仿照hamlet.txt的方式，按照分词方式（jieba分词）对threeking.doms.txt进行词频统计，并输出词频最高的20个词及词频

img

如图所示，程序内提取附件是with open（'threekingdoms.txt'，'r'，encoding＝'utf-8'）as f :
print（f.read（））

说明：代码是使用我自己的数据进行实现的，使用时要把你数据文件的路径传给变量dic_path
请采纳，谢谢！
（1）
代码如下：

import jieba

dic_path = './10.txt' # 文件的路径
with open(dic_path, 'r', encoding='utf8') as f:
    txt = f.read()
print(txt)

words=jieba.lcut(txt)
counts={}

for word in words:
    if len(word) == 1: #排除单个字符的分词结果
        continue
    else:
        counts[word] = counts.get(word,0) + 1  # 统计词频
        items = list(counts.items())
        
items.sort(key=lambda x:x[1], reverse=True) # 按词频进行降序
for i in range(20):  # 打印词频前20 的词
    word, count=items[i]
    print("{0:<10}{1:>5}".format(word, count))

结果：

img

（2）代码如下：

import jieba

dic_path = './10.txt'
with open(dic_path, 'r', encoding='utf8') as f:
    txt = f.read()
print(txt)

words=jieba.lcut(txt)
counts={}

# fu和text分别存储标点符号和转义字符，若统计词频出现时可以在这里添加来洗去
fu = '[·’!"\#$%&\'()＃！（）*+,-./:;<=>?%％^@！\@，：?￥★、—_…．＞【】［］《》？“”‘’\[\\]^_`{|}~]+。'
text = ['\u3000','\n']

for word in words:
    if len(word) != 1: #排除单个字符的分词结果
        continue
    elif word in fu:  # 去除标点符号
        continue
    elif word in text:  # 去转义字符
        continue
    else:
        counts[word] = counts.get(word,0) + 1  # 统计词频
        items = list(counts.items())
        
items.sort(key=lambda x:x[1], reverse=True) # 按词频进行降序
# print(items)
for i in range(20):
    word, count=items[i]
    print("{0:<10}{1:>5}".format(word, count))

结果如下：

img

（3）代码如下：

import jieba

dic_path = './10.txt'
with open(dic_path, 'r', encoding='utf8') as f:
    txt = f.read()
print(txt)

words=jieba.lcut(txt)
counts={}

for word in words:
    if len(word) != 2: #排除单个字符的分词结果
        continue
    else:
        counts[word] = counts.get(word,0) + 1  # 统计词频
        items = list(counts.items())
        
items.sort(key=lambda x:x[1], reverse=True) # 按词频进行降序
for i in range(20):
    word, count=items[i]
    print("{0:<10}{1:>5}".format(word, count))

结果：

img