需要用到的第三方库：
numpy：本例结合wordcloud使用
jieba：对中文惊进行分词
PIL： 对图像进行处理（本例与wordcloud结合使用）
snowlp：对文本信息进行情感判断
wordcloud：生成词云 matplotlib：绘制2D图形
代码语言：javascript复制# -*- coding: utf-8 -*-
"""
朋友圈朋友签名的词云生成以及
签名情感分析
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"""
import re,jieba,itchat
import jieba.analyse
import numpy as np
from PIL import Image
from snownlp import SnowNLP
from wordcloud import WordCloud
import matplotlib.pyplot as plt
itchat.auto_login(hotReload=True)
friends = itchat.get_friends(update=True)
def analyseSignature(friends):
signatures = ''
emotions = []
for friend in friends:
signature = friend['Signature']
if(signature != None):
signature = signature.strip().replace('span', '').replace('class', '').replace('emoji', '')
signature = re.sub(r'1f(d. )','',signature)
if(len(signature)>0):
nlp = SnowNLP(signature)
emotions.append(nlp.sentiments)
signatures = ' '.join(jieba.analyse.extract_tags(signature,5))
with open('signatures.txt','wt',encoding='utf-8') as file:
file.write(signatures)
# 朋友圈朋友签名的词云相关属性设置
back_coloring = np.array(Image.open('alice_color.png'))
wordcloud = WordCloud(
font_path='simfang.ttf',
background_color="white",
max_words=1200,
mask=back_coloring,
max_font_size=75,
random_state=45,
width=1250,
height=1000,
margin=15
)
#生成朋友圈朋友签名的词云
wordcloud.generate(signatures)
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
wordcloud.to_file('signatures.jpg')#保存到本地文件
# Signature Emotional Judgment
count_good = len(list(filter(lambda x:x>0.66,emotions)))#正面积极
count_normal = len(list(filter(lambda x:x>=0.33 and x<=0.66,emotions)))#中性
count_bad = len(list(filter(lambda x:x<0.33,emotions)))#负面消极
labels = [u'负面消极',u'中性',u'正面积极']
values = (count_bad,count_normal,count_good)
plt.rcParams['font.sans-serif'] = ['simHei']
plt.rcParams['axes.unicode_minus'] = False
plt.xlabel(u'情感判断')#x轴
plt.ylabel(u'频数')#y轴
plt.xticks(range(3),labels)
plt.legend(loc='upper right',)
plt.bar(range(3), values, color = 'rgb')
plt.title(u'%s的微信好友签名信息情感分析' % friends[0]['NickName'])
plt.show()
analyseSignature(friends)效果图
