Question 1

What file formats are supported?

Accepted Answer

Modern Excel (.xlsx, the ZIP-based OOXML format), legacy Excel (.xls, the binary BIFF format from Excel 97-2003), and CSV/TSV. Excel 2007+ has saved as .xlsx by default for over 15 years, so .xlsx is the common case. Legacy .xls parsing is slower and supports a slightly smaller feature set.

Question 2

How are dates handled?

Accepted Answer

Excel stores dates as serial numbers (days since 1900-01-01 for Windows Excel, or 1904-01-01 for old Mac Excel). The converter detects date-formatted cells and emits ISO 8601 strings (`2024-05-15T00:00:00.000Z`). Caveats: dates without time render as midnight UTC; dates entered as text strings stay as strings. Excel's date math has a famous bug, Feb 29, 1900 is treated as valid (it wasn't, 1900 wasn't a leap year), retained for Lotus 1-2-3 compatibility.

Question 3

What if my spreadsheet has multiple sheets?

Accepted Answer

The converter exposes a sheet selector, pick which tab to convert. To export all sheets at once, you'd export each separately and combine. For deeply nested data spread across sheets with foreign-key-style relationships, you'd merge in code after conversion.

Question 4

How are merged cells handled?

Accepted Answer

Excel's merged cells are stored as a value in the top-left cell of the merge range, with the other cells empty. Converters either: (a) propagate the value to all merged cells (each row keeps the value, common for hierarchical headers), or (b) only show the value once (matches Excel's UI but creates 'sparse' JSON). This tool picks the propagation approach because the result is more useful in code.

Question 5

What about formulas?

Accepted Answer

Formulas evaluate to their cached result at the time the file was saved. The JSON gets the value, not the formula text. So `=SUM(A1:A10)` becomes whatever sum Excel computed when the user last opened and saved the file. If you need the formula text itself for migration to another spreadsheet, that's a different tool.

Question 6

How big a file can it handle?

Accepted Answer

Excel's hard limit is ~1M rows × 16K columns. The converter parses everything in memory in your browser, so files over ~50MB may struggle on lower-spec devices. For multi-million-row datasets, use a server-side tool (Python `openpyxl`, pandas, Spark), browser memory and main-thread parsing make this an unfair fight.

Question 7

Is my file uploaded anywhere?

Accepted Answer

No. The .xlsx parser runs in your browser. Files never leave your machine. This matters because spreadsheets typically contain unredacted operational data, customer lists, financial details, employee info, that you wouldn't post to a generic converter.

Question 8

What standards does Excel to JSON validate against?

Accepted Answer

Excel to JSON checks compliance with RFC 8259 (JSON), ISO 8824-1 (ASN.1).

Question 9

What are the limitations of Excel to JSON?

Accepted Answer

Large inputs (>10 MB) may slow down the browser. Does not handle binary data. Use Base64 for binary conversion. Character encoding depends on browser settings.

Excel Feature	JSON Output	Handling Logic
Header Row	Object Keys	Normalized per column
Merged Cells	Replicated Values	Top-left propagation
Date Serial	ISO String	CSPRNG-safe ISO-8601
Formula Result	Literal Value	Cached save-state value

Excel to JSON

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What is Excel to JSON?

Frequently Asked Questions

Technical Deep Dive

Excel to JSON

Two-Way Conversion

Type-Faithful

Production-Sized

01 Data Mapping Protocol

02 Transformation Pipeline

Runs 100% in your browser

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