Scraping table from the web with python

Question

I'm trying to get the hole table(all 1000+ universities) from this website - https://www.timeshighereducation.com/world-university-rankings/2018/world-ranking#!/page/0/length/25/sort_by/rank/sort_order/asc/cols/scores.

For this goal, I use the following libraries - requests and BeautifulSoup, and my code is:

import requests
from bs4 import BeautifulSoupenter 

html_content = requests.get('https://www.timeshighereducation.com/world-university-rankings/2018/world-ranking#!/page/0/length/25/sort_by/rank/sort_order/asc/cols/stats')
soup = bs4.BeautifulSoup(html_content, 'lxml')

Then I'm looking for a table:

table = soup.find_all('table')[0]

But as a result, I do not see the table itself <tbody>, the rows <tr> and the columns <td>.

HTML code:

Please help mу to get all the information from this site and build a dataframe from it.

Are you really doing `from bs4 import BeautifulSoupenter`, or is that a transcription mistake? — Kevin, May 04 '18 at 13:32
Checking the network activity for the page, it looks like it's populating the table using an AJAX call. `requests` doesn't execute javascript, so it won't see that data. Related reading and/or possible duplicate: [Using python Requests with javascript pages](https://stackoverflow.com/q/26393231/953482) — Kevin, May 04 '18 at 13:35

score 5 · Accepted Answer · answered May 04 '18 at 14:02

Try the below approach. You can get the url if you take a look at the network activity at xhr section within network tab under devtools. However, this is how your script should look like to get the data from that json response.

import requests

URL = "https://www.timeshighereducation.com/sites/default/files/the_data_rankings/world_university_rankings_2018_limit0_369a9045a203e176392b9fb8f8c1cb2a.json"

res = requests.get(URL)
for items in res.json()['data']:
    rank = items['rank']
    name = items['name']
    intstudents = items['stats_pc_intl_students']
    ratio = items['stats_female_male_ratio']
    print(rank,name,intstudents,ratio)

Output:

1 University of Oxford 38% 46 : 54
2 University of Cambridge 35% 45 : 55
=3 California Institute of Technology 27% 31 : 69
=3 Stanford University 22% 42 : 58
5 Massachusetts Institute of Technology 34% 37 : 63
6 Harvard University 26% None

Ajax1234 · Answer 2 · 2018-05-04T14:01:20.090

It seems that the site is dynamic, as a quick inspection of the source reveals that the table itself is not rendered in the DOM. Therefore, you need to use a browser manipulation tool such as selenium:

from selenium import webdriver
from bs4 import BeautifulSoup as soup
import re
from collections import namedtuple
d = webdriver.Chrome('/Users/jamespetullo/Downloads/chromedriver')
d.get('https://www.timeshighereducation.com/world-university-rankings/2018/world-ranking#!/page/0/length/25/sort_by/rank/sort_order/asc/cols/scores')
def page_results(html):
   school = namedtuple('school', ['ranking', 'name', 'location', 'scores'])
   rankings = [i.text for i in soup(html, 'lxml').find_all('td', {'class':'rank sorting_1 sorting_2'})]
   names = [i.text for i in soup(html, 'lxml').find_all('a', {'class':'ranking-institution-title'})]
   locations = [i.text for i in soup(html, 'lxml').find_all('div', {'class':'location'})]
   full_scores = [i.text for i in soup(html, 'lxml').find_all('td', {'class':re.compile('scores\s+[\w_]+\-score')})]
   final_scores = [dict(zip(['overall', 'teaching', 'research', 'citations', 'income', 'outlook'], full_scores[i:i+6])) for i in range(0, len(full_scores), 6)]
   return [school(*i) for i in zip(rankings, names, locations, final_scores)]

pages = [page_results(d.page_source)]
links = d.find_elements_by_tag_name('a')
for link in links:
   if link.text.isdigit():
      try:
        link.click()
        pages.append(page_results(d.page_source))
      except:
        pass

Example output:

[[school(ranking=u'1', name=u'University of Oxford', location=u'United Kingdom', scores={'outlook': u'95.0', 'overall': u'94.3', 'research': u'99.5', 'citations': u'99.1', 'income': u'63.7', 'teaching': u'86.7'}), school(ranking=u'2', name=u'University of Cambridge', location=u'United Kingdom', scores={'outlook': u'93.0', 'overall': u'93.2', 'research': u'97.8', 'citations': u'97.5', 'income': u'51.5', 'teaching': u'87.8'}), school(ranking=u'=3', name=u'California Institute of Technology', location=u'United States', scores={'outlook': u'59.7', 'overall': u'93.0', 'research': u'97.5', 'citations': u'99.5', 'income': u'92.6', 'teaching': u'90.3'}), school(ranking=u'=3', name=u'Stanford University', location=u'United States', scores={'outlook': u'77.6', 'overall': u'93.0', 'research': u'96.7', 'citations': u'99.9', 'income': u'60.5', 'teaching': u'89.1'}), school(ranking=u'5', name=u'Massachusetts Institute of Technology', location=u'United States', scores={'outlook': u'87.6', 'overall': u'92.5', 'research': u'91.9', 'citations': u'100.0', 'income': u'88.4', 'teaching': u'87.3'}), school(ranking=u'6', name=u'Harvard University', location=u'United States', scores={'outlook': u'79.7', 'overall': u'91.8', 'research': u'98.4', 'citations': u'99.7', 'income': u'46.4', 'teaching': u'84.2'}), school(ranking=u'7', name=u'Princeton University', location=u'United States', scores={'outlook': u'78.7', 'overall': u'91.1', 'research': u'93.9', 'citations': u'99.6', 'income': u'58.0', 'teaching': u'85.7'}), school(ranking=u'8', name=u'Imperial College London', location=u'United Kingdom', scores={'outlook': u'96.6', 'overall': u'89.2', 'research': u'88.7', 'citations': u'96.7', 'income': u'71.6', 'teaching': u'81.7'}), school(ranking=u'9', name=u'University of Chicago', location=u'United States', scores={'outlook': u'69.6', 'overall': u'88.6', 'research': u'90.1', 'citations': u'99.4', 'income': u'39.8', 'teaching': u'85.3'}), school(ranking=u'=10', name=u'ETH Zurich \u2013 Swiss Federal Institute of Technology Zurich', location=u'Switzerland', scores={'outlook': u'98.1', 'overall': u'87.7', 'research': u'92.0', 'citations': u'94.3', 'income': u'60.3', 'teaching': u'76.4'}), school(ranking=u'=10', name=u'University of Pennsylvania', location=u'United States', scores={'outlook': u'61.3', 'overall': u'87.7', 'research': u'90.1', 'citations': u'98.5', 'income': u'56.9', 'teaching': u'83.7'}), school(ranking=u'12', name=u'Yale University', location=u'United States', scores={'outlook': u'64.6', 'overall': u'87.6', 'research': u'87.0', 'citations': u'98.4', 'income': u'45.1', 'teaching': u'86.7'}), school(ranking=u'13', name=u'Johns Hopkins University', location=u'United States', scores={'outlook': u'70.6', 'overall': u'86.5', 'research': u'88.1', 'citations': u'98.4', 'income': u'95.8', 'teaching': u'76.1'}), school(ranking=u'14', name=u'Columbia University', location=u'United States', scores={'outlook': u'76.6', 'overall': u'86.0', 'research': u'83.3', 'citations': u'98.8', 'income': u'41.3', 'teaching': u'82.2'}), school(ranking=u'15', name=u'University of California, Los Angeles', location=u'United States', scores={'outlook': u'59.5', 'overall': u'85.7', 'research': u'88.1', 'citations': u'97.9', 'income': u'48.6', 'teaching': u'80.7'}), school(ranking=u'16', name=u'UCL', location=u'United Kingdom', scores={'outlook': u'94.6', 'overall': u'85.3', 'research': u'88.2', 'citations': u'94.6', 'income': u'41.2', 'teaching': u'74.4'}), school(ranking=u'17', name=u'Duke University', location=u'United States', scores={'outlook': u'62.5', 'overall': u'85.1', 'research': u'80.6', 'citations': u'98.3', 'income': u'100.0', 'teaching': u'80.7'}), school(ranking=u'18', name=u'University of California, Berkeley', location=u'United States', scores={'outlook': u'64.5', 'overall': u'84.3', 'research': u'84.5', 'citations': u'99.8', 'income': u'37.5', 'teaching': u'77.4'}), school(ranking=u'19', name=u'Cornell University', location=u'United States', scores={'outlook': u'69.2', 'overall': u'84.2', 'research': u'86.6', 'citations': u'97.6', 'income': u'34.6', 'teaching': u'76.2'}), school(ranking=u'20', name=u'Northwestern University', location=u'United States', scores={'outlook': u'59.2', 'overall': u'83.3', 'research': u'86.7', 'citations': u'96.9', 'income': u'78.2', 'teaching': u'72.6'}), school(ranking=u'21', name=u'University of Michigan', location=u'United States', scores={'outlook': u'55.8', 'overall': u'83.1', 'research': u'86.3', 'citations': u'95.7', 'income': u'46.2', 'teaching': u'77.2'}), school(ranking=u'=22', name=u'National University of Singapore', location=u'Singapore', scores={'outlook': u'95.8', 'overall': u'82.8', 'research': u'88.2', 'citations': u'81.3', 'income': u'61.9', 'teaching': u'77.4'}), school(ranking=u'=22', name=u'University of Toronto', location=u'Canada', scores={'outlook': u'80.1', 'overall': u'82.8', 'research': u'84.8', 'citations': u'92.6', 'income': u'46.5', 'teaching': u'74.6'}), school(ranking=u'24', name=u'Carnegie Mellon University', location=u'United States', scores={'outlook': u'79.1', 'overall': u'81.9', 'research': u'83.7', 'citations': u'99.7', 'income': u'50.4', 'teaching': u'65.8'}), school(ranking=u'=25', name=u'London School of Economics and Political Science', location=u'United Kingdom', scores={'outlook': u'92.2', 'overall': u'79.4', 'research': u'72.0', 'citations': u'94.9', 'income': u'33.7', 'teaching': u'71.8'})]]

Scraping table from the web with python

2 Answers2