From fb538de5428768f00ef9ca00b5a9e1b58c3e1b3d Mon Sep 17 00:00:00 2001
From: Robin Cole <robmarkcole@gmail.com>
Date: Sat, 4 Jan 2020 14:57:24 +0000
Subject: [PATCH] Address reviewer comments

---
 detective/core.py                             |     7 +-
 detective/functions.py                        |    31 +-
 .../Getting started with detective.ipynb      | 76227 +---------------
 tests/test_functions.py                       |     7 -
 4 files changed, 47 insertions(+), 76225 deletions(-)

diff --git a/detective/core.py b/detective/core.py
index 7eb91bf..9d0bfb4 100644
--- a/detective/core.py
+++ b/detective/core.py
@@ -83,9 +83,8 @@ def fetch_entities(self) -> None:
         response = self.perform_query(query)
 
         # Parse the domains from the entities.
-        entities = [e[0] for e in response]
-        print(f"There are {len(entities)} entities with data")
-        self.entities = entities
+        self.entities = [e[0] for e in response]
+        print(f"There are {len(self.entities)} entities with data")
 
     def fetch_all_sensor_data(self, limit=50000) -> pd.DataFrame:
         """
@@ -98,8 +97,6 @@ def fetch_all_sensor_data(self, limit=50000) -> pd.DataFrame:
                 domain IN ('binary_sensor', 'sensor')
             AND
                 state NOT IN ('unknown', 'unavailable')
-            AND
-                last_changed = last_updated
             ORDER BY last_changed DESC
             LIMIT {limit}
             """
diff --git a/detective/functions.py b/detective/functions.py
index 8f50c9a..e375d03 100644
--- a/detective/functions.py
+++ b/detective/functions.py
@@ -7,40 +7,23 @@
 UNKNOWN = "unknown"
 
 
-def format_binary_state(state: str):
-    """Return a binary for the state of binary sensors."""
-    if state == "on":
-        return 1
-    elif state == "off":
-        return 0
-    return state
-
-
 def get_device_class(attributes: dict):
     """Return the device class."""
-    device_class = attributes.get("device_class")
-    if device_class:
-        return device_class
-    return UNKNOWN
+    return attributes.get("device_class", UNKNOWN)
 
 
 def get_unit_of_measurement(attributes: dict):
     """Return the unit_of_measurement."""
-    unit_of_measurement = attributes.get("unit_of_measurement")
-    if unit_of_measurement:
-        return unit_of_measurement
-    return UNKNOWN
+    return attributes.get("unit_of_measurement", UNKNOWN)
 
 
 def get_friendly_name(attributes: dict):
     """Return the friendly_name."""
-    friendly_name = attributes.get("friendly_name")
-    if friendly_name:
-        return friendly_name
-    return UNKNOWN
+    return attributes.get("friendly_name", UNKNOWN)
 
 
 def generate_features(df: pd.DataFrame) -> pd.DataFrame:
+    """Generate features from the attributes."""
     df["attributes"] = df["attributes"].apply(json.loads)
     df["device_class"] = df["attributes"].apply(get_device_class)
     df["unit_of_measurement"] = df["attributes"].apply(get_unit_of_measurement)
@@ -49,10 +32,8 @@ def generate_features(df: pd.DataFrame) -> pd.DataFrame:
 
 
 def format_dataframe(df: pd.DataFrame) -> pd.DataFrame:
-    df["state"] = df["state"].apply(format_binary_state)
-    df["state"] = pd.to_numeric(
-        df["state"], errors="coerce"
-    )  # coerce will return NaN if unable to convert
+    """Convert states to numeric where possible and format the last_changed."""
+    df["state"] = pd.to_numeric(df["state"], errors="coerce")
     df["last_changed"] = pd.to_datetime(
         df["last_changed"].values, errors="ignore", utc=True
     ).tz_localize(None)
diff --git a/notebooks/Getting started with detective.ipynb b/notebooks/Getting started with detective.ipynb
index 3b51ef2..3e991b7 100644
--- a/notebooks/Getting started with detective.ipynb	
+++ b/notebooks/Getting started with detective.ipynb	
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -37,13 +37,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
-     "text": "Successfully connected to database postgresql://postgres:***@192.168.1.164/homeassistant\nThere are 119 entities with data\n"
+     "text": "Successfully connected to database postgresql://postgres:***@192.168.1.164/homeassistant\nThere are 120 entities with data\n"
     }
    ],
    "source": [
@@ -71,14 +71,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/plain": "['sensor.netatmo_master_bedroom_health',\n 'sensor.mqtt_test',\n 'sensor.hue_front_porch_sensor_temperature',\n 'sensor.blink_living_room_temperature',\n 'sensor.netatmo_master_bedroom_humidity',\n 'sensor.garden_sensor_temperature',\n 'sensor.battery_state',\n 'device_tracker.robin_robin',\n 'sensor.netatmo_master_bedroom_wifi',\n 'water_heater.hot_water']"
+      "text/plain": "['sensor.netatmo_master_bedroom_health',\n 'sensor.mqtt_test',\n 'sensor.hue_front_porch_sensor_temperature',\n 'sensor.blink_living_room_temperature',\n 'persistent_notification.http_login',\n 'sensor.netatmo_master_bedroom_humidity',\n 'sensor.garden_sensor_temperature',\n 'sensor.battery_state',\n 'device_tracker.robin_robin',\n 'sensor.netatmo_master_bedroom_wifi']"
      },
-     "execution_count": 17,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -96,13 +96,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
-     "text": "The returned Pandas dataframe has 30615 rows of data.\n"
+     "text": "The returned Pandas dataframe has 37872 rows of data.\n"
     }
    ],
    "source": [
@@ -120,15 +120,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 7,
    "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>domain</th>\n      <th>entity_id</th>\n      <th>state</th>\n      <th>last_changed</th>\n      <th>attributes</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>on</td>\n      <td>2020-01-03 08:33:43.031971+00:00</td>\n      <td>{\"battery_level\": 51, \"sensitivity\": 2, \"sensi...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>off</td>\n      <td>2020-01-03 08:33:37.031839+00:00</td>\n      <td>{\"battery_level\": 51, \"sensitivity\": 2, \"sensi...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>sensor</td>\n      <td>sensor.next_train_to_wat</td>\n      <td>42</td>\n      <td>2020-01-03 08:33:26.402323+00:00</td>\n      <td>{\"station_code\": \"MAL\", \"calling_at\": \"WAT\", \"...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>sensor</td>\n      <td>sensor.hue_motion_sensor_1_light_level</td>\n      <td>21.93</td>\n      <td>2020-01-03 08:33:25.035455+00:00</td>\n      <td>{\"battery_level\": 100, \"lightlevel\": 13412, \"d...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>on</td>\n      <td>2020-01-03 08:33:25.033274+00:00</td>\n      <td>{\"battery_level\": 51, \"sensitivity\": 2, \"sensi...</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
-      "text/plain": "          domain                               entity_id  state  \\\n0  binary_sensor      binary_sensor.office_sensor_motion     on   \n1  binary_sensor      binary_sensor.office_sensor_motion    off   \n2         sensor                sensor.next_train_to_wat     42   \n3         sensor  sensor.hue_motion_sensor_1_light_level  21.93   \n4  binary_sensor      binary_sensor.office_sensor_motion     on   \n\n                      last_changed  \\\n0 2020-01-03 08:33:43.031971+00:00   \n1 2020-01-03 08:33:37.031839+00:00   \n2 2020-01-03 08:33:26.402323+00:00   \n3 2020-01-03 08:33:25.035455+00:00   \n4 2020-01-03 08:33:25.033274+00:00   \n\n                                          attributes  \n0  {\"battery_level\": 51, \"sensitivity\": 2, \"sensi...  \n1  {\"battery_level\": 51, \"sensitivity\": 2, \"sensi...  \n2  {\"station_code\": \"MAL\", \"calling_at\": \"WAT\", \"...  \n3  {\"battery_level\": 100, \"lightlevel\": 13412, \"d...  \n4  {\"battery_level\": 51, \"sensitivity\": 2, \"sensi...  "
+      "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>domain</th>\n      <th>entity_id</th>\n      <th>state</th>\n      <th>last_changed</th>\n      <th>attributes</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>sensor</td>\n      <td>sensor.office_sensor_light_level</td>\n      <td>1013.44</td>\n      <td>2020-01-04 14:55:25.044933+00:00</td>\n      <td>{\"battery_level\": 50, \"lightlevel\": 30059, \"da...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>sensor</td>\n      <td>sensor.office_sensor_temperature</td>\n      <td>16.92</td>\n      <td>2020-01-04 14:55:19.044966+00:00</td>\n      <td>{\"battery_level\": 50, \"unit_of_measurement\": \"...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>on</td>\n      <td>2020-01-04 14:55:19.042984+00:00</td>\n      <td>{\"battery_level\": 50, \"sensitivity\": 2, \"sensi...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>off</td>\n      <td>2020-01-04 14:55:13.042830+00:00</td>\n      <td>{\"battery_level\": 50, \"sensitivity\": 2, \"sensi...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>on</td>\n      <td>2020-01-04 14:55:07.043189+00:00</td>\n      <td>{\"battery_level\": 50, \"sensitivity\": 2, \"sensi...</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
+      "text/plain": "          domain                           entity_id    state  \\\n0         sensor    sensor.office_sensor_light_level  1013.44   \n1         sensor    sensor.office_sensor_temperature    16.92   \n2  binary_sensor  binary_sensor.office_sensor_motion       on   \n3  binary_sensor  binary_sensor.office_sensor_motion      off   \n4  binary_sensor  binary_sensor.office_sensor_motion       on   \n\n                      last_changed  \\\n0 2020-01-04 14:55:25.044933+00:00   \n1 2020-01-04 14:55:19.044966+00:00   \n2 2020-01-04 14:55:19.042984+00:00   \n3 2020-01-04 14:55:13.042830+00:00   \n4 2020-01-04 14:55:07.043189+00:00   \n\n                                          attributes  \n0  {\"battery_level\": 50, \"lightlevel\": 30059, \"da...  \n1  {\"battery_level\": 50, \"unit_of_measurement\": \"...  \n2  {\"battery_level\": 50, \"sensitivity\": 2, \"sensi...  \n3  {\"battery_level\": 50, \"sensitivity\": 2, \"sensi...  \n4  {\"battery_level\": 50, \"sensitivity\": 2, \"sensi...  "
      },
-     "execution_count": 19,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -152,30 +152,31 @@
     }
    ],
    "source": [
-    "It is necessary to do some formatting of the data before we can plot it, and detective provides several functions to assist. Additionally it will generate some features for you."
+    "It is necessary to do some formatting of the data before we can plot it, and detective provides several functions to assist. You should familiarise yourself with these functions and create your own."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
+    "df = df[df['domain']=='sensor']\n",
     "df = functions.generate_features(df)\n",
     "df = functions.format_dataframe(df)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 9,
    "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>domain</th>\n      <th>entity_id</th>\n      <th>state</th>\n      <th>last_changed</th>\n      <th>attributes</th>\n      <th>device_class</th>\n      <th>unit_of_measurement</th>\n      <th>friendly_name</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>1.00</td>\n      <td>2020-01-03 08:33:43.031971</td>\n      <td>{'battery_level': 51, 'sensitivity': 2, 'sensi...</td>\n      <td>motion</td>\n      <td>unknown</td>\n      <td>Office sensor motion</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>0.00</td>\n      <td>2020-01-03 08:33:37.031839</td>\n      <td>{'battery_level': 51, 'sensitivity': 2, 'sensi...</td>\n      <td>motion</td>\n      <td>unknown</td>\n      <td>Office sensor motion</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>sensor</td>\n      <td>sensor.next_train_to_wat</td>\n      <td>42.00</td>\n      <td>2020-01-03 08:33:26.402323</td>\n      <td>{'station_code': 'MAL', 'calling_at': 'WAT', '...</td>\n      <td>unknown</td>\n      <td>min</td>\n      <td>Next train to WAT</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>sensor</td>\n      <td>sensor.hue_motion_sensor_1_light_level</td>\n      <td>21.93</td>\n      <td>2020-01-03 08:33:25.035455</td>\n      <td>{'battery_level': 100, 'lightlevel': 13412, 'd...</td>\n      <td>illuminance</td>\n      <td>lx</td>\n      <td>Downstairs hallway light level</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>1.00</td>\n      <td>2020-01-03 08:33:25.033274</td>\n      <td>{'battery_level': 51, 'sensitivity': 2, 'sensi...</td>\n      <td>motion</td>\n      <td>unknown</td>\n      <td>Office sensor motion</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
-      "text/plain": "          domain                               entity_id  state  \\\n0  binary_sensor      binary_sensor.office_sensor_motion   1.00   \n1  binary_sensor      binary_sensor.office_sensor_motion   0.00   \n2         sensor                sensor.next_train_to_wat  42.00   \n3         sensor  sensor.hue_motion_sensor_1_light_level  21.93   \n4  binary_sensor      binary_sensor.office_sensor_motion   1.00   \n\n                last_changed  \\\n0 2020-01-03 08:33:43.031971   \n1 2020-01-03 08:33:37.031839   \n2 2020-01-03 08:33:26.402323   \n3 2020-01-03 08:33:25.035455   \n4 2020-01-03 08:33:25.033274   \n\n                                          attributes device_class  \\\n0  {'battery_level': 51, 'sensitivity': 2, 'sensi...       motion   \n1  {'battery_level': 51, 'sensitivity': 2, 'sensi...       motion   \n2  {'station_code': 'MAL', 'calling_at': 'WAT', '...      unknown   \n3  {'battery_level': 100, 'lightlevel': 13412, 'd...  illuminance   \n4  {'battery_level': 51, 'sensitivity': 2, 'sensi...       motion   \n\n  unit_of_measurement                   friendly_name  \n0             unknown            Office sensor motion  \n1             unknown            Office sensor motion  \n2                 min               Next train to WAT  \n3                  lx  Downstairs hallway light level  \n4             unknown            Office sensor motion  "
+      "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>domain</th>\n      <th>entity_id</th>\n      <th>state</th>\n      <th>last_changed</th>\n      <th>attributes</th>\n      <th>device_class</th>\n      <th>unit_of_measurement</th>\n      <th>friendly_name</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>sensor</td>\n      <td>sensor.office_sensor_light_level</td>\n      <td>1013.44</td>\n      <td>2020-01-04 14:55:25.044933</td>\n      <td>{'battery_level': 50, 'lightlevel': 30059, 'da...</td>\n      <td>illuminance</td>\n      <td>lx</td>\n      <td>Office sensor light level</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>sensor</td>\n      <td>sensor.office_sensor_temperature</td>\n      <td>16.92</td>\n      <td>2020-01-04 14:55:19.044966</td>\n      <td>{'battery_level': 50, 'unit_of_measurement': '...</td>\n      <td>temperature</td>\n      <td>°C</td>\n      <td>Office sensor temperature</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>sensor</td>\n      <td>sensor.blink_living_room_wifi_signal</td>\n      <td>-53.00</td>\n      <td>2020-01-04 14:54:16.017161</td>\n      <td>{'unit_of_measurement': 'dBm', 'friendly_name'...</td>\n      <td>unknown</td>\n      <td>dBm</td>\n      <td>blink Living_room Wifi Signal</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>sensor</td>\n      <td>sensor.living_room_sensor_temperature</td>\n      <td>16.87</td>\n      <td>2020-01-04 14:54:13.039709</td>\n      <td>{'battery_level': 60, 'unit_of_measurement': '...</td>\n      <td>temperature</td>\n      <td>°C</td>\n      <td>Living room sensor temperature</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>sensor</td>\n      <td>sensor.hue_front_porch_sensor_light_level</td>\n      <td>802.42</td>\n      <td>2020-01-04 14:53:01.038250</td>\n      <td>{'battery_level': 100, 'lightlevel': 29045, 'd...</td>\n      <td>illuminance</td>\n      <td>lx</td>\n      <td>Hue front porch sensor light level</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
+      "text/plain": "    domain                                  entity_id    state  \\\n0   sensor           sensor.office_sensor_light_level  1013.44   \n1   sensor           sensor.office_sensor_temperature    16.92   \n7   sensor       sensor.blink_living_room_wifi_signal   -53.00   \n8   sensor      sensor.living_room_sensor_temperature    16.87   \n14  sensor  sensor.hue_front_porch_sensor_light_level   802.42   \n\n                 last_changed  \\\n0  2020-01-04 14:55:25.044933   \n1  2020-01-04 14:55:19.044966   \n7  2020-01-04 14:54:16.017161   \n8  2020-01-04 14:54:13.039709   \n14 2020-01-04 14:53:01.038250   \n\n                                           attributes device_class  \\\n0   {'battery_level': 50, 'lightlevel': 30059, 'da...  illuminance   \n1   {'battery_level': 50, 'unit_of_measurement': '...  temperature   \n7   {'unit_of_measurement': 'dBm', 'friendly_name'...      unknown   \n8   {'battery_level': 60, 'unit_of_measurement': '...  temperature   \n14  {'battery_level': 100, 'lightlevel': 29045, 'd...  illuminance   \n\n   unit_of_measurement                       friendly_name  \n0                   lx           Office sensor light level  \n1                   °C           Office sensor temperature  \n7                  dBm       blink Living_room Wifi Signal  \n8                   °C      Living room sensor temperature  \n14                  lx  Hue front porch sensor light level  "
      },
-     "execution_count": 21,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -204,7 +205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -213,15 +214,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 11,
    "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>domain</th>\n      <th>entity_id</th>\n      <th>state</th>\n      <th>last_changed</th>\n      <th>attributes</th>\n      <th>device_class</th>\n      <th>unit_of_measurement</th>\n      <th>friendly_name</th>\n      <th>day_of_week</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>1.00</td>\n      <td>2020-01-03 08:33:43.031971</td>\n      <td>{'battery_level': 51, 'sensitivity': 2, 'sensi...</td>\n      <td>motion</td>\n      <td>unknown</td>\n      <td>Office sensor motion</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>0.00</td>\n      <td>2020-01-03 08:33:37.031839</td>\n      <td>{'battery_level': 51, 'sensitivity': 2, 'sensi...</td>\n      <td>motion</td>\n      <td>unknown</td>\n      <td>Office sensor motion</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>sensor</td>\n      <td>sensor.next_train_to_wat</td>\n      <td>42.00</td>\n      <td>2020-01-03 08:33:26.402323</td>\n      <td>{'station_code': 'MAL', 'calling_at': 'WAT', '...</td>\n      <td>unknown</td>\n      <td>min</td>\n      <td>Next train to WAT</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>sensor</td>\n      <td>sensor.hue_motion_sensor_1_light_level</td>\n      <td>21.93</td>\n      <td>2020-01-03 08:33:25.035455</td>\n      <td>{'battery_level': 100, 'lightlevel': 13412, 'd...</td>\n      <td>illuminance</td>\n      <td>lx</td>\n      <td>Downstairs hallway light level</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>binary_sensor</td>\n      <td>binary_sensor.office_sensor_motion</td>\n      <td>1.00</td>\n      <td>2020-01-03 08:33:25.033274</td>\n      <td>{'battery_level': 51, 'sensitivity': 2, 'sensi...</td>\n      <td>motion</td>\n      <td>unknown</td>\n      <td>Office sensor motion</td>\n      <td>4</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
-      "text/plain": "          domain                               entity_id  state  \\\n0  binary_sensor      binary_sensor.office_sensor_motion   1.00   \n1  binary_sensor      binary_sensor.office_sensor_motion   0.00   \n2         sensor                sensor.next_train_to_wat  42.00   \n3         sensor  sensor.hue_motion_sensor_1_light_level  21.93   \n4  binary_sensor      binary_sensor.office_sensor_motion   1.00   \n\n                last_changed  \\\n0 2020-01-03 08:33:43.031971   \n1 2020-01-03 08:33:37.031839   \n2 2020-01-03 08:33:26.402323   \n3 2020-01-03 08:33:25.035455   \n4 2020-01-03 08:33:25.033274   \n\n                                          attributes device_class  \\\n0  {'battery_level': 51, 'sensitivity': 2, 'sensi...       motion   \n1  {'battery_level': 51, 'sensitivity': 2, 'sensi...       motion   \n2  {'station_code': 'MAL', 'calling_at': 'WAT', '...      unknown   \n3  {'battery_level': 100, 'lightlevel': 13412, 'd...  illuminance   \n4  {'battery_level': 51, 'sensitivity': 2, 'sensi...       motion   \n\n  unit_of_measurement                   friendly_name  day_of_week  \n0             unknown            Office sensor motion            4  \n1             unknown            Office sensor motion            4  \n2                 min               Next train to WAT            4  \n3                  lx  Downstairs hallway light level            4  \n4             unknown            Office sensor motion            4  "
+      "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>domain</th>\n      <th>entity_id</th>\n      <th>state</th>\n      <th>last_changed</th>\n      <th>attributes</th>\n      <th>device_class</th>\n      <th>unit_of_measurement</th>\n      <th>friendly_name</th>\n      <th>day_of_week</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>sensor</td>\n      <td>sensor.office_sensor_light_level</td>\n      <td>1013.44</td>\n      <td>2020-01-04 14:55:25.044933</td>\n      <td>{'battery_level': 50, 'lightlevel': 30059, 'da...</td>\n      <td>illuminance</td>\n      <td>lx</td>\n      <td>Office sensor light level</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>sensor</td>\n      <td>sensor.office_sensor_temperature</td>\n      <td>16.92</td>\n      <td>2020-01-04 14:55:19.044966</td>\n      <td>{'battery_level': 50, 'unit_of_measurement': '...</td>\n      <td>temperature</td>\n      <td>°C</td>\n      <td>Office sensor temperature</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>sensor</td>\n      <td>sensor.blink_living_room_wifi_signal</td>\n      <td>-53.00</td>\n      <td>2020-01-04 14:54:16.017161</td>\n      <td>{'unit_of_measurement': 'dBm', 'friendly_name'...</td>\n      <td>unknown</td>\n      <td>dBm</td>\n      <td>blink Living_room Wifi Signal</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>sensor</td>\n      <td>sensor.living_room_sensor_temperature</td>\n      <td>16.87</td>\n      <td>2020-01-04 14:54:13.039709</td>\n      <td>{'battery_level': 60, 'unit_of_measurement': '...</td>\n      <td>temperature</td>\n      <td>°C</td>\n      <td>Living room sensor temperature</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>sensor</td>\n      <td>sensor.hue_front_porch_sensor_light_level</td>\n      <td>802.42</td>\n      <td>2020-01-04 14:53:01.038250</td>\n      <td>{'battery_level': 100, 'lightlevel': 29045, 'd...</td>\n      <td>illuminance</td>\n      <td>lx</td>\n      <td>Hue front porch sensor light level</td>\n      <td>5</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
+      "text/plain": "    domain                                  entity_id    state  \\\n0   sensor           sensor.office_sensor_light_level  1013.44   \n1   sensor           sensor.office_sensor_temperature    16.92   \n7   sensor       sensor.blink_living_room_wifi_signal   -53.00   \n8   sensor      sensor.living_room_sensor_temperature    16.87   \n14  sensor  sensor.hue_front_porch_sensor_light_level   802.42   \n\n                 last_changed  \\\n0  2020-01-04 14:55:25.044933   \n1  2020-01-04 14:55:19.044966   \n7  2020-01-04 14:54:16.017161   \n8  2020-01-04 14:54:13.039709   \n14 2020-01-04 14:53:01.038250   \n\n                                           attributes device_class  \\\n0   {'battery_level': 50, 'lightlevel': 30059, 'da...  illuminance   \n1   {'battery_level': 50, 'unit_of_measurement': '...  temperature   \n7   {'unit_of_measurement': 'dBm', 'friendly_name'...      unknown   \n8   {'battery_level': 60, 'unit_of_measurement': '...  temperature   \n14  {'battery_level': 100, 'lightlevel': 29045, 'd...  illuminance   \n\n   unit_of_measurement                       friendly_name  day_of_week  \n0                   lx           Office sensor light level            5  \n1                   °C           Office sensor temperature            5  \n7                  dBm       blink Living_room Wifi Signal            5  \n8                   °C      Living room sensor temperature            5  \n14                  lx  Hue front porch sensor light level            5  "
      },
-     "execution_count": 23,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -242,7 +243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -251,13 +252,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": "/usr/local/lib/python3.7/site-packages/pandas/plotting/_matplotlib/converter.py:103: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n\nTo register the converters:\n\t>>> from pandas.plotting import register_matplotlib_converters\n\t>>> register_matplotlib_converters()\n  warnings.warn(msg, FutureWarning)\n"
+    },
     {
      "data": {
-      "image/png": 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288.620796 \nL 205.522332 290.373066 \nL 205.812399 288.620796 \nL 206.682598 286.868526 \nL 208.13293 288.620796 \nL 208.422996 290.373066 \nL 208.70728 288.620796 \nL 209.287394 290.373066 \nL 210.157603 292.125336 \nL 210.447659 293.877605 \nL 211.027791 295.629875 \nL 211.31786 297.382145 \nL 211.897991 299.259577 \nL 212.188059 301.011847 \nL 213.342524 302.764117 \nL 213.632602 304.516387 \nL 215.082936 308.020926 \nL 215.657251 306.268657 \nL 215.947318 304.516387 \nL 216.527462 306.268657 \nL 217.107609 302.764117 \nL 217.977782 301.011847 \nL 218.557914 304.516387 \nL 218.847981 302.764117 \nL 219.422315 304.516387 \nL 219.712379 306.268657 \nL 220.872644 308.020926 \nL 221.162711 311.400304 \nL 221.452785 313.277736 \nL 221.742844 311.400304 \nL 222.897314 315.030006 \nL 228.692836 316.782276 \nL 228.982931 318.534545 \nL 229.563034 316.782276 \nL 229.847302 315.030006 \nL 231.87777 311.400304 \nL 232.167829 308.020926 \nL 233.038028 302.764117 \nL 233.902431 301.011847 \nL 234.482559 293.877605 \nL 235.062698 290.373066 \nL 235.642826 292.125336 \nL 236.222957 288.620796 \nL 236.797289 290.373066 \nL 237.377422 286.868526 \nL 237.667486 288.620796 \nL 238.247623 285.116256 \nL 238.827755 286.868526 \nL 239.117824 288.620796 \nL 239.697958 286.868526 \nL 239.988018 288.620796 \nL 240.562358 286.868526 \nL 243.172965 285.116256 \nL 243.463017 283.238824 \nL 244.037348 285.116256 \nL 244.327411 281.486554 \nL 244.617485 276.229745 \nL 245.197618 272.725205 \nL 246.647947 270.972935 \nL 247.222274 269.095503 \nL 247.51234 262.086424 \nL 247.80241 258.581884 \nL 248.09249 260.334154 \nL 248.382541 256.829614 \nL 248.672608 249.695373 \nL 249.832874 242.686293 \nL 250.122939 239.056592 \nL 250.413023 237.304322 \nL 250.987345 230.295242 \nL 251.56747 232.047512 \nL 251.857541 230.295242 \nL 252.437696 221.408731 \nL 252.727744 219.656461 \nL 253.307867 217.904191 \nL 253.597933 216.151921 \nL 254.752408 217.904191 \nL 255.332531 214.399652 \nL 255.622599 216.151921 \nL 256.20273 212.52222 \nL 256.782863 210.76995 \nL 257.07293 205.51314 \nL 258.227401 209.01768 \nL 259.387667 210.76995 \nL 259.961989 209.01768 \nL 260.252058 210.76995 \nL 260.832189 212.52222 \nL 261.122255 216.151921 \nL 261.702388 212.52222 \nL 262.862654 214.399652 \nL 263.727052 219.656461 \nL 264.017119 217.904191 \nL 265.177384 221.408731 \nL 265.46745 223.161001 \nL 266.047582 230.295242 \nL 267.202046 237.304322 \nL 267.782181 246.190833 \nL 268.942447 244.438563 \nL 269.522578 246.190833 \nL 269.812653 247.943103 \nL 270.102719 246.190833 \nL 271.54725 244.438563 \nL 272.997581 253.199913 \nL 273.28764 258.581884 \nL 275.022238 260.334154 \nL 275.602371 258.581884 \nL 276.182509 262.086424 \nL 276.762652 263.838694 \nL 277.046904 265.590964 \nL 277.336967 269.095503 \nL 277.62704 270.972935 \nL 278.207164 262.086424 \nL 279.947568 260.334154 \nL 280.231828 258.581884 \nL 280.811969 260.334154 \nL 281.102034 262.086424 \nL 281.392094 260.334154 \nL 281.682163 256.829614 \nL 282.262296 258.581884 \nL 283.132492 260.334154 \nL 283.712624 256.829614 \nL 284.286957 254.952182 \nL 285.447221 253.199913 \nL 286.027367 251.447643 \nL 286.317422 249.695373 \nL 286.607497 251.447643 \nL 287.18762 249.695373 \nL 287.761974 251.447643 \nL 288.052027 247.943103 \nL 288.922218 244.438563 \nL 289.502349 247.943103 \nL 290.662623 246.190833 \nL 290.952686 244.438563 \nL 291.242758 246.190833 \nL 292.107158 247.943103 \nL 292.39722 244.438563 \nL 292.687296 242.686293 \nL 293.557486 244.438563 \nL 294.137619 246.190833 \nL 294.711941 244.438563 \nL 295.002008 242.686293 \nL 295.582145 246.190833 \nL 296.162282 247.943103 \nL 296.452345 244.438563 \nL 296.742407 242.686293 \nL 297.32254 240.808861 \nL 297.612615 239.056592 \nL 298.186937 242.686293 \nL 298.767078 244.438563 \nL 299.347204 242.686293 \nL 299.927335 244.438563 \nL 300.797536 246.190833 \nL 301.371866 244.438563 \nL 301.661935 246.190833 \nL 302.242064 244.438563 \nL 304.272532 246.190833 \nL 304.846861 244.438563 \nL 305.426994 246.190833 \nL 306.007128 244.438563 \nL 306.587265 247.943103 \nL 306.877326 246.190833 \nL 308.901999 244.438563 \nL 311.796853 246.190833 \nL 312.086923 247.943103 \nL 312.957119 246.190833 \nL 313.537249 249.695373 \nL 313.827315 247.943103 \nL 314.117385 244.438563 \nL 314.407452 246.190833 \nL 314.98178 244.438563 \nL 315.561915 246.190833 \nL 316.432112 247.943103 \nL 317.012248 246.190833 \nL 317.302312 244.438563 \nL 317.882445 247.943103 \nL 318.462576 249.695373 \nL 318.746854 251.447643 \nL 319.617041 253.199913 \nL 319.907107 254.952182 \nL 320.48725 256.829614 \nL 322.221837 260.334154 \nL 322.511904 262.086424 \nL 323.092042 258.581884 \nL 323.382102 254.952182 \nL 324.542373 247.943103 \nL 325.122503 246.190833 \nL 325.412578 244.438563 \nL 325.986909 242.686293 \nL 327.727311 232.047512 \nL 328.017383 230.295242 \nL 329.461896 228.542972 \nL 329.751967 226.665541 \nL 330.332098 224.913271 \nL 330.912242 221.408731 \nL 331.492368 224.913271 \nL 332.066695 217.904191 \nL 332.646828 221.408731 \nL 333.517026 217.904191 \nL 334.097157 219.656461 \nL 335.257425 217.904191 \nL 335.541686 216.151921 \nL 336.121825 219.656461 \nL 336.411886 217.904191 \nL 336.992024 219.656461 \nL 337.572152 216.151921 \nL 338.44235 217.904191 \nL 338.732419 219.656461 \nL 339.016681 217.904191 \nL 340.176948 219.656461 \nL 340.75708 216.151921 \nL 341.047149 217.904191 \nL 341.62728 214.399652 \nL 341.911545 216.151921 \nL 343.361879 214.399652 \nL 344.522142 216.151921 \nL 345.096473 212.52222 \nL 345.676608 210.76995 \nL 345.966671 209.01768 \nL 346.256738 212.52222 \nL 346.546808 214.399652 \nL 346.836875 212.52222 \nL 347.417007 216.151921 \nL 347.707074 214.399652 \nL 348.287205 217.904191 \nL 348.571469 214.399652 \nL 349.441695 212.52222 \nL 350.021805 214.399652 \nL 350.892001 216.151921 \nL 351.472134 214.399652 \nL 351.762201 212.52222 \nL 352.336551 219.656461 \nL 352.916664 217.904191 \nL 353.206729 216.151921 \nL 354.366996 217.904191 \nL 354.947132 216.151921 \nL 355.811524 217.904191 \nL 356.391662 216.151921 \nL 357.551922 217.904191 \nL 359.866664 216.151921 \nL 360.736862 217.904191 \nL 361.02693 219.656461 \nL 361.891317 223.161001 \nL 362.471457 221.408731 \nL 362.761531 224.913271 \nL 363.631717 230.295242 \nL 363.921782 228.542972 \nL 364.791981 233.799782 \nL 365.082061 232.047512 \nL 365.946475 240.808861 \nL 366.816642 242.686293 \nL 367.106715 244.438563 \nL 367.396776 242.686293 \nL 367.976909 244.438563 \nL 368.266993 246.190833 \nL 368.841307 244.438563 \nL 369.131372 247.943103 \nL 369.711505 251.447643 \nL 370.001574 254.952182 \nL 370.581707 258.581884 \nL 371.161836 260.334154 \nL 371.451904 262.086424 \nL 372.316301 263.838694 \nL 372.606367 267.343233 \nL 373.476568 272.725205 \nL 374.346775 274.477475 \nL 374.9269 272.725205 \nL 375.211165 274.477475 \nL 375.501229 277.982015 \nL 376.081381 276.229745 \nL 376.661501 277.982015 \nL 376.951561 281.486554 \nL 378.396092 290.373066 \nL 378.976226 286.868526 \nL 380.13649 290.373066 \nL 380.426557 292.125336 \nL 380.716633 288.620796 \nL 381.006697 286.868526 \nL 381.296756 288.620796 \nL 381.871093 286.868526 \nL 382.451219 283.238824 \nL 382.741286 279.734285 \nL 383.321418 276.229745 \nL 383.901554 277.982015 \nL 384.191619 279.734285 \nL 384.481694 277.982015 \nL 385.346082 276.229745 \nL 385.926227 274.477475 \nL 386.216281 272.725205 \nL 386.506348 274.477475 \nL 387.086488 272.725205 \nL 387.376551 274.477475 \nL 388.246747 276.229745 \nL 388.531012 272.725205 \nL 388.82108 270.972935 \nL 389.111146 272.725205 \nL 391.14162 269.095503 \nL 391.721743 272.725205 \nL 392.006013 269.095503 \nL 393.456347 270.972935 \nL 394.036479 269.095503 \nL 394.906687 265.590964 \nL 395.771069 263.838694 \nL 396.351201 262.086424 \nL 399.53613 263.838694 \nL 400.696396 272.725205 \nL 403.301202 270.972935 \nL 403.881324 272.725205 \nL 405.04159 270.972935 \nL 405.621723 269.095503 \nL 405.90599 265.590964 \nL 406.486119 262.086424 \nL 407.066262 260.334154 \nL 407.936452 258.581884 \nL 408.226519 260.334154 \nL 409.090916 254.952182 \nL 409.380988 256.829614 \nL 411.411447 244.438563 \nL 411.991582 246.190833 \nL 412.275845 247.943103 \nL 412.855977 244.438563 \nL 413.436122 247.943103 \nL 414.016259 246.190833 \nL 415.466582 244.438563 \nL 417.201174 242.686293 \nL 417.491239 240.808861 \nL 417.77551 244.438563 \nL 418.065569 246.190833 \nL 418.355638 244.438563 \nL 419.220034 242.686293 \nL 420.084443 244.438563 \nL 420.374516 246.190833 \nL 420.658773 242.686293 \nL 421.813235 244.438563 \nL 422.393362 242.686293 \nL 423.553631 244.438563 \nL 423.843695 242.686293 \nL 425.578302 240.808861 \nL 425.868374 239.056592 \nL 426.158423 240.808861 \nL 426.448489 237.304322 \nL 427.312886 235.552052 \nL 427.602952 239.056592 \nL 427.893019 240.808861 \nL 428.183093 239.056592 \nL 429.337551 237.304322 \nL 429.627618 235.552052 \nL 429.911881 237.304322 \nL 430.20195 235.552052 \nL 430.782079 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156.574747 \nL 147.758512 158.327016 \nL 148.04858 156.574747 \nL 148.628748 160.079286 \nL 149.208849 156.574747 \nL 149.498913 158.327016 \nL 150.079044 156.574747 \nL 150.363311 158.327016 \nL 151.813643 156.574747 \nL 152.393788 158.327016 \nL 152.973914 156.574747 \nL 153.263973 154.822477 \nL 153.554073 156.574747 \nL 154.12837 154.822477 \nL 154.708504 158.327016 \nL 155.288635 154.822477 \nL 155.578711 156.574747 \nL 155.868769 160.079286 \nL 156.448901 158.327016 \nL 157.893434 156.574747 \nL 158.473566 160.079286 \nL 158.763637 158.327016 \nL 160.788296 156.574747 \nL 161.368433 158.327016 \nL 161.658511 160.079286 \nL 162.528694 154.822477 \nL 162.818759 156.574747 \nL 163.393092 154.822477 \nL 163.683156 156.574747 \nL 163.973223 160.079286 \nL 164.263292 158.327016 \nL 165.133491 156.574747 \nL 165.713622 153.070207 \nL 166.00369 149.440505 \nL 166.287956 147.688235 \nL 166.868088 145.935965 \nL 167.158154 144.183695 \nL 167.448219 145.935965 \nL 167.738285 144.183695 \nL 168.028354 140.679156 \nL 168.318418 142.431426 \nL 168.892776 138.926886 \nL 169.472882 131.792644 \nL 169.762952 130.040375 \nL 170.053017 131.792644 \nL 170.917424 126.535835 \nL 171.497554 117.649323 \nL 172.077687 119.401593 \nL 172.657818 115.897054 \nL 173.522218 117.649323 \nL 174.102372 114.144784 \nL 174.392409 115.897054 \nL 174.676676 112.392514 \nL 174.966741 107.010542 \nL 175.546872 103.506003 \nL 176.127005 105.258272 \nL 176.707146 103.506003 \nL 176.997204 101.753733 \nL 177.57734 105.258272 \nL 178.441745 107.010542 \nL 178.731802 110.640244 \nL 179.021869 112.392514 \nL 179.311934 110.640244 \nL 179.892076 121.153863 \nL 180.756474 115.897054 \nL 181.046533 117.649323 \nL 181.336599 121.153863 \nL 181.626663 122.906133 \nL 182.206801 124.783565 \nL 183.071193 130.040375 \nL 183.36126 128.288105 \nL 184.521525 131.792644 \nL 184.811594 130.040375 \nL 185.391724 131.792644 \nL 186.256123 130.040375 \nL 187.126334 133.544914 \nL 187.416391 138.926886 \nL 187.996521 135.297184 \nL 188.576659 138.926886 \nL 188.86672 137.049454 \nL 189.150994 138.926886 \nL 189.731117 137.049454 \nL 190.311255 144.183695 \nL 191.471516 145.935965 \nL 191.761585 147.688235 \nL 192.335913 144.183695 \nL 194.076314 145.935965 \nL 194.656446 144.183695 \nL 195.230776 147.688235 \nL 195.81091 144.183695 \nL 196.681109 145.935965 \nL 197.261241 147.688235 \nL 197.551307 149.440505 \nL 197.835584 147.688235 \nL 198.415714 145.935965 \nL 198.705789 147.688235 \nL 198.995851 153.070207 \nL 199.575976 149.440505 \nL 200.156115 156.574747 \nL 201.600661 158.327016 \nL 201.8907 160.079286 \nL 202.470833 158.327016 \nL 202.7609 160.079286 \nL 203.341036 158.327016 \nL 203.631103 156.574747 \nL 204.20543 158.327016 \nL 204.495498 156.574747 \nL 205.365696 153.070207 \nL 205.945829 156.574747 \nL 206.525985 158.327016 \nL 207.106093 154.822477 \nL 207.686235 153.070207 \nL 208.840696 156.574747 \nL 209.130756 160.079286 \nL 210.000956 161.831556 \nL 210.5811 158.327016 \nL 211.161235 161.831556 \nL 212.025621 160.079286 \nL 212.315685 161.831556 \nL 212.605751 165.336096 \nL 212.895836 163.583826 \nL 214.056085 167.213528 \nL 214.34615 168.965798 \nL 214.636217 167.213528 \nL 214.926289 168.965798 \nL 215.500614 167.213528 \nL 215.790682 170.718067 \nL 216.950948 163.583826 \nL 217.531081 167.213528 \nL 218.685544 168.965798 \nL 219.265676 165.336096 \nL 220.135876 167.213528 \nL 220.425942 168.965798 \nL 221.006081 167.213528 \nL 221.296143 165.336096 \nL 222.740671 167.213528 \nL 223.030738 168.965798 \nL 223.320807 167.213528 \nL 223.900968 168.965798 \nL 224.191011 170.718067 \nL 224.771136 168.965798 \nL 225.061208 170.718067 \nL 225.641335 168.965798 \nL 226.795802 172.470337 \nL 227.085869 175.974877 \nL 227.956065 170.718067 \nL 228.246131 167.213528 \nL 228.536197 165.336096 \nL 229.116333 168.965798 \nL 229.690662 161.831556 \nL 230.2708 160.079286 \nL 230.560864 161.831556 \nL 230.850928 165.336096 \nL 231.431062 163.583826 \nL 232.011194 167.213528 \nL 232.591324 163.583826 \nL 232.875606 165.336096 \nL 233.455732 161.831556 \nL 234.615998 163.583826 \nL 235.196128 161.831556 \nL 235.486206 163.583826 \nL 235.776266 167.213528 \nL 236.060521 168.965798 \nL 237.220793 172.470337 \nL 237.510853 174.222607 \nL 237.800925 172.470337 \nL 238.381053 174.222607 \nL 238.961186 172.470337 \nL 240.405723 168.965798 \nL 240.985854 170.718067 \nL 241.560179 167.213528 \nL 242.43038 165.336096 \nL 243.004709 161.831556 \nL 243.584854 163.583826 \nL 244.45504 158.327016 \nL 245.035183 147.688235 \nL 245.325253 149.440505 \nL 245.899579 145.935965 \nL 246.479703 144.183695 \nL 246.769773 142.431426 \nL 247.059843 138.926886 \nL 247.349904 137.049454 \nL 247.930036 130.040375 \nL 248.510177 131.792644 \nL 249.084501 128.288105 \nL 249.374568 124.783565 \nL 249.66464 122.906133 \nL 250.244768 115.897054 \nL 250.824899 114.144784 \nL 251.114986 112.392514 \nL 251.695102 103.506003 \nL 251.985164 105.258272 \nL 252.275229 103.506003 \nL 252.849569 101.753733 \nL 253.139635 100.001463 \nL 254.009827 92.867221 \nL 254.299894 91.114951 \nL 254.589961 87.610412 \nL 255.744425 84.105872 \nL 256.03449 78.7239 \nL 256.324561 76.971631 \nL 256.904691 78.7239 \nL 257.484823 75.219361 \nL 258.059156 73.467091 \nL 258.929363 71.714821 \nL 259.50951 68.210281 \nL 260.083827 71.714821 \nL 260.954022 69.962551 \nL 261.244093 71.714821 \nL 261.534164 75.219361 \nL 261.824224 76.971631 \nL 262.688613 78.7239 \nL 263.558823 84.105872 \nL 264.138948 85.858142 \nL 264.429013 89.362682 \nL 265.299216 91.114951 \nL 265.589277 89.362682 \nL 266.163627 91.114951 \nL 267.033813 94.619491 \nL 267.323876 96.496923 \nL 267.613941 94.619491 \nL 268.194085 98.249193 \nL 268.484142 101.753733 \nL 268.774208 103.506003 \nL 269.638605 105.258272 \nL 270.218743 101.753733 \nL 270.798871 105.258272 \nL 271.379006 103.506003 \nL 271.663278 107.010542 \nL 271.953334 112.392514 \nL 272.533466 114.144784 \nL 272.823543 117.649323 \nL 273.113613 115.897054 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296.852631 144.183695 \nL 297.142724 142.431426 \nL 297.432764 144.183695 \nL 298.012896 142.431426 \nL 298.302963 144.183695 \nL 299.173162 142.431426 \nL 299.463242 140.679156 \nL 300.043361 142.431426 \nL 300.327626 144.183695 \nL 300.617713 147.688235 \nL 301.197828 144.183695 \nL 301.487892 145.935965 \nL 302.358091 147.688235 \nL 302.938234 145.935965 \nL 303.228295 144.183695 \nL 303.802639 145.935965 \nL 305.252954 149.440505 \nL 305.543022 147.688235 \nL 305.833087 144.183695 \nL 306.41322 145.935965 \nL 306.703287 147.688235 \nL 307.27762 144.183695 \nL 307.857759 147.688235 \nL 308.147822 145.935965 \nL 308.727954 147.688235 \nL 310.462546 144.183695 \nL 311.042703 145.935965 \nL 311.912883 147.688235 \nL 312.493009 144.183695 \nL 312.783082 145.935965 \nL 313.073143 149.440505 \nL 313.653277 145.935965 \nL 313.937554 147.688235 \nL 314.227608 144.183695 \nL 314.517673 142.431426 \nL 314.807739 145.935965 \nL 315.387884 149.440505 \nL 315.677939 147.688235 \nL 315.968006 144.183695 \nL 316.258075 145.935965 \nL 316.548138 149.440505 \nL 316.838208 147.688235 \nL 317.122478 144.183695 \nL 317.412545 145.935965 \nL 317.992669 144.183695 \nL 318.862868 149.440505 \nL 319.443005 147.688235 \nL 319.733069 145.935965 \nL 320.887532 147.688235 \nL 322.047799 145.935965 \nL 322.337864 149.440505 \nL 322.62793 151.192775 \nL 322.917995 149.440505 \nL 323.202269 151.192775 \nL 323.7824 147.688235 \nL 324.362534 149.440505 \nL 324.942693 147.688235 \nL 325.517002 151.192775 \nL 326.677267 153.070207 \nL 326.967337 154.822477 \nL 327.257401 153.070207 \nL 328.701928 151.192775 \nL 329.282054 154.822477 \nL 330.152261 156.574747 \nL 330.73239 153.070207 \nL 331.312518 151.192775 \nL 332.176914 156.574747 \nL 332.75705 149.440505 \nL 333.337195 151.192775 \nL 333.917344 149.440505 \nL 334.497447 153.070207 \nL 335.077581 154.822477 \nL 335.361846 151.192775 \nL 335.651915 149.440505 \nL 335.941979 151.192775 \nL 336.812178 149.440505 \nL 337.392309 151.192775 \nL 338.256708 145.935965 \nL 338.836841 147.688235 \nL 339.707039 145.935965 \nL 340.287194 147.688235 \nL 341.151569 145.935965 \nL 341.441636 144.183695 \nL 343.182033 145.935965 \nL 343.762169 144.183695 \nL 344.916631 145.935965 \nL 345.496763 144.183695 \nL 346.657031 145.935965 \nL 346.947097 147.688235 \nL 347.811495 145.935965 \nL 348.391626 147.688235 \nL 348.971762 145.935965 \nL 349.261825 144.183695 \nL 349.84197 147.688235 \nL 350.422093 144.183695 \nL 350.99645 145.935965 \nL 351.866629 144.183695 \nL 352.156691 142.431426 \nL 352.446756 145.935965 \nL 354.181358 144.183695 \nL 355.051559 145.935965 \nL 355.921756 140.679156 \nL 356.211823 142.431426 \nL 356.786148 140.679156 \nL 357.366278 144.183695 \nL 358.816612 145.935965 \nL 359.106683 147.688235 \nL 359.396746 145.935965 \nL 359.976878 147.688235 \nL 360.261144 145.935965 \nL 360.551209 142.431426 \nL 361.711478 145.935965 \nL 363.446071 149.440505 \nL 364.026205 145.935965 \nL 364.316271 149.440505 \nL 364.896414 147.688235 \nL 365.476536 144.183695 \nL 365.766603 145.935965 \nL 366.056667 149.440505 \nL 366.631001 145.935965 \nL 367.211141 149.440505 \nL 367.791267 145.935965 \nL 368.081345 147.688235 \nL 369.81593 149.440505 \nL 370.106008 151.192775 \nL 370.686128 149.440505 \nL 370.976208 145.935965 \nL 371.556351 147.688235 \nL 372.426526 145.935965 \nL 372.716591 147.688235 \nL 373.290925 145.935965 \nL 373.871068 151.192775 \nL 374.451189 149.440505 \nL 374.741255 153.070207 \nL 375.321389 149.440505 \nL 376.191628 154.822477 \nL 376.765921 153.070207 \nL 377.34606 154.822477 \nL 377.926185 158.327016 \nL 378.216257 156.574747 \nL 378.796385 158.327016 \nL 380.530981 156.574747 \nL 381.40118 161.831556 \nL 381.981313 160.079286 \nL 382.27138 158.327016 \nL 382.561445 161.831556 \nL 382.851513 163.583826 \nL 383.141577 160.079286 \nL 383.721712 161.831556 \nL 384.005976 160.079286 \nL 384.58611 161.831556 \nL 385.456311 156.574747 \nL 385.746381 160.079286 \nL 386.036441 161.831556 \nL 386.616573 160.079286 \nL 387.196709 161.831556 \nL 387.771045 160.079286 \nL 388.351177 161.831556 \nL 388.931307 160.079286 \nL 389.511442 163.583826 \nL 390.091581 160.079286 \nL 391.246033 163.583826 \nL 391.826165 161.831556 \nL 392.406303 163.583826 \nL 393.566563 161.831556 \nL 394.436762 163.583826 \nL 395.301167 158.327016 \nL 395.591227 160.079286 \nL 395.881308 158.327016 \nL 396.461449 160.079286 \nL 396.751494 156.574747 \nL 397.041559 154.822477 \nL 397.331625 158.327016 \nL 397.621702 160.079286 \nL 397.911765 158.327016 \nL 399.356289 156.574747 \nL 399.646355 154.822477 \nL 400.226504 156.574747 \nL 400.516554 160.079286 \nL 401.096693 156.574747 \nL 401.676818 160.079286 \nL 402.831283 153.070207 \nL 403.121353 156.574747 \nL 403.411419 158.327016 \nL 403.99155 154.822477 \nL 404.281615 156.574747 \nL 404.571684 154.822477 \nL 405.72615 158.327016 \nL 406.016213 160.079286 \nL 406.59635 158.327016 \nL 407.460744 160.079286 \nL 408.040878 161.831556 \nL 408.330944 167.213528 \nL 408.621011 168.965798 \nL 409.201154 165.336096 \nL 410.935738 167.213528 \nL 411.225805 168.965798 \nL 411.51588 167.213528 \nL 412.676138 168.965798 \nL 412.966202 167.213528 \nL 413.250468 163.583826 \nL 413.830614 165.336096 \nL 414.410736 163.583826 \nL 414.7008 161.831556 \nL 414.990872 163.583826 \nL 415.570999 165.336096 \nL 415.861064 167.213528 \nL 416.151155 163.583826 \nL 416.435398 161.831556 \nL 416.725474 163.583826 \nL 417.015532 167.213528 \nL 417.58987 163.583826 \nL 418.170014 165.336096 \nL 418.460068 167.213528 \nL 419.0402 163.583826 \nL 419.904591 161.831556 \nL 420.194659 163.583826 \nL 420.774791 161.831556 \nL 421.064858 163.583826 \nL 421.639191 161.831556 \nL 421.929258 160.079286 \nL 422.509387 163.583826 \nL 422.799462 161.831556 \nL 423.379589 163.583826 \nL 423.669652 165.336096 \nL 425.694325 163.583826 \nL 425.984383 161.831556 \nL 426.274451 163.583826 \nL 426.854582 165.336096 \nL 427.718992 170.718067 \nL 428.299111 168.965798 \nL 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137.049454 \nL 252.242358 138.926886 \nL 252.482425 140.679156 \nL 253.202524 138.926886 \nL 253.442572 137.049454 \nL 253.682609 138.926886 \nL 254.157881 140.679156 \nL 254.878005 142.431426 \nL 255.118046 140.679156 \nL 255.598132 138.926886 \nL 256.078211 140.679156 \nL 256.318249 142.431426 \nL 256.558298 145.935965 \nL 257.033571 144.183695 \nL 257.273634 142.431426 \nL 257.513653 144.183695 \nL 257.993734 142.431426 \nL 258.233776 144.183695 \nL 258.953898 142.431426 \nL 259.19395 140.679156 \nL 259.674021 142.431426 \nL 259.909261 144.183695 \nL 260.149318 147.688235 \nL 260.629385 144.183695 \nL 260.869425 145.935965 \nL 261.589547 147.688235 \nL 262.069638 145.935965 \nL 262.309674 144.183695 \nL 262.784966 145.935965 \nL 263.985156 149.440505 \nL 264.225199 147.688235 \nL 264.465238 144.183695 \nL 264.94532 145.935965 \nL 265.185362 147.688235 \nL 265.660644 144.183695 \nL 266.140731 147.688235 \nL 266.380769 145.935965 \nL 266.860851 147.688235 \nL 268.296291 144.183695 \nL 268.776393 145.935965 \nL 269.4965 147.688235 \nL 269.976576 144.183695 \nL 270.216623 145.935965 \nL 270.456659 149.440505 \nL 270.936742 145.935965 \nL 271.171992 147.688235 \nL 271.412022 144.183695 \nL 271.652063 142.431426 \nL 271.892103 145.935965 \nL 272.372195 149.440505 \nL 272.612226 147.688235 \nL 272.852268 144.183695 \nL 273.092311 145.935965 \nL 273.332349 149.440505 \nL 273.572393 147.688235 \nL 273.807637 144.183695 \nL 274.047678 145.935965 \nL 274.527753 144.183695 \nL 275.247876 149.440505 \nL 275.727962 147.688235 \nL 275.968 145.935965 \nL 276.923362 147.688235 \nL 277.883527 145.935965 \nL 278.123567 149.440505 \nL 278.363607 151.192775 \nL 278.603647 149.440505 \nL 278.838895 151.192775 \nL 279.318975 147.688235 \nL 279.799058 149.440505 \nL 280.279161 147.688235 \nL 280.754424 151.192775 \nL 281.714587 153.070207 \nL 281.954631 154.822477 \nL 282.19467 153.070207 \nL 283.390071 151.192775 \nL 283.870147 154.822477 \nL 284.590277 156.574747 \nL 285.070356 153.070207 \nL 285.550433 151.192775 \nL 286.265754 156.574747 \nL 286.745839 149.440505 \nL 287.22593 151.192775 \nL 287.706026 149.440505 \nL 288.186083 153.070207 \nL 288.666166 154.822477 \nL 288.901406 151.192775 \nL 289.141448 149.440505 \nL 289.381488 151.192775 \nL 290.10161 149.440505 \nL 290.58169 151.192775 \nL 291.297013 145.935965 \nL 291.777096 147.688235 \nL 292.497217 145.935965 \nL 292.977318 147.688235 \nL 293.692621 145.935965 \nL 293.932663 144.183695 \nL 295.372907 145.935965 \nL 295.852991 144.183695 \nL 296.808353 145.935965 \nL 297.288434 144.183695 \nL 298.248599 145.935965 \nL 298.48864 147.688235 \nL 299.203962 145.935965 \nL 299.684042 147.688235 \nL 300.164127 145.935965 \nL 300.404165 144.183695 \nL 300.884258 147.688235 \nL 301.364331 144.183695 \nL 301.839633 145.935965 \nL 302.559739 144.183695 \nL 302.799776 142.431426 \nL 303.039816 145.935965 \nL 304.475265 144.183695 \nL 305.19539 145.935965 \nL 305.915511 140.679156 \nL 306.155552 142.431426 \nL 306.630828 140.679156 \nL 307.110908 144.183695 \nL 308.311114 145.935965 \nL 308.551158 147.688235 \nL 308.791196 145.935965 \nL 309.271278 147.688235 \nL 309.506519 145.935965 \nL 309.746558 142.431426 \nL 310.706725 145.935965 \nL 312.142166 149.440505 \nL 312.622249 145.935965 \nL 312.86229 149.440505 \nL 313.34238 147.688235 \nL 313.822453 144.183695 \nL 314.062495 145.935965 \nL 314.302533 149.440505 \nL 314.777817 145.935965 \nL 315.257905 149.440505 \nL 315.73798 145.935965 \nL 315.978031 147.688235 \nL 317.413466 149.440505 \nL 317.653517 151.192775 \nL 318.133588 149.440505 \nL 318.37364 145.935965 \nL 318.853731 147.688235 \nL 319.573833 145.935965 \nL 319.813873 147.688235 \nL 320.289157 145.935965 \nL 320.769247 151.192775 \nL 321.249319 149.440505 \nL 321.48936 153.070207 \nL 321.969442 149.440505 \nL 322.689598 154.822477 \nL 323.164848 153.070207 \nL 323.644935 154.822477 \nL 324.12501 158.327016 \nL 324.365055 156.574747 \nL 324.845133 158.327016 \nL 326.280577 156.574747 \nL 327.0007 161.831556 \nL 327.480781 160.079286 \nL 327.720823 158.327016 \nL 327.960863 161.831556 \nL 328.200905 163.583826 \nL 328.440944 160.079286 \nL 328.921028 161.831556 \nL 329.156267 160.079286 \nL 329.63635 161.831556 \nL 330.356474 156.574747 \nL 330.596519 160.079286 \nL 330.836554 161.831556 \nL 331.316635 160.079286 \nL 331.79672 161.831556 \nL 332.272005 160.079286 \nL 332.752086 161.831556 \nL 333.232165 160.079286 \nL 333.712249 163.583826 \nL 334.192336 160.079286 \nL 335.147688 163.583826 \nL 335.62777 161.831556 \nL 336.107856 163.583826 \nL 337.068015 161.831556 \nL 337.788138 163.583826 \nL 338.503466 158.327016 \nL 338.743502 160.079286 \nL 338.983555 158.327016 \nL 339.463643 160.079286 \nL 339.703667 156.574747 \nL 339.943706 154.822477 \nL 340.183747 158.327016 \nL 340.423796 160.079286 \nL 340.663835 158.327016 \nL 341.859233 156.574747 \nL 342.099274 154.822477 \nL 342.579369 156.574747 \nL 342.819396 160.079286 \nL 343.299483 156.574747 \nL 343.779559 160.079286 \nL 344.734922 153.070207 \nL 344.974967 156.574747 \nL 345.215007 158.327016 \nL 345.695088 154.822477 \nL 345.935127 156.574747 \nL 346.17517 154.822477 \nL 347.130535 158.327016 \nL 347.370573 160.079286 \nL 347.850658 158.327016 \nL 348.565977 160.079286 \nL 349.046059 161.831556 \nL 349.2861 167.213528 \nL 349.526141 168.965798 \nL 350.006232 165.336096 \nL 351.441666 167.213528 \nL 351.681707 168.965798 \nL 351.921755 167.213528 \nL 352.881913 168.965798 \nL 353.121952 167.213528 \nL 353.357193 163.583826 \nL 353.837285 165.336096 \nL 354.317359 163.583826 \nL 354.557398 161.831556 \nL 354.797443 163.583826 \nL 355.27752 165.336096 \nL 355.51756 167.213528 \nL 355.757621 163.583826 \nL 355.992843 161.831556 \nL 356.232892 163.583826 \nL 356.472926 167.213528 \nL 356.948212 163.583826 \nL 357.428304 165.336096 \nL 357.668334 167.213528 \nL 358.148415 163.583826 \nL 358.863732 161.831556 \nL 359.103774 163.583826 \nL 359.583856 161.831556 \nL 359.823897 163.583826 \nL 360.299179 161.831556 \nL 360.539221 160.079286 \nL 361.019299 163.583826 \nL 361.259348 161.831556 \nL 361.739424 163.583826 \nL 361.979462 165.336096 \nL 363.654956 163.583826 \nL 363.89499 161.831556 \nL 364.135032 163.583826 \nL 364.615113 165.336096 \nL 365.330445 170.718067 \nL 365.810515 168.965798 \nL 366.2906 165.336096 \nL 366.770689 172.470337 \nL 367.010721 170.718067 \nL 367.245966 167.213528 \nL 367.726047 163.583826 \nL 367.966083 167.213528 \nL 368.446167 161.831556 \nL 368.926248 165.336096 \nL 369.161495 161.831556 \nL 369.40156 160.079286 \nL 369.64157 161.831556 \nL 370.601737 160.079286 \nL 371.07702 158.327016 \nL 371.557097 154.822477 \nL 371.792336 151.192775 \nL 372.032376 149.440505 \nL 372.512465 147.688235 \nL 372.992542 144.183695 \nL 373.232581 140.679156 \nL 373.707865 147.688235 \nL 374.423189 145.935965 \nL 374.663231 144.183695 \nL 375.143323 147.688235 \nL 375.38337 145.935965 \nL 375.86344 147.688235 \nL 377.05884 149.440505 \nL 377.298897 153.070207 \nL 378.014197 158.327016 \nL 378.73432 153.070207 \nL 379.449644 156.574747 \nL 379.929733 151.192775 \nL 380.409825 153.070207 \nL 380.649851 151.192775 \nL 381.129928 149.440505 \nL 381.369969 147.688235 \nL 381.84525 149.440505 \nL 382.325333 147.688235 \nL 382.805413 154.822477 \nL 383.525537 153.070207 \nL 383.765578 151.192775 \nL 384.72094 154.822477 \nL 384.960981 158.327016 \nL 385.201041 156.574747 \nL 385.681111 154.822477 \nL 385.921164 153.070207 \nL 386.161186 156.574747 \nL 386.401229 158.327016 \nL 386.881308 160.079286 \nL 387.356588 156.574747 \nL 387.596632 158.327016 \nL 388.31676 160.079286 \nL 388.556797 161.831556 \nL 388.796834 160.079286 \nL 390.23228 161.831556 \nL 390.47232 160.079286 \nL 391.192446 165.336096 \nL 391.672526 163.583826 \nL 392.152607 165.336096 \nL 392.392649 161.831556 \nL 392.63269 163.583826 \nL 392.87273 167.213528 \nL 393.107971 165.336096 \nL 393.588065 167.213528 \nL 393.828113 168.965798 \nL 394.068134 172.470337 \nL 394.548224 167.213528 \nL 395.028297 168.965798 \nL 395.748421 170.718067 \nL 396.2237 168.965798 \nL 396.703785 170.718067 \nL 397.663974 168.965798 \nL 397.903988 170.718067 \nL 398.38407 167.213528 \nL 398.624118 170.718067 \nL 398.859369 172.470337 \nL 399.099408 170.718067 \nL 399.33944 167.213528 \nL 399.579493 168.965798 \nL 400.059559 167.213528 \nL 400.299603 168.965798 \nL 400.539639 172.470337 \nL 401.01973 168.965798 \nL 401.259764 170.718067 \nL 401.499822 174.222607 \nL 401.975081 168.965798 \nL 402.455164 170.718067 \nL 402.695204 168.965798 \nL 402.935245 170.718067 \nL 403.655368 172.470337 \nL 404.135462 168.965798 \nL 405.330854 170.718067 \nL 405.570895 172.470337 \nL 406.291025 167.213528 \nL 406.531068 170.718067 \nL 407.251181 168.965798 \nL 407.491222 165.336096 \nL 407.966504 161.831556 \nL 408.686626 160.079286 \nL 408.926667 158.327016 \nL 409.646789 156.574747 \nL 410.126872 160.079286 \nL 410.366917 158.327016 \nL 410.842193 160.079286 \nL 411.082233 158.327016 \nL 412.522479 161.831556 \nL 413.002568 160.079286 \nL 413.24261 156.574747 \nL 413.482643 154.822477 \nL 413.717884 156.574747 \nL 414.197965 158.327016 \nL 414.438006 160.079286 \nL 414.918111 158.327016 \nL 415.39819 154.822477 \nL 415.638211 158.327016 \nL 416.358335 160.079286 \nL 416.593574 158.327016 \nL 416.833614 160.079286 \nL 417.313696 156.574747 \nL 418.749144 160.079286 \nL 418.989181 161.831556 \nL 419.469264 158.327016 \nL 419.949344 161.831556 \nL 420.429428 158.327016 \nL 420.909509 161.831556 \nL 421.629632 156.574747 \nL 422.585004 160.079286 \nL 423.065089 158.327016 \nL 423.54516 160.079286 \nL 423.785202 161.831556 \nL 424.025241 160.079286 \nL 424.26529 156.574747 \nL 424.745363 160.079286 \nL 425.460687 161.831556 \nL 425.940773 160.079286 \nL 426.420851 156.574747 \nL 426.660891 158.327016 \nL 427.140972 156.574747 \nL 427.381012 154.822477 \nL 428.101136 160.079286 \nL 428.336399 154.822477 \nL 428.576431 153.070207 \nL 428.816478 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445.835361 147.688235 \nL 446.075399 149.440505 \nL 446.550701 145.935965 \nL 447.990939 147.688235 \nL 448.471016 145.935965 \nL 449.186337 144.183695 \nL 449.666411 147.688235 \nL 450.146495 145.935965 \nL 450.866619 144.183695 \nL 451.3467 147.688235 \nL 451.821981 145.935965 \nL 452.062022 144.183695 \nL 452.302061 145.935965 \nL 453.022192 147.688235 \nL 453.262226 149.440505 \nL 453.742309 147.688235 \nL 454.217589 149.440505 \nL 454.697676 147.688235 \nL 455.417792 145.935965 \nL 455.89788 149.440505 \nL 456.377957 145.935965 \nL 457.333326 147.688235 \nL 457.573364 145.935965 \nL 457.813432 147.688235 \nL 458.533532 151.192775 \nL 459.493703 147.688235 \nL 459.968968 151.192775 \nL 460.44905 149.440505 \nL 461.169173 147.688235 \nL 461.649263 151.192775 \nL 461.889296 149.440505 \nL 462.609422 147.688235 \nL 462.844667 149.440505 \nL 464.044863 151.192775 \nL 464.524966 149.440505 \nL 464.764986 147.688235 \nL 465.005029 149.440505 \nL 465.245069 153.070207 \nL 465.720352 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\"last_changed\": \"2019-12-28T07:04:26.032869\", \"attributes\": {\"battery_level\": 53, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.garden_sensor_temperature\", \"state\": 6.17, \"last_changed\": \"2019-12-28T06:58:44.052737\", \"attributes\": {\"battery_level\": 100, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Garden sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Garden sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.office_sensor_temperature\", \"state\": 18.75, \"last_changed\": \"2019-12-28T06:54:32.033604\", \"attributes\": {\"battery_level\": 53, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.garden_sensor_temperature\", \"state\": 6.31, \"last_changed\": \"2019-12-28T06:53:44.033528\", \"attributes\": {\"battery_level\": 100, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Garden sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Garden sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.living_room_sensor_temperature\", \"state\": 16.45, \"last_changed\": \"2019-12-28T06:53:38.053183\", \"attributes\": {\"battery_level\": 62, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Living room sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Living room sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.hue_motion_sensor_1_temperature\", \"state\": 13.05, \"last_changed\": \"2019-12-28T06:51:14.032064\", \"attributes\": {\"battery_level\": 100, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Downstairs hallway temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Downstairs hallway temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.office_sensor_temperature\", \"state\": 18.89, \"last_changed\": \"2019-12-28T06:49:32.031637\", \"attributes\": {\"battery_level\": 53, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.netatmo_master_bedroom_temperature\", \"state\": 17.7, \"last_changed\": \"2019-12-28T06:48:57.530851\", \"attributes\": {\"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"netatmo Master Bedroom Temperature\", \"icon\": \"mdi:thermometer\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"netatmo Master Bedroom Temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.office_sensor_temperature\", \"state\": 18.47, \"last_changed\": \"2019-12-28T06:48:56.247883\", \"attributes\": {\"battery_level\": 53, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Office sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.hue_motion_sensor_1_temperature\", \"state\": 13.19, \"last_changed\": \"2019-12-28T06:48:56.245785\", \"attributes\": {\"battery_level\": 100, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Downstairs hallway temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Downstairs hallway temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.living_room_sensor_temperature\", \"state\": 16.59, \"last_changed\": \"2019-12-28T06:48:56.242987\", \"attributes\": {\"battery_level\": 62, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Living room sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Living room sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.garden_sensor_temperature\", \"state\": 6.17, \"last_changed\": \"2019-12-28T06:48:56.240924\", \"attributes\": {\"battery_level\": 100, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Garden sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Garden sensor temperature\", \"day_of_week\": 5}, {\"domain\": \"sensor\", \"entity_id\": \"sensor.hue_front_porch_sensor_temperature\", \"state\": 9.08, \"last_changed\": \"2019-12-28T06:48:56.238486\", \"attributes\": {\"battery_level\": 100, \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Hue front porch sensor temperature\", \"device_class\": \"temperature\"}, \"device_class\": \"temperature\", \"unit_of_measurement\": \"\\u00b0C\", \"friendly_name\": \"Hue front porch sensor temperature\", \"day_of_week\": 5}]}}, {\"mode\": \"vega-lite\"});\n</script>",
+      "text/plain": "alt.Chart(...)"
      },
-     "execution_count": 27,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -76515,7 +366,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
diff --git a/tests/test_functions.py b/tests/test_functions.py
index 101b8d0..09371dd 100644
--- a/tests/test_functions.py
+++ b/tests/test_functions.py
@@ -9,13 +9,6 @@
 }
 
 
-def test_format_binary_state():
-    """Test format_binary_state"""
-    assert functions.format_binary_state("on") == 1
-    assert functions.format_binary_state("off") == 0
-    assert functions.format_binary_state("foo") == "foo"
-
-
 def test_device_class():
     """Test get_device_class"""
     assert functions.get_device_class(MOCK_ATTRIBUTE) == MOCK_ATTRIBUTE["device_class"]