python 一键登录微信分析好友性别 地址 生成结果

# -*- coding:utf- -*-

"""
author：Mr Yang
data：//
"""

import itchat
import matplotlib.pyplot as plt
import matplotlib
import os
import re
import numpy as np
from PIL import Image
from wordcloud.wordcloud import WordCloud

class WeiXinAnalyze():
    def __init__(self):
        self.sex_dict = {}
        self.city_dict = {}
        self.self_nickname = ''
        self.wordList = []
        self.save_path = 'result'

    def wx_login(self):
        """微信登录及数据统计方法"""
        itchat.login()
        data = itchat.get_friends(update=True)
        self.self_nickname = data[]['NickName']  # 获取此微信昵称
        for item in data:
            sex = item.get('Sex')            # 性别
            province = item.get('Province')  # 省份
            city = item.get('City')          # 城市
            if sex or sex == :
                if sex not in self.sex_dict:
                    self.sex_dict[sex] =
                else:
                    self.sex_dict[sex] +=
            if province and city:
                address = '-'.join([province, city])
                if address not in self.city_dict:
                    self.city_dict[address] =
                else:
                    self.city_dict[address] += 

            if item["Signature"]:
                signature = re.sub(r'<span.*</span>', '', item["Signature"]).strip().replace('\n', '')
                self.wordList.append(signature)
        if not os.path.exists(self.save_path):
            os.mkdir(self.save_path)

    def get_sex_info(self):
        """分析性别方法"""
        sex_dict = {}
        sex_dict['男'], sex_dict['女'], sex_dict['其它'] = self.sex_dict.pop(), self.sex_dict.pop(), self.sex_dict.pop()
        # 数据准备
        data = sex_dict.items()
        labels = [i[] for i in data]
        nums = [i[] for i in data]
        # 使用Matplotlib画出饼图
        matplotlib.rcParams['font.sans-serif'] = ['SimHei']  # 使用指定的汉字字体类型（此处为黑体）
        plt.title('微信好友性别统计({})'.format(self.self_nickname))
        plt.pie(x=nums, labels=labels, autopct='%1.2f%%')
        plt.savefig(os.path.join(self.save_path,'wx_sex_data.png'))

    def get_address_info(self):
        """分析地址方法"""
        data = self.city_dict.items()
        sort_data = sorted(data, key=lambda i: i[], reverse=True)[:]
        x = [i[] for i in sort_data]
        y = [i[] for i in sort_data]
        matplotlib.rcParams['font.sans-serif'] = ['SimHei']
        fig, ax = plt.subplots()
        rects = ax.barh(x, y, color='greenyellow', align="center")
        ax.set_yticks(x)           # 设置标度的位置
        ax.set_yticklabels(x)      # 设置纵坐标的每一个刻度的属性值
        ax.invert_yaxis()          # 反转标度值
        ax.set_xlabel('人数(位)')  # 设置横坐标的单位
        ax.set_title('微信好友所在城市统计({})'.format(self.self_nickname))  # 设定图片的标题
        for rect, y, num in zip(rects, x, y):
            x = rect.get_width()
            plt.text(x + 0.05, y, "%d" % int(num))
        plt.savefig(os.path.join(self.save_path,'wx_address_data.png'))

    def wx_ciyun(self):
        """微信词云方法"""
        text = " ".join(self.wordList)
        # 获取当前文件的执行路径
        src_dir = os.getcwd()
        # 生成词云形状的图片地址
        imagePath = os.path.join(src_dir , "timg.jpg")
        # 生成词云字体地址（防止中文乱码）
        font = os.path.join(src_dir ,"SimHei.ttf")
        # 生成的词云图地址
        resultPath = os.path.join(self.save_path,'wx_ciyun.png')
        # 开始生成图片
        bg = np.array(Image.open(imagePath))
        wc = WordCloud(
            mode='RGBA',       # 设置透明底色
            mask=bg,           # 造型遮盖
            background_color="white",  # 背景颜色
            max_font_size=,  # 字体最大值
            min_font_size=,  # 字体最小值
            max_words=,    # 词云显示的最大词数
            random_state=,  # 设置有多少种随机生成状态，即有多少种配色方案
            font_path=font,    # 设置字体

        ).generate(text)
        wc.to_file(resultPath)

if __name__ == '__main__':
    weixin = WeiXinAnalyze()
    weixin.wx_login()
    weixin.get_sex_info()
    weixin.get_address_info()
    weixin.wx_ciyun()

最后看结果：

好累，第一次接触数据分析。