Example of parsing a table using BeautifulSoup and requests in Python

gistfile1.py

import requests
from bs4 import BeautifulSoup

# We've now imported the two packages that will do the heavy lifting
# for us, reqeusts and BeautifulSoup

# Let's put the URL of the page we want to scrape in a variable
# so that our code down below can be a little cleaner
url_to_scrape = 'http://apps2.polkcountyiowa.gov/inmatesontheweb/'

# Tell requests to retreive the contents our page (it'll be grabbing
# what you see when you use the View Source feature in your browser)
r = requests.get(url_to_scrape)

# We now have the source of the page, let's ask BeaultifulSoup
# to parse it for us.
soup = BeautifulSoup(r.text)

# Down below we'll add our inmates to this list
inmates_list = []

# BeautifulSoup provides nice ways to access the data in the parsed
# page. Here, we'll use the select method and pass it a CSS style
# selector to grab all the rows in the table (the rows contain the 
# inmate names and ages).

for table_row in soup.select("table.inmatesList tr"):
	# Each tr (table row) has three td HTML elements (most people 
	# call these table cels) in it (first name, last name, and age)
	cells = table_row.findAll('td')

	# Our table has one exception -- a row without any cells.
	# Let's handle that special case here by making sure we
	# have more than zero cells before processing the cells
	if len(cells) > 0:
		# Our first name seems to appear in the second td element
		# that ends up being the cell called 1, since we start
		# counting at 0
		first_name = cells[1].text.strip()
		# Our last name is in the first (0 if we start counting 
		# at 0 like we do in Python td element we encounter
		last_name = cells[0].text.strip()
		# Age seems to be in the last td in our row
		age = cells[2].text.strip()

		# Let's add our inmate to our list in case
		# We do this by adding the values we want to a dictionary, and 
		# appending that dictionary to the list we created above
		inmate = {'first_name': first_name, 'last_name': last_name, 'age': age}
		inmates_list.append(inmate)

		# Let's print our table out.
		print "Added {0} {1}, {2}, to the list".format(first_name, last_name, age)

# What if we want to do more than just print out all the names and
# ages? Maybe we want to filter things a bit. Say, only we want to 
# only print out the inmates with an age between 20 and 30.

# Let's keep track of the number of inmates in the 20s.
inmates_in_20s_count = 0

# Loop through the list of inmates we built
for inmate in inmates_list:
		# The age we originally received from BeautifulSoup is a 
		# string. We need it to be a number so that we can compare
		# it easily. Let's make it an integer.
		age = int(inmate['age'])

		if age > 19 and age < 31:
			# Let's print our table out.
			print "{0} {1}, {2} is in the 20 to 30 age range".format(inmate['first_name'], inmate['last_name'], age)

			# Add one to our inmates in their 20s count
			inmates_in_20s_count = inmates_in_20s_count + 1

# How many inmates did we find in the page? Use the len funciton to find out.
print "Found {0} in the page".format(len(inmates_list))
print "Found {0} between age 20 and 30 in the page".format(inmates_in_20s_count)

Other implementation with support colspan and rowspan (merged cells) : https://github.com/4sushi/htmlParse