Energy demand prediction using machine learning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__***Energy demand prediction using machine learning***__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Problem Description\n",
    "The problem involves predicting the hourly electricity consumption based on historical data. Accurately forecasting electricity demand is crucial for energy providers to optimize power generation, reduce operational costs, and maintain grid stability. This problem falls under the category of time series forecasting, where past data is analyzed to predict future consumption patterns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dataset Description\n",
    "The dataset contains information on electricity consumption over time, including timestamps and other potential explanatory variables. Below are the details of the dataset:\n",
    "\n",
    "1. Columns:\n",
    "+ Timestamp: A datetime field indicating when the electricity consumption was recorded. This serves as the time index for the analysis.\n",
    "+ Energy: The target variable representing the amount of electricity consumed (measured in appropriate units, such as kWh or MW).\n",
    "+ Additional columns (if any): These may include weather conditions, day of the week, holiday indicators, or other factors influencing energy consumption.\n",
    "\n",
    "2. Key Characteristics:\n",
    "- Granularity: Hourly observations.\n",
    "- Temporal Dependencies: Electricity consumption exhibits seasonal patterns (e.g., daily, weekly) and trends over time.\n",
    "- Potential Noise: Variability in the data may arise from external factors like weather changes, holidays, or unexpected disruptions.\n",
    "\n",
    "3. Objective: The primary objective is to build a predictive model capable of forecasting electricity demand for each hour. The analysis will enable proactive planning for energy generation and consumption management."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Business Importance\n",
    "Accurate forecasting of electricity consumption can help:\n",
    "\n",
    "+ Optimize Resource Allocation: Avoiding overproduction or underproduction of electricity.\n",
    "+ Cost Reduction: Minimizing operational expenses and energy wastage.\n",
    "+ Environmental Benefits: Reducing carbon emissions by optimizing the use of renewable energy sources.\n",
    "+ Demand-Supply Matching: Ensuring a balanced energy grid and reducing the risk of blackouts.\n",
    "\n",
    "This analysis provides actionable insights for energy providers and policymakers to achieve efficient energy management."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_percentage_error\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>SquareFootage</th>\n",
       "      <th>Occupancy</th>\n",
       "      <th>HVACUsage</th>\n",
       "      <th>LightingUsage</th>\n",
       "      <th>RenewableEnergy</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>Holiday</th>\n",
       "      <th>EnergyConsumption</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timestamp</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>2022-01-01 00:00:00</th>\n",
       "      <td>25.139433</td>\n",
       "      <td>43.431581</td>\n",
       "      <td>1565.693999</td>\n",
       "      <td>5</td>\n",
       "      <td>On</td>\n",
       "      <td>Off</td>\n",
       "      <td>2.774699</td>\n",
       "      <td>Monday</td>\n",
       "      <td>No</td>\n",
       "      <td>75.364373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 01:00:00</th>\n",
       "      <td>27.731651</td>\n",
       "      <td>54.225919</td>\n",
       "      <td>1411.064918</td>\n",
       "      <td>1</td>\n",
       "      <td>On</td>\n",
       "      <td>On</td>\n",
       "      <td>21.831384</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>No</td>\n",
       "      <td>83.401855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 02:00:00</th>\n",
       "      <td>28.704277</td>\n",
       "      <td>58.907658</td>\n",
       "      <td>1755.715009</td>\n",
       "      <td>2</td>\n",
       "      <td>Off</td>\n",
       "      <td>Off</td>\n",
       "      <td>6.764672</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>No</td>\n",
       "      <td>78.270888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 03:00:00</th>\n",
       "      <td>20.080469</td>\n",
       "      <td>50.371637</td>\n",
       "      <td>1452.316318</td>\n",
       "      <td>1</td>\n",
       "      <td>Off</td>\n",
       "      <td>On</td>\n",
       "      <td>8.623447</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>No</td>\n",
       "      <td>56.519850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 04:00:00</th>\n",
       "      <td>23.097359</td>\n",
       "      <td>51.401421</td>\n",
       "      <td>1094.130359</td>\n",
       "      <td>9</td>\n",
       "      <td>On</td>\n",
       "      <td>Off</td>\n",
       "      <td>3.071969</td>\n",
       "      <td>Friday</td>\n",
       "      <td>No</td>\n",
       "      <td>70.811732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 11:00:00</th>\n",
       "      <td>28.619382</td>\n",
       "      <td>48.850160</td>\n",
       "      <td>1080.087000</td>\n",
       "      <td>5</td>\n",
       "      <td>Off</td>\n",
       "      <td>Off</td>\n",
       "      <td>21.194696</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>No</td>\n",
       "      <td>82.306692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 12:00:00</th>\n",
       "      <td>23.836647</td>\n",
       "      <td>47.256435</td>\n",
       "      <td>1705.235156</td>\n",
       "      <td>4</td>\n",
       "      <td>Off</td>\n",
       "      <td>On</td>\n",
       "      <td>25.748176</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>Yes</td>\n",
       "      <td>66.577320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 13:00:00</th>\n",
       "      <td>23.005340</td>\n",
       "      <td>48.720501</td>\n",
       "      <td>1320.285281</td>\n",
       "      <td>6</td>\n",
       "      <td>Off</td>\n",
       "      <td>On</td>\n",
       "      <td>0.297079</td>\n",
       "      <td>Friday</td>\n",
       "      <td>Yes</td>\n",
       "      <td>72.753471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 14:00:00</th>\n",
       "      <td>25.138365</td>\n",
       "      <td>31.306459</td>\n",
       "      <td>1309.079719</td>\n",
       "      <td>3</td>\n",
       "      <td>On</td>\n",
       "      <td>Off</td>\n",
       "      <td>20.425163</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>Yes</td>\n",
       "      <td>76.950389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 15:00:00</th>\n",
       "      <td>23.051165</td>\n",
       "      <td>42.615421</td>\n",
       "      <td>1018.140606</td>\n",
       "      <td>6</td>\n",
       "      <td>Off</td>\n",
       "      <td>On</td>\n",
       "      <td>2.455657</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>No</td>\n",
       "      <td>71.545311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Temperature   Humidity  SquareFootage  Occupancy  \\\n",
       "Timestamp                                                               \n",
       "2022-01-01 00:00:00    25.139433  43.431581    1565.693999          5   \n",
       "2022-01-01 01:00:00    27.731651  54.225919    1411.064918          1   \n",
       "2022-01-01 02:00:00    28.704277  58.907658    1755.715009          2   \n",
       "2022-01-01 03:00:00    20.080469  50.371637    1452.316318          1   \n",
       "2022-01-01 04:00:00    23.097359  51.401421    1094.130359          9   \n",
       "...                          ...        ...            ...        ...   \n",
       "2022-02-11 11:00:00    28.619382  48.850160    1080.087000          5   \n",
       "2022-02-11 12:00:00    23.836647  47.256435    1705.235156          4   \n",
       "2022-02-11 13:00:00    23.005340  48.720501    1320.285281          6   \n",
       "2022-02-11 14:00:00    25.138365  31.306459    1309.079719          3   \n",
       "2022-02-11 15:00:00    23.051165  42.615421    1018.140606          6   \n",
       "\n",
       "                    HVACUsage LightingUsage  RenewableEnergy  DayOfWeek  \\\n",
       "Timestamp                                                                 \n",
       "2022-01-01 00:00:00        On           Off         2.774699     Monday   \n",
       "2022-01-01 01:00:00        On            On        21.831384   Saturday   \n",
       "2022-01-01 02:00:00       Off           Off         6.764672     Sunday   \n",
       "2022-01-01 03:00:00       Off            On         8.623447  Wednesday   \n",
       "2022-01-01 04:00:00        On           Off         3.071969     Friday   \n",
       "...                       ...           ...              ...        ...   \n",
       "2022-02-11 11:00:00       Off           Off        21.194696   Saturday   \n",
       "2022-02-11 12:00:00       Off            On        25.748176    Tuesday   \n",
       "2022-02-11 13:00:00       Off            On         0.297079     Friday   \n",
       "2022-02-11 14:00:00        On           Off        20.425163   Thursday   \n",
       "2022-02-11 15:00:00       Off            On         2.455657   Saturday   \n",
       "\n",
       "                    Holiday  EnergyConsumption  \n",
       "Timestamp                                       \n",
       "2022-01-01 00:00:00      No          75.364373  \n",
       "2022-01-01 01:00:00      No          83.401855  \n",
       "2022-01-01 02:00:00      No          78.270888  \n",
       "2022-01-01 03:00:00      No          56.519850  \n",
       "2022-01-01 04:00:00      No          70.811732  \n",
       "...                     ...                ...  \n",
       "2022-02-11 11:00:00      No          82.306692  \n",
       "2022-02-11 12:00:00     Yes          66.577320  \n",
       "2022-02-11 13:00:00     Yes          72.753471  \n",
       "2022-02-11 14:00:00     Yes          76.950389  \n",
       "2022-02-11 15:00:00      No          71.545311  \n",
       "\n",
       "[1000 rows x 10 columns]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Loading data\n",
    "data = pd.read_csv(\"D:\\SAGES\\project\\Energy_consumption.csv\")\n",
    "data.set_index('Timestamp', inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Basic information about data:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 1000 entries, 2022-01-01 00:00:00 to 2022-02-11 15:00:00\n",
      "Data columns (total 10 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   Temperature        1000 non-null   float64\n",
      " 1   Humidity           1000 non-null   float64\n",
      " 2   SquareFootage      1000 non-null   float64\n",
      " 3   Occupancy          1000 non-null   int64  \n",
      " 4   HVACUsage          1000 non-null   object \n",
      " 5   LightingUsage      1000 non-null   object \n",
      " 6   RenewableEnergy    1000 non-null   float64\n",
      " 7   DayOfWeek          1000 non-null   object \n",
      " 8   Holiday            1000 non-null   object \n",
      " 9   EnergyConsumption  1000 non-null   float64\n",
      "dtypes: float64(5), int64(1), object(4)\n",
      "memory usage: 85.9+ KB\n",
      "None\n",
      "\n",
      "Data preview:\n",
      "                     Temperature   Humidity  SquareFootage  Occupancy  \\\n",
      "Timestamp                                                               \n",
      "2022-01-01 00:00:00    25.139433  43.431581    1565.693999          5   \n",
      "2022-01-01 01:00:00    27.731651  54.225919    1411.064918          1   \n",
      "2022-01-01 02:00:00    28.704277  58.907658    1755.715009          2   \n",
      "2022-01-01 03:00:00    20.080469  50.371637    1452.316318          1   \n",
      "2022-01-01 04:00:00    23.097359  51.401421    1094.130359          9   \n",
      "\n",
      "                    HVACUsage LightingUsage  RenewableEnergy  DayOfWeek  \\\n",
      "Timestamp                                                                 \n",
      "2022-01-01 00:00:00        On           Off         2.774699     Monday   \n",
      "2022-01-01 01:00:00        On            On        21.831384   Saturday   \n",
      "2022-01-01 02:00:00       Off           Off         6.764672     Sunday   \n",
      "2022-01-01 03:00:00       Off            On         8.623447  Wednesday   \n",
      "2022-01-01 04:00:00        On           Off         3.071969     Friday   \n",
      "\n",
      "                    Holiday  EnergyConsumption  \n",
      "Timestamp                                       \n",
      "2022-01-01 00:00:00      No          75.364373  \n",
      "2022-01-01 01:00:00      No          83.401855  \n",
      "2022-01-01 02:00:00      No          78.270888  \n",
      "2022-01-01 03:00:00      No          56.519850  \n",
      "2022-01-01 04:00:00      No          70.811732  \n"
     ]
    }
   ],
   "source": [
    "# Displaying basic information about the data\n",
    "print(\"Basic information about data:\")\n",
    "print(data.info())\n",
    "print(\"\\nData preview:\")\n",
    "print(data.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Checking for missing data:\n",
      "Temperature          0\n",
      "Humidity             0\n",
      "SquareFootage        0\n",
      "Occupancy            0\n",
      "HVACUsage            0\n",
      "LightingUsage        0\n",
      "RenewableEnergy      0\n",
      "DayOfWeek            0\n",
      "Holiday              0\n",
      "EnergyConsumption    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Data mining\n",
    "print(\"\\nChecking for missing data:\")\n",
    "print(data.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Temperature</th>\n",
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       "      <th>HVACUsage</th>\n",
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       "      <th>DayOfWeek</th>\n",
       "      <th>Holiday</th>\n",
       "      <th>EnergyConsumption</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timestamp</th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>2022-01-01 00:00:00</th>\n",
       "      <td>25.139433</td>\n",
       "      <td>43.431581</td>\n",
       "      <td>1565.693999</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>75.364373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 01:00:00</th>\n",
       "      <td>27.731651</td>\n",
       "      <td>54.225919</td>\n",
       "      <td>1411.064918</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>21.831384</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>83.401855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 02:00:00</th>\n",
       "      <td>28.704277</td>\n",
       "      <td>58.907658</td>\n",
       "      <td>1755.715009</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.764672</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>78.270888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 03:00:00</th>\n",
       "      <td>20.080469</td>\n",
       "      <td>50.371637</td>\n",
       "      <td>1452.316318</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.623447</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>56.519850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 04:00:00</th>\n",
       "      <td>23.097359</td>\n",
       "      <td>51.401421</td>\n",
       "      <td>1094.130359</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.071969</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>70.811732</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Temperature   Humidity  SquareFootage  Occupancy  \\\n",
       "Timestamp                                                               \n",
       "2022-01-01 00:00:00    25.139433  43.431581    1565.693999          5   \n",
       "2022-01-01 01:00:00    27.731651  54.225919    1411.064918          1   \n",
       "2022-01-01 02:00:00    28.704277  58.907658    1755.715009          2   \n",
       "2022-01-01 03:00:00    20.080469  50.371637    1452.316318          1   \n",
       "2022-01-01 04:00:00    23.097359  51.401421    1094.130359          9   \n",
       "\n",
       "                     HVACUsage  LightingUsage  RenewableEnergy  DayOfWeek  \\\n",
       "Timestamp                                                                   \n",
       "2022-01-01 00:00:00          1              0         2.774699          1   \n",
       "2022-01-01 01:00:00          1              1        21.831384          2   \n",
       "2022-01-01 02:00:00          0              0         6.764672          3   \n",
       "2022-01-01 03:00:00          0              1         8.623447          6   \n",
       "2022-01-01 04:00:00          1              0         3.071969          0   \n",
       "\n",
       "                     Holiday  EnergyConsumption  \n",
       "Timestamp                                        \n",
       "2022-01-01 00:00:00        0          75.364373  \n",
       "2022-01-01 01:00:00        0          83.401855  \n",
       "2022-01-01 02:00:00        0          78.270888  \n",
       "2022-01-01 03:00:00        0          56.519850  \n",
       "2022-01-01 04:00:00        0          70.811732  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Transforming categorical data\n",
    "le = LabelEncoder()\n",
    "\n",
    "for col in ['HVACUsage','LightingUsage', 'DayOfWeek', 'Holiday']:\n",
    "    le.fit(data[col])\n",
    "    data[col] = le.transform(data[col])\n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Temperature</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>SquareFootage</th>\n",
       "      <th>Occupancy</th>\n",
       "      <th>HVACUsage</th>\n",
       "      <th>LightingUsage</th>\n",
       "      <th>RenewableEnergy</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>Holiday</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timestamp</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>2022-01-01 00:00:00</th>\n",
       "      <td>25.139433</td>\n",
       "      <td>43.431581</td>\n",
       "      <td>1565.693999</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.774699</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 01:00:00</th>\n",
       "      <td>27.731651</td>\n",
       "      <td>54.225919</td>\n",
       "      <td>1411.064918</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>21.831384</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 02:00:00</th>\n",
       "      <td>28.704277</td>\n",
       "      <td>58.907658</td>\n",
       "      <td>1755.715009</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.764672</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 03:00:00</th>\n",
       "      <td>20.080469</td>\n",
       "      <td>50.371637</td>\n",
       "      <td>1452.316318</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.623447</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01 04:00:00</th>\n",
       "      <td>23.097359</td>\n",
       "      <td>51.401421</td>\n",
       "      <td>1094.130359</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.071969</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 11:00:00</th>\n",
       "      <td>28.619382</td>\n",
       "      <td>48.850160</td>\n",
       "      <td>1080.087000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>21.194696</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 12:00:00</th>\n",
       "      <td>23.836647</td>\n",
       "      <td>47.256435</td>\n",
       "      <td>1705.235156</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>25.748176</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 13:00:00</th>\n",
       "      <td>23.005340</td>\n",
       "      <td>48.720501</td>\n",
       "      <td>1320.285281</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.297079</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 14:00:00</th>\n",
       "      <td>25.138365</td>\n",
       "      <td>31.306459</td>\n",
       "      <td>1309.079719</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>20.425163</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11 15:00:00</th>\n",
       "      <td>23.051165</td>\n",
       "      <td>42.615421</td>\n",
       "      <td>1018.140606</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.455657</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Temperature   Humidity  SquareFootage  Occupancy  \\\n",
       "Timestamp                                                               \n",
       "2022-01-01 00:00:00    25.139433  43.431581    1565.693999          5   \n",
       "2022-01-01 01:00:00    27.731651  54.225919    1411.064918          1   \n",
       "2022-01-01 02:00:00    28.704277  58.907658    1755.715009          2   \n",
       "2022-01-01 03:00:00    20.080469  50.371637    1452.316318          1   \n",
       "2022-01-01 04:00:00    23.097359  51.401421    1094.130359          9   \n",
       "...                          ...        ...            ...        ...   \n",
       "2022-02-11 11:00:00    28.619382  48.850160    1080.087000          5   \n",
       "2022-02-11 12:00:00    23.836647  47.256435    1705.235156          4   \n",
       "2022-02-11 13:00:00    23.005340  48.720501    1320.285281          6   \n",
       "2022-02-11 14:00:00    25.138365  31.306459    1309.079719          3   \n",
       "2022-02-11 15:00:00    23.051165  42.615421    1018.140606          6   \n",
       "\n",
       "                     HVACUsage  LightingUsage  RenewableEnergy  DayOfWeek  \\\n",
       "Timestamp                                                                   \n",
       "2022-01-01 00:00:00          1              0         2.774699          1   \n",
       "2022-01-01 01:00:00          1              1        21.831384          2   \n",
       "2022-01-01 02:00:00          0              0         6.764672          3   \n",
       "2022-01-01 03:00:00          0              1         8.623447          6   \n",
       "2022-01-01 04:00:00          1              0         3.071969          0   \n",
       "...                        ...            ...              ...        ...   \n",
       "2022-02-11 11:00:00          0              0        21.194696          2   \n",
       "2022-02-11 12:00:00          0              1        25.748176          5   \n",
       "2022-02-11 13:00:00          0              1         0.297079          0   \n",
       "2022-02-11 14:00:00          1              0        20.425163          4   \n",
       "2022-02-11 15:00:00          0              1         2.455657          2   \n",
       "\n",
       "                     Holiday  \n",
       "Timestamp                     \n",
       "2022-01-01 00:00:00        0  \n",
       "2022-01-01 01:00:00        0  \n",
       "2022-01-01 02:00:00        0  \n",
       "2022-01-01 03:00:00        0  \n",
       "2022-01-01 04:00:00        0  \n",
       "...                      ...  \n",
       "2022-02-11 11:00:00        0  \n",
       "2022-02-11 12:00:00        1  \n",
       "2022-02-11 13:00:00        1  \n",
       "2022-02-11 14:00:00        1  \n",
       "2022-02-11 15:00:00        0  \n",
       "\n",
       "[1000 rows x 9 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Selecting features and target variable\n",
    "X = data.drop(columns=['EnergyConsumption']) # Features\n",
    "y = data['EnergyConsumption']                # Target variable\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature scaling\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Splitting data into training and test sets\n",
    "X_train = X[:899]\n",
    "X_test = X[900:]\n",
    "y_train = y[:899]\n",
    "y_test = y[900:]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      ],
      "text/plain": [
       "RandomForestRegressor(random_state=42)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training the model\n",
    "model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Evaluation of the model on the test set\n",
    "y_pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Metrics calculation\n",
    "mape = mean_absolute_percentage_error(y_test, y_pred)\n",
    "mae = mean_absolute_error(y_test, y_pred)\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "rmse = np.sqrt(mse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Model Results:\n",
      "Mean Absolute Percentage Error (MAPE): 0.06\n",
      "Mean Absolute Error (MAE): 4.29\n",
      "Mean Squared Error (MSE): 28.47\n",
      "Root Mean Squared Error (RMSE): 5.34\n"
     ]
    }
   ],
   "source": [
    "print(\"\\nModel Results:\")\n",
    "print(f\"Mean Absolute Percentage Error (MAPE): {mape:.2f}\")\n",
    "print(f\"Mean Absolute Error (MAE): {mae:.2f}\")\n",
    "print(f\"Mean Squared Error (MSE): {mse:.2f}\")\n",
    "print(f\"Root Mean Squared Error (RMSE): {rmse:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Model Results Analysis\n",
    "The performance of the time series forecasting model for predicting electricity consumption is summarized by the following metrics:\n",
    "\n",
    "1. Mean Absolute Percentage Error (MAPE): 0.06 (6%)\n",
    "Indicates that, on average, the model's predictions deviate by 6% from the actual values.\n",
    "A low MAPE value (e.g., below 10%) suggests the model is highly accurate in relative terms.\n",
    "\n",
    "2. Mean Absolute Error (MAE): 4.27\n",
    "Represents the average magnitude of error between the predicted and actual electricity consumption values.\n",
    "In this context, the MAE suggests that the model's predictions are, on average, off by 4.27 units (e.g., kWh or MW).\n",
    "\n",
    "3. Mean Squared Error (MSE): 27.04\n",
    "Penalizes larger errors more heavily by squaring the deviations. It provides a useful perspective for analyzing outlier impact.\n",
    "Lower MSE values indicate better model performance.\n",
    "\n",
    "4. Root Mean Squared Error (RMSE): 5.20\n",
    "RMSE takes the square root of MSE to provide an error metric in the same units as the target variable.\n",
    "A value of 5.20 indicates that typical prediction errors are within this range, which is reasonable if the overall consumption values are significantly larger."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Key Insights:\n",
    "\n",
    "+ High Accuracy: The model demonstrates excellent accuracy, with a low MAPE of 6%. This means the predictions are highly reliable for practical use.\n",
    "\n",
    "+ Error Tolerance: Errors in absolute terms (MAE and RMSE) are relatively small, showing that the model captures the majority of the variability in the data well.\n",
    "\n",
    "+ Business Implications: Such accuracy is sufficient for energy providers to make informed decisions about power generation and resource allocation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Actual vs. Predicted Chart\n",
    "plt.figure(figsize=(20, 6))\n",
    "plt.plot(y_test, label='Actual')\n",
    "plt.plot(y_pred, label='Predicted', color='orange')\n",
    "plt.title(\"Actual vs. Projected Energy Demand\")\n",
    "plt.xlabel(\"Time\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylabel(\"Energy Demand\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Predictions saved to file 'energy_predictions.csv'\n"
     ]
    }
   ],
   "source": [
    "# Optional: save model or prediction\n",
    "output = pd.DataFrame({'Timestamp': y_test.index, 'Actual': y_test, 'Predicted': y_pred})\n",
    "output.to_csv('energy_predictions.csv', index=False)\n",
    "print(\"\\nPredictions saved to file 'energy_predictions.csv'\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}