MiniProject.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ec9efbbe",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'pd' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[1], line 49\u001b[0m\n\u001b[0;32m     47\u001b[0m     df[\u001b[39m'\u001b[39m\u001b[39mprice\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m=\u001b[39m df[\u001b[39m'\u001b[39m\u001b[39mprice\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m.\u001b[39mastype(\u001b[39mfloat\u001b[39m)\n\u001b[0;32m     48\u001b[0m     \u001b[39mreturn\u001b[39;00m df\n\u001b[1;32m---> 49\u001b[0m coc()\n",
      "Cell \u001b[1;32mIn[1], line 2\u001b[0m, in \u001b[0;36mcoc\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcoc\u001b[39m():\n\u001b[1;32m----> 2\u001b[0m     dfc1\u001b[39m=\u001b[39mpd\u001b[39m.\u001b[39mDataFrame()\n\u001b[0;32m      3\u001b[0m     headers \u001b[39m=\u001b[39m {\u001b[39m'\u001b[39m\u001b[39mUser-Agent\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mUser-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36\u001b[39m\u001b[39m'\u001b[39m}\n\u001b[0;32m      4\u001b[0m     req \u001b[39m=\u001b[39m requests\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39mhttps://www.oyorooms.com/hotels-in-kochi/\u001b[39m\u001b[39m\"\u001b[39m, headers\u001b[39m=\u001b[39mheaders)\u001b[39m.\u001b[39mtext\n",
      "\u001b[1;31mNameError\u001b[0m: name 'pd' is not defined"
     ]
    }
   ],
   "source": [
    "def coc():\n",
    "    dfc1=pd.DataFrame()\n",
    "    headers = {'User-Agent': 'User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36'}\n",
    "    req = requests.get(\"https://www.oyorooms.com/hotels-in-kochi/\", headers=headers).text\n",
    "    soup = Soup(req, 'html.parser')\n",
    "    apts = soup.find_all(\"div\", {\"class\": \"oyo-row oyo-row--no-spacing listingHotelDescription\"})\n",
    "    l = []\n",
    "    obj = {}\n",
    "    for a in range(0, len(apts)):\n",
    "        try:\n",
    "            obj[\"pricing\"] = apts[a].find(\"span\", {\"class\": \"listingPrice__finalPrice\"}).text\n",
    "        except: obj[\"pricing\"] = None\n",
    "        try:\n",
    "            obj[\"address\"] = apts[a].find(\"div\", {\"class\": \"d-body-lg listingHotelDescription__hotelAddress\"}).text\n",
    "        except:\n",
    "            obj[\"address\"] = None\n",
    "        l.append(obj)\n",
    "        obj = {}\n",
    "    for i in l:\n",
    "        price = i[\"pricing\"]\n",
    "        address = i[\"address\"]\n",
    "        dfc1 = dfc1.append({\"price\": price,\"address\": address}, ignore_index=True)\n",
    "    dfc2=pd.DataFrame()\n",
    "    for page in range(1,14):\n",
    "        req1 = requests.get(\"https://www.booking.com/searchresults.en-us.html?ss=Cochin&ssne=Cochin&ssne_untouched=Cochin&label=gog235jc-1DCAMobEIGY29jaGluSDNYA2hsiAEBmAExuAEXyAEM2AED6AEB-AECiAIBqAIDuAKryf-hBsACAdICJGNmMmQ1ODhmLTJiYWYtNGQyNS05YzE5LWM2OWQyZjk4OTNmNdgCBOACAQ&sid=98568152db64b2f303d5bb990da98b4c&aid=356980&lang=en-us&sb=1&src_elem=sb&src=searchresults&dest_id=-2093645&dest_type=city&checkin=2023-05-01&checkout=2023-05-02&group_adults=2&no_rooms=1&group_children=0&sb_travel_purpose=leisure/{}_p/\".format(page),headers=headers).text\n",
    "        soup = Soup(req1, 'html.parser')\n",
    "        apts = soup.find_all(\"div\", {\"class\": \"a1b3f50dcd a1f3ecff04 f7c6687c3d f996d8c258\"})\n",
    "        l = []\n",
    "        obj = {}\n",
    "        for a in range(0, len(apts)):\n",
    "            try:\n",
    "                obj[\"pricing\"] = apts[a].find(\"span\", {\"class\": \"fcab3ed991 fbd1d3018c e729ed5ab6\"}).text\n",
    "            except: obj[\"pricing\"] = None\n",
    "            try:\n",
    "                obj[\"address\"] = apts[a].find(\"span\", {\"class\": \"f4bd0794db b4273d69aa\"}).text\n",
    "            except:\n",
    "                obj[\"address\"] = None\n",
    "            l.append(obj)\n",
    "            obj = {}\n",
    "        for i in l:\n",
    "            price = i[\"pricing\"]\n",
    "            address = i[\"address\"]\n",
    "            dfc2 = dfc2.append({\"price\": price,\"address\": address}, ignore_index=True)\n",
    "    df = pd.concat([dfc1, dfc2], ignore_index=True)\n",
    "    df[\"price\"] = df[\"price\"].str.replace(r\"₹\", \"\")\n",
    "    df[\"price\"] = df[\"price\"].str.replace(r\",\", \"\")\n",
    "    df['price'] = df['price'].astype(float)\n",
    "    return df\n",
    "coc()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c10f5c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
      "C:\\Users\\Hashif\\AppData\\Local\\Temp\\ipykernel_26400\\783417779.py:42: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>distance</th>\n",
       "      <th>ratings</th>\n",
       "      <th>wifi</th>\n",
       "      <th>AC</th>\n",
       "      <th>TV</th>\n",
       "      <th>Queen Sized Bed</th>\n",
       "      <th>Geyser</th>\n",
       "      <th>King Sized Bed</th>\n",
       "      <th>Power backup</th>\n",
       "      <th>Mini Fridge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>799</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>699</td>\n",
       "      <td>1.4</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>576</td>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>999</td>\n",
       "      <td>4.6</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>999</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>727</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>599</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1782</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>576</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>599</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    price  distance  ratings  wifi  AC  TV  Queen Sized Bed  Geyser  \\\n",
       "0     799       5.0      4.5     1   1   1                1       0   \n",
       "1     699       1.4      3.5     1   1   1                0       1   \n",
       "2     576       6.5      3.0     1   1   1                0       0   \n",
       "3     999       4.6      2.8     1   1   1                0       1   \n",
       "4     999       3.6      3.7     1   1   1                0       1   \n",
       "..    ...       ...      ...   ...  ..  ..              ...     ...   \n",
       "95    727       3.7      3.5     1   1   1                0       1   \n",
       "96    599       4.6      3.9     1   1   1                0       1   \n",
       "97   1782       2.8      4.1     1   1   1                0       0   \n",
       "98    576       8.5      2.4     1   1   1                0       1   \n",
       "99    599       4.8      3.2     1   1   1                0       1   \n",
       "\n",
       "    King Sized Bed  Power backup  Mini Fridge  \n",
       "0                0             1            0  \n",
       "1                0             1            0  \n",
       "2                0             0            0  \n",
       "3                0             1            0  \n",
       "4                0             1            0  \n",
       "..             ...           ...          ...  \n",
       "95               0             1            0  \n",
       "96               0             1            0  \n",
       "97               0             0            0  \n",
       "98               0             1            0  \n",
       "99               0             1            0  \n",
       "\n",
       "[100 rows x 11 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#added more features\n",
    "import requests \n",
    "from bs4 import BeautifulSoup as Soup\n",
    "import pandas as pd\n",
    "def delhi():\n",
    "    df=pd.DataFrame()\n",
    "    headers = {'User-Agent': 'User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36'}\n",
    "    for page in range (1,6):\n",
    "        req = requests.get(\"https://www.oyorooms.com/hotels-in-delhi/\", headers=headers).text\n",
    "        soup = Soup(req, 'html.parser')\n",
    "        apts = soup.find_all(\"div\", {\"class\": \"oyo-row oyo-row--no-spacing listingHotelDescription\"})\n",
    "        l = []\n",
    "        obj = {}\n",
    "        apts1 = soup.find_all(itemprop='url')\n",
    "        for a in range(0, len(apts)):\n",
    "            try:\n",
    "                obj[\"pricing\"] = apts[a].find(\"span\", {\"class\": \"listingPrice__finalPrice\"}).text\n",
    "            except: obj[\"pricing\"] = None\n",
    "            try:\n",
    "                obj[\"Distance\"] = apts[a].find(\"span\", {\"class\": \"listingHotelDescription__distanceText\"}).text\n",
    "            except:\n",
    "                obj[\"Distance\"] = None\n",
    "            try:\n",
    "                link= apts1[a].get('content')\n",
    "                req1 = requests.get(link, headers=headers).text\n",
    "                soup2 = Soup(req1, 'html.parser')\n",
    "                obj[\"amneties\"] = soup2.find(\"div\", {\"class\": \"c-2cojj\"}).text\n",
    "            except:\n",
    "                obj[\"amneties\"] = None\n",
    "            try:\n",
    "                obj[\"ratings\"] = apts[a].find(\"div\", {\"class\": \"hotelRating\"}).text\n",
    "            except:\n",
    "                obj[\"ratings\"] = None\n",
    "            \n",
    "            l.append(obj)\n",
    "            obj = {}\n",
    "        for i in l:\n",
    "            price = i[\"pricing\"]\n",
    "            distance = i[\"Distance\"]\n",
    "            amneties= i[\"amneties\"]\n",
    "            ratings= i[\"ratings\"]\n",
    "            df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
    "#dataCleaning\n",
    "    df[\"price\"] = df[\"price\"].str.replace(r\"₹\", \"\")\n",
    "    df[\"ratings\"] = df[\"ratings\"].str.replace(r\"₹\", \"\")\n",
    "    df['price'] = pd.to_numeric(df['price'])\n",
    "    df['distance']=df['distance'].str.replace(r\"km\",\"\")\n",
    "    df['distance'] = pd.to_numeric(df['distance'])\n",
    "    df[['ratings', 'last_name','y','x']] = df['ratings'].str.split(' ', expand=True)\n",
    "    df = df.drop(columns=['last_name','y','x'],axis=1)\n",
    "    df['ratings'] = pd.to_numeric(df['ratings'],errors='coerce')\n",
    "    import re\n",
    "    df['wifi'] = df['amneties'].str.extract(r'(Wifi)', expand=False,flags=re.IGNORECASE)\n",
    "    df['AC'] = df['amneties'].str.extract(r'(AC)', expand=False)\n",
    "    df['amneties']=df['amneties'].str.replace(r\"CCTV\",\"\")\n",
    "    df['TV'] = df['amneties'].str.extract(r'(TV)', expand=False)\n",
    "    df['Queen Sized Bed'] = df['amneties'].str.extract(r'(Queen Sized Bed)', expand=False)\n",
    "    df['Geyser'] = df['amneties'].str.extract(r'(Geyser)', expand=False)\n",
    "    df['King Sized Bed'] = df['amneties'].str.extract(r'(King Sized Bed)', expand=False)\n",
    "    df['Power backup'] = df['amneties'].str.extract(r'(Power backup)', expand=False)\n",
    "    df['Mini Fridge'] = df['amneties'].str.extract(r'(Mini Fridge)', expand=False)\n",
    "    df= df.drop(columns=['amneties'],axis= 1)\n",
    "    df['AC'] = df['AC'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['TV'] = df['TV'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['wifi'] = df['wifi'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['Queen Sized Bed'] = df['Queen Sized Bed'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['King Sized Bed'] = df['King Sized Bed'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['Geyser'] = df['Geyser'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['Power backup'] = df['Power backup'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['Mini Fridge'] = df['Mini Fridge'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['Mini Fridge'] = df['Mini Fridge'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    df['ratings'] = df['ratings'].fillna(df['ratings'].mean())\n",
    "    return df\n",
    "df= delhi()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "741dc0dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>distance</th>\n",
       "      <th>amneties</th>\n",
       "      <th>ratings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>799</td>\n",
       "      <td>5.0</td>\n",
       "      <td>ACWiFiQueen Sized BedTVPower backupReception</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>499</td>\n",
       "      <td>3.9</td>\n",
       "      <td>ACTVFree WifiFully Functional KitchenKitchenFr...</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>626</td>\n",
       "      <td>2.0</td>\n",
       "      <td>ACFree WifiTVGeyserPower backupElevator</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>576</td>\n",
       "      <td>6.5</td>\n",
       "      <td>WiFiACTV</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>699</td>\n",
       "      <td>1.4</td>\n",
       "      <td>ACFree WifiTVPower backupGeyserElevator</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>796</td>\n",
       "      <td>4.5</td>\n",
       "      <td>ACFree WifiTVGeyserPower backup</td>\n",
       "      <td>NEW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>876</td>\n",
       "      <td>4.5</td>\n",
       "      <td>ACTVFree WifiKing Sized BedMini FridgeSeating ...</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1499</td>\n",
       "      <td>5.0</td>\n",
       "      <td>ACTVFree WifiGeyserPower backupElevator</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>576</td>\n",
       "      <td>8.5</td>\n",
       "      <td>ACFree WifiTVGeyserPower backup</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>599</td>\n",
       "      <td>4.6</td>\n",
       "      <td>ACFree WifiTVGeyserPower backup</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    price  distance                                           amneties ratings\n",
       "0     799       5.0       ACWiFiQueen Sized BedTVPower backupReception     4.5\n",
       "1     499       3.9  ACTVFree WifiFully Functional KitchenKitchenFr...     3.2\n",
       "2     626       2.0            ACFree WifiTVGeyserPower backupElevator     2.9\n",
       "3     576       6.5                                           WiFiACTV     3.0\n",
       "4     699       1.4            ACFree WifiTVPower backupGeyserElevator     3.5\n",
       "..    ...       ...                                                ...     ...\n",
       "95    796       4.5                    ACFree WifiTVGeyserPower backup     NEW\n",
       "96    876       4.5  ACTVFree WifiKing Sized BedMini FridgeSeating ...     2.8\n",
       "97   1499       5.0            ACTVFree WifiGeyserPower backupElevator     4.0\n",
       "98    576       8.5                    ACFree WifiTVGeyserPower backup     2.4\n",
       "99    599       4.6                    ACFree WifiTVGeyserPower backup     3.9\n",
       "\n",
       "[100 rows x 4 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb550d8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests \n",
    "from bs4 import BeautifulSoup as Soup\n",
    "import pandas as pd\n",
    "def delhi():\n",
    "    df=pd.DataFrame()\n",
    "    headers = {'User-Agent': 'User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36'}\n",
    "    req = requests.get(\"https://www.oyorooms.com/hotels-in-delhi/\", headers=headers).text\n",
    "    soup = Soup(req, 'html.parser')\n",
    "    apts = soup.find_all(\"div\", {\"class\": \"oyo-row oyo-row--no-spacing listingHotelDescription\"})\n",
    "    l = []\n",
    "    obj = {}\n",
    "    apts1 = soup.find_all(itemprop='url')\n",
    "    for a in range(0, len(apts)):\n",
    "        try:\n",
    "            obj[\"pricing\"] = apts[a].find(\"span\", {\"class\": \"listingPrice__finalPrice\"}).text\n",
    "        except: obj[\"pricing\"] = None\n",
    "        try:\n",
    "            obj[\"Distance\"] = apts[a].find(\"span\", {\"class\": \"listingHotelDescription__distanceText\"}).text\n",
    "        except:\n",
    "            obj[\"Distance\"] = None\n",
    "        try:\n",
    "            link= apts1[a].get('content')\n",
    "            req1 = requests.get(link, headers=headers).text\n",
    "            soup2 = Soup(req1, 'html.parser')\n",
    "            obj[\"amneties\"] = soup2.find(\"div\", {\"class\": \"c-2cojj\"}).text\n",
    "        except:\n",
    "            obj[\"amneties\"] = None\n",
    "        try:\n",
    "            obj[\"ratings\"] = apts[a].find(\"div\", {\"class\": \"hotelRating\"}).text\n",
    "        except:\n",
    "            obj[\"ratings\"] = None\n",
    "            \n",
    "        l.append(obj)\n",
    "        obj = {}\n",
    "    for i in l:\n",
    "        price = i[\"pricing\"]\n",
    "        distance = i[\"Distance\"]\n",
    "        amneties= i[\"amneties\"]\n",
    "        ratings= i[\"ratings\"]\n",
    "        df = df.append({\"price\": price,\"distance\": distance,\"amneties\":amneties,\"ratings\":ratings}, ignore_index=True)\n",
    "    df[\"price\"] = df[\"price\"].str.replace(r\"₹\", \"\")\n",
    "    df[\"ratings\"] = df[\"ratings\"].str.replace(r\"₹\", \"\")\n",
    "    df['price'] = pd.to_numeric(df['price'])\n",
    "    df['distance']=df['distance'].str.replace(r\"km\",\"\")\n",
    "    df['distance'] = pd.to_numeric(df['distance'])\n",
    "    df[['ratings', 'last_name','y','x']] = df['ratings'].str.split(' ', expand=True)\n",
    "    df = df.drop(columns=['last_name','y','x'],axis=1)\n",
    "    df['ratings'] = pd.to_numeric(df['ratings'],errors='coerce')\n",
    "    dfg['AC'] = dfg['AC'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['TV'] = dfg['TV'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['wifi'] = dfg['wifi'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['Queen Sized Bed'] = dfg['Queen Sized Bed'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['King Sized Bed'] = dfg['King Sized Bed'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['Geyser'] = dfg['Geyser'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['Power backup'] = dfg['Power backup'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['Mini Fridge'] = dfg['Mini Fridge'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    dfg['Mini Fridge'] = dfg['Mini Fridge'].fillna('').replace({'': 0, '[^0]': 1}, regex=True)\n",
    "    import numpy as np\n",
    "    dfg['ratings'] = df['ratings'].replace({'NEW': np.nan})\n",
    "    df['ratings'] = pd.to_numeric(df['ratings'],errors='coerce')\n",
    "    dfg['ratings'] = dfg['ratings'].fillna(df['ratings'].mean())\n",
    "    dfg\n",
    "\n",
    "    return df\n",
    "dfd= delhi()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37177fc1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>distance</th>\n",
       "      <th>ratings</th>\n",
       "      <th>wifi</th>\n",
       "      <th>AC</th>\n",
       "      <th>TV</th>\n",
       "      <th>Queen Sized Bed</th>\n",
       "      <th>Geyser</th>\n",
       "      <th>King Sized Bed</th>\n",
       "      <th>Power backup</th>\n",
       "      <th>Mini Fridge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>799</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>WiFi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>Queen Sized Bed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Power backup</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>499</td>\n",
       "      <td>3.9</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Wifi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>626</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>Wifi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Geyser</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Power backup</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>576</td>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>WiFi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>699</td>\n",
       "      <td>1.4</td>\n",
       "      <td>3.5</td>\n",
       "      <td>Wifi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Geyser</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Power backup</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>796</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NEW</td>\n",
       "      <td>Wifi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Geyser</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Power backup</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>876</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Wifi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>King Sized Bed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mini Fridge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1499</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Wifi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Geyser</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Power backup</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>576</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>Wifi</td>\n",
       "      <td>AC</td>\n",
       "      <td>TV</td>\n",
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       "      <td>Geyser</td>\n",
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       "      <td>Geyser</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Power backup</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    price  distance ratings  wifi  AC  TV  Queen Sized Bed  Geyser  \\\n",
       "0     799       5.0     4.5  WiFi  AC  TV  Queen Sized Bed     NaN   \n",
       "1     499       3.9     3.2  Wifi  AC  TV              NaN     NaN   \n",
       "2     626       2.0     2.9  Wifi  AC  TV              NaN  Geyser   \n",
       "3     576       6.5     3.0  WiFi  AC  TV              NaN     NaN   \n",
       "4     699       1.4     3.5  Wifi  AC  TV              NaN  Geyser   \n",
       "..    ...       ...     ...   ...  ..  ..              ...     ...   \n",
       "95    796       4.5     NEW  Wifi  AC  TV              NaN  Geyser   \n",
       "96    876       4.5     2.8  Wifi  AC  TV              NaN     NaN   \n",
       "97   1499       5.0     4.0  Wifi  AC  TV              NaN  Geyser   \n",
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       "99    599       4.6     3.9  Wifi  AC  TV              NaN  Geyser   \n",
       "\n",
       "    King Sized Bed  Power backup  Mini Fridge  \n",
       "0              NaN  Power backup          NaN  \n",
       "1              NaN           NaN          NaN  \n",
       "2              NaN  Power backup          NaN  \n",
       "3              NaN           NaN          NaN  \n",
       "4              NaN  Power backup          NaN  \n",
       "..             ...           ...          ...  \n",
       "95             NaN  Power backup          NaN  \n",
       "96  King Sized Bed           NaN  Mini Fridge  \n",
       "97             NaN  Power backup          NaN  \n",
       "98             NaN  Power backup          NaN  \n",
       "99             NaN  Power backup          NaN  \n",
       "\n",
       "[100 rows x 11 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2fc817a6",
   "metadata": {},
   "outputs": [
    {
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       "    price  distance ratings  wifi  AC  TV  Queen Sized Bed  Geyser  \\\n",
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       "\n",
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       "\n",
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    "\n",
    "\n",
    "\n"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d132ebca",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "    price  distance   ratings  wifi  AC  TV  Queen Sized Bed  Geyser  \\\n",
       "0     799       5.0       4.5     1   1   1                1       0   \n",
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       "98    576       8.5       2.4     1   1   1                0       1   \n",
       "99    599       4.6       3.9     1   1   1                0       1   \n",
       "\n",
       "    King Sized Bed  Power backup  Mini Fridge  \n",
       "0                0             1            0  \n",
       "1                0             0            0  \n",
       "2                0             1            0  \n",
       "3                0             0            0  \n",
       "4                0             1            0  \n",
       "..             ...           ...          ...  \n",
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       "96               1             0            1  \n",
       "97               0             1            0  \n",
       "98               0             1            0  \n",
       "99               0             1            0  \n",
       "\n",
       "[100 rows x 11 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e0cb4767",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests \n",
    "from bs4 import BeautifulSoup as Soup\n",
    "import pandas as pd\n",
    "df=pd.DataFrame()\n",
    "headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36'}\n",
    "req = requests.get(\"https://www.makemytrip.com/hotels/hotel-listing/?checkin=04252023&city=CTGOI&checkout=04262023&roomStayQualifier=3e0e&locusId=CTGOI&country=IN&locusType=city&searchText=Goa,%20India&regionNearByExp=3\", headers=headers).status_code\n",
    "req"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e16ab24",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60e44daa",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca58f528",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c6f6b62",
   "metadata": {},
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