【python】利用jieba中文分詞進行詞頻統計及生成詞雲

以下代碼對魯迅的《祝福》進行了詞頻統計:

import io
import jieba
txt = io.open("zhufu.txt", "r", encoding='utf-8').read()
words  = jieba.lcut(txt)
counts = {}
for word in words:
    if len(word) == 1:
        continue
    else:
        counts[word] = counts.get(word,0) + 1
items = list(counts.items())
items.sort(key=lambda x:x[1], reverse=True) 
for i in range(15):
    word, count = items[i]
    print (u"{0:<10}{1:>5}".format(word, count))

結果如下：

並把它生成詞雲

from wordcloud import WordCloud
import PIL.Image as image
import numpy as np
import jieba
 
# 分詞
def trans_CN(text):
    # 接收分詞的字符串
    word_list = jieba.cut(text)
    # 分詞后在單獨個體之間加上空格
    result = " ".join(word_list)
    return result
 
with open("zhufu.txt") as fp:
    text = fp.read()
    # print(text)
    # 將讀取的中文文檔進行分詞
    text = trans_CN(text)
    mask = np.array(image.open("xinxing.jpg"))
    wordcloud = WordCloud(
        # 添加遮罩層
        mask=mask,
        font_path = "msyh.ttc"
    ).generate(text)
    image_produce = wordcloud.to_image()
    image_produce.show()

效果如下：