05 Forecasting taxi orders.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Forecasting taxi orders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Project Description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The company \"taksi\" has collected historical data on taxi orders at airports. In order to attract more drivers during the peak period, we need to predict the number of taxi orders for the next hour. \n",
    "\n",
    "**Task:** \n",
    "- Build a model to predict taxi orders for the next hour.\n",
    "\n",
    "**Important Criteria:**\n",
    "- The value of the RMSE metric on the test sample should not be greater than 48.\n",
    "\n",
    "**Plan of work:**\n",
    "- Data loading and preparation\n",
    "- Data analysis\n",
    "- Data preparation and model training\n",
    "- Summarising the results of the work\n",
    "\n",
    "**Description of data - `taxi.csv` file**\n",
    "\n",
    "- `datetime` - time \n",
    "- `num_orders` - number of orders (***target***)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data loading and preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install statsmodels\n",
    "%pip install --upgrade scikit-learn\n",
    "%pip install lightgbm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np \n",
    "import seaborn as sns\n",
    "import warnings\n",
    "\n",
    "from lightgbm import LGBMRegressor\n",
    "\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "\n",
    "from sklearn.model_selection import train_test_split, RandomizedSearchCV, cross_val_score, TimeSeriesSplit\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import mean_squared_error, r2_score, make_scorer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(style=\"darkgrid\")\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save the file to a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    df = pd.read_csv('datasets/taxi.csv', parse_dates=[0], index_col=[0])\n",
    "except:\n",
    "    df = pd.read_csv('https://code.s3.yandex.net/datasets/taxi.csv', parse_dates=[0], index_col=[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Taking a look at some general information about the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 26496 entries, 2018-03-01 00:00:00 to 2018-08-31 23:50:00\n",
      "Data columns (total 1 columns):\n",
      " #   Column      Non-Null Count  Dtype\n",
      "---  ------      --------------  -----\n",
      " 0   num_orders  26496 non-null  int64\n",
      "dtypes: int64(1)\n",
      "memory usage: 414.0 KB\n",
      "\n",
      "Index is monotonic: True\n"
     ]
    },
    {
     "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>num_orders</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-03-01 00:00:00</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 00:10:00</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 00:20:00</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 00:30:00</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 00:40:00</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 23:10:00</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 23:20:00</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 23:30:00</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 23:40:00</th>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 23:50:00</th>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26496 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     num_orders\n",
       "datetime                       \n",
       "2018-03-01 00:00:00           9\n",
       "2018-03-01 00:10:00          14\n",
       "2018-03-01 00:20:00          28\n",
       "2018-03-01 00:30:00          20\n",
       "2018-03-01 00:40:00          32\n",
       "...                         ...\n",
       "2018-08-31 23:10:00          32\n",
       "2018-08-31 23:20:00          24\n",
       "2018-08-31 23:30:00          27\n",
       "2018-08-31 23:40:00          39\n",
       "2018-08-31 23:50:00          53\n",
       "\n",
       "[26496 rows x 1 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.info()\n",
    "print(\"\\nIndex is monotonic:\", df.index.is_monotonic_increasing or df.index.is_monotonic_decreasing)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All data are sorted in order and sorted to date type. There are no gaps in the data either, as the number of rows is the same as the number of indices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resample the dataframe one hour at a time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>num_orders</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-03-01 00:00:00</th>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 01:00:00</th>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 02:00:00</th>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 03:00:00</th>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 04:00:00</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 19:00:00</th>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 20:00:00</th>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 21:00:00</th>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 22:00:00</th>\n",
       "      <td>223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 23:00:00</th>\n",
       "      <td>205</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4416 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     num_orders\n",
       "datetime                       \n",
       "2018-03-01 00:00:00         124\n",
       "2018-03-01 01:00:00          85\n",
       "2018-03-01 02:00:00          71\n",
       "2018-03-01 03:00:00          66\n",
       "2018-03-01 04:00:00          43\n",
       "...                         ...\n",
       "2018-08-31 19:00:00         136\n",
       "2018-08-31 20:00:00         154\n",
       "2018-08-31 21:00:00         159\n",
       "2018-08-31 22:00:00         223\n",
       "2018-08-31 23:00:00         205\n",
       "\n",
       "[4416 rows x 1 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.resample('1H').sum()\n",
    "df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Divide the data into trend, seasonal and noise components and plot the corresponding graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "decomposed = seasonal_decompose(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Residuals')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2500x1500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(25, 15))\n",
    "\n",
    "ax[0, 0] = decomposed.trend.plot(ax=ax[0, 0])\n",
    "ax[0, 0].set_ylabel('Orders')\n",
    "ax[0, 0].set_xlabel('Month')\n",
    "ax[0, 0].set_title('Trend')\n",
    "\n",
    "ax[0, 1] = decomposed.trend.rolling(24 * 7).mean().plot(ax=ax[0, 1])\n",
    "ax[0, 1].set_ylabel('Orders')\n",
    "ax[0, 1].set_xlabel('Month')\n",
    "ax[0, 1].set_title('Trend with moving average')\n",
    "\n",
    "\n",
    "ax[1, 0] = decomposed.seasonal.tail(24 * 7).plot(ax=ax[1, 0])\n",
    "ax[1, 0].set_ylabel('Seasonal Component')\n",
    "ax[1, 0].set_xlabel('Date')\n",
    "ax[1, 0].set_title('Seasonal Component for the Last Week')\n",
    "ax[1, 0].grid(True)\n",
    "\n",
    "\n",
    "ax[1, 1] = decomposed.resid.plot(ax=ax[1, 1])\n",
    "ax[1, 1].set_ylabel('Value')\n",
    "ax[1, 1].set_xlabel('Month')\n",
    "ax[1, 1].set_title('Residuals')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the data for the presence of weekly seasonality (for this purpose we resample the data by days and change the investigated period)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "decomposed = seasonal_decompose(df['2018-08-01':'2018-08-31'].resample(\"1D\").sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Seasonal Component for the Last Month')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 5))\n",
    "decomposed.seasonal.plot(ax=plt.gca())\n",
    "plt.ylabel('Seasonal Component')\n",
    "plt.xlabel('Date')\n",
    "plt.title('Seasonal Component for the Last Month')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of orders increases dramatically at weekly intervals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Conclusions:**\n",
    "- In the provided dataframe there is a trend of increasing number of orders;\n",
    "- There is a daily seasonality: decrease in the number of orders at night, increase in the morning and afternoon, peak in the evening;\n",
    "- There is weekly seasonality;\n",
    "- The residuals are unexplained."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preparation and model training"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write a function to create additional attributes. Since we have identified weekly and daily seasonality, we need to add the day of the week and hour to each record. Also, we will add a moving average to the table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_features(data, max_lag, rolling_mean_size):\n",
    "    new_data = data.copy()\n",
    "    new_data['dayofweek'] = new_data.index.dayofweek\n",
    "    new_data['hour'] = new_data.index.hour\n",
    "    \n",
    "    for lag in range(1, max_lag + 1):\n",
    "        new_data['lag_{}'.format(lag)] = new_data['num_orders'].shift(lag).copy()\n",
    "\n",
    "    new_data['rolling_mean'] = new_data['num_orders'].shift().rolling(rolling_mean_size).mean()\n",
    "    \n",
    "    return new_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's add new attributes to the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>num_orders</th>\n",
       "      <th>dayofweek</th>\n",
       "      <th>hour</th>\n",
       "      <th>lag_1</th>\n",
       "      <th>lag_2</th>\n",
       "      <th>lag_3</th>\n",
       "      <th>lag_4</th>\n",
       "      <th>lag_5</th>\n",
       "      <th>lag_6</th>\n",
       "      <th>lag_7</th>\n",
       "      <th>...</th>\n",
       "      <th>lag_160</th>\n",
       "      <th>lag_161</th>\n",
       "      <th>lag_162</th>\n",
       "      <th>lag_163</th>\n",
       "      <th>lag_164</th>\n",
       "      <th>lag_165</th>\n",
       "      <th>lag_166</th>\n",
       "      <th>lag_167</th>\n",
       "      <th>lag_168</th>\n",
       "      <th>rolling_mean</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",
       "      <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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-03-01 00:00:00</th>\n",
       "      <td>124</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 01:00:00</th>\n",
       "      <td>85</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>124.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 02:00:00</th>\n",
       "      <td>71</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>85.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 03:00:00</th>\n",
       "      <td>66</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>71.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01 04:00:00</th>\n",
       "      <td>43</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>66.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 19:00:00</th>\n",
       "      <td>136</td>\n",
       "      <td>4</td>\n",
       "      <td>19</td>\n",
       "      <td>207.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>...</td>\n",
       "      <td>187.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>164.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 20:00:00</th>\n",
       "      <td>154</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>136.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>...</td>\n",
       "      <td>196.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>167.541667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 21:00:00</th>\n",
       "      <td>159</td>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>154.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>...</td>\n",
       "      <td>118.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>168.041667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 22:00:00</th>\n",
       "      <td>223</td>\n",
       "      <td>4</td>\n",
       "      <td>22</td>\n",
       "      <td>159.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>...</td>\n",
       "      <td>74.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>166.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-31 23:00:00</th>\n",
       "      <td>205</td>\n",
       "      <td>4</td>\n",
       "      <td>23</td>\n",
       "      <td>223.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>...</td>\n",
       "      <td>22.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>169.125000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4416 rows × 172 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     num_orders  dayofweek  hour  lag_1  lag_2  lag_3  lag_4  \\\n",
       "datetime                                                                       \n",
       "2018-03-01 00:00:00         124          3     0    NaN    NaN    NaN    NaN   \n",
       "2018-03-01 01:00:00          85          3     1  124.0    NaN    NaN    NaN   \n",
       "2018-03-01 02:00:00          71          3     2   85.0  124.0    NaN    NaN   \n",
       "2018-03-01 03:00:00          66          3     3   71.0   85.0  124.0    NaN   \n",
       "2018-03-01 04:00:00          43          3     4   66.0   71.0   85.0  124.0   \n",
       "...                         ...        ...   ...    ...    ...    ...    ...   \n",
       "2018-08-31 19:00:00         136          4    19  207.0  217.0  197.0  116.0   \n",
       "2018-08-31 20:00:00         154          4    20  136.0  207.0  217.0  197.0   \n",
       "2018-08-31 21:00:00         159          4    21  154.0  136.0  207.0  217.0   \n",
       "2018-08-31 22:00:00         223          4    22  159.0  154.0  136.0  207.0   \n",
       "2018-08-31 23:00:00         205          4    23  223.0  159.0  154.0  136.0   \n",
       "\n",
       "                     lag_5  lag_6  lag_7  ...  lag_160  lag_161  lag_162  \\\n",
       "datetime                                  ...                              \n",
       "2018-03-01 00:00:00    NaN    NaN    NaN  ...      NaN      NaN      NaN   \n",
       "2018-03-01 01:00:00    NaN    NaN    NaN  ...      NaN      NaN      NaN   \n",
       "2018-03-01 02:00:00    NaN    NaN    NaN  ...      NaN      NaN      NaN   \n",
       "2018-03-01 03:00:00    NaN    NaN    NaN  ...      NaN      NaN      NaN   \n",
       "2018-03-01 04:00:00    NaN    NaN    NaN  ...      NaN      NaN      NaN   \n",
       "...                    ...    ...    ...  ...      ...      ...      ...   \n",
       "2018-08-31 19:00:00  133.0  166.0  136.0  ...    187.0    160.0    246.0   \n",
       "2018-08-31 20:00:00  116.0  133.0  166.0  ...    196.0    187.0    160.0   \n",
       "2018-08-31 21:00:00  197.0  116.0  133.0  ...    118.0    196.0    187.0   \n",
       "2018-08-31 22:00:00  217.0  197.0  116.0  ...     74.0    118.0    196.0   \n",
       "2018-08-31 23:00:00  207.0  217.0  197.0  ...     22.0     74.0    118.0   \n",
       "\n",
       "                     lag_163  lag_164  lag_165  lag_166  lag_167  lag_168  \\\n",
       "datetime                                                                    \n",
       "2018-03-01 00:00:00      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2018-03-01 01:00:00      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2018-03-01 02:00:00      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2018-03-01 03:00:00      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2018-03-01 04:00:00      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "...                      ...      ...      ...      ...      ...      ...   \n",
       "2018-08-31 19:00:00    273.0    173.0    242.0    166.0    179.0    113.0   \n",
       "2018-08-31 20:00:00    246.0    273.0    173.0    242.0    166.0    179.0   \n",
       "2018-08-31 21:00:00    160.0    246.0    273.0    173.0    242.0    166.0   \n",
       "2018-08-31 22:00:00    187.0    160.0    246.0    273.0    173.0    242.0   \n",
       "2018-08-31 23:00:00    196.0    187.0    160.0    246.0    273.0    173.0   \n",
       "\n",
       "                     rolling_mean  \n",
       "datetime                           \n",
       "2018-03-01 00:00:00           NaN  \n",
       "2018-03-01 01:00:00           NaN  \n",
       "2018-03-01 02:00:00           NaN  \n",
       "2018-03-01 03:00:00           NaN  \n",
       "2018-03-01 04:00:00           NaN  \n",
       "...                           ...  \n",
       "2018-08-31 19:00:00    164.875000  \n",
       "2018-08-31 20:00:00    167.541667  \n",
       "2018-08-31 21:00:00    168.041667  \n",
       "2018-08-31 22:00:00    166.416667  \n",
       "2018-08-31 23:00:00    169.125000  \n",
       "\n",
       "[4416 rows x 172 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = make_features(df, 24*7, 24)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now split the data into samples in the proportion 9:1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "RANDOM_STATE = 42\n",
    "TEST_SIZE = 0.1\n",
    "\n",
    "df.dropna(inplace=True)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    df.drop(columns=['num_orders']), # X\n",
    "    df['num_orders'], # y\n",
    "    shuffle=False,\n",
    "    test_size=TEST_SIZE\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train shape: (3823, 171)\n",
      "X_test shape: (425, 171)\n",
      "y_train shape: (3823,)\n",
      "y_test shape: (425,)\n"
     ]
    }
   ],
   "source": [
    "print('X_train shape:', X_train.shape)\n",
    "print('X_test shape:', X_test.shape)\n",
    "print('y_train shape:', y_train.shape)\n",
    "print('y_test shape:', y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Metric"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since it is important for us to evaluate the `RMSE` metric - we need to specify it manually, as it is not built into the `scikit-learn` library."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rmse(y_true, y_pred):\n",
    "    return np.sqrt(mean_squared_error(y_true, y_pred))\n",
    "\n",
    "rmse_scorer = make_scorer(rmse, greater_is_better=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LinearRegression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will look at the metrics of the linear regression model on the cross-validation sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_grid = {}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we are working with a time series, the usual cross-validation will not work for us. Instead, we will use `TimeSeriesSplit`. This way, we can take the time order into account when cross-validating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "tscv = TimeSeriesSplit(n_splits=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 15.6 ms\n",
      "Wall time: 1.59 s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=LinearRegression(), n_jobs=-1,\n",
       "                   param_distributions={}, random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomizedSearchCV</label><div class=\"sk-toggleable__content\"><pre>RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=LinearRegression(), n_jobs=-1,\n",
       "                   param_distributions={}, random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=LinearRegression(), n_jobs=-1,\n",
       "                   param_distributions={}, random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "randomized_search = RandomizedSearchCV(LinearRegression(),\n",
    "                                        param_grid, \n",
    "                                        cv=tscv,\n",
    "                                        scoring=rmse_scorer,\n",
    "                                        n_jobs=-1, \n",
    "                                        random_state=RANDOM_STATE)\n",
    "randomized_search.fit(X_train, y_train)\n",
    "                             "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.027273</td>\n",
       "      <td>0.003417</td>\n",
       "      <td>-22.687125</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  mean_score_time  mean_test_score  rank_test_score\n",
       "0       0.027273         0.003417       -22.687125                1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 22.69\n"
     ]
    }
   ],
   "source": [
    "results = pd.DataFrame(randomized_search.cv_results_)\n",
    "linear_model_rmse = round(-randomized_search.best_score_, 2)\n",
    "\n",
    "display(results[['mean_fit_time', 'mean_score_time', 'mean_test_score', 'rank_test_score']])\n",
    "print('RMSE:', linear_model_rmse)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On this amount of data, the model is trained quickly and its `RMSE' metric is 22.69"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LGBMRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a list of parameters that we want to enumerate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_grid = {\n",
    "    'num_leaves': [31, 50, 100],\n",
    "    'learning_rate': [0.01, 0.05, 0.1],\n",
    "    'n_estimators': [100, 200, 500]\n",
    "}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking for the best model metric and hyperparameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.005346 seconds.\n",
      "You can set `force_col_wise=true` to remove the overhead.\n",
      "[LightGBM] [Info] Total Bins 31587\n",
      "[LightGBM] [Info] Number of data points in the train set: 3823, number of used features: 171\n",
      "[LightGBM] [Info] Start training from score 79.561601\n",
      "CPU times: total: 6.73 s\n",
      "Wall time: 51.9 s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=LGBMRegressor(random_state=42), n_jobs=-1,\n",
       "                   param_distributions={&#x27;learning_rate&#x27;: [0.01, 0.05, 0.1],\n",
       "                                        &#x27;n_estimators&#x27;: [100, 200, 500],\n",
       "                                        &#x27;num_leaves&#x27;: [31, 50, 100]},\n",
       "                   random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomizedSearchCV</label><div class=\"sk-toggleable__content\"><pre>RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=LGBMRegressor(random_state=42), n_jobs=-1,\n",
       "                   param_distributions={&#x27;learning_rate&#x27;: [0.01, 0.05, 0.1],\n",
       "                                        &#x27;n_estimators&#x27;: [100, 200, 500],\n",
       "                                        &#x27;num_leaves&#x27;: [31, 50, 100]},\n",
       "                   random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42)</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=LGBMRegressor(random_state=42), n_jobs=-1,\n",
       "                   param_distributions={'learning_rate': [0.01, 0.05, 0.1],\n",
       "                                        'n_estimators': [100, 200, 500],\n",
       "                                        'num_leaves': [31, 50, 100]},\n",
       "                   random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "randomized_search = RandomizedSearchCV(LGBMRegressor(random_state=RANDOM_STATE),\n",
    "                                        param_grid, \n",
    "                                        cv=tscv,\n",
    "                                        scoring=rmse_scorer,\n",
    "                                        n_jobs=-1, \n",
    "                                        random_state=RANDOM_STATE)\n",
    "randomized_search.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Output the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>mean_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>param_num_leaves</th>\n",
       "      <th>param_learning_rate</th>\n",
       "      <th>param_n_estimators</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36.862517</td>\n",
       "      <td>0.011527</td>\n",
       "      <td>100</td>\n",
       "      <td>0.01</td>\n",
       "      <td>500</td>\n",
       "      <td>-22.970448</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.664219</td>\n",
       "      <td>0.011364</td>\n",
       "      <td>31</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100</td>\n",
       "      <td>-23.059453</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8.127621</td>\n",
       "      <td>0.009712</td>\n",
       "      <td>31</td>\n",
       "      <td>0.05</td>\n",
       "      <td>200</td>\n",
       "      <td>-23.123058</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9.985648</td>\n",
       "      <td>0.010439</td>\n",
       "      <td>100</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100</td>\n",
       "      <td>-23.163416</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14.699530</td>\n",
       "      <td>0.013030</td>\n",
       "      <td>50</td>\n",
       "      <td>0.05</td>\n",
       "      <td>200</td>\n",
       "      <td>-23.225964</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  mean_score_time param_num_leaves param_learning_rate  \\\n",
       "0      36.862517         0.011527              100                0.01   \n",
       "2       4.664219         0.011364               31                0.05   \n",
       "8       8.127621         0.009712               31                0.05   \n",
       "5       9.985648         0.010439              100                0.05   \n",
       "1      14.699530         0.013030               50                0.05   \n",
       "\n",
       "  param_n_estimators  mean_test_score  rank_test_score  \n",
       "0                500       -22.970448                1  \n",
       "2                100       -23.059453                2  \n",
       "8                200       -23.123058                3  \n",
       "5                100       -23.163416                4  \n",
       "1                200       -23.225964                5  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 22.97\n"
     ]
    }
   ],
   "source": [
    "results = pd.DataFrame(randomized_search.cv_results_)\n",
    "lgbm_rmse = round(-randomized_search.best_score_, 2)\n",
    "\n",
    "display(results[['mean_fit_time', 'mean_score_time', 'param_num_leaves', 'param_learning_rate', 'param_n_estimators', 'mean_test_score', 'rank_test_score']]\n",
    "        .sort_values(by='mean_test_score', ascending=False)\n",
    "        .head())\n",
    "print('RMSE:', lgbm_rmse)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best parameters of the model are `num_leaves` = 31; `learning_rate` = 0.05, `n_estimators` = 100. At these parameters the model is trained much faster than the others, but `RMSE` does not differ much from the best one. This model takes much longer to train than `LinearRegression`, and the `RMSE` metric of both models is almost the same"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DecisionTreeRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a parameter grid for the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_grid = {\n",
    "    'max_depth': [None, 10, 40],\n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    'min_samples_leaf': [1, 2, 5]\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking for the best model metric and hyperparameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 1.53 s\n",
      "Wall time: 2.77 s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=DecisionTreeRegressor(random_state=42), n_jobs=-1,\n",
       "                   param_distributions={&#x27;max_depth&#x27;: [None, 10, 40],\n",
       "                                        &#x27;min_samples_leaf&#x27;: [1, 2, 5],\n",
       "                                        &#x27;min_samples_split&#x27;: [2, 5, 10]},\n",
       "                   random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomizedSearchCV</label><div class=\"sk-toggleable__content\"><pre>RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=DecisionTreeRegressor(random_state=42), n_jobs=-1,\n",
       "                   param_distributions={&#x27;max_depth&#x27;: [None, 10, 40],\n",
       "                                        &#x27;min_samples_leaf&#x27;: [1, 2, 5],\n",
       "                                        &#x27;min_samples_split&#x27;: [2, 5, 10]},\n",
       "                   random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor(random_state=42)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor(random_state=42)</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomizedSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None),\n",
       "                   estimator=DecisionTreeRegressor(random_state=42), n_jobs=-1,\n",
       "                   param_distributions={'max_depth': [None, 10, 40],\n",
       "                                        'min_samples_leaf': [1, 2, 5],\n",
       "                                        'min_samples_split': [2, 5, 10]},\n",
       "                   random_state=42,\n",
       "                   scoring=make_scorer(rmse, greater_is_better=False))"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "randomized_search = RandomizedSearchCV(DecisionTreeRegressor(random_state=RANDOM_STATE),\n",
    "                                        param_grid, \n",
    "                                        cv=tscv,\n",
    "                                        scoring=rmse_scorer,\n",
    "                                        n_jobs=-1, \n",
    "                                        random_state=RANDOM_STATE)\n",
    "randomized_search.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Output the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>mean_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>param_max_depth</th>\n",
       "      <th>param_min_samples_split</th>\n",
       "      <th>param_min_samples_leaf</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.480674</td>\n",
       "      <td>0.007137</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>-30.500229</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.465992</td>\n",
       "      <td>0.006354</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>-30.500229</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.476263</td>\n",
       "      <td>0.006605</td>\n",
       "      <td>None</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>-31.260515</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.418669</td>\n",
       "      <td>0.003475</td>\n",
       "      <td>40</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>-31.260515</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.476562</td>\n",
       "      <td>0.004957</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>-31.767310</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  mean_score_time param_max_depth param_min_samples_split  \\\n",
       "6       0.480674         0.007137              10                       5   \n",
       "7       0.465992         0.006354              10                      10   \n",
       "0       0.476263         0.006605            None                      10   \n",
       "9       0.418669         0.003475              40                       2   \n",
       "8       0.476562         0.004957              10                       2   \n",
       "\n",
       "  param_min_samples_leaf  mean_test_score  rank_test_score  \n",
       "6                      5       -30.500229                1  \n",
       "7                      5       -30.500229                1  \n",
       "0                      5       -31.260515                3  \n",
       "9                      5       -31.260515                3  \n",
       "8                      2       -31.767310                5  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 30.5\n"
     ]
    }
   ],
   "source": [
    "results = pd.DataFrame(randomized_search.cv_results_)\n",
    "dt_rmse = round(-randomized_search.best_score_, 2)\n",
    "\n",
    "display(results[['mean_fit_time', 'mean_score_time', 'param_max_depth', 'param_min_samples_split', 'param_min_samples_leaf', 'mean_test_score', 'rank_test_score']]\n",
    "        .sort_values(by='mean_test_score', ascending=False)\n",
    "        .head())\n",
    "print('RMSE:', dt_rmse)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best parameters for this model are `max_depth` = 10, `min_samples_split` = 10, `min_samples_leaf` = 5. With these parameters, the model is trained quite fast and has the highest `RMSE`. This model is trained almost like `LinearRegression`, but its `RMSE` is much higher than the others"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check the best model on a test sample"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, the best model turned out to be `LinearRegression`. It learns faster than others and gives the most accurate results, so we will use it on the test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_model = LinearRegression()\n",
    "best_model.fit(X_train, y_train)\n",
    "\n",
    "y_pred = best_model.predict(X_test)\n",
    "residuals = y_test - y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 34.36356789997796\n",
      "R2: 0.6595648537336555\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(f'RMSE: {rmse(y_test, y_pred)}')\n",
    "print(f'R2: {r2_score(y_test, y_pred)}')\n",
    "\n",
    "\n",
    "plt.scatter(y_pred, residuals, alpha=0.5)\n",
    "plt.title('Residuals Graph')\n",
    "plt.xlabel('Predictions')\n",
    "plt.ylabel('Residuals')\n",
    "plt.axhline(0, color='red', linestyle='--', linewidth=2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, the model is highly erroneous, but `RMSE` on the test sample turned out to be 34.4, which is lower than the specified criterion (`RMSE` <= 48). The task can be considered as fulfilled"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just in case, let's check the `RMSE` metric obtained by predicting the previous series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 59.27241199351863\n"
     ]
    }
   ],
   "source": [
    "y_pred_shifted = y_test.shift()\n",
    "y_pred_shifted.iloc[0] = y_test.iloc[-1]\n",
    "\n",
    "print('RMSE:', rmse(y_test, y_pred_shifted))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our model does a much better job"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualise the result of the model and compare it with the real values on the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Num Orders')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred_linear = pd.Series(y_pred, index=y_test.index)\n",
    "plt.figure(figsize=(20,5))\n",
    "\n",
    "# Lineplot with real values\n",
    "sns.lineplot(y=y_test.values, x=y_test.index, label='Real Values')\n",
    "\n",
    "# Lineplot with predicted values\n",
    "sns.lineplot(y=pred_linear.values, x=pred_linear.index, linewidth=2, label='Model Predictions')\n",
    "\n",
    "plt.grid()\n",
    "plt.xlim(y_test.index.min(), y_test.index.max())\n",
    "plt.legend()\n",
    "plt.ylabel('Quantity')\n",
    "plt.xlabel('Date')\n",
    "plt.title('Num Orders')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- The real values and model predictions have similar trends and patterns, indicating that the model approximates the data reasonably well;\n",
    "- The model appears to be reasonably accurate as the line of predictions follows the line of real values. However, there are times when the model does not accurately predict spikes or dips, which is especially noticeable at large peaks."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task Description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We were tasked with building a model that would be able to determine the number of taxi orders for the next hour.\n",
    "\n",
    "Criteria that were important to the customer:\n",
    "- The value of the RMSE metric on the test sample should not be greater than 48."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Description of work steps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. We downloaded the data and resampled it one hour at a time;\n",
    "2. We analysed the data for trends and seasonal components: there is a trend for higher order values; there is daily seasonality; there is weekly seasonality;\n",
    "4. Added new features to the data and split the data into samples;\n",
    "6. Tested three models (`LinearRegression`, `LGBMRegressor`, `DecisionTreeRegressor`) and determined the best one (based on customer criteria)."
   ]
  },
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   "source": [
    "### Final conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We tested three models:\n",
    "\n",
    "- `LinearRegression` - the model's `RMSE` metric was 22.69; this model has a training time of 0.03 seconds and a prediction rate of 0.003 seconds\n",
    "\n",
    "- `LGBMegressor` (`num_leaves` = 31; `learning_rate` = 0.05, `n_estimators` = 100) - the model's `RMSE` metric was 23.06; this model has a training time of 4.66 seconds and a prediction rate of 0.01 seconds\n",
    "\n",
    "- `DecisionTreeRegressor` (`max_depth` = 10, `min_samples_split` = 10, `min_samples_leaf` = 5) - the `RMSE` metric of the model was 30.5; the training time of such a model is 0.47 seconds and the prediction speed is 0.006 seconds\n",
    "\t\n",
    "So, the best model is `LinearRegression` as its `RMSE` metric is the lowest, and the model is trained and makes predictions in the shortest time. Thus, it should be used for ordering. Also, we checked the metrics of the model on the test sample: `RMSE` of the model is 34.4, which passes the customer's criterion (`RMSE` <= 48)."
   ]
  }
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