Develop Reference

Getting headers from html (parsing)

The source is https://en.wikipedia.org/wiki/COVID-19_pandemic_in_the_United_States. I am looking to use the table called "COVID-19 pandemic in the United States by state and territory" which is the third diagram on the page.
Here is my code so far
from bs4 import BeautifulSoup
import pandas as pd
with open("COVID-19 pandemic in the United States - Wikipedia.htm", "r", encoding="utf-8") as fd:
soup=BeautifulSoup(fd)
print(soup.prettify())
all_tables = soup.find_all("table")
print("The total number of tables are {} ".format(len(all_tables)))
data_table = soup.find("div", {"class": 'mw-stack stack-container stack-clear-right mobile-float-reset'})
print(type(data_table))
sources = data_table.tbody.findAll('tr', recursive=False)[0]
sources_list = [td for td in sources.findAll('td')]
print(len(sources_list))
data = data_table.tbody.findAll('tr', recursive=False)[1].findAll('td', recursive=False)
data_tables = []
for td in data:
data_tables.append(td.findAll('table'))
header1 = [th.getText().strip() for th in data_tables[0][0].findAll('thead')[0].findAll('th')]
header1
This last line with header1 i giving me the error "list index out of range". What it is supposed to print is "U.S State or territory....."
I don't know anything about html, and everything gets me stuck and confused. The soup.find could also be referencing the wrong part of the webpage.

Can you just use
headers = [element.text.strip() for element in data_table.find_all("th")]
To get the text in the headers?
To get the entire table as a pandas dataframe, you can do:
import pandas as pd
from bs4 import BeautifulSoup
soup = BeautifulSoup(html_file)
data_table = soup.find("div", {"class": 'mw-stack stack-container stack-clear-right mobile-float-reset'})
rows = data_table.find_all("tr")
# Delete first row as it's not part of the table and confuses pandas
# this removes it from both soup and data_table
rows[0].decompose()
# Same for third row
rows[2].decompose()
# Same for last two rows
rows[-1].decompose()
rows[-2].decompose()
# Read html with pandas
df = pd.read_html(str(data_table))[0]
# Keep only the useful columns
df = df[['U.S. state or territory[i].1', 'Cases[ii]', 'Deaths', 'Recov.[iii]', 'Hosp.[iv]']]
# Rename columns
df.columns = ["State", "Cases", "Deaths", "Recov.", "Hosp."]

It's probably easier in these cases to try to read tables with pandas, and go from there:
import pandas as pd
table = soup.select_one("div#covid19-container table")
df = pd.read_html(str(table))[0]
df
The output is the target table.

by looking at your code, I think you should call the html tag by find, not by find_all in the title tag

Html table scraping using beautifulsoup

I am trying to a table from SEC filling 10-K, I think it is going allright except the part where pandas converting it to dataframes as I am new to data frames so I think making mistake in indexing, Please help me on this as I am getting fallowing error "IndexError: index 2 is out of bounds for axis 0 with size 2"
I am using this programming
import requests
import pandas as pd
from bs4 import BeautifulSoup
url = 'https://www.sec.gov/Archives/edgar/data/1022344/000155837017000934/spg-20161231x10k.htm#Item8FinancialStatementsandSupplementary'
r = requests.get(url)
html_doc = r.text
soup = BeautifulSoup(html_doc, 'lxml')
table = soup.find_all('table')[0]
new_table = pd.DataFrame(columns=range(0,2), index = [0])
row_marker = 0
for row in table.find_all('tr'):
column_marker = 0
columns = row.find_all('td')
for column in columns:
new_table.iat[row_marker,column_marker] = column.get_text()
column_marker += 1
new_table
If dataframe issue isn't resolvable than please suggest any other substitute like writing data to csv/excel also any sugesstion for extracting mutiple table at once will be really helpful

Get column from a table with Python and Beautiful Soup

I am new to Python and I want to get the "price" column of data from a table however I'm unable to retrieve that data.
Currently what I'm doing:
# Libraies
from urllib.request import urlopen
from bs4 import BeautifulSoup
html = urlopen("http://pythonscraping.com/pages/page3.html")
soup = BeautifulSoup(html, "html.parser")
table = soup.find("table")
for row in table.find_all("tr"):
col = row.find_all("td")
print(col[2])
print("---")
I keep getting a list index out of value range. I've read the documentation and tried a few different ways, but I can't seem to get it down.
Also, I am using Python3.

The problem is that you are iterating over all tr inside the table, and there is 1 header tr at the beginning that you don't need, so just avoid using that one:
# Libraies
from urllib.request import urlopen
from bs4 import BeautifulSoup
html = urlopen("http://pythonscraping.com/pages/page3.html")
soup = BeautifulSoup(html, "html.parser")
table = soup.find("table")
for row in table.find_all("tr")[1:]:
col = row.find_all("td")
print(col[2])
print("---")

Probably means that one of the rows has no td tag. You could wrap the print or whatever usage of col[2] in a try except block and ignore cases where the col is empty or has less than three items
for row in table.find_all("tr"):
col = row.find_all("td")
try:
print(col[2])
print("---")
except IndexError:
pass

Forgetting something - Python BeautifulSoup and FinViz

I'm getting stuck trying to grab the text values off the a.href tags. I've managed to isolate the the target values but keep running into an error when I try to get_text().
import requests
from bs4 import BeautifulSoup
base_url = 'http://finviz.com/screener.ashx?v=152&s=ta_topgainers&o=price&c=0,1,2,3,4,5,6,7,25,63,64,65,66,67'
html = requests.get(base_url)
soup = BeautifulSoup(html.content, "html.parser")
main_div = soup.find('div', attrs = {'id':'screener-content'})
table = main_div.find('table')
sub = table.findAll('tr')
rows = sub[5].findAll('td')
for row in rows:
data = row.a
print data

Assuming you are actually trying to print data.get_text(), it would fail for some of the row in rows - because, in some cases, there are no child link elements in the td cells. You can check that a link was found beforehand:
for row in rows:
link = row.a
if link is not None:
print(link.get_text())
Note that "row" and "rows" are probably not the best variable names since you are actually iterating over the "cells" - td elements.

Parsing html data into python list for manipulation

I am trying to read in html websites and extract their data. For example, I would like to read in the EPS (earnings per share) for the past 5 years of companies. Basically, I can read it in and can use either BeautifulSoup or html2text to create a huge text block. I then want to search the file -- I have been using re.search -- but can't seem to get it to work properly. Here is the line I am trying to access:
EPS (Basic)\n13.4620.6226.6930.1732.81\n\n
So I would like to create a list called EPS = [13.46, 20.62, 26.69, 30.17, 32.81].
Thanks for any help.
from stripogram import html2text
from urllib import urlopen
import re
from BeautifulSoup import BeautifulSoup
ticker_symbol = 'goog'
url = 'http://www.marketwatch.com/investing/stock/'
full_url = url + ticker_symbol + '/financials' #build url
text_soup = BeautifulSoup(urlopen(full_url).read()) #read in
text_parts = text_soup.findAll(text=True)
text = ''.join(text_parts)
eps = re.search("EPS\s+(\d+)", text)
if eps is not None:
print eps.group(1)

It's not a good practice to use regex for parsing html. Use BeautifulSoup parser: find the cell with rowTitle class and EPS (Basic) text in it, then iterate over next siblings with valueCell class:
from urllib import urlopen
from BeautifulSoup import BeautifulSoup
url = 'http://www.marketwatch.com/investing/stock/goog/financials'
text_soup = BeautifulSoup(urlopen(url).read()) #read in
titles = text_soup.findAll('td', {'class': 'rowTitle'})
for title in titles:
if 'EPS (Basic)' in title.text:
print [td.text for td in title.findNextSiblings(attrs={'class': 'valueCell'}) if td.text]
prints:
['13.46', '20.62', '26.69', '30.17', '32.81']
Hope that helps.

I would take a very different approach. We use LXML for scraping html pages
One of the reasons we switched was because BS was not being maintained for a while - or I should say updated.
In my test I ran the following
import requests
from lxml import html
from collections import OrderedDict
page_as_string = requests.get('http://www.marketwatch.com/investing/stock/goog/financials').content
tree = html.fromstring(page_as_string)
Now I looked at the page and I see the data is divided into two tables. Since you want EPS, I noted that it is in the second table. We could write some code to sort this out programmatically but I will leave that for you.
tables = [ e for e in tree.iter() if e.tag == 'table']
eps_table = tables[-1]
now I noticed that the first row has the column headings, so I want to separate all of the rows
table_rows = [ e for e in eps_table.iter() if e.tag == 'tr']
now lets get the column headings:
column_headings =[ e.text_content() for e in table_rows[0].iter() if e.tag == 'th']
Finally we can map the column headings to the row labels and cell values
my_results = []
for row in table_rows[1:]:
cell_content = [ e.text_content() for e in row.iter() if e.tag == 'td']
temp_dict = OrderedDict()
for numb, cell in enumerate(cell_content):
if numb == 0:
temp_dict['row_label'] = cell.strip()
else:
dict_key = column_headings[numb]
temp_dict[dict_key] = cell
my_results.append(temp_dict)
now to access the results
for row_dict in my_results:
if row_dict['row_label'] == 'EPS (Basic)':
for key in row_dict:
print key, ':', row_dict[key]
row_label : EPS (Basic)
2008 : 13.46
2009 : 20.62
2010 : 26.69
2011 : 30.17
2012 : 32.81
5-year trend :
Now there is still more to do, for example I did not test for squareness (number of cells in each row is equal).
Finally I am a novice and I suspect others will advise more direct methods of getting at these elements (xPath or cssselect) but this does work and it gets you everything from the table in a nice structured manner.
I should add that every row from the table is available, they are in the original row order. The first item (which is a dictionary) in the my_results list has the data from the first row, the second item has the data from the second row etc.
When I need a new build of lxml I visit a page maintained by a really nice guy at UC-IRVINE
I hope this helps

from bs4 import BeautifulSoup
import urllib2
import lxml
import pandas as pd
url = 'http://markets.ft.com/research/Markets/Tearsheets/Financials?s=CLLN:LSE&subview=BalanceSheet'
soup = BeautifulSoup(urllib2.urlopen(url).read())
table = soup.find('table', {'data-ajax-content' : 'true'})
data = []
for row in table.findAll('tr'):
cells = row.findAll('td')
cols = [ele.text.strip() for ele in cells]
data.append([ele for ele in cols if ele])
df = pd.DataFrame(data)
print df
dictframe = df.to_dict()
print dictframe
The above code will give you a DataFrame from the webpage and then uses that to create a python dictionary.