notebooks/explore_noise_starter_notebook.ipynb

{
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  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# tRacket - Noise Analysis Starter Notebook\n",
        "\n",
        "This notebook is meant to serve as a starting point to analyse noise data collected by the tRacket project and is set up to run on Google Colab. It shows you how to fetch data from the API and use some of our plotting functions to look at the data.\n",
        "\n",
        "Happy exploring!\n",
        "\n",
        "PS: If you wish to run the notebook locally, you will need to change the Setup code below to clone the Git repo and set up the required packages. We recommend creating a new Python environment for this or even better, using a Docker container. You can find more info on this approach [here](\n",
        "https://github.com/CivicTechTO/tRacket-dashboard/blob/main/DEV-README.md). Alternatively, you we show below the API endpoints where you can find the data and you can write your own functions to request and format dataframes.\n",
        "\n",
        "\n",
        "----\n",
        "\n",
        "\n",
        "## Setup\n",
        "\n",
        "We'll fetch the tRacket dashboard repo firts which comes with a number of useful utilities to interact with the tRacket API."
      ],
      "metadata": {
        "id": "Xe54rIj5F-ou"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y5QletvQDrb1",
        "outputId": "aa34f7b5-25d6-45e1-9ca5-dc8252ee876b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "fatal: destination path 'tRacket-dashboard' already exists and is not an empty directory.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/CivicTechTO/tRacket-dashboard.git"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -r /content/tRacket-dashboard/requirements.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-LIui9GFF29D",
        "outputId": "1960c4f2-893b-412a-f7b1-e0a3f76f5016"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/tRacket-dashboard/app/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p2GygyrbD7sk",
        "outputId": "7dfea10c-5b61-421e-a9ed-90e5a8b9ceb8"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/tRacket-dashboard/app\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Once the packages are set up, we are ready to request the data from the API.\n",
        "\n",
        "## Data Loading\n",
        "\n",
        "We'll start by importing some utilities."
      ],
      "metadata": {
        "id": "w3j8P27oHw35"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from src.data_loading.main import AppDataManager\n",
        "from src.data_loading.models import Granularity\n",
        "from src.utils import COLUMN"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "id": "MRPoiJqbEWYk",
        "outputId": "5c63d621-81df-4e3f-f70b-d052928afd85"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/pydantic/_internal/_model_construction.py:54: UserWarning: `serialize_dt` overrides an existing Pydantic `@field_serializer` decorator\n",
            "  warnings.warn(f'`{k}` overrides an existing Pydantic `{existing.decorator_info.decorator_repr}` decorator')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The following object will be our main tool to issue API calls:"
      ],
      "metadata": {
        "id": "fsLZem45H6iY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_manager = AppDataManager()"
      ],
      "metadata": {
        "id": "4JjUiWjSHH9J"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "The call below will fetch the location data in an attribute of the `data_manager` object:"
      ],
      "metadata": {
        "id": "KFEryfzaHu6X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_manager.load_and_format_locations()"
      ],
      "metadata": {
        "id": "ZaNzxxwzE50A"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "The locations are being pulled from this endpoint: `https://api.tracket.info/v1/locations/`"
      ],
      "metadata": {
        "id": "KSov8EBNXF4E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_manager.locations"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 885
        },
        "id": "ew5urYmeHZYM",
        "outputId": "36fd86e2-fce3-42a6-aa68-c99e83dbc382"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   COLUMN.DEVICEID                      COLUMN.LABEL  COLUMN.LAT  COLUMN.LON  \\\n",
              "0           572227        Scott St. & Wellington St.   43.648156  -79.376049   \n",
              "1           572234         Ossington Ave & Dupont St   43.669501  -79.428834   \n",
              "2           572250      Kingsley Ave & Symington Ave   43.668500  -79.452400   \n",
              "3           637773        Scott St. & Wellington St.   43.648000  -79.376000   \n",
              "4           664429      Bayview Ave & Sheppard Ave E   43.766600  -79.388000   \n",
              "5           747559                Ossington & Dupont   43.669626  -79.428974   \n",
              "6           747580            Ossington & Dupont (9)   43.673224  -79.436632   \n",
              "7           753346                    Cosburn & Pape   43.689612  -79.347870   \n",
              "8           753385  The Queensway and South Kingsway   43.635518  -79.473455   \n",
              "9           756264                Dupont and Spadina   43.674757  -79.407054   \n",
              "10          756271      Bathurst and Lake Shore Blvd   43.636797  -79.399819   \n",
              "11          782239        Main & Catherine, Hamilton   43.254599  -79.865790   \n",
              "12          802525                      Osgoode Hall   43.652201  -79.385909   \n",
              "13          859525                  Ossington/Dupont   43.669680  -79.428964   \n",
              "14          892046              Gardiner & Queensway   43.635702  -79.470720   \n",
              "15          896325                     St. Jamestown   43.670889  -79.373946   \n",
              "16         1086570                          Gabe's 3   43.669625  -79.429028   \n",
              "17         1086619                            Gabe 4   43.669541  -79.428841   \n",
              "18         1186749       Heath St - Cedarvale Ravine   43.686629  -79.414751   \n",
              "19         1251390             Wellington & Scott St   43.648282  -79.376501   \n",
              "\n",
              "    COLUMN.ACTIVE  COLUMN.RADIUS   COLUMN.LATEST_TIMESTAMP  \\\n",
              "0            True      75.452213 2024-07-06 13:03:00-05:00   \n",
              "1            True      84.156117 2024-08-08 14:04:30-05:00   \n",
              "2            True      50.000000 2024-03-27 16:54:30-05:00   \n",
              "3           False      50.000000 1892-01-03 00:11:00-05:00   \n",
              "4            True      50.000000 2024-08-17 09:39:32-05:00   \n",
              "5            True      67.131135 2025-02-14 05:38:43-05:00   \n",
              "6           False      15.000000 1892-01-03 00:11:00-05:00   \n",
              "7           False     220.000000 1892-01-03 00:11:00-05:00   \n",
              "8           False     200.000000 1892-01-03 00:11:00-05:00   \n",
              "9            True      50.000000 2025-02-13 10:00:04-05:00   \n",
              "10           True     150.000000 2024-10-26 12:43:06-05:00   \n",
              "11           True      75.000000 2024-11-30 20:36:01-05:00   \n",
              "12          False      80.014704 1892-01-03 00:11:00-05:00   \n",
              "13          False      57.110808 1892-01-03 00:11:00-05:00   \n",
              "14           True     155.503787 2025-02-16 09:05:23-05:00   \n",
              "15           True      10.000000 2025-02-16 09:08:45-05:00   \n",
              "16           True      90.404774 2025-01-31 07:10:36-05:00   \n",
              "17           True      64.611519 2025-02-16 09:05:47-05:00   \n",
              "18           True      10.000000 2025-02-16 09:07:35-05:00   \n",
              "19           True      34.932645 2025-02-16 09:08:11-05:00   \n",
              "\n",
              "    COLUMN.SENDING_DATA  \n",
              "0                 False  \n",
              "1                 False  \n",
              "2                 False  \n",
              "3                 False  \n",
              "4                 False  \n",
              "5                 False  \n",
              "6                 False  \n",
              "7                 False  \n",
              "8                 False  \n",
              "9                 False  \n",
              "10                False  \n",
              "11                False  \n",
              "12                False  \n",
              "13                False  \n",
              "14                 True  \n",
              "15                 True  \n",
              "16                False  \n",
              "17                 True  \n",
              "18                 True  \n",
              "19                 True  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-14d00957-6448-4d28-a26a-584480095434\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>COLUMN.DEVICEID</th>\n",
              "      <th>COLUMN.LABEL</th>\n",
              "      <th>COLUMN.LAT</th>\n",
              "      <th>COLUMN.LON</th>\n",
              "      <th>COLUMN.ACTIVE</th>\n",
              "      <th>COLUMN.RADIUS</th>\n",
              "      <th>COLUMN.LATEST_TIMESTAMP</th>\n",
              "      <th>COLUMN.SENDING_DATA</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>572227</td>\n",
              "      <td>Scott St. &amp; Wellington St.</td>\n",
              "      <td>43.648156</td>\n",
              "      <td>-79.376049</td>\n",
              "      <td>True</td>\n",
              "      <td>75.452213</td>\n",
              "      <td>2024-07-06 13:03:00-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>572234</td>\n",
              "      <td>Ossington Ave &amp; Dupont St</td>\n",
              "      <td>43.669501</td>\n",
              "      <td>-79.428834</td>\n",
              "      <td>True</td>\n",
              "      <td>84.156117</td>\n",
              "      <td>2024-08-08 14:04:30-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>572250</td>\n",
              "      <td>Kingsley Ave &amp; Symington Ave</td>\n",
              "      <td>43.668500</td>\n",
              "      <td>-79.452400</td>\n",
              "      <td>True</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>2024-03-27 16:54:30-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>637773</td>\n",
              "      <td>Scott St. &amp; Wellington St.</td>\n",
              "      <td>43.648000</td>\n",
              "      <td>-79.376000</td>\n",
              "      <td>False</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>1892-01-03 00:11:00-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>664429</td>\n",
              "      <td>Bayview Ave &amp; Sheppard Ave E</td>\n",
              "      <td>43.766600</td>\n",
              "      <td>-79.388000</td>\n",
              "      <td>True</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>2024-08-17 09:39:32-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>747559</td>\n",
              "      <td>Ossington &amp; Dupont</td>\n",
              "      <td>43.669626</td>\n",
              "      <td>-79.428974</td>\n",
              "      <td>True</td>\n",
              "      <td>67.131135</td>\n",
              "      <td>2025-02-14 05:38:43-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>747580</td>\n",
              "      <td>Ossington &amp; Dupont (9)</td>\n",
              "      <td>43.673224</td>\n",
              "      <td>-79.436632</td>\n",
              "      <td>False</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>1892-01-03 00:11:00-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>753346</td>\n",
              "      <td>Cosburn &amp; Pape</td>\n",
              "      <td>43.689612</td>\n",
              "      <td>-79.347870</td>\n",
              "      <td>False</td>\n",
              "      <td>220.000000</td>\n",
              "      <td>1892-01-03 00:11:00-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>753385</td>\n",
              "      <td>The Queensway and South Kingsway</td>\n",
              "      <td>43.635518</td>\n",
              "      <td>-79.473455</td>\n",
              "      <td>False</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>1892-01-03 00:11:00-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>756264</td>\n",
              "      <td>Dupont and Spadina</td>\n",
              "      <td>43.674757</td>\n",
              "      <td>-79.407054</td>\n",
              "      <td>True</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>2025-02-13 10:00:04-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>756271</td>\n",
              "      <td>Bathurst and Lake Shore Blvd</td>\n",
              "      <td>43.636797</td>\n",
              "      <td>-79.399819</td>\n",
              "      <td>True</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>2024-10-26 12:43:06-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>782239</td>\n",
              "      <td>Main &amp; Catherine, Hamilton</td>\n",
              "      <td>43.254599</td>\n",
              "      <td>-79.865790</td>\n",
              "      <td>True</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>2024-11-30 20:36:01-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>802525</td>\n",
              "      <td>Osgoode Hall</td>\n",
              "      <td>43.652201</td>\n",
              "      <td>-79.385909</td>\n",
              "      <td>False</td>\n",
              "      <td>80.014704</td>\n",
              "      <td>1892-01-03 00:11:00-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>859525</td>\n",
              "      <td>Ossington/Dupont</td>\n",
              "      <td>43.669680</td>\n",
              "      <td>-79.428964</td>\n",
              "      <td>False</td>\n",
              "      <td>57.110808</td>\n",
              "      <td>1892-01-03 00:11:00-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>892046</td>\n",
              "      <td>Gardiner &amp; Queensway</td>\n",
              "      <td>43.635702</td>\n",
              "      <td>-79.470720</td>\n",
              "      <td>True</td>\n",
              "      <td>155.503787</td>\n",
              "      <td>2025-02-16 09:05:23-05:00</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>896325</td>\n",
              "      <td>St. Jamestown</td>\n",
              "      <td>43.670889</td>\n",
              "      <td>-79.373946</td>\n",
              "      <td>True</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>2025-02-16 09:08:45-05:00</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1086570</td>\n",
              "      <td>Gabe's 3</td>\n",
              "      <td>43.669625</td>\n",
              "      <td>-79.429028</td>\n",
              "      <td>True</td>\n",
              "      <td>90.404774</td>\n",
              "      <td>2025-01-31 07:10:36-05:00</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1086619</td>\n",
              "      <td>Gabe 4</td>\n",
              "      <td>43.669541</td>\n",
              "      <td>-79.428841</td>\n",
              "      <td>True</td>\n",
              "      <td>64.611519</td>\n",
              "      <td>2025-02-16 09:05:47-05:00</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1186749</td>\n",
              "      <td>Heath St - Cedarvale Ravine</td>\n",
              "      <td>43.686629</td>\n",
              "      <td>-79.414751</td>\n",
              "      <td>True</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>2025-02-16 09:07:35-05:00</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1251390</td>\n",
              "      <td>Wellington &amp; Scott St</td>\n",
              "      <td>43.648282</td>\n",
              "      <td>-79.376501</td>\n",
              "      <td>True</td>\n",
              "      <td>34.932645</td>\n",
              "      <td>2025-02-16 09:08:11-05:00</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"data_manager\",\n  \"rows\": 20,\n  \"fields\": [\n    {\n      \"column\": \"COLUMN.DEVICEID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"572227\",\n          \"1086619\",\n          \"896325\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.LABEL\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 19,\n        \"samples\": [\n          \"Scott St. & Wellington St.\",\n          \"Ossington & Dupont (9)\",\n          \"Osgoode Hall\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.LAT\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.096547530536631,\n        \"min\": 43.254598692992,\n        \"max\": 43.7666,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          43.64815606522,\n          43.669540887593,\n          43.670889253866\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.LON\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.1070081886119534,\n        \"min\": -79.86579008805,\n        \"max\": -79.34787,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          -79.376049461048,\n          -79.428840508528,\n          -79.37394618988\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.ACTIVE\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false,\n          true\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.RADIUS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 58.64645460526802,\n        \"min\": 10.0,\n        \"max\": 220.0,\n        \"num_unique_values\": 16,\n        \"samples\": [\n          75.452213039348,\n          84.156116888255\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.LATEST_TIMESTAMP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1892-01-03 00:11:00-05:00\",\n        \"max\": \"2025-02-16 09:08:45-05:00\",\n        \"num_unique_values\": 15,\n        \"samples\": [\n          \"2025-02-16 09:05:23-05:00\",\n          \"2025-01-31 07:10:36-05:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.SENDING_DATA\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Given the `DEVICEID`, we can issue a query for the location stats that will tell us the first and last recording date:"
      ],
      "metadata": {
        "id": "M1xc63x8IjMe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "device_id = '896325'"
      ],
      "metadata": {
        "id": "MYlln6PbMj8h"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_manager.load_and_format_location_stats(device_id)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 155
        },
        "id": "SKZmrvPHIUq2",
        "outputId": "d5a940d6-3fb0-436f-afda-7ab19c7d0f0a"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0   2024-08-11 13:25:56\n",
            "Name: COLUMN.START, dtype: datetime64[ns]\n",
            "0   2025-02-16 10:13:45\n",
            "Name: COLUMN.END, dtype: datetime64[ns]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   COLUMN.MIN  COLUMN.MAX  COLUMN.MEAN  COLUMN.COUNT  \\\n",
              "0        52.0       104.0       60.945         47716   \n",
              "\n",
              "               COLUMN.START                COLUMN.END  \n",
              "0 2024-08-11 13:25:56-05:00 2025-02-16 10:13:45-05:00  "
            ],
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              "\n",
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              "        const element = document.querySelector('#df-738c70c1-0644-4bbb-998c-5448bf5b7d2a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"data_manager\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"COLUMN.MIN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 52.0,\n        \"max\": 52.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          52.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MAX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 104.0,\n        \"max\": 104.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          104.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MEAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 60.945,\n        \"max\": 60.945,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          60.945\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.COUNT\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 47716,\n        \"max\": 47716,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          47716\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.START\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-08-11 13:25:56-05:00\",\n        \"max\": \"2024-08-11 13:25:56-05:00\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"2024-08-11 13:25:56-05:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.END\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2025-02-16 10:13:45-05:00\",\n        \"max\": \"2025-02-16 10:13:45-05:00\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"2025-02-16 10:13:45-05:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Finally, we can query data for a given period which can be fetched at different granularity levels between two given dates:\n",
        "- `raw` will fetch the 5-minute, raw data,\n",
        "- `hourly` will aggregate to 1-hour intervals,\n",
        "- `life_time` will aggregate statistics to the specified period.\n",
        "\n",
        "If the `start` and `end` params for the timeframe are left empty, then the last 7 days of recorded data is fetched (whenever that falls for the sensor) - if specified, they need to be `datetime` objects.\n",
        "\n",
        "The results are stored as an attribut of the `data_manager` object, as shown below."
      ],
      "metadata": {
        "id": "H8UP3tgTJKMy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# options for Granularity\n",
        "list(Granularity)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gd-yvLYJJwaa",
        "outputId": "1ac18e24-f5ca-436b-b6b1-37a12c3b55b7"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<Granularity.raw: 'raw'>,\n",
              " <Granularity.hourly: 'hourly'>,\n",
              " <Granularity.life_time: 'life-time'>]"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_manager.load_and_format_location_noise(\n",
        "    device_id,\n",
        "    granularity=Granularity.raw,\n",
        ")"
      ],
      "metadata": {
        "id": "a64yuWM9Iamu"
      },
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "We can also specify dates manually and if `start` is not added, the function will fetch 7-days back from the `end` date.\n",
        "\n"
      ],
      "metadata": {
        "id": "JfmJx6knMeST"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import datetime, timedelta\n",
        "\n",
        "data_manager.load_and_format_location_noise(\n",
        "    device_id,\n",
        "    granularity=Granularity.raw,\n",
        "    end=datetime(2025, 2, 15),\n",
        ")\n",
        "\n",
        "# data_manager.load_and_format_location_noise(\n",
        "#     device_id,\n",
        "#     granularity=Granularity.raw,\n",
        "#     start=datetime(2025, 2, 8),\n",
        "#     end=datetime(2025, 2, 15),\n",
        "# )"
      ],
      "metadata": {
        "id": "XfSpjPEXMeCK"
      },
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "noise_data_raw = data_manager.location_noise[Granularity.raw].copy()\n",
        "noise_data_raw.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "W-Gg0yp3J6Sm",
        "outputId": "2551a551-04d5-42f2-e0c7-45df4c7e65cd"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   COLUMN.MIN  COLUMN.MAX  COLUMN.MEAN          COLUMN.TIMESTAMP\n",
              "0        58.0        67.0         60.0 2025-02-07 19:00:55-05:00\n",
              "1        58.0        61.0         59.0 2025-02-07 19:05:55-05:00\n",
              "2        58.0        61.0         59.0 2025-02-07 19:10:55-05:00\n",
              "3        58.0        65.0         59.0 2025-02-07 19:15:55-05:00\n",
              "4        58.0        63.0         59.0 2025-02-07 19:20:55-05:00\n",
              "5        58.0        62.0         59.0 2025-02-07 19:25:55-05:00\n",
              "6        58.0        62.0         60.0 2025-02-07 19:30:55-05:00\n",
              "7        58.0        69.0         59.0 2025-02-07 19:35:55-05:00\n",
              "8        58.0        61.0         59.0 2025-02-07 19:40:55-05:00\n",
              "9        58.0        65.0         59.0 2025-02-07 19:45:55-05:00"
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              "      <td>59.0</td>\n",
              "      <td>2025-02-07 19:20:55-05:00</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>58.0</td>\n",
              "      <td>62.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>2025-02-07 19:25:55-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>58.0</td>\n",
              "      <td>62.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>2025-02-07 19:30:55-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>58.0</td>\n",
              "      <td>69.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>2025-02-07 19:35:55-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>58.0</td>\n",
              "      <td>61.0</td>\n",
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              "      <td>2025-02-07 19:40:55-05:00</td>\n",
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              "      <td>65.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>2025-02-07 19:45:55-05:00</td>\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "\n",
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              "        document.querySelector('#df-0550d290-3fd9-4183-8235-041a67beee8f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-0550d290-3fd9-4183-8235-041a67beee8f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-71521c96-a2c1-4b2d-b4cb-c2e0aee0f983 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "noise_data_raw",
              "summary": "{\n  \"name\": \"noise_data_raw\",\n  \"rows\": 2073,\n  \"fields\": [\n    {\n      \"column\": \"COLUMN.MIN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4.2110432560304165,\n        \"min\": 53.0,\n        \"max\": 72.0,\n        \"num_unique_values\": 19,\n        \"samples\": [\n          58.0,\n          55.0,\n          62.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MAX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 6.716657259201214,\n        \"min\": 55.0,\n        \"max\": 92.0,\n        \"num_unique_values\": 38,\n        \"samples\": [\n          90.0,\n          91.0,\n          62.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MEAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4.5608138311963335,\n        \"min\": 54.0,\n        \"max\": 81.0,\n        \"num_unique_values\": 22,\n        \"samples\": [\n          60.0,\n          72.0,\n          56.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.TIMESTAMP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2025-02-07 19:00:55-05:00\",\n        \"max\": \"2025-02-14 22:58:45-05:00\",\n        \"num_unique_values\": 2064,\n        \"samples\": [\n          \"2025-02-13 13:58:45-05:00\",\n          \"2025-02-09 11:00:55-05:00\",\n          \"2025-02-10 22:25:55-05:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "For reference, we add a sample API endpoint with parameters for this call:\n",
        "\n",
        "`https://api.tracket.info/v1/locations/896325/noise?granularity=raw&start=2024-11-03%2000%3A00%3A00&end=2024-11-11T00%3A00%3A00-04%3A00`\n",
        "\n",
        "Let's grab some hourly data as well for a longer period."
      ],
      "metadata": {
        "id": "KSZ46kauO3vv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_manager.load_and_format_location_noise(\n",
        "    device_id,\n",
        "    granularity=Granularity.hourly,\n",
        "    start=datetime(2024, 12, 15),\n",
        "    end=datetime(2025, 2, 15),\n",
        ")"
      ],
      "metadata": {
        "id": "nFssQs2_O3cw"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "noise_data_hourly = data_manager.location_noise[Granularity.hourly].copy()\n",
        "noise_data_hourly.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "VTI_M0kdO9ax",
        "outputId": "7993c268-5367-4510-a8b7-79a8f7a5a838"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   COLUMN.MIN  COLUMN.MAX  COLUMN.MEAN          COLUMN.TIMESTAMP\n",
              "0        58.0        83.0       60.333 2024-12-14 19:00:00-05:00\n",
              "1        58.0        84.0       60.083 2024-12-14 20:00:00-05:00\n",
              "2        58.0        83.0       59.917 2024-12-14 21:00:00-05:00\n",
              "3        58.0        80.0       60.000 2024-12-14 22:00:00-05:00\n",
              "4        58.0        81.0       60.000 2024-12-14 23:00:00-05:00\n",
              "5        58.0        83.0       60.500 2024-12-15 00:00:00-05:00\n",
              "6        58.0        85.0       59.667 2024-12-15 01:00:00-05:00\n",
              "7        58.0        83.0       59.500 2024-12-15 02:00:00-05:00\n",
              "8        58.0        66.0       59.250 2024-12-15 03:00:00-05:00\n",
              "9        58.0        64.0       58.833 2024-12-15 04:00:00-05:00"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-32cb10ba-ce90-4925-a103-39443f06536b\" class=\"colab-df-container\">\n",
              "    <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>COLUMN.MIN</th>\n",
              "      <th>COLUMN.MAX</th>\n",
              "      <th>COLUMN.MEAN</th>\n",
              "      <th>COLUMN.TIMESTAMP</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>60.333</td>\n",
              "      <td>2024-12-14 19:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>58.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>60.083</td>\n",
              "      <td>2024-12-14 20:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>59.917</td>\n",
              "      <td>2024-12-14 21:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>58.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>60.000</td>\n",
              "      <td>2024-12-14 22:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>58.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>60.000</td>\n",
              "      <td>2024-12-14 23:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>60.500</td>\n",
              "      <td>2024-12-15 00:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>58.0</td>\n",
              "      <td>85.0</td>\n",
              "      <td>59.667</td>\n",
              "      <td>2024-12-15 01:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>59.500</td>\n",
              "      <td>2024-12-15 02:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>58.0</td>\n",
              "      <td>66.0</td>\n",
              "      <td>59.250</td>\n",
              "      <td>2024-12-15 03:00:00-05:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>58.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>58.833</td>\n",
              "      <td>2024-12-15 04:00:00-05:00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-32cb10ba-ce90-4925-a103-39443f06536b')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-32cb10ba-ce90-4925-a103-39443f06536b button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-32cb10ba-ce90-4925-a103-39443f06536b');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
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              "\n",
              "\n",
              "<div id=\"df-36163c9a-4cb4-4a7f-b892-504b027c2e08\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-36163c9a-4cb4-4a7f-b892-504b027c2e08')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-36163c9a-4cb4-4a7f-b892-504b027c2e08 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "noise_data_hourly",
              "summary": "{\n  \"name\": \"noise_data_hourly\",\n  \"rows\": 1128,\n  \"fields\": [\n    {\n      \"column\": \"COLUMN.MIN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.9734618137020734,\n        \"min\": 52.0,\n        \"max\": 67.0,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          54.0,\n          52.0,\n          58.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MAX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7.739247287281495,\n        \"min\": 59.0,\n        \"max\": 104.0,\n        \"num_unique_values\": 39,\n        \"samples\": [\n          59.0,\n          95.0,\n          85.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MEAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.6920294218670553,\n        \"min\": 54.5,\n        \"max\": 70.083,\n        \"num_unique_values\": 216,\n        \"samples\": [\n          69.5,\n          65.917,\n          64.583\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.TIMESTAMP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-12-14 19:00:00-05:00\",\n        \"max\": \"2025-02-14 22:00:00-05:00\",\n        \"num_unique_values\": 1128,\n        \"samples\": [\n          \"2025-02-13 10:00:00-05:00\",\n          \"2025-02-05 09:00:00-05:00\",\n          \"2025-01-29 18:00:00-05:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now, we are all set up to start exploring the data."
      ],
      "metadata": {
        "id": "kBdedlmIXbqD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Data Visualization\n",
        "\n",
        "The `src.plotting` module has a number of useful functions to visualize the data in different ways."
      ],
      "metadata": {
        "id": "Wf79WkRfL5ZS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from src.plotting import TimeseriesPlotter, HeatmapPlotter\n",
        "from src.utils import HEATMAP_VALUE"
      ],
      "metadata": {
        "id": "gfhLjS9UKz21"
      },
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plotter = TimeseriesPlotter(noise_data_raw)"
      ],
      "metadata": {
        "id": "Y4gQL9u2MLHL"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plotter.plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "MCXpE2P8MN7F",
        "outputId": "44ec3b92-266b-4a54-c779-91fd1450571a"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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    {
      "cell_type": "markdown",
      "source": [
        "We need to add a few columns to the hourly data so the heatmap utility function will work properly:"
      ],
      "metadata": {
        "id": "xrk6lHcAU0bB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "noise_data_hourly[COLUMN.HOUR] = noise_data_hourly[COLUMN.TIMESTAMP].dt.hour\n",
        "noise_data_hourly[COLUMN.DATE] = pd.to_datetime(noise_data_hourly[COLUMN.TIMESTAMP].dt.date)\n",
        "noise_data_hourly[COLUMN.MINNOISE] = noise_data_hourly[COLUMN.MIN]\n",
        "noise_data_hourly[COLUMN.MAXNOISE] = noise_data_hourly[COLUMN.MAX]\n",
        "noise_data_hourly.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "m548VyoKPeuh",
        "outputId": "a5524e6c-02ca-429f-ec36-692f37726990"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   COLUMN.MIN  COLUMN.MAX  COLUMN.MEAN          COLUMN.TIMESTAMP  COLUMN.HOUR  \\\n",
              "0        58.0        83.0       60.333 2024-12-14 19:00:00-05:00           19   \n",
              "1        58.0        84.0       60.083 2024-12-14 20:00:00-05:00           20   \n",
              "2        58.0        83.0       59.917 2024-12-14 21:00:00-05:00           21   \n",
              "3        58.0        80.0       60.000 2024-12-14 22:00:00-05:00           22   \n",
              "4        58.0        81.0       60.000 2024-12-14 23:00:00-05:00           23   \n",
              "\n",
              "  COLUMN.DATE  COLUMN.MINNOISE  COLUMN.MAXNOISE  \n",
              "0  2024-12-14             58.0             83.0  \n",
              "1  2024-12-14             58.0             84.0  \n",
              "2  2024-12-14             58.0             83.0  \n",
              "3  2024-12-14             58.0             80.0  \n",
              "4  2024-12-14             58.0             81.0  "
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>COLUMN.MIN</th>\n",
              "      <th>COLUMN.MAX</th>\n",
              "      <th>COLUMN.MEAN</th>\n",
              "      <th>COLUMN.TIMESTAMP</th>\n",
              "      <th>COLUMN.HOUR</th>\n",
              "      <th>COLUMN.DATE</th>\n",
              "      <th>COLUMN.MINNOISE</th>\n",
              "      <th>COLUMN.MAXNOISE</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>60.333</td>\n",
              "      <td>2024-12-14 19:00:00-05:00</td>\n",
              "      <td>19</td>\n",
              "      <td>2024-12-14</td>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>58.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>60.083</td>\n",
              "      <td>2024-12-14 20:00:00-05:00</td>\n",
              "      <td>20</td>\n",
              "      <td>2024-12-14</td>\n",
              "      <td>58.0</td>\n",
              "      <td>84.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>59.917</td>\n",
              "      <td>2024-12-14 21:00:00-05:00</td>\n",
              "      <td>21</td>\n",
              "      <td>2024-12-14</td>\n",
              "      <td>58.0</td>\n",
              "      <td>83.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>58.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>60.000</td>\n",
              "      <td>2024-12-14 22:00:00-05:00</td>\n",
              "      <td>22</td>\n",
              "      <td>2024-12-14</td>\n",
              "      <td>58.0</td>\n",
              "      <td>80.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>58.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>60.000</td>\n",
              "      <td>2024-12-14 23:00:00-05:00</td>\n",
              "      <td>23</td>\n",
              "      <td>2024-12-14</td>\n",
              "      <td>58.0</td>\n",
              "      <td>81.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-307582eb-007b-4601-88d6-1bb166dab0b0')\"\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      cursor: pointer;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-307582eb-007b-4601-88d6-1bb166dab0b0');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
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              "    </g>\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b45bdf60-fdcf-45c3-b0f8-984f5900aa3c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "noise_data_hourly",
              "summary": "{\n  \"name\": \"noise_data_hourly\",\n  \"rows\": 1128,\n  \"fields\": [\n    {\n      \"column\": \"COLUMN.MIN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.9734618137020734,\n        \"min\": 52.0,\n        \"max\": 67.0,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          54.0,\n          52.0,\n          58.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MAX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7.739247287281495,\n        \"min\": 59.0,\n        \"max\": 104.0,\n        \"num_unique_values\": 39,\n        \"samples\": [\n          59.0,\n          95.0,\n          85.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MEAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.6920294218670553,\n        \"min\": 54.5,\n        \"max\": 70.083,\n        \"num_unique_values\": 216,\n        \"samples\": [\n          69.5,\n          65.917,\n          64.583\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.TIMESTAMP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-12-14 19:00:00-05:00\",\n        \"max\": \"2025-02-14 22:00:00-05:00\",\n        \"num_unique_values\": 1128,\n        \"samples\": [\n          \"2025-02-13 10:00:00-05:00\",\n          \"2025-02-05 09:00:00-05:00\",\n          \"2025-01-29 18:00:00-05:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.HOUR\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 24,\n        \"samples\": [\n          3,\n          11,\n          19\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.DATE\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-12-14 00:00:00\",\n        \"max\": \"2025-02-14 00:00:00\",\n        \"num_unique_values\": 49,\n        \"samples\": [\n          \"2024-12-27 00:00:00\",\n          \"2025-02-11 00:00:00\",\n          \"2025-02-13 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MINNOISE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.9734618137020734,\n        \"min\": 52.0,\n        \"max\": 67.0,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          54.0,\n          52.0,\n          58.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"COLUMN.MAXNOISE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7.739247287281495,\n        \"min\": 59.0,\n        \"max\": 104.0,\n        \"num_unique_values\": 39,\n        \"samples\": [\n          59.0,\n          95.0,\n          85.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "heatmap_plotter = HeatmapPlotter(noise_data_hourly)"
      ],
      "metadata": {
        "id": "Sh3ehpNUMPUj"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "You can call this function for `HEATMAP_VALUE.MIN` and `HEATMAP_VALUE.MAX`:"
      ],
      "metadata": {
        "id": "4-gtSUt_VDm4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "heatmap_plotter.plot(pivot_value=HEATMAP_VALUE.MAX)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "JPa33OmLOsiE",
        "outputId": "d30ed9cf-233b-423b-d6b4-bb5b06ed78fa"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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        "heatmap_plotter.plot(pivot_value=HEATMAP_VALUE.MIN)"
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