Python 微信好友分析 Python源码

# pip install itchat import itchat # pip install pandas import pandas as pd # 以下为pyecharts安装方法 """ pip install echarts-countries-pypkg pip install echarts-china-provinces-pypkg pip install echarts-china-cities-pypkg pip install pyecharts==0.5.11 pip install pyecharts_snapshot """ from pyecharts import Pie, Map, Style, Page, Bar # 根据key值得到对应的信息 def get_key_info(friends_info, key): return list(map(lambda friend_info: friend_info.get(key), friends_info)) # 获得微信好友信息 def get_friends_info(): itchat.auto_login(hotReload=True) friends = itchat.get_friends() friends_info = dict( # 省份 province=get_key_info(friends, "Province"), # 城市 city=get_key_info(friends, "City"), # 昵称 nickname=get_key_info(friends, "Nickname"), # 性别 sex=get_key_info(friends, "Sex"), # 签名 signature=get_key_info(friends, "Signature"), # 备注 remarkname=get_key_info(friends, "RemarkName"), # 用户名拼音全拼 pyquanpin=get_key_info(friends, "PYQuanPin") ) return friends_info # 性别分析 def analysis_sex(): friends_info = get_friends_info() df = pd.DataFrame(friends_info) sex_count = df.groupby(['sex'], as_index=True)['sex'].count() temp = dict(zip(list(sex_count.index), list(sex_count))) data = {} data['保密'] = temp.pop(0) data['男'] = temp.pop(1) data['女'] = temp.pop(2) # 画图 page = Page() attr, value = data.keys(), data.values() chart = Pie('微信好友性别比') chart.add('', attr, value, center=[50, 50], redius=[30, 70], is_label_show=True, legend_orient='horizontal', legend_pos='center', legend_top='bottom', is_area_show=True) page.add(chart) page.render('analysisSex.html') # 全国省份分析 def analysis_province(): friends_info = get_friends_info() df = pd.DataFrame(friends_info) province_count = df.groupby('province', as_index=True)['province'].count().sort_values() temp = list(map(lambda x: x if x != '' else '未知', list(province_count.index))) # 画图 page = Page() style = Style(width=1100, height=600) style_middle = Style(width=900, height=500) attr, value = temp, list(province_count) chart1 = Map('好友分布(中国地图)', **style.init_style) chart1.add('', attr, value, is_label_show=True, is_visualmap=True, visual_text_color='#000') page.add(chart1) chart2 = Bar('好友分布柱状图', **style_middle.init_style) chart2.add('', attr, value, is_stack=True, is_convert=True, label_pos='inside', is_legend_show=True, is_label_show=True) page.add(chart2) page.render('analysisProvince.html') # 精确省份分析 def analysis_city(province): friends_info = get_friends_info() df = pd.DataFrame(friends_info) temp1 = df.query('province == "%s"' % province) city_count = temp1.groupby('city', as_index=True)['city'].count().sort_values() attr = list(map(lambda x: '%s市' % x if x != '' else '未知', list(city_count.index))) value = list(city_count) # 画图 page = Page() style = Style(width=1100, height=600) style_middle = Style(width=900, height=500) chart1 = Map('%s好友分布' % province, **style.init_style) chart1.add('', attr, value, maptype='%s' % province, is_label_show=True, is_visualmap=True, visual_text_color='#000') page.add(chart1) chart2 = Bar('%s好友分布柱状图' % province, **style_middle.init_style) chart2.add('', attr, value, is_stack=True, is_convert=True, label_pos='inside', is_label_show=True) page.add(chart2) page.render('analysisCity.html') if __name__ == '__main__': analysis_sex() analysis_province() # 填入省份名称，例“江苏”，并且不可与市名称相同，例“吉林” analysis_city("浙江")