# Import WordNetLemmatizer

from nltk.stem import WordNetLemmatizer



# Retain alphabetic words: alpha_only

alpha_only = [t for t in lower_tokens if t.isalpha()]



# Remove all stop words: no_stops

no_stops = [t for t in alpha_only if t not in english_stops]



# Instantiate the WordNetLemmatizer

wordnet_lemmatizer = WordNetLemmatizer()


# Lemmatize all tokens into a new list: lemmatized

lemmatized = [wordnet_lemmatizer.lemmatize(t) for t in no_stops]



# Create the bag-of-words: bow

bow = Counter(lemmatized)



# Print the 10 most common tokens

print(bow.most_common(10))
