如何获取YouTube音乐排行榜并制作成可视化图表

Helium实现网页自动化，通过flourish制作的可视化动态图表链接地址https://public.flourish.studio/visualisation/3585290/

import datetime

#1.获取要爬取的url列表
URLbegin = 'https://charts.youtube.com/charts/TopSongs/global/'
URLend = '?hl=zh-cn'

start = datetime.date(2020,1,3)
current = datetime.date.today()

urllist = []
while start+datetime.timedelta(days=6)<=current:
    end = start+datetime.timedelta(days=6)
    url = URLbegin+start.__format__('%Y%m%d')+'-'+end.__format__('%Y%m%d')+URLend
    urllist.append(url)
    start = end+datetime.timedelta(days=1)  
# print(urllist)

#2.运用自动化工具爬取url列表
from helium import *
driver = start_chrome()
for url in urllist:
    go_to(str(url))
    click(Button('Download charts.'))

import os
import pandas as pd
import re

#3.运行bat文件修改所有文件后缀名
#4.拼接爬取url下载的列表文件
inputfile_dir='D:/GOOGLE DONMLOAD/'
outputfile='D:/GOOGLE DONMLOAD/alldata.csv'
for inputfile in os.listdir(inputfile_dir):
#     print(inputfile)
#     添加周排行日期列youtube-charts-top-songs-global-weekly-xxxx-xx-xx.txt
#     week_date=re.search('\\d{4}[-]\\d{2}[-]\\d{2}',inputfile)
#     print(re.search('\\d{4}[-]\\d{2}[-]\\d{2}',inputfile))
#     print(week_date)
    week_date=inputfile[-14:-4]
    data=pd.read_csv(inputfile_dir+inputfile)
#     print(data.columns)
    data['Week Date']=week_date
    print(data.columns)
    data=data.to_csv(outputfile,mode='a',index=False)
    
#5.去掉重复表头
newoutputfile='D:/GOOGLE DONMLOAD/alldata_new.csv'
# 通过df.drop_duplicates()去重对读入的表头只能去掉一个，作为表头的那一行不会进行匹配
pd.read_csv(outputfile,header=None).drop_duplicates().to_csv(newoutputfile,index=False,header=False)

import pandas as pd

def f(x):
    return (x.pivot_table(index = ['Track Name'], columns = ['Week Date'],values = ['Views']))
# 6.将表格内容处理成可视化需要的表格形式，最后通过flourish网站辅助生成可视化图表
parsedfile='D:/GOOGLE DONMLOAD/parseddata.csv'
pd.read_csv('D:/GOOGLE DONMLOAD/finaldataset.csv').groupby(['Track Name']).apply(f).to_csv(parsedfile)

本文地址：https://blog.csdn.net/qq_38920368/article/details/108269043