classifier = Classifier()
analyser = IndicoSentimentAnalyser()
locations = Locations()
with open(temp_file, 'rb') as fp:
reader = csv.reader(fp)
with open(chinese_file, 'wb') as op:
writer = csv.writer(op)
writer.writerow(['Date', 'Location', 'Country', 'Text', 'Sentiment'])
for row in reader:
tweet_text = row[12]
location = row[3]
date = row[7]
country = locations.get_country(location=location)
try:
if any(word in tweet_text.lower().split() for word in chinese_cuisine):
"""
small code to cover up for last failure
"""
count += 1
# diff_count += 1
# if diff_count < 8234:
# continue
# sentiment = classifier.get_sentiment(tweet_text)
sentiment = analyser.analyse_sentiment(text=tweet_text)
writer.writerow([date, location, country, tweet_text, sentiment])
print("Done.. " + str(count))
indian_file = "F:\\SOIC Courses\\Big Data\\Final Project\\Cuisine-Dataset\\locations\\indian_with_date.csv"
italian_file = "F:\\SOIC Courses\\Big Data\\Final Project\\Cuisine-Dataset\\locations\\italian_with_date.csv"
mideast_file = "F:\\SOIC Courses\\Big Data\\Final Project\\Cuisine-Dataset\\locations\\mideast_with_date.csv"
out_file = "F:\\SOIC Courses\\Big Data\\Final Project\\Cuisine-Dataset\\locations\\final\\italy\\italian_cuisine_final.csv"
location = Locations()
with open(italian_file, 'rb') as fp:
reader = csv.reader(fp)
with open(out_file, 'wb') as op:
writer = csv.writer(op)
writer.writerow(['Date', 'Location', 'Country', 'Text', 'Sentiment'])
count = 0
for row in reader:
if count == 0:
count += 1
continue
loc = row[1]
country = location.get_country(loc)
final = [row[0], loc, country, row[2], row[3]]
writer.writerow(final)
count += 1
print("Done [" + str(count) + "] ...")
