A;B","active":true,"note":null},{"name":"C","active":false,"note":""}]

Result

name;active;note
"A;B";true;
C;false;

Tips and best practices

  • Keep identifiers textual when leading zeros or length matter. Changing the file extension cannot recover information already discarded by the software that created the source.
  • Recalculate workbooks in their original application when formulas have changed. The converter reads available values and cannot guarantee that cached results reflect current business inputs.
  • Try a small sample in the destination software. Valid semicolon CSV may open as one column when the receiver expects commas or a different regional delimiter convention.

Sources and references

Frequently asked questions

Are all workbook sheets converted?

No. This interface uses the first sheet and generates one table. It neither merges sheets nor preserves workbook organization. Prepare the desired sheet separately when necessary; combining several source files is the responsibility of the merger tool.

Can I export the old XLS format?

No. XLS is accepted as input, while output choices are XLSX, CSV and JSON. XLSX creates a new value workbook without original macros or styling. Check the receiver’s requirements before selecting an available format.

Why are JSON numbers sometimes quoted?

CSV cells and text values read from workbooks remain strings in exported JSON. The tool does not decide automatically whether a reference or date should be numeric. Apply an explicit checked type conversion afterwards if your application needs specific types.

Is round-trip conversion lossless?

No. CSV does not preserve types, styling or the general distinction between null and empty values. Workbooks lose presentation and active calculations. JSON also inherits JavaScript parsing precision limits. Retain the original document as the reference for subsequent checks.

Related tools

Keep going with these tools

Tools similar or complementary to this one.

Similar tools

Flatten Nested JSON

Turn nested JSON objects into explicit path columns ready for tabular use.

Data & spreadsheetsNewUse this tool

Merge Excel or CSV files

Merge multiple Excel or CSV files into one table with automatic column alignment.

Data & spreadsheetsUse this tool

Read next

GuideBest practicesIntermediate

Build a reproducible data-preparation workflow

Put cleaning, validation, filtering, merging, comparison and conversion in a sensible order, and learn when a reusable pipeline is better than isolated tools.

29 August 20262 min