How to export your Apple Health data and actually see it

Getting the export

Open Health, tap your photo in the top right, scroll to the bottom and tap Export All Health Data. Your iPhone will think for a while — a few minutes is normal, and longer if you have worn a Watch for years — and then offer you a file called export.zip.

Save it somewhere you can reach it again. AirDrop to a Mac, Files, iCloud Drive, whatever suits. The export is a snapshot, not a live link: it reflects the moment you tapped the button.

What is inside

Unzip it and the bulk is one file, export.xml. Everything Health has ever recorded is in there as a flat list of Record elements — one per measurement, per source, per interval.

That last part explains the size. A single day of walking is not one row. It is dozens, because your phone recorded some of it, your Watch recorded some of it, and each of them wrote a separate entry every few minutes. Add sleep stages, heart rate samples every few seconds during a workout, audio exposure, and the file grows fast.

It also explains why a step count in the export can look higher than the one Health shows you. Health de-duplicates overlapping sources when it draws your daily total. The raw export does not, and it does not include the information needed to redo that work exactly.

Why a spreadsheet will not save you

The obvious next move is to open it in something. This is where most people stop. Spreadsheets choke well before a hundred megabytes, and XML is not tabular anyway — you would be writing a parser before you saw a single number.

The other common suggestion is to upload it to a website that will chart it for you. Think about what that means. You are handing a stranger the most detailed record of your body that exists: when you sleep, when you move, when you stopped moving for three weeks. That is not a trade worth making for a bar chart.

One square per day

The visualization that suits this data is not a line. It is a grid — one square per day, shaded by how much you moved, a year at a time. Developers know it as the GitHub contribution graph, and it works for activity for the same reason it works for code: averages hide your gaps, and a grid cannot.

We built a page that does exactly this, and nothing else. Choose your export.zip and it draws your wall in the browser. The file is read in the tab you have open. Nothing is uploaded, nothing is stored, and there is no account — which is the only honest way to handle a file like this one.

Because the shading scales to your own active days rather than to a fixed 10,000-step target, the wall shows the shape of your habit rather than how you compare to a number someone else picked.

What to look for once you can see it

Two things tend to jump out. The first is that the gaps are rarely where you remember them. Most people can name the month they fell off; few guess the right one.

The second is the shape of a restart. A row of empty squares that turns green again does not look like failure when you can see the whole year at once. It looks like a gap between two streaks, which is what it actually was.