练习：微信好友分析
Posted Ryana
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来源：http://www.cnblogs.com/jiaoyu121/p/6944398.html
1.好友性别分布
import itchat itchat.login() #itchat.send(u\'你好\',\'filehelper\') friends = itchat.get_friends(update=True)[0:] #print len(friends) male = female = other = 0 for i in friends[1:]: sex = i[\'Sex\'] #1男性 2 女性 if sex == 1: male += 1 elif sex == 2: female +=1 else: other += 1 total = len(friends[1:]) #print u\'男性好友：\'+(float(male)/total)*100 print u\'男性好友：%.2f%%\'%(float(male)/total*100) print u\'女性好友：%.2f%%\'%(float(female)/total*100) print u\'其他：%.2f%%\'%(float(other)/total*100)
输出：
可视化
from echarts import Echart, Legend, Pie chart = Echart(u\'%s的微信好友性别比例\' % (friends[0][\'NickName\']), \'from WeChat\') chart.use(Pie(\'WeChat\', [{\'value\': male, \'name\': u\'男性 %.2f%%\' % (float(male) / total * 100)}, {\'value\': female, \'name\': u\'女性 %.2f%%\' % (float(female) / total * 100)}, {\'value\': other, \'name\': u\'其他 %.2f%%\' % (float(other) / total * 100)}], radius=["50%", "70%"])) chart.use(Legend(["male", "female", "other"])) del chart.json["xAxis"] #x轴y轴暂时没有隐藏 del chart.json["yAxis"] chart.plot()
输出
2.好友个性签名
tList = [] for i in friends: signature = i["Signature"].replace(" ", "").replace("span", "").replace("class", "").replace("emoji", "") rep = re.compile("1f\\d.+") signature = rep.sub("", signature) tList.append(signature) # 拼接字符串 text = "".join(tList) print text import jieba all_words = [] #用词列表 wordlist_jieba = jieba.cut(text, cut_all=True) all_words.extend(set(wordlist_jieba)) #set(data)去除重复的词 from collections import Counter count = Counter(all_words) #统计出现次数,以字典的键值对形式存储，元素作为key，其计数作为value。 result = sorted(count.items(), key=lambda x: x[1], reverse=True) #key=lambda x: x[1]在此表示用次数作为关键字 print type(result) #元组列表 #for word in result: # print word[0], word[1]
输出：
可视化
from pyecharts import WordCloud
data = dict(result)
wordcloud = WordCloud(\'微信好友个性签名词云\',width = 1200,height = 720)
wordcloud.add(\'test\',data.keys(),data.values(),word_size_range = [20,80]) wordcloud.render(r\'E:\\wordcloud.html\')
输出
3.自动回复
import time @itchat.msg_register(\'Text\') def text_reply(msg): # 当消息不是由自己发出的 if not msg[\'FromUserName\'] == myUserName: # 发送提示给文件助手 itchat.send_msg(u"[%s]收到好友@%s 的信息：%s\\n" % (time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(msg[\'CreateTime\'])), msg[\'User\'][\'NickName\'], msg[\'Text\']), \'filehelper\') # 回复给好友 return u\'[自动回复]您好，我现在有事不在，一会再和您联系。\\n已经收到您的的信息：%s\\n\' % (msg[\'Text\']) if __name__ == \'__main__\': itchat.auto_login() # 获取自己的UserName myUserName = itchat.get_friends(update=True)[0]["UserName"] itchat.run()
输出：
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