Free online SAV to JSON converter

Source format: SAV

SAV is a common file extension for SPSS data files, used by IBM SPSS Statistics and compatible statistical tools. It stores structured dataset information such as variables, value labels, missing-value definitions, and sometimes metadata like measurement levels. Researchers, analysts, social scientists, market researchers, and students often use SAV files for survey data, experiments, and other tabular datasets prepared for statistical analysis.

Target format: JSON

JSON (JavaScript Object Notation) is a lightweight, text-based data format used widely in web development, APIs, data exchange, scripting, and modern data pipelines. Its main advantages are human readability, broad software support, and easy integration with programming languages. JSON is especially useful when you want to move SPSS data into applications, scripts, or systems that expect structured text rather than a proprietary statistical format.

How to convert SAV to JSON

The best method depends on whether you need a quick export or a controlled, reproducible conversion. For most users, the most reliable approach is to use Python with a library that can read SPSS files and write JSON.

1. Install Python if it is not already available.
2. Install a reader for SPSS files, such as pyreadstat: pip install pyreadstat.
3. Use a short script to load the SAV file and export the data to JSON.

Example script:

import pyreadstat
import json

df, meta = pyreadstat.read_sav('input.sav')
records = df.to_dict(orient='records')

with open('output.json', 'w', encoding='utf-8') as f:
json.dump(records, f, ensure_ascii=False, indent=2)

This produces a JSON array of row objects, which is the most common and practical structure for tabular data.

If you prefer a desktop workflow, you can open the SAV file in IBM SPSS Statistics or another compatible tool, then export the data to a text-based format and convert it to JSON with a script. In SPSS, the exact menu options vary by version, but the general path is File → Export or File → Save As for exporting data. Some users also use LibreOffice or spreadsheet tools after importing the data, but these are usually less precise for preserving SPSS-specific metadata.

You can also convert the file on 101convert.com for free, without installing any software.

Notes on quality and limitations

SAV to JSON is not a perfect one-to-one conversion. SAV files can contain rich statistical metadata that JSON does not represent automatically unless you explicitly include it. For example, variable labels, value labels, missing-value rules, and measurement levels may be lost if you export only the raw rows.

Also note that JSON is best for data values, not for SPSS-specific analysis features. If you need to preserve metadata, consider exporting a separate JSON structure that includes both the records and the variable definitions. Another important limitation is file size: JSON can become much larger than SAV, especially for wide datasets or repeated values.

Finally, check character encoding and date handling. SPSS dates may need conversion to ISO-style strings, and non-ASCII text should be saved with UTF-8 to avoid corruption. If the dataset contains nested labels or special missing values, verify the output carefully after conversion.