Plotting Heart Data from an Apple Watch and iPhone

Currently Unmaintained.

11/2/2022. This project uses the lxml package which does not run on Python >v3.9.

What is this project?

This project demonstrates the steps needed to get heart data from the iPhone health app and visualize it using pandas, matplotlib and seaborn in jupyter notebooks.

A second set of notebooks shows how to merge external data with the Apple Health data. This facilitates visualizations of the Apple data organized by categories which are not available within the Apple Health data.

It is not a packaged solution. Jupyter notebooks are tools used to explore data. They are not programs with invisible innards that just run and produce output. In any case, the quantity and nature of your input data will be different and you may need or want to use your own choice of visualizations.

It is not stable. Apple's iOS 15.0.2 allows the health file to be exported As far as I know there is no formal API for the file. In the absence of an API Apple are under no obligation to keep the file format constant nor give any warning of changes. In other words everything here may stop working.

Who is it for?

Anyone who wants to see an example of how to use data science tools with Apple health data.

It not intended for anyone who wants to learn data science, jupyter notebooks, numpy, pandas, matplotlib, or seaborn.

Folder structure

As written the notebooks depend on a folder structure which looks like this:

<<Your Project Folder>>
    Data
        Raw
        Processed
    heart_health (support utilities written in pure Python)
    Notebooks
        Additional Data Visualizations
        Apple Heart Data Visualization
    Reports

Export iPhone Health Data

Demo File

Before you download your own data you may wish to experiment using the dummy export_dummy.xml. If so, rename it to export.xml and run the notebooks in the order in which they are listed below.

These instructions are accurate for iOS 15.3 at 1/29/2022.

• Open the Health app on the iPhone.
• Touch the profile picture on the top-right corner.
• Touch Export All Health Data at the bottom of the next screen.
• You will be presented with several options to export the file.
• Save the file to a convenient directory where you can unzip it.
• Unzip the export.zip file. This will produce a folder called apple_health_export. Inside the folder is a file called export.xml.
• Move the export.xml file to <<Your Project Folder>> / Data / Raw.
• The apple_health_export folder has no further use in this procedure and may be deleted.

Visualizing the iPhone Heart Data

Data Sources

The Apple watch monitors heart rate and records it in the iPhone Apple Health App.

Blood Pressure must be measured with a pressure cuff and manually entered into the iPhone Apple Health App.

The Notebooks

Apple Heart Data Analysis.ipynb

This notebook opens the export.xml file, extracts the heart data, and exports a pickled pandas dataset ready for use by the plotting functions.

Heart Rate Plots

The Heart Rate Boxenplot.ipnb notebook opens the pickled pandas dataset, extracts the heart rate data, and plots the entire dataset. Three charts are produced: boxplot, boxenplot, and combined boxenplot and observation count. The Heart Rate Lineplot.ipnb notebook also opens the pickled pandas dataset, extracts the heart rate data, and plots the entire dataset. It produces a lineplot of observation counts on the y axis against heart rate on the x axis.

Blood Pressure Boxenplot.ipynb

This notebook opens the pickled pandas dataset, extracts the blood pressure data, and plots a combined boxenplot and observation count.

A Brief Note on Boxenplots

Boxenplots show the percentiles 50%, 25% and 75%, 12. 5% and 87.5%, 6.25% and 93.75%, and so on until the visualizations become too small to be meaningful.

For further reading:
stackoverflow.com: how-boxen-plot-is-different-from-box-plot
towards data science
seaborn Docs
Original paper

Merging External Data

Data Sources

Medications and other external factors

External data is anything that the iPhone Apple Health App cannot handle such as medication dosages or environmental factors which may affect the heart. They need to be recorded in a spreadsheet and merged with the iPhone data.

The Notebooks

External Factors Analysis.ipynb

This notebook opens the External Factors.csv file, cleans up the data, and exports a pickled pandas dataset ready for merging with the Apple phone dataset .

External Factors Merge.ipynb

This notebook merges the external factor dataset with the Apple phone dataset and exports a pickled pandas dataset ready for use by the plotting notebooks.

Tablet Boxenplot.ipynb

This notebook opens the pickled pandas dataset, extracts the data from the tablet column as dosage categories, and plots a combined boxenplot and observation count. Each individual dose has its own category.

Alcohol Boxenplot.ipynb

This notebook opens the pickled pandas dataset, extracts the data from the alcohol column, creates categories based on ranges and plots a combined boxenplot and observation count.