BikeSales Modelling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "source": [
    "# BikeSales Modelling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "sns.set()\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "#Load the data and infer the date format for the date features\n",
    "\n",
    "df = pd.read_csv('clean_sport2.csv', \n",
    "                  parse_dates=['First_Seen','Last_Seen','Last_Modified'], \n",
    "                  infer_datetime_format=True)\n",
    "df.head()\n",
    "sport = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "# sport.drop(['Body','Drive_Type','Fuel_Type','Gear_Change_Method','Gear_Type',\n",
    "#             'Network_ID','Registration_Plate','URL','Windscreen'], axis=1, inplace=True)\n",
    "\n",
    "# SELECT INDIVIDUAL FEATURES - we want to simplify the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
    "from sklearn.linear_model import LogisticRegression, LogisticRegressionCV, LinearRegression\n",
    "from sklearn.linear_model import LassoCV, RidgeCV\n",
    "from sklearn.linear_model import PassiveAggressiveRegressor\n",
    "from sklearn.ensemble import BaggingRegressor\n",
    "from sklearn.svm import SVR\n",
    "\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# Regression metrics\n",
    "from sklearn.metrics import explained_variance_score, mean_squared_error\n",
    "from sklearn.metrics import mean_absolute_error, r2_score\n",
    "\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import classification_report\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "def add_dummy_variables(df, categorical_features):\n",
    "    \n",
    "    additional = pd.get_dummies(df[categorical_features])\n",
    "    df[additional.columns] = additional\n",
    "    return df.drop(categorical_features, axis=1)\n",
    "\n",
    "def feature_plot(model,X,top=10):\n",
    "    \n",
    "    feats_imp = pd.DataFrame(model.feature_importances_, index=X.columns, columns=['FeatureImportance'])\n",
    "    feats_imp = feats_imp.sort_values('FeatureImportance', ascending=False)[:top]\n",
    "\n",
    "    feats_imp.plot(kind='barh', figsize=(12,6), legend=False)\n",
    "    plt.title('Feature Importance from XgBoost Classifier')\n",
    "    sns.despine(left=True, bottom=True)\n",
    "    plt.gca().invert_yaxis()\n",
    "    \n",
    "def plot_accuracy_predictions(y_test, pred):\n",
    "    fig, ax = plt.subplots(figsize=(12,10))\n",
    "    ax.scatter(y_test,pred)\n",
    "    ax.plot([y_test(), y_test.max()], [y_test.min(), y_test.max()], 'r--', lw=0.8)\n",
    "    ax.set_xlabel('Measured');\n",
    "    ax.set_ylabel('Predicted');\n",
    "    ax.set_title('Accuracy of Predictions');\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2555, 69)\n",
      "(2555, 27)\n"
     ]
    }
   ],
   "source": [
    "print (sport.shape)\n",
    "sport_numbers = sport.select_dtypes(include='number')\n",
    "print (sport_numbers.shape)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Bore',\n",
       " 'Compression_Ratio',\n",
       " 'Cylinders',\n",
       " 'Dry_Weight',\n",
       " 'Engine_Description',\n",
       " 'Front_Brake_Diameter',\n",
       " 'Front_Suspension_Travel',\n",
       " 'Fuel_Reserve_Capacity',\n",
       " 'Fuel_Tank_Capacity',\n",
       " 'Ground_Clearance',\n",
       " 'Height',\n",
       " 'Kilometers',\n",
       " 'Length',\n",
       " 'Maximum_Power',\n",
       " 'Maximum_Power_RPM',\n",
       " 'Oil_Capacity',\n",
       " 'Price',\n",
       " 'Rear_Brake_Diameter',\n",
       " 'Rear_Suspension_Travel',\n",
       " 'Seat_Height',\n",
       " 'Stroke',\n",
       " 'Trail',\n",
       " 'Warranty_in_Months_from_First_Registration',\n",
       " 'Wheelbase',\n",
       " 'Width',\n",
       " 'Age',\n",
       " 'Time_to_Sale',\n",
       " 'ABS',\n",
       " 'Bike',\n",
       " 'Cam_Type',\n",
       " 'Carburettor',\n",
       " 'Charging_Method',\n",
       " 'Clutch_Type',\n",
       " 'Colour',\n",
       " 'Cooling',\n",
       " 'Country_of_Origin',\n",
       " 'Engine_Config',\n",
       " 'Engine_Immobiliser',\n",
       " 'Engine_Type',\n",
       " 'Exhaust_Config',\n",
       " 'First_Seen',\n",
       " 'Frame_Material',\n",
       " 'Front_Brake_Caliper(s)',\n",
       " 'Front_Brake_Description',\n",
       " 'Front_Suspension',\n",
       " 'Ignition',\n",
       " 'Induction_System',\n",
       " 'Last_Modified',\n",
       " 'Last_Seen',\n",
       " 'Learner_Approved',\n",
       " 'Linked_Braking_System',\n",
       " 'Lock_Type',\n",
       " 'Rear_Brake_Caliper(s)',\n",
       " 'Rear_Brake_Description',\n",
       " 'Rear_Suspension',\n",
       " 'Registration_Expiry',\n",
       " 'Roadworthy_Safety_Certificate',\n",
       " 'Saddlebags_Panniers',\n",
       " 'Seating_Position',\n",
       " 'Side_Stand',\n",
       " 'Side_Stand_Start_Inhibitor',\n",
       " 'Starter',\n",
       " 'Swingarm_Type',\n",
       " 'Traction_Control',\n",
       " 'Warranty_KMs',\n",
       " 'Wheel_Type',\n",
       " 'Seller',\n",
       " 'Brand',\n",
       " 'Model']"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(sport.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "data": {
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       "\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>Bore</th>\n",
       "      <th>Compression_Ratio</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Dry_Weight</th>\n",
       "      <th>Engine_Description</th>\n",
       "      <th>Front_Brake_Diameter</th>\n",
       "      <th>Front_Suspension_Travel</th>\n",
       "      <th>Fuel_Reserve_Capacity</th>\n",
       "      <th>Fuel_Tank_Capacity</th>\n",
       "      <th>Ground_Clearance</th>\n",
       "      <th>...</th>\n",
       "      <th>Side_Stand</th>\n",
       "      <th>Side_Stand_Start_Inhibitor</th>\n",
       "      <th>Starter</th>\n",
       "      <th>Swingarm_Type</th>\n",
       "      <th>Traction_Control</th>\n",
       "      <th>Warranty_KMs</th>\n",
       "      <th>Wheel_Type</th>\n",
       "      <th>Seller</th>\n",
       "      <th>Brand</th>\n",
       "      <th>Model</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>74.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>929.0</td>\n",
       "      <td>290.235019</td>\n",
       "      <td>157.464301</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>18.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Electric</td>\n",
       "      <td>Dual Sided</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Spoke</td>\n",
       "      <td>Private</td>\n",
       "      <td>Honda</td>\n",
       "      <td>Cbr900rr fireblade 929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>No</td>\n",
       "      <td>Electric</td>\n",
       "      <td>Dual Sided</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Spoke</td>\n",
       "      <td>Private</td>\n",
       "      <td>Kawasaki</td>\n",
       "      <td>Ninja 250r ex250j</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>No</td>\n",
       "      <td>Electric</td>\n",
       "      <td>Dual Sided</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Spoke</td>\n",
       "      <td>Private</td>\n",
       "      <td>Kawasaki</td>\n",
       "      <td>Ninja 250r special edition</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>No</td>\n",
       "      <td>Electric</td>\n",
       "      <td>Dual Sided</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Spoke</td>\n",
       "      <td>Private</td>\n",
       "      <td>Kawasaki</td>\n",
       "      <td>Ninja 250r ex250j</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>No</td>\n",
       "      <td>Electric</td>\n",
       "      <td>Dual Sided</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Spoke</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Kawasaki</td>\n",
       "      <td>Ninja 250r ex250j</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 69 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Bore  Compression_Ratio  Cylinders  Dry_Weight  Engine_Description  \\\n",
       "0  74.0               11.0        4.0       170.0               929.0   \n",
       "1  62.0               11.0        2.0       152.0               250.0   \n",
       "2  62.0               11.0        2.0       130.0               250.0   \n",
       "3  62.0               11.0        2.0       152.0               250.0   \n",
       "4  62.0               11.0        2.0       152.0               250.0   \n",
       "\n",
       "   Front_Brake_Diameter  Front_Suspension_Travel  Fuel_Reserve_Capacity  \\\n",
       "0            290.235019               157.464301               4.000000   \n",
       "1            290.000000               120.000000               3.440919   \n",
       "2            290.000000               120.000000               3.440919   \n",
       "3            290.000000               120.000000               3.440919   \n",
       "4            290.000000               120.000000               3.440919   \n",
       "\n",
       "   Fuel_Tank_Capacity  Ground_Clearance             ...              \\\n",
       "0                18.0             138.0             ...               \n",
       "1                18.0             130.0             ...               \n",
       "2                18.0             135.0             ...               \n",
       "3                18.0             130.0             ...               \n",
       "4                18.0             130.0             ...               \n",
       "\n",
       "   Side_Stand  Side_Stand_Start_Inhibitor   Starter  Swingarm_Type  \\\n",
       "0         Yes                          No  Electric     Dual Sided   \n",
       "1    Standard                          No  Electric     Dual Sided   \n",
       "2    Standard                          No  Electric     Dual Sided   \n",
       "3    Standard                          No  Electric     Dual Sided   \n",
       "4    Standard                          No  Electric     Dual Sided   \n",
       "\n",
       "   Traction_Control  Warranty_KMs  Wheel_Type   Seller     Brand  \\\n",
       "0                No            No       Spoke  Private     Honda   \n",
       "1                No            No       Spoke  Private  Kawasaki   \n",
       "2                No            No       Spoke  Private  Kawasaki   \n",
       "3                No            No       Spoke  Private  Kawasaki   \n",
       "4                No            No       Spoke   Dealer  Kawasaki   \n",
       "\n",
       "                        Model  \n",
       "0      Cbr900rr fireblade 929  \n",
       "1           Ninja 250r ex250j  \n",
       "2  Ninja 250r special edition  \n",
       "3           Ninja 250r ex250j  \n",
       "4           Ninja 250r ex250j  \n",
       "\n",
       "[5 rows x 69 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sport.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "numerical_features = list(df.select_dtypes(include='number').columns)\n",
    "categorical_features = list(df.select_dtypes(exclude='number').columns)\n",
    "\n",
    "# categorical_features = ['Bike', 'Body', 'Colour', 'Cooling', 'Country_of_Origin', \n",
    "#                         'Engine_Config', 'Fuel_Type', 'State', 'Suburb', 'Seller', \n",
    "#                         'Brand', 'Model'] \n",
    "\n",
    "#categorical_features = ['Bike', 'Body', 'Brand', 'Model', 'Seller']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "sport = add_dummy_variables(sport, categorical_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Bore</th>\n",
       "      <th>Compression_Ratio</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Dry_Weight</th>\n",
       "      <th>Engine_Description</th>\n",
       "      <th>Front_Brake_Diameter</th>\n",
       "      <th>Front_Suspension_Travel</th>\n",
       "      <th>Fuel_Reserve_Capacity</th>\n",
       "      <th>Fuel_Tank_Capacity</th>\n",
       "      <th>Ground_Clearance</th>\n",
       "      <th>...</th>\n",
       "      <th>Model_f4 1000 abs</th>\n",
       "      <th>Model_f4 1000s corse</th>\n",
       "      <th>Model_f4 312 r 1000</th>\n",
       "      <th>Model_f4 312 r 1000 11</th>\n",
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       "      <th>Model_f4 750 s f4s 11</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>74.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>929.0</td>\n",
       "      <td>290.235019</td>\n",
       "      <td>157.464301</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>18.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.440919</td>\n",
       "      <td>18.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 654 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Bore  Compression_Ratio  Cylinders  Dry_Weight  Engine_Description  \\\n",
       "0  74.0               11.0        4.0       170.0               929.0   \n",
       "1  62.0               11.0        2.0       152.0               250.0   \n",
       "2  62.0               11.0        2.0       130.0               250.0   \n",
       "3  62.0               11.0        2.0       152.0               250.0   \n",
       "4  62.0               11.0        2.0       152.0               250.0   \n",
       "\n",
       "   Front_Brake_Diameter  Front_Suspension_Travel  Fuel_Reserve_Capacity  \\\n",
       "0            290.235019               157.464301               4.000000   \n",
       "1            290.000000               120.000000               3.440919   \n",
       "2            290.000000               120.000000               3.440919   \n",
       "3            290.000000               120.000000               3.440919   \n",
       "4            290.000000               120.000000               3.440919   \n",
       "\n",
       "   Fuel_Tank_Capacity  Ground_Clearance        ...         Model_f4 1000 abs  \\\n",
       "0                18.0             138.0        ...                         0   \n",
       "1                18.0             130.0        ...                         0   \n",
       "2                18.0             135.0        ...                         0   \n",
       "3                18.0             130.0        ...                         0   \n",
       "4                18.0             130.0        ...                         0   \n",
       "\n",
       "   Model_f4 1000s corse  Model_f4 312 r 1000  Model_f4 312 r 1000 11  \\\n",
       "0                     0                    0                       0   \n",
       "1                     0                    0                       0   \n",
       "2                     0                    0                       0   \n",
       "3                     0                    0                       0   \n",
       "4                     0                    0                       0   \n",
       "\n",
       "   Model_f4 750 s  Model_f4 750 s f4s 11  Model_f4 r  Model_f4 rr  \\\n",
       "0               0                      0           0            0   \n",
       "1               0                      0           0            0   \n",
       "2               0                      0           0            0   \n",
       "3               0                      0           0            0   \n",
       "4               0                      0           0            0   \n",
       "\n",
       "   Model_f4 rr 1000  Model_f4ago 1000  \n",
       "0                 0                 0  \n",
       "1                 0                 0  \n",
       "2                 0                 0  \n",
       "3                 0                 0  \n",
       "4                 0                 0  \n",
       "\n",
       "[5 rows x 654 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sport.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "sport_df = sport.select_dtypes(include='number')\n",
    "\n",
    "target = 'Price'\n",
    "features = list(set(sport_df.columns) - set([target]))\n",
    "#features = ['Age']\n",
    "\n",
    "sc = StandardScaler()\n",
    "sc.fit(sport_df[features])\n",
    "s = sc.transform(sport_df[features])\n",
    "scaleSport = pd.DataFrame(s,columns=features)\n",
    "\n",
    "X = scaleSport[features]\n",
    "y = sport_df[target]\n",
    "\n",
    "\n",
    "#X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "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>Bike_CBR600RR MY09 Road Manual 6sp</th>\n",
       "      <th>Colour_purple</th>\n",
       "      <th>Exhaust_Config_2 into 1</th>\n",
       "      <th>Cooling_Liquid &amp; Fan</th>\n",
       "      <th>Registration_Expiry_01/04/2020</th>\n",
       "      <th>Model_Ninja 300 special edition</th>\n",
       "      <th>Starter_Electric</th>\n",
       "      <th>Bike_Ninja ZX-6R  Road Manual 6sp 636cc</th>\n",
       "      <th>Side_Stand_Standard</th>\n",
       "      <th>Model_Ninja zx 6r 636</th>\n",
       "      <th>...</th>\n",
       "      <th>Bike_F3 800 RC Road Manual 6sp 800cc</th>\n",
       "      <th>Bike_Ninja 400 Special Edition MY19 Road Manual 6sp</th>\n",
       "      <th>Carburettor_Carburettor</th>\n",
       "      <th>Bike_GSX-R1000  GSX-R1000 - 988cc</th>\n",
       "      <th>Registration_Expiry_01/04/2017</th>\n",
       "      <th>Carburettor_Constant velocity</th>\n",
       "      <th>Engine_Config_Inline</th>\n",
       "      <th>Bike_Daytona 675 R MY12 Road Manual 6sp</th>\n",
       "      <th>Bike_Daytona 675 R</th>\n",
       "      <th>Bike_Ninja 250R Special Edition MY12 Road Manual 6sp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "      <td>2.555000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.557680e-16</td>\n",
       "      <td>-4.357028e-16</td>\n",
       "      <td>-3.867313e-16</td>\n",
       "      <td>9.142502e-17</td>\n",
       "      <td>1.014507e-15</td>\n",
       "      <td>-1.239224e-15</td>\n",
       "      <td>1.172839e-15</td>\n",
       "      <td>1.034669e-15</td>\n",
       "      <td>6.026056e-16</td>\n",
       "      <td>-6.279495e-16</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.383422e-16</td>\n",
       "      <td>1.529951e-16</td>\n",
       "      <td>1.430564e-15</td>\n",
       "      <td>7.747065e-16</td>\n",
       "      <td>1.474359e-16</td>\n",
       "      <td>-2.548038e-15</td>\n",
       "      <td>-8.739259e-16</td>\n",
       "      <td>4.389183e-16</td>\n",
       "      <td>6.167278e-16</td>\n",
       "      <td>1.143826e-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "      <td>1.000196e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-5.576098e-01</td>\n",
       "      <td>-1.615686e-01</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>-9.319524e-02</td>\n",
       "      <td>-2.258318e+01</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>-1.173347e+00</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>-4.428074e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-2.703304e-01</td>\n",
       "      <td>-1.076923e+00</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-6.575636e-02</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-5.576098e-01</td>\n",
       "      <td>-1.615686e-01</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>-9.319524e-02</td>\n",
       "      <td>4.428074e-02</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>-1.173347e+00</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>-4.428074e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-2.703304e-01</td>\n",
       "      <td>-1.076923e+00</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-6.575636e-02</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-5.576098e-01</td>\n",
       "      <td>-1.615686e-01</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>-9.319524e-02</td>\n",
       "      <td>4.428074e-02</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>8.522625e-01</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>-4.428074e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-2.703304e-01</td>\n",
       "      <td>9.285714e-01</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-6.575636e-02</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-5.576098e-01</td>\n",
       "      <td>-1.615686e-01</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>-9.319524e-02</td>\n",
       "      <td>4.428074e-02</td>\n",
       "      <td>-9.103457e-02</td>\n",
       "      <td>8.522625e-01</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-5.241424e-02</td>\n",
       "      <td>-4.428074e-02</td>\n",
       "      <td>-1.978744e-02</td>\n",
       "      <td>-2.703304e-01</td>\n",
       "      <td>9.285714e-01</td>\n",
       "      <td>-3.428627e-02</td>\n",
       "      <td>-6.575636e-02</td>\n",
       "      <td>-2.798914e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.053712e+01</td>\n",
       "      <td>2.916619e+01</td>\n",
       "      <td>1.793369e+00</td>\n",
       "      <td>6.189321e+00</td>\n",
       "      <td>1.098484e+01</td>\n",
       "      <td>1.073016e+01</td>\n",
       "      <td>4.428074e-02</td>\n",
       "      <td>1.098484e+01</td>\n",
       "      <td>8.522625e-01</td>\n",
       "      <td>1.907878e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>3.572814e+01</td>\n",
       "      <td>5.053712e+01</td>\n",
       "      <td>1.907878e+01</td>\n",
       "      <td>2.258318e+01</td>\n",
       "      <td>5.053712e+01</td>\n",
       "      <td>3.699177e+00</td>\n",
       "      <td>9.285714e-01</td>\n",
       "      <td>2.916619e+01</td>\n",
       "      <td>1.520765e+01</td>\n",
       "      <td>3.572814e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 653 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Bike_CBR600RR MY09 Road Manual 6sp  Colour_purple  \\\n",
       "count                        2.555000e+03   2.555000e+03   \n",
       "mean                         1.557680e-16  -4.357028e-16   \n",
       "std                          1.000196e+00   1.000196e+00   \n",
       "min                         -1.978744e-02  -3.428627e-02   \n",
       "25%                         -1.978744e-02  -3.428627e-02   \n",
       "50%                         -1.978744e-02  -3.428627e-02   \n",
       "75%                         -1.978744e-02  -3.428627e-02   \n",
       "max                          5.053712e+01   2.916619e+01   \n",
       "\n",
       "       Exhaust_Config_2 into 1  Cooling_Liquid & Fan  \\\n",
       "count             2.555000e+03          2.555000e+03   \n",
       "mean             -3.867313e-16          9.142502e-17   \n",
       "std               1.000196e+00          1.000196e+00   \n",
       "min              -5.576098e-01         -1.615686e-01   \n",
       "25%              -5.576098e-01         -1.615686e-01   \n",
       "50%              -5.576098e-01         -1.615686e-01   \n",
       "75%              -5.576098e-01         -1.615686e-01   \n",
       "max               1.793369e+00          6.189321e+00   \n",
       "\n",
       "       Registration_Expiry_01/04/2020  Model_Ninja 300 special edition  \\\n",
       "count                    2.555000e+03                     2.555000e+03   \n",
       "mean                     1.014507e-15                    -1.239224e-15   \n",
       "std                      1.000196e+00                     1.000196e+00   \n",
       "min                     -9.103457e-02                    -9.319524e-02   \n",
       "25%                     -9.103457e-02                    -9.319524e-02   \n",
       "50%                     -9.103457e-02                    -9.319524e-02   \n",
       "75%                     -9.103457e-02                    -9.319524e-02   \n",
       "max                      1.098484e+01                     1.073016e+01   \n",
       "\n",
       "       Starter_Electric  Bike_Ninja ZX-6R  Road Manual 6sp 636cc  \\\n",
       "count      2.555000e+03                             2.555000e+03   \n",
       "mean       1.172839e-15                             1.034669e-15   \n",
       "std        1.000196e+00                             1.000196e+00   \n",
       "min       -2.258318e+01                            -9.103457e-02   \n",
       "25%        4.428074e-02                            -9.103457e-02   \n",
       "50%        4.428074e-02                            -9.103457e-02   \n",
       "75%        4.428074e-02                            -9.103457e-02   \n",
       "max        4.428074e-02                             1.098484e+01   \n",
       "\n",
       "       Side_Stand_Standard  Model_Ninja zx 6r 636  \\\n",
       "count         2.555000e+03           2.555000e+03   \n",
       "mean          6.026056e-16          -6.279495e-16   \n",
       "std           1.000196e+00           1.000196e+00   \n",
       "min          -1.173347e+00          -5.241424e-02   \n",
       "25%          -1.173347e+00          -5.241424e-02   \n",
       "50%           8.522625e-01          -5.241424e-02   \n",
       "75%           8.522625e-01          -5.241424e-02   \n",
       "max           8.522625e-01           1.907878e+01   \n",
       "\n",
       "                               ...                           \\\n",
       "count                          ...                            \n",
       "mean                           ...                            \n",
       "std                            ...                            \n",
       "min                            ...                            \n",
       "25%                            ...                            \n",
       "50%                            ...                            \n",
       "75%                            ...                            \n",
       "max                            ...                            \n",
       "\n",
       "       Bike_F3 800 RC Road Manual 6sp 800cc  \\\n",
       "count                          2.555000e+03   \n",
       "mean                          -2.383422e-16   \n",
       "std                            1.000196e+00   \n",
       "min                           -2.798914e-02   \n",
       "25%                           -2.798914e-02   \n",
       "50%                           -2.798914e-02   \n",
       "75%                           -2.798914e-02   \n",
       "max                            3.572814e+01   \n",
       "\n",
       "       Bike_Ninja 400 Special Edition MY19 Road Manual 6sp  \\\n",
       "count                                       2.555000e+03     \n",
       "mean                                        1.529951e-16     \n",
       "std                                         1.000196e+00     \n",
       "min                                        -1.978744e-02     \n",
       "25%                                        -1.978744e-02     \n",
       "50%                                        -1.978744e-02     \n",
       "75%                                        -1.978744e-02     \n",
       "max                                         5.053712e+01     \n",
       "\n",
       "       Carburettor_Carburettor  Bike_GSX-R1000  GSX-R1000 - 988cc  \\\n",
       "count             2.555000e+03                       2.555000e+03   \n",
       "mean              1.430564e-15                       7.747065e-16   \n",
       "std               1.000196e+00                       1.000196e+00   \n",
       "min              -5.241424e-02                      -4.428074e-02   \n",
       "25%              -5.241424e-02                      -4.428074e-02   \n",
       "50%              -5.241424e-02                      -4.428074e-02   \n",
       "75%              -5.241424e-02                      -4.428074e-02   \n",
       "max               1.907878e+01                       2.258318e+01   \n",
       "\n",
       "       Registration_Expiry_01/04/2017  Carburettor_Constant velocity  \\\n",
       "count                    2.555000e+03                   2.555000e+03   \n",
       "mean                     1.474359e-16                  -2.548038e-15   \n",
       "std                      1.000196e+00                   1.000196e+00   \n",
       "min                     -1.978744e-02                  -2.703304e-01   \n",
       "25%                     -1.978744e-02                  -2.703304e-01   \n",
       "50%                     -1.978744e-02                  -2.703304e-01   \n",
       "75%                     -1.978744e-02                  -2.703304e-01   \n",
       "max                      5.053712e+01                   3.699177e+00   \n",
       "\n",
       "       Engine_Config_Inline  Bike_Daytona 675 R MY12 Road Manual 6sp  \\\n",
       "count          2.555000e+03                             2.555000e+03   \n",
       "mean          -8.739259e-16                             4.389183e-16   \n",
       "std            1.000196e+00                             1.000196e+00   \n",
       "min           -1.076923e+00                            -3.428627e-02   \n",
       "25%           -1.076923e+00                            -3.428627e-02   \n",
       "50%            9.285714e-01                            -3.428627e-02   \n",
       "75%            9.285714e-01                            -3.428627e-02   \n",
       "max            9.285714e-01                             2.916619e+01   \n",
       "\n",
       "       Bike_Daytona 675 R  \\\n",
       "count        2.555000e+03   \n",
       "mean         6.167278e-16   \n",
       "std          1.000196e+00   \n",
       "min         -6.575636e-02   \n",
       "25%         -6.575636e-02   \n",
       "50%         -6.575636e-02   \n",
       "75%         -6.575636e-02   \n",
       "max          1.520765e+01   \n",
       "\n",
       "       Bike_Ninja 250R Special Edition MY12 Road Manual 6sp  \n",
       "count                                       2.555000e+03     \n",
       "mean                                        1.143826e-15     \n",
       "std                                         1.000196e+00     \n",
       "min                                        -2.798914e-02     \n",
       "25%                                        -2.798914e-02     \n",
       "50%                                        -2.798914e-02     \n",
       "75%                                        -2.798914e-02     \n",
       "max                                         3.572814e+01     \n",
       "\n",
       "[8 rows x 653 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaleSport.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def adjusted_r2(r2, n, k):\n",
    "    return 1 - (1-r2)*((n-1)/(n-k-1)) \n",
    "\n",
    "\n",
    "\n",
    "def run_model(df, features, y):\n",
    "\n",
    "    X = df[list(set(df.select_dtypes(include='number').columns) - set('Price'))]\n",
    "\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1, test_size=0.3)\n",
    "\n",
    "\n",
    "    models = []\n",
    "\n",
    "    models.append((\"LassoCV\",LassoCV(cv=5)))\n",
    "    models.append((\"LinearRegression\",LinearRegression()))\n",
    "    models.append((\"PassiveAggressiveRegressor\",PassiveAggressiveRegressor()))\n",
    "    models.append((\"RidgeCV\",RidgeCV(cv=5)))\n",
    "    models.append((\"Bagging\",BaggingRegressor()))\n",
    "    models.append((\"SVR\",SVR()))\n",
    "\n",
    "    results = []\n",
    "    names = []\n",
    "    n,k = X_train[features].shape\n",
    "\n",
    "    for name, model in models:\n",
    "        score = cross_val_score(model, X_train[features], y_train,  cv=5)\n",
    "        \n",
    "        result = adjusted_r2(score,n,k)\n",
    "        #result = score\n",
    "        names.append(name)\n",
    "        results.append(result)\n",
    "\n",
    "    for i in range(len(names)):\n",
    "        print(names[i],results[i].mean())\n",
    "    \n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "bike_cols = [col for col in sport_df.columns if 'Bike' in col]\n",
    "brand_cols = [col for col in sport_df.columns if 'Brand' in col]\n",
    "model_cols = [col for col in sport_df.columns if 'Model' in col]\n",
    "niave_feature = ['Kilometers','Age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "#run_model(scaleSport, niave_feature, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LassoCV 0.10980277819450399\n",
      "LinearRegression 0.12555495127724445\n",
      "PassiveAggressiveRegressor -7740.137040943198\n",
      "RidgeCV 0.12555433578782826\n",
      "Bagging 0.04129522825924352\n",
      "SVR -0.12117913585670878\n"
     ]
    }
   ],
   "source": [
    "run_model(sport_df, niave_feature, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "#run_model(scaleSport, bike_cols, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LassoCV 0.7084228026179725\n",
      "LinearRegression -1.3881992397439972e+25\n",
      "PassiveAggressiveRegressor -0.6764575765023041\n",
      "RidgeCV 0.7204110102221719\n",
      "Bagging 0.5624577196623014\n",
      "SVR -0.33406803203486096\n"
     ]
    }
   ],
   "source": [
    "run_model(sport_df, bike_cols, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "#run_model(scaleSport, brand_cols, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LassoCV 0.3671031454105404\n",
      "LinearRegression -3.800209241128709e+23\n",
      "PassiveAggressiveRegressor -0.4028246464756073\n",
      "RidgeCV 0.3661082422023708\n",
      "Bagging 0.3684013150436476\n",
      "SVR -0.12534868322892295\n"
     ]
    }
   ],
   "source": [
    "run_model(sport_df, brand_cols, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "#run_model(scaleSport, model_cols, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LassoCV 0.7531863349851358\n",
      "LinearRegression -2.729344360411598e+24\n",
      "PassiveAggressiveRegressor -0.5413557402207004\n",
      "RidgeCV 0.7587249400357449\n",
      "Bagging 0.7306862087299921\n",
      "SVR -0.22768801806748287\n"
     ]
    }
   ],
   "source": [
    "run_model(sport_df, model_cols, sport_df[target])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Added feature Maximum_Power with R^2 = 0.547 and adjusted R^2 = 0.546\n",
      "Added feature Kilometers with R^2 = 0.683 and adjusted R^2 = 0.682\n",
      "Added feature Traction_Control_No with R^2 = 0.750 and adjusted R^2 = 0.749\n",
      "Added feature Bore with R^2 = 0.778 and adjusted R^2 = 0.777\n",
      "Added feature Time_to_Sale with R^2 = 0.793 and adjusted R^2 = 0.791\n",
      "Added feature Age  with R^2 = 0.803 and adjusted R^2 = 0.802\n",
      "Added feature Cylinders with R^2 = 0.812 and adjusted R^2 = 0.810\n",
      "Added feature Model_Yzf r1m with R^2 = 0.818 and adjusted R^2 = 0.816\n",
      "Added feature Cam_Type_DOHC (Double Over Head Cam) with R^2 = 0.825 and adjusted R^2 = 0.822\n",
      "Added feature Model_Ninja zx 10r krt abs replica with R^2 = 0.831 and adjusted R^2 = 0.828\n",
      "Added feature Colour_none with R^2 = 0.837 and adjusted R^2 = 0.834\n",
      "Added feature Ignition_Digital with R^2 = 0.841 and adjusted R^2 = 0.838\n",
      "Added feature Side_Stand_Start_Inhibitor_Standard with R^2 = 0.845 and adjusted R^2 = 0.842\n",
      "Added feature Model_1199 panigale r abs with R^2 = 0.849 and adjusted R^2 = 0.846\n",
      "Added feature Dry_Weight with R^2 = 0.852 and adjusted R^2 = 0.849\n",
      "Added feature Linked_Braking_System_Part-Integral with R^2 = 0.856 and adjusted R^2 = 0.853\n",
      "Added feature Bike_F3 800 RC Road Manual 6sp 800cc with R^2 = 0.859 and adjusted R^2 = 0.856\n",
      "Added feature Bike_1098S Tri Colore Road Manual 6sp 1098cc with R^2 = 0.863 and adjusted R^2 = 0.859\n",
      "Added feature Model_1198 s corse edition with R^2 = 0.866 and adjusted R^2 = 0.863\n",
      "Added feature Learner_Approved_No with R^2 = 0.869 and adjusted R^2 = 0.865\n",
      "Added feature Ignition_CDI (Capacitive Discharge Ignition) with R^2 = 0.872 and adjusted R^2 = 0.868\n",
      "Added feature Bike_GT650R EFI Road Manual 6sp 650cc with R^2 = 0.874 and adjusted R^2 = 0.870\n",
      "Added feature Bike_Ninja ZX-10R ABS MY17 Road Manual 6sp with R^2 = 0.876 and adjusted R^2 = 0.872\n",
      "Added feature Model_1198 s with R^2 = 0.878 and adjusted R^2 = 0.874\n",
      "Added feature Model_899 panigale with R^2 = 0.880 and adjusted R^2 = 0.875\n",
      "Added feature Carburettor_Constant velocity with R^2 = 0.881 and adjusted R^2 = 0.877\n",
      "Added feature Model_Gsx r1000r with R^2 = 0.883 and adjusted R^2 = 0.878\n",
      "Added feature Model_Ninja 300 se krt replica ex300a with R^2 = 0.884 and adjusted R^2 = 0.879\n",
      "Added feature Model_Ninja zx 10rr zx1000z with R^2 = 0.885 and adjusted R^2 = 0.881\n",
      "Added feature Rear_Suspension_Spring with R^2 = 0.887 and adjusted R^2 = 0.882\n",
      "Added feature Rear_Brake_Caliper(s)_Four Piston with R^2 = 0.888 and adjusted R^2 = 0.883\n",
      "Added feature Bike_YZF-R1M MY19 Road Manual 6sp with R^2 = 0.889 and adjusted R^2 = 0.884\n",
      "Added feature Model_Panigale v4 with R^2 = 0.890 and adjusted R^2 = 0.885\n",
      "Added feature Side_Stand_Yes with R^2 = 0.891 and adjusted R^2 = 0.886\n",
      "Added feature Bike_F4 1000 Road Manual 6sp 1000cc with R^2 = 0.892 and adjusted R^2 = 0.887\n",
      "Added feature Bike_Daytona 675 Road Manual 6sp 675cc with R^2 = 0.893 and adjusted R^2 = 0.888\n",
      "Added feature Model_Cbr1000rr fireblade with R^2 = 0.894 and adjusted R^2 = 0.889\n",
      "Added feature Model_Ninja zx 10r with R^2 = 0.895 and adjusted R^2 = 0.890\n",
      "Added feature Brand_Suzuki with R^2 = 0.896 and adjusted R^2 = 0.890\n",
      "Added feature Model_848 with R^2 = 0.897 and adjusted R^2 = 0.891\n",
      "Added feature Front_Brake_Diameter with R^2 = 0.898 and adjusted R^2 = 0.892\n",
      "Added feature Bike_Road Manual 6sp 1098cc with R^2 = 0.900 and adjusted R^2 = 0.894\n",
      "Added feature Bike_959 Panigale Road Manual 6sp 959cc with R^2 = 0.901 and adjusted R^2 = 0.895\n",
      "Added feature Bike_1199 Panigale Road Manual 6sp with R^2 = 0.902 and adjusted R^2 = 0.896\n",
      "Added feature Bike_ZX-12R Road Manual 6sp 1200cc with R^2 = 0.903 and adjusted R^2 = 0.897\n",
      "Added feature Registration_Expiry_01/01/1970 with R^2 = 0.904 and adjusted R^2 = 0.898\n",
      "Added feature Model_Cbr250r with R^2 = 0.905 and adjusted R^2 = 0.898\n",
      "Added feature Model_Ninja 300 abs ex300b with R^2 = 0.905 and adjusted R^2 = 0.899\n",
      "Added feature Model_Ninja 300 abs special edition with R^2 = 0.906 and adjusted R^2 = 0.900\n",
      "Added feature Rear_Brake_Caliper(s)_Double Piston with R^2 = 0.907 and adjusted R^2 = 0.901\n",
      "Added feature Oil_Capacity with R^2 = 0.908 and adjusted R^2 = 0.901\n",
      "Added feature Model_Rsv1000 mille with R^2 = 0.909 and adjusted R^2 = 0.902\n",
      "Added feature Bike_Road Manual 6sp 749cc with R^2 = 0.909 and adjusted R^2 = 0.903\n",
      "Added feature Model_Ninja 300 abs se 30th anniversary with R^2 = 0.910 and adjusted R^2 = 0.903\n",
      "Added feature Cam_Type_Desmodromic with R^2 = 0.911 and adjusted R^2 = 0.904\n",
      "Added feature Bike_TT600 Road Manual 6sp 600cc with R^2 = 0.912 and adjusted R^2 = 0.904\n",
      "Added feature Starter_Electric with R^2 = 0.912 and adjusted R^2 = 0.905\n",
      "Added feature Roadworthy_Safety_Certificate_No with R^2 = 0.913 and adjusted R^2 = 0.906\n",
      "Added feature Bike_F3 800 RC MY19 Road Manual 6sp with R^2 = 0.913 and adjusted R^2 = 0.906\n",
      "Added feature Bike_CBR954RR Fireblade with R^2 = 0.914 and adjusted R^2 = 0.906\n",
      "Added feature Model_Gsx r125 gsx r125a with R^2 = 0.914 and adjusted R^2 = 0.907\n",
      "Added feature Height with R^2 = 0.915 and adjusted R^2 = 0.907\n",
      "Added feature Front_Suspension_Telescopic with R^2 = 0.915 and adjusted R^2 = 0.907\n",
      "Added feature Front_Brake_Description_Calliper with R^2 = 0.916 and adjusted R^2 = 0.908\n",
      "Added feature Country_of_Origin_JAPAN with R^2 = 0.916 and adjusted R^2 = 0.908\n",
      "Added feature Model_Cbr650f lams cbr650fl with R^2 = 0.917 and adjusted R^2 = 0.909\n",
      "Added feature Model_Rs4 125 4t with R^2 = 0.917 and adjusted R^2 = 0.909\n",
      "Added feature Carburettor_Electronic fuel injection with R^2 = 0.917 and adjusted R^2 = 0.909\n",
      "Added feature Bike_GSX-R1000 MY16 Road Manual 6sp with R^2 = 0.918 and adjusted R^2 = 0.909\n",
      "Added feature Colour_gold with R^2 = 0.918 and adjusted R^2 = 0.910\n",
      "Added feature Bike_1098 S Road Manual 6sp 1098cc with R^2 = 0.918 and adjusted R^2 = 0.910\n",
      "Added feature Model_Ninja zx 14r abs zx1400 with R^2 = 0.919 and adjusted R^2 = 0.910\n",
      "Added feature Front_Brake_Caliper(s)_Six Piston with R^2 = 0.919 and adjusted R^2 = 0.910\n",
      "Added feature Induction_System_Supercharged (Centrifugal; Scroll type) with R^2 = 0.919 and adjusted R^2 = 0.911\n",
      "Added feature Bike_S 1000 RR MY16 Road Manual 6sp with R^2 = 0.920 and adjusted R^2 = 0.911\n",
      "Added feature Bike_DB8 Road Manual 6sp 1198cc with R^2 = 0.920 and adjusted R^2 = 0.911\n",
      "Added feature Model_Supersport s with R^2 = 0.920 and adjusted R^2 = 0.911\n",
      "Added feature Model_Gsx r1000 with R^2 = 0.921 and adjusted R^2 = 0.911\n",
      "Added feature Front_Suspension_Hydraulic with R^2 = 0.921 and adjusted R^2 = 0.912\n",
      "Added feature Bike_RSV4 R APRC Road Manual 6sp 1000cc with R^2 = 0.921 and adjusted R^2 = 0.912\n",
      "Added feature Front_Suspension_Inverted with R^2 = 0.922 and adjusted R^2 = 0.912\n",
      "Added feature Front_Suspension_Upside Down with R^2 = 0.922 and adjusted R^2 = 0.912\n",
      "Added feature Carburettor_Fuel injection with R^2 = 0.922 and adjusted R^2 = 0.913\n",
      "Added feature Length with R^2 = 0.923 and adjusted R^2 = 0.913\n",
      "Added feature Model_Gsx250r with R^2 = 0.923 and adjusted R^2 = 0.913\n",
      "Added feature Model_Gsx r1000 abs with R^2 = 0.923 and adjusted R^2 = 0.913\n",
      "Added feature Bike_GSX-R600 Road Manual 6sp 599cc with R^2 = 0.923 and adjusted R^2 = 0.913\n",
      "Added feature Model_Cbr250ra abs se repsol with R^2 = 0.924 and adjusted R^2 = 0.914\n",
      "Added feature Model_S 1000 rr race with R^2 = 0.924 and adjusted R^2 = 0.914\n",
      "Added feature Brand_Aprilia with R^2 = 0.924 and adjusted R^2 = 0.914\n",
      "Added feature Model_Daytona 675 abs with R^2 = 0.924 and adjusted R^2 = 0.914\n",
      "Added feature Bike_F3 800 MY19 Road Manual with R^2 = 0.925 and adjusted R^2 = 0.914\n",
      "Added feature Bike_S 1000 RR Sport with R^2 = 0.925 and adjusted R^2 = 0.914\n",
      "Added feature Bike_Ninja ZX-10R ABS MY16 Road Manual 6sp with R^2 = 0.925 and adjusted R^2 = 0.914\n",
      "Added feature Bike_Ninja 300 ABS MY13 Road Manual with R^2 = 0.925 and adjusted R^2 = 0.914\n",
      "Added feature Bike_CBR900RR Fireblade with R^2 = 0.925 and adjusted R^2 = 0.914\n",
      "Added feature Colour_yellow with R^2 = 0.925 and adjusted R^2 = 0.915\n",
      "Added feature Model_Daytona 675 with R^2 = 0.926 and adjusted R^2 = 0.915\n",
      "Added feature Model_Cbr300r abs se cbr300rase with R^2 = 0.926 and adjusted R^2 = 0.915\n",
      "Added feature Model_Ninja zx 6r 636 with R^2 = 0.926 and adjusted R^2 = 0.915\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Added feature Model_1098 s with R^2 = 0.926 and adjusted R^2 = 0.915\n",
      "Added feature Seating_Position_Forward with R^2 = 0.926 and adjusted R^2 = 0.915\n",
      "Added feature Model_S 1000 rr m sport with R^2 = 0.926 and adjusted R^2 = 0.915\n",
      "Added feature Bike_999S Road Manual 6sp 999cc with R^2 = 0.927 and adjusted R^2 = 0.915\n",
      "Added feature Brand_Hyosung with R^2 = 0.927 and adjusted R^2 = 0.915\n",
      "Added feature Model_Cbr954rr fireblade with R^2 = 0.927 and adjusted R^2 = 0.915\n",
      "Added feature Rear_Suspension_Hydraulic with R^2 = 0.927 and adjusted R^2 = 0.915\n",
      "Added feature Model_Yzf r6sp with R^2 = 0.927 and adjusted R^2 = 0.915\n",
      "Added feature Colour_white with R^2 = 0.927 and adjusted R^2 = 0.915\n",
      "Added feature Model_Ninja zx 10r abs with R^2 = 0.928 and adjusted R^2 = 0.915\n",
      "Added feature Front_Brake_Caliper(s)_Four Piston with R^2 = 0.928 and adjusted R^2 = 0.915\n",
      "Added feature Model_Yzf r1 with R^2 = 0.928 and adjusted R^2 = 0.915\n",
      "Added feature Exhaust_Config_4 into 2 with R^2 = 0.928 and adjusted R^2 = 0.916\n",
      "Added feature Country_of_Origin_UNITED KINGDOM with R^2 = 0.928 and adjusted R^2 = 0.916\n",
      "Added feature Model_f4 1000 with R^2 = 0.928 and adjusted R^2 = 0.916\n",
      "Added feature Registration_Expiry_01/02/2019 with R^2 = 0.929 and adjusted R^2 = 0.916\n",
      "Added feature Bike_Ninja 250R Special Edition MY10 Road Manual 6sp with R^2 = 0.929 and adjusted R^2 = 0.916\n",
      "Added feature Clutch_Type_Multi plate with R^2 = 0.929 and adjusted R^2 = 0.916\n",
      "Added feature Model_Cbr1000rra abs fireblade with R^2 = 0.929 and adjusted R^2 = 0.916\n",
      "Added feature Model_Ninja zx 10r abs krt winter edition zx1000s with R^2 = 0.929 and adjusted R^2 = 0.916\n",
      "Added feature Model_Cbr600rr with R^2 = 0.929 and adjusted R^2 = 0.916\n",
      "Added feature Bike_Ninja ZX-6R  Road Manual 6sp 636cc with R^2 = 0.929 and adjusted R^2 = 0.916\n",
      "Added feature Bike_YZF-R6 Road Manual 6sp 600cc with R^2 = 0.930 and adjusted R^2 = 0.916\n",
      "Added feature Model_Gsx250rz with R^2 = 0.930 and adjusted R^2 = 0.916\n",
      "Added feature Bike_CBR600RR Telefonica Road Manual 6sp 599cc with R^2 = 0.930 and adjusted R^2 = 0.916\n",
      "Added feature Front_Brake_Caliper(s)_Single Piston with R^2 = 0.930 and adjusted R^2 = 0.916\n",
      "Added feature Model_Cbr600rra abs with R^2 = 0.930 and adjusted R^2 = 0.917\n",
      "\n",
      "Resulting features:\n",
      "Maximum_Power, Kilometers, Traction_Control_No, Bore, Time_to_Sale, Age, Cylinders, Model_Yzf r1m, Cam_Type_DOHC (Double Over Head Cam), Model_Ninja zx 10r krt abs replica, Colour_none, Ignition_Digital, Side_Stand_Start_Inhibitor_Standard, Model_1199 panigale r abs, Dry_Weight, Linked_Braking_System_Part-Integral, Bike_F3 800 RC Road Manual 6sp 800cc, Bike_1098S Tri Colore Road Manual 6sp 1098cc, Model_1198 s corse edition, Learner_Approved_No, Ignition_CDI (Capacitive Discharge Ignition), Bike_GT650R EFI Road Manual 6sp 650cc, Bike_Ninja ZX-10R ABS MY17 Road Manual 6sp, Model_1198 s, Model_899 panigale, Carburettor_Constant velocity, Model_Gsx r1000r, Model_Ninja 300 se krt replica ex300a, Model_Ninja zx 10rr zx1000z, Rear_Suspension_Spring, Rear_Brake_Caliper(s)_Four Piston, Bike_YZF-R1M MY19 Road Manual 6sp, Model_Panigale v4, Side_Stand_Yes, Bike_F4 1000 Road Manual 6sp 1000cc, Bike_Daytona 675 Road Manual 6sp 675cc, Model_Cbr1000rr fireblade, Model_Ninja zx 10r, Brand_Suzuki, Model_848, Front_Brake_Diameter, Bike_Road Manual 6sp 1098cc, Bike_959 Panigale Road Manual 6sp 959cc, Bike_1199 Panigale Road Manual 6sp, Bike_ZX-12R Road Manual 6sp 1200cc, Registration_Expiry_01/01/1970, Model_Cbr250r, Model_Ninja 300 abs ex300b, Model_Ninja 300 abs special edition, Rear_Brake_Caliper(s)_Double Piston, Oil_Capacity, Model_Rsv1000 mille, Bike_Road Manual 6sp 749cc, Model_Ninja 300 abs se 30th anniversary, Cam_Type_Desmodromic, Bike_TT600 Road Manual 6sp 600cc, Starter_Electric, Roadworthy_Safety_Certificate_No, Bike_F3 800 RC MY19 Road Manual 6sp, Bike_CBR954RR Fireblade, Model_Gsx r125 gsx r125a, Height, Front_Suspension_Telescopic, Front_Brake_Description_Calliper, Country_of_Origin_JAPAN, Model_Cbr650f lams cbr650fl, Model_Rs4 125 4t, Carburettor_Electronic fuel injection, Bike_GSX-R1000 MY16 Road Manual 6sp, Colour_gold, Bike_1098 S Road Manual 6sp 1098cc, Model_Ninja zx 14r abs zx1400, Front_Brake_Caliper(s)_Six Piston, Induction_System_Supercharged (Centrifugal; Scroll type), Bike_S 1000 RR MY16 Road Manual 6sp, Bike_DB8 Road Manual 6sp 1198cc, Model_Supersport s, Model_Gsx r1000, Front_Suspension_Hydraulic, Bike_RSV4 R APRC Road Manual 6sp 1000cc, Front_Suspension_Inverted, Front_Suspension_Upside Down, Carburettor_Fuel injection, Length, Model_Gsx250r, Model_Gsx r1000 abs, Bike_GSX-R600 Road Manual 6sp 599cc, Model_Cbr250ra abs se repsol, Model_S 1000 rr race, Brand_Aprilia, Model_Daytona 675 abs, Bike_F3 800 MY19 Road Manual, Bike_S 1000 RR Sport, Bike_Ninja ZX-10R ABS MY16 Road Manual 6sp, Bike_Ninja 300 ABS MY13 Road Manual, Bike_CBR900RR Fireblade, Colour_yellow, Model_Daytona 675, Model_Cbr300r abs se cbr300rase, Model_Ninja zx 6r 636, Model_1098 s, Seating_Position_Forward, Model_S 1000 rr m sport, Bike_999S Road Manual 6sp 999cc, Brand_Hyosung, Model_Cbr954rr fireblade, Rear_Suspension_Hydraulic, Model_Yzf r6sp, Colour_white, Model_Ninja zx 10r abs, Front_Brake_Caliper(s)_Four Piston, Model_Yzf r1, Exhaust_Config_4 into 2, Country_of_Origin_UNITED KINGDOM, Model_f4 1000, Registration_Expiry_01/02/2019, Bike_Ninja 250R Special Edition MY10 Road Manual 6sp, Clutch_Type_Multi plate, Model_Cbr1000rra abs fireblade, Model_Ninja zx 10r abs krt winter edition zx1000s, Model_Cbr600rr, Bike_Ninja ZX-6R  Road Manual 6sp 636cc, Bike_YZF-R6 Road Manual 6sp 600cc, Model_Gsx250rz, Bike_CBR600RR Telefonica Road Manual 6sp 599cc, Front_Brake_Caliper(s)_Single Piston, Model_Cbr600rra abs\n"
     ]
    }
   ],
   "source": [
    "## Use Forward Feature Selection to pick a good model\n",
    "X = sport_df[features]\n",
    "y = sport_df[target]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1, test_size=0.3)\n",
    "\n",
    "# start with no predictors\n",
    "included = []\n",
    "# keep track of model and parameters\n",
    "best = {'feature': '', 'r2': 0, 'a_r2': 0}\n",
    "# create a model object to hold the modelling parameters\n",
    "model = RidgeCV(cv=5) \n",
    "# get the number of cases in the test data\n",
    "n = X_test.shape[0]\n",
    "\n",
    "while True:\n",
    "    changed = False\n",
    "    \n",
    "    # list the features to be evaluated\n",
    "    excluded = list(set(features) - set(included))\n",
    "    \n",
    "    \n",
    "    # for each remaining feature to be evaluated\n",
    "    for new_column in excluded:\n",
    "        \n",
    "        # fit the model with the Training data\n",
    "        fit = model.fit(X_train[included + [new_column]], y_train) # fit a model; consider which predictors should be included\n",
    "        # calculate the score (R^2 for Regression)\n",
    "        r2 = model.score(X_test[included + [new_column]], y_test) # calculate the score\n",
    "        # number of predictors in this model\n",
    "        k = len(included + [new_column]) + 1\n",
    "        # calculate the adjusted R^2\n",
    "        adjusted_r = adjusted_r2(r2,n,k) \n",
    "\n",
    "   \n",
    "        # if model improves\n",
    "        if adjusted_r > best['a_r2']:\n",
    "            # record new parameters\n",
    "            best = {'feature': new_column, 'r2': r2, 'a_r2': adjusted_r}\n",
    "            # flag that found a better model\n",
    "            changed = True\n",
    "   \n",
    "    # if found a better model after testing all remaining features\n",
    "    if changed:\n",
    "        # update control details\n",
    "        included.append(best['feature'])\n",
    "        excluded = list(set(excluded) - set(best['feature']))\n",
    "        print('Added feature %-4s with R^2 = %.3f and adjusted R^2 = %.3f' % \n",
    "              (best['feature'], best['r2'], best['a_r2']))\n",
    "    else:\n",
    "        # terminate if no better model\n",
    "        break\n",
    "\n",
    "print('')\n",
    "print('Resulting features:')\n",
    "print(', '.join(included))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "127"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(included)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9304581071244014"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = RidgeCV(cv=5)\n",
    "model.fit(X_train[included], y_train)\n",
    "model.score(X_test[included], y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.fit(sport_df[included],sport_df[target])\n",
    "predictions = model.predict(sport_df[included])\n",
    "sport_df['Predicted_Price'] = predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "sport_df['Price_ratio'] = sport_df['Price'] / sport_df['Predicted_Price']\n",
    "\n",
    "sport_df['Deal_type'] = 'Dont Bother'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 0.9] = 'Negotiate'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 0.8] = 'Good Deal'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 0.75] = 'Great Deal'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 0.5] = 'Its a steel'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scatter(data,x,y,hue=None,title='',figsize=(12,10)):\n",
    "    ax = plt.figure(figsize=figsize)\n",
    "    sns.scatterplot(x=x,y=y,hue=hue,data=data);\n",
    "    plt.title(title,fontsize=14)\n",
    "    plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "    #plt.ylim(0,40000)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter(sport_df,'Price','Predicted_Price',hue='Deal_type',title='Great Deals on Motorbikes')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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>Price</th>\n",
       "      <th>Predicted_Price</th>\n",
       "      <th>Price_ratio</th>\n",
       "      <th>Deal_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1127</th>\n",
       "      <td>15200.0</td>\n",
       "      <td>15759.525279</td>\n",
       "      <td>0.964496</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1128</th>\n",
       "      <td>15200.0</td>\n",
       "      <td>14589.409022</td>\n",
       "      <td>1.041852</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1129</th>\n",
       "      <td>15500.0</td>\n",
       "      <td>16538.555841</td>\n",
       "      <td>0.937204</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1130</th>\n",
       "      <td>15500.0</td>\n",
       "      <td>15214.666925</td>\n",
       "      <td>1.018754</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1131</th>\n",
       "      <td>15500.0</td>\n",
       "      <td>15797.216999</td>\n",
       "      <td>0.981185</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1132</th>\n",
       "      <td>15500.0</td>\n",
       "      <td>15704.481229</td>\n",
       "      <td>0.986979</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1133</th>\n",
       "      <td>15500.0</td>\n",
       "      <td>12636.441276</td>\n",
       "      <td>1.226611</td>\n",
       "      <td>Good Deal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1134</th>\n",
       "      <td>15500.0</td>\n",
       "      <td>13930.194993</td>\n",
       "      <td>1.112691</td>\n",
       "      <td>Negotiate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1135</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>17881.927243</td>\n",
       "      <td>0.872389</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1136</th>\n",
       "      <td>15700.0</td>\n",
       "      <td>16525.186605</td>\n",
       "      <td>0.950065</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Price  Predicted_Price  Price_ratio    Deal_type\n",
       "1127  15200.0     15759.525279     0.964496  Dont Bother\n",
       "1128  15200.0     14589.409022     1.041852  Dont Bother\n",
       "1129  15500.0     16538.555841     0.937204  Dont Bother\n",
       "1130  15500.0     15214.666925     1.018754  Dont Bother\n",
       "1131  15500.0     15797.216999     0.981185  Dont Bother\n",
       "1132  15500.0     15704.481229     0.986979  Dont Bother\n",
       "1133  15500.0     12636.441276     1.226611    Good Deal\n",
       "1134  15500.0     13930.194993     1.112691    Negotiate\n",
       "1135  15600.0     17881.927243     0.872389  Dont Bother\n",
       "1136  15700.0     16525.186605     0.950065  Dont Bother"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "sport_df[['Price','Predicted_Price','Price_ratio','Deal_type']][sport_df['Price'] > 15000].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "model = RidgeCV(cv=5)\n",
    "\n",
    "X = sport_df[features]\n",
    "y = sport_df[target]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1, test_size=0.3)\n",
    "\n",
    "n = X_train.shape[0]\n",
    "\n",
    "best_score = 0\n",
    "best_feature = ''\n",
    "feature_set = features\n",
    "included = []\n",
    "\n",
    "# top 10 features\n",
    "for i in range(10):\n",
    "\n",
    "    for col in features_set:\n",
    "\n",
    "        model.fit(X_train[included + [col]], y_train)\n",
    "        r2 = model.score(X_test[included + [col]], y_test)\n",
    "\n",
    "        score = adjusted_r2(r2,n,1) \n",
    "\n",
    "        if (score > best_score):\n",
    "            best_score = score\n",
    "            best_feature = col\n",
    "\n",
    "\n",
    "    print ('Added ',best_feature)\n",
    "    included.append(best_feature)\n",
    "    # reset for the next round\n",
    "    best_score = 0\n",
    "    best_feature = ''\n",
    "    feature_set = set(features) - set(included)\n",
    "\n",
    "print (included)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.75388828, 0.78876739, 0.79761285, 0.7969353 , 0.7364585 ])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = LassoCV(cv=5)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(sport_df[features], sport_df['Price'],\n",
    "                                                    random_state=1, test_size=0.3)\n",
    "\n",
    "#result = cross_val_score(model, scaleSport[model_cols], sport_df['Price'], cv=5, scoring='r2')\n",
    "result = cross_val_score(model, X_train[model_cols], y_train, cv=5, scoring='r2')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.60100941, 0.63718051, 0.50006065, 0.70923495, 0.6166904 ])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = cross_val_score(model, X_test[model_cols], y_test, cv=5, scoring='r2')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-2.76386866, -1.98439363,  0.5310654 ,  0.64212447,  0.67558663])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = cross_val_score(model, sport_df[features], sport_df['Price'], cv=5, scoring='r2')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training: R2: 0.706419255150665\n",
      "Training: adjusted R2 1.219095115870418\n",
      "Testing: R2: 0.680765496934826\n",
      "Testing: adjusted R2 1.2382401491446384\n",
      "mean_squared_error: 12014464.15790585\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def run_LinearModel(X_train, X_test, y_train, y_test):\n",
    "    model = LinearRegression()\n",
    "    model.fit(X_train, y_train)\n",
    "    pred = model.predict(X_test)\n",
    "\n",
    "    n, k = X_test.shape\n",
    "\n",
    "    r2 = model.score(X_train,y_train)\n",
    "    print ('Training: R2:',r2)\n",
    "    print ('Training: adjusted R2',adjusted_r2(r2, n, k))\n",
    "\n",
    "    r2 = model.score(X_test,y_test)\n",
    "    print ('Testing: R2:',r2)\n",
    "    print ('Testing: adjusted R2',adjusted_r2(r2, n, k))\n",
    "    print ('mean_squared_error:',mean_squared_error(y_test,pred))\n",
    "    \n",
    "    return model, pred\n",
    "\n",
    "\n",
    "def run_LassoCV(X_train, X_test, y_train, y_test,cv=5):\n",
    "    model = LassoCV(cv=cv) \n",
    "    model.fit(X_train, y_train)\n",
    "    pred = model.predict(X_test)\n",
    "\n",
    "    n, k = X_test.shape\n",
    "\n",
    "    r2 = model.score(X_train,y_train)\n",
    "    print ('Training: R2:',r2)\n",
    "    print ('Training: adjusted R2',adjusted_r2(r2, n, k))\n",
    "\n",
    "    r2 = model.score(X_test,y_test)\n",
    "    print ('Testing: R2:',r2)\n",
    "    print ('Testing: adjusted R2',adjusted_r2(r2, n, k))\n",
    "    print ('mean_squared_error:',mean_squared_error(y_test,pred))\n",
    "    \n",
    "    return model, pred\n",
    "\n",
    "\n",
    "model, predictions = run_LassoCV(X_train, X_test, y_train, y_test)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "source": [
    "# Determine which bikes are a good deal\n",
    "\n",
    "This will be the bikes that have an advertised price lower than the predicted price. The determination of a good deal or not will be based on a threshold of the ratio of the advertised price to the predicted price."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "model.fit(sport_df[features], sport_df['Price'])\n",
    "sport_df['Predicted_Price'] = model.predict(sport_df[features])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "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>Price</th>\n",
       "      <th>Predicted_Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1500.0</td>\n",
       "      <td>-1719.187941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1700.0</td>\n",
       "      <td>2056.228071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1900.0</td>\n",
       "      <td>-3779.143691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1990.0</td>\n",
       "      <td>-1130.815868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1999.0</td>\n",
       "      <td>133.180327</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Price  Predicted_Price\n",
       "0  1500.0     -1719.187941\n",
       "1  1700.0      2056.228071\n",
       "2  1900.0     -3779.143691\n",
       "3  1990.0     -1130.815868\n",
       "4  1999.0       133.180327"
      ]
     },
     "execution_count": 324,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tranasform the values back to standard meaning\n",
    "sport_df[['Price','Predicted_Price']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_predictions(y_test,pred):\n",
    "    fig, ax = plt.subplots(figsize=(12,10))\n",
    "    ax.scatter(y_test,pred)\n",
    "    ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--', lw=0.8)\n",
    "    ax.set_xlabel('Measured');\n",
    "    ax.set_ylabel('Predicted');\n",
    "    ax.set_title('Accuracy of Predictions');\n",
    "    #ax.set_ylim(0,y_test.max());\n",
    "    \n",
    "plot_predictions(sport_df['Price'],sport_df['Predicted_Price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "sport_df['Price_ratio'] = sport_df['Price'] / sport_df['Predicted_Price']\n",
    "\n",
    "sport_df['Deal_type'] = 'Dont Bother'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 1.1] = 'Negotiate'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 1.2] = 'Good Deal'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 1.5] = 'Great Deal'\n",
    "sport_df['Deal_type'][sport_df['Price_ratio'] > 2] = 'Its a steel'\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "def scatter(data,x,y,hue=None,title='',figsize=(12,10)):\n",
    "    ax = plt.figure(figsize=figsize)\n",
    "    sns.scatterplot(x=x,y=y,hue=hue,data=data);\n",
    "    plt.title(title,fontsize=14)\n",
    "    plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "    #plt.ylim(0,40000)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter(sport_df,'Price','Predicted_Price',hue='Deal_type',title='Great Deals on Motorbikes')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "hideCode": false,
    "hidePrompt": false
   },
   "outputs": [],
   "source": [
    "outliers = sport_df[(sport_df['Predicted_Price'] > 40000) | (sport_df['Predicted_Price'] < 0)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {
    "hideCode": false,
    "hideOutput": true,
    "hidePrompt": false
   },
   "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>Bore</th>\n",
       "      <th>Carburettor(s)</th>\n",
       "      <th>Compression_Ratio</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Dry_Weight</th>\n",
       "      <th>Engine_Description</th>\n",
       "      <th>Front_Brake_Diameter</th>\n",
       "      <th>Front_Suspension_Travel</th>\n",
       "      <th>Fuel_Reserve_Capacity</th>\n",
       "      <th>Fuel_Tank_Capacity</th>\n",
       "      <th>...</th>\n",
       "      <th>Model_f4 312 r 1000 11</th>\n",
       "      <th>Model_f4 750 s</th>\n",
       "      <th>Model_f4 750 s f4s 11</th>\n",
       "      <th>Model_f4 r</th>\n",
       "      <th>Model_f4 rr</th>\n",
       "      <th>Model_f4 rr 1000</th>\n",
       "      <th>Model_f4ago 1000</th>\n",
       "      <th>Predicted_Price</th>\n",
       "      <th>Price_ratio</th>\n",
       "      <th>Deal_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>57.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>290.43605</td>\n",
       "      <td>158.312257</td>\n",
       "      <td>3.459387</td>\n",
       "      <td>12.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6.160000e+02</td>\n",
       "      <td>-3.246753e+00</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>81.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>650.0</td>\n",
       "      <td>300.00000</td>\n",
       "      <td>158.312257</td>\n",
       "      <td>3.459387</td>\n",
       "      <td>17.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.496419e+18</td>\n",
       "      <td>1.522181e-15</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351</th>\n",
       "      <td>97.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>320.00000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.987703e+17</td>\n",
       "      <td>6.258370e-15</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>97.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>320.00000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.987703e+17</td>\n",
       "      <td>6.885584e-15</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563</th>\n",
       "      <td>53.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.463877</td>\n",
       "      <td>2.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>290.43605</td>\n",
       "      <td>158.312257</td>\n",
       "      <td>3.459387</td>\n",
       "      <td>15.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.017931e+17</td>\n",
       "      <td>3.434210e-14</td>\n",
       "      <td>Dont Bother</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1532 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Bore  Carburettor(s)  Compression_Ratio  Cylinders  Dry_Weight  \\\n",
       "9    57.0             1.0          10.000000        1.0       123.0   \n",
       "176  81.5             1.0          11.000000        2.0       200.0   \n",
       "351  97.0             1.0          11.000000        2.0       275.0   \n",
       "421  97.0             1.0          11.000000        2.0       275.0   \n",
       "563  53.5             2.0          10.463877        2.0       129.0   \n",
       "\n",
       "     Engine_Description  Front_Brake_Diameter  Front_Suspension_Travel  \\\n",
       "9                 150.0             290.43605               158.312257   \n",
       "176               650.0             300.00000               158.312257   \n",
       "351              1000.0             320.00000               120.000000   \n",
       "421              1000.0             320.00000               120.000000   \n",
       "563               250.0             290.43605               158.312257   \n",
       "\n",
       "     Fuel_Reserve_Capacity  Fuel_Tank_Capacity  ...  Model_f4 312 r 1000 11  \\\n",
       "9                 3.459387                12.0  ...                       0   \n",
       "176               3.459387                17.0  ...                       0   \n",
       "351               4.000000                20.0  ...                       0   \n",
       "421               4.000000                20.0  ...                       0   \n",
       "563               3.459387                15.0  ...                       0   \n",
       "\n",
       "     Model_f4 750 s  Model_f4 750 s f4s 11  Model_f4 r  Model_f4 rr  \\\n",
       "9                 0                      0           0            0   \n",
       "176               0                      0           0            0   \n",
       "351               0                      0           0            0   \n",
       "421               0                      0           0            0   \n",
       "563               0                      0           0            0   \n",
       "\n",
       "     Model_f4 rr 1000  Model_f4ago 1000  Predicted_Price   Price_ratio  \\\n",
       "9                   0                 0    -6.160000e+02 -3.246753e+00   \n",
       "176                 0                 0     2.496419e+18  1.522181e-15   \n",
       "351                 0                 0     7.987703e+17  6.258370e-15   \n",
       "421                 0                 0     7.987703e+17  6.885584e-15   \n",
       "563                 0                 0     2.017931e+17  3.434210e-14   \n",
       "\n",
       "       Deal_type  \n",
       "9    Dont Bother  \n",
       "176  Dont Bother  \n",
       "351  Dont Bother  \n",
       "421  Dont Bother  \n",
       "563  Dont Bother  \n",
       "\n",
       "[5 rows x 1532 columns]"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
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