30.EDA-7

SOWA·2023년 4월 5일
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🖇️ 영화평점 사이트 분석

from bs4 import BeautifulSoup
import pandas as pd
from urllib.request import urlopen
url = 'https://www.imdb.com/chart/moviemeter/?ref_=nv_mv_mpm'
page = urlopen(url)

soup = BeautifulSoup(page, 'html.parser')
soup

⇊

Output exceeds the size limit. Open the full output data in a text editor

<!DOCTYPE html>

<html xmlns:fb="http://www.facebook.com/2008/fbml" xmlns:og="http://ogp.me/ns#">
<head>
<meta charset="utf-8"/>
<style>
                body#styleguide-v2 {
                    background: no-repeat fixed center top #000;
                }
            </style>
<script type="text/javascript">var IMDbTimer={starttime: new Date().getTime(),pt:'java'};</script>
<script>
    if (typeof uet == 'function') {
      uet("bb", "LoadTitle", {wb: 1});
    }
</script>
<script>(function(t){ (t.events = t.events || {})["csm_head_pre_title"] = new Date().getTime(); })(IMDbTimer);</script>
<title>Most Popular Movies - IMDb</title>
<script>(function(t){ (t.events = t.events || {})["csm_head_post_title"] = new Date().getTime(); })(IMDbTimer);</script>
<script>
    if (typeof uet == 'function') {
      uet("be", "LoadTitle", {wb: 1});
    }
</script>
...
      uet("be");
    }
</script>
</body>
</html>
  • 사이트 정보 가져오기


soup.find_all('td', 'titleColumn')

⇊

Output exceeds the size limit. Open the full output data in a text editor
[<td class="titleColumn">
 <a href="/title/tt10366206/" title="Chad Stahelski (dir.), Keanu Reeves, Laurence Fishburne">John Wick: Chapter 4</a>
 <span class="secondaryInfo">(2023)</span>
 <div class="velocity">1
 (no change)
 </div>
 </td>,
 <td class="titleColumn">
 <a href="/title/tt2906216/" title="John Francis Daley (dir.), Chris Pine, Michelle Rodriguez">Dungeons &amp; Dragons: Honor Among Thieves</a>
 <span class="secondaryInfo">(2023)</span>
 <div class="velocity">2
 <span class="secondaryInfo">(
 <span class="global-sprite titlemeter up"></span>
 6)</span>
 </div>
 </td>,
 <td class="titleColumn">
 <a href="/title/tt14230388/" title="Wes Anderson (dir.), Jason Schwartzman, Scarlett Johansson">Asteroid City</a>
 <span class="secondaryInfo">(2023)</span>
 <div class="velocity">3
 <span class="secondaryInfo">(
 <span class="global-sprite titlemeter up"></span>
 506)</span>
 </div>
 </td>,
...
 <span class="secondaryInfo">(
 <span class="global-sprite titlemeter up"></span>
 183)</span>
 </div>
 </td>]

  • 영화 제목 찾기 (td 태그 안 titleColumn)



 soup.find_all('td', 'titleColumn')[0].a

⇊

 <a href="/title/tt10366206/" title="Chad Stahelski (dir.), Keanu Reeves, Laurence Fishburne">John Wick: Chapter 4</a>

soup.find_all('td', 'titleColumn')[0].a.string

⇊

'John Wick: Chapter 4'

  • a 태그 string으로 영화 제목만 가져오기



soup.find_all('td', 'ratingColumn imdbRating')

⇊

Output exceeds the size limit. Open the full output data in a text editor
[<td class="ratingColumn imdbRating">
 <strong title="8.3 based on 87,940 user ratings">8.3</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 <strong title="7.6 based on 22,737 user ratings">7.6</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 </td>,
 <td class="ratingColumn imdbRating">
 <strong title="7.7 based on 338,971 user ratings">7.7</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 <strong title="7.9 based on 415,270 user ratings">7.9</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 <strong title="7.4 based on 668,852 user ratings">7.4</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 <strong title="6.8 based on 55,169 user ratings">6.8</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 <strong title="6.5 based on 27,759 user ratings">6.5</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 <strong title="5.7 based on 18,331 user ratings">5.7</strong>
...
 <td class="ratingColumn imdbRating">
 <strong title="9.0 based on 2,695,932 user ratings">9.0</strong>
 </td>,
 <td class="ratingColumn imdbRating">
 </td>]

soup.find_all('td','ratingColumn imdbRating')[0].strong

⇊

<strong title="8.3 based on 87,940 user ratings">8.3</strong>

soup.find_all('td','ratingColumn imdbRating')[0].strong.string

⇊

'8.3'
  • 평점 정보 가져오기


end = len(soup.find_all('td', 'titleColumn'))
movie_name = [soup.find_all('td', 'titleColumn')[n].a.string for n in range(0, end)]
movie_name

⇊

['John Wick: Chapter 4',
 'Dungeons & Dragons: Honor Among Thieves',
 'Asteroid City',
 'Avatar: The Way of Water',
 '에브리씽 에브리웨어 올 앳 원스',
 '존 윅',
 'I See You',
 'Shazam! Fury of the Gods',
 'Murder Mystery 2',
 'Scream VI',
 '더 웨일',
 'John Wick: Chapter 3 - Parabellum',
 'Cocaine Bear',
 'The Super Mario Bros. Movie',
 'Air',
 'Tetris',
 'Creed III',
 'John Wick: Chapter 2',
 'Boston Strangler',
 'Luther: The Fallen Sun',
 '트라이앵글 오브 새드니스',
 '탑건: 매버릭',
 'Chor Nikal Ke Bhaga',
 'Evil Dead Rise',
 'Champions',
...
 '해리포터와 마법사의 돌',
 '더 블랙 폰',
 'Pathaan',
 '다크 나이트',
 'John Wick: Chapter 5']

  • end변수에 한 페이지에 나오는 영화 제목갯수 넣기

  • 0부터 그 갯수-1 만큼 for문 실행



end = len(soup.find_all('td', 'ratingColumn imdbRating'))
movie_rate = [rating.strong.string if rating.strong else 'No Rated' for rating in soup.find_all('td', 'ratingColumn imdbRating')]
movie_rate

⇊

['8.3',
 '7.6',
 'No Rated',
 '7.7',
 '7.9',
 '7.4',
 '6.8',
 '6.5',
 '5.7',
 '7.1',
 '7.7',
 '7.4',
 '6.0',
 '7.6',
 '7.8',
 '7.4',
 '7.1',
 '7.4',
 '6.5',
 '6.4',
 '7.4',
 '8.3',
 '7.8',
 '8.1',
 '6.8',
...
 '7.6',
 '6.9',
 '6.1',
 '9.0',
 'No Rated']
  • 평점에도 for 문.(평점이 매겨져있지 않은 것은No rated로)



─ 데이터 확보

  • 원하는 기간만큼의 데이터 얻기
date = pd.date_range('2023.03.01', periods=30, freq='D')
date

⇊

DatetimeIndex(['2023-03-01', '2023-03-02', '2023-03-03', '2023-03-04',
               '2023-03-05', '2023-03-06', '2023-03-07', '2023-03-08',
               '2023-03-09', '2023-03-10', '2023-03-11', '2023-03-12',
               '2023-03-13', '2023-03-14', '2023-03-15', '2023-03-16',
               '2023-03-17', '2023-03-18', '2023-03-19', '2023-03-20',
               '2023-03-21', '2023-03-22', '2023-03-23', '2023-03-24',
               '2023-03-25', '2023-03-26', '2023-03-27', '2023-03-28',
               '2023-03-29', '2023-03-30'],
              dtype='datetime64[ns]', freq='D')
  • pandas의 date_range로 손쉽게 날짜얻기 가능 

from tqdm import tqdm_notebook
#from tqdm.notebook import tqdm
import time
movie_date = []
movie_name = []
for today in tqdm_notebook(date):
    html = 'https://www.boxofficemojo.com/date/{date}/?ref_=bo_da_nav'
    response = urlopen(html.format(date=today.strftime('%Y-%m-%d')))
    soup = BeautifulSoup(response, 'html.parser')

    end = len(soup.find_all('td', 'a-text-left mojo-field-type-release_studios'))

    movie_date.extend([today for n in range(0, end)])
    movie_name.extend([soup.find_all('td', 'a-text-left mojo-field-type-release mojo-cell-wide')[n].a.string for n in range(0 ,end)])


    time.sleep(0.5)

⇊

100%
30/30 [01:54<00:00, 3.68s/it]
  • 30일치 데이터 받아오기


movie = pd.DataFrame({'date': movie_date, 'name': movie_name)
movie.head()

⇊

  • 데이터 프레임 제작

  • .astype() : 괄호안 숫자 형태로 변환



`***

from.제로베이스 데이터 취업스쿨 강의

+사족

네이버 영화 평점 서비스가 2023년 3월31일부로 종료하여

IMDB 과 Box Offic mojo를 참고

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