from knock30 import load_morpheme
from collections import defaultdict
from knock36 import calc_word_frequency
from matplotlib import pyplot as plt
path = 'neko.txt.mecab'
result = load_morpheme(path)
words_freq = calc_word_frequency(result)
dic = sorted(words_freq.items(), key = lambda x:x[1], reverse = True)
words = [dic[i][0] for i in range(10)]
counts = [dic[i][1] for i in range(10)]
plt.rcParams['font.family'] = 'AppleGothic'
plt.xlabel('出現頻度が高い10語')
plt.ylabel('出現頻度')
plt.bar(words,counts)
plt.show()
# 35. 名詞の連接
# 名詞の連接（連続して出現する名詞）を最長一致で抽出せよ．
from knock30 import load_morpheme
from typing import List, Dict
M = List[Dict[str, str]]
T = List[M]
def get_consecutive_nouns(morphemes: T) -> List[str]:
consecutive_nouns = [] # type: List[str]
for sentence in morphemes:
nouns = []
for morpheme in sentence:
if morpheme["pos"] == "名詞":
nouns.append(morpheme["surface"])
else:
if len(nouns) > 1:
consecutive_nouns.append("".join(nouns))
nouns = []
return consecutive_nouns
if __name__ == "__main__":
for noun in get_consecutive_nouns(load_morpheme()):
print(noun)
