Investigate Hotel Data Viz.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "aa2954bc-f394-45f2-92b3-04782df5f9e9",
   "metadata": {},
   "source": [
    "# Mini Project: Investigate Hotel Business using Data Visualization\n",
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4e518d0-b185-4a78-a38f-d3f3ab08beb3",
   "metadata": {},
   "source": [
    "## Latar Belakang"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28be0dff-db89-4a11-be43-4323f86e7785",
   "metadata": {},
   "source": [
    "Analisis kinerja bisnis merupakan kunci penting bagi perusahaan untuk mencapai keberhasilan dalam bisnisnya. Perusahaan dapat melakukan analisis untuk mengidentifikasi permasalahan, kelemahan, dan kekuatan yang dimilikinya. Dalam bisnis perhotelan, penting untuk memahami perilaku pelanggan. Dengan memahami perilaku pelanggan, perusahaan dapat mengetahui faktor apa saja yang mempengaruhi pelanggan dalam melakukan pemesanan hotel. Selain itu, perusahaan juga dapat mengidentifikasi produk atau layanan apa yang kurang laku di pasar. Hal ini dilakukan untuk menyesuaikan strategi bisnis yang tepat guna sehingga perusahaan dapat meningkatkan pengalaman pelanggan dan dapat mencapai tujuan bisnis jangka panjang."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce45e399-f1b7-4967-8087-5c0b9841096d",
   "metadata": {},
   "source": [
    "**Business Questions|**\n",
    "<br>\n",
    "\n",
    "* Jenis hotel apa yang paling sering dikunjungi oleh pelanggan?\n",
    "* Apakah durasi menginap mempengaruhi tingkat pembatalan pemesanan hotel?\n",
    "* Apakah jarak waktu antara pemesanan hotel dan hari kedatangan tamu mempengaruhi tingkat pembatalan pemesanan hotel?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0780b4d3-f088-4860-add1-74b2eb90b773",
   "metadata": {},
   "source": [
    "**Objektif**<br>\n",
    "\n",
    "Membuat visualisasi berbasis data sebagai insight bagi bisnis hotel"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdfbe0a7-dfb1-44d9-bf19-cbc13a8ff1f9",
   "metadata": {},
   "source": [
    "## Load Dataset\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6a51d199-2f55-4ab9-b424-74ed58c331b9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numpy version :  1.26.2\n",
      "pandas version :  2.0.3\n",
      "seaborn version :  0.12.2\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "print('numpy version : ',np.__version__)\n",
    "print('pandas version : ',pd.__version__)\n",
    "print('seaborn version : ',sns.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ecf4bd5c-401f-4523-8e62-29ed3d6bfe86",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>lead_time</th>\n",
       "      <th>arrival_date_year</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>arrival_date_week_number</th>\n",
       "      <th>arrival_date_day_of_month</th>\n",
       "      <th>stays_in_weekend_nights</th>\n",
       "      <th>stays_in_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</th>\n",
       "      <th>booking_changes</th>\n",
       "      <th>deposit_type</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "      <th>days_in_waiting_list</th>\n",
       "      <th>customer_type</th>\n",
       "      <th>adr</th>\n",
       "      <th>required_car_parking_spaces</th>\n",
       "      <th>total_of_special_requests</th>\n",
       "      <th>reservation_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55696</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>291</td>\n",
       "      <td>2018</td>\n",
       "      <td>October</td>\n",
       "      <td>34</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>Non Refund</td>\n",
       "      <td>39.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>115.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Canceled</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24360</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "      <td>2018</td>\n",
       "      <td>July</td>\n",
       "      <td>20</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>243.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Contract</td>\n",
       "      <td>73.75</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78799</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>December</td>\n",
       "      <td>42</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>99.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Family</td>\n",
       "      <td>100.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108876</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>2019</td>\n",
       "      <td>May</td>\n",
       "      <td>13</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>142.20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32078</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>2019</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>58.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
       "55696     City Hotel            1        291               2018   \n",
       "24360   Resort Hotel            0        114               2018   \n",
       "78799     City Hotel            0         14               2017   \n",
       "108876    City Hotel            0         81               2019   \n",
       "32078   Resort Hotel            0         11               2019   \n",
       "\n",
       "       arrival_date_month  arrival_date_week_number  \\\n",
       "55696             October                        34   \n",
       "24360                July                        20   \n",
       "78799            December                        42   \n",
       "108876                May                        13   \n",
       "32078               March                         2   \n",
       "\n",
       "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
       "55696                          19                        0   \n",
       "24360                          12                        2   \n",
       "78799                          15                        0   \n",
       "108876                         31                        1   \n",
       "32078                          12                        1   \n",
       "\n",
       "        stays_in_weekdays_nights  adults  ...  booking_changes  deposit_type  \\\n",
       "55696                          2       2  ...                0    Non Refund   \n",
       "24360                          5       2  ...                1    No Deposit   \n",
       "78799                          2       1  ...                0    No Deposit   \n",
       "108876                         2       2  ...                2    No Deposit   \n",
       "32078                          3       2  ...                0    No Deposit   \n",
       "\n",
       "        agent company days_in_waiting_list customer_type     adr  \\\n",
       "55696    39.0     NaN                    0      Personal  115.00   \n",
       "24360   243.0     NaN                    0      Contract   73.75   \n",
       "78799    99.0     NaN                    0        Family  100.00   \n",
       "108876    9.0     NaN                    0      Personal  142.20   \n",
       "32078   240.0     NaN                    0      Personal   58.00   \n",
       "\n",
       "        required_car_parking_spaces  total_of_special_requests  \\\n",
       "55696                             0                          0   \n",
       "24360                             0                          0   \n",
       "78799                             0                          0   \n",
       "108876                            0                          0   \n",
       "32078                             0                          0   \n",
       "\n",
       "        reservation_status  \n",
       "55696             Canceled  \n",
       "24360            Check-Out  \n",
       "78799            Check-Out  \n",
       "108876           Check-Out  \n",
       "32078            Check-Out  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('hotel_bookings_data.csv')\n",
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e7e98891-3a23-4d28-b89c-0d38ae440255",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 119390 entries, 0 to 119389\n",
      "Data columns (total 29 columns):\n",
      " #   Column                          Non-Null Count   Dtype  \n",
      "---  ------                          --------------   -----  \n",
      " 0   hotel                           119390 non-null  object \n",
      " 1   is_canceled                     119390 non-null  int64  \n",
      " 2   lead_time                       119390 non-null  int64  \n",
      " 3   arrival_date_year               119390 non-null  int64  \n",
      " 4   arrival_date_month              119390 non-null  object \n",
      " 5   arrival_date_week_number        119390 non-null  int64  \n",
      " 6   arrival_date_day_of_month       119390 non-null  int64  \n",
      " 7   stays_in_weekend_nights         119390 non-null  int64  \n",
      " 8   stays_in_weekdays_nights        119390 non-null  int64  \n",
      " 9   adults                          119390 non-null  int64  \n",
      " 10  children                        119386 non-null  float64\n",
      " 11  babies                          119390 non-null  int64  \n",
      " 12  meal                            119390 non-null  object \n",
      " 13  city                            118902 non-null  object \n",
      " 14  market_segment                  119390 non-null  object \n",
      " 15  distribution_channel            119390 non-null  object \n",
      " 16  is_repeated_guest               119390 non-null  int64  \n",
      " 17  previous_cancellations          119390 non-null  int64  \n",
      " 18  previous_bookings_not_canceled  119390 non-null  int64  \n",
      " 19  booking_changes                 119390 non-null  int64  \n",
      " 20  deposit_type                    119390 non-null  object \n",
      " 21  agent                           103050 non-null  float64\n",
      " 22  company                         6797 non-null    float64\n",
      " 23  days_in_waiting_list            119390 non-null  int64  \n",
      " 24  customer_type                   119390 non-null  object \n",
      " 25  adr                             119390 non-null  float64\n",
      " 26  required_car_parking_spaces     119390 non-null  int64  \n",
      " 27  total_of_special_requests       119390 non-null  int64  \n",
      " 28  reservation_status              119390 non-null  object \n",
      "dtypes: float64(4), int64(16), object(9)\n",
      "memory usage: 26.4+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a36c7be-aac5-4129-8bbf-c335df065db2",
   "metadata": {},
   "source": [
    "* Dataset berjumlah **119390** baris dan **29** fitur\n",
    "* Tipe data dalam dataset: **float64**, **int64**, dan **object**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4026e1f7-d3c1-494d-988b-45ec41041c86",
   "metadata": {},
   "source": [
    "### Check value dari tiap fitur"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "00c78a79-fbdb-4ce3-8b76-25a5cd67dad0",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hotel memiliki 2 unique values: object\n",
      "hotel values: ['Resort Hotel' 'City Hotel']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "is_canceled memiliki 2 unique values: int64\n",
      "is_canceled values: [0 1]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "lead_time memiliki 479 unique values: int64\n",
      "lead_time values: [342 737   7  13  14   0   9  85  75  23  35  68  18  37  12  72 127  78\n",
      "  48  60  77  99 118  95  96  69  45  40  15  36  43  70  16 107  47 113\n",
      "  90  50  93  76   3   1  10   5  17  51  71  63  62 101   2  81 368 364\n",
      " 324  79  21 109 102   4  98  92  26  73 115  86  52  29  30  33  32   8\n",
      " 100  44  80  97  64  39  34  27  82  94 110 111  84  66 104  28 258 112\n",
      "  65  67  55  88  54 292  83 105 280 394  24 103 366 249  22  91  11 108\n",
      " 106  31  87  41 304 117  59  53  58 116  42 321  38  56  49 317   6  57\n",
      "  19  25 315 123  46  89  61 312 299 130  74 298 119  20 286 136 129 124\n",
      " 327 131 460 140 114 139 122 137 126 120 128 135 150 143 151 132 125 157\n",
      " 147 138 156 164 346 159 160 161 333 381 149 154 297 163 314 155 323 340\n",
      " 356 142 328 144 336 248 302 175 344 382 146 170 166 338 167 310 148 165\n",
      " 172 171 145 121 178 305 173 152 354 347 158 185 349 183 352 177 200 192\n",
      " 361 207 174 330 134 350 334 283 153 197 133 241 193 235 194 261 260 216\n",
      " 169 209 238 215 141 189 187 223 284 214 202 211 168 230 203 188 232 709\n",
      " 219 162 196 190 259 228 176 250 201 186 199 180 206 205 224 222 182 210\n",
      " 275 212 229 218 208 191 181 179 246 255 226 288 253 252 262 236 256 234\n",
      " 254 468 213 237 198 195 239 263 265 274 217 220 307 221 233 257 227 276\n",
      " 225 264 311 277 204 290 266 270 294 319 282 251 322 291 269 240 271 184\n",
      " 231 268 247 273 300 301 267 244 306 293 309 272 242 295 285 243 308 398\n",
      " 303 245 424 279 331 281 339 434 357 325 329 278 332 343 345 360 348 367\n",
      " 353 373 374 406 400 326 379 399 316 341 320 385 355 363 358 296 422 390\n",
      " 335 370 376 375 397 289 542 403 383 384 359 393 337 362 365 435 386 378\n",
      " 313 351 287 471 462 411 450 318 372 371 454 532 445 389 388 407 443 437\n",
      " 451 391 405 412 419 420 426 433 440 429 418 447 461 605 457 475 464 482\n",
      " 626 489 496 503 510 517 524 531 538 545 552 559 566 573 580 587 594 601\n",
      " 608 615 622 629 396 410 395 423 408 409 448 465 387 414 476 479 467 490\n",
      " 493 478 504 507 458 518 521 377 444 380 463]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "arrival_date_year memiliki 3 unique values: int64\n",
      "arrival_date_year values: [2017 2018 2019]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "arrival_date_month memiliki 12 unique values: object\n",
      "arrival_date_month values: ['September' 'October' 'November' 'December' 'January' 'February' 'March'\n",
      " 'April' 'May' 'June' 'July' 'August']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "arrival_date_week_number memiliki 53 unique values: int64\n",
      "arrival_date_week_number values: [27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50\n",
      " 51 52 53  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21\n",
      " 22 23 24 25 26]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "arrival_date_day_of_month memiliki 31 unique values: int64\n",
      "arrival_date_day_of_month values: [ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24\n",
      " 25 26 27 28 29 30 31]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "stays_in_weekend_nights memiliki 17 unique values: int64\n",
      "stays_in_weekend_nights values: [ 0  1  2  4  3  6 13  8  5  7 12  9 16 18 19 10 14]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "stays_in_weekdays_nights memiliki 35 unique values: int64\n",
      "stays_in_weekdays_nights values: [ 0  1  2  3  4  5 10 11  8  6  7 15  9 12 33 20 14 16 21 13 30 19 24 40\n",
      " 22 42 50 25 17 32 26 18 34 35 41]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "adults memiliki 14 unique values: int64\n",
      "adults values: [ 2  1  3  4 40 26 50 27 55  0 20  6  5 10]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "children memiliki 5 unique values: float64\n",
      "children values: [ 0.  1.  2. 10.  3. nan]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "babies memiliki 5 unique values: int64\n",
      "babies values: [ 0  1  2 10  9]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "meal memiliki 5 unique values: object\n",
      "meal values: ['Breakfast' 'Full Board' 'Dinner' 'No Meal' 'Undefined']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "city memiliki 177 unique values: object\n",
      "city values: ['Kota Denpasar' 'Kabupaten Bangka' 'Kabupaten Sleman' 'Kota Batu'\n",
      " 'Kota Malang' 'Kota Yogyakarta' nan 'Kabupaten Tangerang' 'Kota Semarang'\n",
      " 'Kota Serang' 'Kota Tangerang' 'Kota Bogor' 'Kabupaten Bandung'\n",
      " 'Kabupaten Magelang' 'Kabupaten Sumedang' 'Kota Jakarta Timur'\n",
      " 'Kabupaten Purwakarta' 'Kabupaten Kepulauan Seribu' 'Kabupaten Belitung'\n",
      " 'Kota Jakarta Pusat' 'Kota Jakarta Selatan' 'Kota Surabaya'\n",
      " 'Kota Jakarta Utara' 'Kota Gorontalo' 'Kota Jambi' 'Kota Jakarta Barat'\n",
      " 'Kota Bengkulu' 'Kabupaten Bandung Barat' 'Kabupaten Bekasi'\n",
      " 'Kabupaten Bogor' 'Kabupaten Ciamis' 'Kabupaten Cianjur'\n",
      " 'Kabupaten Cirebon' 'Kota Cimahi' 'Kabupaten Indramayu'\n",
      " 'Kabupaten Karawang' 'Kabupaten Kuningan' 'Kabupaten Majalengka'\n",
      " 'Kabupaten Serang' 'Kota Pangkal Pinang' 'Kabupaten Subang'\n",
      " 'Kabupaten Sukabumi' 'Kabupaten Garut' 'Kabupaten Tasikmalaya'\n",
      " 'Kota Bandung' 'Kota Banjar' 'Kota Bekasi' 'Kabupaten Pandeglang'\n",
      " 'Kabupaten Pangandaran' 'Kota Cirebon' 'Kota Depok' 'Kota Sukabumi'\n",
      " 'Kota Tasikmalaya' 'Kabupaten Banjarnegara' 'Kabupaten Banyumas'\n",
      " 'Kabupaten Batang' 'Kabupaten Blora' 'Kabupaten Boyolali'\n",
      " 'Kabupaten Brebes' 'Kabupaten Cilacap' 'Kabupaten Demak'\n",
      " 'Kabupaten Grobogan' 'Kabupaten Jepara' 'Kabupaten Karanganyar'\n",
      " 'Kabupaten Kebumen' 'Kabupaten Kendal' 'Kabupaten Klaten'\n",
      " 'Kabupaten Kudus' 'Kota Kediri' 'Kabupaten Pati' 'Kabupaten Pekalongan'\n",
      " 'Kabupaten Pemalang' 'Kabupaten Purbalingga' 'Kabupaten Purworejo'\n",
      " 'Kabupaten Rembang' 'Kabupaten Semarang' 'Kabupaten Sragen'\n",
      " 'Kabupaten Sukoharjo' 'Kabupaten Tegal' 'Kabupaten Temanggung'\n",
      " 'Kabupaten Wonogiri' 'Kabupaten Wonosobo' 'Kota Magelang'\n",
      " 'Kota Pekalongan' 'Kota Salatiga' 'Kabupaten Bantul' 'Kota Surakarta'\n",
      " 'Kota Tegal' 'Kabupaten Bangkalan' 'Kabupaten Banyuwangi'\n",
      " 'Kabupaten Blitar' 'Kabupaten Bojonegoro' 'Kabupaten Bondowoso'\n",
      " 'Kabupaten Gresik' 'Kabupaten Jember' 'Kabupaten Jombang'\n",
      " 'Kabupaten Kediri' 'Kabupaten Lamongan' 'Kabupaten Lumajang'\n",
      " 'Kabupaten Madiun' 'Kabupaten Magetan' 'Kabupaten Kerinci'\n",
      " 'Kabupaten Mojokerto' 'Kabupaten Nganjuk' 'Kabupaten Ngawi'\n",
      " 'Kabupaten Pacitan' 'Kabupaten Pamekasan' 'Kabupaten Pasuruan'\n",
      " 'Kabupaten Ponorogo' 'Kabupaten Probolinggo' 'Kabupaten Sampang'\n",
      " 'Kabupaten Sidoarjo' 'Kabupaten Situbondo' 'Kabupaten Sumenep'\n",
      " 'Kabupaten Trenggalek' 'Kabupaten Tuban' 'Kabupaten Tulungagung'\n",
      " 'Kabupaten Gunung Kidul' 'Kota Blitar' 'Kota Tangerang Selatan'\n",
      " 'Kota Madiun' 'Kota Cilegon' 'Kota Mojokerto' 'Kota Pasuruan'\n",
      " 'Kota Probolinggo' 'Kabupaten Malang' 'Kabupaten Kapuas Hulu'\n",
      " 'Kabupaten Ketapang' 'Kota Pontianak' 'Kabupaten Banjar'\n",
      " 'Kabupaten Barito Kuala' 'Kota Banjarbaru' 'Kota Banjarmasin'\n",
      " 'Kabupaten Kapuas' 'Kabupaten Katingan' 'Kabupaten Kotawaringin Barat'\n",
      " 'Kabupaten Kotawaringin Timur' 'Kabupaten Musi Banyuasin'\n",
      " 'Kabupaten Murung Raya' 'Kota Palembang' 'Kabupaten Seruyan'\n",
      " 'Kabupaten Sukamara' 'Kota Palangka Raya' 'Kota Balikpapan'\n",
      " 'Kota Bontang' 'Kota Samarinda' 'Kabupaten Berau' 'Kabupaten Kutai Barat'\n",
      " 'Kota Tarakan' 'Kota Batam' 'Kabupaten Pesisir Barat'\n",
      " 'Kabupaten Pringsewu' 'Kota Bandar Lampung' 'Kota Lampung Timur'\n",
      " 'Kota Ambon' 'Kabupaten Kepulauan Aru' 'Kabupaten Maluku Barat Daya'\n",
      " 'Kabupaten Maluku Tengah' 'Kabupaten Maluku Tenggara'\n",
      " 'Kabupaten Maluku Tenggara Barat' 'Kabupaten Halmahera Selatan'\n",
      " 'Kota Ternate' 'Kota Tidore Kepulauan' 'Kabupaten Aceh Jaya'\n",
      " 'Kota Banda Aceh' 'Kota Lhokseumawe' 'Kota Sabang'\n",
      " 'Kabupaten Lombok Barat' 'Kabupaten Sumbawa' 'Kota Mataram'\n",
      " 'Kabupaten Flores Timur' 'Kabupaten Timor Tengah Selatan' 'Kota Jayapura'\n",
      " 'Kota Bukittinggi' 'Kota Padang' 'Kabupaten Nias' 'Kota Binjai' 'Medan']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "market_segment memiliki 8 unique values: object\n",
      "market_segment values: ['Direct' 'Corporate' 'Online TA' 'Offline TA/TO' 'Complementary' 'Groups'\n",
      " 'Undefined' 'Aviation']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "distribution_channel memiliki 5 unique values: object\n",
      "distribution_channel values: ['Direct' 'Corporate' 'TA/TO' 'Undefined' 'GDS']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "is_repeated_guest memiliki 2 unique values: int64\n",
      "is_repeated_guest values: [0 1]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "previous_cancellations memiliki 15 unique values: int64\n",
      "previous_cancellations values: [ 0  1  2  3 26 25 14  4 24 19  5 21  6 13 11]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "previous_bookings_not_canceled memiliki 73 unique values: int64\n",
      "previous_bookings_not_canceled values: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 20 21 22 23 24\n",
      " 25 27 28 29 30 19 26 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47\n",
      " 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71\n",
      " 72]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "booking_changes memiliki 21 unique values: int64\n",
      "booking_changes values: [ 3  4  0  1  2  5 17  6  8  7 10 16  9 13 12 20 14 15 11 21 18]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "deposit_type memiliki 3 unique values: object\n",
      "deposit_type values: ['No Deposit' 'Refundable' 'Non Refund']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "agent memiliki 333 unique values: float64\n",
      "agent values: [ nan 304. 240. 303.  15. 241.   8. 250. 115.   5. 175. 134. 156. 243.\n",
      " 242.   3. 105.  40. 147. 306. 184.  96.   2. 127.  95. 146.   9. 177.\n",
      "   6. 143. 244. 149. 167. 300. 171. 305.  67. 196. 152. 142. 261. 104.\n",
      "  36.  26.  29. 258. 110.  71. 181.  88. 251. 275.  69. 248. 208. 256.\n",
      " 314. 126. 281. 273. 253. 185. 330. 334. 328. 326. 321. 324. 313.  38.\n",
      " 155.  68. 335. 308. 332.  94. 348. 310. 339. 375.  66. 327. 387. 298.\n",
      "  91. 245. 385. 257. 393. 168. 405. 249. 315.  75. 128. 307.  11. 436.\n",
      "   1. 201. 183. 223. 368. 336. 291. 464. 411. 481.  10. 154. 468. 410.\n",
      " 390. 440. 495. 492. 493. 434.  57. 531. 420. 483. 526. 472. 429.  16.\n",
      " 446.  34.  78. 139. 252. 270.  47. 114. 301. 193. 182. 135. 350. 195.\n",
      " 352. 355. 159. 363. 384. 360. 331. 367.  64. 406. 163. 414. 333. 427.\n",
      " 431. 430. 426. 438. 433. 418. 441. 282. 432.  72. 450. 180. 454. 455.\n",
      "  59. 451. 254. 358. 469. 165. 467. 510. 337. 476. 502. 527. 479. 508.\n",
      " 535. 302. 497. 187.  13.   7.  27.  14.  22.  17.  28.  42.  20.  19.\n",
      "  45.  37.  61.  39.  21.  24.  41.  50.  30.  54.  52.  12.  44.  31.\n",
      "  83.  32.  63.  60.  55.  56.  89.  87. 118.  86.  85. 210. 214. 129.\n",
      " 179. 138. 174. 170. 153.  93. 151. 119.  35. 173.  58.  53. 133.  79.\n",
      " 235. 192. 191. 236. 162. 215. 157. 287. 132. 234.  98.  77. 103. 107.\n",
      " 262. 220. 121. 205. 378.  23. 296. 290. 229.  33. 286. 276. 425. 484.\n",
      " 323. 403. 219. 394. 509. 111. 423.   4.  70.  82.  81.  74.  92.  99.\n",
      "  90. 112. 117. 106. 148. 158. 144. 211. 213. 216. 232. 150. 267. 227.\n",
      " 247. 278. 280. 285. 289. 269. 295. 265. 288. 122. 294. 325. 341. 344.\n",
      " 346. 359. 283. 364. 370. 371.  25. 141. 391. 397. 416. 404. 299. 197.\n",
      "  73. 354. 444. 408. 461. 388. 453. 459. 474. 475. 480. 449.]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "company memiliki 352 unique values: float64\n",
      "company values: [ nan 110. 113. 270. 178. 240. 154. 144. 307. 268.  59. 204. 312. 318.\n",
      "  94. 174. 274. 195. 223. 317. 281. 118.  53. 286.  12.  47. 324. 342.\n",
      " 373. 371. 383.  86.  82. 218.  88.  31. 397. 392. 405. 331. 367.  20.\n",
      "  83. 416.  51. 395. 102.  34.  84. 360. 394. 457. 382. 461. 478. 386.\n",
      " 112. 486. 421.   9. 308. 135. 224. 504. 269. 356. 498. 390. 513. 203.\n",
      " 263. 477. 521. 169. 515. 445. 337. 251. 428. 292. 388. 130. 250. 355.\n",
      " 254. 543. 531. 528.  62. 120.  42.  81. 116. 530. 103.  39.  16.  92.\n",
      "  61. 501. 165. 291. 290.  43. 325. 192. 108. 200. 465. 287. 297. 490.\n",
      " 482. 207. 282. 437. 225. 329. 272.  28.  77. 338.  72. 246. 319. 146.\n",
      " 159. 380. 323. 511. 407. 278.  80. 403. 399.  14. 137. 343. 346. 347.\n",
      " 349. 289. 351. 353.  54.  99. 358. 361. 362. 366. 372. 365. 277. 109.\n",
      " 377. 379.  22. 378. 330. 364. 401. 232. 255. 384. 167. 212. 514. 391.\n",
      " 400. 376. 402. 396. 302. 398.   6. 370. 369. 409. 168. 104. 408. 413.\n",
      " 148.  10. 333. 419. 415. 424. 425. 423. 422. 435. 439. 442. 448. 443.\n",
      " 454. 444.  52. 459. 458. 456. 460. 447. 470. 466. 484. 184. 485.  32.\n",
      " 487. 491. 494. 193. 516. 496. 499.  29.  78. 520. 507. 506. 512. 126.\n",
      "  64. 242. 518. 523. 539. 534. 436. 525. 541.  40. 455. 410.  45.  38.\n",
      "  49.  48.  67.  68.  65.  91.  37.   8. 179. 209. 219. 221. 227. 153.\n",
      " 186. 253. 202. 216. 275. 233. 280. 309. 321.  93. 316.  85. 107. 350.\n",
      " 279. 334. 348. 150.  73. 385. 418. 197. 450. 452. 115.  46.  76.  96.\n",
      " 100. 105. 101. 122.  11. 139. 142. 127. 143. 140. 149. 163. 160. 180.\n",
      " 238. 183. 222. 185. 217. 215. 213. 237. 230. 234.  35. 245. 158. 258.\n",
      " 259. 260. 411. 257. 271.  18. 106. 210. 273.  71. 284. 301. 305. 293.\n",
      " 264. 311. 304. 313. 288. 320. 314. 332. 341. 352. 243. 368. 393. 132.\n",
      " 220. 412. 420. 426. 417. 429. 433. 446. 357. 479. 483. 489. 229. 481.\n",
      " 497. 451. 492.]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "days_in_waiting_list memiliki 128 unique values: int64\n",
      "days_in_waiting_list values: [  0  50  47  65 122  75 101 150 125  14  60  34 100  22 121  61  39   5\n",
      "   1   8 107  43  52   2  11 142 116  13  44  97  83   4 113  18  20 185\n",
      "  93 109   6  37 105 154  64  99  38  48  33  77  21  80  59  40  58  89\n",
      "  53  49  69  87  91  57 111  79  98  85  63  15   3  41 224  31  56 187\n",
      " 176  71  55  96 236 259 207 215 160 120  30  32  27  62  24 108 147 379\n",
      "  70  35 178 330 223 174 162 391  68 193  10  76  16  28   9 165  17  25\n",
      "  46   7  84 175 183  23 117  12  54  26  73  45  19  42  72  81  92  74\n",
      " 167  36]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "customer_type memiliki 4 unique values: object\n",
      "customer_type values: ['Personal' 'Contract' 'Family' 'Bussiness']\n",
      "----------------------------------------------------------------------------------------------------\n",
      "adr memiliki 8879 unique values: float64\n",
      "adr values: [  0.    75.    98.   ... 266.75 209.25 157.71]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "required_car_parking_spaces memiliki 5 unique values: int64\n",
      "required_car_parking_spaces values: [0 1 2 8 3]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "total_of_special_requests memiliki 6 unique values: int64\n",
      "total_of_special_requests values: [0 1 3 2 4 5]\n",
      "----------------------------------------------------------------------------------------------------\n",
      "reservation_status memiliki 3 unique values: object\n",
      "reservation_status values: ['Check-Out' 'Canceled' 'No-Show']\n",
      "----------------------------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for col in df.columns:\n",
    "    print(\"{} memiliki {} unique values: {}\".format(col, df[col].nunique(), df[col].dtypes))\n",
    "    if df[col].dtypes == 'int64' or df[col].dtypes == 'float64' or df[col].dtypes == 'object':\n",
    "        print(\"{} values: {}\".format(col,df[col].unique()))\n",
    "        print('-' * 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae0b3f61-f22b-47c1-9aab-895ef040ca47",
   "metadata": {},
   "source": [
    "## Data Cleansing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e856959-04bf-428e-bb8e-11e353be829e",
   "metadata": {},
   "source": [
    "### 1. Checking null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "96e4131e-41f9-44bd-95fd-201120eb166c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                Jumlah Null  Rasio Null %\n",
      "hotel                                     0      0.000000\n",
      "is_canceled                               0      0.000000\n",
      "lead_time                                 0      0.000000\n",
      "arrival_date_year                         0      0.000000\n",
      "arrival_date_month                        0      0.000000\n",
      "arrival_date_week_number                  0      0.000000\n",
      "arrival_date_day_of_month                 0      0.000000\n",
      "stays_in_weekend_nights                   0      0.000000\n",
      "stays_in_weekdays_nights                  0      0.000000\n",
      "adults                                    0      0.000000\n",
      "children                                  4      0.003350\n",
      "babies                                    0      0.000000\n",
      "meal                                      0      0.000000\n",
      "city                                    488      0.408744\n",
      "market_segment                            0      0.000000\n",
      "distribution_channel                      0      0.000000\n",
      "is_repeated_guest                         0      0.000000\n",
      "previous_cancellations                    0      0.000000\n",
      "previous_bookings_not_canceled            0      0.000000\n",
      "booking_changes                           0      0.000000\n",
      "deposit_type                              0      0.000000\n",
      "agent                                 16340     13.686238\n",
      "company                              112593     94.306893\n",
      "days_in_waiting_list                      0      0.000000\n",
      "customer_type                             0      0.000000\n",
      "adr                                       0      0.000000\n",
      "required_car_parking_spaces               0      0.000000\n",
      "total_of_special_requests                 0      0.000000\n",
      "reservation_status                        0      0.000000\n"
     ]
    }
   ],
   "source": [
    "jumlah_null = df.isnull().sum()\n",
    "rasio_null = jumlah_null / len(df) * 100\n",
    "df_rasio_null = pd.DataFrame({'Jumlah Null': jumlah_null,\n",
    "                             'Rasio Null %': rasio_null})\n",
    "\n",
    "print(df_rasio_null)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64dfb87a-c5f4-4b2d-a8d1-124004369f7f",
   "metadata": {},
   "source": [
    "**Fitur yang memiliki null value:**\n",
    "* children\n",
    "* city\n",
    "* agent\n",
    "* company"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf7d2b65-8159-4723-b0db-52f8a09cfcad",
   "metadata": {},
   "source": [
    "### 2. Mengatasi null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8615cc62-469d-4dbd-9b0d-2f1ba9b09750",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# mengisi fitur dengan nilai 0\n",
    "\n",
    "df['children'] = df['children'].fillna(0)\n",
    "df['agent'] = df['agent'].fillna(0)\n",
    "df['company'] = df['company'].fillna(0)\n",
    "\n",
    "\n",
    "# fitur city diisni dengan 'unknown'\n",
    "df['city'] = df['city'].fillna('unknown')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "788f9819-cee7-4a41-969a-273f4a5fb958",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hotel                             0\n",
       "is_canceled                       0\n",
       "lead_time                         0\n",
       "arrival_date_year                 0\n",
       "arrival_date_month                0\n",
       "arrival_date_week_number          0\n",
       "arrival_date_day_of_month         0\n",
       "stays_in_weekend_nights           0\n",
       "stays_in_weekdays_nights          0\n",
       "adults                            0\n",
       "children                          0\n",
       "babies                            0\n",
       "meal                              0\n",
       "city                              0\n",
       "market_segment                    0\n",
       "distribution_channel              0\n",
       "is_repeated_guest                 0\n",
       "previous_cancellations            0\n",
       "previous_bookings_not_canceled    0\n",
       "booking_changes                   0\n",
       "deposit_type                      0\n",
       "agent                             0\n",
       "company                           0\n",
       "days_in_waiting_list              0\n",
       "customer_type                     0\n",
       "adr                               0\n",
       "required_car_parking_spaces       0\n",
       "total_of_special_requests         0\n",
       "reservation_status                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77451eef-616a-4ecb-a45d-f8eb8b98a993",
   "metadata": {},
   "source": [
    "### 3. Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9a603a85-03f2-42e2-96c3-bf113a944ae0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# ubah value yang tidak sesuai pada fitur meal\n",
    "df['meal'] = df['meal'].replace({'Breakfast': 'with meal',\n",
    "                                 'Dinner': 'with meal',\n",
    "                                 'No Meal': 'no meal',\n",
    "                                 'Undefined': 'no meal',\n",
    "                                 'Full Board': 'with meal'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "424e3a6f-be41-48b1-bbcf-e3c6ccdda80f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "meal\n",
       "with meal    107571\n",
       "no meal       11819\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['meal'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30fd57d7-d2f3-4aca-bf25-11a1030e6ccc",
   "metadata": {},
   "source": [
    "## Analisis Jumlah Pemesanan Hotel per Bulan Berdasarkan Tipe Hotel\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f666490b-f987-4ed5-b706-f3a50cdeb1ba",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>lead_time</th>\n",
       "      <th>arrival_date_year</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>arrival_date_week_number</th>\n",
       "      <th>arrival_date_day_of_month</th>\n",
       "      <th>stays_in_weekend_nights</th>\n",
       "      <th>stays_in_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</th>\n",
       "      <th>booking_changes</th>\n",
       "      <th>deposit_type</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "      <th>days_in_waiting_list</th>\n",
       "      <th>customer_type</th>\n",
       "      <th>adr</th>\n",
       "      <th>required_car_parking_spaces</th>\n",
       "      <th>total_of_special_requests</th>\n",
       "      <th>reservation_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>342</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>737</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>304.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n",
       "0  Resort Hotel            0        342               2017          September   \n",
       "1  Resort Hotel            0        737               2017          September   \n",
       "2  Resort Hotel            0          7               2017          September   \n",
       "3  Resort Hotel            0         13               2017          September   \n",
       "4  Resort Hotel            0         14               2017          September   \n",
       "\n",
       "   arrival_date_week_number  arrival_date_day_of_month  \\\n",
       "0                        27                          1   \n",
       "1                        27                          1   \n",
       "2                        27                          1   \n",
       "3                        27                          1   \n",
       "4                        27                          1   \n",
       "\n",
       "   stays_in_weekend_nights  stays_in_weekdays_nights  adults  ...  \\\n",
       "0                        0                         0       2  ...   \n",
       "1                        0                         0       2  ...   \n",
       "2                        0                         1       1  ...   \n",
       "3                        0                         1       1  ...   \n",
       "4                        0                         2       2  ...   \n",
       "\n",
       "   booking_changes  deposit_type  agent company days_in_waiting_list  \\\n",
       "0                3    No Deposit    0.0     0.0                    0   \n",
       "1                4    No Deposit    0.0     0.0                    0   \n",
       "2                0    No Deposit    0.0     0.0                    0   \n",
       "3                0    No Deposit  304.0     0.0                    0   \n",
       "4                0    No Deposit  240.0     0.0                    0   \n",
       "\n",
       "  customer_type   adr  required_car_parking_spaces  total_of_special_requests  \\\n",
       "0      Personal   0.0                            0                          0   \n",
       "1      Personal   0.0                            0                          0   \n",
       "2      Personal  75.0                            0                          0   \n",
       "3      Personal  75.0                            0                          0   \n",
       "4      Personal  98.0                            0                          1   \n",
       "\n",
       "   reservation_status  \n",
       "0           Check-Out  \n",
       "1           Check-Out  \n",
       "2           Check-Out  \n",
       "3           Check-Out  \n",
       "4           Check-Out  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8b5a03c3-497f-4e7d-81a6-bc5f1e42a640",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Resort Hotel', 'City Hotel'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['hotel'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "46fd0dc2-4887-4db1-b453-5e7b400caa9b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hotel\n",
       "City Hotel      79330\n",
       "Resort Hotel    40060\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hotel_counts = df['hotel'].value_counts()\n",
    "hotel_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "35b027a9-a4f2-4fde-9df6-ca598c1a7d74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = hotel_counts.index\n",
    "sizes = hotel_counts.values\n",
    "\n",
    "plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)\n",
    "plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.title('Rasio total pemesanan Hotel berdasarkan jenis Hotel')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0a093c4-c66a-45fd-9105-ad83c8b73349",
   "metadata": {},
   "source": [
    "* Kategori \"City Hotel\" lebih banyak di book oleh pelanggan sebesar 66,4% dibandingkan \"Resort Hotel\".\n",
    "* Perbedaan nilai distribusi tersebut mungkin disebabkan oleh tujuan pelanggan dalam memesan Hotel. City Hotel biasanya terletak di area strategis perkotaan, dan mudah diakses. Sedangkan Resort Hotel terletak di area pantai, pegunungan, dll dan biasanya dituju oleh pelanggan yang berlibur dan bersantai."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fad93314-f385-4f67-8278-337794b14aa4",
   "metadata": {},
   "source": [
    "### Rata-rata Total Booking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3c87c4a0-0f93-45ac-8558-be771de3035c",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>lead_time</th>\n",
       "      <th>arrival_date_year</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>arrival_date_week_number</th>\n",
       "      <th>arrival_date_day_of_month</th>\n",
       "      <th>stays_in_weekend_nights</th>\n",
       "      <th>stays_in_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</th>\n",
       "      <th>booking_changes</th>\n",
       "      <th>deposit_type</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "      <th>days_in_waiting_list</th>\n",
       "      <th>customer_type</th>\n",
       "      <th>adr</th>\n",
       "      <th>required_car_parking_spaces</th>\n",
       "      <th>total_of_special_requests</th>\n",
       "      <th>reservation_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>892</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>61</td>\n",
       "      <td>2017</td>\n",
       "      <td>October</td>\n",
       "      <td>32</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>153.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Canceled</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105270</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2019</td>\n",
       "      <td>April</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>396.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Family</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7342</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>199</td>\n",
       "      <td>2018</td>\n",
       "      <td>October</td>\n",
       "      <td>32</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Canceled</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43450</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>2017</td>\n",
       "      <td>November</td>\n",
       "      <td>38</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Family</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60356</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>277</td>\n",
       "      <td>2018</td>\n",
       "      <td>January</td>\n",
       "      <td>46</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>Non Refund</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Canceled</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
       "892     Resort Hotel            1         61               2017   \n",
       "105270    City Hotel            0          4               2019   \n",
       "7342    Resort Hotel            1        199               2018   \n",
       "43450     City Hotel            0         74               2017   \n",
       "60356     City Hotel            1        277               2018   \n",
       "\n",
       "       arrival_date_month  arrival_date_week_number  \\\n",
       "892               October                        32   \n",
       "105270              April                         5   \n",
       "7342              October                        32   \n",
       "43450            November                        38   \n",
       "60356             January                        46   \n",
       "\n",
       "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
       "892                             3                        2   \n",
       "105270                          3                        0   \n",
       "7342                            4                        2   \n",
       "43450                          18                        0   \n",
       "60356                           7                        1   \n",
       "\n",
       "        stays_in_weekdays_nights  adults  ...  booking_changes  deposit_type  \\\n",
       "892                            5       2  ...                0    No Deposit   \n",
       "105270                         1       1  ...                1    No Deposit   \n",
       "7342                           3       2  ...                0    No Deposit   \n",
       "43450                          2       2  ...                0    No Deposit   \n",
       "60356                          2       2  ...                0    Non Refund   \n",
       "\n",
       "        agent company days_in_waiting_list customer_type    adr  \\\n",
       "892     240.0     0.0                    0      Personal  153.0   \n",
       "105270    0.0   396.0                    0        Family   80.0   \n",
       "7342    240.0     0.0                    0      Personal  240.0   \n",
       "43450     6.0     0.0                    0        Family  109.0   \n",
       "60356     0.0     0.0                    0      Personal  100.0   \n",
       "\n",
       "        required_car_parking_spaces  total_of_special_requests  \\\n",
       "892                               0                          0   \n",
       "105270                            0                          0   \n",
       "7342                              0                          1   \n",
       "43450                             0                          0   \n",
       "60356                             0                          0   \n",
       "\n",
       "        reservation_status  \n",
       "892               Canceled  \n",
       "105270           Check-Out  \n",
       "7342              Canceled  \n",
       "43450            Check-Out  \n",
       "60356             Canceled  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b6f8ce99-069f-4448-bc3d-edd492e35c2d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hotel</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>nunique_year</th>\n",
       "      <th>total_bookings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>4965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>7894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>7605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>4132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>4357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>8232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>7480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>3736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>6458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>7400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>8983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>8088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>3103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>3045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>3555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>2648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>2437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>3559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>3609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>2193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>3336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>3108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>4894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>4573</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel arrival_date_month  nunique_year  total_bookings\n",
       "0     City Hotel              April             2            4965\n",
       "1     City Hotel             August             2            7894\n",
       "2     City Hotel           December             2            7605\n",
       "3     City Hotel           February             2            4132\n",
       "4     City Hotel            January             2            4357\n",
       "5     City Hotel               July             2            8232\n",
       "6     City Hotel               June             2            7480\n",
       "7     City Hotel              March             2            3736\n",
       "8     City Hotel                May             2            6458\n",
       "9     City Hotel           November             2            7400\n",
       "10    City Hotel            October             3            8983\n",
       "11    City Hotel          September             3            8088\n",
       "12  Resort Hotel              April             2            3103\n",
       "13  Resort Hotel             August             2            3045\n",
       "14  Resort Hotel           December             2            3555\n",
       "15  Resort Hotel           February             2            2648\n",
       "16  Resort Hotel            January             2            2437\n",
       "17  Resort Hotel               July             2            3559\n",
       "18  Resort Hotel               June             2            3609\n",
       "19  Resort Hotel              March             2            2193\n",
       "20  Resort Hotel                May             2            3336\n",
       "21  Resort Hotel           November             2            3108\n",
       "22  Resort Hotel            October             3            4894\n",
       "23  Resort Hotel          September             3            4573"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly_book = df.groupby(['hotel', 'arrival_date_month'])['arrival_date_year'].agg(['nunique', 'count']).reset_index()\n",
    "\n",
    "# Rename the columns for clarity\n",
    "monthly_book.columns = ['hotel', 'arrival_date_month', 'nunique_year', 'total_bookings']\n",
    "\n",
    "# Display the result\n",
    "monthly_book"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bb393fb-cfb5-41f7-ac3c-08c80beaab29",
   "metadata": {},
   "source": [
    "* Pada bulan September dan Oktober didapatkan nilai nunique_year = 3, artinya bulan tersebut tercatat pada 3 tahun yang berbeda yaitu 2017, 2018, dan 2019. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4311d75-2a49-4a08-a480-5de41ca441cd",
   "metadata": {},
   "source": [
    "### Normalisasi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "afdeab82-d474-4be5-ab69-a79aab522f55",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hotel</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>nunique_year</th>\n",
       "      <th>total_bookings</th>\n",
       "      <th>average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>4965</td>\n",
       "      <td>2482.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>7894</td>\n",
       "      <td>3947.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
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       "      <td>3802.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>4132</td>\n",
       "      <td>2066.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>4357</td>\n",
       "      <td>2178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>8232</td>\n",
       "      <td>4116.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>7480</td>\n",
       "      <td>3740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>3736</td>\n",
       "      <td>1868.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>6458</td>\n",
       "      <td>3229.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>7400</td>\n",
       "      <td>3700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>8983</td>\n",
       "      <td>2994.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>8088</td>\n",
       "      <td>2696.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>3103</td>\n",
       "      <td>1552.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>3045</td>\n",
       "      <td>1522.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>3555</td>\n",
       "      <td>1778.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>2648</td>\n",
       "      <td>1324.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>2437</td>\n",
       "      <td>1218.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>3559</td>\n",
       "      <td>1780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>3609</td>\n",
       "      <td>1804.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>2193</td>\n",
       "      <td>1096.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>3336</td>\n",
       "      <td>1668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>3108</td>\n",
       "      <td>1554.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>4894</td>\n",
       "      <td>1631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>4573</td>\n",
       "      <td>1524.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel arrival_date_month  nunique_year  total_bookings  average\n",
       "0     City Hotel              April             2            4965   2482.0\n",
       "1     City Hotel             August             2            7894   3947.0\n",
       "2     City Hotel           December             2            7605   3802.0\n",
       "3     City Hotel           February             2            4132   2066.0\n",
       "4     City Hotel            January             2            4357   2178.0\n",
       "5     City Hotel               July             2            8232   4116.0\n",
       "6     City Hotel               June             2            7480   3740.0\n",
       "7     City Hotel              March             2            3736   1868.0\n",
       "8     City Hotel                May             2            6458   3229.0\n",
       "9     City Hotel           November             2            7400   3700.0\n",
       "10    City Hotel            October             3            8983   2994.0\n",
       "11    City Hotel          September             3            8088   2696.0\n",
       "12  Resort Hotel              April             2            3103   1552.0\n",
       "13  Resort Hotel             August             2            3045   1522.0\n",
       "14  Resort Hotel           December             2            3555   1778.0\n",
       "15  Resort Hotel           February             2            2648   1324.0\n",
       "16  Resort Hotel            January             2            2437   1218.0\n",
       "17  Resort Hotel               July             2            3559   1780.0\n",
       "18  Resort Hotel               June             2            3609   1804.0\n",
       "19  Resort Hotel              March             2            2193   1096.0\n",
       "20  Resort Hotel                May             2            3336   1668.0\n",
       "21  Resort Hotel           November             2            3108   1554.0\n",
       "22  Resort Hotel            October             3            4894   1631.0\n",
       "23  Resort Hotel          September             3            4573   1524.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly_book['average'] = round(monthly_book['total_bookings']/monthly_book['nunique_year'])\n",
    "monthly_book"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58aa1a1b-5360-4fbe-a13a-e6e4e6b22e24",
   "metadata": {},
   "source": [
    "### Sorted Month Grouping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fef184ce-940e-45c0-ab6e-068098ca6448",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>nunique_year</th>\n",
       "      <th>total_bookings</th>\n",
       "      <th>average</th>\n",
       "      <th>sorted_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>4357</td>\n",
       "      <td>2178.0</td>\n",
       "      <td>Jan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>2437</td>\n",
       "      <td>1218.0</td>\n",
       "      <td>Jan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>4132</td>\n",
       "      <td>2066.0</td>\n",
       "      <td>Feb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>2648</td>\n",
       "      <td>1324.0</td>\n",
       "      <td>Feb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>3736</td>\n",
       "      <td>1868.0</td>\n",
       "      <td>Mar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>2193</td>\n",
       "      <td>1096.0</td>\n",
       "      <td>Mar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>4965</td>\n",
       "      <td>2482.0</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>3103</td>\n",
       "      <td>1552.0</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>3336</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>6458</td>\n",
       "      <td>3229.0</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>7480</td>\n",
       "      <td>3740.0</td>\n",
       "      <td>Jun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>3609</td>\n",
       "      <td>1804.0</td>\n",
       "      <td>Jun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>8232</td>\n",
       "      <td>4116.0</td>\n",
       "      <td>Jul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>3559</td>\n",
       "      <td>1780.0</td>\n",
       "      <td>Jul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>7894</td>\n",
       "      <td>3947.0</td>\n",
       "      <td>Aug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>3045</td>\n",
       "      <td>1522.0</td>\n",
       "      <td>Aug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>8088</td>\n",
       "      <td>2696.0</td>\n",
       "      <td>Sep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>4573</td>\n",
       "      <td>1524.0</td>\n",
       "      <td>Sep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>4894</td>\n",
       "      <td>1631.0</td>\n",
       "      <td>Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>8983</td>\n",
       "      <td>2994.0</td>\n",
       "      <td>Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>7400</td>\n",
       "      <td>3700.0</td>\n",
       "      <td>Nov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>3108</td>\n",
       "      <td>1554.0</td>\n",
       "      <td>Nov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>7605</td>\n",
       "      <td>3802.0</td>\n",
       "      <td>Dec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>3555</td>\n",
       "      <td>1778.0</td>\n",
       "      <td>Dec</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel arrival_date_month  nunique_year  total_bookings  average  \\\n",
       "4     City Hotel            January             2            4357   2178.0   \n",
       "16  Resort Hotel            January             2            2437   1218.0   \n",
       "3     City Hotel           February             2            4132   2066.0   \n",
       "15  Resort Hotel           February             2            2648   1324.0   \n",
       "7     City Hotel              March             2            3736   1868.0   \n",
       "19  Resort Hotel              March             2            2193   1096.0   \n",
       "0     City Hotel              April             2            4965   2482.0   \n",
       "12  Resort Hotel              April             2            3103   1552.0   \n",
       "20  Resort Hotel                May             2            3336   1668.0   \n",
       "8     City Hotel                May             2            6458   3229.0   \n",
       "6     City Hotel               June             2            7480   3740.0   \n",
       "18  Resort Hotel               June             2            3609   1804.0   \n",
       "5     City Hotel               July             2            8232   4116.0   \n",
       "17  Resort Hotel               July             2            3559   1780.0   \n",
       "1     City Hotel             August             2            7894   3947.0   \n",
       "13  Resort Hotel             August             2            3045   1522.0   \n",
       "11    City Hotel          September             3            8088   2696.0   \n",
       "23  Resort Hotel          September             3            4573   1524.0   \n",
       "22  Resort Hotel            October             3            4894   1631.0   \n",
       "10    City Hotel            October             3            8983   2994.0   \n",
       "9     City Hotel           November             2            7400   3700.0   \n",
       "21  Resort Hotel           November             2            3108   1554.0   \n",
       "2     City Hotel           December             2            7605   3802.0   \n",
       "14  Resort Hotel           December             2            3555   1778.0   \n",
       "\n",
       "   sorted_month  \n",
       "4           Jan  \n",
       "16          Jan  \n",
       "3           Feb  \n",
       "15          Feb  \n",
       "7           Mar  \n",
       "19          Mar  \n",
       "0           Apr  \n",
       "12          Apr  \n",
       "20          May  \n",
       "8           May  \n",
       "6           Jun  \n",
       "18          Jun  \n",
       "5           Jul  \n",
       "17          Jul  \n",
       "1           Aug  \n",
       "13          Aug  \n",
       "11          Sep  \n",
       "23          Sep  \n",
       "22          Oct  \n",
       "10          Oct  \n",
       "9           Nov  \n",
       "21          Nov  \n",
       "2           Dec  \n",
       "14          Dec  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "months = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'] # Mengurutkan data berdasarkan bulan\n",
    "monthly_book['sorted_month'] = monthly_book['arrival_date_month'].str[:3] #mengambil 3 huruf terdepan dari \"arrival_date_month\"  \n",
    "monthly_book['sorted_month'] = pd.Categorical(monthly_book['sorted_month'], categories=months)\n",
    "monthly_book.sort_values('sorted_month')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd3f3472-3ae7-46c5-b52b-5462ffb93e4e",
   "metadata": {},
   "source": [
    "### Visualisasi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5fb53367-0303-4411-80cb-fecdf4f6ac54",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "\n",
    "sns.lineplot(data=monthly_book, x='sorted_month', y='average', hue='hotel', marker='o', palette='Set1', ax=ax)\n",
    "\n",
    "sns.barplot(data=monthly_book, x='sorted_month', y='average', hue='hotel', palette='Set1', ax=ax, alpha=0.5)\n",
    "\n",
    "\n",
    "plt.title('Rata-rata Booking per Bulan')\n",
    "plt.xlabel('Bulan')\n",
    "plt.ylabel('Rata-rata Booking')\n",
    "plt.grid(True)\n",
    "plt.legend(title='Hotel')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0db1aa6-662f-49ac-af62-915094ca805c",
   "metadata": {},
   "source": [
    "* Tingkat pemesanan kedua tipe Hotel pada bulan Maret adalah yang paling rendah karena belum memasuki musim liburan.\n",
    "* Berdasarkan gambar plot, peningkatan jumlah pemesanan Hotel mengalami penigkatan pada dua periode yaitu bulan Mei - Juli kemudian bulan Oktober - Desember. Peningkatan tersebut terjadi karena periode waktu tersebut telah memasuki musim liburan, untuk musim liburan pertama dari Mei - Juli yaitu libur musim panas, sedangkan musim liburan kedua adalah natal dan tahun baru."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1602c541-ecd4-42b2-86ee-13efff4a05b0",
   "metadata": {},
   "source": [
    "## Analisa Pengaruh Durasi Menginap terhadap tingkat Pembatalan Pemesanan Hotel\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2ee1522-7819-4e09-bccd-74ef00e5a5fe",
   "metadata": {},
   "source": [
    "### Total Hotel Booking yang Batal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "867ebaef-c992-4bbd-bf6e-5f87957830ff",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>total_canceled</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>33102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>11122</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel  total_canceled\n",
       "0    City Hotel           33102\n",
       "1  Resort Hotel           11122"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canceled_bookings = df[df['is_canceled'] == 1]\n",
    "grouped_hotel_canceled = canceled_bookings.groupby('hotel').size().reset_index()\n",
    "grouped_hotel_canceled.columns= ['hotel','total_canceled']\n",
    "grouped_hotel_canceled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "928b98d8-2969-4a0d-a8e8-2f482d8b2529",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = grouped_hotel_canceled['hotel']\n",
    "sizes = grouped_hotel_canceled['total_canceled']\n",
    "\n",
    "# Create the pie chart\n",
    "plt.figure(figsize=(5, 5))\n",
    "plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Rasio Pembatalan Booking Berdasarkan Tipe Hotel')\n",
    "plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a79ca263-62c1-4479-97f2-b3f9bb472d3d",
   "metadata": {},
   "source": [
    "* Pembatalan hotel dengan jenis City Hotel adalah yang paling banyak terjadi pembatalan pemesanan dibandingkan dengan Resort Hotel. Hal ini mungkin disebabkan karena City Hotel terletak di area perkotaan dimana banyak kegiatan dan aktifitas yang sibuk terjadi, oleh karena itu pelangganpun dapat dipengaruhi oleh faktor kesibukan tersebut.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2332ff2-71b2-43f2-9bda-4193bf250233",
   "metadata": {},
   "source": [
    "### Total Durasi Menginap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "562232fa-4b3e-45cc-9e75-7d58f212e764",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>lead_time</th>\n",
       "      <th>arrival_date_year</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>arrival_date_week_number</th>\n",
       "      <th>arrival_date_day_of_month</th>\n",
       "      <th>stays_in_weekend_nights</th>\n",
       "      <th>stays_in_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</th>\n",
       "      <th>deposit_type</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "      <th>days_in_waiting_list</th>\n",
       "      <th>customer_type</th>\n",
       "      <th>adr</th>\n",
       "      <th>required_car_parking_spaces</th>\n",
       "      <th>total_of_special_requests</th>\n",
       "      <th>reservation_status</th>\n",
       "      <th>total_stay_duration</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>342</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>737</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>304.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n",
       "0  Resort Hotel            0        342               2017          September   \n",
       "1  Resort Hotel            0        737               2017          September   \n",
       "2  Resort Hotel            0          7               2017          September   \n",
       "3  Resort Hotel            0         13               2017          September   \n",
       "4  Resort Hotel            0         14               2017          September   \n",
       "\n",
       "   arrival_date_week_number  arrival_date_day_of_month  \\\n",
       "0                        27                          1   \n",
       "1                        27                          1   \n",
       "2                        27                          1   \n",
       "3                        27                          1   \n",
       "4                        27                          1   \n",
       "\n",
       "   stays_in_weekend_nights  stays_in_weekdays_nights  adults  ...  \\\n",
       "0                        0                         0       2  ...   \n",
       "1                        0                         0       2  ...   \n",
       "2                        0                         1       1  ...   \n",
       "3                        0                         1       1  ...   \n",
       "4                        0                         2       2  ...   \n",
       "\n",
       "   deposit_type  agent company days_in_waiting_list customer_type   adr  \\\n",
       "0    No Deposit    0.0     0.0                    0      Personal   0.0   \n",
       "1    No Deposit    0.0     0.0                    0      Personal   0.0   \n",
       "2    No Deposit    0.0     0.0                    0      Personal  75.0   \n",
       "3    No Deposit  304.0     0.0                    0      Personal  75.0   \n",
       "4    No Deposit  240.0     0.0                    0      Personal  98.0   \n",
       "\n",
       "   required_car_parking_spaces  total_of_special_requests  reservation_status  \\\n",
       "0                            0                          0           Check-Out   \n",
       "1                            0                          0           Check-Out   \n",
       "2                            0                          0           Check-Out   \n",
       "3                            0                          0           Check-Out   \n",
       "4                            0                          1           Check-Out   \n",
       "\n",
       "   total_stay_duration  \n",
       "0                    0  \n",
       "1                    0  \n",
       "2                    1  \n",
       "3                    1  \n",
       "4                    2  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['total_stay_duration'] = df['stays_in_weekdays_nights'] + df['stays_in_weekend_nights']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2b294cda-9982-4e0f-b1d3-021a98bb01f9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max duration = 69\n",
      "min duration = 0\n"
     ]
    }
   ],
   "source": [
    "maxx = df['total_stay_duration'].max()\n",
    "minn = df['total_stay_duration'].min()\n",
    "\n",
    "print('max duration =',maxx)\n",
    "print('min duration =',minn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fa1a005c-5fdb-4887-9141-c97d3305c3c6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 5))\n",
    "plt.hist(df['total_stay_duration'], bins=20, color='skyblue', edgecolor='black', alpha=0.7)\n",
    "plt.xlabel('Total Durasi Menginap')\n",
    "plt.ylabel('Frekuensi')\n",
    "plt.title('Distribusi Total Durasi Menginap')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f634b5e8-e371-49eb-9afe-46fed9680328",
   "metadata": {},
   "source": [
    "### Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c4729aca-4375-49ce-abf8-3549e73adee2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Melakukan labelling group kolom baru dari `total_stay_duration`\n",
    "df['total_weeks_stayed'] = np.where(df['total_stay_duration'] <= 7, '<1 week',\n",
    "                                     np.where(df['total_stay_duration'] <= 14, '1-2 weeks',\n",
    "                                              np.where(df['total_stay_duration'] <= 21, '2-3 weeks',\n",
    "                                                       np.where(df['total_stay_duration'] <= 28, '3-4 weeks', 'more than 4 weeks'))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "020a60a4-8d48-4225-8dc2-725893988b73",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>lead_time</th>\n",
       "      <th>arrival_date_year</th>\n",
       "      <th>arrival_date_month</th>\n",
       "      <th>arrival_date_week_number</th>\n",
       "      <th>arrival_date_day_of_month</th>\n",
       "      <th>stays_in_weekend_nights</th>\n",
       "      <th>stays_in_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "      <th>days_in_waiting_list</th>\n",
       "      <th>customer_type</th>\n",
       "      <th>adr</th>\n",
       "      <th>required_car_parking_spaces</th>\n",
       "      <th>total_of_special_requests</th>\n",
       "      <th>reservation_status</th>\n",
       "      <th>total_stay_duration</th>\n",
       "      <th>total_weeks_stayed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6723</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>August</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>8.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Canceled</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;1 week</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53177</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>245</td>\n",
       "      <td>2018</td>\n",
       "      <td>August</td>\n",
       "      <td>25</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Canceled</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;1 week</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117429</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>2019</td>\n",
       "      <td>September</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>195.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>4</td>\n",
       "      <td>&lt;1 week</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>110.70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Canceled</td>\n",
       "      <td>7</td>\n",
       "      <td>&lt;1 week</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42327</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>82</td>\n",
       "      <td>2017</td>\n",
       "      <td>November</td>\n",
       "      <td>36</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>98.25</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;1 week</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
       "6723    Resort Hotel            1          0               2018   \n",
       "53177     City Hotel            1        245               2018   \n",
       "117429    City Hotel            0         99               2019   \n",
       "107     Resort Hotel            1        102               2017   \n",
       "42327     City Hotel            0         82               2017   \n",
       "\n",
       "       arrival_date_month  arrival_date_week_number  \\\n",
       "6723               August                        27   \n",
       "53177              August                        25   \n",
       "117429          September                        31   \n",
       "107             September                        27   \n",
       "42327            November                        36   \n",
       "\n",
       "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
       "6723                           27                        1   \n",
       "53177                          17                        0   \n",
       "117429                         31                        1   \n",
       "107                             4                        2   \n",
       "42327                           5                        0   \n",
       "\n",
       "        stays_in_weekdays_nights  adults  ...  agent  company  \\\n",
       "6723                           0       2  ...    0.0      0.0   \n",
       "53177                          2       2  ...   12.0      0.0   \n",
       "117429                         3       3  ...    9.0      0.0   \n",
       "107                            5       2  ...  240.0      0.0   \n",
       "42327                          1       2  ...    9.0      0.0   \n",
       "\n",
       "       days_in_waiting_list customer_type     adr required_car_parking_spaces  \\\n",
       "6723                      0      Personal    8.00                           0   \n",
       "53177                     0      Personal   75.00                           0   \n",
       "117429                    0      Personal  195.00                           0   \n",
       "107                       0      Personal  110.70                           0   \n",
       "42327                     0      Personal   98.25                           1   \n",
       "\n",
       "        total_of_special_requests  reservation_status  total_stay_duration  \\\n",
       "6723                            0            Canceled                    1   \n",
       "53177                           0            Canceled                    2   \n",
       "117429                          1           Check-Out                    4   \n",
       "107                             1            Canceled                    7   \n",
       "42327                           2           Check-Out                    1   \n",
       "\n",
       "        total_weeks_stayed  \n",
       "6723               <1 week  \n",
       "53177              <1 week  \n",
       "117429             <1 week  \n",
       "107                <1 week  \n",
       "42327              <1 week  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40f16d78-8887-46c5-8583-db4179de9d79",
   "metadata": {},
   "source": [
    "### Cancelation Rate dari Durasi Menginap "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a7830b29-e93a-46a7-9f06-e146f77c5bdd",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>total_weeks_stayed</th>\n",
       "      <th>total_count</th>\n",
       "      <th>cancelled_count</th>\n",
       "      <th>cancelation_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>1-2 weeks</td>\n",
       "      <td>1086</td>\n",
       "      <td>558</td>\n",
       "      <td>0.513812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>2-3 weeks</td>\n",
       "      <td>108</td>\n",
       "      <td>77</td>\n",
       "      <td>0.712963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>3-4 weeks</td>\n",
       "      <td>28</td>\n",
       "      <td>21</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>&lt;1 week</td>\n",
       "      <td>78082</td>\n",
       "      <td>32426</td>\n",
       "      <td>0.415281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>more than 4 weeks</td>\n",
       "      <td>26</td>\n",
       "      <td>20</td>\n",
       "      <td>0.769231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1-2 weeks</td>\n",
       "      <td>3732</td>\n",
       "      <td>1078</td>\n",
       "      <td>0.288853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>2-3 weeks</td>\n",
       "      <td>169</td>\n",
       "      <td>79</td>\n",
       "      <td>0.467456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>3-4 weeks</td>\n",
       "      <td>83</td>\n",
       "      <td>39</td>\n",
       "      <td>0.469880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>&lt;1 week</td>\n",
       "      <td>36051</td>\n",
       "      <td>9919</td>\n",
       "      <td>0.275138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>more than 4 weeks</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>0.280000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel total_weeks_stayed  total_count  cancelled_count  \\\n",
       "0    City Hotel          1-2 weeks         1086              558   \n",
       "1    City Hotel          2-3 weeks          108               77   \n",
       "2    City Hotel          3-4 weeks           28               21   \n",
       "3    City Hotel            <1 week        78082            32426   \n",
       "4    City Hotel  more than 4 weeks           26               20   \n",
       "5  Resort Hotel          1-2 weeks         3732             1078   \n",
       "6  Resort Hotel          2-3 weeks          169               79   \n",
       "7  Resort Hotel          3-4 weeks           83               39   \n",
       "8  Resort Hotel            <1 week        36051             9919   \n",
       "9  Resort Hotel  more than 4 weeks           25                7   \n",
       "\n",
       "   cancelation_rate  \n",
       "0          0.513812  \n",
       "1          0.712963  \n",
       "2          0.750000  \n",
       "3          0.415281  \n",
       "4          0.769231  \n",
       "5          0.288853  \n",
       "6          0.467456  \n",
       "7          0.469880  \n",
       "8          0.275138  \n",
       "9          0.280000  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cancelled_bookings = df[df['is_canceled'] == 1]\n",
    "grouped_cancelled = cancelled_bookings.groupby(['hotel', 'total_weeks_stayed']).size().reset_index(name='cancelled_count')\n",
    "\n",
    "total_bookings = df.groupby(['hotel', 'total_weeks_stayed']).size().reset_index(name='total_count')\n",
    "\n",
    "# Gabungkan kedua DataFrame di atas\n",
    "merged_df = pd.merge(total_bookings, grouped_cancelled, on=['hotel', 'total_weeks_stayed'], how='left')\n",
    "\n",
    "# Hitung tingkat pembatalan\n",
    "merged_df['cancelation_rate'] = merged_df['cancelled_count'] / merged_df['total_count']\n",
    "\n",
    "# Tampilkan DataFrame hasil\n",
    "merged_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdf650f8-96a5-453a-bdba-6a0f4f31dd93",
   "metadata": {},
   "source": [
    "### Visualisasi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2b47b733-ae94-456c-a66f-9904b8d30adb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "barplot = sns.barplot(data=merged_df, x='total_weeks_stayed', y='cancelation_rate', hue='hotel')\n",
    "\n",
    "# Add percentage labels above each bar\n",
    "for p in barplot.patches:\n",
    "    height = p.get_height()\n",
    "    barplot.text(p.get_x() + p.get_width() / 2, height + 0.01, '{:.2%}'.format(height), ha=\"center\")\n",
    "\n",
    "# Add title and labels\n",
    "plt.title('Tingkat Pembatalan Hotel dari Total Menginap dan Tipe Hotel')\n",
    "plt.xlabel('Total Menginap ')\n",
    "plt.ylabel('Tingkat Pembatalan')\n",
    "plt.legend(title='Tipe Hotel')\n",
    "plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf2d0344-78f7-413f-a83f-96825d903df4",
   "metadata": {},
   "source": [
    "* Berdasarkan hasil visualisasi, persentase tingkat pembatalan pemesanan ketegori City Hotel semakin meningkat seiring dengan lama durasi menginapnya. Sedangkan untuk kategori Resort Hotel tingkat pembatalan pemesanan memiliki persentase yang tinggi pada durasi menginap selama 2-3 minggu dan 3-4 minggu.\n",
    "\n",
    "* Dapat diinterpretasikan bahwa korelasi antara lamanya durasi menginap memiliki pengaruh terhadap tingkat pembatalan pemesanan untuk kategori City Hotel."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db14794c-7a50-4c0f-92cc-48d830930897",
   "metadata": {},
   "source": [
    "## Analisis Pengaruh Lead Time terhadap Tingkat Pembatalan Pemesanan Hotel\n",
    "----"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "43507321-c9f5-4d97-aca8-45f9b76bde0d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "479\n",
      "0\n",
      "737\n"
     ]
    }
   ],
   "source": [
    "nunique = df['lead_time'].nunique()\n",
    "minn = df['lead_time'].min()\n",
    "maxx= df['lead_time'].max()\n",
    "\n",
    "print(nunique)\n",
    "print(minn)\n",
    "print(maxx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "dfd09959-9cdf-4c4b-8498-25408bb7c523",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(df['lead_time'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a88ba149-c3e3-42f0-85eb-2bb862bc7099",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# melaukan grouping label untuk waktu lead time\n",
    "df['lead_time_group'] = np.where((df['lead_time']) <= 30, '1 bulan',\n",
    "                        np.where((df['lead_time']) <= 60, '2 bulan',\n",
    "                        np.where((df['lead_time']) <= 90, '3 bulan', \n",
    "                        np.where((df['lead_time']) <= 120, '4 bulan',\n",
    "                        np.where((df['lead_time']) <= 150, '5 bulan',\n",
    "                        np.where((df['lead_time']) <= 180, '6 bulan',\n",
    "                        np.where((df['lead_time']) <= 210, '7 bulan', \n",
    "                        np.where((df['lead_time']) <= 240, '8 bulan',\n",
    "                        np.where((df['lead_time']) <= 270, '9 bulan',\n",
    "                        np.where((df['lead_time']) <= 300, '10 bulan', \n",
    "                        np.where((df['lead_time']) <= 330, '11 bulan',\n",
    "                        np.where((df['lead_time']) <= 360, '12 bulan', 'lebih dari 1 tahun'))))))))))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c2eccc8d-839d-4e8d-bfe2-902939267dee",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 6))\n",
    "sns.histplot(df['lead_time_group'])\n",
    "plt.xticks(rotation = 45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ec1df05-b7be-4819-848b-525b2938d150",
   "metadata": {},
   "source": [
    "## Tingkat Pembatalan Berdasarkan Lead Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f3c8e309-5e6c-4047-b659-dd192cec62cc",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>lead_time_group</th>\n",
       "      <th>total_count</th>\n",
       "      <th>cancelled_count</th>\n",
       "      <th>cancelation_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>1 bulan</td>\n",
       "      <td>23362</td>\n",
       "      <td>5199</td>\n",
       "      <td>0.222541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>10 bulan</td>\n",
       "      <td>2519</td>\n",
       "      <td>1859</td>\n",
       "      <td>0.737991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>11 bulan</td>\n",
       "      <td>2118</td>\n",
       "      <td>1604</td>\n",
       "      <td>0.757318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>12 bulan</td>\n",
       "      <td>1223</td>\n",
       "      <td>1004</td>\n",
       "      <td>0.820932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>2 bulan</td>\n",
       "      <td>11889</td>\n",
       "      <td>4608</td>\n",
       "      <td>0.387585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>3 bulan</td>\n",
       "      <td>8908</td>\n",
       "      <td>3692</td>\n",
       "      <td>0.414459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>4 bulan</td>\n",
       "      <td>7447</td>\n",
       "      <td>3486</td>\n",
       "      <td>0.468108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>5 bulan</td>\n",
       "      <td>5613</td>\n",
       "      <td>2543</td>\n",
       "      <td>0.453055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>6 bulan</td>\n",
       "      <td>5163</td>\n",
       "      <td>2717</td>\n",
       "      <td>0.526244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>7 bulan</td>\n",
       "      <td>3594</td>\n",
       "      <td>1793</td>\n",
       "      <td>0.498887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>8 bulan</td>\n",
       "      <td>2505</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.510978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>9 bulan</td>\n",
       "      <td>2124</td>\n",
       "      <td>1242</td>\n",
       "      <td>0.584746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>lebih dari 1 tahun</td>\n",
       "      <td>2865</td>\n",
       "      <td>2075</td>\n",
       "      <td>0.724258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1 bulan</td>\n",
       "      <td>15344</td>\n",
       "      <td>1986</td>\n",
       "      <td>0.129432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>10 bulan</td>\n",
       "      <td>906</td>\n",
       "      <td>350</td>\n",
       "      <td>0.386313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>11 bulan</td>\n",
       "      <td>637</td>\n",
       "      <td>315</td>\n",
       "      <td>0.494505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>12 bulan</td>\n",
       "      <td>493</td>\n",
       "      <td>198</td>\n",
       "      <td>0.401623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>2 bulan</td>\n",
       "      <td>5081</td>\n",
       "      <td>1566</td>\n",
       "      <td>0.308207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>3 bulan</td>\n",
       "      <td>3675</td>\n",
       "      <td>1275</td>\n",
       "      <td>0.346939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>4 bulan</td>\n",
       "      <td>2987</td>\n",
       "      <td>1159</td>\n",
       "      <td>0.388015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>5 bulan</td>\n",
       "      <td>2531</td>\n",
       "      <td>1032</td>\n",
       "      <td>0.407744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>6 bulan</td>\n",
       "      <td>2698</td>\n",
       "      <td>884</td>\n",
       "      <td>0.327650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>7 bulan</td>\n",
       "      <td>2066</td>\n",
       "      <td>770</td>\n",
       "      <td>0.372701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>8 bulan</td>\n",
       "      <td>1805</td>\n",
       "      <td>754</td>\n",
       "      <td>0.417729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>9 bulan</td>\n",
       "      <td>1286</td>\n",
       "      <td>619</td>\n",
       "      <td>0.481337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>lebih dari 1 tahun</td>\n",
       "      <td>551</td>\n",
       "      <td>214</td>\n",
       "      <td>0.388385</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel     lead_time_group  total_count  cancelled_count  \\\n",
       "0     City Hotel             1 bulan        23362             5199   \n",
       "1     City Hotel            10 bulan         2519             1859   \n",
       "2     City Hotel            11 bulan         2118             1604   \n",
       "3     City Hotel            12 bulan         1223             1004   \n",
       "4     City Hotel             2 bulan        11889             4608   \n",
       "5     City Hotel             3 bulan         8908             3692   \n",
       "6     City Hotel             4 bulan         7447             3486   \n",
       "7     City Hotel             5 bulan         5613             2543   \n",
       "8     City Hotel             6 bulan         5163             2717   \n",
       "9     City Hotel             7 bulan         3594             1793   \n",
       "10    City Hotel             8 bulan         2505             1280   \n",
       "11    City Hotel             9 bulan         2124             1242   \n",
       "12    City Hotel  lebih dari 1 tahun         2865             2075   \n",
       "13  Resort Hotel             1 bulan        15344             1986   \n",
       "14  Resort Hotel            10 bulan          906              350   \n",
       "15  Resort Hotel            11 bulan          637              315   \n",
       "16  Resort Hotel            12 bulan          493              198   \n",
       "17  Resort Hotel             2 bulan         5081             1566   \n",
       "18  Resort Hotel             3 bulan         3675             1275   \n",
       "19  Resort Hotel             4 bulan         2987             1159   \n",
       "20  Resort Hotel             5 bulan         2531             1032   \n",
       "21  Resort Hotel             6 bulan         2698              884   \n",
       "22  Resort Hotel             7 bulan         2066              770   \n",
       "23  Resort Hotel             8 bulan         1805              754   \n",
       "24  Resort Hotel             9 bulan         1286              619   \n",
       "25  Resort Hotel  lebih dari 1 tahun          551              214   \n",
       "\n",
       "    cancelation_rate  \n",
       "0           0.222541  \n",
       "1           0.737991  \n",
       "2           0.757318  \n",
       "3           0.820932  \n",
       "4           0.387585  \n",
       "5           0.414459  \n",
       "6           0.468108  \n",
       "7           0.453055  \n",
       "8           0.526244  \n",
       "9           0.498887  \n",
       "10          0.510978  \n",
       "11          0.584746  \n",
       "12          0.724258  \n",
       "13          0.129432  \n",
       "14          0.386313  \n",
       "15          0.494505  \n",
       "16          0.401623  \n",
       "17          0.308207  \n",
       "18          0.346939  \n",
       "19          0.388015  \n",
       "20          0.407744  \n",
       "21          0.327650  \n",
       "22          0.372701  \n",
       "23          0.417729  \n",
       "24          0.481337  \n",
       "25          0.388385  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cancelled_bookings = df[df['is_canceled'] == 1]\n",
    "lead_cancelled = cancelled_bookings.groupby(['hotel', 'lead_time_group']).agg(cancelled_count=('arrival_date_year', 'count')).reset_index()\n",
    "\n",
    "total_bookings = df.groupby(['hotel', 'lead_time_group']).agg(total_count=('arrival_date_year', 'count')).reset_index()\n",
    "\n",
    "# Gabungkan kedua DataFrame di atas\n",
    "merged_df1 = pd.merge(total_bookings, lead_cancelled, on=['hotel', 'lead_time_group'], how='left')\n",
    "\n",
    "# Hitung tingkat pembatalan\n",
    "merged_df1['cancelation_rate'] = merged_df1['cancelled_count'] / merged_df1['total_count']\n",
    "\n",
    "# Tampilkan DataFrame hasil\n",
    "merged_df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "06381af4-5c56-4ad7-95f9-e0d221cbe593",
   "metadata": {
    "tags": []
   },
   "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>hotel</th>\n",
       "      <th>lead_time_group</th>\n",
       "      <th>total_count</th>\n",
       "      <th>cancelled_count</th>\n",
       "      <th>cancelation_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>1 bulan</td>\n",
       "      <td>23362</td>\n",
       "      <td>5199</td>\n",
       "      <td>0.222541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1 bulan</td>\n",
       "      <td>15344</td>\n",
       "      <td>1986</td>\n",
       "      <td>0.129432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>2 bulan</td>\n",
       "      <td>11889</td>\n",
       "      <td>4608</td>\n",
       "      <td>0.387585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>2 bulan</td>\n",
       "      <td>5081</td>\n",
       "      <td>1566</td>\n",
       "      <td>0.308207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>3 bulan</td>\n",
       "      <td>8908</td>\n",
       "      <td>3692</td>\n",
       "      <td>0.414459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>3 bulan</td>\n",
       "      <td>3675</td>\n",
       "      <td>1275</td>\n",
       "      <td>0.346939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>4 bulan</td>\n",
       "      <td>2987</td>\n",
       "      <td>1159</td>\n",
       "      <td>0.388015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>4 bulan</td>\n",
       "      <td>7447</td>\n",
       "      <td>3486</td>\n",
       "      <td>0.468108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>5 bulan</td>\n",
       "      <td>2531</td>\n",
       "      <td>1032</td>\n",
       "      <td>0.407744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>5 bulan</td>\n",
       "      <td>5613</td>\n",
       "      <td>2543</td>\n",
       "      <td>0.453055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>6 bulan</td>\n",
       "      <td>2698</td>\n",
       "      <td>884</td>\n",
       "      <td>0.327650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>6 bulan</td>\n",
       "      <td>5163</td>\n",
       "      <td>2717</td>\n",
       "      <td>0.526244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>7 bulan</td>\n",
       "      <td>3594</td>\n",
       "      <td>1793</td>\n",
       "      <td>0.498887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>7 bulan</td>\n",
       "      <td>2066</td>\n",
       "      <td>770</td>\n",
       "      <td>0.372701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>8 bulan</td>\n",
       "      <td>1805</td>\n",
       "      <td>754</td>\n",
       "      <td>0.417729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>8 bulan</td>\n",
       "      <td>2505</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.510978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>9 bulan</td>\n",
       "      <td>1286</td>\n",
       "      <td>619</td>\n",
       "      <td>0.481337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>9 bulan</td>\n",
       "      <td>2124</td>\n",
       "      <td>1242</td>\n",
       "      <td>0.584746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>10 bulan</td>\n",
       "      <td>2519</td>\n",
       "      <td>1859</td>\n",
       "      <td>0.737991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>10 bulan</td>\n",
       "      <td>906</td>\n",
       "      <td>350</td>\n",
       "      <td>0.386313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>11 bulan</td>\n",
       "      <td>637</td>\n",
       "      <td>315</td>\n",
       "      <td>0.494505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>11 bulan</td>\n",
       "      <td>2118</td>\n",
       "      <td>1604</td>\n",
       "      <td>0.757318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>12 bulan</td>\n",
       "      <td>493</td>\n",
       "      <td>198</td>\n",
       "      <td>0.401623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>12 bulan</td>\n",
       "      <td>1223</td>\n",
       "      <td>1004</td>\n",
       "      <td>0.820932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>lebih dari 1 tahun</td>\n",
       "      <td>2865</td>\n",
       "      <td>2075</td>\n",
       "      <td>0.724258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>lebih dari 1 tahun</td>\n",
       "      <td>551</td>\n",
       "      <td>214</td>\n",
       "      <td>0.388385</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel     lead_time_group  total_count  cancelled_count  \\\n",
       "0     City Hotel             1 bulan        23362             5199   \n",
       "13  Resort Hotel             1 bulan        15344             1986   \n",
       "4     City Hotel             2 bulan        11889             4608   \n",
       "17  Resort Hotel             2 bulan         5081             1566   \n",
       "5     City Hotel             3 bulan         8908             3692   \n",
       "18  Resort Hotel             3 bulan         3675             1275   \n",
       "19  Resort Hotel             4 bulan         2987             1159   \n",
       "6     City Hotel             4 bulan         7447             3486   \n",
       "20  Resort Hotel             5 bulan         2531             1032   \n",
       "7     City Hotel             5 bulan         5613             2543   \n",
       "21  Resort Hotel             6 bulan         2698              884   \n",
       "8     City Hotel             6 bulan         5163             2717   \n",
       "9     City Hotel             7 bulan         3594             1793   \n",
       "22  Resort Hotel             7 bulan         2066              770   \n",
       "23  Resort Hotel             8 bulan         1805              754   \n",
       "10    City Hotel             8 bulan         2505             1280   \n",
       "24  Resort Hotel             9 bulan         1286              619   \n",
       "11    City Hotel             9 bulan         2124             1242   \n",
       "1     City Hotel            10 bulan         2519             1859   \n",
       "14  Resort Hotel            10 bulan          906              350   \n",
       "15  Resort Hotel            11 bulan          637              315   \n",
       "2     City Hotel            11 bulan         2118             1604   \n",
       "16  Resort Hotel            12 bulan          493              198   \n",
       "3     City Hotel            12 bulan         1223             1004   \n",
       "12    City Hotel  lebih dari 1 tahun         2865             2075   \n",
       "25  Resort Hotel  lebih dari 1 tahun          551              214   \n",
       "\n",
       "    cancelation_rate  \n",
       "0           0.222541  \n",
       "13          0.129432  \n",
       "4           0.387585  \n",
       "17          0.308207  \n",
       "5           0.414459  \n",
       "18          0.346939  \n",
       "19          0.388015  \n",
       "6           0.468108  \n",
       "20          0.407744  \n",
       "7           0.453055  \n",
       "21          0.327650  \n",
       "8           0.526244  \n",
       "9           0.498887  \n",
       "22          0.372701  \n",
       "23          0.417729  \n",
       "10          0.510978  \n",
       "24          0.481337  \n",
       "11          0.584746  \n",
       "1           0.737991  \n",
       "14          0.386313  \n",
       "15          0.494505  \n",
       "2           0.757318  \n",
       "16          0.401623  \n",
       "3           0.820932  \n",
       "12          0.724258  \n",
       "25          0.388385  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sorting\n",
    "lead_time_order = ['1 bulan', '2 bulan', '3 bulan', '4 bulan', '5 bulan', '6 bulan', \n",
    "                   '7 bulan', '8 bulan', '9 bulan', '10 bulan', '11 bulan', '12 bulan', \n",
    "                   'lebih dari 1 tahun']\n",
    "\n",
    "# Convert 'lead_time_group' to ordered categorical datatype\n",
    "merged_df1['lead_time_group'] = pd.Categorical(merged_df1['lead_time_group'], categories=lead_time_order, ordered=True)\n",
    "\n",
    "# Sort the DataFrame based on 'lead_time_group'\n",
    "merged_df1 = merged_df1.sort_values(by='lead_time_group')\n",
    "\n",
    "# Display the sorted DataFrame\n",
    "merged_df1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18fe03a3-521e-445d-92a8-790a9541c2cf",
   "metadata": {},
   "source": [
    "### Visualisasi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "aaee7ab9-836d-48fe-be0c-eb60575c8629",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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55pMduJGV1Qv/0qVLNXToUI0ePVrbtm3T7bffrp49eyotLU0ScwEAAEBZKK3FE2fOnNGgQYNUp04dVaxYUaGhoVq+fLmx/WoLuCQWTwC4fqo1bqWqjVqqYo3aqlijtiZMmKDKlStrw4YNkqQff/xR/fr1U5cuXdSgQQM9++yzatmypTZv3lxonz/++KM6dOigxx9/XA0aNFCPHj302GOP5bvP+fPn1bdvX82dO1fVq1d32pacnKzw8HB169ZNd9xxh8LDw5WcnCxJmjx5sjp16qS2bduW8NG4siKdYiWvYcOG6amnntKkSZOcTrDfs2dPpyvSAtfDvffe63R7woQJmj17tjZs2KAWLVo4Pdkl6dlnn9U777yjzZs3q3fv3gX2WaNGDafbS5YsUaVKlZwK5P/6179Ur149zZ8/34g1aNDA+P+8T3ZJxpPdYrGU2ZMduJFVa9zK6faECS9f81yQ94Vfyn2OP/bYY9q0aZPRZurUqXr66aeNc9lNnz5dq1at0uzZsxUfH89cUERp48LKeghFVn/sjrIeAgAAuArH4gnvagGSpG61z6p3797atm2bWrRoodjYWH377bdatGiRGjRooNWrV2vgwIGqW7duoe8Ns7KyFBkZKX9/f3300UcKCgrSoUOHnOoijgVcN998syRpwYIFTo/rWDzx5Zdfym6365577lFkZKQsFouxeGLOnDksngBQ4uw5OVqyZIkuXLigiIgISVLHjh31+eefa8CAAapbt64SExOVkpKiGTNmFNpPx44dtWjRIm3atEnt2rXT/v37tXz5cvXr18+p3aBBg9SrVy91795d48ePd9oWFhamlJQUpaWlyW63KyUlRRaLRfv27VNCQoLT2Rmul2KvIE9KStJzzz2XLx4YGKjjx48XewBX+2l6Yf7v//5Pnp6euuWWW4r9mLgx2Wy2Qp/sR44ckd1u17fffquUlBTdeeedRe533rx56tOnj3x9fY3Y559/rjZt2ujhhx+Wv7+/WrVqpblz5xrb8z7ZDx48mO/JfvnkAKDkXOmFvzhzQceOHbVlyxajIO544XecbikrK0tbtmxRjx49nO7Xo0cP/fDDD5KYCwAAAMpCaaya/O9//6vffvtNn376qTp06KDg4GB17NhRLVu2NNrce++9uvvuu9W0aVM1bdo03+O64qpJADe2jJOHtH3Gs9o27WnFxMTok08+UfPmzSVJb731lpo3b66goCBVqFBBd911l2bNmqWOHTsW2l+fPn30+uuvq2PHjvLy8lLjxo3VtWtXjRgxwmizZMkSbd26VfHx8QX2ERoaqokTJyoyMlI9evRQfHy8QkNDFRMTo0mTJmnVqlWyWCxq1aqV1q9fX7IHpBDFXkFesWJF/f777/nie/bsUa1atYrVl+On6bNmzVKHDh30zjvvqGfPntq1a5fq169f6P3Onj2rqKgo3XHHHfr111+Luwu4wezYsUMRERG6dOmSKleunO/J/swzzygoKEienp7y8PDQf/7znys+2fPatGmTdu7cqXnz5jnF9+/fr9mzZ2vYsGEaNWqUNm3apBdffFHe3t6KiopyerJLMp7s3bt3N57scXFx8vLy0owZM9SpU6eSPSiAG8o4eUh7Fr+unGyrYqr4XfNc0KdPH508eVIdO3aU3W5Xdna2nn/+eeOFPz09XTabTQEBAU73CwgIML4wZi4AAAAoWyW1avLzzz9XRESEBg0apM8++0y1atXS448/ruHDhxe44ttms+nDDz90elxXXDUJ4MbmXaOOmkW9LlvmRT0QdEn9+vXTunXr1Lx5c7311lvasGGDPv/8cwUHB2v9+vUaOHCg6tSpo+7duxfYX2JioiZMmKBZs2apffv22rdvn4YMGaI6depozJgxOnTokIYMGaLVq1cXeNFOh5iYGMXExBi3ExIS5Ofnp4iICIWEhCgpKUmHDx9Wnz59lJqaKm9v7xI/NnkVu0Deu3dvjRs3Th988IEkyWQyKS0tTSNGjNDf//73YvV1tZ+mF+a5557T448/LrPZrE8//bS4u4AbTEhIiLZv364zZ87o448/vuYne17z5s2TxWJRu3btnOI5OTlq06aNJk6cKElq1aqVfv75Z82ePVtRUVGSXO/JDtzorvcLv4PJZHK6n91ud4oxFwAAAFx/Jb14Yv/+/frmm2/Ut29fLV++XHv37tWgQYOUnZ2tsWPHGu2utICLxRMArjcPs6cqVs9d1BUfH6WkpCTNmDFD06dP16hRo/TJJ58Yv5IODw/X9u3bNWXKlEI/J48ZM0ZPPvmkUcsNCwvThQsX9Oyzz2r06NHasmWLTpw4odatWxv3sdlsWr9+vf79738rMzMz35eK6enpGjdunNavX6+NGzeqadOmatKkiZo0aSKr1aqUlBSFhZXuaTmLXSCfMmWK7r77bvn7+ysjI0OdO3fW8ePHFRERoQkTJhS5H8dP0/MuwZecf5pekPnz5+uXX37RokWL+Gk6JEkVKlQwzvHWpk2ba36yO1y8eFFLlizRuHHj8m2rU6eO8SbHITQ0VB9//HGBfbnCkx240V3vF/6bbrpJZrM53+nFTpw4kW9VuQNzAQAAwPVR0osncnJy5O/vb5wjvHXr1jp69KgmT57sVCC/0gIuicUTAMqW3W5XZmamrFarrFarPDycz75tNpuVk5NT6P0vXrxY4H3sdrvsdrvuuOMO7djhfN2m/v37q1mzZoX+4mbo0KGKjY1VUFCQkpKSZLVajW3Z2dnX5cLFxS6QV6lSRd9//72++eYbbd26VTk5Ofrb3/5WpNW4eRXlp+mX27t3r0aMGKHvvvtOnp5FG3pmZqYyMzON247Tw2RnZys7O1uS5OHhIQ8PD+Xk5Dj9ETjiNptNdrv9qnGz2SyTyWT0mzcuKV9CC4t7enrKbrc7xU0mk/FHmneMhcXdeZ9ycnKUkZFhPOEdp0bI2z4nJ+eq+/T+++8rMzNTffv2zTf22267TXv27HGK79692zg10OVjHDJkiGJjY1W3bl1t2LBBWVlZys7OloeHh7Kzs2W1WvON8UbPkyR5eki2HMkuyWyS8i7EdcQ9L7tSQvYfXRYnbpJkzhO32yWbvfC4hyn3n0POH4faHZ9PeeOS6+cp5494dnZ2keeCwvJ04cKF3LH9cR+z2SwPDw/Z7XZZrVaZzWb97W9/0+rVq3X//fcb+VizZo1xAeHL81TYXOD4uyhsLiju3155yZMjnmPyksluk0k5yjF5Kre3XIXHs2WSXTkmL6cxmuzZkuyy54tbJZlkNzm/f/CwW2XPF7fLw54tuzxkN5md4lLhc8FfnSMcx9nV8+TYd3ea9wqKm1QO8vRH3J3z5Nin8pAnx5ztmM9cbd4rKO6YC0r6vZHj+LtynvIcGZfPk5QjD7ut1N7DOrhsnjw8Za4eILuk8eP7atOmTZo2bZqmTp1qLJ5wXI+mefPm2rp1q6ZMmaI77rijwHmvTp06xjznOBahoaE6fvy4Ll68qAoVKhhtb775ZuXk5OiWW24xHvftt9/ON+/lXTzx448/qkmTJmrYsKEaNmxoLJ5o3rx5iczlLpsnOX8mzPvcccnnk8msvJfzK433Rnlz4qp5csQPvP63cpEnk92m4LH/K5X3Rp4erpunw999qGoNw1WhSg1ZL13S6NGjlZiYqK+++kqVKlVSp06d9NJLL6lixYoKCgrS+vXrtXDhQk2ePNk4Hk8++aQCAwONRdH33nuvpk6dqvDwcLVr106//PKLxowZo/vuu08mk0k+Pj5q1qxZ7nH/4/2er6+vqlevrmbNmhm1MMf7iNWrVyslJUX//e9/lZOTo3bt2mn37t368ssvdejQIZnNZjVp0sQ47pfnqaQUu0Du0K1bN3Xr1u2aB3C1n6Y72Gw2Pf7443rttdfUtGnTIvcfHx+v1157LV9827ZtxkUXa9WqpcaNGys1NVUnT5402gQFBSkoKEgpKSk6e/asEW/UqJH8/f21c+dOZWRkGPFmzZqpWrVq2rZtm9OTJTw8XBUqVMh3wY82bdooKytLP/30kxEzm81q27atzp49q927dxtxHx8ftWzZUunp6dq/f78Rr1q1qkJDQ3X06FEdPnzYiLvLPs2ePVv33XefWrdurf/973/65JNPtG7dOk2bNk1ZWVnq3Lmzhg4dqmHDhql27dratm2b3n33XU2dOtXYp9dee021atXS22+/7bRPM2fO1O23365q1aopIyPDaZ/uuusuRUdHa+zYsQoPD9euXbs0Z84c47QLefdp06ZN2rFjh959910dPXpUFSpUUHJysmbOnKmLFy/KbDbL29vb6VjeaHkqbJ8ealZJm45maf+ZbPVoVFFVvf98dUg8eEnHL+SodxMfeZn/nBOW/5Khi1a7HmpWyWmfPtp9UZW8TLq7sY8Rs9rs+nhPhgJ8PdQl+M9zX53NzNGKXy6pYTVPtatbwYgfP29TYlqmmt/kJUutP1/E95/OfVG80Z9PV9snSS6bpxUfL1aVBuHal+Wn5lVtio6ONuaC8+fPq3PnzoqNjVVaWlq+ucCRJ8dc8NZbb6latWpq3bq1Zs2apSpVqqhFixby8vLS2LFj1aFDB23btk2SdN9992ncuHEKDw9X9erV9emnn+rAgQPq0KFD7j7kydOmTZv0008/6d1331V6errTXPD777/LbDbLz8/P6e/gr87lrponKff5tOlYltrUrqBG1XPfhqSaH1X1Mz+pxpmf9Kt/Z130qfPnMUjfoCrn9+lI3Z7K8qpqxOv8+rUqZRzTwfoPOr0Zr3fkC3lmX1Rq8KNO+9Tw4FJle1bSocB7jZiH3aqGB5cqw6e2jgXcYcQrWM+q3pEvdK5yI5286VYjXinjmBpIJf6a6zj+rp4n/bHv7jTvFbRPAb4eLp+nnSet2nnS6tZ5cuxTecjT7fW8VbuyWanm3HnL1ea9Or9+rdPVLDpdLdyI21JTS+WzhiMvrpwnh3OnG7l8nvzO75N/+oZSew9bxdvk8nlyfNbYuXO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      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "barplot = sns.barplot(data=merged_df1, x='lead_time_group', y='cancelation_rate', hue='hotel')\n",
    "\n",
    "# Add percentage labels above each bar\n",
    "for p in barplot.patches:\n",
    "    height = p.get_height()\n",
    "    barplot.text(p.get_x() + p.get_width() / 2, height + 0.01, '{:.2%}'.format(height), ha=\"center\")\n",
    "\n",
    "# Add title and labels\n",
    "plt.title('Cancelation Rate by Lead Time and Hotel Type')\n",
    "plt.xlabel('Lead Time')\n",
    "plt.ylabel('Cancelation Rate')\n",
    "plt.legend(title='Hotel Type')\n",
    "plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86ad9ea1-00b0-425d-b90c-1575ea2e47de",
   "metadata": {},
   "source": [
    "* Berdasarkan hasil visualisasi, persentase tingkat pembatalan pemesanan ketegori City Hotel secara umum meningkat seiring dengan lama durasi lead time. Sedangkan untuk kategori Resort Hotel tingkat pembatalan pemesanan memiliki persentase yang tinggi pada durasi lead time selama 9 bulan dan 11 bulan, namun jika dilihat secara keseluruhan grafik Resert Hotel juga dapat dikatakan memiliki persentase tingkat pembatalan yang semakin meningkat.\n",
    "\n",
    "* Dapat diinterpretasikan bahwa korelasi antara lamanya durasi lead time memiliki pengaruh terhadap tingkat pembatalan pemesanan untuk lebih spesifiknya untuk kategori City Hotel."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6736f53a-cf61-4609-8e6f-8929b1deea1f",
   "metadata": {},
   "source": [
    "## Kesimpulan"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c06e1b0e-23d4-47c1-a734-d49ecd860b02",
   "metadata": {},
   "source": [
    "**Business Questions**\n",
    "\n",
    "* Jenis hotel apa yang paling sering dikunjungi oleh pelanggan?<br>\n",
    "\n",
    "Kategori \"City Hotel\" lebih banyak di book oleh pelanggan sebesar 66,4% dibandingkan \"Resort Hotel\".\n",
    "Peningkatan jumlah pemesanan City Hotel mengalami penigkatan pada dua periode yaitu bulan Mei - Juli kemudian bulan Oktober - Desember. Peningkatan tersebut terjadi karena periode waktu tersebut telah memasuki musim liburan.\n",
    "\n",
    "* Apakah durasi menginap mempengaruhi tingkat pembatalan pemesanan hotel?<br>\n",
    "\n",
    "Korelasi antara lamanya durasi menginap dari seluruh rentang waktu 1 minggu sampai lebih dari 4 minggu memiliki pengaruh terhadap tingkat pembatalan pemesanan untuk kategori City Hotel. Namun, untuk kategori Resort Hotel memiliki persentase pembatalan paling tinggi pada durasi menginap 2-4 minggu. \n",
    "\n",
    "* Apakah jarak waktu antara pemesanan hotel dan hari kedatangan tamu (lead time) mempengaruhi tingkat pembatalan pemesanan hotel?<br>\n",
    "\n",
    "Korelasi antara lamanya durasi lead time memiliki pengaruh terhadap tingkat pembatalan pemesanan untuk lebih spesifiknya untuk kategori City Hotel. Sedangkan untuk kategori Resort Hotel tingkat pembatalan pemesanan memiliki persentase yang tinggi pada durasi lead time selama 9 bulan dan 11 bulan, namun jika dilihat secara keseluruhan grafik Resert Hotel juga dapat dikatakan memiliki persentase tingkat pembatalan yang semakin meningkat."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75fce1a3-b447-4937-88a8-6732058b31b0",
   "metadata": {},
   "source": [
    "## Rekomendasi"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01822861-a758-4169-bdb7-7c81a0ca4b53",
   "metadata": {},
   "source": [
    "* Memberikan promosi terhadap City Hotel karena lebih sering dipesan oleh pelanggan, dan promosi dapat difokuskan pada musim liburan dimana jumlah pemesanan tinggi seperti Mei-Juli dan Oktober-Desember.\n",
    "* Pihak Hotel dapat mempertimbangkan strategi untuk mengurangi tingkat lead time karena berpengaruh terhadap tingkat pembatalan pemesanan hotel, seperti memberikan promosi atau insentif bagi pelanggan yang memesan jauh hari."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
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 },
 "nbformat": 4,
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