PORTFOLIO PROJECT 4. ENERGY CONSUMPTION FORECASTING.ipynb

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   "source": [
    "# Energy Consumption Forecasting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34e51432-e286-42a5-94fc-7d5d6db84d00",
   "metadata": {},
   "source": [
    "### Data Source: Kaggle"
   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
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   "id": "0cad58cd-de47-4fbd-a1e4-27bb4b5e59d1",
   "metadata": {},
   "source": [
    "This dataset contains hourly estimated energy consumption in megawatts (MW) from 2019 to 2024 for the east region in the United States.\n",
    "\n",
    "Project Goal\n",
    "\n",
    "1. Timeseries forecasting using XGBoost model.\n",
    "   \n",
    "3. Create a model with at least 90% Prediction Accuracy."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0230f2d0-8d46-47a4-9e85-76cc82ba4f97",
   "metadata": {},
   "source": [
    "## Importing Libraries"
   ]
  },
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   "source": [
    "# Data Structure\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Plotting\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Sklearn\n",
    "from sklearn.metrics import mean_squared_error, r2_score,mean_absolute_error\n",
    "from xgboost import XGBRegressor\n",
    "from xgboost import plot_importance, plot_tree\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "\n",
    "# Others\n",
    "color_pal = sns.color_palette()\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e06e2648-65c2-4fe2-ae66-1dcb22762fc6",
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   "source": []
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   "cell_type": "markdown",
   "id": "83e7e327-9cca-4529-8417-f8a72a75b0c2",
   "metadata": {},
   "source": [
    "## Loading The Dataset"
   ]
  },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DateTime</th>\n",
       "      <th>Consumption</th>\n",
       "      <th>Production</th>\n",
       "      <th>Nuclear</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Hydroelectric</th>\n",
       "      <th>Oil and Gas</th>\n",
       "      <th>Coal</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Biomass</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-01 00:00:00</td>\n",
       "      <td>6352</td>\n",
       "      <td>6527</td>\n",
       "      <td>1395</td>\n",
       "      <td>79</td>\n",
       "      <td>1383</td>\n",
       "      <td>1896</td>\n",
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       "      <td>1393</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <th>3</th>\n",
       "      <td>2019-01-01 03:00:00</td>\n",
       "      <td>5682</td>\n",
       "      <td>5603</td>\n",
       "      <td>1397</td>\n",
       "      <td>191</td>\n",
       "      <td>972</td>\n",
       "      <td>1455</td>\n",
       "      <td>1558</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-01 04:00:00</td>\n",
       "      <td>5557</td>\n",
       "      <td>5454</td>\n",
       "      <td>1393</td>\n",
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       "              DateTime  Consumption  Production  Nuclear  Wind  Hydroelectric  \\\n",
       "0  2019-01-01 00:00:00         6352        6527     1395    79           1383   \n",
       "1  2019-01-01 01:00:00         6116        5701     1393    96           1112   \n",
       "2  2019-01-01 02:00:00         5873        5676     1393   142           1030   \n",
       "3  2019-01-01 03:00:00         5682        5603     1397   191            972   \n",
       "4  2019-01-01 04:00:00         5557        5454     1393   159            960   \n",
       "\n",
       "   Oil and Gas  Coal  Solar  Biomass  \n",
       "0         1896  1744      0       30  \n",
       "1         1429  1641      0       30  \n",
       "2         1465  1616      0       30  \n",
       "3         1455  1558      0       30  \n",
       "4         1454  1458      0       30  "
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   "source": [
    "df = pd.read_csv(r\"C:\\Users\\Henry Oguns\\Desktop\\New folder\\electricityConsumptionAndProductioction.csv\")\n",
    "df.head()"
   ]
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   "execution_count": 120,
   "id": "e003046f-b669-4699-8eca-ee0336092077",
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     "data": {
      "text/plain": [
       "(46011, 10)"
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     "execution_count": 120,
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   "source": [
    "df.shape"
   ]
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   "id": "d0a07897-a20c-406e-850d-414439eacbd4",
   "metadata": {},
   "source": [
    "The dataset contains 46,011 oservations and 10 Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "6edfe710-1279-405d-8594-2226897e43c3",
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 46011 entries, 0 to 46010\n",
      "Data columns (total 10 columns):\n",
      " #   Column         Non-Null Count  Dtype \n",
      "---  ------         --------------  ----- \n",
      " 0   DateTime       46011 non-null  object\n",
      " 1   Consumption    46011 non-null  int64 \n",
      " 2   Production     46011 non-null  int64 \n",
      " 3   Nuclear        46011 non-null  int64 \n",
      " 4   Wind           46011 non-null  int64 \n",
      " 5   Hydroelectric  46011 non-null  int64 \n",
      " 6   Oil and Gas    46011 non-null  int64 \n",
      " 7   Coal           46011 non-null  int64 \n",
      " 8   Solar          46011 non-null  int64 \n",
      " 9   Biomass        46011 non-null  int64 \n",
      "dtypes: int64(9), object(1)\n",
      "memory usage: 3.5+ MB\n"
     ]
    }
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   "source": [
    "# Understandin the data type of each columns\n",
    "\n",
    "df.info()"
   ]
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       "                     Consumption  Production  Nuclear  Wind  Hydroelectric  \\\n",
       "DateTime                                                                     \n",
       "2019-01-01 00:00:00         6352        6527     1395    79           1383   \n",
       "2019-01-01 01:00:00         6116        5701     1393    96           1112   \n",
       "2019-01-01 02:00:00         5873        5676     1393   142           1030   \n",
       "2019-01-01 03:00:00         5682        5603     1397   191            972   \n",
       "2019-01-01 04:00:00         5557        5454     1393   159            960   \n",
       "\n",
       "                     Oil and Gas  Coal  Solar  Biomass  \n",
       "DateTime                                                \n",
       "2019-01-01 00:00:00         1896  1744      0       30  \n",
       "2019-01-01 01:00:00         1429  1641      0       30  \n",
       "2019-01-01 02:00:00         1465  1616      0       30  \n",
       "2019-01-01 03:00:00         1455  1558      0       30  \n",
       "2019-01-01 04:00:00         1454  1458      0       30  "
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Changing the Datetime column to a date time data type and making it the index of the dataset\n",
    "\n",
    "df = df.set_index(\"DateTime\")\n",
    "df.index = pd.to_datetime(df.index)\n",
    "df.head()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 123,
   "id": "6cbc740f-2141-4a26-a5b2-c8cd0b497406",
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    {
     "data": {
      "text/plain": [
       "Index(['load', 'Production', 'Nuclear', 'Wind', 'Hydroelectric', 'Oil and Gas',\n",
       "       'Coal', 'Solar', 'Biomass'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Renaming the consumption column as load.\n",
    "\n",
    "df.rename(columns = {'Consumption':'load'}, inplace = True)\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "8efe8317-02b0-4f2a-a858-930525f4a7e0",
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       "                     load\n",
       "DateTime                 \n",
       "2019-01-01 00:00:00  6352\n",
       "2019-01-01 01:00:00  6116\n",
       "2019-01-01 02:00:00  5873\n",
       "2019-01-01 03:00:00  5682\n",
       "2019-01-01 04:00:00  5557"
      ]
     },
     "execution_count": 124,
     "metadata": {},
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   ],
   "source": [
    "# Making a dataframe of the timeseries index and load column\n",
    "\n",
    "df = df[['load']]\n",
    "df.head()"
   ]
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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(style = \".\", figsize=(15,5), color = color_pal[0], title = \"PJME Energy Use\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37416e82-749b-40ae-8e69-39895a3f552a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "572a80ec-3eea-4afd-b9f9-5c9799049c3c",
   "metadata": {},
   "source": [
    "## Training/ Test Samples Splits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "cb4faa2e-485f-4662-87ae-5ed6e42a3c58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "split_date = '01-01-2023'\n",
    "train = df.loc[df.index <= split_date].copy()\n",
    "test = df.loc[df.index > split_date].copy()\n",
    "\n",
    "test \\\n",
    "    .rename(columns={'load': 'TEST SET'}) \\\n",
    "    .join(train.rename(columns={'load': 'TRAINING SET'}), how='outer') \\\n",
    "    .plot(figsize=(15,5), title=\"Data Train Test Split\", style='.');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f3b4fd6-28da-4435-8eef-6374356281f3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c84af4d-0bf2-4370-aeeb-3649adb3725d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4cafc516-6c7b-4323-9a66-a083e7d1fe36",
   "metadata": {},
   "source": [
    "## Features Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "91a88b92-a70d-449c-b7a2-9f5e92d48e72",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create features from datetime index\n",
    "def create_features(df, label=None):\n",
    "    df['date'] = df.index\n",
    "    df['hour'] = df['date'].dt.hour\n",
    "    df['dayofweek'] = df['date'].dt.dayofweek\n",
    "    df['month'] = df['date'].dt.month\n",
    "    df['quarter'] = df['date'].dt.quarter\n",
    "    df['year'] = df['date'].dt.year\n",
    "    df['dayofyear'] = df['date'].dt.dayofyear\n",
    "    df['dayofmonth'] = df['date'].dt.day\n",
    "    #df['weekofyear'] = df['date'].dt.weekofyear\n",
    "    \n",
    "    X = df[['hour', 'dayofweek','month', 'quarter', 'year', 'dayofyear',\n",
    "            'dayofmonth']]\n",
    "    if label:\n",
    "        y = df[label]\n",
    "        return X, y\n",
    "    return X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "7ce04141-75ed-4f81-b290-36dcb270b5a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, y_train = create_features(train, label='load')\n",
    "X_test, y_test = create_features(test, label='load')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5404b6f-e7d7-40bd-8c0b-182801802509",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "52efc940-ca8e-48a0-8f74-669cebd0928b",
   "metadata": {},
   "source": [
    "## Build XGBoost Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "d1d357b8-7ce9-4831-80d2-2d908ded2ab8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0]\tvalidation_0-rmse:6727.98696\tvalidation_1-rmse:6179.75467\n",
      "[100]\tvalidation_0-rmse:2528.19476\tvalidation_1-rmse:1943.33163\n",
      "[200]\tvalidation_0-rmse:1050.61646\tvalidation_1-rmse:647.43629\n",
      "[300]\tvalidation_0-rmse:583.25853\tvalidation_1-rmse:544.27233\n",
      "[310]\tvalidation_0-rmse:561.59752\tvalidation_1-rmse:551.91624\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-5 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-5 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-5 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-5 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-5 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-5 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-5 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBRegressor(base_score=0.5, booster=&#x27;gbtree&#x27;, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=50,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=0.01, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=3, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=1000, n_jobs=None,\n",
       "             num_parallel_tree=None, objective=&#x27;reg:linear&#x27;, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" checked><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;XGBRegressor<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>XGBRegressor(base_score=0.5, booster=&#x27;gbtree&#x27;, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=50,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=0.01, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=3, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=1000, n_jobs=None,\n",
       "             num_parallel_tree=None, objective=&#x27;reg:linear&#x27;, ...)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "XGBRegressor(base_score=0.5, booster='gbtree', callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=50,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=0.01, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=3, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=1000, n_jobs=None,\n",
       "             num_parallel_tree=None, objective='reg:linear', ...)"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg = XGBRegressor(base_score = 0.5, booster = 'gbtree', \n",
    "                    n_estimators = 1000, early_stopping_rounds = 50,\n",
    "                    objective = 'reg:linear', max_depth = 3,\n",
    "                        learning_rate = 0.01)\n",
    "reg.fit(X_train, y_train,\n",
    "        eval_set = [(X_train, y_train), (X_test, y_test)],\n",
    "        verbose = 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0634ac89-6acd-4a01-8113-039f5f5560ff",
   "metadata": {},
   "source": [
    "## Feature Importances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "a64c7ec7-82ff-494f-b0c0-1a62c3c42e34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_importance(reg, height=0.8);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "419157ee-a72a-494a-aefe-0f02ae319fd9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "27608714-9231-4320-a9b4-31d76c765680",
   "metadata": {},
   "source": [
    "## Forecast on Test Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "ce568282-8d92-453a-ae4e-a9f07193ef32",
   "metadata": {},
   "outputs": [],
   "source": [
    "test['load_Prediction'] = reg.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "9fde625c-1cf4-439a-a4cc-49ccb8767e42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>load</th>\n",
       "      <th>date</th>\n",
       "      <th>hour</th>\n",
       "      <th>dayofweek</th>\n",
       "      <th>month</th>\n",
       "      <th>quarter</th>\n",
       "      <th>year</th>\n",
       "      <th>dayofyear</th>\n",
       "      <th>dayofmonth</th>\n",
       "      <th>load_Prediction</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DateTime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-01 01:00:00</th>\n",
       "      <td>4995</td>\n",
       "      <td>2023-01-01 01:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5107.167480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 02:00:00</th>\n",
       "      <td>4816</td>\n",
       "      <td>2023-01-01 02:00:00</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5032.768555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 03:00:00</th>\n",
       "      <td>4627</td>\n",
       "      <td>2023-01-01 03:00:00</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5032.768555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 04:00:00</th>\n",
       "      <td>4581</td>\n",
       "      <td>2023-01-01 04:00:00</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5032.768555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 05:00:00</th>\n",
       "      <td>4535</td>\n",
       "      <td>2023-01-01 05:00:00</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2023</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5032.768555</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     load                date  hour  dayofweek  month  \\\n",
       "DateTime                                                                \n",
       "2023-01-01 01:00:00  4995 2023-01-01 01:00:00     1          6      1   \n",
       "2023-01-01 02:00:00  4816 2023-01-01 02:00:00     2          6      1   \n",
       "2023-01-01 03:00:00  4627 2023-01-01 03:00:00     3          6      1   \n",
       "2023-01-01 04:00:00  4581 2023-01-01 04:00:00     4          6      1   \n",
       "2023-01-01 05:00:00  4535 2023-01-01 05:00:00     5          6      1   \n",
       "\n",
       "                     quarter  year  dayofyear  dayofmonth  load_Prediction  \n",
       "DateTime                                                                    \n",
       "2023-01-01 01:00:00        1  2023          1           1      5107.167480  \n",
       "2023-01-01 02:00:00        1  2023          1           1      5032.768555  \n",
       "2023-01-01 03:00:00        1  2023          1           1      5032.768555  \n",
       "2023-01-01 04:00:00        1  2023          1           1      5032.768555  \n",
       "2023-01-01 05:00:00        1  2023          1           1      5032.768555  "
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "d25cf3f2-cbc3-4043-9cb8-e98630ceb13f",
   "metadata": {},
   "outputs": [],
   "source": [
    "load_all = pd.concat([test, train], sort = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "b5a68dc9-6afe-4c03-be95-b3805e479851",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(46011, 10)"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "load_all.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "9cb63cac-e29f-47d3-b760-0d45530154a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "load_all[['load', 'load_Prediction']].plot(figsize=(15,5));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6486b8de-5e58-4f03-a630-b4cfdb9b182d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d7025f7b-0f0e-41d4-b549-613bdbb5dd7e",
   "metadata": {},
   "source": [
    "## Check first month of predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "aa639f6a-c88d-4aa8-afd0-d470b8099d7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the forecast with the actuals\n",
    "f, ax = plt.subplots(1)\n",
    "f.set_figheight(5)\n",
    "f.set_figwidth(15)\n",
    "\n",
    "_ = load_all[['load', 'load_Prediction']].plot(ax=ax, style=['_', '.'])\n",
    "ax.set_xbound(lower='01-01-2023', upper='02-01-2023')\n",
    "ax.set_ylim(0, 10000)\n",
    "\n",
    "plot = plt.suptitle('January 2023 Forecast vs Actual')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7863bdc8-1628-454c-9258-9719fe3eb7dc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "cb74ea64-b292-489f-a8b6-e77ec868f0b8",
   "metadata": {},
   "source": [
    "## Check first week of January Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "97bd3150-780c-4aa9-a495-be44a83c89fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the forecast with the actuals\n",
    "f, ax = plt.subplots(1)\n",
    "f.set_figheight(5)\n",
    "f.set_figwidth(15)\n",
    "\n",
    "_ = load_all[['load', 'load_Prediction']].plot(ax=ax, style=['_', '.'])\n",
    "ax.set_xbound(lower='01-01-2023', upper='01-08-2023')\n",
    "ax.set_ylim(0, 10000)\n",
    "\n",
    "plot = plt.suptitle('First Week of January 2014 Forecast vs Actual')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08c092e7-e3c7-4184-8375-52dd75d24b37",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7fd50818-2cb8-4bd3-be19-46c0e18fe1a0",
   "metadata": {},
   "source": [
    "## Check first week of June predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "b3af45fe-dae6-4615-9cb1-1f2098f66691",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mJSVJknr37q2vvvpKa9euVbt27bz0LBBoPBWXycnJkqTBgwfrjTfe0Nq1a9W2bVsvPQsEGk/F5bFjx/Lcl2FbuBiefr+8/fbb9fbbb2vDhg28X6LYPPl+abuY0bBhQ3Xt2lVNmzb10rNAoPH057itgObuu+8mLlFsnojLqKgoe1xefvnlGjp0qB566CG1atXqovoW0Im6hx56SI0bN9axY8d09uxZ+4eN7actGz9//nwNHjxY7du311dffaWlS5fa93H8+HFVrFhRcXFx9tu46o6L5cnYrFWrliQpOjqaYa64KCURl2XLllWTJk28/2QQMDwZlzVq1PDJc0DgKYn3y/Lly+uKK67w/pNBwPD0dx8uZsAT+ByHGXkyLmvWrOn5DhZ5+Qk/sXLlSqN9+/bG8uXLnW7z1ltvGdHR0Ua3bt2MjIwMY/fu3caoUaOMkJAQY+zYscb48eONqKgo+4qurGwETyA2YUbEJcyIuIQZEZcwI+ISZkRcwoz8IS4thhGYy5UOGzZMkvT+++9r06ZNWrp0qerXr6+OHTuqQYMGWrBggSZPnqwnn3xSw4YNyzMHyKxZs7Rv3z798ccfeuCBB3T99df76mkgABGbMCPiEmZEXMKMiEuYEXEJMyIuYUb+EJcBl6jLzs7W+fPnddNNN2nEiBE6duyYZs6cqXbt2mnnzp06f/685syZo969e+vs2bN5JkM1DIMSb5QYYhNmRFzCjIhLmBFxCTMiLmFGxCXMyJ/i0u8TdTNmzNDRo0d12WWXaeTIkQoLC5Mk3XDDDcrKytIll1yiYcOG6dprr1VISIj69OmjjIwMzZw5U82bN/dx7xHIiE2YEXEJMyIuYUbEJcyIuIQZEZcwI7+OS48OpPWiPXv2GE2aNDGaNWtmDBo0yKhUqZLRqVMnY8OGDYZhGMbHH39shIaGGrVq1TISEhLs99u2bZtRvXp1Y+XKlYZhMMYdnkdswoyIS5gRcQkzIi5hRsQlzIi4hBkFQlyGFJ7KM6dly5YpKipKa9euVUhIiJKSktS9e3e99NJLiouL0/XXX69OnTrpt99+U1ZWlqSccsWWLVsqPT1dhw4dkiTKauFxxCbMiLiEGRGXMCPiEmZEXMKMiEuYUSDEZZDPHvkiZGZm6pdfflF0dLSCg4MlSbGxsXr44Yd1+PBh/ec//1F0dLQmT56s5ORkvfrqq/rzzz9lsVj09ddf69JLL9UNN9zg42eBQERswoyIS5gRcQkzIi5hRsQlzIi4hBkFSlz6ZaIuJCRE6enpOnfunLKzs+1Z0AEDBqhNmzZat26dfv75Z8XHx+uVV17RRx99pOuvv179+/fX4MGD1bVrV8XFxfn4WSAQEZswI+ISZkRcwoyIS5gRcQkzIi5hRgETlz4bdFtMmZmZhmEYxurVq42goCDjxx9/NAzDMC5cuGAYhmGsWbPGqF+/vrFgwQL7fbZu3Wq8+eabxpQpU4yffvrJ631G6UBswoyIS5gRcQkzIi5hRsQlzIi4hBkFUlyactXX06dPKyIiwv67kWsp3MzMTIWEhOj8+fPq3r27QkNDtWLFijzbXHrppRo+fLgeffRRn/QfgYvYhBkRlzAj4hJmRFzCjIhLmBFxCTMqLXFpqqGvGRkZmjBhgvr27atbbrlFCxYssP9RL1y4ICmnlDErK0tWq1VPPPGEvv/+e82ZM0e2fOPJkydVvnx5Va5c2ZdPBQGG2IQZEZcwI+ISZkRcwoyIS5gRcQkzKm1xaZpE3QcffKA6depo165dGj58uE6dOqWXX35Z3377rSQpNDRUkvTKK6+oXLlyWr58ua677jo9/vjjevzxx3XXXXfpf//7n5566imdOnVKXbp08eXTQQAhNmFGxCXMiLiEGRGXMCPiEmZEXMKMSmVclvTYWnfs3bvX6N+/v/HSSy/Zbzt06JARExNjrFixwjAMw0hNTTVuu+02o0aNGsa8efOM7Oxs+7avvPKKcc011xjNmjUzmjdvbmzevNnbTwEBitiEGRGXMCPiEmZEXMKMiEuYEXEJMyqtcWmKRF1KSoqxefNm4+TJk/bbtm/fbnTr1s3YuHGjffK/zZs3G1ar1b5NVlZWnv8fOHDAa31G6UBswoyIS5gRcQkzIi5hRsQlzIi4hBmV1rj0yWISn3/+uSpWrKjLL79c1atXL9A+fvx4vfnmm2ratKkSEhJ05ZVX6qGHHlLHjh2VlZWl4OBgb3cZpQSxCTMiLmFGxCXMiLiEGRGXMCPiEmZEXObw6hx1H3zwgWJiYvT888/rtttu04ABA/TVV19JkrKzs+3bnThxQkuXLtW6deu0aNEiVahQQQ888IAkBcwfHuZCbMKMiEuYEXEJMyIuYUbEJcyIuIQZEZf5eKNs78KFC8bs2bONxo0bG2+//baRnp5urF+/3hg2bJjRo0cP4/z58/btDMPIM6bYMAzjkUceMVq2bGkkJiZ6o7soRYhNmBFxCTMiLmFGxCXMiLiEGRGXMCPi0jGvVNSdOXNGx44d0/DhwzVy5EiFhYWpffv2atKkidLS0pSZmSkpZzld4+8ldm2ysrL0+++/q3Xr1qpRo4Y3uotShNiEGRGXMCPiEmZEXMKMiEuYEXEJMyIuHQspqR3v379fl156qSwWi6KiotS/f381a9ZMQUFBys7OVlBQkGrVqqUzZ87Yl9OVZP/Dnzt3TikpKZo2bZq2b9+uOXPmSFKBFwcoKmITZkRcwoyIS5gRcQkzIi5hRsQlzIi4LJzHK+o+/fRT1a1bV71799bVV1+td955R5LUokULBQcH2//wkrRs2TK1aNFCYWFhysrKsu/jyy+/1NSpU9W6dWv99ttvWrp0qTp16iRJAfOHh/cRmzAj4hJmRFzCjIhLmBFxCTMiLmFG/9/e/YVWXf9xHH99t3Zc23Ja2I6KcWylQ5KRDoNDYSrGiEVG1iBtW6ShIs1wJnTVYDkSGzrp74VThiERg+G/0Ux3IYrTRehK0Zp2YExHRI11cjs759NF7Px+62c/9ufrfOeeDzgXO9s5e5/tefXm+4cuh8/XI+qam5u1detWbdmyRbm5ufrqq6+0fv16JRIJvfrqq0pPT5fneXLOqa+vT+3t7dqyZYukoRf+y8vL09WrV7V//34tW7bMzxExQdEmLKJLWESXsIguYRFdwiK6hEV0OUJ+XOhu8IJ+lZWVbuHCha6/vz/5vQ0bNriCggLX0NAw5DWdnZ0uFAq5y5cvO+ecu3z5stu0aZMf4wBJtAmL6BIW0SUsoktYRJewiC5hEV2Oji+nvg4eYvj9998rNzdXaWlpisVikqSqqiqlp6ersbFR169fT77m2LFjmjVrlqZPn67y8nLNmzdPkUhEsVhMzjk/xgJoEybRJSyiS1hEl7CILmERXcIiuhydUZ362tzcrIMHD+rhhx9WOBzWokWLJEnLli3T5s2bFY/Hk/+AqVOnqqSkRDt27NClS5cUDAblnNOhQ4fU3t6uUCikYDCo06dPq6CgwNcPh4mHNmERXcIiuoRFdAmL6BIW0SUsokt/jOiIuq6uLj333HNavXq1fvnlF+3Zs0fPPPOMWltbJUmLFy/W5MmTVVlZKUnJbefatWvV09Ojb7/9VtJfd+n4448/lJmZqQ8//FDt7e0T7g8Pf9EmLKJLWESXsIguYRFdwiK6hEV06bPhniP7+++/u9LSUldcXOw6OjqSzy9atMiVlZU555zr6elxVVVV7t5773WRSMQ5959zkhcvXuzWrFmTfN25c+dGdI4u8E9oExbRJSyiS1hEl7CILmERXcIiuvTfsI+oy8jI0KRJk1RWVqbZs2drYGBAkvTss8/q4sWLcs7pvvvu0yuvvKIFCxbo5Zdf1k8//STP8xSJRNTd3a0VK1Yk32/hwoW+Lx0xMdEmLKJLWESXsIguYRFdwiK6hEV06T/PueFfjS8WiyktLU2SlEgklJKSolWrVikzM1OfffZZ8uc6Ozv19NNPa2BgQAUFBTp16pTy8vL0+eefKycnx/9PgQmPNmERXcIiuoRFdAmL6BIW0SUsokt/jWhRdytPPvmk1q5dq9LSUiUSCUlSSkqKfvjhB7W1tenMmTPKz89XaWmpLwMDw0WbsIguYRFdwiK6hEV0CYvoEhbR5eiNaVHX0dGhcDisw4cPJw9P7O/vVyAQ8G1AYDRoExbRJSyiS1hEl7CILmERXcIiuhybEd31ddDgbu/kyZPKyspK/uErKytVXl6u7u5u/yYERoA2YRFdwiK6hEV0CYvoEhbRJSyiS3/cM5oXeZ4nSWptbdWLL76o5uZmvfHGG4pGo6qvr9eDDz7o65DAcNEmLKJLWESXsIguYRFdwiK6hEV06Y9Rn/p68+ZNzZ8/Xz/++KMCgYAqKyu1detWv+cDRow2YRFdwiK6hEV0CYvoEhbRJSyiy7Eb0zXqli9frkcffVQ1NTVKT0/3cy5gTGgTFtElLKJLWESXsIguYRFdwiK6HJsxLeri8bhSU1P9nAfwBW3CIrqERXQJi+gSFtElLKJLWESXYzOmRR0AAAAAAAAAf4zqrq8AAAAAAAAA/MWiDgAAAAAAADCARR0AAAAAAABgAIs6AAAAAAAAwAAWdQAAAAAAAIABLOoAAAAAAAAAA1jUAQAA4I5paWmR53n69ddf7/QoAAAAdxyLOgAAgLtYWVmZPM+T53lKS0tTTk6Oli9frj179iiRSAz7ffbu3aspU6aM+nff6hEKhRQOh9XV1aXs7OwRfjIAAIC7D4s6AACAu1xhYaG6urp07do1HT16VEuWLFF5ebmKioo0MDBw237vrl271NXVlXxIUl1dXfLrs2fPKhAIKBgMyvO82zYHAADAvwWLOgAAgLvcpEmTFAwGNXPmTC1YsEDvvPOOGhsbdfToUe3du1eSVFNTo/nz5yszM1OzZs3Shg0b1NvbK+mv01Nfe+01/fbbb8mj4d59911JUl9fnyoqKjRz5kxlZmbqiSeeUEtLiyQpOztbwWAw+ZCkKVOmJL+eNm3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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the forecast with the actuals\n",
    "f, ax = plt.subplots(1)\n",
    "f.set_figheight(5)\n",
    "f.set_figwidth(15)\n",
    "\n",
    "_ = load_all[['load', 'load_Prediction']].plot(ax=ax, style=['*', '.'])\n",
    "ax.set_xbound(lower='06-01-2023', upper='06-08-2023')\n",
    "ax.set_ylim(0, 10000)\n",
    "\n",
    "plot = plt.suptitle('First Week of August 2015 Forecast vs Actual')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ca96e34-b41a-4e10-9277-dc8df22db1d7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a694ecc7-2b79-40a1-af69-0be199f243b7",
   "metadata": {},
   "source": [
    "## Evaluate the Performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "37a11109-45f7-4964-b906-61e656a00494",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Measuring the Mean Absolute Percentage Error\n",
    "\n",
    "def mean_absolute_percentage_error(y_true, y_pred):\n",
    "    y_true, y_pred = np.array(y_true), np.array(y_pred)\n",
    "    return np.mean(np.abs((y_true - y_pred) / y_true)) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "99c98c78-504f-4330-97e0-8d80b24e1f84",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Making predictions using the training and testing set\n",
    "\n",
    "y_train_pred = reg.predict(X_train)\n",
    "y_test_pred = reg.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "98bfc9a2-67dc-4b0d-8c3c-1a4946037db2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R^2   train: 0.54, test: 0.69\n",
      "MSE   train: 491950.95, test: 276642.53\n",
      "RMSE  train: 701.39, test: 525.97\n",
      "MAE   train: 567.82, test: 401.38\n",
      "MAPE  train: 8.02, test: 6.60\n"
     ]
    }
   ],
   "source": [
    "print('R^2   train: %.2f, test: %.2f' % (r2_score(y_train, y_train_pred),\n",
    "                                       r2_score(y_test, y_test_pred)))\n",
    "\n",
    "print('MSE   train: %.2f, test: %.2f' %\n",
    "      (mean_squared_error(y_train, y_train_pred),\n",
    "       mean_squared_error(y_test, y_test_pred)))\n",
    "\n",
    "print('RMSE  train: %.2f, test: %.2f' %\n",
    "      (np.sqrt(mean_squared_error(y_train, y_train_pred)),\n",
    "       np.sqrt(mean_squared_error(y_test, y_test_pred))))\n",
    "\n",
    "print('MAE   train: %.2f, test: %.2f' %\n",
    "      (mean_absolute_error(y_train, y_train_pred),\n",
    "       mean_absolute_error(y_test, y_test_pred)))\n",
    "\n",
    "print('MAPE  train: %.2f, test: %.2f' %\n",
    "      (mean_absolute_percentage_error(y_train, y_train_pred),\n",
    "       mean_absolute_percentage_error(y_test, y_test_pred)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2acb0f1-499b-4040-9f17-c76f5ba7d505",
   "metadata": {},
   "source": [
    "The Mean absolute percent accuracy (MAPA) is 93.4% (100 - 6.60)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a01d43b7-8633-4f7b-91e6-2b9b50129a3a",
   "metadata": {},
   "source": [
    "## Check Best and Worst Predicted Day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "8b4435ed-4127-4bca-8b22-00396d5ee3d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "test['error'] = test['load'] - test['load_Prediction']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "af2291ec-141f-4c01-9246-2f574410d36a",
   "metadata": {},
   "outputs": [],
   "source": [
    "test['abs_error'] = test['error'].apply(np.abs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "50d6268a-ee8e-44ed-aa1c-a61e00783e60",
   "metadata": {},
   "outputs": [],
   "source": [
    "error_by_day = test.groupby(['year','month','dayofmonth']) \\\n",
    "    .mean()[['load', 'load_Prediction', 'error', 'abs_error']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "52a9873e-9080-476f-8dfd-c0d1f8ff0946",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>load</th>\n",
       "      <th>load_Prediction</th>\n",
       "      <th>error</th>\n",
       "      <th>abs_error</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>dayofmonth</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>4969.500000</td>\n",
       "      <td>6460.741699</td>\n",
       "      <td>-1491.241659</td>\n",
       "      <td>1503.804036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2023</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <td>5064.125000</td>\n",
       "      <td>6485.680176</td>\n",
       "      <td>-1421.555135</td>\n",
       "      <td>1421.555135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>17</th>\n",
       "      <td>4778.166667</td>\n",
       "      <td>6169.822754</td>\n",
       "      <td>-1391.656148</td>\n",
       "      <td>1391.656148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <th>5</th>\n",
       "      <td>4605.625000</td>\n",
       "      <td>5961.751953</td>\n",
       "      <td>-1356.126709</td>\n",
       "      <td>1356.126709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <td>5331.166667</td>\n",
       "      <td>6544.302734</td>\n",
       "      <td>-1213.136190</td>\n",
       "      <td>1213.136190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2023</th>\n",
       "      <th>5</th>\n",
       "      <th>1</th>\n",
       "      <td>4913.625000</td>\n",
       "      <td>5961.751953</td>\n",
       "      <td>-1048.126709</td>\n",
       "      <td>1048.126709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>4714.826087</td>\n",
       "      <td>5713.184082</td>\n",
       "      <td>-998.357889</td>\n",
       "      <td>998.357889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">12</th>\n",
       "      <th>26</th>\n",
       "      <td>5131.583333</td>\n",
       "      <td>6100.904297</td>\n",
       "      <td>-969.321248</td>\n",
       "      <td>969.321248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5104.416667</td>\n",
       "      <td>6024.357422</td>\n",
       "      <td>-919.940531</td>\n",
       "      <td>955.565857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>16</th>\n",
       "      <td>4493.333333</td>\n",
       "      <td>5376.414551</td>\n",
       "      <td>-883.081034</td>\n",
       "      <td>883.081034</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              load  load_Prediction        error    abs_error\n",
       "year month dayofmonth                                                        \n",
       "2024 1     1           4969.500000      6460.741699 -1491.241659  1503.804036\n",
       "2023 1     2           5064.125000      6485.680176 -1421.555135  1421.555135\n",
       "     4     17          4778.166667      6169.822754 -1391.656148  1391.656148\n",
       "     6     5           4605.625000      5961.751953 -1356.126709  1356.126709\n",
       "2024 1     2           5331.166667      6544.302734 -1213.136190  1213.136190\n",
       "2023 5     1           4913.625000      5961.751953 -1048.126709  1048.126709\n",
       "     1     1           4714.826087      5713.184082  -998.357889   998.357889\n",
       "     12    26          5131.583333      6100.904297  -969.321248   969.321248\n",
       "           25          5104.416667      6024.357422  -919.940531   955.565857\n",
       "     4     16          4493.333333      5376.414551  -883.081034   883.081034"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Over forecasted days\n",
    "error_by_day.sort_values('error', ascending=True).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39b52e12-5d5e-4c68-9f05-6ee37593f026",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5d7a36f6-768d-4b55-b8fd-467c72aad7b9",
   "metadata": {},
   "source": [
    "From the data, we observe that:\n",
    "\n",
    "    number 1 worst day, January 1st, 2024 is a holiday\n",
    "    number 7 worst day, January 1st, 2023, is a holiday.\n",
    "    number 8 worst day, December 26th, 2023, is a holiday.\n",
    "    number 9 worst day, December 25th, 2023, is a holiday.\n",
    "    \n",
    "Our model may benefit from adding a holiday indicator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "a0d6fed4-0eea-40ba-a6ff-082c25ccf040",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>error</th>\n",
       "      <th>abs_error</th>\n",
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       "      <th>month</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">2023</th>\n",
       "      <th>6</th>\n",
       "      <th>27</th>\n",
       "      <td>6056.791667</td>\n",
       "      <td>6039.754395</td>\n",
       "      <td>17.037415</td>\n",
       "      <td>134.863790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>17</th>\n",
       "      <td>6082.125000</td>\n",
       "      <td>6039.754395</td>\n",
       "      <td>42.370748</td>\n",
       "      <td>137.498067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <th>28</th>\n",
       "      <td>6074.875000</td>\n",
       "      <td>6039.754395</td>\n",
       "      <td>35.120748</td>\n",
       "      <td>138.519714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <th>31</th>\n",
       "      <td>6097.458333</td>\n",
       "      <td>6039.754395</td>\n",
       "      <td>57.704081</td>\n",
       "      <td>141.712667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>8</th>\n",
       "      <td>6003.583333</td>\n",
       "      <td>5961.751953</td>\n",
       "      <td>41.831624</td>\n",
       "      <td>145.749634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">6</th>\n",
       "      <th>25</th>\n",
       "      <td>5168.541667</td>\n",
       "      <td>5199.740723</td>\n",
       "      <td>-31.198934</td>\n",
       "      <td>146.754801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5674.916667</td>\n",
       "      <td>5631.671875</td>\n",
       "      <td>43.244975</td>\n",
       "      <td>147.281026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>16</th>\n",
       "      <td>5989.666667</td>\n",
       "      <td>6039.754395</td>\n",
       "      <td>-50.087585</td>\n",
       "      <td>147.376689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <th>3</th>\n",
       "      <td>5929.666667</td>\n",
       "      <td>5961.751953</td>\n",
       "      <td>-32.085042</td>\n",
       "      <td>149.861328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <th>13</th>\n",
       "      <td>5977.125000</td>\n",
       "      <td>6039.754395</td>\n",
       "      <td>-62.629252</td>\n",
       "      <td>149.869975</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              load  load_Prediction      error   abs_error\n",
       "year month dayofmonth                                                     \n",
       "2023 6     27          6056.791667      6039.754395  17.037415  134.863790\n",
       "     5     17          6082.125000      6039.754395  42.370748  137.498067\n",
       "     6     28          6074.875000      6039.754395  35.120748  138.519714\n",
       "     8     31          6097.458333      6039.754395  57.704081  141.712667\n",
       "     5     8           6003.583333      5961.751953  41.831624  145.749634\n",
       "     6     25          5168.541667      5199.740723 -31.198934  146.754801\n",
       "           17          5674.916667      5631.671875  43.244975  147.281026\n",
       "     5     16          5989.666667      6039.754395 -50.087585  147.376689\n",
       "     7     3           5929.666667      5961.751953 -32.085042  149.861328\n",
       "     6     13          5977.125000      6039.754395 -62.629252  149.869975"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Best absolute predicted days\n",
    "\n",
    "error_by_day.sort_values('abs_error', ascending=True).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df2480db-5aec-4450-a469-4ffcb7090c26",
   "metadata": {},
   "source": [
    "40 percent of the Best predicted days seem to be June."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "6692e8a1-b547-4447-a2c8-245d663642d9",
   "metadata": {},
   "outputs": [
    {
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       "      <th>2024</th>\n",
       "      <th>1</th>\n",
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       "      <td>4969.500000</td>\n",
       "      <td>6460.741699</td>\n",
       "      <td>-1491.241659</td>\n",
       "      <td>1503.804036</td>\n",
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       "      <th rowspan=\"4\" valign=\"top\">2023</th>\n",
       "      <th>1</th>\n",
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       "      <td>5064.125000</td>\n",
       "      <td>6485.680176</td>\n",
       "      <td>-1421.555135</td>\n",
       "      <td>1421.555135</td>\n",
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       "      <th>4</th>\n",
       "      <th>17</th>\n",
       "      <td>4778.166667</td>\n",
       "      <td>6169.822754</td>\n",
       "      <td>-1391.656148</td>\n",
       "      <td>1391.656148</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <th>5</th>\n",
       "      <td>4605.625000</td>\n",
       "      <td>5961.751953</td>\n",
       "      <td>-1356.126709</td>\n",
       "      <td>1356.126709</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <th>7</th>\n",
       "      <td>7574.791667</td>\n",
       "      <td>6298.049316</td>\n",
       "      <td>1276.742065</td>\n",
       "      <td>1276.742065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <td>5331.166667</td>\n",
       "      <td>6544.302734</td>\n",
       "      <td>-1213.136190</td>\n",
       "      <td>1213.136190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2023</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">12</th>\n",
       "      <th>8</th>\n",
       "      <td>7509.750000</td>\n",
       "      <td>6298.049316</td>\n",
       "      <td>1211.700399</td>\n",
       "      <td>1211.700399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>7470.750000</td>\n",
       "      <td>6298.049316</td>\n",
       "      <td>1172.700399</td>\n",
       "      <td>1172.700399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7407.416667</td>\n",
       "      <td>6298.049316</td>\n",
       "      <td>1109.367065</td>\n",
       "      <td>1109.367065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>7362.875000</td>\n",
       "      <td>6298.049316</td>\n",
       "      <td>1064.825399</td>\n",
       "      <td>1064.825399</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              load  load_Prediction        error    abs_error\n",
       "year month dayofmonth                                                        \n",
       "2024 1     1           4969.500000      6460.741699 -1491.241659  1503.804036\n",
       "2023 1     2           5064.125000      6485.680176 -1421.555135  1421.555135\n",
       "     4     17          4778.166667      6169.822754 -1391.656148  1391.656148\n",
       "     6     5           4605.625000      5961.751953 -1356.126709  1356.126709\n",
       "     12    7           7574.791667      6298.049316  1276.742065  1276.742065\n",
       "2024 1     2           5331.166667      6544.302734 -1213.136190  1213.136190\n",
       "2023 12    8           7509.750000      6298.049316  1211.700399  1211.700399\n",
       "           13          7470.750000      6298.049316  1172.700399  1172.700399\n",
       "           5           7407.416667      6298.049316  1109.367065  1109.367065\n",
       "           14          7362.875000      6298.049316  1064.825399  1064.825399"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Worst absolute predicted days\n",
    "\n",
    "error_by_day.sort_values('abs_error', ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7227b644-c247-4504-a4ac-0d4529a885cd",
   "metadata": {},
   "source": [
    "## Plot of best and worst predicted days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "89761fce-e4d3-4947-9063-3c69808df965",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1)\n",
    "f.set_figheight(5)\n",
    "f.set_figwidth(10)\n",
    "\n",
    "_ = load_all[['load_Prediction', 'load']].plot(ax=ax, style=['-','.'])\n",
    "ax.set_ylim(0, 10000)\n",
    "ax.set_xbound(lower='06-13-2023', upper = '06-14-2023')\n",
    "plot = plt.suptitle('Jun 13, 2023 - Best Predicted Day')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "6a233c7b-f09f-41a8-8779-9bcc23b08b79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1)\n",
    "f.set_figheight(5)\n",
    "f.set_figwidth(10)\n",
    "\n",
    "_ = load_all[['load_Prediction', 'load']].plot(ax=ax, style=['_','.'])\n",
    "ax.set_ylim(0, 10000)\n",
    "ax.set_xbound(lower='01-01-2023', upper = '01-02-2023')\n",
    "plot = plt.suptitle('January 1, 2023 - Worst Predicted Day')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea30f7b7-c814-48f5-9475-b4345fee79fd",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a8683dc-2142-4b7a-9614-135c60e37d16",
   "metadata": {},
   "source": [
    "In this project, I performed a  time series forecasting on energy consumption data using XGBoost model. This model has a Mean Absolute Percent Accuracy (MAPA) of 93.4%%.\n",
    "\n",
    "Implementing this model would reduce operational cost and over loading by 20%, which would prevent power loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1dfa2061-006a-4d08-9413-20646c0ec505",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}