Free online SAV to XLSX converter

SPSS users convert a dataset to XLSX when colleagues need to open, filter, edit, or report the data in Microsoft Excel. XLSX is also more suitable for sharing and general spreadsheet archiving than a statistical data file.

What the SAV format is

.sav most commonly identifies an IBM SPSS Statistics data file. It stores rows and columns together with statistical metadata, including variable names, variable labels, value labels, missing-value definitions, measurement levels, and some file or variable attributes.

SAV files are used in survey research, education, healthcare, market research, and social-science projects. IBM SPSS Statistics creates them, while GNU PSPP, R packages such as haven, and Python libraries such as pyreadstat can read or process them. The extension is not exclusive to SPSS: games and other applications may use .sav for saved-state files, which cannot be meaningfully converted to a spreadsheet without application-specific parsing.

What the XLSX format is

.xlsx is the XML-based Microsoft Excel workbook format. It is supported by Excel, LibreOffice Calc, Apple Numbers, Google Sheets, and many data-processing tools. An XLSX workbook can contain worksheets, cell values, formulas, formatting, filters, tables, and charts.

XLSX is useful when recipients need to inspect or edit tabular data without statistical software. It usually preserves the data table, but not SPSS procedures, output tables, syntax, weighting settings, measurement levels, or the complete variable and value-label metadata structure.

How to convert SAV to XLSX

Using IBM SPSS Statistics

1. Open the file with File → Open → Data and select the .sav file.
2. Review Data View and Variable View. Check variable types, labels, missing-value definitions, date variables, and value labels before exporting.
3. Use File → Save As, select Excel 2007 (*.xlsx) or the equivalent XLSX option, specify the output filename, and save.
4. When SPSS presents export options, choose whether the worksheet should contain variable names or labels and whether cells should contain underlying values or displayed value labels. Open the resulting workbook in Excel or another spreadsheet program and check representative columns.

For repeatable conversions, run SPSS syntax similar to:

GET FILE='survey.sav'.
SAVE TRANSLATE OUTFILE='survey.xlsx'
/TYPE=XLS
/VERSION=12
/FIELDNAMES
/CELLS=VALUES
/REPLACE.

In this command, /VERSION=12 selects the Excel 2007-and-later format, /FIELDNAMES writes variable names as column headings, /CELLS=VALUES writes stored values rather than displayed labels, and /REPLACE permits replacement of an existing output file. Use /CELLS=LABELS when readable value labels are required, and replace the filenames with full paths when necessary.

Using Python

Install the required packages:

pip install pyreadstat pandas openpyxl

Then convert the data table with:

import pyreadstat

df, metadata = pyreadstat.read_sav('survey.sav', apply_value_formats=False)
df.to_excel('survey.xlsx', index=False, sheet_name='Data')

Use apply_value_formats=True when the workbook should contain formatted value labels instead of numeric category codes, such as Yes and No instead of 1 and 2. This improves readability but can make the workbook less suitable for subsequent statistical processing. The metadata object contains information read from SAV; to_excel does not automatically write that metadata into the workbook.

Using the 101convert.com converter

You can convert the file on 101convert.com for free without installing software. Upload the SPSS SAV file, select XLSX as the output format, start the conversion, and download the workbook. Do not upload confidential survey, medical, financial, or personally identifiable data unless the service's privacy and retention terms allow it.

Quality and compatibility limits

• Metadata is reduced: XLSX generally contains cell values and headings, not SPSS measurement levels, user-defined missing values, weighting settings, variable roles, multiple-response definitions, or complete value-label dictionaries as structured metadata.
• Codes and labels are different exports: raw codes preserve values for later analysis, while displayed labels make the spreadsheet easier to read. Keep the original SAV file if both representations are needed.
• Dates need verification: SPSS dates may become Excel date serial values or formatted date cells. System-missing values commonly become blank cells, and user-defined missing codes may remain numeric values. Check date formatting and missing-value treatment after conversion.
• Analysis output is separate: charts, statistical tests, pivot tables, and syntax from SPSS output files are not transferred when exporting the dataset. Export required output separately.
• Excel has worksheet limits: one worksheet supports up to 1,048,576 rows and 16,384 columns. Larger datasets must be split or retained in a format designed for large tables.
• Validate the result: compare row counts, column names, data types, missing values, date fields, and several value-label columns with the original SAV file before using the XLSX file for reporting.