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 "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",
    "- Filter down CGM data to only one day\n",
    "- Plot CGM data for that day"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import datetime\n",
    "\n",
    "# Read in CSV file\n",
    "df = pd.read_csv('export.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": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "# Print all days with data\n",
    "daysWithData = df['occurred_at_day'].unique()\n",
    "print(daysWithData)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "# Filter down to one day, pick the second day in the dataset\n",
    "df = df[df['occurred_at_day']==daysWithData[1]]\n",
    "\n",
    "# Chart the data\n",
    "fig = px.line(df, x = \"occurred_at\", y=\"value\")\n",
    "fig.show()"
   ],
   "outputs": [],
   "metadata": {}
  }
 ],
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