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DATA JSON
File conversion

Convert DATA to JSON

Verified by Adam B.· reviewed by FE Editorial ·updated Jul 7, 2026
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Is it possible to convert DATA to JSON?
Yes - DATA converts to JSON.

The most direct path is a Python/pandas script: load the .data file with tab as the separator and the correct skiprows count, then call .to_json(). Alternatively, import into LibreOffice Calc, export as CSV, and convert CSV to JSON. Count header rows in a text editor before starting.

Also to JSON: BDOB · EXPRESS · REPLIT

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Tested on macOS, Windows & Linux
Last verified Oct 2026

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Why convert DATA to JSON?

JSON is the standard interchange format for web APIs and modern data pipelines. Converting an Analysis Studio export to JSON makes the records immediately consumable by web applications, REST endpoints, and JavaScript tools that expect structured data rather than tab-delimited text.

How to convert DATA to JSON

Python (pandas) FREE

Install pandas, then load the .data file with pd.read_csv using tab as the separator and skiprows=N (where N is the number of header rows), and call .to_json('output.json', orient='records', indent=2).

LibreOffice Calc FREE

Open the .data file with Tab as the delimiter and skip header rows, then export as CSV and convert that CSV to JSON using a second script step or an online CSV-to-JSON tool.

Microsoft Excel APP

Import the .data via Data > From Text/CSV with Tab as the delimiter, save as CSV, then convert the CSV to JSON in a Python step or another tool.

About these formats

.DATA Analysis Studio Data File

A .data file is a plain-text, tab-delimited export created by Appricon Analysis Studio, a Windows data-mining and statistical-analysis program. To open it, use Analysis Studio itself, or…

Open .DATA details →
.JSON JavaScript Object Notation file

A JSON file is a plain-text data file in JavaScript Object Notation format, used by web APIs, app configurations, and data exports. Any text editor opens it - Notepad on Windows, TextEdit…

Open .JSON details →

Quality & what to watch

  • The .data file is paired with a .stp schema file that holds column names; if the .data itself has missing or numeric column headers, check the .stp for the real names before building the JSON.
  • The number of header rows to skip varies per Analysis Studio export - count them in a text editor before running the script; the wrong skiprows value shifts all columns.
  • Analysis Studio .data files may contain sensitive database records; convert locally rather than uploading to an online service.

Frequently asked questions

What does `skiprows=N` mean in the Python script?
It tells pandas to ignore the first N rows of the file, which are Analysis Studio metadata rather than actual data records.
Do I need the `.stp` file to convert to JSON?
Not strictly, but the .stp holds the column names; without it you may get numeric column headers in the JSON output.
Can I use Excel instead of Python?
Yes - import to Excel first, export as CSV, then convert the CSV to JSON; it is slower but lets you inspect and clean the data first.