TSDA_BDA.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u6CR_wJPWgkZ",
        "outputId": "8ee0e043-ed09-4044-ec1c-6f234264e117"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pyspark in /usr/local/lib/python3.10/dist-packages (3.5.0)\n",
            "Requirement already satisfied: py4j==0.10.9.7 in /usr/local/lib/python3.10/dist-packages (from pyspark) (0.10.9.7)\n",
            "Requirement already satisfied: pyspark in /usr/local/lib/python3.10/dist-packages (3.5.0)\n",
            "Requirement already satisfied: py4j==0.10.9.7 in /usr/local/lib/python3.10/dist-packages (from pyspark) (0.10.9.7)\n"
          ]
        }
      ],
      "source": [
        "!pip install pyspark"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from statsmodels.tsa.stattools import adfuller\n",
        "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
        "import pyspark\n"
      ],
      "metadata": {
        "id": "DK5mFDgkW2Yd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from pyspark.sql import SparkSession"
      ],
      "metadata": {
        "id": "E3oxfvV7Xbbn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Initialize Spark\n",
        "spark = SparkSession.builder.appName(\"EnergyConsumption\").getOrCreate()\n"
      ],
      "metadata": {
        "id": "VOTgauRYW-LY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "historical_data  = spark.read.csv(\"SM Cleaned Data BR Aggregated.csv\", header=True, inferSchema=True)\n"
      ],
      "metadata": {
        "id": "NnneVUA5W-25"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "historical_data.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XKoc0FV2XT7i",
        "outputId": "0d7fa2d0-227e-4f1e-a6cd-40a6fefcc459"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+-----+----------+------------------+\n",
            "|meter|      Date|             t_kWh|\n",
            "+-----+----------+------------------+\n",
            "| BR02|2019-07-10| 6.959999999999997|\n",
            "| BR02|2019-07-11| 4.910999999999991|\n",
            "| BR02|2019-07-13| 5.872999999999988|\n",
            "| BR02|2019-07-14| 5.457999999999984|\n",
            "| BR02|2019-07-15| 4.859999999999995|\n",
            "| BR02|2019-07-16| 4.281999999999985|\n",
            "| BR02|2019-07-17| 4.421999999999985|\n",
            "| BR02|2019-07-18|  4.33699999999998|\n",
            "| BR02|2019-07-19| 5.441999999999984|\n",
            "| BR02|2019-07-20| 5.650999999999988|\n",
            "| BR02|2019-07-30| 5.847999999999994|\n",
            "| BR02|2019-07-31|5.8319999999999865|\n",
            "| BR02|2019-08-01| 5.006999999999988|\n",
            "| BR02|2019-08-04| 7.383999999999983|\n",
            "| BR02|2019-08-05| 6.977999999999994|\n",
            "| BR02|2019-08-06|5.2839999999999945|\n",
            "| BR02|2019-08-07| 5.651999999999995|\n",
            "| BR02|2019-08-08|4.7749999999999835|\n",
            "| BR02|2019-08-09| 5.005999999999984|\n",
            "| BR02|2019-08-10|5.8899999999999775|\n",
            "+-----+----------+------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pyspark.sql.functions import year, month, dayofweek\n",
        "\n",
        "# Extract year, month, and day of the week as features\n",
        "historical_data = historical_data.withColumn(\"Year\", year(\"Date\"))\n",
        "historical_data = historical_data.withColumn(\"Month\", month(\"Date\"))\n",
        "historical_data = historical_data.withColumn(\"DayOfWeek\", dayofweek(\"Date\"))\n",
        "\n",
        "# Show the DataFrame with added time-based features\n",
        "historical_data.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6L3mtT5UYrBE",
        "outputId": "be2e42b0-367a-41fe-ed86-0b3bf7276036"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+-----+----------+------------------+----+-----+---------+\n",
            "|meter|      Date|             t_kWh|Year|Month|DayOfWeek|\n",
            "+-----+----------+------------------+----+-----+---------+\n",
            "| BR02|2019-07-10| 6.959999999999997|2019|    7|        4|\n",
            "| BR02|2019-07-11| 4.910999999999991|2019|    7|        5|\n",
            "| BR02|2019-07-13| 5.872999999999988|2019|    7|        7|\n",
            "| BR02|2019-07-14| 5.457999999999984|2019|    7|        1|\n",
            "| BR02|2019-07-15| 4.859999999999995|2019|    7|        2|\n",
            "| BR02|2019-07-16| 4.281999999999985|2019|    7|        3|\n",
            "| BR02|2019-07-17| 4.421999999999985|2019|    7|        4|\n",
            "| BR02|2019-07-18|  4.33699999999998|2019|    7|        5|\n",
            "| BR02|2019-07-19| 5.441999999999984|2019|    7|        6|\n",
            "| BR02|2019-07-20| 5.650999999999988|2019|    7|        7|\n",
            "| BR02|2019-07-30| 5.847999999999994|2019|    7|        3|\n",
            "| BR02|2019-07-31|5.8319999999999865|2019|    7|        4|\n",
            "| BR02|2019-08-01| 5.006999999999988|2019|    8|        5|\n",
            "| BR02|2019-08-04| 7.383999999999983|2019|    8|        1|\n",
            "| BR02|2019-08-05| 6.977999999999994|2019|    8|        2|\n",
            "| BR02|2019-08-06|5.2839999999999945|2019|    8|        3|\n",
            "| BR02|2019-08-07| 5.651999999999995|2019|    8|        4|\n",
            "| BR02|2019-08-08|4.7749999999999835|2019|    8|        5|\n",
            "| BR02|2019-08-09| 5.005999999999984|2019|    8|        6|\n",
            "| BR02|2019-08-10|5.8899999999999775|2019|    8|        7|\n",
            "+-----+----------+------------------+----+-----+---------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Convert the Spark DataFrame to a Pandas DataFrame\n",
        "historical_pd = historical_data.toPandas()\n",
        "\n",
        "# Set the Date column as the index\n",
        "historical_pd['Date'] = pd.to_datetime(historical_pd['Date'])\n",
        "historical_pd.set_index(\"Date\", inplace=True)\n",
        "\n",
        "# Extract the target variable\n",
        "t_kWh = historical_pd['t_kWh']\n"
      ],
      "metadata": {
        "id": "Vo-T9jL_W-6R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def test_stationarity(timeseries):\n",
        "    # Perform the ADF test\n",
        "    result = adfuller(timeseries, autolag='AIC')\n",
        "    print('ADF Statistic:', result[0])\n",
        "    print('p-value:', result[1])\n",
        "    print('Critical Values:')\n",
        "    for key, value in result[4].items():\n",
        "        print(f'   {key}: {value}')\n",
        "\n",
        "# Check stationarity of the target variable\n",
        "test_stationarity(t_kWh)\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aDbUY1--W-9j",
        "outputId": "f1076e79-6875-4070-ae97-547370b6a62c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ADF Statistic: -10.521281392532694\n",
            "p-value: 9.668275724474122e-19\n",
            "Critical Values:\n",
            "   1%: -3.430583001929187\n",
            "   5%: -2.8616429802942416\n",
            "   10%: -2.5668248133133242\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In output, the ADF Statistic is -10.521, and the p-value is approximately 9.67e-19. The ADF Statistic value is significantly lower than the critical values at the 1%, 5%, and 10% significance levels. Additionally, the p-value is very close to zero. These results suggest that one can reject the null hypothesis of non-stationarity, indicating that  time series data (t_kWh) is likely stationary."
      ],
      "metadata": {
        "id": "83kcQSM9a10s"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from pyspark.sql.functions import year, month, avg\n",
        "from pyspark.sql.types import DateType\n",
        "from pyspark.sql.functions import to_date"
      ],
      "metadata": {
        "id": "dstWG-LpZXNR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Assuming you have a DataFrame named \"historical_data\" with Date and t_kWh columns\n",
        "historical_data = historical_data.withColumn(\"Date\", to_date(historical_data[\"Date\"]))\n",
        "\n",
        "# Collect the data to the driver for plotting (only if data fits in memory)\n",
        "historical_data_pd = historical_data.toPandas()\n",
        "\n",
        "# Create a line plot for the time series data\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.plot(historical_data_pd[\"Date\"], historical_data_pd[\"t_kWh\"])\n",
        "plt.xlabel(\"Date\")\n",
        "plt.ylabel(\"t_kWh\")\n",
        "plt.title(\"Time Series Plot of t_kWh\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "24TJqlaaZrvK",
        "outputId": "ddb88c4f-6fc8-4d56-d3f5-621e82e3ab99"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Assuming you have a DataFrame named \"historical_data\" with Date and t_kWh columns\n",
        "# Collect the data to the driver for plotting (only if data fits in memory)\n",
        "historical_data_pd = historical_data.toPandas()\n",
        "\n",
        "# Create a histogram to visualize the distribution of \"t_kWh\"\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.hist(historical_data_pd[\"t_kWh\"], bins=20, edgecolor=\"k\")\n",
        "plt.xlabel(\"t_kWh\")\n",
        "plt.ylabel(\"Frequency\")\n",
        "plt.title(\"Histogram of t_kWh\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "KccOIHtWZryG",
        "outputId": "0439a765-4198-4e1e-dd04-f8ebca3200df"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Assuming you have a DataFrame named \"monthly_data\" with Year, Month, and sum(t_kWh) columns\n",
        "# Collect the data to the driver for plotting (only if data fits in memory)\n",
        "monthly_data_pd = monthly_data.toPandas()\n",
        "\n",
        "# Create a bar plot to visualize monthly aggregated data\n",
        "plt.figure(figsize=(10, 6))\n",
        "plt.bar(monthly_data_pd[\"Year\"].astype(str) + \"-\" + monthly_data_pd[\"Month\"].astype(str), monthly_data_pd[\"sum(t_kWh)\"])\n",
        "plt.xlabel(\"Year-Month\")\n",
        "plt.ylabel(\"Total t_kWh\")\n",
        "plt.title(\"Monthly Aggregated t_kWh\")\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 601
        },
        "id": "QjpLGxttZr3j",
        "outputId": "9823f8dd-3cca-46ec-e875-3f6071d1bd3d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pyspark.sql.functions import year, month, avg\n",
        "\n",
        "# Group the data by year and month and calculate the mean of \"t_kWh\"\n",
        "monthly_data = historical_data.groupBy(\"Year\", \"Month\").agg(avg(\"t_kWh\").alias(\"Mean_t_kWh\")).orderBy(\"Year\", \"Month\")\n",
        "\n",
        "# Collect the data to the driver for plotting (only if data fits in memory)\n",
        "monthly_data_pd = monthly_data.toPandas()\n",
        "\n",
        "# Create a bar plot to visualize the mean \"t_kWh\" for each month\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.bar(monthly_data_pd[\"Year\"].astype(str) + \"-\" + monthly_data_pd[\"Month\"].astype(str), monthly_data_pd[\"Mean_t_kWh\"])\n",
        "plt.xlabel(\"Year-Month\")\n",
        "plt.ylabel(\"Mean t_kWh\")\n",
        "plt.title(\"Monthly Mean t_kWh\")\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 601
        },
        "id": "namsSaQOZr7_",
        "outputId": "2c1ff7fd-73b2-4c7b-b867-1c3a2f755e6a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "we can observe a seasonal pattern though no strong trend appears to be there"
      ],
      "metadata": {
        "id": "3O4g6mmJa-Ek"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot ACF and PACF\n",
        "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(20, 20))\n",
        "plot_acf(t_kWh, lags=365, ax=ax1)\n",
        "plot_pacf(t_kWh, lags=365, ax=ax2)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Aegwmq3mW_AS",
        "outputId": "6a32f033-1c54-4dd0-8a91-448af3c67823"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x2000 with 2 Axes>"
            ],
            "image/png": 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AAAAoK8EKdEOZaKHhSmvHZCI+dufzlgYDAAAAACgjwQp0Q6X0XGmUiYgl67bG9377N0uDAQAAAACUSf+uvgGgqenjRsfbDt0vTr/5qYho6LlSbA1L/e4GLJfetyAeWbgmjhq5b5w9oSrGDN+7wJEAAAAAABSiYgW6qdyeKzdML72CJSLiiUXrVLAAAAAAAHQgFSvQA7S1giUTKlgAAAAAADqSihXoIXIrWB64eFL2dSmFLCpYAAAAAADaR7ACPVDVsMHZ16kSkpXGCpZ0JuKy+xfE8g01HX9zAAAAAAC9mGAFerjrp7Wt/0omE/GxO5+P2XMXxTIBCwAAAABAUfRYgR6uPf1XlqzbGss21MSceUvj5KNGxD6DBsQh+++lBwsAAAAAQAsEK9AL5PZfuWH6sXHVgwsjXUy6Enua2z+xeH1UpCJSqZSgBQAAAACgBYIV6GXaWsESEQ1hTKZp0HLrk0tj9pnHxVkTqspyzwAAAAAAPYUeK9ALJStY2tKDJaIhaGlsdn/pfQviygf+qB8LAAAAANCnCVagl5s+bnQ8dMnk7LiNGUtERPx4/oo45Wvz4t7nV7b/xgAAAAAAeiDBCvQBuRUsqXYkK5loqGK57P4FsVzlCgAAAADQBwlWoI+5flrblwZrlMlEfOzO52P23EWWBgMAAAAA+hTBCvQxyaXBTjpyeMlVLJmIWLJua3zvt3+zNBgAAAAA0KcIVqAPyl0abM554+PhNgYtjY3tLQ0GAAAAAPQVghWg1aClGJYGAwAAAAD6CsEK0ERu0FJMPxZLgwEAAAAAfYVgBWjV/R+flH1dKGOxNBgAAAAA0NsJVoBWVQ0bnH1dbO8VS4MBAAAAAL2VYAUo2vXTjrU0GAAAAADQpwlWgKJNHzc6HsppbG9pMAAAAACgrxGsACXJbWxvaTAAAAAAoK8RrABtZmkwAAAAAKCvEawAbWZpMAAAAACgrxGsAO1iaTAAAAAAoC8RrAAdxtJgAAAAAEBvJ1gBOoylwQAAAACA3k6wAnQoS4MBAAAAAL2ZYAUoG0uDAQAAAAC9jWAFKBtLgwEAAAAAvY1gBSirtiwNlkql4h5VKwAAAABANyRYATpNsUuD1acz8eif1+q3AgAAAAB0O4IVoNOUsjTY0nVb9VsBAAAAALqd/l19A0DfklwaLJNpfr9MNGy79L4F8cjCNXHUyH3j7AlVMWb43s0fAAAAAADQCVSsAF2m2KXBnli0Lr7327+pYAEAAAAAupyKFaDLTB83Ot526H5x+s1PtbpfJhr6rkSoYAEAAAAAupaKFaBL5S4NViwVLAAAAABAV1GxAvQ4KlgAAAAAgK6iYgXoNorpt9IcFSwAAAAAQGcRrADdxv0fn5R9XUrG0ljBks40VLB89I7nYvbcRbFsQ02H3yMAAAAA0LcJVoBuo2rY4OzrG6Yfq4IFAAAAAOh2BCtAtzR93Oh46JLJ2XFbK1guu39BLFe5AgAAAAB0EMEK0G296YA9jejbWsGSyUR87M7nLQ0GAAAAAHSI/l19AwDFmD5udLzt0P3i9JufioiGCpZMEcdlImLJuq2xbENNzJm3NE4+akTsM2hAHLL/XnH2hKoYM3zvgucAAAAAAGgkWAF6jGQFy1UPLox0MelKNCwNFhHxxOL12cqX785bGsdXDY1JY4cLWQAAAACAoghWgB6prRUsEZEXxry0cnMsWLVZNQsAAAAAUBTBCtBjtaeCJVfjMY3VLKlUStACAAAAADRLsAL0Cu2pYMmVzkRDx/vID1pufXJpzD7zuDhrQlWH3TMAAAAA0PMIVoBeI7eCJZXK5iPtkhu0XHrfgnhk4Zo4auS+KlgAAAAAoI8SrAC90vXT2r40WGueWLQunvzLekuFAQAAAEAfVdHVNwBQDtPHjY6HLpmcHZ905PBIpdp/3kxE1KczkYmGpcIeWvBafO+3f4tTvjYv7n1+ZfsvAAAAAAB0aypWgF4rd2mwOeeNj1c21rS7B0uSpcIAAAAAoG9RsQL0GblBywMXT8q+7qhqloiGpcJUsAAAAABA7yVYAfqkqmGDs6/nnDc+Hu6gZcMalwpLZyIuu39BLN9Q0847BQAAAAC6E8EKQDRdNiw3aGlrMUsqlYp7VK0AAAAAQK8iWAFoRm7QcsP0Y6OiDelKfToTP3vptZg9d1EsU7kCAAAAAL2CYAWggOnjRsdDbVwqbPWm7XquAAAAAEAvIlgBKEJblwrL7bly6X0L4soH/qh6BQAAAAB6sP5dfQMAPVFyqbCrHlwY6Uzh4348f0X8eP6KOPmoEbHPoAFxyP57xdkTqmLM8L0LHwwAAAAAdDnBCkA7TR83Ot526H5x+s1PRURDBUtLGUvj+08sXh8VqYYG93PmLRW0AAAAAEAPIVgB6AC5FSwVqVTUZwqXr6QzEbF7v9yg5dYnl8bsM4+LsyZUlet2AQAAAIA2EqwAdLBMi/UqrcsNWi69b0E8snBNHDVyXxUsAAAAANCNaF4P0MGun3ZsVLTW0b5ITyxaF9/77d/ilK/Ni3ufX9n+EwIAAAAA7dYpwcott9wShx12WAwaNCgmTpwY8+fPb3HfO+64I1KpVN7XoEGD8vbJZDJx9dVXx8EHHxx77bVXTJkyJf7617+W+2MAFGX6uNHx0CWT232eTETUpzORzkRcdv+CWL6hpv03BwAAAAC0S9mDlXvuuSdmzZoV11xzTfz+97+Pt771rTF16tRYt25di8cMGTIkVq9enf165ZVX8rZ/+ctfjm9+85sxZ86cePbZZ2PvvfeOqVOnxo4dO8r9cQCKkt9zpf3ny2QiPnbn8zF77qJYJmABAAAAgC5T9mDl61//elx44YUxY8aMOOaYY2LOnDkxePDguP3221s8JpVKxciRI7NfBx10UHZbJpOJm266Kb7whS/E+9///jjuuOPizjvvjNdeey0efPDBcn8cgJLd//FJ2dcnHTk8Um0IWjIRsWTdVkuDAQAAAEAXK2uwsnPnznjhhRdiypQpey5YURFTpkyJZ555psXjtm7dGm9605uiqqoq3v/+98ef/vSn7LZly5bFmjVr8s45dOjQmDhxYovnrK2tjerq6rwvgM5SNWxw9vWc88bHwznLhJUatFgaDAAAAAC6VlmDlQ0bNkR9fX1exUlExEEHHRRr1qxp9pijjjoqbr/99vjZz34WP/zhDyOdTseJJ54Yq1atiojIHlfKOW+88cYYOnRo9quqqqq9Hw2gzXKXCUsGLcVmLJYGAwAAAICu0b+rbyBp0qRJMWnSnmVzTjzxxDj66KPj1ltvjeuvv75N57ziiiti1qxZ2XF1dbVwBeg2coOWG6YfG1c9uDDSmdaPaVwabNmGmpgzb2mcfNSI2GfQgDhk/73i7AlVMWb43q2fAAAAAABok7IGK8OHD49+/frF2rVr895fu3ZtjBw5sqhzDBgwIMaNGxdLliyJiMget3bt2jj44IPzznn88cc3e47KysqorKxswycA6FzTx42Otx26X5x+81MR0VDB0lrGUr87gXli8fqo2F3u8t15S+P4qqExaexwIQsAAAAAdLCyLgU2cODAGD9+fDz22GPZ99LpdDz22GN5VSmtqa+vjz/+8Y/ZEGXMmDExcuTIvHNWV1fHs88+W/Q5Abqz3AqWUvqvpDORrXR5aeXmuPXJpfHur86LGd+fH5/88YuWDQMAAACADlD2pcBmzZoVH/7wh2PChAlxwgknxE033RQ1NTUxY8aMiIg4//zzY/To0XHjjTdGRMR1110Xb3/72+OII46ITZs2xVe+8pV45ZVX4mMf+1hERKRSqfjUpz4VN9xwQ/zd3/1djBkzJq666qoYNWpUTJs2rdwfB6BTXT+tuKXBmtN4TGM1SyqVsmwYAAAAALRT2YOVc845J9avXx9XX311rFmzJo4//viYO3dutvn8ihUroqJiT+HMG2+8ERdeeGGsWbMm9t9//xg/fnw8/fTTccwxx2T3+dznPhc1NTVx0UUXxaZNm2Ly5Mkxd+7cGDRoULk/DkCnKnVpsJakM9HQ8T7yg5Zbn1was888Ls6aoO8UAAAAABSjU5rXz5w5M2bOnNnstnnz5uWNv/GNb8Q3vvGNVs+XSqXiuuuui+uuu66jbhGg20ouDZZpS7KSkBu0XHrfgnhk4Zo4auS+KlgAAAAAoIBOCVYA6BjtWRqsNU8sWhdP/mW9pcIAAAAAoADBCkAPklwa7KQjh8fv/rqh3VUsmYioTzddKkzQAgAAAAD5BCsAPUzu0mBzzhsfr2ysaXcPlqSWerIIWgAAAADo6wQrAD1cbtDywMWTYvp3nomIjqtmiWg+aImI+O68pXF81dCYNHa4kAUAAACAPqGiq28AgI5TNWxw9vWc88bHw5dMzo5POnJ4pFIdc510JrJ9Xl5auTlufXJpnPK1eXHv8ys75gIAAAAA0E2pWAHoxTpj2bCIPSHLpfctiEcWromjRu6rggUAAACAXkmwAtCH5AYtN0w/Nq56cGE2FOkoTyxaF0/+Zb1+LAAAAAD0SoIVgD5q+rjR8bZD98tWsHRUT5ZMRNSnNb4HAAAAoHcSrAD0Ya0tFdZRQUtzje8FLQAAAAD0VJrXA5CVDFoevmRydnzSkcMjlWr/NdKZhoqWTDQELQ8teC2+99u/xSlfmxf3Pr+y/RcAAAAAgDJSsQJAi1qraElFw7Jf7ZVb0XLpfQvikYVr4qiR+6pgAQAAAKBbEqwAULTcoOWBiyfF9O88ExEdF7JERDyxaF08+Zf1lgoDAAAAoFuyFBgAbVI1bHD29Q3Tj42KDlgmLKIhoLFUGAAAAADdlWAFgHabPm50PFSGfiwRe3qypDMNS4Vd+cAfY9mGmo45OQAAAACUSLACQIfojMb3ERE/nr9C9QoAAAAAXUawAkBZlCtoyURkq1c+esdzMXvuIhUsAAAAAHQazesB6BTJoOWVjTVx+s1PRUREKhoCk1K11Oj+xLEHxNNLN8aqN7ZrfA8AAABAhxKsANAlcoOWG6YfG1c9uDDSJaYrjY3uIxoa3VekGt777rylUbG7IiaVSjUJXgQtAAAAALSVYAWALjd93Oh426H7ZStYTjpyePzurxsiU2LQkhvMZF9n8oMXQQsAAAAA7SFYAaBbaG2psI6SzoSgBQAAAIB2EawA0C3lBi0VqSh5mbBiNBe0RDQsJXZ81dCYNHa4kAUAAACAPIIVALq9+z8+KaZ/55mIaHuj+2LkhjcvrdwcC1ZtblLNcuLYA+LppRtj1RvbVbcAAAAA9EGCFQC6vaphg7Ov29rovi0ar9FYzZKJhmqWxsoWy4gBAAAA9D0VXX0DAFCK6eNGx0OXTM6OTzpyeKRSe7anmjmmI6Qz2VXDIp1p+KpPZyITDcHLQwtei+/99m9xytfmxb3PryzTXQAAAADQ1QQrAPQ4yUb3D+cELRe8Y0zc9uHx2XEyeCmXxqAlnYm49L4F8dE7novZcxfFsg015b84AAAAAJ3GUmAA9Hi5Qcus9xyZt23OeePjlY01cfrNT0VEQ9Dyu79uyFaflMsTi9bFk39Zb6kwAAAAgF5GxQoAvV5rFS7lqmjJhKXCAAAAAHojFSsA9DnJoCW3oiUVDaFIR0tnItuk5dL7FsQjC9fEUSP3VcECAAAA0MOoWAGgz8sNWh64eFL2dbKapSMLW55YtC5ufXJpvOur82LaLU/pxwIAAADQQ6hYAYAcVcMGZ18nq1kueMeYmHT4sLjgBy9ERPv6teQUsMRLKzfHglWb9WMBAAAA6AEEKwDQitxqllnvOTJvW0cuI5befeATi9dHRSoilUo1CVpOHHtAPL10Y6x6Y7vgBQAAAKCLCFYAoB1yg5cbph8bVz24MBuStFVuP5bGoCUTEd+dtzQqdq9Hlkql4tYnl8bsM4+LsyZUte+CAAAAABRNjxUA6CDTx42Ohy6ZnB0ne7S0VTqzZ9mwdKbhqz6diXQm4tL7FsRH73hOjxYAAACATqJiBQA6UG4FS0cuFdaaJxatiyf/sl6PFgAAAIBOIFgBgDIqx1JhSZloqGCJaL1Hi6AFAAAAoP0EKwDQSaaPGx1vO3S/slewNNejJaKhR8vxVUNj0tjhQhYAAACANtJjBQA6UW4FywMXT8q+7qh+LM1p7MsSEfHSys1x65NL45SvzYt7n19ZngsCAAAA9GKCFQDoIlXDBmdfzzlvfDzcSuP7jsxcGoMWje8BAAAASidYAYBuItn4PjdoueAdY+K2D4/PjjsqaHli0br43m//poIFAAAAoEiCFQDopnKDllnvOTImjR2eHd8w/dhs75T2aGx8r4IFAAAAoDia1wNADzR93Oh426H7xek3PxURDUuH/e6vGxp71rfZE4vWxZN/WR9z5i2Nk48aEfsMGhCH7L9XnDj2gHh66cZY9cb2OGT/veLsCVUxZvjehU8IAAAA0MsIVgCgh0ouHfbKxpp2By2NFSwREU8sXh8VqYb3vjtvabZCJpVKNQleBC0AAABAXyFYAYBeorWgJRUNAUmp0plmXmfyg5eIhuDl+KqhMWnscCELAAAA0KvpsQIAvVRu0PLAxZOyrzuq8X1EQ9jSGLi8tHJz3Prk0jjla/Pi3udXduBVAAAAALoPwQoA9AFVwwZnX3dU4/vmNAYtl963ID56x3Mxe+6iWLahpjwXAwAAAOgCghUA6GOmjxsdD10yOTsuU8YSTyxaF9/77d9UsAAAAAC9imAFAPqg3GXCylXBkomI+nRGBQsAAADQq2heDwB93PRxo+Nth+6XbXR/0pHD43d/3dDYo77Nje+Tnli0Lp78y/qYM29pnHzUiNhn0IA4ZP+9NLsHAAAAehTBCgCQV8Ey57zx8crGmmzQcsE7xsSkw4fFBT94ISKaBi/FaqxgiYh4YvH6qEhFpFIpQQsAAADQowhWAIAmcoOWWe85Mm9bMnhpa0VLOhPRmM7kBi23Prk0Zp95XJw1oaqNdw8AAABQPoIVAKBkucHLAxdPiunfeSYi2rdsWG7Qcul9C+KRhWviqJH7xoljD4inl26MVW9sV9ECAAAAdDnBCgDQLlXDBmdf3zD92LjqwYWR7oCmLE8sWhdPLF4X3523NCpSDe+paAEAAAC6WkVX3wAA0HtMHzc6Hrpkcnacase5cgpYIp1p+KpPZyKdaahoufKBP8ayDTXtul8AAACAUqlYAQA6VO4yYR1ZwZL04/kr4sfzV2h8DwAAAHQqwQoAUDbTx42Otx26X7bR/UlHDo/f/XVDthKlPRpPkdv4fs68pYIWAAAAoKwEKwBAWeVWsMw5b3y8srGmw4OW3Mb3ghYAAACgnAQrAECnai1oScWeSpT2aClo0fgeAAAAaC/BCgDQpVrryVKOoOXS+xbEIwvXxFEj940Txx4QTy/dGKve2K6iBQAAACiKYAUA6DaSPVkueMeYmHT4sLjgBy906HWeWLQunli8Lr47b2lUpBreU9ECAAAAFEOwAgB0K7kVLLPec2TetopUZKtZ2iOT/Z+c8zVT0aKCBQAAAEiq6OobAAAo1v0fn5R9fdKRwyOVKs91nli0Lr7327/FKV+bF/c+v7I8FwEAAAB6JMEKANBjVA0bnH0957zx8fAlk7PjjgxaMhFRn85EOtNQwXLlA3+MZRtqOubkAAAAQI9mKTAAoMfKXTZsznnj45WNNdn+LCcdOTx+99cNjSt8tcuP56+IH89fEScfNSL2GTRAo3sAAADowwQrAECv0VrQkopsW5WSNR73xOL1UZHS6B4AAAD6MkuBAQC9Vm7QcsP0Y6MiZ6mwtq4als7kLxP20Tuei9lzF1kqDAAAAPoIFSsAQJ8wfdzoeNuh+2UrWC54x5iYdPiwuOAHL0RE2ytanli0Lp78y/qYM2+ppcIAAACgDxCsAAB9Rm4Fy6z3HJm37Ybpx8ZVDy6MdInpSmOj+4j8pcKSQcuJYw+Ip5dujFVvbBe8AAAAPd6yDTXxk+dXluV3nOS5k79Ptfb7VanHFvpdLfd8+1T2i1SkYkvtrjadu733QvchWAEAiKYVLW2VzkREJj9oyUTEd+ctzS5F1lzw4gdmAACgO2ktoNi6oy6e/Mv6SKVSkclkOvR3nJ88vzIuv39B9tzJ36eS49g9Pr5qaOw/eGDefRU6ttDvarmfM53OZFc5SO3+n1LOXeo493NNGjvc74zdjGAFAGC33IqWilSUXL3SnNxzZF8ngpcIPzADAACdq5TgJHfSP5PJWUZ59+82hX7HKbZSY9GaLTFv0bqG82fyfyFL/n6WHL+0cvOeQYnHNve7Wt5y0YnzZWLPxqLP3cbxSys3x4JVm62K0M0IVgAAmnH/xyfF9O88ExERJx05PH731w3Jn6U7RO4PzY0/MN/65NKYfeZxcdaEqo6/IAAA0CflBiklBye7FfPwWfJ3nD+s3Fx0pUZHPNzWUbrRrWS/L1ZF6D4EKwAAzagaNjj7es554+OVjTXZZcLa2ui+GI0/MF9634J4ZOGaOGrkvn4gBgAA2qQxTHl66cZYsHJTpDogOClV4ylLrdSgecWsiqDvZ/kJVgAAipC7TFhbG92X6olF6+LJv6z3AzEAAPQirS3B1ZHN0RurUiL2TMCXowqf7qXYvp9WSmgfwQoAQImSje7LtVRYJiLq04V/IFbyDQAAXae1oKStvUva2xw9ryqFPq21CpfL7l8Q/3DYsDjM748lE6wAALRBbgVLcqmwZNDSUUuHFVvy7ckjAAAon2J7lUS0EnYUWIKrI5uj93TJ36dK+f2q0LHt+V2t1HOX817aKpVKxT3Pr4zLTntzJ1+556vo6hsAAOgNkkHLw5dMzo4veMeYuO3D47Pjk44cHqlUx99DOtNQ4ZLONPRo+egdz8XsuYti2Yaajr8YAAD0Yss21MTsuYvikz9+Ma54YEFc+cAf45M/fjFmfH9+nPK1efG93/4tfvmH1+KJxevzfg7P5IQhyXFPzjuSv770S6Xy3ivX7zgRTX+fSo5zL5u8r0LHFvpdLXm+D4wb1eZzlzou07czTyaTiVVvbO+EK/U+KlYAAMogN2iZ9Z4j87YlK1zK9WRSSz1aLBUGAAD5WqpCSaczzf+s3sualSR/J+mXSkU6s+ezX/COMTHp8GFxwQ9eiIiIGZMPizPfNjr7O01rv+OUWqnRL5WKTGSylTfJ36eS4wcunhTTv/NMs/dV6NhCv6slz3flGUfHAy++1qZzlzrO/VzlWhUhlUrFIfvv1QFn6ns6pWLllltuicMOOywGDRoUEydOjPnz57e473//93/HO97xjth///1j//33jylTpjTZ/yMf+UikUqm8r9NOO63cHwMAoMPkBi8PXDwp+7ojn0pq7NGSiYalwh5a8Frc+uTSeNdX58W0W55SzQIAQJ+RW4Eye+6i+N1f12fHrVWh9K74ZI+KVLRa2TFj8mHx8P/bU4U/6z1HxqSxw/PGub/TRLT8O06plRozJh8WD+WsAFBI1bDBrd5XqZIPybX3fG2V+7nKtSpCJpOJcywh3SZlr1i55557YtasWTFnzpyYOHFi3HTTTTF16tRYvHhxHHjggU32nzdvXvzLv/xLnHjiiTFo0KCYPXt2nHrqqfGnP/0pRo8end3vtNNOi+9///vZcWVlZbk/CgBAWeT+wHzD9GPjqgcXlmVd5NxzvrRycyxYtVk/FgAAeqVi+6C01vekt6mIiPTu1x+dPKakyo5SJcOO1s7d0dfurUpZFaFQhUtjVdDsM4/TuL6Nyh6sfP3rX48LL7wwZsyYERERc+bMiYceeihuv/32uPzyy5vsf9ddd+WN/+d//ifuv//+eOyxx+L888/Pvl9ZWRkjR44s780DAHSy6eNGx9sO3a/oH4jbozFoufS+BfHIwjVx1Mh9LRMGAECPVNRSXgUaxneF1n6+b2/z8+RyXuef+Ka44+lXIkJ40Rsl+37mBi3NLeV23sQ3CVXaoazBys6dO+OFF16IK664IvteRUVFTJkyJZ555pmizrFt27aoq6uLYcOG5b0/b968OPDAA2P//fePd7/73XHDDTfEAQcc0KH3DwDQFUr5gTgZvLSVfiwAAPQkbQlSOkOpYUfy5/sPjBuV7eGR3FbqONkfZOa7j8gGK/R+rVW4zHrPkTF4oPbr7VHW796GDRuivr4+DjrooLz3DzrooFi0aFFR57jsssti1KhRMWXKlOx7p512WnzgAx+IMWPGxNKlS+PKK6+M008/PZ555pno169fk3PU1tZGbW1tdlxdXd3GTwQA0PlKKflua0VLYz+WiIZ+LBWphkaGghYAADpKbhhyyP57xYljD4inl24sefz00o2xYOWmSHWDpbwKBSWFwo7kz/flbI4OdJxuHUv913/9V9x9990xb968GDRoUPb9c889N/v6LW95Sxx33HExduzYmDdvXpxyyilNznPjjTfGtdde2yn3DADQ2XKDl47q0ZLORPYXU0ELAADt9ZPnV8bl9y9ots9JRBQ9zn2QqCtaoiSDlEJBibADeqeyBivDhw+Pfv36xdq1a/PeX7t2bcH+KF/96lfjv/7rv+I3v/lNHHfcca3ue/jhh8fw4cNjyZIlzQYrV1xxRcyaNSs7rq6ujqoqDVoBgN6nUI+WthK0AABQqsYKlUVrtsS8ResawogCfU4KjTsjS0mGJ7nLcxUKUoC+oazBysCBA2P8+PHx2GOPxbRp0yIiIp1Ox2OPPRYzZ85s8bgvf/nL8Z//+Z/xq1/9KiZMmFDwOqtWrYqNGzfGwQcf3Oz2ysrKqKysbNNnAADoaVrr0dLWpcKSBC0AAH1Tcjmv3J/3Wup7Ut8dusTnKNT3JBmetLY8F9A3lX0psFmzZsWHP/zhmDBhQpxwwglx0003RU1NTcyYMSMiIs4///wYPXp03HjjjRERMXv27Lj66qvjRz/6URx22GGxZs2aiIjYZ599Yp999omtW7fGtddeG2eeeWaMHDkyli5dGp/73OfiiCOOiKlTp5b74wAA9Di5QcsDF0+K6d95JiI6LmSJaD5oiWhYruH4qqExaexwIQsAQA/QWh+U3LAkk8nkPVjz+ra6btP3JKlQHxRVKECpyh6snHPOObF+/fq4+uqrY82aNXH88cfH3Llzsw3tV6xYERUVFdn9v/vd78bOnTvjgx/8YN55rrnmmvjiF78Y/fr1iwULFsQPfvCD2LRpU4waNSpOPfXUuP7661WlAAAUUDVscPZ1R/VjaU7uOV9auTkWrNqsmgUAoBsoJTjJ7XPSbFiS82BNclNXam8fFIBCOqV5/cyZM1tc+mvevHl54+XLl7d6rr322it+9atfddCdAQD0XeXqx9KcxqDFsmEAQE/RWgDR2T+7FLqX1sb7VPaLVKRiS+2u0oOT3brZSl5NJO9fBQpQbp0SrAAA0D211o+lXEGL/iwAQHfUUn+QZAARUdzPLq2FIblhR6FgpNC9tDbOC0tydYPgJLksbanjiohI73790cljBClApxKsAACQJWgBAHqzlsKOp5duLKo/SDaAKPCzS7GVIand/1NUMFIgDCk07m6SfU5KHZ9/4pvijqdfiQhBCtD5BCsAALRI0AIA9GTFVKHkVkK05eea5M8ueZUVBcKQTOzZuacFI6Xql0pFJjLZz1Woz0mh8cx3H5ENVgA6m2AFAICiCVoAgO6k2Ebs6XSmxbCjo/OLXpaHtFmhvicAPZlgBQCANmstaEmug91RWgpabn1yacw+87g4a0JVGa4KAHQHxfZBaW0JLYqX/HmuXyoV6cyekCr5YI2+J0BfIVgBAKDD5AYtD1w8KaZ/55mIKF81S0R+0HLpfQvixRWb4sKTDle9AgDt0FGN19s7zr1WsRUovW0JrXIqFJwk+5okq06SD9boewL0FYIVAADKomrY4Ozrzlo2LCLix/NXxI/nr7BMGACUoC2VIIUar7d3nFd1kqsLKlDKVYnbFsl7KTTOVWpwUqjPSUT+gzX6ngB9hWAFAIBO0Vn9WRpP0Vo/luSTsYIXAHqb1ipO2tqLpD2N19s77mzJYCcZQJT6s0trYUehYKRQGFJo/IFxo+KBF1+LiLYFJwA0JVgBAKBLdEbQ0lw/luSTsc0FL4IWAHqC3PCkpSWzkhUnEa1UhfSxXiTJAKOU/iCFfnYpFIbkhh2FgpFSw5Dk+Mozjs5eS3AC0DEEKwAAdAudFrQkXyeCF0ELAN1Fa1UnLVaZ5CpQcdLVVSGdrVDYUWp/kNZ+dikUhrQWdqgiAej+BCsAAHRLnbV0WK7mKlySQUuyYa/QBYCWlLIcV2vBSWt9TvpalUlrCi2hVSjsaG9/kNyfXYQhAL2bYAUAgB6htaClXJJBS+6ETSoiKipUtwD0NcWGJU8v3RgLVm6KVHubtheoOunL2tuIHQDaSrACAECPlBu0VKQ6Z6Ipk3hdn7aMGEBP19Ym7631LskN4pMFJd29aXtz2tN4vb3jXKVWoAhSACgXwQoAAD3e/R+fFNO/80xElG+ZsEKKWUasuQk7wQtA+bUUnpRSVVJKFUk3zEZK0pGN19s7zr2WChQAugvBCgAAPV7VsMHZ14X6sbT2JGxHai5oSU7YqXABKI/cIKWlKpP2VJX0NIWqQkqtBGlP4/VSx61dCwC6imAFAIBep7V+LMknYTurwiV3Ui6dmMnLrXC59cmlMfvM4+KsCVXlvSGAHqSty3Wl05kWq0x6eFbSqkIVJ3qRAED7CFYAAOj1coOW5GRRoQqXzpJb4XLpfQvikYVr4qAhlZGKVGyp3aWaBej1csOTfSr7Zf/+K7avSaHlunq6QlUmpSyZpRcJALSPYAUAgD6vtQqXrgpaHl+0Lvs6FREVFZYNA3q21qpOWqwyyVWgr0l3X66r1KbthapOkuGJJbMAoPMIVgAAIKG1oCX3ieDOCl0yEVGfbrpsWDJoSS6NI3gBOlOxwUmy6qQnV5kUCkcqIiK9+3WpTdtLrToBADqPYAUAAArIDVpynwjuquqW3GXDGoOW5NI4zQUvghagkGQ4kvv3RjmCk+5WZdLeKpLk+PwT3xR3PP1KRLS/iTsA0H0IVgAAoB1KWUYsOUHXUXInJrOvMypcgLY3fc9kMnl/b7y+rS4WrNwUqRL7mnS34CSifVUlpVaRzHz3EdlgBQDoPQQrAADQgVoLWpITdN2pwiV2j4+vGhqTxg4XskA31lKT91KqSCKKCEdy/t5IbmrUHYOTpEJVJu2pKgEA+ibBCgAAlFFu0JKckEsGL+WqaElqtsJlt5dWbo4FqzarboEu1JYm76nd/9OWKpKeEI7kKnW5rkJVJqpKAIBSCVYAAKAL5QYvN0w/Nq56cGGXT3I2Xl//FugcuUFKW3uVZLL/0/OCkkJK7WtSKEgBAGgvwQoAAHQT08eNjrcdul92MvAD40bFAy++FhGdt2xYkv4tULq29jXJrUDpCb1K2qNQlUnu33+l9jURpAAA5SZYAQCAbiS3guXKM47OTiwmlw1LBi2dtYxYUjH9W1S40Bc0hilPL93YYpP35Li1CpSerlBwUqjKJPfvP0EJANDdCFYAAKCHyA1dkkFLcpKyO1e4RDRMLB9fNTQmjR2uuoWyKbbJe3vHjVUnEXv+3Bdq8t7TK1DaG5yoMgEAejLBCgAA9FC5QUtyUrJbV7js9tLKzfGHlZsLVreUMsGdnDwX0vQuySW2kv9+W+pV0lqT94jWq0oKjfOqTrq5Upu+J//eqIiI9O5tghMAoC8TrAAAQC9VSoVLVwUtjddsqbqlrRPcqYioqLAEWXfX1l4kmUymSQhXbK+S1pq8t3fc1UqtIikUjiT/3jj/xDfFHU+/EhGCEwCgbxOsAABAH9FahcsDF0+K6d95JiK6Z3VLqRPcmYioT+eHNMVUwwhemiol/Chl3O5eJDkhXN6f0T7WqyS3yXt7q0iaC0dy/96Y+e4jssEKAEBfJlgBAACiatjg7Ovu2r+lPdKZKFgNU2rwUmhZqu6stbAkdzm1ZJVIe5bMyh3nhgUd0YukB/1RLKgjm7yrIgEAKA/BCgAA0ERP7N9SimarYUoIXl7fVpdXbdHe3jCl9o7piEbrzYUlLfYLSaQf7V0yq7v/+ehIpfY10asEAKD7E6wAAAAlK6V/S4+tcEm+zgleIv+tdvWGKTRO9o5pT+P1ZpfUauYz0z6tNXkvdbkuAAC6H8EKAADQbqVUuOQ+sd8TqltK1Z7eMEVVenRQ4/W+rFAVSanjZNVJKU3eBSkAAD1PRVffAAAA0PvlBi8PXDwp+/qCd4yJ2z48Pjs+6cjh2eW1InZXaETxY2jUL5XK+/PxgXGjsq+Tf+7aO54x+bB4+P9Nzo5nvvuIjvoYAAB0Q4IVAACgU1UNG5x9Pes9R8akscOz4znnjY+HL9kzQV3qBHfu5HkypKF7KxSaJYOS5L/f5PZk2HHlGUdnXyf/3HXEODc8BACgdxOsAAAA3UpyWbFSJrhzJ8+TIU2hahgKK7WCqNA49xfSUqtCkv9+k9uFHQAAlItgBQAA6LVyJ9YLVcP01eCltc+ZrALp6CW0zj/xTdnXbakKSYZwghQAADqDYAUAAOgzWquGKTV4yf1lqr29YUrpHdPecxUKS3KXU2uuCqQjl9DSiwQAgJ5IsAIAALBbKcFLbrVFe3vDlNI7pqMbrbe2nJoqEAAAaKp/V98AAABAT5EbMsx89xFxx9OvNLtt1nuOzDuuveMrzzg6HnjxtbKcGwCA9stkMpHJ7BnXpzORyXlj56503v476urzxtt35o+31e4Zb9lRl7dt8/bEeFv++I2a/PHrW3dGzq1F9Y66GDxQNNAevnsAAAAAAGWSO7meTmfyJrh31afzxnW79owKTbzX1O7KGxeafK/etmf/TTV1eddNTrxv2LIzcu90XXVt3rnWbN6RN35t0468z/nqG3u2r9y4PW/fVzZsyxsv21CTN166viYi59pL1m3Nu7e/rt2ad29/WbM1+/rl1dV54cafX8sf/3HV5rxr/WHlprzxiys25V3796+8kXftF1/Zs//8Za/nnXv+sjfyzvX88vxxw7lzr51/LwsS9/bn16pzXm/J27ZodWK8Jn/8l7X547+u25o3Xr+lNkYO2StoO8EKAAAAAL1O7iRvRNMJ7eTT5HX1LT9ZXrurPm8CtbkJ79yzJye8tybHO/aMCz15vnlbXd61Cz2JvmHLzrztueP11bV5+67dXHiyPNerb+RPkK96PX/86ut79l+xcVvefS9vZjI9914aJtP3WJKYCP7ruq2589152xev2ZJ3reYm13P96dXqvH9ff1y1Oe9e/rByU2K8Z8L7xRVv5J37hVfyx88tez3v2Gf/9nretZ9LTLa/kDNR33jt5q4b0XTifeGr+Z+r0OR77mT74gIT70vX54+T4ccrG/P/fa58PX+8etOePxuvbc7/c7KmOv/PVTK02bAlf7xxa/6f6ddr8sfVOf8NVW9Phk35422JcGpHXf5/68n/9nP/Xoho+HujUeKvGPoYwQoAAADdTnJCtLkJ0uQ4OWGaa1fOxMiu+uSkSeuTKs1NsCbHubdXmzNJk5x8Lbjsx87kBNCuvHMnJ2trcpYJ2Vq7K+/7lHxyubrQMiLb6/ImLZOTu8knnXMlJ3rfqKnLu5fXE5NiyUmyQhPBuZITw+uqa/O+R2s31+ZNmK7ZvCNv++rERPHqnInlQpPGyXHyKewVyYnGnO3NTSrn+luBJ7aXrt+a9zmST3AvXbfn+OTT3IvXtD7Z+vLq5ORs03FLk9QLX92cty058Zt8GvyllZvy9m/u6fBcuU94J5/+LjSBnXx6PDmhnTzfH3KulXyy/KUVyc9V2oT3nxLj3H8HhZ48L/VJ9OSE+PKcP1vJP2fLN5Y2Wb4q8d/Iq5vyx6tzJtBXJ0Kate2dTE+Mc/8e2pT8+6rA5Hoy6Co02V6X8/8DO3e1/P8vERFpk+3QJwhWAADIKrRMQa5CawTnTiwW8xRn7rWbnfxrZbJvc82e8yUn8wpN3q3fUuKEXc4kQHOTdbnHJpdEKHWCLnd7crIuuYRC2ybscvfflrMtf0Im+cRok+UYkk+Urs0fJyeAkk+Y5ko+cVpo8i/5RGru/s1NDOZKTnIlxwtfTU6S5Y9z908uK5GcYCs00Zh8MvalxPbc45OTfU3HyUnJ/Cdpk5OWTZa4yDnfC6+0Pgn5/PI38v6MP7csOanZ+vj5nEnPQhOihSZIC02YvpT3uTblbft9Ylzoe5ycYE2Oc/88JCdfC03G/nFVdavj5GTtyzl/rpN/hpNPLr9caBmREpYVST7pnPzvvNDEb/LvlVImgpPj5N93hSaKVyQmil/NGReaNE6Ok09htzaRXGhSORkgJSeZk///lfz/tzdynuBOPs2dnHRusjxQgUnoJk985wR6ueFeRNOwMDlBXVvq0+E542RgagIbgK4iWAEAuo1ks7+6+nSLTwAnn+jdsiN/jeDmmvflTv41t2Zw7rXWJJ5ezd3W3BrBudduOoGd/4RpctI5d1xoTeDkU6HNrwm8R5OnPnMmD9u7TEGhNYJzJxZLfYqz4OTfmuSE3Z5xa5P4EU0n7/62vrQJu5U5E3SFJuuST3mWOkGXuxxHcrIuuYRCeyfsNuaMC03eFXqCNDmhl3ySvbUnTEud/EuOc5dWKTQx2GRZllYqAZob504eJp90TU4sFppoLDjxWJf7pGyh6opMq+PkpGVrk5jJp3CTk5qFJjmTS2RYMgMAgN5AsAIA3VAyYNi5K50XAmzfWR/pxNP9yXWXkyFCo+TyGMkn5pMhQXIZitaWlkiuVZx8Ajv51HRyYj/5NHLyCeLcifrkE7xN1hMusGRCoTWDV7Xy9GqhNYKbTmC3PumcGwIVemI0ObHbnjWBPeUJAAAApROsANCrpdOZvABiR13+GujJKodNOcsJrd9Sm7f0UHJJn2QzxmRVQnI5m2TokPsEf7LhYTJgSFYGJJ/+Tz7dnwwRcpfTSC6PkXxiPhkSJJ9qT4YCW3KCgOTT3k0n/S3fAAAAAPRsghUA2i3Zh2FHXX41RbI3woYtO/MCimRg8cqGbZHOa9S5JwhILpO0YNXmvGu98Mobec1sk0sZJZcqSlY5LMlZTii5PFBySZ/ksjzJqoTkcjbJ0CF3WZfkUisAAAAAdE+CFYAeLjeQyF0CaGvtrrzA4fWtO6M+EWbkBhDLE2HGX9ZuiXROscEfEwFGbgVFofAi2RshuQRTMrBIVky8kbN2f3KZpOSa9QIKAAAAAMpJsAJQBrlhR27z2c3b6yKTE1asq67NCyuSlRrJcCNZnfHcstfzllJakBNoJBtB/3Vd62FGsulxstFwsilvvQADAAAAgD5IsAL0ebW76vPCi001dXnhRbKyY+n6rXn7L3x1c14z6PnLXs9bqiq32XayciPZLLtJpUYi3EhWZ+hPAQAAAACdS7AC9Bi54UZN7a7YlTNeX12bt8zVsg01eeHIn1+rzgs/fp+zdNVLK/KXrVqcaPqdrOxI9tGoqc0POzLCDgAAAADotQQrQKfZUVefF25s2LIzb/zKxj0BRjIISVaBLEwsc/W3ROXHuuravPGWHfl9OVR6AAAAAABtIVgBilZXn84LOzZu3ZnXKHzp+pq8qpKXVm7K2z/Z0DzZwHx9ThiSDEJUgQAAAAAA3YFgBfqg3PBj87a6vCW1XtmwLXbldFfP7Q/y+1c25Z1nSaIZ+oYt+VUiuU3bAQAAAAB6A8EK9AK76vcEGG/U1OWNl67fmldV8vzyN/KqSBatye8nkmyeLhwBAAAAANhDsALdVG44snHrzqjLGedWijy37PW8fiF/STReTzZar9dcBAAAAACgzQQr0AW27dwVdbv2BBzLN2zLC06SYUlyya1NNXXZ13ISAAAAAIDOI1iBDrRz155wZF31nkqRl1dX523746rqvOPWJpbfEpYAAAAAAHRPghUoUjqdidqccGTV69ujtpUqkxUba7Kvq7fv6pR7BAAAAACgvAQrsFsmkx+crNy4PWrr67Pj55a/kbf/q5u2541VmQAAAAAA9H6CFfqUdE76sXrTjrwg5bnlb0QmJxx5bXN+cAIAAAAAAIIVerV11bWxfeeeqpMXV2zKvl7x+ra8fTMqTgAAAAAAKECwQo9Wu6s+duzcU3Xy59eqY3vdniBl2YaavP2FJwAAAAAAtIdghR5lXXVt1Ozc0wj+pRWb87Zv2aFJPAAAAAAA5SNYodvZVb+nAmXJuq2xbWfLFSgAAAAAANCZBCt0uZraPcHJglWb83qibNy6sytuCQAAAAAAmiVYodNt3laXt2TXy69VZ1/nhioAAAAAANDdCFYou83b66J6254gZdGaLV14NwAAAAAA0HaCFTpc7a762JwbpKwWpAAAAAAA0DsIVugQtbv2LOH10orNXXgnAAAAAABQPoIV2u3l1dVRvX1X4R0BAAAAAKCHE6xQsp270rGuujY7FqoAAAAAANBXCFYo2R9Wbop0pqvvAgAAAAAAOp9ghYK27KiLNZv3VKgIVQAAAAAA6KsEKxT059e2dPUtAAAAAABAt1DRGRe55ZZb4rDDDotBgwbFxIkTY/78+a3uf++998ab3/zmGDRoULzlLW+Jhx9+OG97JpOJq6++Og4++ODYa6+9YsqUKfHXv/61nB+hz3lt046uvgUAAAAAAOh2yh6s3HPPPTFr1qy45ppr4ve//3289a1vjalTp8a6deua3f/pp5+Of/mXf4kLLrggXnzxxZg2bVpMmzYtFi5cmN3ny1/+cnzzm9+MOXPmxLPPPht77713TJ06NXbsEAZ0lIzlvgAAAAAAoImyLwX29a9/PS688MKYMWNGRETMmTMnHnroobj99tvj8ssvb7L/zTffHKeddlpceumlERFx/fXXx6OPPhrf/va3Y86cOZHJZOKmm26KL3zhC/H+978/IiLuvPPOOOigg+LBBx+Mc889t+h727ZzV/TfuasDPmXvsC3ne7Gjrj77ujbndVnGu1yrW53btVzLtVyrO53btVzLtVyrO53btVzLtVyrO53btVzLtVyrO53btXrUtXbU1efNBdOglO9JKpMpX23Czp07Y/DgwXHffffFtGnTsu9/+MMfjk2bNsXPfvazJscceuihMWvWrPjUpz6Vfe+aa66JBx98MP7whz/E3/72txg7dmy8+OKLcfzxx2f3eec73xnHH3983HzzzU3OWVtbG7W1e5qvV1dXR1VVVVR96idRUTm4Qz4rAAAAAADQM6Vrt8XKm86OzZs3x5AhQ1rdt6xLgW3YsCHq6+vjoIMOynv/oIMOijVr1jR7zJo1a1rdv/GfpZzzxhtvjKFDh2a/qqqq2vR5AAAAAACAvq3sS4F1B1dccUXMmjUrO26sWJn/+VMKJk991arXt8erm7Z39W0AAAAAANCBhu87MMaO2Kerb6Pbqa6ujoNvKm7fsgYrw4cPj379+sXatWvz3l+7dm2MHDmy2WNGjhzZ6v6N/1y7dm0cfPDBefvkLg2Wq7KyMiorK5u8P3hg/xg8sE9kSyXba2C/GDSgX1ffBgAAAAAAHWivAf3MizdjVwnfk7IuBTZw4MAYP358PPbYY9n30ul0PPbYYzFp0qRmj5k0aVLe/hERjz76aHb/MWPGxMiRI/P2qa6ujmeffbbFcwIAAAAAAHSEssdSs2bNig9/+MMxYcKEOOGEE+Kmm26KmpqamDFjRkREnH/++TF69Oi48cYbIyLi//2//xfvfOc742tf+1qcccYZcffdd8fzzz8f3/ve9yIiIpVKxac+9am44YYb4u/+7u9izJgxcdVVV8WoUaNi2rRp5f44fcaQvQbE4JqdsW1nfVffCgAAAAAAdBtlD1bOOeecWL9+fVx99dWxZs2aOP7442Pu3LnZ5vMrVqyIioo9hTMnnnhi/OhHP4ovfOELceWVV8bf/d3fxYMPPhjHHntsdp/Pfe5zUVNTExdddFFs2rQpJk+eHHPnzo1BgwaV++P0GUP3GhBvrdovXq/ZGa9t2h5bduzq6lsCAAAAAIAul8pkMpmuvonOVl1dHUOHDo3NmzdrXl+k6h118dqm7fFGTV1X3woAAAAAAG00Yt+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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot ACF and PACF\n",
        "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 8))\n",
        "plot_acf(t_kWh, lags=700, ax=ax1)\n",
        "plot_pacf(t_kWh, lags=700, ax=ax2)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 699
        },
        "id": "2XWBl4KMYv_m",
        "outputId": "85507df2-a437-44ea-913d-8b65df7ff774"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "If you observe strong values in the ACF plot for the first 150 lags and strong values in the PACF plot for about 15 lags, it suggests that your time series may have a seasonal component. To fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model in this scenario, you'll need to specify both the non-seasonal and seasonal orders."
      ],
      "metadata": {
        "id": "YkNkN1mscKBv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "xO_ThvTZYwCS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from pyspark.sql.functions import to_date\n",
        "\n",
        "df  = spark.read.csv(\"SM Cleaned Data BR Aggregated.csv\", header=True, inferSchema=True)\n"
      ],
      "metadata": {
        "id": "N6zmN3TPYwFm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pxyzMQmrh2Xb",
        "outputId": "17e84111-cc6d-4357-a982-c5e837b4e1c8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+-----+----------+------------------+\n",
            "|meter|      Date|             t_kWh|\n",
            "+-----+----------+------------------+\n",
            "| BR02|2019-07-10| 6.959999999999997|\n",
            "| BR02|2019-07-11| 4.910999999999991|\n",
            "| BR02|2019-07-13| 5.872999999999988|\n",
            "| BR02|2019-07-14| 5.457999999999984|\n",
            "| BR02|2019-07-15| 4.859999999999995|\n",
            "| BR02|2019-07-16| 4.281999999999985|\n",
            "| BR02|2019-07-17| 4.421999999999985|\n",
            "| BR02|2019-07-18|  4.33699999999998|\n",
            "| BR02|2019-07-19| 5.441999999999984|\n",
            "| BR02|2019-07-20| 5.650999999999988|\n",
            "| BR02|2019-07-30| 5.847999999999994|\n",
            "| BR02|2019-07-31|5.8319999999999865|\n",
            "| BR02|2019-08-01| 5.006999999999988|\n",
            "| BR02|2019-08-04| 7.383999999999983|\n",
            "| BR02|2019-08-05| 6.977999999999994|\n",
            "| BR02|2019-08-06|5.2839999999999945|\n",
            "| BR02|2019-08-07| 5.651999999999995|\n",
            "| BR02|2019-08-08|4.7749999999999835|\n",
            "| BR02|2019-08-09| 5.005999999999984|\n",
            "| BR02|2019-08-10|5.8899999999999775|\n",
            "+-----+----------+------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df=df['Date', 't_kWh']\n"
      ],
      "metadata": {
        "id": "_48FI8abhSQo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zJcfW5t1iIcM",
        "outputId": "663f1acf-bcf2-4cf0-816b-b395b0d6cca3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------------------+\n",
            "|      Date|             t_kWh|\n",
            "+----------+------------------+\n",
            "|2019-07-10| 6.959999999999997|\n",
            "|2019-07-11| 4.910999999999991|\n",
            "|2019-07-13| 5.872999999999988|\n",
            "|2019-07-14| 5.457999999999984|\n",
            "|2019-07-15| 4.859999999999995|\n",
            "|2019-07-16| 4.281999999999985|\n",
            "|2019-07-17| 4.421999999999985|\n",
            "|2019-07-18|  4.33699999999998|\n",
            "|2019-07-19| 5.441999999999984|\n",
            "|2019-07-20| 5.650999999999988|\n",
            "|2019-07-30| 5.847999999999994|\n",
            "|2019-07-31|5.8319999999999865|\n",
            "|2019-08-01| 5.006999999999988|\n",
            "|2019-08-04| 7.383999999999983|\n",
            "|2019-08-05| 6.977999999999994|\n",
            "|2019-08-06|5.2839999999999945|\n",
            "|2019-08-07| 5.651999999999995|\n",
            "|2019-08-08|4.7749999999999835|\n",
            "|2019-08-09| 5.005999999999984|\n",
            "|2019-08-10|5.8899999999999775|\n",
            "+----------+------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.printSchema()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z6b3mggyjraf",
        "outputId": "3b1f2b34-d604-4f87-ece3-1ff7f1c4efde"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "root\n",
            " |-- Date: date (nullable = true)\n",
            " |-- t_kWh: double (nullable = true)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.summary().show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e7WzNk1Xjvxq",
        "outputId": "122b60d6-c28d-4add-b7cf-5000ceb9b288"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+-------+------------------+\n",
            "|summary|             t_kWh|\n",
            "+-------+------------------+\n",
            "|  count|             28119|\n",
            "|   mean|  8.20758266652449|\n",
            "| stddev| 7.719020205928047|\n",
            "|    min|               0.0|\n",
            "|    25%| 2.920999999999982|\n",
            "|    50%| 6.015999999999985|\n",
            "|    75%|11.022000000000007|\n",
            "|    max| 82.62199999999989|\n",
            "+-------+------------------+\n",
            "\n",
            "+-------+------------------+\n",
            "|summary|             t_kWh|\n",
            "+-------+------------------+\n",
            "|  count|             28119|\n",
            "|   mean|  8.20758266652449|\n",
            "| stddev| 7.719020205928047|\n",
            "|    min|               0.0|\n",
            "|    25%| 2.920999999999982|\n",
            "|    50%| 6.015999999999985|\n",
            "|    75%|11.022000000000007|\n",
            "|    max| 82.62199999999989|\n",
            "+-------+------------------+\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PandasDF = df.toPandas()"
      ],
      "metadata": {
        "id": "gIlQa3uTiG6p"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "xCq-YR2ZW_H_"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}