Python project

Prj3_Files/Project_3.py

import nltk def process_hashes(tweet): pass #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':3,'retweet': 4,'favorite': 5} #map columns in data to what they represent result = {} #store results in a dictionary with open('sen_tweets_edited_2.csv', '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() #separate data by column for this line #print(data) #you may find this debugging print line helpful - use with SMALL file if data[how] == cutoff: #check if we've met the cutoff #print(data[how]) #you may find this debugging print line helpful - use with SMALL file if (data[how]) in result: #check if username already in dictionary result[(data[how])] = data[2] #add to the existing tweets for that user else: result[(data[how])] += data[2] #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(data) return result def graph_usage(tweets, cutoff= 10): pass #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