webscrapper

# -*- coding: utf-8 -*-
"""Copy of Mini-project-1-Debayan.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1U1rCxhS2iPk_WSM1QyebCkGz1J1xzjaE

Please read this instruction before running this notebook, or else there might be error. These websites were scrapped and visualized on a certain time so the data might get changed in a while making it difficult to read and process:

PLEASE RUN ONLY THE BELOW PORTIONS AS NEEDED

AT FIRST THE SCRAPPING HAPPENS

THEN THE VISUALIZATION

THEN THE USER INTERACTION

**Ignore all the print statements apart from the user interaction part which is at the bottom (2nd last)**

Run one by one

A1 - This only initializes the code
"""

# Commented out IPython magic to ensure Python compatibility.
from bs4 import BeautifulSoup
import requests
import csv
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
# %matplotlib inline


link2= 'https://www.booking.com/searchresults.en-gb.html?label=gen173nr-1FCAEoggI46AdIM1gEaEiIAQGYAQm4AQfIAQzYAQHoAQH4AQuIAgGoAgO4AsXZrJkGwAIB0gIkZmZlZGRjMDItOWU5My00MmJmLWJmZmUtZDZhYWFmMmQxNWE32AIG4AIB&sid=44ac8de6d5475c2eb18761e39631bacd&aid=304142&ss=Paris&ssne=Paris&ssne_untouched=Paris&lang=en-gb&sb=1&src_elem=sb&src=searchresults&dest_id=-1456928&dest_type=city&checkin=2022-12-03&checkout=2022-12-04&group_adults=2&no_rooms=1&group_children=0&sb_travel_purpose=leisure&offset=100'


# Create the pandas DataFrame
df= pd.DataFrame(columns=['Name','Hotels_Address','Distance_from_city_center','Price','Review_Score','Hotel_Rating','Hotel_Summary','Photos'])
#print(df.head())

##

"""A2 -The will scrap the data from booking.com"""

source = requests.get(link2, headers={
    "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",

    }).text
#source = requests.get(link5).text
soup = BeautifulSoup(source, 'lxml')
#print(soup.find("section", attrs={"data-stid":"section-results"}).text)
#print(soup.find_all("div", attrs={"data-testid":"property-card"}))
#print(soup.find("div", attrs={"data-testid":"property-card"}).text)
#print(soup)

for Post in soup.find_all('div', attrs={"data-testid":"property-card"}):
    #print("New Entry")
    print("********")
    #print("")
    try:
      name = Post.h3.text
      name= name.replace('Opens in new window', '')
      #print(name) r
      #print('')
    except:
      name=''
      print(name)
      #print('')
    try:
      #print("inside dist try")
      distance = Post.find('span', attrs={"data-testid":"distance"})
      dist= str(distance)
      dist= dist.replace('<span aria-expanded="false" data-testid="distance">', '')
      dist= dist.replace('miles from centre</span>', '')
      dist= dist.replace('km from centre</span>', '')
      #print(dist) r
      #print('')
    except:
      print("inside dist except")
      distance=''
      print(distance)
      print('')
    try:
      #print("inside price try")
      price_full = Post.find('span', class_='bd73d13072')
      price= str(price_full)
      price= price.replace('<span class="fcab3ed991 bd73d13072">US$', '')
      price= price.replace('</span>', '')
      #print(price) r
      #print('')
    except:
      print("inside price except")
      price=''
      print(price)
      print('')
    try:
      #print("inside review try")
      review_full = Post.find('div', class_='d10a6220b4').text
      #review= str(review_full)
      #review= review.replace('<div aria-label="Scored 8.4 " class="b5cd09854e d10a6220b4">', '')
      #review= review.replace('</div>', '')
      #print(review_full) r
      #print('')
    except:
      print("inside review except")
      review=''
      print(review)
      print('')
    try:
      #print("inside rating try")
      rating_full = Post.find('div', class_='fbb11b26f5')
      rating_str= str(rating_full)
      rating= rating_str.count('class="b6dc9a9e69 adc357e4f1 fe621d6382')
      #review= review.replace('<div aria-label="Scored 8.4 " class="b5cd09854e d10a6220b4">', '')
      #review= review.replace('</div>', '')
      #print(rating) r
      #print('')
    except:
      print("inside rating except")
      rating=''
      print(rating)
      print('')
    #try:
    #print("inside hotel_link try ")
    hotel_link_full= Post.find('a', attrs={"data-testid":"title-link"})
    hotel_link_str= str(hotel_link_full)
    hotel_link= hotel_link_str.replace('<a class="e13098a59f" data-testid="title-link" href="', '')
    hotel_link= hotel_link.replace('" rel="noopener noreferrer" target="_blank"><div class="fcab3ed991 a23c043802" data-testid="title">', '')
    hotel_link= hotel_link.replace(name, '')
    hotel_link= hotel_link.replace('</div><div class="e6e585da68">Opens in new window</div></a>', '')
    #print(hotel_link)
    source_hotel = requests.get(hotel_link, headers={"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",}).text
    soup_hotel = BeautifulSoup(source_hotel, 'lxml')
    #print("")
    #print(soup_hotel)
    address_full=soup_hotel.find('p', class_='address address_clean').text
    address_str=str(address_full)
    address = address_str.replace("\n", "")
    address = address.split("–")[0]
    address.strip()
    #rem= address.split(", ")[-1]
    #address = address.replace(rem, "")
    #print(address) r
    description_full= soup_hotel.find('div', attrs={"id":"property_description_content"}).text
    description_cut = "You're eligible for a Genius discount at "  +name + "! To save at this property, all you have to do is sign in."
    description_full= description_full.replace(description_cut,"")
    description_full = description_full.replace("\n","")
    #print(description_full) r
    image_link_full = soup_hotel.find_all('div', class_='bh-photo-grid-thumb-cell')
    #image_link= image_link_full.find(attrs={"id":"property_description_content"})
    #image_link=[]
    #image_link =image_link.append(image_link_full.find_all('img')['src'])
    image_list =[]
    for parts in image_link_full:
      image= parts.a["style"]
      image= image.replace("background-image: url(","")
      image= image.replace(");","")
      
      #print(image)
      image_list.append(image)
      #print(image_list)
      #print("")



    
      #print('')

    #except:
      #print("inside hotel_link except")
      #address=''
      #print(address)
      #description=''
      #print(description)
      #print('')
    #print(image_list) real
    new_row = {'Name':name, 'Hotels_Address':address, 'Distance_from_city_center':dist, 'Price':price,'Review_Score':review_full,'Hotel_Rating':rating,'Hotel_Summary':description_full,'Photos':image_list}
    df = df.append(new_row, ignore_index=True)
    #print(new_row)
    #image_list.clear()
    #print('')
#df.to_csv('file_name2.csv')
#df.isnull().sum()
#df['Distance_from_city_center'] = pd.to_numeric(df['Distance_from_city_center'])
#df['Price'] = pd.to_numeric(df['Price'])
#df['Review_Score'] = pd.to_numeric(df['Review_Score'])
#df['Hotel_Rating'] = pd.to_numeric(df['Hotel_Rating'])

"""A3 this will scrap edreams.com"""

dream_link= 'https://hotels.edreams.com/searchresults.html?aid=350435&checkin=2022-12-03&checkout=2022-12-04&fp_referrer_aid=1171464&group_adults=2&group_children=0&label=edr-link-com-seosearchbox-conf-pc-of&lang=en-gb&no_rooms=1&selected_currency=EUR&si=ai%2Cco%2Cci%2Cre%2Cdi&sp_plprd=UmFuZG9tSVYkc2RlIyh9YVXcKaaJl1ClqALJLPfcxMrW3cUtpQCJICXxCeUszNb7HtaQDpi3MeNBJjBUql2B1yFndp5hdoYRzhIkih17O_TCCala4AsWUIQxULxzWpQy6JBoMk09AhHlSAAttaCvYw&ss=Paris&submit=Search+hotels&utm_campaign=sb4&utm_medium=sp&utm_source=AW_Searchbox'

dream_source = requests.get(dream_link, headers={
    "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",

    }).text

dream_soup= BeautifulSoup(dream_source, 'lxml')

#print(dream_soup)

for Post in dream_soup.find_all('div', attrs={"data-testid":"property-card"}):
    print("New Entry")
    print("********")
    print("")
    try:
      name = Post.h3.text
      name= name.replace('Opens in new window', '')
      print(name) 
      #print('')
    except:
      name=''
      print(name)
      print('')
    try:
      #print("inside dist try")
      distance = Post.find('span', attrs={"data-testid":"distance"})
      dist= str(distance)
      dist= dist.replace('<span aria-expanded="false" data-testid="distance">', '')
      dist= dist.replace('miles from centre</span>', '')
      dist= dist.replace('km from centre</span>', '')
      print(dist) 
      #print('')
    except:
      print("inside dist except")
      distance=''
      print(distance)
      print('')
    try:
      #print("inside price try")
      price_full = Post.find('span', class_='bd73d13072')
      price= str(price_full)
      price= price.replace('<span class="fcab3ed991 bd73d13072">US$', '')
      price= price.replace('</span>', '')
      print(price) 
      #print('')
    except:
      print("inside price except")
      price=''
      print(price)
      print('')
    try:
      #print("inside review try")
      review_full = Post.find('div', class_='d10a6220b4').text
      #review= str(review_full)
      #review= review.replace('<div aria-label="Scored 8.4 " class="b5cd09854e d10a6220b4">', '')
      #review= review.replace('</div>', '')
      print(review_full) 
      #print('')
    except:
      print("inside review except")
      review=''
      print(review)
      print('')
    try:
      #print("inside rating try")
      rating_full = Post.find('div', class_='fbb11b26f5')
      rating_str= str(rating_full)
      rating= rating_str.count('class="b6dc9a9e69 adc357e4f1 fe621d6382')
      #review= review.replace('<div aria-label="Scored 8.4 " class="b5cd09854e d10a6220b4">', '')
      review= review.replace('</div>', '')
      #print(rating) 
      #print('')
    except:
      print("inside rating except")
      rating=''
      #print(rating)
      #print('')

    hotel_link_full= Post.find('a', attrs={"data-testid":"title-link"})
    hotel_link_str= str(hotel_link_full)
    hotel_link= hotel_link_str.replace('<a class="e13098a59f" data-testid="title-link" href="', '')
    hotel_link= hotel_link.replace('" rel="noopener noreferrer" target="_blank"><div class="fcab3ed991 a23c043802" data-testid="title">', '')
    hotel_link= hotel_link.replace(name, '')
    hotel_link= hotel_link.replace('</div><div class="e6e585da68">Opens in new window</div></a>', '')
    #print(hotel_link)
    source_hotel = requests.get(hotel_link, headers={"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",}).text
    dream_soup_hotel = BeautifulSoup(source_hotel, 'lxml')
    #print(soup_hotel)
    address_full=dream_soup_hotel.find('p', class_='address address_clean').text
    address_str=str(address_full)
    address = address_str.replace("\n", "")
    address = address.split("–")[0]
    address.strip()
    #rem= address.split(", ")[-1]
    #address = address.replace(rem, "")
    print(address)
    description_full= dream_soup_hotel.find('div', attrs={"id":"property_description_content"}).text
    description_cut = "You're eligible for a Genius discount at "  +name + "! To save at this property, all you have to do is sign in."
    description_full= description_full.replace(description_cut,"")
    description_full = description_full.replace("\n","")
    print(description_full)
    image_link_full = dream_soup_hotel.find_all('div', class_='bh-photo-grid-thumb-cell')
    #image_link= image_link_full.find(attrs={"id":"property_description_content"})
    #image_link=[]
    #image_link =image_link.append(image_link_full.find_all('img')['src'])
    image_list =[]
    for parts in image_link_full:
      image= parts.a["style"]
      image= image.replace("background-image: url(","")
      image= image.replace(");","")
      
      print(image)
      image_list.append(image)
      #print(image_list)
      #print("") 
    
    new_row = {'Name':name, 'Hotels_Address':address, 'Distance_from_city_center':dist, 'Price':price,'Review_Score':review_full,'Hotel_Rating':rating,'Hotel_Summary':description_full,'Photos':image_list}
    df = df.append(new_row, ignore_index=True)
#df.to_csv('file_name3.csv')

"""A4 this will scrap the letsbookhotel.com and will fill the dataframe completely and also create a csv with all the result"""

#lets_link= 'https://www.letsbookhotel.com/en/france/paris/hotels-accommodation.aspx?page='

for i in range(1, 18):
  lets_link= 'https://www.letsbookhotel.com/en/france/paris/hotels-accommodation.aspx?page=' + str(i)
  lets_source = requests.get(lets_link, headers={
      "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",

      }).text

  lets_soup= BeautifulSoup(lets_source, 'lxml')

  #print(lets_soup)

  for Post in lets_soup.find_all('li', class_="hotelitem"):
      #print(Post)
      print("New Entry")
      print("********")
      print("")
      try:
        #print("inside try")
        name = Post.find('a',class_="clickable").text
        print(name) 
        #print('')
      except:
        print("inside except")
        name=''
        #print(name)
        #print('')
      try:
        #print("inside try")
        dist_full = Post.find('div',class_="hoteltitle").text
        dist_full= str(dist_full)
        dist_full = dist_full.replace("\n","")
        dist_full = dist_full.replace("Km > Paris","")
        dist_full = dist_full.replace(name,"")


        print(dist_full) 
        #print('')
      except:
        print("inside except")
        dist_full=''
        #print(name)
        #print('')
      try:
        #print("inside try")
        #rating_full = Post.find('div',class_="hoteltitle")[img]
        rating_full= Post.find('img')['alt']
        rating_full= str(rating_full)
        rating_full = rating_full.replace("stars","")
        #rating_full = rating_full.remove("starsm.gif","")
        #rating_full = str(rating_full)
        #rating_full = rating_full.split('"')[3]



        print(rating_full) 
        #print('')
      except:
        print("inside except")
        rating_full=''
        #print(name)
        #print('')
      try:
        address_full= Post.find('span', class_="text icon-text icon-distance").text
        address_full = str(address_full)
        address_full= address_full.replace("map","")
        print(address_full)
      except:
        address_full=""
      
      try:
        info_full= Post.find('div', class_="info").text
        info_full= info_full.strip()
        info_full= info_full.replace("  ","")
        info_full= info_full.replace("/n","")
        print(info_full)
      except:
        info_full=''

      try:
        price_full = Post.find('div', class_="price").text
        price_full = str(price_full)
        price_full= price_full.strip()
        price_full=price_full.replace("/n","")
        price_full=price_full.replace("from US$ ","")
        print(price_full)
      except:
        price_full=""

      try:
        rev_sco_full = Post.find('div', class_="reviews").text
        rev_sco_full= str(rev_sco_full)
        rev_sco_full.strip()
        rev_sco_full=rev_sco_full.replace(" ","")
        rev_sco_full=rev_sco_full.split(".")[0]
        num = ""
        for c in rev_sco_full:
          if c.isdigit():
            num = num + c

        print(num)

      except:
        rev_sco_full =''
      try:
        print("inside soup try")
        hotel_link_lets = Post.find('a')['href']
        hotel_link_lets = str(hotel_link_lets)
        hotel_link_lets = "https://www.letsbookhotel.com" + hotel_link_lets
        #print(hotel_link_lets)
        source_hotel_lets = requests.get(hotel_link_lets, headers={"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36",}).text
        soup_hotel_lets = BeautifulSoup(source_hotel_lets, 'lxml')
        #print(soup_hotel_lets)
        #images_li = soup_hotel_lets.find('div',class_="hotelreview").text
        imagess=soup_hotel_lets.find("img", id="contentdisplaypic")["src"]
        imagess=str(imagess)
        imagess= "https://www.letsbookhotel.com" +imagess

        print(imagess)
        #for ele in soup_hotel_lets.find_all('div', class_="fotorama__nav fotorama__nav--thumbs fotorama__shadows--right"):
          #img=ele.find('img')['src']
          #print(ele)
        #print(images_li)
        #print(soup_hotel_lets)
      except:
        images=''
      new_row = {'Name':name, 'Hotels_Address':address_full, 'Distance_from_city_center':dist_full, 'Price':price_full,'Review_Score':num,'Hotel_Rating':rating_full,'Hotel_Summary':info_full,'Photos':imagess}
      df = df.append(new_row, ignore_index=True)
df.to_csv('file_name_with_all_scraped.csv')






    




#print("out")

#df.isnull().sum()
try:
  df['Distance_from_city_center'] = pd.to_numeric(df['Distance_from_city_center'])
  df['Price'] = pd.to_numeric(df['Price'])
  df['Review_Score'] = pd.to_numeric(df['Review_Score'])
  df['Hotel_Rating'] = pd.to_numeric(df['Hotel_Rating'])
except:
  print("inside df type conversion except")

df_latest

# Let's calculate the percentage of each hotel star category.
df.Hotel_Rating.value_counts(normalize=True)

#plot the bar graph of percentage hotel star categories
df.Hotel_Rating.value_counts(normalize=True).plot.barh()
plt.show()

#plot the pie chart of Hotel Ratings
df.Hotel_Rating.value_counts(normalize=True).plot.pie()
plt.show()

df.Price.describe()

df.Distance_from_city_center.describe()

#plot the scatter plot of price and review_score v

df.plot.scatter(x="Price",y="Review_Score")
plt.show()

#plot the scatter plot of Hotel_rating and review_score variable in data
df.plot.scatter(x="Hotel_Rating",y="Review_Score")
plt.show()

#plot the scatter plot of price and hotel_rating variable in data
df.plot.scatter(x="Price",y="Hotel_Rating")
plt.show()

#plot the scatter plot of price and distance from city center 
df.plot.scatter(x="Price",y="Distance_from_city_center")
plt.show()

#plot the scatter plot of hotel rating and distance from city center 
df.plot.scatter(x="Hotel_Rating",y="Distance_from_city_center")
plt.show()



#plot the pair plot of price, rating and distance from city center
sns.pairplot(data = df, vars=['Price','Hotel_Rating','Distance_from_city_center'])
plt.show()

# Creating a matrix using price, Review_score, distance from center as rows and columns
df[['Price', 'Review_Score', 'Distance_from_city_center']].corr()

#plot the correlation matrix 
sns.heatmap(df[['Price', 'Review_Score', 'Distance_from_city_center']].corr(), annot=True, cmap = 'Reds')
plt.show()

"""User Interaction , this will also make a result csv with the final result"""

#user_output= pd.read_csv("Booking.csv")

#Userinput

#according to price
print('Please choose price range for hotel that you want from below')
print('1 : 100 Euros or below')
print('2 : 100 Euros - 200 Euros')
print('3 : 200 Euros - 300 Euros')
print('4 : 300 Euros - 400 Euros ')
print('5 : 400 Euros - 500 Euros')

duchoise_price = input('Your Choice =')

if duchoise_price == '1':
  dch_price1 = 0
  dch_price2 = 100
  print(dch_price1, dch_price2)

elif duchoise_price == '2':
  dch_price1 = 100
  dch_price2 = 200
  print(dch_price1, dch_price2)

elif duchoise_price == '3':
  dch_price1 = 200
  dch_price2 = 300
  print(dch_price1, dch_price2)

elif duchoise_price == '4':
  dch_price1 = 300
  dch_price2 = 400
  print(dch_price1, dch_price2)

elif duchoise_price == '5':
  dch_price1 = 400
  dch_price2 = 500
  print(dch_price1, dch_price2)

else:
  print('You selected a wrong option')

print('Please choose distance range for hotel from below')
print('1 : 1 miles')
print('2 : 1 miles - 2 miles ')
print('3 : 2 miles - 3 miles ')
print('4 : 3 miles - 4 miles ')
print('5 : 4 miles - 5 miles ')

duchoise_dist = input('Your Choice =')

if duchoise_dist == '1':
  dch_dist1 = 0
  dch_dist2 = 1
  print(dch_dist1,',', dch_dist2)

elif duchoise_dist == '2':
  dch_dist1 = 1
  dch_dist2 = 2
  print(dch_dist1,',', dch_dist2)

elif duchoise_dist == '3':
  dch_dist1 = 2
  dch_dist2 = 3
  print(dch_dist1,',', dch_dist2)

elif duchoise_dist == '4':
  dch_dist1 = 3
  dch_dist2 = 4
  print(dch_dist1,',', dch_dist2)

elif duchoise_dist == '5':
  dch_dist1 = 4
  dch_dist2 = 5
  print(dch_dist1,',', dch_dist2)

else:
  print('You selected a wrong option')


#according to hotel review score
print('Please choose review range for hotel from below')
print('1 : 8  or below')
print('2 : 8 - 8.5')
print('3 : 8.5 - 9')
print('4 : 9 - 9.5')
print('5 : 9.5 - 10')

duchoise_review = input('Your Choice =')

if duchoise_review == '1':
  dch_review1 = 0
  dch_review2 = 8
  print(dch_review1,',', dch_review2)

elif duchoise_review == '2':
  dch_review1 = 8
  dch_review2 = 8.5
  print(dch_review1,',', dch_review2)

elif duchoise_review == '3':
  dch_review1 = 8.5
  dch_review2 = 9
  print(dch_review1,',', dch_review2)

elif duchoise_review == '4':
  dch_review1 = 9
  dch_review2 = 9.5
  print(dch_review1,',', dch_review2)

elif duchoise_review == '5':
  dch_review1 = 9.5
  dch_review2 = 10
  print(dch_review1,',', dch_review2)

else:
  print('You selected a wrong option')

#accoring to rating
print('Please choose a rating for hotel from below')
print('1 : 1')
print('2 : 2')
print('3 : 3')
print('4 : 4 ')
print('5 : 5')

duchoise_rating = input('Your Choice =')

if duchoise_rating == '1':
  dch_rating =1
  print(dch_rating)

elif duchoise_rating == '2':
  dch_rating =2
  print(dch_rating)

elif duchoise_rating == '3':
  dch_rating =3
  print(dch_rating)

elif duchoise_rating == '4':
  dch_rating =4
  print(dch_rating)

elif duchoise_rating == '5':
  dch_rating =5
  print(dch_rating)

else:
  print('You selected a wrong option')

#sorting with cols
print('Choose criteria by which you want to sort the data')
print('1 : Distance from the city center')
print('2 : Price')
print('3 : Hotel Rating')
print('4 : Review Score ')

duchoise_col = input('Your Choice =')

if duchoise_col == '1':
  dcol_input ='Distance_from_city_center'
  print(dcol_input)

elif duchoise_col == '2':
  dcol_input ='Price'
  print(dcol_input)

elif duchoise_col == '3':
  dcol_input ='Review_Score'
  print(dcol_input)

elif duchoise_col == '4':
  dcol_input ='Hotel_Rating'
  print(dcol_input)

else:
  print('You selected wrong option')

print('                                                       ********* List of Hotels Names *********')
#df_list=pd.DataFrame(columns=['Name'])
df_new2= pd.DataFrame(columns=['Name','Hotels_Address','Distance_from_city_center','Price','Review_Score','Hotel_Rating','Hotel_Summary','Photos'])
df_new2 = df.loc[(df['Distance_from_city_center']> dch_dist1) & (df['Distance_from_city_center']<=dch_dist2) & (df['Price'] >dch_price1) & (df['Price'] <=dch_price2) & (df['Review_Score']>dch_review1) & (df['Review_Score']<=dch_review2) & (df['Hotel_Rating'] == dch_rating)]
df.sort_values(by=[dcol_input])
#df_new2 = df.loc[(df['Distance_from_city_center']> 0) & (df['Distance_from_city_center']<=8) & (df['Price'] >0) & (df['Price'] <=1000) & (df['Review_Score']>0) & (df['Review_Score']<=100)]

print(df_new2['Name'])
#hotel_name= input('Choose Name of hotel')
print("")
print("")
print("")
print("")
print("")

print('Choose the name of the hotel from the list')
print('Type it exactly as it is')
name_input = input('Your Choice =')
print("")
print("")
print("")
print("")

print('                                                       ********* Details of Hotels *********')


print("")
print("")
print("")


#df_latest=df_new2.where(df_new2['Name'] == name_input)
df_latest= df_new2.loc[(df_new2['Name'] == name_input)]
print(df_latest)
df_latest.to_csv('final_result.csv')

df_latest