Price_Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import modules\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "pd.set_option('display.max_columns', 50)\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "model = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import datasets\n",
    "df = pd.read_csv('data_predict.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>beds</th>\n",
       "      <th>price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>review_scores_rating</th>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>6627449</td>\n",
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       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>10464</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>125</td>\n",
       "      <td>3</td>\n",
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>10464</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>69</td>\n",
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       "      <td>19609887</td>\n",
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       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>10464</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>150</td>\n",
       "      <td>2</td>\n",
       "      <td>1125</td>\n",
       "      <td>3</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7949480</td>\n",
       "      <td>100</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>10464</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>31</td>\n",
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       "      <td>9147025</td>\n",
       "      <td>100</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>10464</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>125</td>\n",
       "      <td>2</td>\n",
       "      <td>28</td>\n",
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      ],
      "text/plain": [
       "         id  host_response_rate  host_is_superhost  host_total_listings_count  \\\n",
       "0   6627449                 100              False                          1   \n",
       "1   5557381                 100               True                          1   \n",
       "2  19609887                 100              False                          1   \n",
       "3   7949480                 100               True                          1   \n",
       "4   9147025                 100               True                          1   \n",
       "\n",
       "   host_has_profile_pic  host_identity_verified  zipcode property_type  \\\n",
       "0                  True                    True    10464     Apartment   \n",
       "1                  True                    True    10464         House   \n",
       "2                  True                   False    10464     Apartment   \n",
       "3                  True                    True    10464         House   \n",
       "4                  True                   False    10464         House   \n",
       "\n",
       "         room_type  accommodates  bathrooms  bedrooms  beds price  \\\n",
       "0  Entire home/apt             3        1.0         1     1   125   \n",
       "1     Private room             4        1.0         1     1    69   \n",
       "2  Entire home/apt             7        1.0         2     5   150   \n",
       "3     Private room             2        1.0         1     1   101   \n",
       "4  Entire home/apt             2        1.0         0     1   125   \n",
       "\n",
       "   minimum_nights  maximum_nights  number_of_reviews  review_scores_rating  \\\n",
       "0               3              21                 21                    95   \n",
       "1               3            1125                 94                    97   \n",
       "2               2            1125                  3                   100   \n",
       "3               1               7                 31                   100   \n",
       "4               2              28                 60                    97   \n",
       "\n",
       "   review_scores_accuracy  review_scores_cleanliness  review_scores_checkin  \\\n",
       "0                      10                         10                     10   \n",
       "1                      10                         10                     10   \n",
       "2                      10                         10                     10   \n",
       "3                      10                         10                     10   \n",
       "4                      10                         10                     10   \n",
       "\n",
       "   review_scores_communication  review_scores_location  review_scores_value  \n",
       "0                           10                      10                   10  \n",
       "1                           10                      10                   10  \n",
       "2                           10                      10                   10  \n",
       "3                           10                      10                   10  \n",
       "4                           10                      10                   10  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cleaning Data\n",
    "df['price'] = df['price'].str.strip('$')\n",
    "df['price'] = df['price'].str.replace(',','')\n",
    "df['price'] = df['price'].astype(np.float32)\n",
    "\n",
    "# Convert the boolean to int\n",
    "arr_mapping = {True:1, False:0}\n",
    "df['host_is_superhost'] = df['host_is_superhost'].map(arr_mapping)\n",
    "df['host_has_profile_pic'] = df['host_has_profile_pic'].map(arr_mapping)\n",
    "df['host_identity_verified'] = df['host_identity_verified'].map(arr_mapping)\n",
    "\n",
    "# Create New Column\n",
    "df['Price_daily'] = df['price']/df['minimum_nights']\n",
    "df = df.drop('price', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create X and Y to predict Listing Price \n",
    "y = np.array(df['Price_daily'])\n",
    "\n",
    "df_x = df.drop(['Price_daily','id','zipcode'], axis=1)\n",
    "df_x_dummy = pd.get_dummies(df_x)\n",
    "# create dummy variables by categorical data\n",
    "x = np.array(df_x_dummy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the model\n",
    "model.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Predict the price\n",
    "Y_pred = model.predict(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the column about Predicted Price\n",
    "df['predicted_price'] = Y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Calculate the diff\n",
    "df['diif_price'] = df['Price_daily'] - df['predicted_price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_has_profile_pic</th>\n",
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       "      <th>zipcode</th>\n",
       "      <th>property_type</th>\n",
       "      <th>room_type</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>beds</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>review_scores_rating</th>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>Price_daily</th>\n",
       "      <th>predicted_price</th>\n",
       "      <th>diif_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6627449</td>\n",
       "      <td>100</td>\n",
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       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>41.666667</td>\n",
       "      <td>80.203275</td>\n",
       "      <td>-38.536608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5557381</td>\n",
       "      <td>100</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10464</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
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       "      <td>3</td>\n",
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       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>103.920700</td>\n",
       "      <td>-80.920700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19609887</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10464</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1125</td>\n",
       "      <td>3</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>115.790172</td>\n",
       "      <td>-40.790172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7949480</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10464</td>\n",
       "      <td>House</td>\n",
       "      <td>Private room</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>7</td>\n",
       "      <td>31</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>60.785434</td>\n",
       "      <td>40.214566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9147025</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10464</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>28</td>\n",
       "      <td>60</td>\n",
       "      <td>97</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>62.500000</td>\n",
       "      <td>53.505134</td>\n",
       "      <td>8.994866</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id  host_response_rate  host_is_superhost  host_total_listings_count  \\\n",
       "0   6627449                 100                  0                          1   \n",
       "1   5557381                 100                  1                          1   \n",
       "2  19609887                 100                  0                          1   \n",
       "3   7949480                 100                  1                          1   \n",
       "4   9147025                 100                  1                          1   \n",
       "\n",
       "   host_has_profile_pic  host_identity_verified  zipcode property_type  \\\n",
       "0                     1                       1    10464     Apartment   \n",
       "1                     1                       1    10464         House   \n",
       "2                     1                       0    10464     Apartment   \n",
       "3                     1                       1    10464         House   \n",
       "4                     1                       0    10464         House   \n",
       "\n",
       "         room_type  accommodates  bathrooms  bedrooms  beds  minimum_nights  \\\n",
       "0  Entire home/apt             3        1.0         1     1               3   \n",
       "1     Private room             4        1.0         1     1               3   \n",
       "2  Entire home/apt             7        1.0         2     5               2   \n",
       "3     Private room             2        1.0         1     1               1   \n",
       "4  Entire home/apt             2        1.0         0     1               2   \n",
       "\n",
       "   maximum_nights  number_of_reviews  review_scores_rating  \\\n",
       "0              21                 21                    95   \n",
       "1            1125                 94                    97   \n",
       "2            1125                  3                   100   \n",
       "3               7                 31                   100   \n",
       "4              28                 60                    97   \n",
       "\n",
       "   review_scores_accuracy  review_scores_cleanliness  review_scores_checkin  \\\n",
       "0                      10                         10                     10   \n",
       "1                      10                         10                     10   \n",
       "2                      10                         10                     10   \n",
       "3                      10                         10                     10   \n",
       "4                      10                         10                     10   \n",
       "\n",
       "   review_scores_communication  review_scores_location  review_scores_value  \\\n",
       "0                           10                      10                   10   \n",
       "1                           10                      10                   10   \n",
       "2                           10                      10                   10   \n",
       "3                           10                      10                   10   \n",
       "4                           10                      10                   10   \n",
       "\n",
       "   Price_daily  predicted_price  diif_price  \n",
       "0    41.666667        80.203275  -38.536608  \n",
       "1    23.000000       103.920700  -80.920700  \n",
       "2    75.000000       115.790172  -40.790172  \n",
       "3   101.000000        60.785434   40.214566  \n",
       "4    62.500000        53.505134    8.994866  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "      <th>id</th>\n",
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       "            id  host_response_rate  host_is_superhost  \\\n",
       "6712   7089310                 100                  0   \n",
       "4948  11708688                 100                  0   \n",
       "2455    512209                 100                  1   \n",
       "6917    867220                 100                  0   \n",
       "7378  16923912                 100                  0   \n",
       "\n",
       "      host_total_listings_count  host_has_profile_pic  host_identity_verified  \\\n",
       "6712                          1                     1                       1   \n",
       "4948                          1                     1                       0   \n",
       "2455                          1                     1                       1   \n",
       "6917                          1                     1                       1   \n",
       "7378                          2                     1                       0   \n",
       "\n",
       "      zipcode property_type        room_type  accommodates  bathrooms  \\\n",
       "6712    11432         House  Entire home/apt            16        5.5   \n",
       "4948    10456     Apartment  Entire home/apt            15        1.0   \n",
       "2455    11201         House  Entire home/apt            16        5.5   \n",
       "6917    11226         House  Entire home/apt            16        4.0   \n",
       "7378    11375         House  Entire home/apt            10        4.5   \n",
       "\n",
       "      bedrooms  beds  minimum_nights  maximum_nights  number_of_reviews  \\\n",
       "6712         5     5               3              28                 15   \n",
       "4948         2     3               1            1125                  6   \n",
       "2455         5    12               5              99                 47   \n",
       "6917         5     5               3            1125                 13   \n",
       "7378         6     8               5              57                  2   \n",
       "\n",
       "      review_scores_rating  review_scores_accuracy  review_scores_cleanliness  \\\n",
       "6712                    80                       9                          8   \n",
       "4948                    95                      10                         10   \n",
       "2455                    99                      10                         10   \n",
       "6917                    88                       9                         10   \n",
       "7378                   100                      10                         10   \n",
       "\n",
       "      review_scores_checkin  review_scores_communication  \\\n",
       "6712                      9                            9   \n",
       "4948                      8                           10   \n",
       "2455                     10                           10   \n",
       "6917                      9                            9   \n",
       "7378                     10                           10   \n",
       "\n",
       "      review_scores_location  review_scores_value  Price_daily  \\\n",
       "6712                       9                    9   132.666667   \n",
       "4948                      10                   10    75.000000   \n",
       "2455                      10                   10   160.000000   \n",
       "6917                       9                    9   246.666667   \n",
       "7378                      10                    9    80.000000   \n",
       "\n",
       "      predicted_price  diif_price  \n",
       "6712       591.340913 -458.674247  \n",
       "4948       394.741657 -319.741657  \n",
       "2455       455.508014 -295.508014  \n",
       "6917       530.750826 -284.084159  \n",
       "7378       354.688546 -274.688546  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the Negative largest difference between actial price and predicted price\n",
    "# This is the listings that we can propose that they can increase their price\n",
    "df.sort_values('diif_price').head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10128</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>8</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1125</td>\n",
       "      <td>1</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2500.000000</td>\n",
       "      <td>322.629584</td>\n",
       "      <td>2177.370416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4141</th>\n",
       "      <td>2952861</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11205</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>16</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1125</td>\n",
       "      <td>3</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>4500.000000</td>\n",
       "      <td>659.818948</td>\n",
       "      <td>3840.181052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4143</th>\n",
       "      <td>2953058</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11205</td>\n",
       "      <td>House</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>16</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1125</td>\n",
       "      <td>1</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>8000.000000</td>\n",
       "      <td>764.232931</td>\n",
       "      <td>7235.767069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            id  host_response_rate  host_is_superhost  \\\n",
       "7123   3585309                 100                  0   \n",
       "7221  18854380                 100                  0   \n",
       "2378  12591059                  50                  0   \n",
       "7054   3181834                 100                  0   \n",
       "3857  19178296                 100                  0   \n",
       "3586   1056256                 100                  0   \n",
       "3814  12469563                 100                  0   \n",
       "5638   2939700                   0                  0   \n",
       "4141   2952861                 100                  1   \n",
       "4143   2953058                 100                  1   \n",
       "\n",
       "      host_total_listings_count  host_has_profile_pic  host_identity_verified  \\\n",
       "7123                          2                     1                       0   \n",
       "7221                          1                     1                       0   \n",
       "2378                          1                     1                       0   \n",
       "7054                          1                     1                       1   \n",
       "3857                          1                     1                       0   \n",
       "3586                         17                     1                       1   \n",
       "3814                          2                     1                       1   \n",
       "5638                          1                     1                       0   \n",
       "4141                         11                     1                       1   \n",
       "4143                         11                     1                       1   \n",
       "\n",
       "      zipcode property_type        room_type  accommodates  bathrooms  \\\n",
       "7123    11358         House  Entire home/apt             9        3.0   \n",
       "7221    11354   Condominium  Entire home/apt             2        1.0   \n",
       "2378    11225     Apartment  Entire home/apt             4        1.0   \n",
       "7054    10011     Apartment  Entire home/apt            10        2.0   \n",
       "3857    10001     Apartment  Entire home/apt            10        1.5   \n",
       "3586    11231         House  Entire home/apt            12        2.5   \n",
       "3814    10001     Apartment  Entire home/apt            10        2.0   \n",
       "5638    10128     Apartment  Entire home/apt             8        3.5   \n",
       "4141    11205         House  Entire home/apt            16        6.0   \n",
       "4143    11205         House  Entire home/apt            16        6.0   \n",
       "\n",
       "      bedrooms  beds  minimum_nights  maximum_nights  number_of_reviews  \\\n",
       "7123         4     5               1            1125                  9   \n",
       "7221         0     1             365             365                  6   \n",
       "2378         2     2               1            1125                  4   \n",
       "7054         4     5               1            1125                 15   \n",
       "3857         4     5               1            1125                  3   \n",
       "3586         5     5               1             365                 46   \n",
       "3814         4     4               1            1125                 11   \n",
       "5638         5     5               1            1125                  1   \n",
       "4141         5     5               1            1125                  3   \n",
       "4143         5     5               1            1125                  1   \n",
       "\n",
       "      review_scores_rating  review_scores_accuracy  review_scores_cleanliness  \\\n",
       "7123                   100                      10                         10   \n",
       "7221                    88                       8                          9   \n",
       "2378                    80                       9                          7   \n",
       "7054                    92                       9                         10   \n",
       "3857                    93                       9                          9   \n",
       "3586                    94                       9                          9   \n",
       "3814                    94                       9                          9   \n",
       "5638                   100                      10                         10   \n",
       "4141                   100                      10                          9   \n",
       "4143                   100                      10                         10   \n",
       "\n",
       "      review_scores_checkin  review_scores_communication  \\\n",
       "7123                     10                           10   \n",
       "7221                      9                            8   \n",
       "2378                      9                           10   \n",
       "7054                      9                            9   \n",
       "3857                      9                            9   \n",
       "3586                     10                           10   \n",
       "3814                      9                            9   \n",
       "5638                     10                           10   \n",
       "4141                      9                           10   \n",
       "4143                      6                            6   \n",
       "\n",
       "      review_scores_location  review_scores_value  Price_daily  \\\n",
       "7123                      10                   10   950.000000   \n",
       "7221                       9                    8     0.452055   \n",
       "2378                      10                    8   800.000000   \n",
       "7054                      10                    9   990.000000   \n",
       "3857                       9                    9   990.000000   \n",
       "3586                      10                    9  1395.000000   \n",
       "3814                       9                    9  1500.000000   \n",
       "5638                      10                   10  2500.000000   \n",
       "4141                      10                   10  4500.000000   \n",
       "4143                      10                   10  8000.000000   \n",
       "\n",
       "      predicted_price   diif_price  \n",
       "7123       292.877986   657.122014  \n",
       "7221      -672.099410   672.551464  \n",
       "2378       114.606462   685.393538  \n",
       "7054       295.041393   694.958607  \n",
       "3857       248.739828   741.260172  \n",
       "3586       352.723361  1042.276639  \n",
       "3814       297.732107  1202.267893  \n",
       "5638       322.629584  2177.370416  \n",
       "4141       659.818948  3840.181052  \n",
       "4143       764.232931  7235.767069  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the positive largest difference between actial price and predicted price\n",
    "df.sort_values('diif_price').tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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_daily</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Price_daily</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>diif_price</th>\n",
       "      <td>0.891564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>predicted_price</th>\n",
       "      <td>0.452894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>accommodates</th>\n",
       "      <td>0.367932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bedrooms</th>\n",
       "      <td>0.288813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beds</th>\n",
       "      <td>0.267686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bathrooms</th>\n",
       "      <td>0.259970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_location</th>\n",
       "      <td>0.083667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_is_superhost</th>\n",
       "      <td>0.023434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <td>0.018885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number_of_reviews</th>\n",
       "      <td>0.017249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_rating</th>\n",
       "      <td>0.009161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <td>0.003600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <td>-0.001251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_response_rate</th>\n",
       "      <td>-0.003722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>maximum_nights</th>\n",
       "      <td>-0.004380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_identity_verified</th>\n",
       "      <td>-0.006906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <td>-0.006993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>-0.016068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_value</th>\n",
       "      <td>-0.017508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_communication</th>\n",
       "      <td>-0.062392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <td>-0.063431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>minimum_nights</th>\n",
       "      <td>-0.122721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <td>-0.125526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Price_daily\n",
       "Price_daily                     1.000000\n",
       "diif_price                      0.891564\n",
       "predicted_price                 0.452894\n",
       "accommodates                    0.367932\n",
       "bedrooms                        0.288813\n",
       "beds                            0.267686\n",
       "bathrooms                       0.259970\n",
       "review_scores_location          0.083667\n",
       "host_is_superhost               0.023434\n",
       "review_scores_cleanliness       0.018885\n",
       "number_of_reviews               0.017249\n",
       "review_scores_rating            0.009161\n",
       "host_has_profile_pic            0.003600\n",
       "host_total_listings_count      -0.001251\n",
       "host_response_rate             -0.003722\n",
       "maximum_nights                 -0.004380\n",
       "host_identity_verified         -0.006906\n",
       "review_scores_accuracy         -0.006993\n",
       "id                             -0.016068\n",
       "review_scores_value            -0.017508\n",
       "review_scores_communication    -0.062392\n",
       "review_scores_checkin          -0.063431\n",
       "minimum_nights                 -0.122721\n",
       "zipcode                        -0.125526"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Confrim the correlation\n",
    "pd.DataFrame(df.corr()['Price_daily']).sort_values('Price_daily', ascending=False)"
   ]
  }
 ],
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