python微信好友数据分析详解

基于微信开放的个人号接口python库itchat，实现对微信好友的获取，并对省份、性别、微信签名做数据分析。

效果：

直接上代码，建三个空文本文件stopwords.txt，newdit.txt、unionwords.txt，下载字体simhei.ttf或删除字体要求的代码，就可以直接运行。

 #wxfriends.py 2018-07-09
import itchat
import sys
import pandas as pd
import matplotlib.pyplot as plt
plt.rcparams['font.sans-serif']=['simhei']#绘图时可以显示中文
plt.rcparams['axes.unicode_minus']=false#绘图时可以显示中文
import jieba
import jieba.posseg as pseg
from scipy.misc import imread
from wordcloud import wordcloud
from os import path
#解决编码问题
non_bmp_map = dict.fromkeys(range(0x10000, sys.maxunicode + 1), 0xfffd)
 
 
#获取好友信息
def getfriends():
  friends = itchat.get_friends(update=true)[0:]
  flists = []
  for i in friends:
    fdict={}
    fdict['nickname']=i['nickname'].translate(non_bmp_map)
    if i['sex'] == 1:
      fdict['sex']='男'
    elif i['sex'] == 2:
      fdict['sex']='女'
    else:
      fdict['sex']='雌雄同体'
    if i['province'] == '':
      fdict['province'] ='未知'
    else:
      fdict['province']=i['province']
    fdict['city']=i['city']
    fdict['signature']=i['signature']
    flists.append(fdict)
  return flists
 
 
#将好友信息保存成csv
def savecsv(lists):
  df = pd.dataframe(lists)
  try:
    df.to_csv("wxfriends.csv",index = true,encoding='gb18030')
  except exception as ret:
    print(ret)
  return df
 
 
#统计性别、省份字段  
def anysys(df):
  df_sex = pd.dataframe(df['sex'].value_counts())
  df_province = pd.dataframe(df['province'].value_counts()[:15])
  df_signature = pd.dataframe(df['signature'])
  return df_sex,df_province,df_signature
 
 
#绘制柱状图，并保存  
def draw_chart(df_list,x_feature):
  try:
    x = list(df_list.index)
    ylist = df_list.values
    y = []
    for i in ylist :
      for j in i:
        y.append(j)
    plt.bar(x,y,label=x_feature)
    plt.legend()
    plt.savefig(x_feature)
    plt.close()
  except:
    print("绘图失败")
 
 
#解析取个性签名构成列表   
def getsignlist(signature):
  sig_list = []
  for i in signature.values:
    for j in i:
      sig_list.append(j.translate(non_bmp_map))
  return sig_list
 
 
#分词处理，并根据需要填写停用词、自定义词、合并词替换
def segmentwords(txtlist):
  stop_words = set(line.strip() for line in open('stopwords.txt', encoding='utf-8'))
  newslist = []
  #新增自定义词
  jieba.load_userdict("newdit.txt")
  for subject in txtlist:
    if subject.isspace():
      continue
    word_list = pseg.cut(subject)
    
    for word, flag in word_list:
      if not word in stop_words and flag == 'n' or flag == 'eng' and word !='span' and word !='class':
        newslist.append(word)
   #合并指定的相似词
  for line in open('unionwords.txt', encoding='utf-8'):
    newline = line.encode('utf-8').decode('utf-8-sig')  #解决\ufeff问题
    unionlist = newline.split("*")
    for j in range(1,len(unionlist)):
      #worddict[unionlist[0]] += worddict.pop(unionlist[j],0)
      for index,value in enumerate(newslist):
        if value == unionlist[j]:
          newslist[index] = unionlist[0] 
  return newslist
 
 
#高频词统计
def countwords(newslist):
  worddict = {}
  for item in newslist:
    worddict[item] = worddict.get(item,0) + 1
  itemlist = list(worddict.items())
  itemlist.sort(key=lambda x:x[1],reverse=true)    
  for i in range(100):
    word, count = itemlist[i]
    print("{}:{}".format(word,count))
 
 
#绘制词云
def drawplant(newslist):
  d = path.dirname(__file__)
  mask_image = imread(path.join(d, "timg.png"))
  content = ' '.join(newslist)
  wordcloud = wordcloud(font_path='simhei.ttf', background_color="white",width=1300,height=620, max_words=200).generate(content)  #mask=mask_image,
  # display the generated image:
  plt.imshow(wordcloud)
  plt.axis("off")
  wordcloud.to_file('wordcloud.jpg')
  plt.show()
 
 
def main():
  #登陆微信
  itchat.auto_login()  # 登陆后不需要扫码  hotreload=true
  flists = getfriends()
  fdf = savecsv(flists)
  df_sex,df_province,df_signature = anysys(fdf)
  draw_chart(df_sex,"性别")
  draw_chart(df_province,"省份")
  wordlist = segmentwords(getsignlist(df_signature))
  countwords(wordlist)
  drawplant(wordlist)
  
main()

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持。