29.EDA-6

SOWA·2023년 4월 4일
EDA웹데이터
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EDA

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🧷 웹데이터 분석

🖇️ Beautiful Soup

태그로 되어있는 문서를 해석하는 기능을 가진 파이썬 모듈

from bs4 import BeautifulSoup
page = open('../data/03. test_first.html', 'r').read()
soup = BeautifulSoup(page, 'html.parser')
print(soup.prettify())

⇊

<!DOCTYPE html>
<html>
 <head>
  <title>
   Very Simple HTML Code by PinkWink
  </title>
 </head>
 <body>
  <div>
   <p class="inner-text first-item" id="first">
    Happy PinkWink.
    <a href="http://www.pinkwink.kr" id="pw-link">
     PinkWink
    </a>
   </p>
   <p class="inner-text second-item">
    Happy Data Science.
    <a href="https://www.python.org" id="py-link">
     Python
    </a>
   </p>
  </div>
  <p class="outer-text first-item" id="second">
   <b>
    Data Science is funny.
   </b>
  </p>
  <p class="outer-text">
   <b>
    All I need is Love.
   </b>
  </p>
 </body>
</html>
  • html 파일을 읽을때
  • open: 파일명과 함꼐 읽기(r), 쓰기(w) 속성 지정
  • html.parser: Beautiful SOup의 html을 읽는 엔진 중 하나(lxml도 많이 사용)
    -prettify(): html 출력을 이쁘게 만들어 주는 기능(들여쓰기가 들어간 상태)

soup.body

⇊

<body>
<div>
<p class="inner-text first-item" id="first">
                Happy PinkWink.
                <a href="http://www.pinkwink.kr" id="pw-link">PinkWink</a>
</p>
<p class="inner-text second-item">
                Happy Data Science.
                <a href="https://www.python.org" id="py-link">Python</a>
</p>
</div>
<p class="outer-text first-item" id="second">
<b>
                Data Science is funny.
            </b>
</p>
<p class="outer-text">
<b>
                All I need is Love.
            </b>
</p>
</body>
  • body: body태그만 보고 싶은 경우

soup.find('p')

⇊

<p class="inner-text first-item" id="first">
                Happy PinkWink.
                <a href="http://www.pinkwink.kr" id="pw-link">PinkWink</a>
</p>
  • find(): 특정 태그를 찾아줌(단, 맨 먼저 보여지는 하나만 찾을 수 있음) 

soup.find_all('p')

⇊

[<p class="inner-text first-item" id="first">
                 Happy PinkWink.
                 <a href="http://www.pinkwink.kr" id="pw-link">PinkWink</a>
 </p>,
 <p class="inner-text second-item">
                 Happy Data Science.
                 <a href="https://www.python.org" id="py-link">Python</a>
 </p>,
 <p class="outer-text first-item" id="second">
 <b>
                 Data Science is funny.
             </b>
 </p>,
 <p class="outer-text">
 <b>
                 All I need is Love.
             </b>
 </p>]
  • find_all(): 지정된 태그를 전부 찾아줌 (리스트형 데이터로)

for each_tag in soup.find_all('p'):
    print('------------------')
    print(each_tag.get_text())

⇊

------------------

                Happy PinkWink.
                PinkWink

------------------

                Happy Data Science.
                Python

------------------


                Data Science is funny.
            

------------------


                All I need is Love.
  • get_text(): 태그로 쌓여져 있는 글자를 가져오는 함수

links = soup.find_all('a')
links

⇊

[<a href="http://www.pinkwink.kr" id="pw-link">PinkWink</a>,
 <a href="https://www.python.org" id="py-link">Python</a>]
for each in links:
    href = each['href']
    text = each.string
    print(text + '->' + href)

⇊

PinkWink->http://www.pinkwink.kr
Python->https://www.python.org
  • 외부로 연결되는 링크 주소 알아내는 법

🖇️ 크롬 개발자 도구 이용

from urllib.request import urlopen
#url = 'https://finance.naver.com/marketindex/'
url = 'https://finance.naver.com/marketindex/'
page = urlopen(url)

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

print(soup.prettify())

⇊

Output exceeds the size limit. Open the full output data in a text editor
<script language="javascript" src="/template/head_js.naver?referer=info.finance.naver.com&amp;menu=marketindex&amp;submenu=market">
</script>
<script src="https://ssl.pstatic.net/imgstock/static.pc/20230321170048/js/info/jindo.min.ns.1.5.3.euckr.js" type="text/javascript">
</script>
<script src="https://ssl.pstatic.net/imgstock/static.pc/20230321170048/js/jindo.1.5.3.element-text-patch.js" type="text/javascript">
</script>
<div id="container" style="padding-bottom:0px;">
 <div class="market_include">
  <div class="market_data">
   <div class="market1">
    <div class="title">
     <h2 class="h_market1">
      <span>
       환전 고시 환율
      </span>
     </h2>
    </div>
    <!-- data -->
    <div class="data">
     <ul class="data_lst" id="exchangeList">
      <li class="on">
       <a class="head usd" href="/marketindex/exchangeDetail.naver?marketindexCd=FX_USDKRW" onclick="clickcr(this, 'fr1.usdt', '', '', event);">
        <h3 class="h_lst">
         <span class="blind">
          미국 USD
...
	window.addEventListener('mousedown', gnbLayerClose);
}
</script>
  • 웹주소(url)에 접근할 때는 urllib의 request모듈 필요
  • response, res 도 많이 사용

url = 'https://finance.naver.com/marketindex/'
response = urlopen(url)
response.status

⇊
200

  • response: http 상태 코드,정상적으로 요청을 했고 정상적으로 응답을 받았다는 코드
  • 결과값은 어떤 상태인지 표현
    ㄴ http 상태코드


import requests
#from urllib.request.Request
from bs4 import BeautifulSoup
url = 'https://finance.naver.com/marketindex/'
response = requests.get(url)
# response.text
soup = BeautifulSoup(response.text, 'html.parser')
print(soup.prettify())

⇊

Output exceeds the size limit. Open the full output data in a text editor
<script language="javascript" src="/template/head_js.naver?referer=info.finance.naver.com&amp;menu=marketindex&amp;submenu=market">
</script>
<script src="https://ssl.pstatic.net/imgstock/static.pc/20230321170048/js/info/jindo.min.ns.1.5.3.euckr.js" type="text/javascript">
</script>
<script src="https://ssl.pstatic.net/imgstock/static.pc/20230321170048/js/jindo.1.5.3.element-text-patch.js" type="text/javascript">
</script>
<div id="container" style="padding-bottom:0px;">
 <div class="market_include">
  <div class="market_data">
   <div class="market1">
    <div class="title">
     <h2 class="h_market1">
      <span>
       환전 고시 환율
      </span>
     </h2>
    </div>
    <!-- data -->
    <div class="data">
     <ul class="data_lst" id="exchangeList">
      <li class="on">
       <a class="head usd" href="/marketindex/exchangeDetail.naver?marketindexCd=FX_USDKRW" onclick="clickcr(this, 'fr1.usdt', '', '', event);">
        <h3 class="h_lst">
         <span class="blind">
          미국 USD
...
	window.addEventListener('mousedown', gnbLayerClose);
}
</script>
  • find, select_one :단일 선택
  • find_all, select: 다중선택


exchangeList = soup.select('#exchangeList > li') #바로 밑 하위데이터들
len(exchangeList), exchangeList

⇊

Output exceeds the size limit. Open the full output data in a text editor
(4,
 [<li class="on">
  <a class="head usd" href="/marketindex/exchangeDetail.naver?marketindexCd=FX_USDKRW" onclick="clickcr(this, 'fr1.usdt', '', '', event);">
  <h3 class="h_lst"><span class="blind">미국 USD</span></h3>
  <div class="head_info point_up">
  <span class="value">1,315.00</span>
  <span class="txt_krw"><span class="blind">원</span></span>
  <span class="change">2.00</span>
  <span class="blind">상승</span>
  </div>
  </a>
  <a class="graph_img" href="/marketindex/exchangeDetail.naver?marketindexCd=FX_USDKRW" onclick="clickcr(this, 'fr1.usdc', '', '', event);">
  <img alt="" height="153" src="https://ssl.pstatic.net/imgfinance/chart/marketindex/FX_USDKRW.png" width="295"/>
  </a>
  <div class="graph_info">
  <span class="time">2023.04.04 16:13</span>
  <span class="source">하나은행 기준</span>
  <span class="count">고시회차<span class="num">579</span>회</span>
  </div>
  </li>,
  <li class="">
  <a class="head jpy" href="/marketindex/exchangeDetail.naver?marketindexCd=FX_JPYKRW" onclick="clickcr(this, 'fr1.jpyt', '', '', event);">
  <h3 class="h_lst"><span class="blind">일본 JPY(100엔)</span></h3>
  <div class="head_info point_up">
  <span class="value">991.37</span>
...
  <span class="time">2023.04.04 16:13</span>
  <span class="source">하나은행 기준</span>
  <span class="count">고시회차<span class="num">579</span>회</span>
  </div>
  </li>])

title = exchangeList[0].select_one('.h_lst').text  #제목
exchange = exchangeList[0].select_one('.value').text # 현재 환율
change = exchangeList[0].select_one('.change'). text # 환율 변화값
updown = exchangeList[0].select_one('div.head_info.point_up > .blind').text #>를 주면 div.head_info.point_up의 바로 밑의 하위 데이터 반환
title, exchange, change, updown

⇊

('미국 USD', '1,315.00', '2.00', '상승')
  • id => # , class => .
  • id는 단 하나씩만 존재
  • '>' 는 '>'표시 앞에 있는 클래스의 바로 밑 데이터 반환

baseUrl = 'https://finance.naver.com'
baseUrl +exchangeList[0].select_one('a').get('href')

⇊

'https://finance.naver.com/marketindex/exchangeDetail.naver?marketindexCd=FX_USDKRW'


#4개 데이터 수집

exchange_datas = []
baseUrl = 'https://finance.naver.com'

for item in exchangeList:
    data = {
        'title':item.select_one('.h_lst').text,
        'exchange':item.select_one('.value').text,
        'change':item.select_one('.change').text,
        'updown':item.select_one('.head_info > .blind').text,
        'link':baseUrl + item.select_one('a').get('href')

    }
    exchange_datas.append(data)

df = pd.DataFrame(exchange_datas)
df

⇊



🖇️ 위키백과 문서 정보 가져오기

import urllib
from urllib.request import Request

html = 'https://ko.wikipedia.org/wiki/{search_words}' #중괄호가 들어가면 문자열(str)에서 변수가 됨
req = Request(html.format(search_words=urllib.parse.quote('여명의_눈동자')))

response = urlopen(req)

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

⇊

Output exceeds the size limit. Open the full output data in a text editor
<!DOCTYPE html>

<html class="client-nojs vector-feature-language-in-header-enabled vector-feature-language-in-main-page-header-disabled vector-feature-language-alert-in-sidebar-enabled vector-feature-sticky-header-disabled vector-feature-page-tools-enabled vector-feature-page-tools-pinned-disabled vector-feature-toc-pinned-enabled vector-feature-main-menu-pinned-disabled vector-feature-limited-width-enabled vector-feature-limited-width-content-enabled" dir="ltr" lang="ko">
<head>
<meta charset="utf-8"/>
<title>여명의 눈동자 - 위키백과, 우리 모두의 백과사전</title>
<script>document.documentElement.className="client-js vector-feature-language-in-header-enabled vector-feature-language-in-main-page-header-disabled vector-feature-language-alert-in-sidebar-enabled vector-feature-sticky-header-disabled vector-feature-page-tools-enabled vector-feature-page-tools-pinned-disabled vector-feature-toc-pinned-enabled vector-feature-main-menu-pinned-disabled vector-feature-limited-width-enabled vector-feature-limited-width-content-enabled";(function(){var cookie=document.cookie.match(/(?:^|; )kowikimwclientprefs=([^;]+)/);if(cookie){var featureName=cookie[1];document.documentElement.className=document.documentElement.className.replace(featureName+'-enabled',featureName+'-disabled');}}());RLCONF={"wgBreakFrames":false,"wgSeparatorTransformTable":["",""],"wgDigitTransformTable":["",""],"wgDefaultDateFormat":"ko","wgMonthNames":["","1월","2월","3월","4월","5월","6월","7월","8월","9월","10월","11월","12월"],"wgRequestId":"fa90b647-63d7-4ebc-ae46-bd412f65665a",
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</body>
</html>


n = 0
for each in soup.find_all('ul'):
    print('=>'+str(n)+'=========================')
    print(each.get_text())
    n += 1

⇊

Output exceeds the size limit. Open the full output data in a text editor
=>0=========================
대문최근 바뀜요즘 화제임의의 문서로기부
=>1=========================
사랑방사용자 모임관리 요청
=>2=========================
도움말정책과 지침질문방
=>3=========================
계정 만들기로그인
=>4=========================
 계정 만들기 로그인
=>5=========================
기여토론
=>6=========================



처음 위치





1개요

...
  • ul을 찾은 다음 구분기호를 집어넣음

soup.find_all('ul')[32].text.strip().replace('\xa0', '').replace('\n', '')

⇊

'채시라: 윤여옥 역 (아역: 김민정)박상원: 장하림(하리모토 나츠오) 역 (아역: 김태진)최재성: 최대치(사카이) 역 (아역: 장덕수)'


🖇️ 시카고 맛집 데이터 분석

from bs4 import BeautifulSoup

from urllib.request import Request, urlopen

url_base = 'https://www.chicagomag.com'
url_sub = '/chicago-magazine/november-2012/best-sandwiches-chicago/'
url = url_base + url_sub

#html = urlopen(url)

req = Request(url, headers = {'User-Agent':'Chrome'})
html = urlopen(req).read()
soup = BeautifulSoup(html, 'html.parser')

soup

⇊

Output exceeds the size limit. Open the full output data in a text editor
<!DOCTYPE html>

<html lang="en-US">
<head>
<meta charset="utf-8"/>
<meta content="IE=edge" http-equiv="X-UA-Compatible">
<link href="https://gmpg.org/xfn/11" rel="profile"/>
<script src="https://cmp.osano.com/16A1AnRt2Fn8i1unj/f15ebf08-7008-40fe-9af3-db96dc3e8266/osano.js"></script>
<title>The 50 Best Sandwiches in Chicago – Chicago Magazine</title>
<style type="text/css">
					.heateor_sss_button_instagram span.heateor_sss_svg,a.heateor_sss_instagram span.heateor_sss_svg{background:radial-gradient(circle at 30% 107%,#fdf497 0,#fdf497 5%,#fd5949 45%,#d6249f 60%,#285aeb 90%)}
						div.heateor_sss_horizontal_sharing a.heateor_sss_button_instagram span{background:#000!important;}div.heateor_sss_standard_follow_icons_container a.heateor_sss_button_instagram span{background:#000;}
										.heateor_sss_horizontal_sharing .heateor_sss_svg,.heateor_sss_standard_follow_icons_container .heateor_sss_svg{
							background-color: #000!important;
				background: #000!important;
							color: #fff;
						border-width: 0px;
			border-style: solid;
			border-color: transparent;
		}
					.heateor_sss_horizontal_sharing .heateorSssTCBackground{
				color:#666;
			}
					.heateor_sss_horizontal_sharing span.heateor_sss_svg:hover,.heateor_sss_standard_follow_icons_container span.heateor_sss_svg:hover{
						border-color: transparent;
...
  }
}
</script>
</body>
</html>


print(soup.find_all('div', 'sammy'))

⇊

Output exceeds the size limit. Open the full output data in a text editor
[<div class="sammy" style="position: relative;">
<div class="sammyRank">1</div>
<div class="sammyListing"><a href="/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Old-Oak-Tap-BLT/"><b>BLT</b><br/>
Old Oak Tap<br/>
<em>Read more</em> </a></div>
</div>, <div class="sammy" style="position: relative;">
<div class="sammyRank">2</div>
<div class="sammyListing"><a href="/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Au-Cheval-Fried-Bologna/"><b>Fried Bologna</b><br/>
Au Cheval<br/>
<em>Read more</em> </a></div>
</div>, <div class="sammy" style="position: relative;">
<div class="sammyRank">3</div>
<div class="sammyListing"><a href="/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Xoco-Woodland-Mushroom/"><b>Woodland Mushroom</b><br/>
Xoco<br/>
<em>Read more</em> </a></div>
</div>, <div class="sammy" style="position: relative;">
<div class="sammyRank">4</div>
<div class="sammyListing"><a href="/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Als-Deli-Roast-Beef/"><b>Roast Beef</b><br/>
Al’s Deli<br/>
<em>Read more</em> </a></div>
</div>, <div class="sammy" style="position: relative;">
<div class="sammyRank">5</div>
<div class="sammyListing"><a href="/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Publican-Quality-Meats-PB-L/"><b>PB&amp;L</b><br/>
Publican Quality Meats<br/>
<em>Read more</em> </a></div>
...
<div class="sammyListing"><a href="https://www.chicagomag.com/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Phoebes-Bakery-The-Gatsby/"><b>The Gatsby</b><br/>
Phoebe’s Bakery<br/>
<em>Read more</em> </a></div>
</div>]


tmp_one = soup.find_all('div', 'sammy')[0]
type(tmp_one)

⇊

bs4.element.Tag
  • type이 bs4.element.Tag라는것은 find 명령을 사용할 수 있다는 뜻

tmp_one.find(class_='sammyListing').get_text()

⇊

'BLT\nOld Oak Tap\nRead more '
  • 메뉴, 가게이름 데이터 한꺼번에 존재

tmp_one.find('a')['href']

⇊

'/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Old-Oak-Tap-BLT/'
  • 연결되는 홈페이지 주소가 '상대경로'

import re
tmp_string = tmp_one.find(class_='sammyListing').get_text()
re.split(('\n|\r\n'), tmp_string)

⇊

['BLT', 'Old Oak Tap', 'Read more ']
  • 가게 이름과 메뉴는 re모듈의 split으로 쉽게 구분 가능

print(re.split(('\n|\r\n'), tmp_string)[0])
print(re.split(('\n|\r\n'), tmp_string)[1])

⇊

BLT
Old Oak Tap

ㄴ 위 내용들을 전체 반복문으로 호출

from urllib.parse import urljoin

url_base = 'https://www.chicagomag.com'

rank = []
main_menu = []
cafe_name = []
url_add = []

list_soup = soup.find_all('div', 'sammy')

for item in list_soup:
    rank.append(item.find(class_='sammyRank').get_text())
    tmp_string = item.find(class_='sammyListing').get_text()
    main_menu.append(re.split(('\n|\r\n'), tmp_string)[0])
    cafe_name.append(re.split(('\n|\r\n'), tmp_string)[1])
    url_add.append(urljoin(url_base, item.find('a')['href']))  #urljoin=가져온 두번째 주소가 만약 절대주소라면 url_base 붙이지 않음. 상대주소일 경우만 붙임
  • urljoin : 가져온 두번째주소가 절대주소라면 url_base를 붙이지 않음.상대주소일 경우에만 붙임

rank[:5]

⇊
['1', '2', '3', '4', '5']


main_menu[:5]

⇊

['BLT', 'Fried Bologna', 'Woodland Mushroom', 'Roast Beef', 'PB&L']

cafe_name[:5]

⇊

['Old Oak Tap', 'Au Cheval', 'Xoco', 'Al’s Deli', 'Publican Quality Meats']

url_add[:5]

⇊

['https://www.chicagomag.com/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Old-Oak-Tap-BLT/',
 'https://www.chicagomag.com/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Au-Cheval-Fried-Bologna/',
 'https://www.chicagomag.com/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Xoco-Woodland-Mushroom/',
 'https://www.chicagomag.com/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Als-Deli-Roast-Beef/',
 'https://www.chicagomag.com/Chicago-Magazine/November-2012/Best-Sandwiches-in-Chicago-Publican-Quality-Meats-PB-L/']


ㄴ 데이터 프레임으로 정리

import pandas as pd

data = {'Rank': rank, 'Menu':main_menu, 'Cafe':cafe_name, 'URL':url_add}
df = pd.DataFrame(data)
df.head()

⇊


🖇️ 시카고 맛집 데이터 하위 페이지 분석

req = Request(df['URL'][0], headers={"User-Agent":"Chrome"})
html = urlopen(req).read()

soup_tmp = BeautifulSoup(html, 'html.parser')
print(soup_tmp.find('p', 'addy'))

⇊

<p class="addy">
<em>$10. 2109 W. Chicago Ave., 773-772-0406, <a href="http://www.theoldoaktap.com/">theoldoaktap.com</a></em></p>

ㄴ 정규식으로 정리

─ 정규식(Regular Expression)

  • 문장내에서의 패턴을 손쉽게 찾을 수 있음


price_tmp = soup_tmp.find('p', 'addy').get_text()
price_tmp

⇊

'\n$10. 2109 W. Chicago Ave., 773-772-0406, theoldoaktap.com'
  • text로 먼저 변환

import re
re.split('.,', price_tmp)
price_tmp = re.split('.,', price_tmp)[0]
price_tmp

⇊
'\n$10. 2109 W. Chicago Ave'

  • 가격과 주소만 가져오기 위해 .,로 분리

re.search('\$\d+\.(\d+)?', price_tmp).group()

⇊
'$10.'

  • '\$\d+.(\d+)?' : 달러 기호가 오고, 숫자 여러개가 오고, .이 와야하고, .뒤에는 숫자 여러개가 있을 수도 있고, 없을 수도 있음.

tmp = re.search('\$\d+\.(\d+)?', price_tmp).group()
price_tmp[len(tmp) + 2:]

⇊

'2109 W. Chicago Ave'
  • 가격이 끝나는 지점의 위치를 이용. 그 뒤는 주소로 생각


price = []
address = []

for n in df.index[:3]:
    # html = urlopen(df['URL'][n])
    req = Request(df['URL'][n], headers={'User-Agent':'Mozilla/5.0'})
    html = urlopen(req).read()

    soup_tmp = BeautifulSoup(html, 'lxml')

    gettings = soup_tmp.find('p', 'addy').get_text()

    price_tmp = re.split('.,', gettings)[0]
    tmp = re.search('\$\d+\.(\d+)?', price_tmp).group()

    price.append(tmp)
    address.append(price_tmp[len(tmp) + 2 :])

    print(n)


for item in df[:3]['URL']:
    print(item)

ㄴ 리스트형 데이터 반복시킬떄는 위와같은 방법이 정석이지만, 여러 컬럼을 for문 내에서 사용할때는 어려움



from tqdm import tqdm

price = []
address = []

for idx, row in tqdm(df.iterrows()):
    # html = urlopen(df['URL'][n])
    req = Request(row['URL'][n], headers={'User-Agent':'Mozilla/5.0'})
    html = urlopen(req).read()

    soup_tmp = BeautifulSoup(html, 'lxml')

    gettings = soup_tmp.find('p', 'addy').get_text()

    price_tmp = re.split('.,', gettings)[0]
    tmp = re.search('\$\d+\.(\d+)?', price_tmp).group()

    price.append(tmp)
    address.append(price_tmp[len(tmp) + 2 :])

    print(n)
  • tqdm: 프로그세스 바 생성

⇊

50it [01:09,  1.40s/it]

🖇️ 시카고 맛집 데이터 지도 시각화

import folium
import pandas as pd
import googlemaps
import numpy as np
from tqdm import tqdm
df =pd.read_csv('../data/03.best_sandwiches_list_chicago2.csv', index_col=0)
df.head(5)

⇊


gmaps_key = 'AI....'
gmaps = googlemaps.Client(key=gmaps_key)
lat = []
lng = []

for idx, row in tqdm(df.iterrows()):
    if not row['Address'] == 'Multiple location':
        target_name = row['Address'] + ',' + 'Chicago'
        gmaps_output = gmaps.geocode(target_name)
        location_output = gmaps_output[0].get('geometry')
        lat.append(location_output['location']['lat'])
        lng.append(location_output['location']['lng'])

    else:
        lat.append(np.nan)
        lng.append(np.nan)
df['lat'] = lat
df['lng'] = lng
df.head()

⇊


mapping = folium.Map(location=[41.8781136, -87.6297982], zoom_start=11)
mapping

⇊



mapping = folium.Map(location=[41.8781136, -87.6297982], zoom_start=11)

for idx, row in df.iterrows():
    if not row['Address'] == 'Multiple location':
        folium.Marker([row['lat'], row['lng']], popup=row['Cafe']).add_to(mapping)

mapping

⇊

  • 마커 추가


mapping = folium.Map(location=[41.8781136, -87.6297982], zoom_start=11)

for idx, row in df.iterrows():
    if not row['Address'] == 'Multiple location':
        folium.Marker([row['lat'], row['lng']], popup=row['Cafe'],
                      tooltip=row['Menu'], icon= folium.Icon(icon='coffee', prefix='fa'),
                      ).add_to(mapping)

mapping

⇊

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