参考： B站_葩葩数据_2021年4月流量明星百度搜索指数动态排名.
小姐姐讲的非常好，希望多多关注、点赞。

流程

1.微博爬取排名前120的明星2.百度指数获取明星热度值3.flourish生成动态排行
明星排行数据来源： 微博-超话排行-明星.
明星热度数据来源： 百度指数.
动态排行生成工具： flourish Bar chart race.

1.微博爬取排名前120的明星

import requests import pandas as pd import numpy as np import time import re import json import demjson import datetime as dt from lxml import etree from selenium import webdriver # 获取namelist headers = { "Accept": "application/json, text/plain, */*", "Accept-Encoding": "gzip, deflate, br", "Accept-Language": "zh-CN,zh;q=0.9", "Cache-Control": "no-cache", "Connection": "keep-alive", "Cookie": "你的cookie", # 换成你的cookie "Host": "huati.weibo.cn", "Pragma": "no-cache", "Referer": "https://huati.weibo.cn/discovery/super", "sec-ch-ua-mobile": "?0", "Sec-Fetch-Dest": "empty", "Sec-Fetch-Mode": "cors", "user-agent":"你的user-agent", # 换成你的user-agent "X-Re-With": "XMLHttpRequest" } name_list = [] base_url = "https://huati.weibo.cn/aj/discovery/rank?cate_id=2&page={page}&topic_to_page=&block_time=0&star_type=star&from=&wm=&isvivo=false" for i in range(1,7): url = base_url.format(page=i) page_text = requests.get(url=url,headers=headers).text ex = '"display_name":"(.*?)","toprank"' page_name_list = re.findall(ex, page_text, re.S) for name in page_name_list: name_list.append(name) name_list # with open("name.txt","a+",encoding="utf-8") as fp: # fp.write()

运行结果：

2.百度指数获取明星热度值

headers = { "user-agent":"自己的user-agent", "cookie":'自己的cookie' } # 爬取百度指数每日值（需要解码，可一次爬取大量数据） def decrypt(ptbk, data): d = {} res = [] for i in range(len(ptbk)//2): d[ptbk[i]] = ptbk[len(ptbk)//2 + i] for x in data: res.append(d[x]) return "".join(res) def get_ptbk(uniqid): url = 'https://index.baidu.com/Interface/ptbk?uniqid={}'.format(uniqid) response = requests.get(url=url, headers=headers).text whh = demjson.encode(response, encoding='utf-8') h1 = json.loads(whh) h2 = json.loads(h1).get("data") return h2 def get_dailydata(keyword, start, end): url = f'https://index.baidu.com/api/SearchApi/index?area=0&word=[[%7B%22name%22:%22{keyword}%22,%22wordType%22:1%7D]]&startDate={start}&endDate={end}' res = requests.get(url, headers=headers) j = res.json() uniqid = j.get('data').get('uniqid') ptbk = get_ptbk(uniqid) data = j.get('data').get('userIndexes')[0].get('all').get('data') res = decrypt(ptbk, data) return res # 爬取多人的百度指数并制作成字典 def make_dict(name_list, sy, sm, sd, ey, em, ed): start = str(dt.date(sy, sm, sd)) end = str(dt.date(ey, em, ed)) data_dict = {} for name in name_list: print(name+" loading...") try: data_dict[name] = get_dailydata(name, start, end).split(',') except: break time.sleep(2) return data_dict data_d = make_dict(name_list, 2021,1,1,2021,5,4) start = dt.date(2021,1,1) end = dt.date(2021,5,5) # 注意：end要比抓取的end日期多一天 day_list = [] for i in range(start.toordinal(), end.toordinal()): day_list.append(str(dt.date.fromordinal(i))) df = pd.DataFrame(data_d, index=day_list) # 对空白数据进行填充 df.replace('','0',inplace=True) # 取当前日期和前两天的日期的平均值作为当天的热度值 df_rolling = df.rolling(window=3).mean().round(0) # 生成表格 根据flourish的需求需要将表格进行处理 df_rolling.transpose().to_excel("百度热度.xls")

3.flourish生成动态排行

将生成的表格导入flourish中，效果图如下图所示：