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) + "] ...")