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SPSS SAV to CSV Converter (Update)
AddMaple is built for analyzing SPSS survey data, with instant charts, pivots, dashboards, and AI-powered thematic coding.
No upload required. Explore the full product using a sample dataset.
If you only need a one-time file conversion to open your data in Excel, AddMaple probably is not what you are looking for.
We focus on what happens after conversion: exploring survey results, analyzing verbatims, running stats, and producing dashboards stakeholders can actually use.
Jump to free ways to convert a .sav fileSample Dataset Demo
Explore AddMaple on a sample survey dataset and see stats, charts, thematic coding, and dashboards in minutes.
“I don’t think I’ve ever had a relationship with a software company that was as responsive. I love working in AddMaple. My team loves working in AddMaple. My clients love AddMaple.”
Most analysis tools aren't built for surveys and feedback. They don't handle "select all that apply" or grids. Analysing a single question takes more steps than it should. Insight discovery hinges on outsourced data table prep, then endless Excel scrolling - hoping to spot what is important.
Too much time lost on data preparation.
Verbatims are either ignored, or analyzed in other tools, losing all links to the quant data.
Spreadsheets break on large files and require endless formulas.
Insights trapped in decks; dashboards out of the question - too slow and costly.
Old-school stats, steep learning curve, one manual test at a time, leaving insights untapped.
Forget starting with raw columns. AddMaple instantly summarises your data into tables, pivots, and charts. Begin exploring your survey results with answers, not setup tasks.
Transform open-ended responses into themes, fast. AddMaple's AI not only categorises text but highlights the exact phrases behind each theme. This means you can go from messy text data to meaningful insights with full transparency.
Static reports? Not here. AddMaple makes it easy to create Story Dashboards — interactive, shareable stories built from your charts and analysis. Say goodbye to PowerPoint slides that get buried in inboxes—now your findings are explorable and engaging for colleagues and clients.
Find insights faster. AddMaple runs statistical significance tests across all columns—including AI-generated themes—and ranks relationships by importance. This means you're instantly guided to the patterns and trends that matter most.
AddMaple takes the frustration out of analysing dates and numbers. It detects date ranges for you, enabling easy segmentation by time period. For numeric data, AddMaple creates histograms and grouped ranges right away, so you can uncover patterns without spending hours on setup.
Handling "Select all that apply" or multi-tag columns? AddMaple automatically detects these, summarises them into clear visual charts, and skips the hassle of manual column-splitting or formulas.
AddMaple takes your Likert-scale questions to the next level with elegant, neutral-aligned charts. Instantly see where opinions fall, then pivot by any other column—like demographics or preferences—to dig deeper into your data.
If you simply need to convert a .sav file to CSV, these are the most common approaches:
Best if: you already have SPSS installed.
Docs and links
Best if: you want a free desktop app that can open .sav files.
SAVE TRANSLATE
/OUTFILE='mydata.csv'
/TYPE=CSV
/FIELDNAMES
/REPLACE.Docs and links
Best if: you want a reproducible research workflow.
install.packages("haven")
library(haven)
df <- read_sav("mydata.sav")
write.csv(df, "mydata.csv", row.names = FALSE)If you want labels converted into readable text:
install.packages("labelled")
library(labelled)
df <- to_factor(df)
write.csv(df, "mydata.csv", row.names = FALSE)Best if: you want a simple Python conversion script.
pip install pyreadstat pandasimport pyreadstat
df, meta = pyreadstat.read_sav("mydata.sav")
df.to_csv("mydata.csv", index=False)Docs and links
Best if: you want a fast SQL workflow (load, filter, export).
INSTALL read_stat FROM community;
LOAD read_stat;
CREATE TABLE spss_data AS
FROM read_stat('mydata.sav');
COPY spss_data TO 'mydata.csv' (HEADER, DELIMITER ',');Best if: your goal is insight, not just file format conversion.
CSV exports usually lose SPSS metadata, including variable labels, value labels, missing value rules, and measurement types.
If your goal is analysis (not just conversion), the AddMaple tile above is the fastest path to themes, pivots, and dashboards.
Cut down the time from raw data to insights you can share.
AddMaple combines an explore-ready dashboard, a powerful stats engine, and explainable AI to help you make data-driven decisions - no data wrangling required.
We enable you to thematically code tens of thousands of open-ended responses in minutes not days. This data can then be further analyzed, visualized and explored with our powerful quant features.
Combine quantitative metrics with qualitative feedback in one platform, giving you a complete view of your survey data.
Bring your data from anywhere, AddMaple will generate an explore-ready dashboard in less than a second. No data cleaning or prep needed.
No. AddMaple is a survey and feedback analysis platform. We no longer offer a standalone conversion tool.
AddMaple supports working with survey exports including SPSS-style datasets, and is designed to instantly summarise data into pivots, charts, and dashboards.
Currently, AddMaple's instant demo experience runs on a sample dataset so you can explore the full feature set immediately.
AddMaple is an alternative approach to survey analysis, focused on fast exploration, explainable AI thematic coding, and interactive dashboards.
No. AddMaple runs analysis locally in your browser. Cloud sharing is optional and controlled by you.
Stop fighting raw exports and endless spreadsheets. AddMaple turns survey data into instant answers, charts, and dashboards.
