{ "cells": [ { "cell_type": "markdown", "source": [ "**What does this notebook do?**\n", "- Load the exported CGM values from NutriSense\n", "- Print out what days are included in the dataset\n", "- Pair down data to only one day, include CGM values, meals and exercise\n", "- Smooth CGM data and interpolate missing values\n", "- Pull in Garmin step information and \"run activities\" and plot them\n", "- Calculate key metrics for that day, both glucose and steps\n", "- Retrieve sleep data from an outside Excel file for that day\n", "- Create a chart of the glucose values, meals, activities, steps, sleep and include some metrics" ], "metadata": {} }, { "cell_type": "code", "execution_count": 1, "source": [ "import pandas as pd\n", "import plotly.express as px\n", "from plotly.subplots import make_subplots\n", "import plotly.graph_objects as go\n", "import datetime\n", "from datetime import date\n", "from garminconnect import (\n", " Garmin,\n", " GarminConnectConnectionError,\n", " GarminConnectTooManyRequestsError,\n", " GarminConnectAuthenticationError,\n", ")\n", "from openpyxl import Workbook, load_workbook\n", "\n", "# Read in CSV file\n", "df = pd.read_csv('export2.csv')\n", "\n", "# Remove \"time zone offset\" from \"occurred_at\" column and add new \"occurred_at_day\" column\n", "df['occurred_at_day'] = df['occurred_at'].apply(lambda x: x[:len(x) - 15])\n", "df['occurred_at'] = df['occurred_at'].apply(lambda x: x[:len(x) - 6])\n", "df.head()" ], "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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" ], "text/plain": [ " class value time length photo_url description \\\n", "0 GlucoseMeasurement 110.0 NaN NaN NaN NaN \n", "1 GlucoseMeasurement 110.0 NaN NaN NaN NaN \n", "2 GlucoseMeasurement 109.0 NaN NaN NaN NaN \n", "3 GlucoseMeasurement 104.0 NaN NaN NaN NaN \n", "4 GlucoseMeasurement 105.0 NaN NaN NaN NaN \n", "\n", " occurred_at body updated_at started_at ended_at created_by \\\n", "0 2021-09-02 07:44:20 NaN NaN NaN NaN NaN \n", "1 2021-09-02 07:29:20 NaN NaN NaN NaN NaN \n", "2 2021-09-02 07:12:27 NaN NaN NaN NaN NaN \n", "3 2021-09-02 06:57:27 NaN NaN NaN NaN NaN \n", "4 2021-09-02 06:42:27 NaN NaN NaN NaN NaN \n", "\n", " occurred_at_day \n", "0 2021-09-02 \n", "1 2021-09-02 \n", "2 2021-09-02 \n", "3 2021-09-02 \n", "4 2021-09-02 " ] }, "metadata": {}, "execution_count": 1 } ], "metadata": {} }, { "cell_type": "code", "execution_count": 2, "source": [ "# Print all days with data\n", "daysWithData = df['occurred_at_day'].unique()\n", "print(daysWithData)" ], "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "['2021-09-02' '2021-09-01' '2021-08-31' '2021-08-30' '2021-08-29'\n", " '2021-08-28' '2021-08-27' '2021-08-26' '2021-08-25' '2021-08-24'\n", " '2021-08-23' '2021-08-22' '2021-08-21' '2021-08-20' '2021-08-19'\n", " '2021-08-18' '2021-08-17' '2021-08-16' '2021-08-15' '2021-08-14'\n", " '2021-08-13' '2021-08-12' '2021-08-11' '2021-08-10' '2021-08-09'\n", " '2021-08-08' '2021-08-07' '2021-08-06' '2021-08-05']\n" ] } ], "metadata": {} }, { "cell_type": "code", "execution_count": 3, "source": [ "# Filter down to one day, pick the second day in the dataset\n", "df = df[df['occurred_at_day']==daysWithData[2]]\n", "day = daysWithData[2]\n", "\n", "# Create a datasets just with glucose measurments\n", "gm = df[df['class']=='GlucoseMeasurement']\n", "\n", "# Create a dataset for meals and exercise, sort it\n", "mealsExercise = df[((df['class']=='Meal') | (df['class']=='ExerciseActivity') )]\n", "mealsExerciseSorted = mealsExercise.sort_values(by=[\"occurred_at\"], ascending=True)" ], "outputs": [], "metadata": {} }, { "cell_type": "code", "execution_count": 4, "source": [ "# Get Garmin Data\n", "# This may not be so great, defaulting to simply retrieving the last 100 activities on Garmin.\n", "# If the day that is plotted is further in the past, this may not work.\n", "numberOfActivities = 100\n", "try:\n", " # Read UserID and Password from config file\n", " # Put your userID and password for https://connect.garmin.com/ here\n", " config = {}\n", " with open(\"config.dat\") as myfile:\n", " for line in myfile:\n", " name, var = line.partition(\"=\")[::2]\n", " config[name.strip()] = str(var).strip()\n", " # Initialize Garmin client with credentials\n", " client = Garmin(config[\"uid\"], config[\"password\"])\n", " # Login to Garmin Connect portal\n", " client.login()\n", " # Get running activities\n", " allActivities = client.get_activities(0,numberOfActivities) # 0=start, numberOfActivities=limit\n", " dayOfInterest = datetime.datetime.strptime(day, '%Y-%m-%d').date()\n", " # Get steps for the whole day\n", " allDayStepData = client.get_steps_data(dayOfInterest.isoformat())\n", "except (GarminConnectConnectionError, GarminConnectAuthenticationError, GarminConnectTooManyRequestsError,) as err:\n", " print(\"Error occured during Garmin Connect Client init: %s\" % err)\n", " quit()\n", "except Exception:\n", " print(\"Unknown error occured during Garmin Connect Client init.\")" ], "outputs": [], "metadata": {} }, { "cell_type": "code", "execution_count": 5, "source": [ "# convert garmin data in list form to Pandas dataframe\n", "dfGarmin = pd.DataFrame.from_dict(allDayStepData)\n", "\n", "# manipulate start time so that it is local (And not GMT)\n", "dfGarmin['time'] = dfGarmin['startGMT'].apply(lambda x: x[:len(x) - 5])\n", "dfGarmin['time'] = dfGarmin['time'].apply(lambda x: x[11:])\n", "offset = dfGarmin[\"time\"][0]\n", "offsetHour = int(offset.split(':')[0])\n", "offsetMinutes=int(offset.split(':')[1])\n", "dfGarmin['time'] = pd.to_datetime(dfGarmin['startGMT'])\n", "dfGarmin['time'] = dfGarmin['time'].apply(lambda x: x - datetime.timedelta(hours=offsetHour, minutes=offsetMinutes))\n", "dfGarmin" ], "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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02021-08-31T04:00:00.02021-08-31T04:15:00.00sedentaryTrue2021-08-31 00:00:00
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96 rows × 6 columns

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" ], "text/plain": [ " startGMT endGMT steps primaryActivityLevel \\\n", "0 2021-08-31T04:00:00.0 2021-08-31T04:15:00.0 0 sedentary \n", "1 2021-08-31T04:15:00.0 2021-08-31T04:30:00.0 0 sedentary \n", "2 2021-08-31T04:30:00.0 2021-08-31T04:45:00.0 0 sedentary \n", "3 2021-08-31T04:45:00.0 2021-08-31T05:00:00.0 0 sedentary \n", "4 2021-08-31T05:00:00.0 2021-08-31T05:15:00.0 0 sedentary \n", ".. ... ... ... ... \n", "91 2021-09-01T02:45:00.0 2021-09-01T03:00:00.0 0 sedentary \n", "92 2021-09-01T03:00:00.0 2021-09-01T03:15:00.0 0 sedentary \n", "93 2021-09-01T03:15:00.0 2021-09-01T03:30:00.0 0 sedentary \n", "94 2021-09-01T03:30:00.0 2021-09-01T03:45:00.0 0 sedentary \n", "95 2021-09-01T03:45:00.0 2021-09-01T04:00:00.0 0 sedentary \n", "\n", " activityLevelConstant time \n", "0 True 2021-08-31 00:00:00 \n", "1 True 2021-08-31 00:15:00 \n", "2 True 2021-08-31 00:30:00 \n", "3 True 2021-08-31 00:45:00 \n", "4 True 2021-08-31 01:00:00 \n", ".. ... ... \n", "91 True 2021-08-31 22:45:00 \n", "92 True 2021-08-31 23:00:00 \n", "93 True 2021-08-31 23:15:00 \n", "94 True 2021-08-31 23:30:00 \n", "95 True 2021-08-31 23:45:00 \n", "\n", "[96 rows x 6 columns]" ] }, "metadata": {}, "execution_count": 5 } ], "metadata": {} }, { "cell_type": "code", "execution_count": 6, "source": [ "# Just for exploring the data, lets look at all 15 minute segments that have non-zero steps\n", "dfGarmin = dfGarmin[dfGarmin.steps != 0]\n", "print(dfGarmin[['time', 'steps', 'primaryActivityLevel']])\n", "#dfGarmin.head(n=20)" ], "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " time steps primaryActivityLevel\n", "24 2021-08-31 06:00:00 271 active\n", "25 2021-08-31 06:15:00 154 sedentary\n", "26 2021-08-31 06:30:00 60 sedentary\n", "27 2021-08-31 06:45:00 108 sedentary\n", "32 2021-08-31 08:00:00 15 sedentary\n", "33 2021-08-31 08:15:00 9 sedentary\n", "35 2021-08-31 08:45:00 220 sedentary\n", "36 2021-08-31 09:00:00 2685 highlyActive\n", "37 2021-08-31 09:15:00 2682 highlyActive\n", "38 2021-08-31 09:30:00 865 generic\n", "39 2021-08-31 09:45:00 105 sedentary\n", "46 2021-08-31 11:30:00 41 sedentary\n", "47 2021-08-31 11:45:00 103 sedentary\n", "48 2021-08-31 12:00:00 1000 active\n", "49 2021-08-31 12:15:00 636 active\n", "50 2021-08-31 12:30:00 34 sedentary\n", "51 2021-08-31 12:45:00 11 sedentary\n", "52 2021-08-31 13:00:00 81 sedentary\n", "55 2021-08-31 13:45:00 33 sedentary\n", "59 2021-08-31 14:45:00 1095 active\n", "60 2021-08-31 15:00:00 121 sedentary\n", "61 2021-08-31 15:15:00 11 sedentary\n", "63 2021-08-31 15:45:00 85 sedentary\n", "64 2021-08-31 16:00:00 690 active\n", "65 2021-08-31 16:15:00 1524 active\n", "66 2021-08-31 16:30:00 223 sedentary\n", "67 2021-08-31 16:45:00 92 sedentary\n", "68 2021-08-31 17:00:00 79 sedentary\n", "70 2021-08-31 17:30:00 30 sedentary\n", "71 2021-08-31 17:45:00 206 sedentary\n", "72 2021-08-31 18:00:00 80 sedentary\n", "73 2021-08-31 18:15:00 119 sedentary\n", "74 2021-08-31 18:30:00 53 sedentary\n", "75 2021-08-31 18:45:00 306 sedentary\n", "77 2021-08-31 19:15:00 474 active\n", "78 2021-08-31 19:30:00 235 active\n", "79 2021-08-31 19:45:00 159 sedentary\n", "80 2021-08-31 20:00:00 26 sedentary\n", "82 2021-08-31 20:30:00 128 active\n" ] } ], "metadata": {} }, { "cell_type": "code", "execution_count": 7, "source": [ "# Create a dataset with just 2 columns\n", "gm_data = gm.filter(['occurred_at', 'value'])\n", "\n", "# rename the columns for easier readability\n", "gm_data.columns = ['time', 'value']\n", "\n", "# turn time column into the index and delete time column\n", "gm_data['time']= pd.to_datetime(gm_data['time'])\n", "gm_data.index = gm_data['time']\n", "del gm_data['time']\n", "\n", "gm_data = gm_data.resample('1T').mean() # add rows for every 1 minute\n", "gm_data = gm_data.interpolate(method='cubic') # interpolate the new 1 minute points with data\n", "\n", "# Calculate a few metrics\n", "threshold = 120 # this is an arbitrary threshold\n", "above = gm_data[gm_data['value'] > threshold] # create a dataset with glucose measuremnts over threshold\n", "minutesAboveThreshold = above.count()\n", "print('Number of minutes above '+str(threshold)+': '+ minutesAboveThreshold.to_string(index=False))\n", "\n", "percentageAboveThreshold = int(round(minutesAboveThreshold/(60*24)*100,0))\n", "print(\"Time above Threshold = \"+str(percentageAboveThreshold)+\"%\")\n", "\n", "averageGlucose = int(round(gm_data['value'].mean()))\n", "medianGlucose = int(round(gm_data['value'].median()))\n", "print(\"Average Glucose = \"+str(averageGlucose))\n", "print(\"Median Glucose = \"+str(medianGlucose))\n", "\n", "# Calculate statistics on the Garmin data\n", "numberOfRunningActivitiesToday = 0\n", "numberOfActivitiesToday = 0\n", "for i in range(numberOfActivities):\n", " activity = allActivities[i]\n", " activityDateTime = activity['startTimeLocal']\n", " activityDate = datetime.datetime.strptime(activityDateTime, \"%Y-%m-%d %H:%M:%S\")\n", " if str(activityDate.date()) == day:\n", " numberOfActivitiesToday = numberOfActivitiesToday + 1\n", " if activity[\"activityType\"][\"typeKey\"] == \"running\":\n", " numberOfRunningActivitiesToday = numberOfRunningActivitiesToday + 1\n", "\n", "print(\"Steps today = \"+str(dfGarmin.steps.sum()))\n", "print(\"Activities today = \"+str(numberOfActivitiesToday))\n", "print(\"Runs today = \"+str(numberOfRunningActivitiesToday))" ], "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Number of minutes above 120: 55\n", "Time above Threshold = 4%\n", "Average Glucose = 105\n", "Median Glucose = 105\n", "Steps today = 14849\n", "Activities today = 1\n", "Runs today = 1\n" ] } ], "metadata": {} }, { "cell_type": "code", "execution_count": 8, "source": [ "# The following code is very specific to how I track my sleep data and is just meant to illustrate\n", "# what is possible. The code below will basically retrieve 2 values from an Excel sheet, the first one\n", "# is when I woke up in the morning and the second one is the time I fell asleep before midnight.\n", "\n", "# Read Excel file\n", "workbook = load_workbook(filename = 'tracking.xlsx')\n", "# Load the sheet with the data I am interested in\n", "todaySheet = workbook['Today']\n", "# Loop through rows until I find the day I am looking for\n", "for x in range(3,55):\n", " cell = todaySheet[str(\"A\"+str(x))]\n", " # Skip over \"empty\" cells\n", " if cell.value is None:\n", " continue\n", " # Assume the cell contains a date value, thus convert it\n", " cellDate = cell.value.date()\n", " if str(cellDate) == str(day):\n", " sleepEnd = todaySheet[str(\"E\"+str(x))].value\n", " sleepBegin = todaySheet[str(\"F\"+str(x))].value\n", " sleepBegin = datetime.datetime.combine(date.min, datetime.datetime.strptime('23:59', '%H:%M').time()) - datetime.datetime.combine(date.min, sleepBegin)\n", " break" ], "outputs": [], "metadata": {} }, { "cell_type": "code", "execution_count": 10, "source": [ "# using subplots here to easily get a secondary y-axis\n", "fig = make_subplots(specs=[[{\"secondary_y\": True}]])\n", "# first add the glucose measurement data\n", "fig.add_trace( go.Scatter(x=gm_data.index, y=gm_data.value, mode='lines',line=dict(color=\"purple\")))\n", "\n", "# add meals and exercise to the chart\n", "yText = 145\n", "eventColor = \"green\"\n", "for index, row in mealsExerciseSorted.iterrows():\n", "\n", " # If the activity has \"run\" in the description, don't use it as it is a duplicate from Garmin\n", " if \"run\" in str(row['description']).lower(): continue\n", "\n", " # Convert the time in pandas to something that we can use as an index for the x-axis placement\n", " time = datetime.datetime.strptime(row['occurred_at'], '%Y-%m-%d %H:%M:%S')\n", "\n", " # Pick a different color depending on the event\n", " if (row['class'] == \"Meal\"): eventColor = \"black\"\n", " else: eventColor = \"green\"\n", "\n", " # Alternate text placement so adjacent text doesn't overlap\n", " if (yText >= 175): yText = 145\n", " else: yText = yText + 8\n", "\n", " # draw a vertical line at the time of the meal/exercise\n", " gmAtThatTime = gm_data.loc[str(time.replace(second=0))].value\n", " fig.add_shape(type=\"line\", xref=\"x\", yref=\"y\", x0=time, y0=gmAtThatTime, x1=time , y1=yText-2, line_color=eventColor,)\n", " \n", " # Add text\n", " fig.add_annotation(text=row['description'], xref=\"x\", yref=\"y\", x=time, y=yText, showarrow=False, font=dict(color=eventColor))\n", "\n", "# Add Garmin running activities\n", "for i in range(numberOfActivities):\n", " activity = allActivities[i]\n", " # only activities that are of type \"running\"\n", " if activity[\"activityType\"][\"typeKey\"] == \"running\":\n", " activityDateTime = activity['startTimeLocal']\n", " activityDate = datetime.datetime.strptime(activityDateTime, \"%Y-%m-%d %H:%M:%S\")\n", " if str(activityDate.date()) == day:\n", " # draw a vertical line at the time of the running activity\n", " gmAtThatTime = gm_data.loc[str(activityDate.replace(second=0))].value\n", " fig.add_shape(type=\"line\", xref=\"x\", yref=\"y\", x0=activityDateTime, y0=gmAtThatTime, x1=activityDateTime , y1=133, line_color=\"green\",)\n", " # Add text... yes this is specific to kilometers. This may need changes for miles.\n", " textDescr = str(activity['activityName']) + \" \" + str(int(round(activity['distance']/1000))) + \"K run\"\n", " fig.add_annotation(text=textDescr, xref=\"x\", yref=\"y\", x=activityDateTime, y=135, showarrow=False, font=dict(color=\"green\"))\n", "\n", "\n", "\n", "# Draw a line at the threshold\n", "fig.add_shape(type=\"line\", xref=\"x\", yref=\"y\",\n", " x0=gm_data.index[0], y0=threshold, x1=gm_data.index.max(), y1=threshold, line_color=\"red\",)\n", "\n", "# Show text box with summary values\n", "fig.add_annotation(\n", " text='Glucose Threshold = '+str(threshold)+\n", " '
Minutes above Threshold = '+str(int(round(minutesAboveThreshold,0)))+\n", " '
Time above Threshold = '+str(percentageAboveThreshold)+\"%\"+\n", " '
Average Glucose = '+str(averageGlucose)+\n", " '
Median Glucose = '+str(medianGlucose)+\n", " '
Steps Today = '+str(dfGarmin.steps.sum()),\n", " align='right', showarrow=False,\n", " xref='paper', yref='paper', x=0.002, y=0.005,\n", " bordercolor='black', borderwidth=1\n", " )\n", "\n", "# Setting primary and secondary y axis titles and ticks\n", "fig.update_layout(yaxis = dict(range=[0, 180], tick0=0, dtick=20, title_text='mg/dL'),yaxis2=dict(tick0=0, dtick=500, range=[0,4500], title_text='Steps'))\n", "# Adding step data to the chart, using the secondary y axis\n", "fig.add_trace( go.Bar(x=dfGarmin.time, y=dfGarmin.steps), secondary_y=True)\n", "\n", "# Set x axis title\n", "fig.update_xaxes(title_text=str(dayOfInterest.strftime('%A'))+ \", \" +str(day), tickformat='%H:%M')\n", "# Hide the legend\n", "fig.update_layout(showlegend=False)\n", "\n", "# Draw sleep\n", "# Morning sleep\n", "fig.add_shape(type=\"rect\",\n", " xref=\"x\", yref=\"y\",\n", " x0=gm_data.index[0], y0=57, x1=datetime.datetime.strptime(str(day) + \" \" + str(sleepEnd), '%Y-%m-%d %H:%M:%S'), y1=150,\n", " line=dict(color=\"RoyalBlue\"),fillcolor=\"LightSkyBlue\",opacity=0.5,line_width=0,)\n", "# Evening sleep\n", "fig.add_shape(type=\"rect\",\n", " xref=\"x\", yref=\"y\",\n", " x0=gm_data.index.max(), y0=57, x1=datetime.datetime.strptime(str(day) + \" \" + str(sleepBegin), '%Y-%m-%d %H:%M:%S'), y1=150,\n", " line=dict(color=\"RoyalBlue\"),fillcolor=\"LightSkyBlue\",opacity=0.5,line_width=0,)\n", "\n", "# Resize the chart\n", "fig.update_layout(autosize=False, width=1400, height=600,margin=dict(l=20, r=20, t=40, b=20),)\n", "\n", "# Show the chart\n", "fig.show()" ], "outputs": [ { "output_type": "display_data", "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "line": { "color": "purple" }, "mode": "lines", "type": "scatter", "x": [ "2021-08-31T00:11:00", "2021-08-31T00:12:00", "2021-08-31T00:13:00", "2021-08-31T00:14:00", "2021-08-31T00:15:00", "2021-08-31T00:16:00", "2021-08-31T00:17:00", "2021-08-31T00:18:00", 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