微信好友城市分布分析

2018-02-08

字数统计: 859字 | 阅读时长≈ 4分

缘由

在朋友圈看到一个分享-matplotlib[05]——微信好友的全国分布的热图

回想起之前也做过微信好友分析；有道云地址。

但没有加上地图，这次刚好加上吧。

思路

微信好友分析；
3D.js 地图展示（这次不做，因为发现了pyecharts）
pyecharts展示城市分布图

过程

itchat爬取好友数据，存储到本地json文件；读取，并用pyecharts展示出来。

话不多说，Talk is cheap, show me the code.

代码

1.首先抓取好友信息，存入json文件，以备后面分析

# -*- coding: utf-8 -*-

import json
import itchat

# 登陆网页版微信, 需要扫描弹出的二维码, 不过新注册微信被封了
itchat.login()
# 爬取好友信息,json字符串
friends = itchat.get_friends(update=True)[0:]
# print(friends) # 测试是否正常输出好友

# 将friends写入文件，以后就不用每次调试都要登陆网页版了
file = open("/Users/yourUserName/.../weChatFriendArealDistribution.json", 'w',
            encoding='utf-8')
json.dump(friends, file, ensure_ascii=False)
file.close()

2.读取文件，并分析好友城市分布，绘制图形

# -*- encoding:utf-8 -*-
# ! python3

import json
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
import matplotlib
from collections import Counter
from pyecharts import Geo

# 读取json 文件
openfile = open('/Users/linking/PycharmProjects/weChatCraw/output/weChatFriendArealDistribution.json', 'r',
                encoding='utf-8')
loadFriends = json.load(openfile)


# 定义一个函数，用来爬取各个变量, return list arr
def get_var(var):
    variable = []
    for i in loadFriends:
        value = i[var]
        variable.append(value)
    return variable


Province = get_var('Province')
City = get_var('City')

# provinceCount = Counter(Province)
cityCount = Counter(City)

# print(provinceCount)
# print(list(provinceCount.elements()))
# print(sorted(provinceCount.elements()))
# print(list(provinceCount.values()))
# print(sum(provinceCount.values()))  # 381
# print(len(Province)) # 381
# print(len(provinceCount)) # 37

# for key in provinceCount.elements():
#     print(key, provinceCount[key])

totalCount = len(cityCount)
pName = []
pNum = []
pPercent = []

for each in cityCount.items():
    # (a, b) = each
    # print(a, b)
    pName.append(each[0])
    pNum.append(each[1])
    pPercent.append(each[1] / totalCount)

# print(pName)
# print(pNum)

# print(matplotlib.matplotlib_fname())
# /usr/local/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc

# from matplotlib.font_manager import _rebuild
#
# _rebuild()

plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号

# font = FontProperties(fname='/Library/Fonts/Songti.ttc') # 该方法未验证

# 1.柱状图
# plt.bar(range(len(pNum)), pNum, tick_label=pName)
# plt.show()


# 2.饼状图
# labels = pName
# fracs = pPercent
# explode = [0, 0.1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
#            0]  # 0.1 凸出这部分，共len(provinceCount)=37个
# plt.axes(aspect=1)  # set this , Figure is round, otherwise it is an ellipse
# # autopct ，show percet
# plt.pie(x=fracs, labels=labels, explode=explode, autopct='%3.1f %%',
#         shadow=False, labeldistance=1.1, startangle=90, pctdistance=0.6)
# plt.show()

# 3.地图
value = pNum
attr = pName
geo = Geo("我的好友分布图", width=1200, height=600)
geo.add("各城市分布情况", attr, value, type="effectScatter", border_color="#ffffff", symbol_size=20, \
        is_label_show=True, label_text_color="#00FF00", label_pos="inside", symbol="circle", \
        symbol_color="FF0000", geo_normal_color="#006edd", geo_emphasis_color="#0000ff")
geo.show_config()
# geo.render("friendProvinceDistribution.html")
geo.render("friendCityDistribution.html")