cloud.py.py

import requests
from bs4 import BeautifulSoup
import re
from konlpy.tag import Okt
from wordcloud import WordCloud
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.font_manager as fm
import numpy as np
import pandas as pd
from collections import Counter
from wordcloud import STOPWORDS



def filter(s):
    hangul = re.compile('[^ ㄱ-ㅣ가-힣]+')
    
    result = hangul.sub('',s)
    return result

url_page = "https://movie.naver.com/movie/bi/mi/pointWriteFormList.nhn?code=164143&type=after&isActualPointWriteExecute=false&isMileageSubscriptionAlready=false&isMileageSubscriptionReject=false"

page=0
list_text=[]
nnpy = Okt()

while page<10 :
    page+=1
    if page > 1:
        url = "https://movie.naver.com/movie/bi/mi/pointWriteFormList.nhn?code=164143&type=after&isActualPointWriteExecute=false&isMileageSubscriptionAlready=false&isMileageSubscriptionReject=false"
        url_page = url + "&page=" + str(page)
    else: pass
    
    res = requests.get(url_page)
    soup = BeautifulSoup(res.text, "lxml")
    div = soup.find_all(class_="score_reple")

    count = 0
    list=[]
    for i in div:
        span_id = "_filtered_ment_" + str(count)
        list.append(i.p.find(id=span_id))
        count+=1
        
    for j in list :
        text = filter(j.text)
        noun = nnpy.nouns(text)
        list_text += noun

list_keywords = [n for n in list_text if len(n) > 1]

counts = Counter(list_keywords)
tags = counts.most_common(30)
keywords = dict(tags)
stoplist = ['영화','연기','너무','정말','배우','내내','영상','자체']

for word in stoplist :
    if word in keywords.keys():
        keywords.pop(word)


print(keywords)


stopwords = {'영화', '연기','너무','정말','배우','내내','영상','자체'}

wordcloud = WordCloud(font_path='/Library/Fonts/NanumBarunGothic.ttf'
, background_color='white', width=800, height=600)
cloud = wordcloud.generate_from_frequencies(keywords)


plt.figure(figsize=(10, 8))
plt.axis('off')
plt.imshow(cloud)
plt.show()