Convert SAV to CSV

A .sav file is a data file from IBM SPSS Statistics, and you normally need SPSS — expensive, license-managed software — to open it. There is no in-browser .sav converter on this site yet, because the format needs a real statistics library to parse. But you can still convert it for free: the fastest option with no software installs is Google Colab (below), and if you already use Python or R, jump to those sections.

No installation: Google Colab (works on any computer)

Google Colab is a free service that runs Python in your browser — nothing to install, and it works on a Chromebook or a locked-down library computer. You need only a Google account.

1. Open Colab — Go to colab.research.google.com, sign in with any Google account, and click New Notebook.
2. Upload your file — Click the folder icon in the left sidebar, then the upload button, and select your .sav file.
3. Run the code — Paste this code into the cell and press the run button:

!pip install pyreadstat
import pandas as pd
df = pd.read_spss("survey.sav")  # replace survey.sav with your file's name
df.to_csv("output.csv", index=False)

4. Download the result — Refresh the file sidebar, right-click output.csv, and choose Download.

Your uploaded file lives in a temporary private session that disappears when the tab closes — but it is processed on Google’s servers, so for confidential data prefer one of the desktop apps below, which never send your file anywhere.

Free desktop apps (no code)

• GNU PSPP — a free SPSS replacement from the GNU project, and the best pick for a straight conversion. It opens .sav files natively on Windows, macOS, and Linux. Open your file, then use File → Export and choose Comma-Separated Values to save a CSV. If you were searching for a “.sav viewer,” this is also the answer: you can browse the data and variable views just like in SPSS.
• jamovi — a free statistics app with a friendlier interface than PSPP. It imports .sav files with value labels intact, and File → Export writes CSV. The better choice if you also need to run analyses after converting.
• JASP — same pitch as jamovi: free, imports .sav (plus .zsav and .por), and exports data as CSV.

Python

Install the two required packages, then run the script:

pip install pandas pyreadstat

import pandas as pd
df = pd.read_spss("survey.sav")  # replace survey.sav with your file's name
df.to_csv("output.csv", index=False)

One thing to decide: codes or labels. SPSS columns often store numeric codes with labels attached (1 = Male, 2 = Female). pandas.read_spss writes the labels into your CSV by default; pass convert_categoricals=False to keep the raw codes. If you need both, use pyreadstat directly — df, meta = pyreadstat.read_sav("survey.sav") returns the data plus a meta object whose variable_value_labels holds every code-to-label mapping.

R

install.packages(c("haven", "readr"))
library(haven)
df <- read_sav("survey.sav")  # replace survey.sav with your file's name
readr::write_csv(df, "output.csv")

This writes the underlying numeric codes for labeled columns. To write the labels instead, convert first: df <- as_factor(df).

Which method should I use?