url = 'https://gist.githubusercontent.com/nzhukov/b66c831ea88b4e5c4a044c952fb3e1ae/raw/7935e52297e2e85933e41d1fd16ed529f1e689f5/A%2520Brief%2520History%2520of%2520the%2520Web.txt'

import requests

import nltk

nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')
nltk.download('universal_tagset')

text = requests.get(url).text
print('-' * 50)
print(text)
print('-' * 50)

tokenized_text = nltk.word_tokenize(text)
tagged_text = nltk.pos_tag(tokenized_text, tagset='universal')

print(tagged_text[:5])

top_five = dict()

for _p in tagged_text:
    if _p[1] not in top_five:
        top_five.update({_p[1]: 1})
    else:
        top_five[_p[1]] += 1

print(top_five)


result_lst = []
for _w in sorted(top_five, key=top_five.get, reverse=True):
    result_lst.append((_w, top_five[_w]))

VERB - verbs (all tenses and modes)

NOUN - nouns (common and proper)

PRON - pronouns

ADJ - adjectives

ADV - adverbs

ADP - adpositions (prepositions and postpositions)

CONJ - conjunctions

DET - determiners

NUM - cardinal numbers

PRT - particles or other function words

X - other: foreign words, typos, abbreviations

. - punctuation

print("1. ", result_lst[0]) # Существительные
print("2. ", result_lst[1]) # Глаголы
print("3. ", result_lst[2]) # Определители
print("4. ", result_lst[3]) # Предлоги и послелоги
print("5. ", result_lst[4]) # Знаки пунктуации
print("6. ", result_lst[5]) # Прилагательные
print("7. ", result_lst[6]) #  Наречия

1.  ('NOUN', 1076)
2.  ('VERB', 588)
3.  ('DET', 477)
4.  ('ADP', 476)
5.  ('.', 465)
6.  ('ADJ', 277)
7.  ('ADV', 181)