input: Write a function to read in a tweet and remove all punctuation, special characters, and stopwords. Return the filtered list of words.
  import re
  import string
  from nltk.corpus import stopwords
  
  def clean_tweet(tweet):
      tweet_clean = re.sub(r'[^\w\s]','',tweet) #remove punctuation
      tokens = tweet_clean.split() #split string into individual words 
      stop_words = set(stopwords.words("english")) #get list of stopwords
      filtered_tokens = [w for w in tokens if not w in stop_words] #remove stopwords
      return filtered_tokens
  
  assert clean_tweet("I'm so excited to be going to the #MuseumTour! #BigDay #travel")==['excited', 'going', 'MuseumTour', 'BigDay', 'travel']
  assert clean_tweet("Hello, world! This is a test.")==['Hello', 'world', 'test']
  assert clean_tweet("")==[]
  assert clean_tweet("Just another test tweet with numbers 123 and symbols @#$.")==['Just', 'another', 'test', 'tweet', 'numbers', '123', 'symbols']
output: def clean_tweet(tweet):
      tweet_clean = re.sub(r'[^\w\s]','',tweet)
      tokens = tweet_clean.split()
      stop_words = set(stopwords.words("english"))
      filtered_tokens = [w for w in tokens if not w in stop_words]
      return filtered_tokens