Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

Chapter 1
Introduction
def parseSoupTable(self, table):
#print "parsing table"
images = table.findAll("img")
over_all = str(images[0]).split("grn_bar_")[1].
split(".gif")[0]
money_value = str(images[1]).split("SCORE_")[1].
split(".gif")[0]
seat_comfort = str(images[2]).split("SCORE_")[1].
split(".gif")[0]
staff_service = str(images[3]).split("SCORE_")[1].
split(".gif")[0]
catering = str(images[4]).split("SCORE_")[1].
split(".gif")[0]
entertainment = str(images[4]).split("SCORE_")[1].
split(".gif")[0]
if 'YES' in str(images[6]):
recommend = 'YES'
else:
recommend = 'NO'
status = table.findAll("p", {"class":"text25"})
stat = str(status[2]).split(">")[1].split("<")[0]
return (stat, over_all, money_value, seat_comfort,
staff_service, catering, entertainment, recomend)
def collectThoughts(self):
#print "Collecting Thoughts"
for al in AirLineReviewCollector.airlines:
count = 0
while count < AirLineReviewCollector.limit:
count = count + 1
url = ''
7