Our friends are from all corners of the country. We can use python's powerful database to realize the statistics of friends.

Tools: wxpy library, wordcloud library, matplotlib library, openpyxl library, pandas library, numpy library.

1, first realize the landing and acquisition of friend data operation.

  Code:

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#Introducing WeChat landing interface
from wxpy import *

#Obtaining logon two-dimensional code
bot = Bot(cache_path = True)

#Get basic data from WeChat friends
friend_all = bot.friends()

#Create a two-dimensional list to store basic friend information
lis = [['NickName','Sex','City','Province','Signature','HeadImgUrl','HeadImgFlag']]
#Save the feature data as a list
for a_friend in friend_all:
    NickName = a_friend.raw.get('NickName', None)
    Sex = {1:"male", 2:"female", 0:"Other"}.get(a_friend.raw.get('Sex', None), None)
    City = a_friend.raw.get('City', None)
    Province = a_friend.raw.get('Province', None)
    Signature = a_friend.raw.get('Signature', None)
    HeadImgUrl = a_friend.raw.get('HeadImgUrl', None)
    HeadImgFlag = a_friend.raw.get('HeadImgFlag', None)
    list_0 = [NickName, Sex, City, Province, Signature, HeadImgUrl, HeadImgFlag]
    lis.append(list_0)

  Operation results:

At this point, a two-dimensional code is popped up, and the data of friends can be acquired automatically by scanning the code and landing.

2. Save Friend Data as xlsx Files

 Convenient processing of world cloud Libraries

Code:

#Convert lists to xlsx tables
def list_to_xlsx(filename, list):
    
    import openpyxl
    wb = openpyxl.Workbook()
    sheet = wb.active
    sheet.title = 'Friends'
    file_name = filename + '.xlsx'
    for i in range(0, len(list)):
        for j in range(0, len(list[i])):
            sheet.cell(row = i+1, column = j+1, value = str(list[i][j]))
            
    wb.save(file_name)
    print("Read and write data successfully")

#Generate lists into tables
list_to_xlsx('wechat_friend', lis)

    Operation results:

Generated an xlsx file

3. Generative Word Cloud

  Generating a word cloud using the world cloud Library

Code:

from wordcloud import WordCloud
import matplotlib.pyplot as plt
import pandas as pd
from pandas import read_excel
import numpy as np

df = read_excel('wechat_friend.xlsx')

#Generating word clouds using WordCloud
word_list = df['City'].fillna('0').tolist()
new_text = ' '.join(word_list)
wordcloud = WordCloud(font_path='msyh.ttc', background_color = 'white').generate(new_text)
plt.imshow(wordcloud)
plt.axis("off")
plt.show()


#Using pyecharts to generate word clouds
from pyecharts import WordCloud

city_list = df['City'].fillna('').tolist()
count_city = pd.value_counts(city_list)
name = count_city.index.tolist()
value = count_city.tolist()

wordcloud = WordCloud(width=1300,height=620)
wordcloud.add("",name,value,word_size_range=[20,100])
#wordcloud.show_config()
#wordcloud.render(r'D:\wc.html')
wordcloud.render('wordcloud.html')


#Show your friends on the map 
from pyecharts import Map

province

  Operation results:

Two. Create a robot.
Tools: requests module, itchat module

Then we apply for api interface http://www.itpk.cn on Molly Robot.

Code:

#-*- coding:utf-8 -*-
import itchat
import requests

def get_response(msg):
    apiurl = 'http://i.itpk.cn/api.php'  //moli Robot's Web Site
    data={
        "question": msg,    //Get Text Information for Chat
        "api_key": "9ddf52cacd0ef429d1c63bf411b9bed6",
        "api_secret": "n4gxkdyckd7p"
    }
 
    r=requests.post(apiurl,data=data)  //Constructing network requests
    return r.text
@itchat.msg_register(itchat.content.TEXT)     //Dealing with Friends'News
def print_content(msg):
    return get_response(msg['Text'])
@itchat.msg_register([itchat.content.TEXT], isGroupChat=True)    //Group Message Processing
def print_content(msg):
    return get_response(msg['Text'])
itchat.auto_login(True)           //automatic logon
itchat.run()                       //Start a chat robot

Just run the login.