Stats File Viewer

If you're on macOS and do anything with stats data then you'll know the pain and strife of trying to quickly review or visualise your data.

So I've created a new native macOS quick look extension and application to solve exactly that problem.

Academic and clinical data moves in proprietary formats. A collaborator sends a Stata .dta, a colleague sends an SPSS .sav, a clinical dataset arrives as SAS Transport .xpt, and an R user sends .rds. Reading any of them traditionally means owning the software that wrote them, which can run to thousands per seat.

Stats File Viewer opens all four families directly. Data browses in a fast grid with sorting and filtering across every column. Crucially, value labels are shown as labels: a gender column reads Female rather than 2, and variable labels appear alongside the cryptic variable names that statistical software encourages. Thumbnails and Quick Look show labelled data in your file browser.

Every reader is hand-written from published documentation. Stata .dta covers releases 113 to 119, spanning both the old flat binary layout and the newer tagged format with its long-string storage. SPSS .sav covers uncompressed, bytecode-compressed and zsav files. SAS Transport handles both V5 and V8, including converting IBM mainframe hexadecimal floating point into modern IEEE doubles, which is exactly as fiddly as it sounds. R files use a scoped serialization walker, and R factors map neatly onto the same value-label machinery.

All of it was verified by decoding reference files produced by pyreadstat, pyreadr and pandas, and checking the results matched digit for digit.

Features

Quick look support for range of stats data formats and software:

• Stata - .dta (releases 113–119, Stata 8 to 15+)
• SPSS - .sav and .zsav (uncompressed, compressed, and zsav)
• SAS Transport - .xpt (V5 and V8, FDA submission format)
• R - .rds and .RData (data.frames and vectors, including gzip/xz compressed)

Each allows:

• Finder thumbnails and Quick Look
• Value labels everywhere: see "Female · Undergraduate", not "2 · 4" (R factors too)
• Sort by any column; filter rows across every variable
• Variables view: every variable's type, label, and value-label mapping
• Read-only - your source files are unchanged
• 100% on-device, no accounts, universal binary

Pro features via the Mac App Store.

Demo

Pro Features (available as IAP from Mac App Store)

• Descriptive statistics: n, missing, mean, sample SD, min, median, max per variable
• Pairwise correlation matrix (Pearson r)
• Chart builder: histograms, banded means with multiple Y series (z-score normalise), bars or lines
• Scatter plots with a least-squares fit and r / r²
• CSV export of the whole dataset (raw data or labeled)

Requirements

Universal binary, so it runs on both Intel and Apple Silicon Macs.

• macOS 14 (Sonoma) or later
• Intel Mac or Apple Silicon (M1 or newer)

Installation

Download the file, unzip it, and copy it into your Applications folder. Open it once and it registers the Quick Look handler itself. Instructions are included with the download.

Apps downloaded here are signed by Apple, so you shouldn't see any Gatekeeper warnings.

Licence

What you may do: install and use the software, at no cost, on any Mac you own or control, for personal or business purposes.

What you may not do: sell, rent, lease, sublicense or otherwise charge anyone for the software; redistribute, repackage, bundle or host it for download (please point people at the official download page instead); or modify, adapt, translate, reverse-engineer, decompile or disassemble it, except to the limited extent applicable law expressly permits.

The software is licensed, not sold. All rights not expressly granted above are reserved by the copyright holder, who may offer future or paid versions under different terms.

Privacy

100% on-device. No accounts, no tracking, never connects to the internet, collects no data whatsoever.

Feedback

Please contact me with any feedback, issues, suggestions or requests!