import pandas as pd
import numpy as np
from nltk.corpus import stopwords
from sklearn.metrics.pairwise import linear_kernel
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfVectorizer
import re
import random
import cufflinks
import cufflinks
from plotly.offline import iplot
"Located on the southern tip of Lake Union, the Hilton Garden Inn Seattle Downtown hotel is perfectly located for business and leisure. \nThe neighborhood is home to numerous major international companies including Amazon, Google and the Bill & Melinda Gates Foundation. A wealth of eclectic restaurants and bars make this area of Seattle one of the most sought out by locals and visitors. Our proximity to Lake Union allows visitors to take in some of the Pacific Northwest's majestic scenery and enjoy outdoor activities like kayaking and sailing. over 2,000 sq. ft. of versatile space and a complimentary business center. State-of-the-art A/V technology and our helpful staff will guarantee your conference, cocktail reception or wedding is a success. Refresh in the sparkling saltwater pool, or energize with the latest equipment in the 24-hour fitness center. Tastefully decorated and flooded with natural light, our guest rooms and suites offer everything you need to relax and stay productive. Unwind in the bar, and enjoy American cuisine for breakfast, lunch and dinner in our restaurant. The 24-hour Pavilion Pantry? stocks a variety of snacks, drinks and sundries."
chart_info1.plot(kind='barh',figsize=(14,10),title='top 20 before remove stopwords')
<AxesSubplot:title={'center':'top 20 before remove stopwords'}, ylabel='desc'>
defget_any1_top_n_words_after_stopwords(corpus,n=None):vec=CountVectorizer(stop_words='english',ngram_range=(1,1)).fit(df['desc'])bag_of_words=vec.transform(df['desc'])sum_words=bag_of_words.sum(axis=0)words_freq=[(word,sum_words[0,idx])for word,idx in vec.vocabulary_.items()]sum_words=sorted(words_freq,key=lambda x: x[1],reverse=True)return sum_words[:n]
common_words=get_any1_top_n_words_after_stopwords(df['desc'],20)
df2=pd.DataFrame(common_words,columns=['desc','count'])
chart_info2=df2.groupby(['desc']).sum().sort_values('count',ascending=False)
chart_info2.plot(kind='barh',figsize=(14,10),title='top 20 before after stopwords')
<AxesSubplot:title={'center':'top 20 before after stopwords'}, ylabel='desc'>
defget_any2_top_n_words_after_stopwords(corpus,n=None):vec=CountVectorizer(stop_words='english',ngram_range=(2,2)).fit(df['desc'])bag_of_words=vec.transform(df['desc'])sum_words=bag_of_words.sum(axis=0)words_freq=[(word,sum_words[0,idx])for word,idx in vec.vocabulary_.items()]sum_words=sorted(words_freq,key=lambda x: x[1],reverse=True)return sum_words[:n]common_words=get_any2_top_n_words_after_stopwords(df['desc'],20)
df2=pd.DataFrame(common_words,columns=['desc','count'])
chart_info2=df2.groupby(['desc']).sum().sort_values('count',ascending=False)
chart_info2.plot(kind='barh',figsize=(14,10),title='top 20 before after stopwords')
<AxesSubplot:title={'center':'top 20 before after stopwords'}, ylabel='desc'>
defget_any3_top_n_words_after_stopwords(corpus,n=None):vec=CountVectorizer(stop_words='english',ngram_range=(3,3)).fit(df['desc'])bag_of_words=vec.transform(df['desc'])sum_words=bag_of_words.sum(axis=0)words_freq=[(word,sum_words[0,idx])for word,idx in vec.vocabulary_.items()]sum_words=sorted(words_freq,key=lambda x: x[1],reverse=True)return sum_words[:n]common_words=get_any3_top_n_words_after_stopwords(df['desc'],20)
df2=pd.DataFrame(common_words,columns=['desc','count'])
chart_info2=df2.groupby(['desc']).sum().sort_values('count',ascending=False)
chart_info2.plot(kind='barh',figsize=(14,10),title='top 20 before after stopwords')
<AxesSubplot:title={'center':'top 20 before after stopwords'}, ylabel='desc'>
"Located on the southern tip of Lake Union, the Hilton Garden Inn Seattle Downtown hotel is perfectly located for business and leisure. \nThe neighborhood is home to numerous major international companies including Amazon, Google and the Bill & Melinda Gates Foundation. A wealth of eclectic restaurants and bars make this area of Seattle one of the most sought out by locals and visitors. Our proximity to Lake Union allows visitors to take in some of the Pacific Northwest's majestic scenery and enjoy outdoor activities like kayaking and sailing. over 2,000 sq. ft. of versatile space and a complimentary business center. State-of-the-art A/V technology and our helpful staff will guarantee your conference, cocktail reception or wedding is a success. Refresh in the sparkling saltwater pool, or energize with the latest equipment in the 24-hour fitness center. Tastefully decorated and flooded with natural light, our guest rooms and suites offer everything you need to relax and stay productive. Unwind in the bar, and enjoy American cuisine for breakfast, lunch and dinner in our restaurant. The 24-hour Pavilion Pantry? stocks a variety of snacks, drinks and sundries."
defclean_txt(text):text.lower()text=sub_replace.sub(' ',text)''.join( word for word in text.split(' ')if word notin stopwords )return text
df['desc_clean']=df['desc'].apply(clean_txt)
df['desc_clean'][0]
' ocated on the southern tip of ake nion the ilton arden nn eattle owntown hotel is perfectly located for business and leisure he neighborhood is home to numerous major international companies including mazon oogle and the ill elinda ates oundation wealth of eclectic restaurants and bars make this area of eattle one of the most sought out by locals and visitors ur proximity to ake nion allows visitors to take in some of the acific orthwest s majestic scenery and enjoy outdoor activities like kayaking and sailing over 2 000 sq ft of versatile space and a complimentary business center tate-of-the-art technology and our helpful staff will guarantee your conference cocktail reception or wedding is a success efresh in the sparkling saltwater pool or energize with the latest equipment in the 24-hour fitness center astefully decorated and flooded with natural light our guest rooms and suites offer everything you need to relax and stay productive nwind in the bar and enjoy merican cuisine for breakfast lunch and dinner in our restaurant he 24-hour avilion antry stocks a variety of snacks drinks and sundries '
相似度计算
df.index
RangeIndex(start=0, stop=152, step=1)
df.head()
name
address
desc
word_count
desc_clean
0
Hilton Garden Seattle Downtown
1821 Boren Avenue, Seattle Washington 98101 USA
Located on the southern tip of Lake Union, the...
184
ocated on the southern tip of ake nion the...
1
Sheraton Grand Seattle
1400 6th Avenue, Seattle, Washington 98101 USA
Located in the city's vibrant core, the Sherat...
152
ocated in the city s vibrant core the herat...
2
Crowne Plaza Seattle Downtown
1113 6th Ave, Seattle, WA 98101
Located in the heart of downtown Seattle, the ...
147
ocated in the heart of downtown eattle the ...
3
Kimpton Hotel Monaco Seattle
1101 4th Ave, Seattle, WA98101
What?s near our hotel downtown Seattle locatio...
151
hat s near our hotel downtown eattle locatio...
4
The Westin Seattle
1900 5th Avenue, Seattle, Washington 98101 USA
Situated amid incredible shopping and iconic a...
151
ituated amid incredible shopping and iconic a...
df.set_index('name',inplace=True)
df.index[:5]
Index(['Hilton Garden Seattle Downtown', 'Sheraton Grand Seattle','Crowne Plaza Seattle Downtown', 'Kimpton Hotel Monaco Seattle ','The Westin Seattle'],dtype='object', name='name')
0 Hilton Garden Seattle Downtown
1 Sheraton Grand Seattle
2 Crowne Plaza Seattle Downtown
3 Kimpton Hotel Monaco Seattle
4 The Westin Seattle
Name: name, dtype: object
defrecommendation(name,cosine_similarity):recommend_hotels=[]idx=indices[indices==name].index[0]score_series=pd.Series(cosine_similarity[idx]).sort_values(ascending=False)top_10_indexes=list(score_series[1:11].index)for i in top_10_indexes:recommend_hotels.append(list(df.index)[i])return recommend_hotels
['Staybridge Suites Seattle Downtown - Lake Union','Silver Cloud Inn - Seattle Lake Union','Residence Inn by Marriott Seattle Downtown/Lake Union','MarQueen Hotel','The Charter Hotel Seattle, Curio Collection by Hilton','Embassy Suites by Hilton Seattle Tacoma International Airport','SpringHill Suites Seattle\xa0Downtown','Courtyard by Marriott Seattle Downtown/Pioneer Square','The Loyal Inn','EVEN Hotel Seattle - South Lake Union']
