Develop Reference

Skip Certain Rows in Table Using BeautifulSoup

I want to pull the entire table of 2018 NFL fantasy football statistics, the below code is able to do this but I am running into this error: 'NoneType' object has no attribute 'a'.
I figured out this is occurring because there are rows that repeat the header names every 30 rows. These rows do not contain the 'a' tag all the other rows contain but they are a different class, class = "thead". I found a similar problem from a few years ago but am having trouble adapting the solution to my code. Would appreciate any help!
from bs4 import BeautifulSoup
url = 'https://www.pro-football-reference.com'
year = 2018
r = requests.get(url + '/years/' + str(year) + '/fantasy.htm')
soup = BeautifulSoup(r.content, 'html.parser')
parsed_table = soup.find_all('table')[0]
# first 2 rows are col headers so skip them with [2:]
for i,row in enumerate(parsed_table.find_all('tr')[2:]):
print(i)
dat = row.find('td', attrs={'data-stat': 'player'})
name = dat.a.get_text()
stub = dat.a.get('href')

Just need a bit of logic. There's a number of ways to do that, to check if there is an <a> tag.
What I did was simply add if dat:. Since dat = row.find('td', attrs={'data-stat': 'player'}), if it doesn't return anything, it'll come back False, and thus not look to get the <a> tag.
Also just as a note, since you are grabbing the first <table> tag (Ie soup.find_all('table')[0]), you can simply use .find() as that will find and return the first instance it finds.
from bs4 import BeautifulSoup
import requests
url = 'https://www.pro-football-reference.com'
year = 2018
r = requests.get(f'{url}/years/{year}/fantasy.htm')
soup = BeautifulSoup(r.content, 'html.parser')
parsed_table = soup.find('table')
# first 2 rows are col headers so skip them with [2:]
for i,row in enumerate(parsed_table.find_all('tr')[2:]):
print(i)
dat = row.find('td', attrs={'data-stat': 'player'})
if dat:
name = dat.a.get_text()
stub = dat.a.get('href')

Beautiful Soup to Scrape Data from Static Webpages

I am trying to values from a table of multiple static webpages. It is the verb conjugation data for Korean verbs here: https://koreanverb.app/
My Python script uses Beautiful Soup. The goal is to grab all conjugations from multiple URL inputs and output the data to a CSV file.
Conjugations are stored on the page in table with class "table-responsive" and under the table rows with class "conjugation-row". There are multiple "conjugation-row" table rows on each page. My script is someone only grabbing the first table row with class "conjugation-row".
Why isn't the for loop grabbing all the td elements with class "conjugation-row"? I would appreciate a solution that grabs all tr with class "conjugation-row". I tried using job_elements = results.find("tr", class_="conjugation-row"), but I get the following error:
AttributeError: ResultSet object has no attribute 'find'. You're probably treating a list of elements like a single element. Did you call find_all() when you meant to call find()?
Furthermore, when I do get the data and output to a CSV file, the data is in separate rows as expected, but leaves empty spaces., It places the data rows for the second URL at the index after all data rows for the first URL. See example output here:
See code here:
import requests
from bs4 import BeautifulSoup
import pandas as pd
import csv
# create csv file
outfile = open("scrape.csv","w",newline='')
writer = csv.writer(outfile)
## define first URL to grab conjugation names
url1 = 'https://koreanverb.app/?search=%ED%95%98%EB%8B%A4'
# define dataframe columns
df = pd.DataFrame(columns=['conjugation name'])
# get URL content
response = requests.get(url1)
soup = BeautifulSoup(response.content, 'html.parser')
# get table with all verb conjugations
results = soup.find("div", class_="table-responsive")
##### GET CONJUGATIONS AND APPEND TO CSV
# define URLs
urls = ['https://koreanverb.app/?search=%ED%95%98%EB%8B%A4',
'https://koreanverb.app/?search=%EB%A8%B9%EB%8B%A4',
'https://koreanverb.app/?search=%EB%A7%88%EC%8B%9C%EB%8B%A4']
# loop to get data
for url in urls:
response = requests.get(url)
soup2 = BeautifulSoup(response.content, 'html.parser')
# get table with all verb conjugations
results2 = soup2.find("div", class_="table-responsive")
# get dictionary form of verb/adjective
verb_results = soup2.find('dl', class_='dl-horizontal')
verb_title = verb_results.find('dd')
verb_title_text = verb_title.text
job_elements = results2.find_all("tr", class_="conjugation-row")
for job_element in job_elements:
conjugation_name = job_element.find("td", class_="conjugation-name")
conjugation_korean = conjugation_name.find_next_sibling("td")
conjugation_name_text = conjugation_name.text
conjugation_korean_text = conjugation_korean.text
data_column = pd.DataFrame({ 'conjugation name': [conjugation_name_text],
verb_title_text: [conjugation_korean_text],
})
#data_column = pd.DataFrame({verb_title_text: [conjugation_korean_text]})
df = df.append(data_column, ignore_index = True)
# save to csv
df.to_csv('scrape.csv')
outfile.close()
print('Verb Conjugations Collected and Appended to CSV, one per column')

Get all the job_elements using find_all() since find() only returns the first occurrence and iterate over them in a for loop like below.
job_elements = results.find_all("tr", class_="conjugation-row")
for job_element in job_elements:
conjugation_name = job_element.find("td", class_="conjugation-name")
conjugation_korean = conjugation_name.find_next_sibling("td")
conjugation_name_text = conjugation_name.text
conjugation_korean_text = conjugation_korean.text
# append element to data
df2 = pd.DataFrame([[conjugation_name_text,conjugation_korean_text]],columns=['conjugation_name','conjugation_korean'])
df = df.append(df2)
The error is where you are trying to use find() on a variable of type list.
As your script is growing big, I made some modifications like using get_conjugations() function and some proper names that are easy to understand. Firstly, conjugation_names and conjugation_korean_names are added into pandas Dataframe columns and then other columns are added subsequently (korean0, korean1 ...).
import requests
from bs4 import BeautifulSoup
import pandas as pd
# function to parse the html data & get conjugations
def get_conjugations(url):
#set return lists
conjugation_names = []
conjugation_korean_names = []
#get html text
html = requests.get(url).text
#parse the html text
soup = BeautifulSoup(html, 'html.parser')
#get table
table = soup.find("div", class_="table-responsive")
table_rows = table.find_all("tr", class_="conjugation-row")
for row in table_rows:
conjugation_name = row.find("td", class_="conjugation-name")
conjugation_korean = conjugation_name.find_next_sibling("td")
conjugation_names.append(conjugation_name.text)
conjugation_korean_names.append(conjugation_korean.text)
#return both lists
return conjugation_names, conjugation_korean_names
# create csv file
outfile = open("scrape.csv", "w", newline='')
urls = ['https://koreanverb.app/?search=%ED%95%98%EB%8B%A4',
'https://koreanverb.app/?search=%EB%A8%B9%EB%8B%A4',
'https://koreanverb.app/?search=%EB%A7%88%EC%8B%9C%EB%8B%A4']
# define dataframe columns
df = pd.DataFrame(columns=['conjugation_name', 'conjugation_korean', 'korean0', 'korean1'])
conjugation_names, conjugation_korean_names = get_conjugations(urls[0])
df['conjugation_name'] = conjugation_names
df['conjugation_korean'] = conjugation_korean_names
for index, url in enumerate(urls[1:]):
conjugation_names, conjugation_korean_names = get_conjugations(url)
#set column name
column_name = 'korean' + str(index)
df[column_name] = conjugation_korean_names
#save to csv
df.to_csv('scrape.csv')
outfile.close()
# Print DONE
print('Export to CSV Complete')
Output:
,conjugation_name,conjugation_korean,korean0,korean1
0,declarative present informal low,해,먹어,마셔
1,declarative present informal high,해요,먹어요,마셔요
2,declarative present formal low,한다,먹는다,마신다
3,declarative present formal high,합니다,먹습니다,마십니다
...
Note:
This assumes that elements in different URLs are in same order.

Python Web Scraping: Output to csv

I'm doing some progress with web scraping however I still need some help to perform some operations:
import requests
import pandas as pd
from bs4 import BeautifulSoup
url = 'http://fcf.cat/equip/1920/1i/sant-ildefons-ue-b'
# soup = BeautifulSoup(requests.get(converturl).content, 'html.parser')
soup = BeautifulSoup(requests.get(url).content, 'html.parser')
out = []
for tr in soup.select('.col-md-4 tbody tr'):
On the class col-md-4 I know there are 3 tables I want to generate a csv which as an output has three values: first name, last name, and for the last value I want the header name of the table.
first name, last name, header table
Any help would be appreciated.

This is what I have done on my own:
import requests
import pandas as pd
from bs4 import BeautifulSoup
url = 'http://fcf.cat/equip/1920/1i/sant-ildefons-ue-b'
soup = BeautifulSoup(requests.get(url).content, 'html.parser')
filename = url.rsplit('/', 1)[1] + '.csv'
tables = soup.select('.col-md-4 table')
rows = []
for tr in tables:
t = tr.get_text(strip=True, separator='|').split('|')
rows.append(t)
df = pd.DataFrame(rows)
print(df)
df.to_csv(filename)
Thanks,

This might work:
import requests
import pandas as pd
from bs4 import BeautifulSoup
url = 'http://fcf.cat/equip/1920/1i/sant-ildefons-ue-b'
soup = BeautifulSoup(requests.get(url).content, 'html.parser')
tables = soup.select('.col-md-4 table')
rows = []
for table in tables:
cleaned = list(table.stripped_strings)
header, names = cleaned[0], cleaned[1:]
data = [name.split(', ') + [header] for name in names]
rows.extend(data)
result = pd.DataFrame.from_records(rows, columns=['surname', 'name', 'table'])

You need to first iterate through each table you want to scrape, then for each table, get its header and rows of data. For each row of data, you want to parse out the First Name and Last Name (along with the header of the table).
Here's a verbose working example:
import requests
import pandas as pd
from bs4 import BeautifulSoup
url = 'http://fcf.cat/equip/1920/1i/sant-ildefons-ue-b'
soup = BeautifulSoup(requests.get(url).content, 'html.parser')
out = []
# Iterate through each of the three tables
for table in soup.select(".col-md-4 table"):
# Grab the header and rows from the table
header = table.select("thead th")[0].text.strip()
rows = [s.text.strip() for s in table.select("tbody tr")]
t = [] # This list will contain the rows of data for this table
# Iterate through rows in this table
for row in rows:
# Split by comma (last_name, first_name)
split = row.split(",")
last_name = split[0].strip()
first_name = split[1].strip()
# Create the row of data
t.append([first_name, last_name, header])
# Convert list of rows to a DataFrame
df = pd.DataFrame(t, columns=["first_name", "last_name", "table_name"])
# Append to list of DataFrames
out.append(df)
# Write to CSVs...
out[0].to_csv("first_table.csv", index=None) # etc...
Whenever you're web scraping, I highly recommend using strip() on all of the text you parse to make sure you don't have superfluous spaces in your data.
I hope this helps!

Beautiful Soup scrape table with table breaks

I'm trying to scrape a table into a dataframe. My attempt only returns the table name and not the data within rows for each region.
This is what i have so far:
from bs4 import BeautifulSoup as bs4
import requests
url = 'https://www.eia.gov/todayinenergy/prices.php'
r = requests.get(url)
soup = bs4(r.text, "html.parser")
table_regions = soup.find('table', {'class': "t4"})
regions = table_regions.find_all('tr')
for row in regions:
print row
ideal outcome i'd like to get:
region | price
---------------|-------
new england | 2.59
new york city | 2.52
Thanks for any assistance.

If you check your html response (soup) you will see that the table tag you get in this line table_regions = soup.find('table', {'class': "t4"}) its closed up before the rows that contain the information you need (the ones that contain the td's with the class names: up dn d1 and s1.
So how about using the raw td tags like this:
from bs4 import BeautifulSoup as bs4
import requests
import pandas as pd
url = 'https://www.eia.gov/todayinenergy/prices.php'
r = requests.get(url)
soup = bs4(r.text, "html.parser")
a = soup.find_all('tr')
rows = []
subel = []
for tr in a[42:50]:
b = tr.find_all('td')
for td in b:
subel.append(td.string)
rows.append(subel)
subel = []
df = pd.DataFrame(rows, columns=['Region','Price_1', 'Percent_change_1', 'Price_2', 'Percent_change_2', 'Spark Spread'])
Notice that I use just the a[42:50] slice of the results because a contains all the td's of the website. You can use the rest too if you need to.

BeautifulSoup: Can't Access Info Within TD

I'm looking at the following website:
https://modules.ussquash.com/ssm/pages/leagues/League_Information.asp?leagueid=1859
I want to extract the name of each university and the href associated with it. So for the first entry, I'd like to get Stanford and https://modules.ussquash.com/ssm/pages/leagues/Team_Information.asp?id=18564
I've gotten to the point where I have all of the TDs, using BeautifulSoup. I'm just having difficulty extracting the school and its href.
Here's my attempt:
def main():
r = requests.get('https://modules.ussquash.com/ssm/pages/leagues/League_Information.asp?leagueid=1859')
data = r.text
soup = BeautifulSoup(data)
table = soup.find_all('table')[1]
rows = table.find_all('tr')[1:]
for row in rows:
cols = row.find_all('td')
print(cols)
When I try to access cols[0], I get:
IndexError: list index out of range
Any idea how to fix this would be awesome!
Thanks

The first two tr's are in the thead which have no td tags, you want to skip the first two tr's:
rows = table.find_all('tr')[2:]
To get what you want, we can simplify using css selectors:
table = soup.find_all('table', limit=2)[1]
# skip first two tr's
rows = table.select("tr + tr + tr")
for row in rows:
# anchor we want is inside the first td
a = row.select_one("td a") # or a = row.find("td").a
print(a.text,a["href"])
Also the href is a relative path so you need to join it to a base url:
import requests
from bs4 import BeautifulSoup
from urllib.urlparse import urljoin
def main():
base = "https://modules.ussquash.com/ssm/pages/leagues/"
r = requests.get('https://modules.ussquash.com/ssm/pages/leagues/League_Information.asp?leagueid=1859')
data = r.text
soup = BeautifulSoup(data)
table = soup.find_all('table', limit=2)[1]
# skip first two tr's
rows = table.select("tr + tr + tr")
for row in rows:
a = row.select_one("td a")
print(a.text, urljoin(base, a["href"]))