Week11.ipynb

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        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/AlainWalbar/database/blob/main/Week11.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "SQLite Pandas Examples"
      ],
      "metadata": {
        "id": "MA0zsab5rTea"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "S1IHap0rosJ1"
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      "outputs": [],
      "source": [
        "import sqlite3 as sl \n",
        "con = sl.connect('my-test.db')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with con:\n",
        "  con.execute(\"\"\"\n",
        "    CREATE TABLE USER (\n",
        "      id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,\n",
        "      name TEXT,\n",
        "      age INTEGER\n",
        "    );\n",
        "  \"\"\")"
      ],
      "metadata": {
        "id": "wV8pcyMAqtTc"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sql = 'INSERT INTO USER (id, name, age) values (?, ?, ?)'\n",
        "data = [\n",
        "    (1, 'Alice', 21),\n",
        "    (2, 'Bob', 22),\n",
        "    (3, 'Chris', 23)\n",
        "]"
      ],
      "metadata": {
        "id": "3Cb_i2F1q4ZT"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with con:\n",
        "  con.executemany(sql, data)"
      ],
      "metadata": {
        "id": "RlLFbQLtrEew"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with con: \n",
        "  data= con.execute(\"SELECT *  FROM USER WHERE age <= 22\")\n",
        "  for row in data:\n",
        "    print(row)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "F2ScTZNNrIKH",
        "outputId": "faa95689-4c15-4597-9598-e50472b48336"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(1, 'Alice', 21)\n",
            "(2, 'Bob', 22)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Integrate SQLite with Pandas"
      ],
      "metadata": {
        "id": "38gYK1P3rRAa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "df_skill = pd.DataFrame({\n",
        "    'user_id': [1,1,2,2,3,3,3],\n",
        "    'skill': ['Network Security', 'Algorithm Development', 'Network Security', 'Java', 'Python', 'Data Science', 'Machine Learning']\n",
        "})\n",
        "df_skill"
      ],
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      "execution_count": 6,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "   user_id                  skill\n",
              "0        1       Network Security\n",
              "1        1  Algorithm Development\n",
              "2        2       Network Security\n",
              "3        2                   Java\n",
              "4        3                 Python\n",
              "5        3           Data Science\n",
              "6        3       Machine Learning"
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              "      <th>6</th>\n",
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      "cell_type": "code",
      "source": [
        "df_skill.to_sql('SKILL', con)\n",
        "df = pd.read_sql('''\n",
        "  SELECT s.user_id, u.name, u.age, s.skill\n",
        "  FROM USER u LEFT JOIN SKILL s ON u.id = s.user_id\n",
        "  ''', con)\n",
        "\n",
        "df "
      ],
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      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   user_id   name  age                  skill\n",
              "0        1  Alice   21  Algorithm Development\n",
              "1        1  Alice   21       Network Security\n",
              "2        2    Bob   22                   Java\n",
              "3        2    Bob   22       Network Security\n",
              "4        3  Chris   23           Data Science\n",
              "5        3  Chris   23       Machine Learning\n",
              "6        3  Chris   23                 Python"
            ],
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              "      <th>6</th>\n",
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              "      <td>Python</td>\n",
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              "                                                     [key], {});\n",
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              "\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",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "df.to_sql('USER_SKILL', con)"
      ],
      "metadata": {
        "id": "bb1rNFFCr6L6"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Uing SQLite as a Time Series Database"
      ],
      "metadata": {
        "id": "JdiJZPyEsRWr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql\n",
        "from random import uniform, choice\n",
        "import time\n",
        "from datetime import datetime, timedelta\n",
        "import pandas as pd\n",
        "%matplotlib inline"
      ],
      "metadata": {
        "id": "ZYFaleVtsTxO"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%sql sqlite:///demo.db3"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "0-0Tuzy6smvv",
        "outputId": "0deb5847-c47c-4f3a-8170-b8c2a04dfa5f"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Connected: @demo.db3'"
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              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql SELECT date('now');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 96
        },
        "id": "YOzCGQvysquj",
        "outputId": "bf04334a-cbe2-42eb-eef3-1536d3060cd4"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " * sqlite:///demo.db3\n",
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('2022-11-09',)]"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>date(&#x27;now&#x27;)</th>\n",
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              "    </thead>\n",
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              "            <td>2022-11-09</td>\n",
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              "</table>"
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql SELECT date('now', 'start of month', '+1 month', '-1 day');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 96
        },
        "id": "wN3m-c1dsuW7",
        "outputId": "dcdf43a5-7c10-4862-ce6f-aea5bac508c4"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " * sqlite:///demo.db3\n",
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('2022-11-30',)]"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>date(&#x27;now&#x27;, &#x27;start of month&#x27;, &#x27;+1 month&#x27;, &#x27;-1 day&#x27;)</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>2022-11-30</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql sqlite://\n",
        "DROP TABLE IF EXISTS Temperature;\n",
        "CREATE TABLE Temperature(Timestamp DATETIME NOT NULL, Temperature NUMERIC NOT NULL)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uHtetLKis1BT",
        "outputId": "3b4d923c-e740-46c4-cf44-4de9fa13be0a"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Done.\n",
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql sqlite://\n",
        "CREATE UNIQUE INDEX idx_timestamp ON Temperature (Timestamp);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7UC6grPFs-al",
        "outputId": "020dcc54-7616-45ba-d35a-684535d4977f"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def dt(days):\n",
        "  return timedelta(days=days)\n",
        "\n",
        "N_rows= 500\n",
        "now = datetime.now()\n",
        "\n",
        "for i in range (N_rows):\n",
        "  timestamp = now - dt(days=(N_rows - i))\n",
        "  temperature = uniform(18, 26)\n",
        "  %sql INSERT INTO Temperature VALUES (:timestamp, :temperature);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s2kcL2GKtDZw",
        "outputId": "7448b4f8-e97f-45be-f62f-8dc47d90dadc"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
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            "1 rows affected.\n",
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            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n",
            " * sqlite:///demo.db3\n",
            "1 rows affected.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql SELECT datetime(Timestamp) as Date, Temperature FROM Temperature LIMIT 5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 182
        },
        "id": "WXTCb9-_tYNv",
        "outputId": "ca69e3f5-204e-4749-b31b-0ff3accd9afc"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " * sqlite:///demo.db3\n",
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('2021-06-27 09:25:24', 25.456466516929375),\n",
              " ('2021-06-28 09:25:24', 25.08194822020671),\n",
              " ('2021-06-29 09:25:24', 18.02003565857419),\n",
              " ('2021-06-30 09:25:24', 19.810526922230757),\n",
              " ('2021-07-01 09:25:24', 21.112912350807566)]"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>Date</th>\n",
              "            <th>Temperature</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>2021-06-27 09:25:24</td>\n",
              "            <td>25.456466516929375</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-06-28 09:25:24</td>\n",
              "            <td>25.08194822020671</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-06-29 09:25:24</td>\n",
              "            <td>18.02003565857419</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-06-30 09:25:24</td>\n",
              "            <td>19.810526922230757</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-01 09:25:24</td>\n",
              "            <td>21.112912350807566</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql sqlite://\n",
        "SELECT Timestamp as Date, Temperature\n",
        "FROM Temperature\n",
        "WHERE Date <= '2022-06-31 14:21:45'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "7PYPehk0tdKm",
        "outputId": "d07a9839-449d-424d-e56b-b6b8de0d0238"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('2021-06-27 09:25:24.174008', 25.456466516929375),\n",
              " ('2021-06-28 09:25:24.174008', 25.08194822020671),\n",
              " ('2021-06-29 09:25:24.174008', 18.02003565857419),\n",
              " ('2021-06-30 09:25:24.174008', 19.810526922230757),\n",
              " ('2021-07-01 09:25:24.174008', 21.112912350807566),\n",
              " ('2021-07-02 09:25:24.174008', 20.800907718472633),\n",
              " ('2021-07-03 09:25:24.174008', 18.448013962702134),\n",
              " ('2021-07-04 09:25:24.174008', 24.470218722119778),\n",
              " ('2021-07-05 09:25:24.174008', 25.157674007746834),\n",
              " ('2021-07-06 09:25:24.174008', 24.486404917103272),\n",
              " ('2021-07-07 09:25:24.174008', 25.81832649655456),\n",
              " ('2021-07-08 09:25:24.174008', 25.134481638418592),\n",
              " ('2021-07-09 09:25:24.174008', 24.89875805492679),\n",
              " ('2021-07-10 09:25:24.174008', 18.071192712105344),\n",
              " ('2021-07-11 09:25:24.174008', 23.985347573743493),\n",
              " ('2021-07-12 09:25:24.174008', 23.87384945212648),\n",
              " ('2021-07-13 09:25:24.174008', 22.89201275841107),\n",
              " ('2021-07-14 09:25:24.174008', 18.190306449810972),\n",
              " ('2021-07-15 09:25:24.174008', 20.21664159112378),\n",
              " ('2021-07-16 09:25:24.174008', 20.597733727300046),\n",
              " ('2021-07-17 09:25:24.174008', 19.570371000012848),\n",
              " ('2021-07-18 09:25:24.174008', 21.29992823004546),\n",
              " ('2021-07-19 09:25:24.174008', 23.961524741312015),\n",
              " ('2021-07-20 09:25:24.174008', 25.616870127319615),\n",
              " ('2021-07-21 09:25:24.174008', 20.89200041527153),\n",
              " ('2021-07-22 09:25:24.174008', 19.497103727149494),\n",
              " ('2021-07-23 09:25:24.174008', 20.092936112902905),\n",
              " ('2021-07-24 09:25:24.174008', 19.600499856532046),\n",
              " ('2021-07-25 09:25:24.174008', 21.4311676857373),\n",
              " ('2021-07-26 09:25:24.174008', 22.662100224622467),\n",
              " ('2021-07-27 09:25:24.174008', 25.18936291077102),\n",
              " ('2021-07-28 09:25:24.174008', 23.868334284551604),\n",
              " ('2021-07-29 09:25:24.174008', 20.565297893171813),\n",
              " ('2021-07-30 09:25:24.174008', 20.543511621751517),\n",
              " ('2021-07-31 09:25:24.174008', 21.433510852491885),\n",
              " ('2021-08-01 09:25:24.174008', 21.69593097737011),\n",
              " ('2021-08-02 09:25:24.174008', 22.698784934732306),\n",
              " ('2021-08-03 09:25:24.174008', 23.9421090003538),\n",
              " ('2021-08-04 09:25:24.174008', 25.45852705508443),\n",
              " ('2021-08-05 09:25:24.174008', 22.671644973787313),\n",
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            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>Date</th>\n",
              "            <th>Temperature</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>2021-06-27 09:25:24.174008</td>\n",
              "            <td>25.456466516929375</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-06-28 09:25:24.174008</td>\n",
              "            <td>25.08194822020671</td>\n",
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              "        <tr>\n",
              "            <td>2021-06-29 09:25:24.174008</td>\n",
              "            <td>18.02003565857419</td>\n",
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              "        <tr>\n",
              "            <td>2021-06-30 09:25:24.174008</td>\n",
              "            <td>19.810526922230757</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-01 09:25:24.174008</td>\n",
              "            <td>21.112912350807566</td>\n",
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              "            <td>2021-07-02 09:25:24.174008</td>\n",
              "            <td>20.800907718472633</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-03 09:25:24.174008</td>\n",
              "            <td>18.448013962702134</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-04 09:25:24.174008</td>\n",
              "            <td>24.470218722119778</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-05 09:25:24.174008</td>\n",
              "            <td>25.157674007746834</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-06 09:25:24.174008</td>\n",
              "            <td>24.486404917103272</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-07 09:25:24.174008</td>\n",
              "            <td>25.81832649655456</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-08 09:25:24.174008</td>\n",
              "            <td>25.134481638418592</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-09 09:25:24.174008</td>\n",
              "            <td>24.89875805492679</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-10 09:25:24.174008</td>\n",
              "            <td>18.071192712105344</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-11 09:25:24.174008</td>\n",
              "            <td>23.985347573743493</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-12 09:25:24.174008</td>\n",
              "            <td>23.87384945212648</td>\n",
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              "            <td>2021-07-13 09:25:24.174008</td>\n",
              "            <td>22.89201275841107</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-14 09:25:24.174008</td>\n",
              "            <td>18.190306449810972</td>\n",
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              "            <td>2021-07-15 09:25:24.174008</td>\n",
              "            <td>20.21664159112378</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-16 09:25:24.174008</td>\n",
              "            <td>20.597733727300046</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-17 09:25:24.174008</td>\n",
              "            <td>19.570371000012848</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-18 09:25:24.174008</td>\n",
              "            <td>21.29992823004546</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-19 09:25:24.174008</td>\n",
              "            <td>23.961524741312015</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-20 09:25:24.174008</td>\n",
              "            <td>25.616870127319615</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-21 09:25:24.174008</td>\n",
              "            <td>20.89200041527153</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-22 09:25:24.174008</td>\n",
              "            <td>19.497103727149494</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-23 09:25:24.174008</td>\n",
              "            <td>20.092936112902905</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-24 09:25:24.174008</td>\n",
              "            <td>19.600499856532046</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-25 09:25:24.174008</td>\n",
              "            <td>21.4311676857373</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-26 09:25:24.174008</td>\n",
              "            <td>22.662100224622467</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-27 09:25:24.174008</td>\n",
              "            <td>25.18936291077102</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-28 09:25:24.174008</td>\n",
              "            <td>23.868334284551604</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-29 09:25:24.174008</td>\n",
              "            <td>20.565297893171813</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-30 09:25:24.174008</td>\n",
              "            <td>20.543511621751517</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-31 09:25:24.174008</td>\n",
              "            <td>21.433510852491885</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-01 09:25:24.174008</td>\n",
              "            <td>21.69593097737011</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-02 09:25:24.174008</td>\n",
              "            <td>22.698784934732306</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-03 09:25:24.174008</td>\n",
              "            <td>23.9421090003538</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-04 09:25:24.174008</td>\n",
              "            <td>25.45852705508443</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-05 09:25:24.174008</td>\n",
              "            <td>22.671644973787313</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-06 09:25:24.174008</td>\n",
              "            <td>18.30855402103405</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-07 09:25:24.174008</td>\n",
              "            <td>23.50225482292432</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-08 09:25:24.174008</td>\n",
              "            <td>20.268968135036143</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-09 09:25:24.174008</td>\n",
              "            <td>18.363272378965416</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-10 09:25:24.174008</td>\n",
              "            <td>19.335923018305543</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-11 09:25:24.174008</td>\n",
              "            <td>19.36425393261696</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-12 09:25:24.174008</td>\n",
              "            <td>23.009903065740545</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-13 09:25:24.174008</td>\n",
              "            <td>20.44236680806804</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-14 09:25:24.174008</td>\n",
              "            <td>20.856903656822524</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-15 09:25:24.174008</td>\n",
              "            <td>21.649786765016913</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-16 09:25:24.174008</td>\n",
              "            <td>18.70479877569586</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-17 09:25:24.174008</td>\n",
              "            <td>23.910069983729773</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-18 09:25:24.174008</td>\n",
              "            <td>21.156748300654158</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-19 09:25:24.174008</td>\n",
              "            <td>18.611975921124547</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-20 09:25:24.174008</td>\n",
              "            <td>24.20496705601469</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-21 09:25:24.174008</td>\n",
              "            <td>25.55220854253946</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-22 09:25:24.174008</td>\n",
              "            <td>22.043398584609484</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-23 09:25:24.174008</td>\n",
              "            <td>22.171427794343717</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-24 09:25:24.174008</td>\n",
              "            <td>18.72808915454693</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-25 09:25:24.174008</td>\n",
              "            <td>24.130656467895147</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-26 09:25:24.174008</td>\n",
              "            <td>23.201056631849646</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-27 09:25:24.174008</td>\n",
              "            <td>25.931898561051216</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-28 09:25:24.174008</td>\n",
              "            <td>19.57054489999622</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-29 09:25:24.174008</td>\n",
              "            <td>25.579425930971983</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-30 09:25:24.174008</td>\n",
              "            <td>18.53843806521833</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-31 09:25:24.174008</td>\n",
              "            <td>18.73375444150738</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-01 09:25:24.174008</td>\n",
              "            <td>21.065523272578996</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-02 09:25:24.174008</td>\n",
              "            <td>22.61912585671356</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-03 09:25:24.174008</td>\n",
              "            <td>25.006959215858608</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-04 09:25:24.174008</td>\n",
              "            <td>20.92253815713645</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-05 09:25:24.174008</td>\n",
              "            <td>20.51123592528669</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-06 09:25:24.174008</td>\n",
              "            <td>20.501271797822735</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-07 09:25:24.174008</td>\n",
              "            <td>23.95551497275985</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-08 09:25:24.174008</td>\n",
              "            <td>22.535807286361752</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-09 09:25:24.174008</td>\n",
              "            <td>25.851602133273936</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-10 09:25:24.174008</td>\n",
              "            <td>18.139889332933905</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-11 09:25:24.174008</td>\n",
              "            <td>20.76906427375925</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-12 09:25:24.174008</td>\n",
              "            <td>18.577279741282513</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-13 09:25:24.174008</td>\n",
              "            <td>25.838439002100564</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-14 09:25:24.174008</td>\n",
              "            <td>25.60039880116839</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-15 09:25:24.174008</td>\n",
              "            <td>21.298961661254893</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-16 09:25:24.174008</td>\n",
              "            <td>22.15763670337828</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-17 09:25:24.174008</td>\n",
              "            <td>19.375847899725926</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-18 09:25:24.174008</td>\n",
              "            <td>21.94893881479571</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-19 09:25:24.174008</td>\n",
              "            <td>21.34561107838343</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-20 09:25:24.174008</td>\n",
              "            <td>24.005483290251636</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-21 09:25:24.174008</td>\n",
              "            <td>18.2270283011273</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-22 09:25:24.174008</td>\n",
              "            <td>22.270098985631044</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-23 09:25:24.174008</td>\n",
              "            <td>22.185239487459384</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-24 09:25:24.174008</td>\n",
              "            <td>21.242830219641945</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-25 09:25:24.174008</td>\n",
              "            <td>19.40372699703223</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-26 09:25:24.174008</td>\n",
              "            <td>22.708206153045406</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-27 09:25:24.174008</td>\n",
              "            <td>19.608403400009728</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-28 09:25:24.174008</td>\n",
              "            <td>21.610563252034073</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-29 09:25:24.174008</td>\n",
              "            <td>23.160362850611364</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-30 09:25:24.174008</td>\n",
              "            <td>22.81024432801468</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-01 09:25:24.174008</td>\n",
              "            <td>18.843351696375386</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-02 09:25:24.174008</td>\n",
              "            <td>20.521262780257047</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-03 09:25:24.174008</td>\n",
              "            <td>25.857284709531342</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-04 09:25:24.174008</td>\n",
              "            <td>25.109299798138878</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-05 09:25:24.174008</td>\n",
              "            <td>24.490519442458336</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-06 09:25:24.174008</td>\n",
              "            <td>18.620407815674145</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-07 09:25:24.174008</td>\n",
              "            <td>23.533232841782237</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-08 09:25:24.174008</td>\n",
              "            <td>18.11285563950693</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-09 09:25:24.174008</td>\n",
              "            <td>22.76433436512066</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-10 09:25:24.174008</td>\n",
              "            <td>21.13456039138876</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-11 09:25:24.174008</td>\n",
              "            <td>18.893398943774685</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-12 09:25:24.174008</td>\n",
              "            <td>24.878805988234387</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-13 09:25:24.174008</td>\n",
              "            <td>23.086454949840395</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-14 09:25:24.174008</td>\n",
              "            <td>25.467536469400763</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-15 09:25:24.174008</td>\n",
              "            <td>20.173519043365737</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-16 09:25:24.174008</td>\n",
              "            <td>22.907025561848997</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-17 09:25:24.174008</td>\n",
              "            <td>20.754779263500403</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-18 09:25:24.174008</td>\n",
              "            <td>22.801786719477523</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-19 09:25:24.174008</td>\n",
              "            <td>21.180221725973638</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-20 09:25:24.174008</td>\n",
              "            <td>23.396859131322653</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-21 09:25:24.174008</td>\n",
              "            <td>24.624143637590198</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-22 09:25:24.174008</td>\n",
              "            <td>24.787868872735693</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-23 09:25:24.174008</td>\n",
              "            <td>22.16056509042678</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-24 09:25:24.174008</td>\n",
              "            <td>19.87263976553627</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-25 09:25:24.174008</td>\n",
              "            <td>20.841383714226225</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-26 09:25:24.174008</td>\n",
              "            <td>20.425477239112574</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-27 09:25:24.174008</td>\n",
              "            <td>24.282893121103584</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-28 09:25:24.174008</td>\n",
              "            <td>20.3530274213767</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-29 09:25:24.174008</td>\n",
              "            <td>25.47520265721136</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-30 09:25:24.174008</td>\n",
              "            <td>21.751319873333568</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-31 09:25:24.174008</td>\n",
              "            <td>23.357535261046607</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-01 09:25:24.174008</td>\n",
              "            <td>20.444109830206305</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-02 09:25:24.174008</td>\n",
              "            <td>20.22047248285347</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-03 09:25:24.174008</td>\n",
              "            <td>25.92458971475984</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-04 09:25:24.174008</td>\n",
              "            <td>19.95022910210589</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-05 09:25:24.174008</td>\n",
              "            <td>24.09437660230563</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-06 09:25:24.174008</td>\n",
              "            <td>19.255681939100114</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-07 09:25:24.174008</td>\n",
              "            <td>19.539289736538624</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-08 09:25:24.174008</td>\n",
              "            <td>25.04705823796777</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-09 09:25:24.174008</td>\n",
              "            <td>18.537639396400895</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-10 09:25:24.174008</td>\n",
              "            <td>25.14504671212659</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-11 09:25:24.174008</td>\n",
              "            <td>20.976017795286182</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-12 09:25:24.174008</td>\n",
              "            <td>21.822763443538587</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-13 09:25:24.174008</td>\n",
              "            <td>21.900529820879058</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-14 09:25:24.174008</td>\n",
              "            <td>20.069487145819735</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-15 09:25:24.174008</td>\n",
              "            <td>23.286691041098386</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-16 09:25:24.174008</td>\n",
              "            <td>21.214399977753818</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-17 09:25:24.174008</td>\n",
              "            <td>25.645869251791762</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-18 09:25:24.174008</td>\n",
              "            <td>22.491522517526644</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-19 09:25:24.174008</td>\n",
              "            <td>25.579070486383994</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-20 09:25:24.174008</td>\n",
              "            <td>23.278372586647862</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-21 09:25:24.174008</td>\n",
              "            <td>21.195250645730752</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-22 09:25:24.174008</td>\n",
              "            <td>22.373297783825475</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-23 09:25:24.174008</td>\n",
              "            <td>25.90030011694888</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-24 09:25:24.174008</td>\n",
              "            <td>22.894805477837675</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-25 09:25:24.174008</td>\n",
              "            <td>18.192019357154635</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-26 09:25:24.174008</td>\n",
              "            <td>24.717034875069377</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-27 09:25:24.174008</td>\n",
              "            <td>25.214459761568754</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-28 09:25:24.174008</td>\n",
              "            <td>24.924772601595173</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-29 09:25:24.174008</td>\n",
              "            <td>20.45838134070921</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-30 09:25:24.174008</td>\n",
              "            <td>20.393265830523564</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-01 09:25:24.174008</td>\n",
              "            <td>21.503926132218616</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-02 09:25:24.174008</td>\n",
              "            <td>23.44300807832388</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-03 09:25:24.174008</td>\n",
              "            <td>18.950060351416404</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-04 09:25:24.174008</td>\n",
              "            <td>21.866050977035187</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-05 09:25:24.174008</td>\n",
              "            <td>25.758574916842345</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-06 09:25:24.174008</td>\n",
              "            <td>18.915077815043496</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-07 09:25:24.174008</td>\n",
              "            <td>25.68342242837952</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-08 09:25:24.174008</td>\n",
              "            <td>22.344988474590807</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-09 09:25:24.174008</td>\n",
              "            <td>21.654401864114057</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-10 09:25:24.174008</td>\n",
              "            <td>18.553280947653448</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-11 09:25:24.174008</td>\n",
              "            <td>21.170402310150333</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-12 09:25:24.174008</td>\n",
              "            <td>19.123396796003497</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-13 09:25:24.174008</td>\n",
              "            <td>18.14456158341882</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-14 09:25:24.174008</td>\n",
              "            <td>20.91648078559285</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-15 09:25:24.174008</td>\n",
              "            <td>25.50130172759603</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-16 09:25:24.174008</td>\n",
              "            <td>22.237354013333313</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-17 09:25:24.174008</td>\n",
              "            <td>22.18990414009759</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-18 09:25:24.174008</td>\n",
              "            <td>23.01892462634287</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-19 09:25:24.174008</td>\n",
              "            <td>19.290186615244473</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-20 09:25:24.174008</td>\n",
              "            <td>23.82209003613093</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-21 09:25:24.174008</td>\n",
              "            <td>22.234147885052092</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-22 09:25:24.174008</td>\n",
              "            <td>21.64344885542633</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-23 09:25:24.174008</td>\n",
              "            <td>23.000810027447116</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-24 09:25:24.174008</td>\n",
              "            <td>18.58970218097072</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-25 09:25:24.174008</td>\n",
              "            <td>25.707530514790253</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-26 09:25:24.174008</td>\n",
              "            <td>24.04212863711845</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-27 09:25:24.174008</td>\n",
              "            <td>25.54328295360086</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-28 09:25:24.174008</td>\n",
              "            <td>20.72155353899806</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-29 09:25:24.174008</td>\n",
              "            <td>19.358601617294934</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-30 09:25:24.174008</td>\n",
              "            <td>24.38376701699359</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-31 09:25:24.174008</td>\n",
              "            <td>21.256489942593664</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-01 09:25:24.174008</td>\n",
              "            <td>21.342281413746967</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-02 09:25:24.174008</td>\n",
              "            <td>23.612114574085673</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-03 09:25:24.174008</td>\n",
              "            <td>23.971767523223132</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-04 09:25:24.174008</td>\n",
              "            <td>19.70778395684156</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-05 09:25:24.174008</td>\n",
              "            <td>20.2136872370195</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-06 09:25:24.174008</td>\n",
              "            <td>21.54634027445743</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-07 09:25:24.174008</td>\n",
              "            <td>20.13765021250392</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-08 09:25:24.174008</td>\n",
              "            <td>24.34175684773502</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-09 09:25:24.174008</td>\n",
              "            <td>25.581872299804303</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-10 09:25:24.174008</td>\n",
              "            <td>23.91488590779244</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-11 09:25:24.174008</td>\n",
              "            <td>21.298681369743413</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-12 09:25:24.174008</td>\n",
              "            <td>23.21453761656503</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-13 09:25:24.174008</td>\n",
              "            <td>22.71999894010857</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-14 09:25:24.174008</td>\n",
              "            <td>23.34970428570398</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-15 09:25:24.174008</td>\n",
              "            <td>25.2170423860724</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-16 09:25:24.174008</td>\n",
              "            <td>23.77891660450682</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-17 09:25:24.174008</td>\n",
              "            <td>21.168676072365653</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-18 09:25:24.174008</td>\n",
              "            <td>18.856311876404465</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-19 09:25:24.174008</td>\n",
              "            <td>25.66539700297466</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-20 09:25:24.174008</td>\n",
              "            <td>18.989653496032638</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-21 09:25:24.174008</td>\n",
              "            <td>25.296762365173766</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-22 09:25:24.174008</td>\n",
              "            <td>22.168744831408667</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-23 09:25:24.174008</td>\n",
              "            <td>25.429696879838815</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-24 09:25:24.174008</td>\n",
              "            <td>24.668269034773893</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-25 09:25:24.174008</td>\n",
              "            <td>23.438503398767494</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-26 09:25:24.174008</td>\n",
              "            <td>18.027900286015786</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-27 09:25:24.174008</td>\n",
              "            <td>20.124592824238448</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-28 09:25:24.174008</td>\n",
              "            <td>25.47167733418759</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-29 09:25:24.174008</td>\n",
              "            <td>24.58722293044576</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-30 09:25:24.174008</td>\n",
              "            <td>22.550136182706147</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-01-31 09:25:24.174008</td>\n",
              "            <td>24.81206218896969</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-01 09:25:24.174008</td>\n",
              "            <td>25.10087430130314</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-02 09:25:24.174008</td>\n",
              "            <td>18.783536629088022</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-03 09:25:24.174008</td>\n",
              "            <td>20.699168023028435</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-04 09:25:24.174008</td>\n",
              "            <td>20.6503739876708</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-05 09:25:24.174008</td>\n",
              "            <td>24.140792605804663</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-06 09:25:24.174008</td>\n",
              "            <td>21.310853993459144</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-07 09:25:24.174008</td>\n",
              "            <td>23.272353213607843</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-08 09:25:24.174008</td>\n",
              "            <td>19.6023323647562</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-09 09:25:24.174008</td>\n",
              "            <td>22.19483215818379</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-10 09:25:24.174008</td>\n",
              "            <td>23.113479976793066</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-11 09:25:24.174008</td>\n",
              "            <td>24.57108279350208</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-12 09:25:24.174008</td>\n",
              "            <td>23.241810951541943</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-13 09:25:24.174008</td>\n",
              "            <td>18.874156787033296</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-14 09:25:24.174008</td>\n",
              "            <td>24.462366637117718</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-15 09:25:24.174008</td>\n",
              "            <td>20.321223541135975</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-16 09:25:24.174008</td>\n",
              "            <td>23.08666130355333</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-17 09:25:24.174008</td>\n",
              "            <td>24.396595253680854</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-18 09:25:24.174008</td>\n",
              "            <td>21.189359331976032</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-19 09:25:24.174008</td>\n",
              "            <td>24.243265210070128</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-20 09:25:24.174008</td>\n",
              "            <td>20.4793436140863</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-21 09:25:24.174008</td>\n",
              "            <td>25.657719382910823</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-22 09:25:24.174008</td>\n",
              "            <td>18.23989522090849</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-23 09:25:24.174008</td>\n",
              "            <td>21.330258823431816</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-24 09:25:24.174008</td>\n",
              "            <td>23.22567470512177</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-25 09:25:24.174008</td>\n",
              "            <td>18.642020127170667</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-26 09:25:24.174008</td>\n",
              "            <td>23.414803990906872</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-27 09:25:24.174008</td>\n",
              "            <td>19.830067044645112</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-02-28 09:25:24.174008</td>\n",
              "            <td>20.14545485474102</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-01 09:25:24.174008</td>\n",
              "            <td>19.69940822716945</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-02 09:25:24.174008</td>\n",
              "            <td>18.24910862969964</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-03 09:25:24.174008</td>\n",
              "            <td>22.564865555704397</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-04 09:25:24.174008</td>\n",
              "            <td>20.467892174441577</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-05 09:25:24.174008</td>\n",
              "            <td>20.52874512375115</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-06 09:25:24.174008</td>\n",
              "            <td>24.314973808481867</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-07 09:25:24.174008</td>\n",
              "            <td>22.353696315052346</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-08 09:25:24.174008</td>\n",
              "            <td>21.01349786748697</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-09 09:25:24.174008</td>\n",
              "            <td>18.385684928005087</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-10 09:25:24.174008</td>\n",
              "            <td>19.573347652002997</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-11 09:25:24.174008</td>\n",
              "            <td>21.202646059157765</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-12 09:25:24.174008</td>\n",
              "            <td>21.78386813753518</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-13 09:25:24.174008</td>\n",
              "            <td>22.14354386075354</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-14 09:25:24.174008</td>\n",
              "            <td>20.770501348674426</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-15 09:25:24.174008</td>\n",
              "            <td>18.700801551894866</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-16 09:25:24.174008</td>\n",
              "            <td>25.80674900637808</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-17 09:25:24.174008</td>\n",
              "            <td>24.259692316617794</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-18 09:25:24.174008</td>\n",
              "            <td>21.599840110835913</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-19 09:25:24.174008</td>\n",
              "            <td>24.88255331585441</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-20 09:25:24.174008</td>\n",
              "            <td>21.11815254712252</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-21 09:25:24.174008</td>\n",
              "            <td>22.415119455893713</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-22 09:25:24.174008</td>\n",
              "            <td>22.269778116263073</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-23 09:25:24.174008</td>\n",
              "            <td>25.505663966460105</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-24 09:25:24.174008</td>\n",
              "            <td>20.007893061482555</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-25 09:25:24.174008</td>\n",
              "            <td>25.63644640395943</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-26 09:25:24.174008</td>\n",
              "            <td>24.51418589392095</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-27 09:25:24.174008</td>\n",
              "            <td>22.136197014609145</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-28 09:25:24.174008</td>\n",
              "            <td>24.777247156172173</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-29 09:25:24.174008</td>\n",
              "            <td>21.714607186180444</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-30 09:25:24.174008</td>\n",
              "            <td>20.76548584635066</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-03-31 09:25:24.174008</td>\n",
              "            <td>25.810924015862437</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-01 09:25:24.174008</td>\n",
              "            <td>24.75088051402578</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-02 09:25:24.174008</td>\n",
              "            <td>23.607416914998172</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-03 09:25:24.174008</td>\n",
              "            <td>24.983080963927414</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-04 09:25:24.174008</td>\n",
              "            <td>23.91623681833259</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-05 09:25:24.174008</td>\n",
              "            <td>22.412346820183185</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-06 09:25:24.174008</td>\n",
              "            <td>23.699092268286694</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-07 09:25:24.174008</td>\n",
              "            <td>19.117690194270544</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-08 09:25:24.174008</td>\n",
              "            <td>18.42201477686949</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-09 09:25:24.174008</td>\n",
              "            <td>21.96221299972636</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-10 09:25:24.174008</td>\n",
              "            <td>21.62875159112192</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-11 09:25:24.174008</td>\n",
              "            <td>20.70942629999205</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-12 09:25:24.174008</td>\n",
              "            <td>24.220471111540945</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-13 09:25:24.174008</td>\n",
              "            <td>23.323252758065642</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-14 09:25:24.174008</td>\n",
              "            <td>21.662492345192213</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-15 09:25:24.174008</td>\n",
              "            <td>20.662113540835215</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-16 09:25:24.174008</td>\n",
              "            <td>25.6880937368573</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-17 09:25:24.174008</td>\n",
              "            <td>20.79232438708057</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-18 09:25:24.174008</td>\n",
              "            <td>19.892543519533614</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-19 09:25:24.174008</td>\n",
              "            <td>19.849669953087066</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-20 09:25:24.174008</td>\n",
              "            <td>19.10689851540227</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-21 09:25:24.174008</td>\n",
              "            <td>22.111559777965336</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-22 09:25:24.174008</td>\n",
              "            <td>19.456274717770466</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-23 09:25:24.174008</td>\n",
              "            <td>23.646885189373105</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-24 09:25:24.174008</td>\n",
              "            <td>18.385212428827174</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-25 09:25:24.174008</td>\n",
              "            <td>18.17988852892123</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-26 09:25:24.174008</td>\n",
              "            <td>23.770904010560034</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-27 09:25:24.174008</td>\n",
              "            <td>25.789262173341882</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-28 09:25:24.174008</td>\n",
              "            <td>18.294908472452587</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-29 09:25:24.174008</td>\n",
              "            <td>18.96010138067355</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-04-30 09:25:24.174008</td>\n",
              "            <td>22.493115890479167</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-01 09:25:24.174008</td>\n",
              "            <td>20.5880834911401</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-02 09:25:24.174008</td>\n",
              "            <td>21.367693739122934</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-03 09:25:24.174008</td>\n",
              "            <td>21.487258357334383</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-04 09:25:24.174008</td>\n",
              "            <td>22.39884482419742</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-05 09:25:24.174008</td>\n",
              "            <td>20.375020735974108</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-06 09:25:24.174008</td>\n",
              "            <td>21.404319232500377</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-07 09:25:24.174008</td>\n",
              "            <td>18.373853028511693</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-08 09:25:24.174008</td>\n",
              "            <td>18.185439699256264</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-09 09:25:24.174008</td>\n",
              "            <td>23.966207666412718</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-10 09:25:24.174008</td>\n",
              "            <td>25.79733189328443</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-11 09:25:24.174008</td>\n",
              "            <td>22.25904768474745</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-12 09:25:24.174008</td>\n",
              "            <td>25.078536383080603</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-13 09:25:24.174008</td>\n",
              "            <td>23.220735766735086</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-14 09:25:24.174008</td>\n",
              "            <td>21.295642757534274</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-15 09:25:24.174008</td>\n",
              "            <td>23.396552744606012</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-16 09:25:24.174008</td>\n",
              "            <td>25.290509237755103</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-17 09:25:24.174008</td>\n",
              "            <td>24.86217681180864</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-18 09:25:24.174008</td>\n",
              "            <td>19.39580173287756</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-19 09:25:24.174008</td>\n",
              "            <td>24.272844595974377</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-20 09:25:24.174008</td>\n",
              "            <td>18.461965755552793</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-21 09:25:24.174008</td>\n",
              "            <td>20.335521234190836</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-22 09:25:24.174008</td>\n",
              "            <td>24.84297935291523</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-23 09:25:24.174008</td>\n",
              "            <td>25.039308703217166</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-24 09:25:24.174008</td>\n",
              "            <td>18.93168210776141</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-25 09:25:24.174008</td>\n",
              "            <td>20.248147921494322</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-26 09:25:24.174008</td>\n",
              "            <td>23.892095925779252</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-27 09:25:24.174008</td>\n",
              "            <td>22.73329460101304</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-28 09:25:24.174008</td>\n",
              "            <td>21.41087864388283</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-29 09:25:24.174008</td>\n",
              "            <td>20.00069082721359</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-30 09:25:24.174008</td>\n",
              "            <td>24.07362781497213</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-05-31 09:25:24.174008</td>\n",
              "            <td>23.389668341044917</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-01 09:25:24.174008</td>\n",
              "            <td>23.637082634478446</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-02 09:25:24.174008</td>\n",
              "            <td>25.92811186102494</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-03 09:25:24.174008</td>\n",
              "            <td>22.957581051430026</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-04 09:25:24.174008</td>\n",
              "            <td>21.871771531347623</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-05 09:25:24.174008</td>\n",
              "            <td>24.298029410560147</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-06 09:25:24.174008</td>\n",
              "            <td>19.59954987572</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-07 09:25:24.174008</td>\n",
              "            <td>19.68940136231261</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-08 09:25:24.174008</td>\n",
              "            <td>23.519448492618</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-09 09:25:24.174008</td>\n",
              "            <td>20.71351472341609</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-10 09:25:24.174008</td>\n",
              "            <td>24.311749875964868</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-11 09:25:24.174008</td>\n",
              "            <td>20.269788272406565</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-12 09:25:24.174008</td>\n",
              "            <td>20.46480719467782</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-13 09:25:24.174008</td>\n",
              "            <td>20.854973774862405</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-14 09:25:24.174008</td>\n",
              "            <td>24.46851443300315</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-15 09:25:24.174008</td>\n",
              "            <td>23.325660550256664</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-16 09:25:24.174008</td>\n",
              "            <td>21.888979480275125</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-17 09:25:24.174008</td>\n",
              "            <td>25.165411290483284</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-18 09:25:24.174008</td>\n",
              "            <td>23.858024328648654</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-19 09:25:24.174008</td>\n",
              "            <td>24.304958905651514</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-20 09:25:24.174008</td>\n",
              "            <td>20.308324786736797</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-21 09:25:24.174008</td>\n",
              "            <td>21.30378290069623</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-22 09:25:24.174008</td>\n",
              "            <td>23.444073450856962</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-23 09:25:24.174008</td>\n",
              "            <td>22.912660580592295</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-24 09:25:24.174008</td>\n",
              "            <td>22.587980934075972</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-25 09:25:24.174008</td>\n",
              "            <td>21.051189211704486</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-26 09:25:24.174008</td>\n",
              "            <td>23.83172679044125</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-27 09:25:24.174008</td>\n",
              "            <td>18.801937533073126</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-28 09:25:24.174008</td>\n",
              "            <td>22.42340792085914</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-29 09:25:24.174008</td>\n",
              "            <td>20.33734390772414</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022-06-30 09:25:24.174008</td>\n",
              "            <td>18.22224360213111</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql sqlite://\n",
        "SELECT Timestamp as Date, Temperature\n",
        "FROM Temperature\n",
        "WHERE CAST(strftime('%Y', Date) as Int) = 2021"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "udMX6qB2toTn",
        "outputId": "20813e08-95ec-4c5e-98ec-f81dbffda69f"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>Date</th>\n",
              "            <th>Temperature</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>2021-06-27 09:25:24.174008</td>\n",
              "            <td>25.456466516929375</td>\n",
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              "        <tr>\n",
              "            <td>2021-06-28 09:25:24.174008</td>\n",
              "            <td>25.08194822020671</td>\n",
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              "        <tr>\n",
              "            <td>2021-06-29 09:25:24.174008</td>\n",
              "            <td>18.02003565857419</td>\n",
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              "        <tr>\n",
              "            <td>2021-06-30 09:25:24.174008</td>\n",
              "            <td>19.810526922230757</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-01 09:25:24.174008</td>\n",
              "            <td>21.112912350807566</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-02 09:25:24.174008</td>\n",
              "            <td>20.800907718472633</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-03 09:25:24.174008</td>\n",
              "            <td>18.448013962702134</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-04 09:25:24.174008</td>\n",
              "            <td>24.470218722119778</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-05 09:25:24.174008</td>\n",
              "            <td>25.157674007746834</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-06 09:25:24.174008</td>\n",
              "            <td>24.486404917103272</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-07 09:25:24.174008</td>\n",
              "            <td>25.81832649655456</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-08 09:25:24.174008</td>\n",
              "            <td>25.134481638418592</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-09 09:25:24.174008</td>\n",
              "            <td>24.89875805492679</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-10 09:25:24.174008</td>\n",
              "            <td>18.071192712105344</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-11 09:25:24.174008</td>\n",
              "            <td>23.985347573743493</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-12 09:25:24.174008</td>\n",
              "            <td>23.87384945212648</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-13 09:25:24.174008</td>\n",
              "            <td>22.89201275841107</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-14 09:25:24.174008</td>\n",
              "            <td>18.190306449810972</td>\n",
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              "            <td>2021-07-15 09:25:24.174008</td>\n",
              "            <td>20.21664159112378</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-16 09:25:24.174008</td>\n",
              "            <td>20.597733727300046</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-17 09:25:24.174008</td>\n",
              "            <td>19.570371000012848</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-18 09:25:24.174008</td>\n",
              "            <td>21.29992823004546</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-19 09:25:24.174008</td>\n",
              "            <td>23.961524741312015</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-20 09:25:24.174008</td>\n",
              "            <td>25.616870127319615</td>\n",
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              "        <tr>\n",
              "            <td>2021-07-21 09:25:24.174008</td>\n",
              "            <td>20.89200041527153</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-22 09:25:24.174008</td>\n",
              "            <td>19.497103727149494</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-23 09:25:24.174008</td>\n",
              "            <td>20.092936112902905</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-24 09:25:24.174008</td>\n",
              "            <td>19.600499856532046</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-25 09:25:24.174008</td>\n",
              "            <td>21.4311676857373</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-26 09:25:24.174008</td>\n",
              "            <td>22.662100224622467</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-27 09:25:24.174008</td>\n",
              "            <td>25.18936291077102</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-28 09:25:24.174008</td>\n",
              "            <td>23.868334284551604</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-29 09:25:24.174008</td>\n",
              "            <td>20.565297893171813</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-30 09:25:24.174008</td>\n",
              "            <td>20.543511621751517</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-07-31 09:25:24.174008</td>\n",
              "            <td>21.433510852491885</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-01 09:25:24.174008</td>\n",
              "            <td>21.69593097737011</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-02 09:25:24.174008</td>\n",
              "            <td>22.698784934732306</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-03 09:25:24.174008</td>\n",
              "            <td>23.9421090003538</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-04 09:25:24.174008</td>\n",
              "            <td>25.45852705508443</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-05 09:25:24.174008</td>\n",
              "            <td>22.671644973787313</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-06 09:25:24.174008</td>\n",
              "            <td>18.30855402103405</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-07 09:25:24.174008</td>\n",
              "            <td>23.50225482292432</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-08 09:25:24.174008</td>\n",
              "            <td>20.268968135036143</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-09 09:25:24.174008</td>\n",
              "            <td>18.363272378965416</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-10 09:25:24.174008</td>\n",
              "            <td>19.335923018305543</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-11 09:25:24.174008</td>\n",
              "            <td>19.36425393261696</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-12 09:25:24.174008</td>\n",
              "            <td>23.009903065740545</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-13 09:25:24.174008</td>\n",
              "            <td>20.44236680806804</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-14 09:25:24.174008</td>\n",
              "            <td>20.856903656822524</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-15 09:25:24.174008</td>\n",
              "            <td>21.649786765016913</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-16 09:25:24.174008</td>\n",
              "            <td>18.70479877569586</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-17 09:25:24.174008</td>\n",
              "            <td>23.910069983729773</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-18 09:25:24.174008</td>\n",
              "            <td>21.156748300654158</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-19 09:25:24.174008</td>\n",
              "            <td>18.611975921124547</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-20 09:25:24.174008</td>\n",
              "            <td>24.20496705601469</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-21 09:25:24.174008</td>\n",
              "            <td>25.55220854253946</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-22 09:25:24.174008</td>\n",
              "            <td>22.043398584609484</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-23 09:25:24.174008</td>\n",
              "            <td>22.171427794343717</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-24 09:25:24.174008</td>\n",
              "            <td>18.72808915454693</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-25 09:25:24.174008</td>\n",
              "            <td>24.130656467895147</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-26 09:25:24.174008</td>\n",
              "            <td>23.201056631849646</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-27 09:25:24.174008</td>\n",
              "            <td>25.931898561051216</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-28 09:25:24.174008</td>\n",
              "            <td>19.57054489999622</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-29 09:25:24.174008</td>\n",
              "            <td>25.579425930971983</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-30 09:25:24.174008</td>\n",
              "            <td>18.53843806521833</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-08-31 09:25:24.174008</td>\n",
              "            <td>18.73375444150738</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-01 09:25:24.174008</td>\n",
              "            <td>21.065523272578996</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-02 09:25:24.174008</td>\n",
              "            <td>22.61912585671356</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-03 09:25:24.174008</td>\n",
              "            <td>25.006959215858608</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-04 09:25:24.174008</td>\n",
              "            <td>20.92253815713645</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-05 09:25:24.174008</td>\n",
              "            <td>20.51123592528669</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-06 09:25:24.174008</td>\n",
              "            <td>20.501271797822735</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-07 09:25:24.174008</td>\n",
              "            <td>23.95551497275985</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-08 09:25:24.174008</td>\n",
              "            <td>22.535807286361752</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-09 09:25:24.174008</td>\n",
              "            <td>25.851602133273936</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-10 09:25:24.174008</td>\n",
              "            <td>18.139889332933905</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-11 09:25:24.174008</td>\n",
              "            <td>20.76906427375925</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-12 09:25:24.174008</td>\n",
              "            <td>18.577279741282513</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-13 09:25:24.174008</td>\n",
              "            <td>25.838439002100564</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-14 09:25:24.174008</td>\n",
              "            <td>25.60039880116839</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-15 09:25:24.174008</td>\n",
              "            <td>21.298961661254893</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-16 09:25:24.174008</td>\n",
              "            <td>22.15763670337828</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-17 09:25:24.174008</td>\n",
              "            <td>19.375847899725926</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-18 09:25:24.174008</td>\n",
              "            <td>21.94893881479571</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-19 09:25:24.174008</td>\n",
              "            <td>21.34561107838343</td>\n",
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              "        <tr>\n",
              "            <td>2021-09-20 09:25:24.174008</td>\n",
              "            <td>24.005483290251636</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-21 09:25:24.174008</td>\n",
              "            <td>18.2270283011273</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-22 09:25:24.174008</td>\n",
              "            <td>22.270098985631044</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-23 09:25:24.174008</td>\n",
              "            <td>22.185239487459384</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-24 09:25:24.174008</td>\n",
              "            <td>21.242830219641945</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-25 09:25:24.174008</td>\n",
              "            <td>19.40372699703223</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-26 09:25:24.174008</td>\n",
              "            <td>22.708206153045406</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-27 09:25:24.174008</td>\n",
              "            <td>19.608403400009728</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-28 09:25:24.174008</td>\n",
              "            <td>21.610563252034073</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-29 09:25:24.174008</td>\n",
              "            <td>23.160362850611364</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-09-30 09:25:24.174008</td>\n",
              "            <td>22.81024432801468</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-01 09:25:24.174008</td>\n",
              "            <td>18.843351696375386</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-02 09:25:24.174008</td>\n",
              "            <td>20.521262780257047</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-03 09:25:24.174008</td>\n",
              "            <td>25.857284709531342</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-04 09:25:24.174008</td>\n",
              "            <td>25.109299798138878</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-05 09:25:24.174008</td>\n",
              "            <td>24.490519442458336</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-06 09:25:24.174008</td>\n",
              "            <td>18.620407815674145</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-07 09:25:24.174008</td>\n",
              "            <td>23.533232841782237</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-08 09:25:24.174008</td>\n",
              "            <td>18.11285563950693</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-09 09:25:24.174008</td>\n",
              "            <td>22.76433436512066</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-10 09:25:24.174008</td>\n",
              "            <td>21.13456039138876</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-11 09:25:24.174008</td>\n",
              "            <td>18.893398943774685</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-12 09:25:24.174008</td>\n",
              "            <td>24.878805988234387</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-13 09:25:24.174008</td>\n",
              "            <td>23.086454949840395</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-14 09:25:24.174008</td>\n",
              "            <td>25.467536469400763</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-15 09:25:24.174008</td>\n",
              "            <td>20.173519043365737</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-16 09:25:24.174008</td>\n",
              "            <td>22.907025561848997</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-17 09:25:24.174008</td>\n",
              "            <td>20.754779263500403</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-18 09:25:24.174008</td>\n",
              "            <td>22.801786719477523</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-19 09:25:24.174008</td>\n",
              "            <td>21.180221725973638</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-20 09:25:24.174008</td>\n",
              "            <td>23.396859131322653</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-21 09:25:24.174008</td>\n",
              "            <td>24.624143637590198</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-22 09:25:24.174008</td>\n",
              "            <td>24.787868872735693</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-23 09:25:24.174008</td>\n",
              "            <td>22.16056509042678</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-24 09:25:24.174008</td>\n",
              "            <td>19.87263976553627</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-25 09:25:24.174008</td>\n",
              "            <td>20.841383714226225</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-26 09:25:24.174008</td>\n",
              "            <td>20.425477239112574</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-27 09:25:24.174008</td>\n",
              "            <td>24.282893121103584</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-28 09:25:24.174008</td>\n",
              "            <td>20.3530274213767</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-29 09:25:24.174008</td>\n",
              "            <td>25.47520265721136</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-30 09:25:24.174008</td>\n",
              "            <td>21.751319873333568</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-10-31 09:25:24.174008</td>\n",
              "            <td>23.357535261046607</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-01 09:25:24.174008</td>\n",
              "            <td>20.444109830206305</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-02 09:25:24.174008</td>\n",
              "            <td>20.22047248285347</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-03 09:25:24.174008</td>\n",
              "            <td>25.92458971475984</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-04 09:25:24.174008</td>\n",
              "            <td>19.95022910210589</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-05 09:25:24.174008</td>\n",
              "            <td>24.09437660230563</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-06 09:25:24.174008</td>\n",
              "            <td>19.255681939100114</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-07 09:25:24.174008</td>\n",
              "            <td>19.539289736538624</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-08 09:25:24.174008</td>\n",
              "            <td>25.04705823796777</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-09 09:25:24.174008</td>\n",
              "            <td>18.537639396400895</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-10 09:25:24.174008</td>\n",
              "            <td>25.14504671212659</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-11 09:25:24.174008</td>\n",
              "            <td>20.976017795286182</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-12 09:25:24.174008</td>\n",
              "            <td>21.822763443538587</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-13 09:25:24.174008</td>\n",
              "            <td>21.900529820879058</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-14 09:25:24.174008</td>\n",
              "            <td>20.069487145819735</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-15 09:25:24.174008</td>\n",
              "            <td>23.286691041098386</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-16 09:25:24.174008</td>\n",
              "            <td>21.214399977753818</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-17 09:25:24.174008</td>\n",
              "            <td>25.645869251791762</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-18 09:25:24.174008</td>\n",
              "            <td>22.491522517526644</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-19 09:25:24.174008</td>\n",
              "            <td>25.579070486383994</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-20 09:25:24.174008</td>\n",
              "            <td>23.278372586647862</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-21 09:25:24.174008</td>\n",
              "            <td>21.195250645730752</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-22 09:25:24.174008</td>\n",
              "            <td>22.373297783825475</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-23 09:25:24.174008</td>\n",
              "            <td>25.90030011694888</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-24 09:25:24.174008</td>\n",
              "            <td>22.894805477837675</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-25 09:25:24.174008</td>\n",
              "            <td>18.192019357154635</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-26 09:25:24.174008</td>\n",
              "            <td>24.717034875069377</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-27 09:25:24.174008</td>\n",
              "            <td>25.214459761568754</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-28 09:25:24.174008</td>\n",
              "            <td>24.924772601595173</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-29 09:25:24.174008</td>\n",
              "            <td>20.45838134070921</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-11-30 09:25:24.174008</td>\n",
              "            <td>20.393265830523564</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-01 09:25:24.174008</td>\n",
              "            <td>21.503926132218616</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-02 09:25:24.174008</td>\n",
              "            <td>23.44300807832388</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-03 09:25:24.174008</td>\n",
              "            <td>18.950060351416404</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-04 09:25:24.174008</td>\n",
              "            <td>21.866050977035187</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-05 09:25:24.174008</td>\n",
              "            <td>25.758574916842345</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-06 09:25:24.174008</td>\n",
              "            <td>18.915077815043496</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-07 09:25:24.174008</td>\n",
              "            <td>25.68342242837952</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-08 09:25:24.174008</td>\n",
              "            <td>22.344988474590807</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-09 09:25:24.174008</td>\n",
              "            <td>21.654401864114057</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-10 09:25:24.174008</td>\n",
              "            <td>18.553280947653448</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-11 09:25:24.174008</td>\n",
              "            <td>21.170402310150333</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-12 09:25:24.174008</td>\n",
              "            <td>19.123396796003497</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-13 09:25:24.174008</td>\n",
              "            <td>18.14456158341882</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-14 09:25:24.174008</td>\n",
              "            <td>20.91648078559285</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-15 09:25:24.174008</td>\n",
              "            <td>25.50130172759603</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-16 09:25:24.174008</td>\n",
              "            <td>22.237354013333313</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-17 09:25:24.174008</td>\n",
              "            <td>22.18990414009759</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-18 09:25:24.174008</td>\n",
              "            <td>23.01892462634287</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-19 09:25:24.174008</td>\n",
              "            <td>19.290186615244473</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-20 09:25:24.174008</td>\n",
              "            <td>23.82209003613093</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-21 09:25:24.174008</td>\n",
              "            <td>22.234147885052092</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-22 09:25:24.174008</td>\n",
              "            <td>21.64344885542633</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-23 09:25:24.174008</td>\n",
              "            <td>23.000810027447116</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-24 09:25:24.174008</td>\n",
              "            <td>18.58970218097072</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-25 09:25:24.174008</td>\n",
              "            <td>25.707530514790253</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-26 09:25:24.174008</td>\n",
              "            <td>24.04212863711845</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-27 09:25:24.174008</td>\n",
              "            <td>25.54328295360086</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-28 09:25:24.174008</td>\n",
              "            <td>20.72155353899806</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-29 09:25:24.174008</td>\n",
              "            <td>19.358601617294934</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-30 09:25:24.174008</td>\n",
              "            <td>24.38376701699359</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2021-12-31 09:25:24.174008</td>\n",
              "            <td>21.256489942593664</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql sqlite://\n",
        "SELECT strftime('%Y', Timestamp) as Year,\n",
        "  AVG(Temperature) AS MEAN_TMP,\n",
        "  MAX(Temperature) AS MAX_TMP,\n",
        "  MIN(Temperature) AS MIN_TMP\n",
        "FROM Temperature\n",
        "GROUP BY strftime('%Y', Timestamp)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 100
        },
        "id": "rS_0Yt4Bt2Fg",
        "outputId": "7221ae3a-3cd6-4cb6-97ee-6ccbfd0d87e2"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('2021', 22.03221261870554, 25.931898561051216, 18.02003565857419),\n",
              " ('2022', 22.130909932509113, 25.92811186102494, 18.027900286015786)]"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>Year</th>\n",
              "            <th>MEAN_TMP</th>\n",
              "            <th>MAX_TMP</th>\n",
              "            <th>MIN_TMP</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>2021</td>\n",
              "            <td>22.03221261870554</td>\n",
              "            <td>25.931898561051216</td>\n",
              "            <td>18.02003565857419</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2022</td>\n",
              "            <td>22.130909932509113</td>\n",
              "            <td>25.92811186102494</td>\n",
              "            <td>18.027900286015786</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ts = %sql SELECT datetime(Timestamp) as date, Temperature FROM Temperature\n",
        "df = ts. DataFrame()\n",
        "df.set_index(\"date\", inplace = True)\n",
        "df.index = pd.to_datetime(df.index)\n",
        "df.index"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vCAzzZyAuJLq",
        "outputId": "fe0f4e95-c6ef-4a40-b333-e1f558afbac4"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " * sqlite:///demo.db3\n",
            "Done.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['2021-06-27 09:25:24', '2021-06-28 09:25:24',\n",
              "               '2021-06-29 09:25:24', '2021-06-30 09:25:24',\n",
              "               '2021-07-01 09:25:24', '2021-07-02 09:25:24',\n",
              "               '2021-07-03 09:25:24', '2021-07-04 09:25:24',\n",
              "               '2021-07-05 09:25:24', '2021-07-06 09:25:24',\n",
              "               ...\n",
              "               '2022-10-30 09:25:24', '2022-10-31 09:25:24',\n",
              "               '2022-11-01 09:25:24', '2022-11-02 09:25:24',\n",
              "               '2022-11-03 09:25:24', '2022-11-04 09:25:24',\n",
              "               '2022-11-05 09:25:24', '2022-11-06 09:25:24',\n",
              "               '2022-11-07 09:25:24', '2022-11-08 09:25:24'],\n",
              "              dtype='datetime64[ns]', name='date', length=500, freq=None)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.plot(figsize=(12,6))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "id": "vbPXJmrHua6O",
        "outputId": "7c3ac925-28af-45f8-a003-8cf1114e84b8"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2246203850>"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}