Python project

import nltk import string setPunc = set(string.punctuation) setPunc.remove('#') setPunc.remove("'") def process_hashes(tweet): tweet = tweet.upper() tweet = ''.join(ch for ch in tweet if ch not in setPunc) hashes = [] for word in tweet.split(): if word[0] == '#': if word[-2:] == "'S": word = word[:-2] hashes.append(word[1:]) return hashes #Correct the next function #The comments tell you what the code SHOULD be doing #In many cases it is not doing that #Do not add or delete lines def popular_tweets(filename, how = 'retweet', cutoff = 100, counts = False): info = {'reply':2,'retweet': 3,'favorite': 4} #map columns in data to what they represent result = {} #store results in a dictionary with open(filename, 'r') as file: #open file for line in file: #read through file line by line #print(line) #you may find this debugging print line helpful - use with SMALL file data = line.split('\t') #separate data by column for this line #print(data) #you may find this debugging print line helpful - use with SMALL file if int(data[info[how]]) >= cutoff: #check if we've met the cutoff #print(data[info[how]]) #you may find this debugging print line helpful - use with SMALL file if data[5] in result: #check if username already in dictionary result[data[5]].append(data[1]) #add to the existing tweets for that user else: result[data[5]] = [data[1]] #create new list of tweets for that user if counts: #If we want counts for each user in dictionary for item in result: #for each user, figure out how many tweets they have and store in dictionary result[item] = len(result[item]) return result def graph_usage(tweets, cutoff= 10): hashes = [] for tweet in tweets: h = process_hashes(tweet) for hash in h: hashes.append(hash) fd = nltk.FreqDist(hashes) fd.plot(cutoff,cumulative=False) #The function below is correct #Do not change it in any way #Input is a dictionary with lists of strings as values #Output is a list of strings that is ALL of the strings from ALL of the values in the dictionary, see .pdf for example def join_tweets(info): result = [] for v in info.values(): result.extend(v) return result #Extra credit only - do not delete the def lines if you don't do these, just leave them as they are def process_hashes_regex(tweet): pass def join_tweets_lc(info): pass