Initial commit

.gitignore

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+*.feather

README.md

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+# Apple Health Data Analysis Examples
+
+This repo contains some example scripts that use Apple Health data to produce
+visualizations and reports.
+
+## Prerequisites
+
+Use the
+[apple-health-exporter](https://github.com/mganjoo/apple-health-exporter)
+script to produce a dump of Apple Health data in this directory named
+`data.feather`. All scripts rely on the data being present in this directory
+**under this exact name**.
+
+To run the Shiny apps included here, import the `shiny` library.
+
+```r
+library(shiny)
+runApp("plotHeartRate.R")
+```
+
+## Examples
+
+* `plotHeartRate.R`: Creates an interactive time series plot of heart rate
+  data.  Adapted from [Jeff Johnston](https://github.com/jeffjjohnston)'s
+  [excellent walkthrough](https://jeffjjohnston.github.io/rstudio/rmarkdown/2016/04/28/explore-your-apple-watch-heart-rate-data.html).

loadHealthData.R

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+library(feather)
+
+dataPath = "data.feather"
+
+loadHealthData <- function() {
+  if (!file.exists(dataPath)) {
+    stop(paste("Cannot find Health data dump under", dataPath, ". Ensure",
+               "that the file has been created at this path using the",
+               "exporter.py script."))
+  } else {
+    read_feather(dataPath)
+  }
+}

plotHeartRate.R

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+library(dplyr)
+library(feather)
+library(ggplot2)
+library(lubridate)
+library(shiny)
+
+source("loadHealthData.R")
+
+heartRateData <- loadHealthData() %>%
+  filter(type == "HKQuantityTypeIdentifierHeartRate") %>%
+  mutate(dayOnly = as.Date(format(endDate, "%Y-%m-%d")))
+
+ui <- fluidPage(
+  titlePanel("Plot Heart Rate"),
+  sidebarLayout(
+    sidebarPanel(
+      helpText("View heart rate plot across a date range (granularity of 1 day)"),
+      dateRangeInput("dateRange", label = "Date range",
+                     min = min(heartRateData$dayOnly),
+                     max = max(heartRateData$dayOnly),
+                     start = max(heartRateData$dayOnly),
+                     end = max(heartRateData$dayOnly))
+    ),
+    mainPanel(
+      plotOutput("heartRate"),
+      tableOutput("dataSummary")
+    )
+  )
+)
+
+server <- function(input, output) {
+  heartRateDataForRange <- reactive({
+    begin <- as.Date(input$dateRange[1])
+    end <- as.Date(input$dateRange[2]) + days(1)
+    heartRateData %>% filter(begin <= endDate & endDate < end)
+  })
+  output$heartRate <- renderPlot({
+    heartRateDataForRange() %>%
+      ggplot(aes(x = endDate, y = value)) + geom_line() +
+      labs(x = "Date", y = "Heart rate (bpm)")
+  })
+  output$dataSummary <- renderTable({
+    heartRateDataForRange() %>%
+      summarize(
+        earliestRecord = as.character(min(endDate)),
+        latestRecord = as.character(max(endDate)),
+        maxHeartRate = max(value),
+        minHeartRate = min(value),
+        numMeasurements = n()
+      )
+  })
+}
+
+shinyApp(ui = ui, server = server)