data-from-a-pod.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project: Fetching data from ThingsBoard\n",
    "\n",
    "[ThingsBoard](https://thingsboard.io/) is a service that accepts, processes, stores and visualizes data streams. We use it to store and plot IoT data from LoRaWAN sensors in the [Purdue OATS DataStation (POD)](https://github.com/oats-center/pod) project.\n",
    "\n",
    "In this notebook, we will go through programmatically fetching data from the ThingsBoard from a real POD deployed on Professor Buckmaster's home farm.\n",
    "\n",
    "Let us begin by importing some useful libraries that will be used throughout the notebook. Those are:\n",
    "1. requests: Makes HTTP requests. We will use it to grab data from ThingsBoard.\n",
    "2. pandas: A popular tool for doing data analysis in python.\n",
    "3. matplotlib: A tool for making graphical plots.\n",
    "4. pprint: A python module for printing variables nicely.\n",
    "\n",
    "_Note:_ I set the matplotlib style to “seaborn” because I like it better. It is not required and you are welcome to adjust it to your liking."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt # This is just so we don't have to type \"matplotlib.pyplot\" all the time.\n",
    "import pprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup some plotting styles \n",
    "%matplotlib notebook\n",
    "#%matplotlib inline # Use this if you do not want interactive plots (like we saving a final notebook with answers)\n",
    "plt.style.use('seaborn')\n",
    "\n",
    "plt.rc('font', size=20)          # controls default text sizes\n",
    "plt.rc('axes', titlesize=20)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=20)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=20)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=20)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=20)    # legend fontsize\n",
    "plt.rc('figure', titlesize=20, figsize=(15, 8))  # fontsize of the figure title\n",
    "\n",
    "# Setup a Pretty Printer\n",
    "pp = pprint.PrettyPrinter(indent=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Logging in\n",
    "\n",
    "To log into ThingsBoard as an application, you must make an HTTP request that trades a valid username / password combination for a so-called token. \n",
    "\n",
    "The token is equivalent to the username and password, but it does not actually contain the user's password, and it is time limited. This design has slight higher security posture because third party applications (like this notebook) do not have to store the users' password (and therefore can not accidentally leak it).\n",
    "\n",
    "_**Note: If the below API calls start to fail while working with this notebook, your token may have timed out. You simply need to run the below block again**_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{ 'refreshToken': 'eyJhbGciOiJIUzUxMiJ9.eyJzdWIiOiJjbGFzc0BvYXRzY2VudGVyLm9yZyIsInNjb3BlcyI6WyJSRUZSRVNIX1RPS0VOIl0sInVzZXJJZCI6ImZhODM1NzMwLWMzMzQtMTFlYy05NDg1LWVmNTY2NmRlZTkwZSIsImlzUHVibGljIjpmYWxzZSwiaXNzIjoidGhpbmdzYm9hcmQuaW8iLCJqdGkiOiJmMjU0Y2Y0YS1kYjdlLTQ1YTgtOGRhZC03YmU3YmIyYTZlZGYiLCJpYXQiOjE2NTA4ODczMTAsImV4cCI6MTY1MTQ5MjExMH0.lBZr6iyMphA4RU4xoPJu-rnGc6SRlAs0_neCjd47D0Og3zylXa5B4ltJCwUT-8NX0LtXvwqLhQ483TnlsCNljA',\n",
      "  'token': 'eyJhbGciOiJIUzUxMiJ9.eyJzdWIiOiJjbGFzc0BvYXRzY2VudGVyLm9yZyIsInNjb3BlcyI6WyJDVVNUT01FUl9VU0VSIl0sInVzZXJJZCI6ImZhODM1NzMwLWMzMzQtMTFlYy05NDg1LWVmNTY2NmRlZTkwZSIsImVuYWJsZWQiOnRydWUsImlzUHVibGljIjpmYWxzZSwidGVuYW50SWQiOiI1ZDQ5NzEwMC1iMWQ0LTExZWMtOGYyMy04ZDJiYzNkM2I4MWUiLCJjdXN0b21lcklkIjoiODA0YTk3MjAtYjFlMi0xMWVjLThmMjMtOGQyYmMzZDNiODFlIiwiaXNzIjoidGhpbmdzYm9hcmQuaW8iLCJpYXQiOjE2NTA4ODczMTAsImV4cCI6MTY1MDg5NjMxMH0.eJfo1vClPVbOEkmsXl9kVl7cJKy1cLv39gYm6aFpP7sjaCohI0GIdV7bMHZrIrT47gwKwt_AMdBnf-mcSESPRA'}\n"
     ]
    }
   ],
   "source": [
    "url=\"https://pod-buckmaster.oatscenter.org\"\n",
    "username=\"class@oatscenter.org\"\n",
    "password=\"password123\"\n",
    "\n",
    "# Fetch \n",
    "resp = requests.post(f\"{url}/api/auth/login\", json={\n",
    "            \"username\": username,\n",
    "            \"password\": password\n",
    "        }).json()\n",
    "\n",
    "# See what we got\n",
    "pp.pprint(resp)\n",
    "\n",
    "# Keep the token around\n",
    "token = resp['token']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fetching the available time series for a specific device\n",
    "\n",
    "It is a bit complex (but possible if needed) to fetch all available devices with the ThingsBoard API. So to simplify things for this demonstration, please just log into the ThingsBoard UI, navigate to the \"Devices\" page, select the device of interest, and then choose \"Copy device id\". \n",
    "\n",
    "Finally, paste the copied value into the `device_id` variable below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 'data_battery_voltage',\n",
      "  'data_data',\n",
      "  'data_fix_failed',\n",
      "  'data_heading_deg',\n",
      "  'data_in_trip',\n",
      "  'data_lat_deg',\n",
      "  'data_lon_deg',\n",
      "  'data_port',\n",
      "  'data_speed_kmph',\n",
      "  'dr',\n",
      "  'fcnt',\n",
      "  'fport',\n",
      "  'rssi',\n",
      "  'snr',\n",
      "  'status_battery_level',\n",
      "  'status_battery_level_unavailable',\n",
      "  'status_external_power_source',\n",
      "  'status_margin',\n",
      "  'data_avg_fail_sec',\n",
      "  'data_avg_fix_sec',\n",
      "  'data_avg_freshen_time_sec',\n",
      "  'data_avg_wakeups_per_trip',\n",
      "  'data_gps_failures',\n",
      "  'data_gps_successes',\n",
      "  'data_initial_battery_voltage',\n",
      "  'data_trip_count',\n",
      "  'data_tx_count',\n",
      "  'data_uptime_weeks']\n"
     ]
    }
   ],
   "source": [
    "device_id = \"32bb7330-b1e7-11ec-8f23-8d2bc3d3b81e\" # oyster-EBA3 (A GPS tracker)\n",
    "\n",
    "keys = requests.get(f\"{url}/api/plugins/telemetry/DEVICE/{device_id}/keys/timeseries\",\n",
    "                 headers={\n",
    "                     'content-type': 'application/json',\n",
    "                     'x-authorization': f\"bearer {token}\"\n",
    "                 }).json()\n",
    "\n",
    "pp.pprint(keys)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fetching a time series of interest\n",
    "\n",
    "In this case, I selected an Oyster GPS device and I want to plot the device's battery and vehicles speed over time. So I choose `data_battery_voltage` and `data_speed_kmph`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "                            {'ts': 1650502683646, 'value': '5.1'},\n",
      "                            {'ts': 1650499058580, 'value': '5.08'},\n",
      "                            {'ts': 1650495442571, 'value': '5.05'},\n",
      "                            {'ts': 1650491813600, 'value': '5.05'},\n",
      "                            {'ts': 1650491805581, 'value': '5.05'},\n",
      "                            {'ts': 1650491794587, 'value': '5.05'},\n",
      "                            {'ts': 1650491785660, 'value': '5.05'},\n",
      "                            {'ts': 1650491775749, 'value': '5.05'},\n",
      "                            {'ts': 1650491764577, 'value': '5.05'},\n",
      "                            {'ts': 1650491754591, 'value': '5.05'},\n",
      "                            {'ts': 1650491744582, 'value': '5.05'},\n",
      "                            {'ts': 1650491733567, 'value': '5.05'},\n",
      "                            {'ts': 1650491723611, 'value': '5.05'},\n",
      "                            {'ts': 1650491713934, 'value': '5.05'},\n",
      "                            {'ts': 1650491703576, 'value': '5.05'},\n",
      "                            {'ts': 1650491692638, 'value': '5.05'},\n",
      "                            {'ts': 1650491681566, 'value': '5.05'},\n",
      "                            {'ts': 1650491670598, 'value': '5.05'},\n",
      "                            {'ts': 1650491660560, 'value': '5.05'},\n",
      "                            {'ts': 1650491649591, 'value': '5.05'},\n",
      "                            {'ts': 1650491639608, 'value': '5.05'},\n",
      "                            {'ts': 1650491628587, 'value': '5.05'},\n",
      "                            {'ts': 1650491617745, 'value': '5.05'},\n",
      "                            {'ts': 1650491606649, 'value': '5.05'},\n",
      "                            {'ts': 1650491595581, 'value': '5.05'},\n",
      "                            {'ts': 1650491584615, 'value': '5.05'},\n",
      "                            {'ts': 1650491574582, 'value': '5.05'},\n",
      "                            {'ts': 1650491564592, 'value': '5.05'},\n",
      "                            {'ts': 1650491554606, 'value': '5.05'},\n",
      "                            {'ts': 1650491543585, 'value': '5.05'},\n",
      "                            {'ts': 1650491531658, 'value': '5.05'},\n",
      "                            {'ts': 1650491517587, 'value': '5.05'},\n",
      "                            {'ts': 1650491506567, 'value': '5.05'},\n",
      "                            {'ts': 1650491495599, 'value': '5.05'},\n",
      "                            {'ts': 1650491479588, 'value': '5.05'},\n",
      "                            {'ts': 1650491463752, 'value': '5.05'},\n",
      "                            {'ts': 1650491453566, 'value': '5.05'},\n",
      "                            {'ts': 1650491423609, 'value': '5.05'},\n",
      "                            {'ts': 1650491412917, 'value': '5.05'},\n",
      "                            {'ts': 1650491398645, 'value': '5.05'},\n",
      "                            {'ts': 1650491387575, 'value': '5.05'},\n",
      "                            {'ts': 1650491375597, 'value': '5.05'},\n",
      "                            {'ts': 1650491366618, 'value': '5.05'},\n",
      "                            {'ts': 1650491355525, 'value': '5.05'},\n",
      "                            {'ts': 1650491343567, 'value': '5.05'},\n",
      "                            {'ts': 1650491333604, 'value': '5.05'},\n",
      "                            {'ts': 1650491293760, 'value': '5.05'},\n",
      "                            {'ts': 1650491151911, 'value': '5.05'},\n",
      "                            {'ts': 1650453101651, 'value': '5.05'},\n",
      "                            {'ts': 1650453016562, 'value': '5.05'},\n",
      "                            {'ts': 1650453006656, 'value': '5.05'},\n",
      "                            {'ts': 1650452997607, 'value': '5.05'},\n",
      "                            {'ts': 1650452988603, 'value': '5.05'},\n",
      "                            {'ts': 1650452363546, 'value': '5.05'},\n",
      "                            {'ts': 1650448748758, 'value': '5.05'},\n",
      "                            {'ts': 1650445114579, 'value': '5.05'},\n",
      "                            {'ts': 1650441496575, 'value': '5.05'},\n",
      "                            {'ts': 1650437881603, 'value': '5.05'},\n",
      "                            {'ts': 1650434242661, 'value': '5.05'},\n",
      "                            {'ts': 1650430632585, 'value': '5.05'}],\n",
      "  'data_speed_kmph': [ {'ts': 1650736630524, 'value': '0'},\n",
      "                       {'ts': 1650732999616, 'value': '0'},\n",
      "                       {'ts': 1650729389629, 'value': '0'},\n",
      "                       {'ts': 1650725747548, 'value': '0'},\n",
      "                       {'ts': 1650722138573, 'value': '0'},\n",
      "                       {'ts': 1650718499604, 'value': '0'},\n",
      "                       {'ts': 1650714882552, 'value': '0'},\n",
      "                       {'ts': 1650711255543, 'value': '0'},\n",
      "                       {'ts': 1650707625736, 'value': '0'},\n",
      "                       {'ts': 1650703999596, 'value': '0'},\n",
      "                       {'ts': 1650700377676, 'value': '0'},\n",
      "                       {'ts': 1650696753572, 'value': '0'},\n",
      "                       {'ts': 1650693123546, 'value': '0'},\n",
      "                       {'ts': 1650689508621, 'value': '0'},\n",
      "                       {'ts': 1650685878557, 'value': '0'},\n",
      "                       {'ts': 1650682251542, 'value': '0'},\n",
      "                       {'ts': 1650678634646, 'value': '0'},\n",
      "                       {'ts': 1650675004588, 'value': '0'},\n",
      "                       {'ts': 1650671366558, 'value': '2'},\n",
      "                       {'ts': 1650667741571, 'value': '0'},\n",
      "                       {'ts': 1650664120625, 'value': '0'},\n",
      "                       {'ts': 1650664111580, 'value': '0'},\n",
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      "                       {'ts': 1650664077935, 'value': '0'},\n",
      "                       {'ts': 1650664065679, 'value': '0'},\n",
      "                       {'ts': 1650664053573, 'value': '0'},\n",
      "                       {'ts': 1650664030572, 'value': '0'},\n",
      "                       {'ts': 1650664018546, 'value': '0'},\n",
      "                       {'ts': 1650664004620, 'value': '0'},\n",
      "                       {'ts': 1650663993572, 'value': '0'},\n",
      "                       {'ts': 1650663980661, 'value': '0'},\n",
      "                       {'ts': 1650663957632, 'value': '0'},\n",
      "                       {'ts': 1650663945576, 'value': '0'},\n",
      "                       {'ts': 1650663934760, 'value': '0'},\n",
      "                       {'ts': 1650663923589, 'value': '0'},\n",
      "                       {'ts': 1650663910604, 'value': '0'},\n",
      "                       {'ts': 1650663886671, 'value': '0'},\n",
      "                       {'ts': 1650663862611, 'value': '0'},\n",
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      "                       {'ts': 1650663827608, 'value': '0'},\n",
      "                       {'ts': 1650663803677, 'value': '9'},\n",
      "                       {'ts': 1650663793606, 'value': '19'},\n",
      "                       {'ts': 1650663784930, 'value': '18'},\n",
      "                       {'ts': 1650663774765, 'value': '21'},\n",
      "                       {'ts': 1650663763570, 'value': '21'},\n",
      "                       {'ts': 1650663751615, 'value': '24'},\n",
      "                       {'ts': 1650663739611, 'value': '21'},\n",
      "                       {'ts': 1650663729598, 'value': '23'},\n",
      "                       {'ts': 1650663719638, 'value': '24'},\n",
      "                       {'ts': 1650663710662, 'value': '15'},\n",
      "                       {'ts': 1650663699593, 'value': '0'},\n",
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      "                       {'ts': 1650663649676, 'value': '0'},\n",
      "                       {'ts': 1650663640608, 'value': '42'},\n",
      "                       {'ts': 1650663616560, 'value': '102'},\n",
      "                       {'ts': 1650663596614, 'value': '98'},\n",
      "                       {'ts': 1650663535962, 'value': '84'},\n",
      "                       {'ts': 1650625792524, 'value': '92'},\n",
      "                       {'ts': 1650625748620, 'value': '80'},\n",
      "                       {'ts': 1650625733593, 'value': '59'},\n",
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      "                       {'ts': 1650491531658, 'value': '0'},\n",
      "                       {'ts': 1650491517587, 'value': '2'},\n",
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      "                       {'ts': 1650491463752, 'value': '27'},\n",
      "                       {'ts': 1650491453566, 'value': '17'},\n",
      "                       {'ts': 1650491423609, 'value': '24'},\n",
      "                       {'ts': 1650491412917, 'value': '0'},\n",
      "                       {'ts': 1650491398645, 'value': '0'},\n",
      "                       {'ts': 1650491387575, 'value': '0'},\n",
      "                       {'ts': 1650491375597, 'value': '0'},\n",
      "                       {'ts': 1650491366618, 'value': '6'},\n",
      "                       {'ts': 1650491355525, 'value': '83'},\n",
      "                       {'ts': 1650491343567, 'value': '94'},\n",
      "                       {'ts': 1650491333604, 'value': '96'},\n",
      "                       {'ts': 1650491293760, 'value': '102'},\n",
      "                       {'ts': 1650491151911, 'value': '76'},\n",
      "                       {'ts': 1650453101651, 'value': '86'},\n",
      "                       {'ts': 1650453016562, 'value': '22'},\n",
      "                       {'ts': 1650453006656, 'value': '19'},\n",
      "                       {'ts': 1650452997607, 'value': '17'},\n",
      "                       {'ts': 1650452988603, 'value': '17'},\n",
      "                       {'ts': 1650452363546, 'value': '0'},\n",
      "                       {'ts': 1650448748758, 'value': '0'},\n",
      "                       {'ts': 1650445114579, 'value': '0'},\n",
      "                       {'ts': 1650441496575, 'value': '0'},\n",
      "                       {'ts': 1650437881603, 'value': '0'},\n",
      "                       {'ts': 1650434242661, 'value': '0'},\n",
      "                       {'ts': 1650430632585, 'value': '0'}]}\n"
     ]
    }
   ],
   "source": [
    "key = ['data_battery_voltage', 'data_speed_kmph']\n",
    "start = 1650427200000 # Use: https://www.epochconverter.com/ to convert your desired date to a \"Timestamp in milliseconds\"\n",
    "stop = 1650740223000 # Use: https://www.epochconverter.com/ to convert your desired date to a \"Timestamp in milliseconds\"\n",
    "limit = 10000 # Maximum number of points to return. By default this value is small. If you want everything, set to something large.\n",
    "\n",
    "data = requests.get(f\"{url}/api/plugins/telemetry/DEVICE/{device_id}/values/timeseries\",\n",
    "             headers={\n",
    "                 'content-type': 'application/json',\n",
    "                 'x-authorization': f\"bearer {token}\"\n",
    "             },\n",
    "            params= {\n",
    "                'keys': key,\n",
    "                'startTs': start,\n",
    "                'endTs': stop,\n",
    "                'limit': limit,\n",
    "                'agg': 'NONE'\n",
    "            }).json()\n",
    "\n",
    "pp.pprint(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Convert the raw data into a Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>voltage</th>\n",
       "      <th>speed_mph</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ts</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-04-23 17:57:10.524</th>\n",
       "      <td>5.15</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-23 16:56:39.616</th>\n",
       "      <td>5.15</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-23 15:56:29.629</th>\n",
       "      <td>5.15</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-23 14:55:47.548</th>\n",
       "      <td>5.15</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-23 13:55:38.573</th>\n",
       "      <td>5.15</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-20 08:58:34.579</th>\n",
       "      <td>5.05</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-20 07:58:16.575</th>\n",
       "      <td>5.05</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-20 06:58:01.603</th>\n",
       "      <td>5.05</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-20 05:57:22.661</th>\n",
       "      <td>5.05</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-20 04:57:12.585</th>\n",
       "      <td>5.05</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>251 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         voltage  speed_mph\n",
       "ts                                         \n",
       "2022-04-23 17:57:10.524     5.15        0.0\n",
       "2022-04-23 16:56:39.616     5.15        0.0\n",
       "2022-04-23 15:56:29.629     5.15        0.0\n",
       "2022-04-23 14:55:47.548     5.15        0.0\n",
       "2022-04-23 13:55:38.573     5.15        0.0\n",
       "...                          ...        ...\n",
       "2022-04-20 08:58:34.579     5.05        0.0\n",
       "2022-04-20 07:58:16.575     5.05        0.0\n",
       "2022-04-20 06:58:01.603     5.05        0.0\n",
       "2022-04-20 05:57:22.661     5.05        0.0\n",
       "2022-04-20 04:57:12.585     5.05        0.0\n",
       "\n",
       "[251 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Parse voltage\n",
    "## Convert the raw Python map to a Pandas DataFrame\n",
    "voltage = pd.DataFrame(data['data_battery_voltage'])\n",
    "\n",
    "## Convert from string to float\n",
    "voltage[\"value\"] = voltage[\"value\"].astype(float)\n",
    "\n",
    "## ThingsBoard API calls the value timeseries \"value\", rename it to \"voltage\" for our sanity\n",
    "voltage.rename( columns={'value': 'voltage'}, inplace=True)\n",
    "\n",
    "## Convert the date \"string\" into a real Pandas date object (enables some Pandas niceties)\n",
    "voltage['ts'] = pd.to_datetime(voltage['ts'], unit='ms')\n",
    "\n",
    "# Tell Pandas to use the \"ts\" column as the index ... the x-axis of our plots and queries\n",
    "voltage.set_index('ts', inplace=True)\n",
    "    \n",
    "# Parse speed\n",
    "\n",
    "## Convert the raw Python map to a Pandas DataFrame\n",
    "speed = pd.DataFrame(data['data_speed_kmph'])\n",
    "\n",
    "## Convert from string to float and MPH\n",
    "speed[\"value\"] = speed[\"value\"].astype(float) * 0.621371 \n",
    "\n",
    "## ThingsBoard API calls the value timeseries \"value\", rename it to \"speed_kmph\" for our sanity\n",
    "speed.rename(columns={'value': 'speed_mph'}, inplace=True)\n",
    "\n",
    "## Convert the date \"string\" into a real Pandas date object (enables some Pandas niceties)\n",
    "speed['ts'] = pd.to_datetime(speed['ts'], unit='ms')\n",
    "\n",
    "# Tell Pandas to use the \"ts\" column as the index ... the x-axis of our plots and queries\n",
    "speed.set_index('ts', inplace=True)\n",
    "\n",
    "## Combine the two into one common DataFrame\n",
    "oyster = pd.concat([voltage, speed], axis=1, join=\"inner\")\n",
    "\n",
    "oyster"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The `subplot` command allows us to slice up one image and draw multiple independent figures into each slice\n",
    "# In this case, we are slicing the image into 2 rows and 1 column. We select the first slice.\n",
    "ax = plt.subplot(2, 1, 1)\n",
    "plt.plot(oyster['voltage'], '*-')\n",
    "plt.ylabel('Voltage (V)')\n",
    "plt.title('Oyster Battery Votlage')\n",
    "plt.xticks(rotation=35)\n",
    "\n",
    "plt.subplot(2, 1, 2, sharex=ax)\n",
    "plt.plot(oyster['speed_mph'], '*-')\n",
    "plt.ylabel('Speed (MPH)')\n",
    "plt.xticks(rotation=35)\n",
    "\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}