├── LICENSE.txt ├── Python数据分析初探结课项目 └── NeteaseCloudMusicDataAnalysis │ ├── __pycache__ │ ├── label_ea_song.cpython-39.pyc │ ├── music_detail.cpython-39.pyc │ ├── music_index.cpython-39.pyc │ ├── music_wordcloud.cpython-39.pyc │ ├── top_10_ea_song_collection_distribution.cpython-39.pyc │ ├── top_10_ea_song_playlists.cpython-39.pyc │ ├── top_10_ea_song_playlists_distribution.cpython-39.pyc │ ├── top_10_of_ea_song_collection.cpython-39.pyc │ ├── top_10_of_ea_song_comment.cpython-39.pyc │ ├── top_10_song.cpython-39.pyc │ └── top_10_song_up.cpython-39.pyc │ ├── font_resources │ └── STZHONGS.ttf │ ├── label_ea_song.py │ ├── music_data │ ├── music_detail.csv │ ├── music_list.csv │ └── music_name.csv │ ├── music_detail.py │ ├── music_image │ ├── background_image.jpg │ ├── label_ea_song.png │ ├── music_wordcloud.png │ ├── top_10_ea_song_playlists.png │ ├── top_10_ea_song_playlists_distribution.png │ ├── top_10_of_ea_song_comment.png │ ├── top_10_song.png │ └── top_10_song_up.png │ ├── music_index.py │ ├── music_wordcloud.py │ ├── netease_cloud_music_data_analysis.py │ ├── top_10_ea_song_collection_distribution.py │ ├── top_10_ea_song_playlists.py │ ├── top_10_ea_song_playlists_distribution.py │ ├── top_10_of_ea_song_collection.py │ ├── top_10_of_ea_song_comment.py │ ├── top_10_song.py │ └── top_10_song_up.py ├── Python数据分析初探项目 基于Python数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022年）.md ├── Python数据分析初探项目 基于Python数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022年）.pdf └── README.md /LICENSE.txt: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/__pycache__/label_ea_song.cpython-39.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MYXHcode/Python-data-analysis-preliminary-project-data-visualization-music-list-analysis-system-TUST-2022/dced390c5181b10233757e8a15b5a2a08daf91b8/Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/__pycache__/label_ea_song.cpython-39.pyc -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/__pycache__/music_detail.cpython-39.pyc: -------------------------------------------------------------------------------- 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https://raw.githubusercontent.com/MYXHcode/Python-data-analysis-preliminary-project-data-visualization-music-list-analysis-system-TUST-2022/dced390c5181b10233757e8a15b5a2a08daf91b8/Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/font_resources/STZHONGS.ttf -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/label_ea_song.py: -------------------------------------------------------------------------------- 1 | """数据可视化，网易云音乐欧美歌单标签图""" 2 | import squarify 3 | import pandas as pd 4 | import matplotlib.pyplot as plt 5 | import time 6 | 7 | 8 | def data_visualization_of_label_ea_song(): 9 | """网易云音乐欧美歌单标签图""" 10 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 11 | 12 | print("正在生成网易云音乐欧美歌单标签图片...") 13 | 14 | # 输出进度条 15 | t = 60 16 | start = time.perf_counter() 17 | 18 | for i in range(t + 1): 19 | finsh = "▓" * i 20 | need_do = "-" * (t - i) 21 | progress = (i / t) * 100 22 | dur = time.perf_counter() - start 23 | 24 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 25 | 26 | time.sleep(0.02) 27 | 28 | # 处理标签信息 29 | tags = [] 30 | dom2 = [] 31 | 32 | for i in df[1]: 33 | c = i.split('-') 34 | 35 | for j in c: 36 | if j not in tags: 37 | tags.append(j) 38 | else: 39 | continue 40 | 41 | for item in tags: 42 | num = 0 43 | 44 | for i in df[1]: 45 | type2 = i.split('-') 46 | 47 | for j in range(len(type2)): 48 | if type2[j] == item: 49 | num += 1 50 | else: 51 | continue 52 | 53 | dom2.append(num) 54 | 55 | # 数据创建 56 | data = {'tags': tags, 'num': dom2} 57 | frame = pd.DataFrame(data) 58 | df1 = frame.sort_values(by='num', ascending=False) 59 | name = df1['tags'][:10] 60 | income = df1['num'][:10] 61 | 62 | # 绘图 details 63 | colors = ['#993333', '#CC9966', '#333333', '#663366', '#003366', '#009966', '#FF6600', '#FF0033', '#009999', 64 | '#333366'] 65 | plot = squarify.plot(sizes=income, label=name, color=colors, alpha=1, value=income, edgecolor='white', 66 | linewidth=1.5) 67 | 68 | # 设置图片显示属性,字体及大小 69 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 70 | plt.rcParams['font.size'] = 8 71 | plt.rcParams['axes.unicode_minus'] = False 72 | 73 | # 设置标签大小为 1 74 | plt.rc('font', size=6) 75 | 76 | # 设置标题大小 77 | plot.set_title('网易云音乐欧美歌单标签图', fontsize=13, fontweight='light') 78 | 79 | # 除坐标轴 80 | plt.axis('off') 81 | 82 | # 除上边框和右边框刻度 83 | plt.tick_params(top=False, right=False) 84 | 85 | # 保存图片 86 | plt.savefig('./music_image/label_ea_song.png', dpi=None) 87 | 88 | # 显示图片 89 | plt.show() 90 | 91 | print("\n已生成网易云音乐欧美歌单标签图片，保存至 music_image/label_ea_song.png") 92 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/music_data/music_list.csv: -------------------------------------------------------------------------------- 1 | /playlist?id=5212877669,[EDM Progressive House] 感受电音正能量,431万,云音乐电音专区 2 | /playlist?id=7336545029,[卧室漫游] 盖上被子 独享你心里的宇宙,119万,云音乐官方歌单 3 | /playlist?id=5252671474,[Trip Hop] 神游舞曲 致幻神游,434万,云音乐电音专区 4 | /playlist?id=7403566770,[健身必备] 动感节奏点燃训练激情,219万,云音乐官方歌单 5 | /playlist?id=2829816518,[欧美私人订制] 最懂你的欧美推荐 每日更新35首,41794万,云音乐官方歌单 6 | /playlist?id=7479923898,[HIIT一下] 热力节奏，极速燃脂！,70万,云音乐官方歌单 7 | /playlist?id=7461646215,[她力量] 手握麦克风的她们势不可挡,88万,云音乐官方歌单 8 | /playlist?id=7725920397,[徒步随响]深秋轨迹，在路途中找答案,16万,云音乐官方歌单 9 | /playlist?id=2859214503,[一周欧美上新]Alec Benjamin热单《Paper Crown》重录发行,3689万,云音乐官方歌单 10 | /playlist?id=7680903955,[出门大作战] 合着音乐不紧不慢,98833,云音乐官方歌单 11 | /playlist?id=7461440491,[HipHop练习曲] 律动型歌荒拯救计划,168万,云音乐官方歌单 12 | /playlist?id=5212729721,[欧美点唱机] 重温热播欧美流行单曲 每日30首,2748万,云音乐官方歌单 13 | /playlist?id=6675213621,[当代节奏布鲁斯] 来一杯丝滑且醇厚的R&B咖啡,170万,云音乐官方歌单 14 | /playlist?id=6654532835,[打游戏听说唱] 说唱律动是你最佳游戏伴侣,675万,云音乐官方歌单 15 | /playlist?id=5395488578,[一周欧美说唱] 嘻哈众星云集Metro Boomin新专,756万,云音乐官方歌单 16 | /playlist?id=2829779628,[运动随身听] 必听活力音乐燃料 今天运动了吗,8427万,云音乐官方歌单 17 | /playlist?id=7669623718,Chill Time丨浸润于夜色中的一抹寂静,10万,丨IIIIIIIIII丨 18 | /playlist?id=6948039584,微醺｜R&B 慵懒 浪漫氛围感,667万,-孤岛与海_ 19 | /playlist?id=7717519184,Chill Time丨围炉夜话 温酒煮茶,27693,丨IIIIIIIIII丨 20 | /playlist?id=7641567359,Chill Time丨安逸恬静的舒适角落,22544,丨IIIIIIIIII丨 21 | /playlist?id=7636411529,英文说唱丨欧美腔调与丝滑Flow的化学反应,42万,芳心收集人士 22 | /playlist?id=2863615757,双倍快乐 | 听了心情会变好,394万,RgC2 23 | /playlist?id=7559330337,Chill Time丨落日渐沉 晕染宁静小时光,10万,丨IIIIIIIIII丨 24 | /playlist?id=6960440256,一些很欲 缠绵 性感 的歌｜欧美,354万,alwaysbeROMANTIC 25 | /playlist?id=7647692003,『地下/匪帮/New Wave』Trap 陷阱说唱,43430,贝嘞个京泽 26 | /playlist?id=7644469463,秋游絮语➹轻快律动，氤氲遐想氛围,18万,Martin网易云Carlos 27 | /playlist?id=7711019881,暖心抚慰丨浪漫翻涌成诗 邂逅美好冬日,15223,丨IIIIIIIIII丨 28 | /playlist?id=7629023289,清舒音萃♬灵动电子，加班必备,19万,Martin网易云Carlos 29 | /playlist?id=7668604332,『欧美』单曲循环百遍都听不腻的优质女声,83608,冷森Listen 30 | /playlist?id=7672668302,2小时沉浸式健身：开启电子碎脂机✔,10万,Martin网易云Carlos 31 | /playlist?id=7228606210,[节奏控]【超好听的小众英文歌】,738万,h枯燥 32 | /playlist?id=7635460898,欧美小调｜沉溺于温柔的迷人旋律,17550,永远ok丨 33 | /playlist?id=7694702474,清新疗愈氛围☁沉溺灵动音律(˵¯͒〰¯͒˵),91554,Martin网易云Carlos 34 | /playlist?id=7639357328,电子灵动夜♠假期宇航，独享欢畅,14万,Martin网易云Carlos 35 | /playlist?id=7687416720,37.2°C电子❀遐想氛围，微醺治愈,52570,Martin网易云Carlos 36 | /playlist?id=7737523640,西海岸说唱 | Trap陷阱给大脑过电,44218,让梦感动你 37 | /playlist?id=7699408632,Justin Bieber | 起起落落归来仍是少年,48361,芳心收集人士 38 | /playlist?id=6620086396,很chill的R&B歌单 节奏布鲁斯 欧美,1134万,alwaysbeROMANTIC 39 | /playlist?id=7739228781,逃离城市计划｜别赶路 去感受路,44300,雾岛与歌 40 | /playlist?id=2155383482,正宗好货 | 请打开随机播放收听,392万,Trickyboiii 41 | /playlist?id=7685677806,欧美乡村民谣｜娓娓道来的故事,4762,榴芒小白粥 42 | /playlist?id=7709164755,解压电子☁自律学习の心情调色盘,71129,Martin网易云Carlos 43 | /playlist?id=7635705596,电子多巴胺：完美身材练出来✌,37979,Martin网易云Carlos 44 | /playlist?id=7725696145,辣妹必入 糟糕已经开始辣了！,10420,晚秋月色 45 | /playlist?id=7648026850,游戏宅专享♛助燃神曲，逆风也嚣张！,43401,Martin网易云Carlos 46 | /playlist?id=7417914721,DOiS微醺 性感情调| 氛围感拉满,281万,迷藏lb 47 | /playlist?id=7744826670,英式微醺 | 酿造浓郁香醇午间时光,18124,迷藏lb 48 | /playlist?id=7671850006,节奏控•盘点那些忍不住单曲循环的电音歌曲,23258,冷森Listen 49 | /playlist?id=7642263761,欧美电子⚡️甜美女声心动瞬间,63456,贝克克y 50 | /playlist?id=7745046896,迎着风向驰骋 | 追赶日落的余晖,25201,迷藏lb 51 | /playlist?id=2518831221,英文歌的天花板,3047万,ruiRuishy 52 | /playlist?id=7676292648,戴上耳机｜一个人听｜全世界都是你的,30737,你的媛宝宝鸭 53 | /playlist?id=2445945181,"我永远屈服于温柔，你是温柔本身",898万,杉茶先生 54 | /playlist?id=7740415503,毒性Drill精选UK Drill+US Drill更新⬆,7910,YeahAyy 55 | /playlist?id=6755721491,欧美｜落日黄昏浪漫至死不渝,247万,PinkSway 56 | /playlist?id=7659052715,Future Bass✰恣意低音，潺暝滤波激流,20633,Martin网易云Carlos 57 | /playlist?id=7696396254,电子情话：随微甜音弦摇曳生姿♥,7995,Martin网易云Carlos 58 | /playlist?id=7663766562,欧美电子｜旋律柔和男声柔情似水,12682,Headhunter-z 59 | /playlist?id=7702352213,溺幻男电：治愈磁嗓の浪漫美学,18781,Martin网易云Carlos 60 | /playlist?id=7651646901,夜电空间站☁缥缈如梦，漫游女电宇宙,11275,Martin网易云Carlos 61 | /playlist?id=5169111277,放轻松 就当漫游地球 来和我一起听吧！,1323万,大大怪怪阿姨 62 | /playlist?id=7644330173,打工人必备｜通勤路上的必备单曲,25507,嘿-Tedua 63 | /playlist?id=7665597792,【欧美】perception本人喜欢系列,11679,h枯燥 64 | 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/playlist?id=932071711,画画时听的歌 艺术 设计 (专注的做一件事),343万,无所谓的灵魂 192 | /playlist?id=7488984978,暖阳微醺｜所幸世上有光总会相遇的,28万,月亮藏不住的小情绪 193 | /playlist?id=6597679343,慵懒随性 | 戴上耳机舒适度100%,782万,期待每次见面 194 | /playlist?id=5193221116,黄昏将至| 蓝调R&B奏响日落橘海,29850,迷藏lb 195 | /playlist?id=2411629173,温柔英文歌-睡觉专用,3700万,柚uze 196 | /playlist?id=2140808907,Louis Vuitton 路易威登（店内曲精选）,340万,Carroll-Hall-Shelby 197 | /playlist?id=2521376051,宿醉感 | 在一个暮色沉沉的早上醒来,412万,未完成的渥修斯基 198 | /playlist?id=129706870,【监听煲机测试】母带32BitDSP 24K德国HD,171万,马文威 199 | /playlist?id=77695007,超好听的小清新英文歌1,1375万,yml-michelle 200 | /playlist?id=2979201561,「下午茶」街角咖啡店 悠闲下午茶,144万,Amber丶Queen 201 | /playlist?id=6607186274,Vintage | 复古漩涡 让灵魂保持分解,61万,尘埃之海 202 | /playlist?id=5363172472,很温柔吧 | 一秒沦陷的小众沉溺嗓音,562万,布洛芬解药 203 | /playlist?id=7722484417,星际漫步物语☛慢节奏燃脂格调,280,Martin网易云Carlos 204 | /playlist?id=6994450975,【浓情爵士】久经思念的黄昏，缓缓而来的你,22万,鼠一属二 205 | /playlist?id=2856131956,英文歌|干净舒适温柔治愈系,1225万,-倦猫_ 206 | /playlist?id=7026289543,日落兜风丨 穿梭在光影之间的跃动音符,22万,丨IIIIIIIIII丨 207 | /playlist?id=2839184829,超级无敌好听的英文歌.,1830万,TXJS007 208 | /playlist?id=2513522691,梦龙 酷玩 魔力红 林肯公园 共和时代,62万,-Crist-Francis- 209 | /playlist?id=54064296,◎情调【怡情咖啡屋】,104万,潮画 210 | /playlist?id=2161803752,欢快小调·清凉节奏唤醒你的抖腿因子,565万,树洞狸奴 211 | /playlist?id=19971832,20首欧美经典电影的经典金曲,151万,墨_子陳 212 | /playlist?id=7657263116,慵懒～放空|让那些不好的情绪都消失吧,1563,__komorebi-_ 213 | /playlist?id=429253487,Hip-Hop/90s/Golden Age/Old School,74万,ZTM41 214 | /playlist?id=7739212509,『刷题充电宝』奋笔疾书，思绪动起来！,1048,Martin网易云Carlos 215 | /playlist?id=7743155621,俄语·听不懂也能爱上的旋律,11124,AdeeL丨 216 | /playlist?id=2678572883,开口就是沦陷～,519万,C99S4 217 | /playlist?id=7018479608,灵魂歌手Adele回归|空灵嗓音诠释纯粹深情,352万,网易云音乐 218 | /playlist?id=36432129,NICE SONG 金曲集,289万,雰川水也 219 | /playlist?id=2514269356,欧美微醺 · 韵味十足的高级爵士女嗓,561万,shakemyhead 220 | /playlist?id=311692545,【民谣盛宴】100首必听欧美民谣,3076万,pure日月 221 | /playlist?id=7658518955,【Pitchfork】90年代最佳250首歌曲,8918,Keung13 222 | /playlist?id=2160524528,经典而又浪漫的爵士乐，绝不能错过,46万,云音乐曲库 223 | /playlist?id=7640890321,Future Bounce⚡弹跳音律，失重金属领域,2090,Martin网易云Carlos 224 | /playlist?id=153717657,慵懒鼓点 舒服到骨子里,270万,云村人 225 | /playlist?id=2920934734,『怀旧欧美』百首不得不听的英文经典,148万,枫jackie 226 | /playlist?id=7748364873,运动不息｜保持速度 尽享呼吸间的酣畅淋漓,62531,ClairoToday 227 | /playlist?id=2414158210,英语课上的那些英文歌【青春印象】,1766万,云音乐曲库 228 | /playlist?id=5352821257,「欧美」比伯 萌德 戳爷 碧梨 断眉 黄老板.,588万,艾尔艾克斯 229 | /playlist?id=2151381888,『欧美风』节奏感｜运动｜醒脑｜耳孕专用,429万,Cceciliao 230 | /playlist?id=2077372083,女声控 | 愿你被这世界温柔以待,68万,薄荷奶啵啵 231 | /playlist?id=7674912583,迷醉微醺R&B｜灵魂比肉欲要性感得多,27508,夏日与晚安君 232 | /playlist?id=1984845175,『Taylor·Swift』美国甜心的音乐世界！全集,21万,Chloris-Cc 233 | /playlist?id=3018739880,晚安曲‖开普勒的浪漫 只有银河知道,307万,ClairoToday 234 | /playlist?id=7755264499,冬日氛围｜寂寥旋律 虚无缥缈的疏离,44602,Bzstrive 235 | /playlist?id=932176943,「PB-R&B 」另类迷幻的空灵音律。,453万,JazzLove 236 | /playlist?id=2051476669,trap，嘻哈榜，（最洗脑的歌曲）,171万,Boy2099 237 | /playlist?id=398767929,新迷幻/Dreampop｜灵魂泳池,66万,南北包子君 238 | /playlist?id=7628982676,黑胶酒馆|耳畔的浪漫眼中的你,6937,爱做音乐的E8r 239 | /playlist?id=647135926,『欧美前奏控』论歌曲前奏的重要性,1642万,冷森Listen 240 | /playlist?id=630304838,溫柔宇宙的核心,309万,i9xx 241 | /playlist?id=7376592408,郊游必备丨沿路的旅途邂逅美妙的奇遇,42万,丨IIIIIIIIII丨 242 | /playlist?id=7709014791,Chill Time丨一个人的惬意与安宁,123,丨IIIIIIIIII丨 243 | /playlist?id=504347934,开口就爱上的欧美音乐【慎点！】,6329万,ModernTony 244 | /playlist?id=987359473,戳爷 六公主 碧梨 萌德 断眉 黄老板 joji…,588万,-Crist-Francis- 245 | /playlist?id=2186405575,【Rap】说唱嘛 跟着晃就完事了,614万,猴里贵好想吃豆腐花 246 | /playlist?id=768352357,深情密码 | 醉入沧桑男嗓的岁月与沉浮,168万,KillBunny 247 | /playlist?id=2818648102,「雷鬼音乐500首精选」雷鬼党必藏歌单,34万,侠侣亲子-许天准 248 | /playlist?id=2848226139,欧美｜极品旋律 无限循环！,1671万,跟风的胖虎 249 | /playlist?id=7448280652,纵享丝滑好旋律,43549,lOriagxN 250 | /playlist?id=7635470680,欧美说唱丨惊艳耳膜的快乐音符,2262,永远ok丨 251 | /playlist?id=5472208221,欧美|单曲循环系列「持续更新」,95万,人帅个高小汤姆 252 | /playlist?id=6907243774,好听到爆的温柔英文歌曲,60764,wzh1one 253 | /playlist?id=2324605704,【化妆】拽姐的专属BGM,2159万,单杀修女_ 254 | /playlist?id=7738198309,「冬日恋歌」有你在才是冬天该有的模样,25727,夏日与晚安君 255 | /playlist?id=7212442830,「欧美说唱」温柔rap唱给你听,62532,The_Shire 256 | /playlist?id=7723787675,历久弥新丨放在时间胶囊里的经典记忆,26126,丨IIIIIIIIII丨 257 | /playlist?id=7634755939,曼哈顿海滩的夜晚｜空气中绵延着迷人的情调,6367,戴知山 258 | /playlist?id=6940116169,橘色心情｜驾车飞驰在黄昏下的日落大道,363万,Evelauren 259 | /playlist?id=985540853,「荒诞的梦」末日余欢与最后的狂奔,90万,苏子星河 260 | /playlist?id=3163139856,悠悠时光｜语调轻柔的诉说一场浪漫,191万,Bzstrive 261 | /playlist?id=478761222,仙女化妆/洗澡/敷面膜歌单 卡点 节奏,577万,浪漫土土 262 | /playlist?id=443637511,欧美轻快小调//让烦恼随风飘散,1946万,赋魅 263 | /playlist?id=473759386,〖优质男嗓〗听到就心动的声音,952万,浮丨光 264 | /playlist?id=7752730266,运动必备 | 跑在风里 是热爱生活的开始,1691,月亮藏不住的小情绪 265 | /playlist?id=7388247922,节奏控｜怦然心动的优美旋律,20万,这条平凡的狗_QwQ 266 | /playlist?id=2798921885,R&B·沉浸在克莱因蓝的浪漫中,53万,干饭小天才丶 267 | /playlist?id=520172117,♪适合学习英语的歌曲,898万,--苏麻离青-- 268 | /playlist?id=2729246388,欧美烟嗓丨大叔嗓、,36万,pwdkzl 269 | /playlist?id=2873336061,旋律说唱，听你诉说这个世界,443万,原点FM 270 | /playlist?id=2296601213,青柠味复古 ✘ 凌步夏傍西海岸的空幻,667万,-XxxGreyenios- 271 | /playlist?id=7753637092,【精选车载音乐】【Maxinida Aglag】,250,DJ-Moriss 272 | /playlist?id=372908519,史上最耐听的经典英文歌曲与名人异国同唱,145万,马文威 273 | /playlist?id=404203653,275首值得一生欣听的英文歌,992万,帝歌-世界因你而更美好 274 | /playlist?id=2392949338,开车听的美国乡村音乐（A）,82万,马克安德森 275 | /playlist?id=7708525447,蓝调R&B｜布鲁斯 旋律的随性与独特,33577,蛋壳Maxd 276 | /playlist?id=6855863619,Bedroom Pop森室恋歌/都市人的忘忧乐园,19万,零度光影乄 277 | /playlist?id=5307191849,声色撩人丨一见倾心 迷醉旋律摄入100%,20万,丨IIIIIIIIII丨 278 | /playlist?id=2729114851,欧美经典丨乡村音乐、,10万,pwdkzl 279 | /playlist?id=86886745,「指环王」中古民谣，凯尔特中古风,543万,烈雨 280 | /playlist?id=7774799150,除躁电境☁心随音动，悠然宜放空,132,Martin网易云Carlos 281 | /playlist?id=7013835226,秋日咖啡店 | 充满阳光的下午茶,17万,樱桃味音乐 282 | /playlist?id=2623057239,【节奏控】｜健身歌单,261万,STAGE-G 283 | /playlist?id=15425552,可以单曲循环的摇滚歌曲,179万,墨_子陳 284 | /playlist?id=378139503,『Neo Soul』了解一下新感觉灵魂乐吧,110万,VEEZiE_WYGD 285 | /playlist?id=7667792137,灵魂R&B✨旋律如云☁️飘渺随性,30739,蛋壳Maxd 286 | /playlist?id=7762028848,「跑步歌单」come on一起变好！,353,h枯燥 287 | 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/playlist?id=5122277984,电影留声｜大叔嗓音 唱尽沧桑,47万,下一颗巧克力 304 | /playlist?id=7536883235,浪漫情调丨烛光下的微醺小酒馆,43435,丨IIIIIIIIII丨 305 | /playlist?id=2661667887,直抵心灵深处的欧美伤感女嗓,944万,-电音迷弟 306 | /playlist?id=532401498,〖节奏控〗欧美女声让人中毒的旋律,488万,-电音迷弟 307 | /playlist?id=6613382982,精选｜雷鬼·Reggae节奏蓝调抒情音乐,23万,知心0316 308 | /playlist?id=312734124,【节奏控】超带感的英文歌（经典篇）,16306万,原点FM 309 | /playlist?id=2144037259,经典英语歌曲300首-听歌学英语,128万,野寁 310 | /playlist?id=7751208464,欧美小调：再次相遇记得给我买一束花,3169,常迷道故 311 | /playlist?id=7506664469,放松心情丨捕捉美好 享受一份宁静的惬意,11万,丨IIIIIIIIII丨 312 | /playlist?id=2314766620,『电音女毒』女声响起，即沦陷之时,1215万,HUMAN00 313 | /playlist?id=7533927134,欧美女电❀治愈节拍，心跳撩耳派对,30万,Martin网易云Carlos 314 | /playlist?id=7724678602,治愈向｜ 温柔飘游在浪漫音乐时空,4457,COOLIN1217 315 | /playlist?id=2570474270,专业修复您的耳朵-R&b,108万,6k1Ms 316 | /playlist?id=739981123,响指系｜沉醉于清新悦耳的响指节奏中♬,815万,-电音迷弟 317 | /playlist?id=7711117075,【欧美经典】怀旧时光机准备就绪,26937,贝克克y 318 | /playlist?id=5352120320,R&B | 撩动旋律，引入深邃眼眸,233万,生活委员 319 | /playlist?id=2656845942,三分高冷 七分性感 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336 | /playlist?id=549368187,欧美嘻哈＆【篮球节奏控】,766万,毒克文 337 | /playlist?id=124923559,【百年经典】欧美时光穿梭机,166万,ModernTony 338 | /playlist?id=981591899,「欧美治愈」愿你被这个世界温柔以待,143万,夕日向暖 339 | /playlist?id=389177356,「欧美」开口跪 旋律脆 节奏控,53万,pwdkzl 340 | /playlist?id=5209517392,R&B | 挽留于心的撩人节奏,219万,生活委员 341 | /playlist?id=7710688301,【跑步歌单】节奏感超强燃烧卡路里,1930,JJSSTTBBBB 342 | /playlist?id=7348024286,英语四级丨洗脑背单词无意识记忆,11万,宇杭_歌单文案分享看主页 343 | /playlist?id=7608197601,治愈男嗓｜陷入柔煦之森的温柔呢喃,43241,芳心收集人士 344 | /playlist?id=7616549503,好身材必备！燃脂电音，沉浸心动节奏,98014,Martin网易云Carlos 345 | /playlist?id=2082967510,〖私藏〗越听越有感觉的英文歌,398万,林Bucheon 346 | /playlist?id=109308645,咖啡馆里一本书，邂逅一首爵士,749万,desnuages 347 | /playlist?id=373270611,1000首好听英文歌,123万,做个爱笑的大男孩 348 | /playlist?id=110943637,慵懒、烟酒和感人,1165万,窺鏡自憐 349 | /playlist?id=83105064,257位西海岸说唱歌手精选,360万,EmBanks_Arman 350 | /playlist?id=7595367606,听见好心情丨徜徉于暖风中的元气因子,42351,丨IIIIIIIIII丨 351 | /playlist?id=7656666886,【法式浪漫】柔情脉脉，优雅温柔,935,我你爹奥 352 | /playlist?id=5316109682,Evergreen | 复古浪潮 温情时光,125万,尘埃之海 353 | /playlist?id=2464078995,ʚɞ精致的猪猪女孩化妆歌单,728万,JeanaChong 354 | /playlist?id=7438875716,微醺慵懒 | 趁着醉意和你讲浪漫和爱,18万,月亮藏不住的小情绪 355 | /playlist?id=2664297240,『乡村音乐』舒适惬意，田野休闲好时光,38万,一生向海 356 | /playlist?id=5344775532,复古系|光怪陆离的幻想之旅,114万,Spectual 357 | /playlist?id=7467635660,精致女嗓丨俘获心动的迷人旋律,14万,丨IIIIIIIIII丨 358 | /playlist?id=134606748,【毒】开口沉醉，迷失于这女声,1598万,瘦茶 359 | /playlist?id=7359295346,【英文】温柔治愈开口跪系列！,13万,热心音乐人橘子 360 | /playlist?id=5469009904,梦龙乐队『精选免费』,118万,林肯公圜 361 | /playlist?id=452527805,清新节奏控//愉悦就在弹指间,42万,赋魅 362 | /playlist?id=451222004,学霸计划|反正都要听歌，不如顺便记词汇,1339万,Nemuree 363 | /playlist?id=692254353,国外超级swag的说唱音乐 trap boombap,324万,拒分 364 | /playlist?id=6776379524,欧美向｜生活总是充满美好的,331万,小黄啾眯 365 | /playlist?id=7759767757,欧美R&B·节奏布鲁斯巅峰作品 耳机里的律动,60,内啡肽_Fentany丨 366 | /playlist?id=7348482600,【欧美乡村】民谣深处的另一个时光小巷,27529,星空悟羽 367 | /playlist?id=7722171803,Chill Time丨晚风轻佛 醇享冬日柔音,103,丨IIIIIIIIII丨 368 | /playlist?id=2687869264,比伯 戳爷 霉霉 碧梨 艾薇儿 火星哥 麦姐,283万,花花甜莓日系 369 | /playlist?id=2417401611,行走的CD | 莫若此刻最缠绵,75万,KillBunny 370 | /playlist?id=7386964160,元气指南丨轻快节奏与迷人嗓音的极致律动,87169,丨IIIIIIIIII丨 371 | /playlist?id=3127807964,情绪不好就不爱说话,114万,决劣 372 | /playlist?id=2390539027,【欧美】那些让耳朵怀孕的英文歌曲～,5144万,Mysterious-Box 373 | /playlist?id=102689614,发烧男声 当·威廉姆斯,96万,老乔-如歌 374 | /playlist?id=750259340,|大叔嗓| 把灵魂里的深情唱给你听,338万,-TRTan- 375 | /playlist?id=4962813565,浪漫薄暮 | 勃艮第红色天空下的温柔絮语,57万,后现代养猪专业户 376 | /playlist?id=7607455542,『欧美』节奏轻快&旋律好听英文歌曲,13955,芳心收集人士 377 | /playlist?id=310719068,|刷题| 写作业专用特效药,1076万,-TRTan- 378 | /playlist?id=5455674946,晚安序曲 | 把浪漫和温柔藏进美梦里,72万,与银河对视 379 | /playlist?id=2777953134,巨温柔的英文歌✨,1132万,奈奈生晴子 380 | /playlist?id=2049779104,辣妹听hiphop!!,756万,CreepyCreepyCreepy 381 | /playlist?id=405337496,「无径之林」春末里的废墟,176万,独行的棕鹿 382 | /playlist?id=2325024301,【游戏必备BGM】旋律系电音伴你自由畅玩！,816万,谐星七十六号 383 | /playlist?id=5200944839,欧美流行歌曲｜好听到单曲循环,836万,G寄予 384 | /playlist?id=504855461,欧美•舒缓•助眠『许你一晚安眠』,174万,-Lilian 385 | /playlist?id=5474594286,心动模式•今日份的美好旋律与明朗节奏,87万,樱桃味音乐 386 | /playlist?id=7710280234,极致治愈 | 遇见每一场晚霞 把温柔留在心底,92,月亮藏不住的小情绪 387 | /playlist?id=2774769182,小众冷门 · 品味高级,27万,ProzacXanax 388 | /playlist?id=5003037677,自嗨必备||200首优质HipHop歌曲精选,83万,JealousBoy 389 | /playlist?id=2712936322,踩点 | 前方高能 让你欲罢不能的BGM,4548万,Vxe- 390 | /playlist?id=7660988987,假日限定｜休闲&旅行 这个假期由你决定,30284,蛋壳Maxd 391 | /playlist?id=7640377432,欧美｜如果再也不能见到你祝你早安午安晚安,36412,夏日与晚安君 392 | /playlist?id=7551130936,弹跳力测试｜运动电音，塑造窈窕身材,11万,Martin网易云Carlos 393 | /playlist?id=7571144972,假日Vlog｜跃动节奏，空灵奏鸣曲,13万,Martin网易云Carlos 394 | /playlist?id=7585522896,假日心动甜美｜注入一剂电音活力剂,92642,Martin网易云Carlos 395 | /playlist?id=2141010431,独处伴侣｜飘到地球尽头,100万,赋魅 396 | /playlist?id=7562477050,消暑薄荷电韵☀悠游空灵节奏浪潮,14万,Martin网易云Carlos 397 | /playlist?id=4882049068,心不被人事物羁绊 生活会特别轻盈自在,56万,樱桃味音乐 398 | /playlist?id=3088426772,欧美小调° | 冬日舒适心情指南,563万,Feillica 399 | /playlist?id=440561933,当女声邂逅电音：百首精选,6505万,xept 400 | /playlist?id=60662715,越练越High 20首（肆）女声专场,180万,丁炜 401 | /playlist?id=5806476,Taylor Swift（泰勒-斯威芙特） 天籁之灵,241万,随风入梦 402 | /playlist?id=2952088224,云端漫步丨迷失在如梦似幻的北欧仙境中,157万,丨IIIIIIIIII丨 403 | /playlist?id=2634203521,迷死人的前奏 百听不厌的前十秒,1169万,螚安Vivienne 404 | /playlist?id=5383783763,冷门电音丨当同频灵魂遇上惊喜宝藏,91819,-Pherusaaaa 405 | /playlist?id=774175747,保持乐观，热爱音乐，每天起来吃早餐！,1528万,向来歌哥 406 | /playlist?id=2305854356,一级警报：小哥哥你甜度值爆表了啦,314万,KillBunny 407 | /playlist?id=3012142454,晚安曲 愿一切美好的事物伴你左右,389万,樱桃味音乐 408 | /playlist?id=7485613983,欧美经典 | 用一首歌回顾流金岁月,44809,芳心收集人士 409 | /playlist?id=7556821079,『欧美民谣』在夜半的小镇享受安静,14万,我你爹奥 410 | /playlist?id=1997189512,北欧民谣 | 赐你一剂澄净安逸的心灵圣药,1363万,Xthousis6 411 | /playlist?id=6595240183,「空灵飘渺」冰天雪地中的绝美吟唱,26万,空山鹤行 412 | /playlist?id=367179654,45度角仰望天空才是听朋克的正确姿势,337万,帅到掉渣 413 | /playlist?id=377552261,【节奏控】超燃带感英文歌,674万,胖座不能橘 414 | /playlist?id=2523761864,希望你的可爱，可以治愈一切烦恼,1733万,mayuko然 415 | /playlist?id=111126364,超赞！跑步燃脂的健身运动节奏,884万,瑾妤汐 416 | /playlist?id=554846241,「慵懒吟唱」柔美又脆弱的疏离,520万,JonathanHyden 417 | /playlist?id=7469766336,开车必备|安全驾驶 音乐交给我（总和持更）,62809,NavyBluuueSkies 418 | /playlist?id=4874886418,无前奏系列 | 心动挑战，耳朵喜欢好音乐,562万,olly的牙缝 419 | /playlist?id=2679916677,『Melodic Rap』 | 令人沉醉的旋律说唱 |,512万,HsiungTheKid 420 | /playlist?id=2906456704,轻快音乐 一键开启今日份满满活力,432万,樱桃味音乐 421 | /playlist?id=2087193208,永远的霉霉（vip专享）,215万,SJ_小石子 422 | /playlist?id=2255720648,〖私藏〗节奏盛宴，总有一首你的单曲循环,1075万,名侦探-柯北 423 | /playlist?id=7390521666,游戏电子 | 辅助也可以逆风翻盘呀！,24万,Martin网易云Carlos 424 | /playlist?id=7569305333,欧美节奏控☁仙女嗓音&捕音捉影,84422,Martin网易云Carlos 425 | /playlist?id=7724650088,轻欢曲调丨烦恼解忧音药,239,COOLIN1217 426 | /playlist?id=7777387307,欧美清新馆：氤氲电流，撩人心弦,76,Martin网易云Carlos 427 | /playlist?id=804228172,精选Psy Trance丨致人深度出神的电子巫术,99605,Shamania_Hermesavic_Raven 428 | /playlist?id=442341746,✞PB R&B✞新派R&B✞另类R&B✞,47677,VEEZiE_WYGD 429 | /playlist?id=533582963,开口即俘获人心，一听就爱上的英文歌,2635万,原点FM 430 | /playlist?id=7118964156,耳机分你一半,19万,Liuuuy7 431 | /playlist?id=7546517709,♛【法语温柔女声】给夜加点幽雅浪漫♡,41742,Alim_Official 432 | /playlist?id=2825552570,刷题|节奏轻快旋律惊艳的欧美歌单!!,552万,周二下午八点 433 | /playlist?id=2734329573,超级温柔治愈的英文歌曲,181万,静静nice哦 434 | /playlist?id=6880655744,温柔至极 • 失望世界的避难所,100万,OmenTwwnmfm 435 | /playlist?id=7562782562,健身必备热电｜燃脂律动，训练核心力量,13万,Martin网易云Carlos 436 | /playlist?id=118321798,【欧美翻唱】叫醒耳朵系列,2526万,零下Young 437 | /playlist?id=543660166,欧洲中古、凯尔特、爱尔兰、北欧民谣,39万,YTsuki 438 | /playlist?id=7748833148,在田园共进野餐 | 尽享自然的诗意,170,迷藏lb 439 | /playlist?id=538190807,好听到爆英语歌曲，绝对耳熟,1180万,南风过西洲__ 440 | /playlist?id=2937630080,超好听的欧美歌单,318万,Liiiazy 441 | /playlist?id=2536552183,R&B | 漫漫寒夜庇护所,146万,CoolKidsShelter 442 | /playlist?id=2812485332,晚安 引起极度舒适的美好梦境,545万,西柚甜 443 | /playlist?id=7506971090,别再拖延！随电而动，塑造强健体魄✰,21万,Martin网易云Carlos 444 | /playlist?id=4988927144,chillin’,83万,Jennxu 445 | /playlist?id=720230976,酥心收割机 ✘ 甜筒般一撩即化的空幻,40万,-XxxGreyenios- 446 | /playlist?id=7477547538,在舒缓的旋律中陪你渐入佳境,40681,遇见-Music 447 | /playlist?id=2256615030,「高质量英文歌」让你单曲循环的英文歌,1870万,咕咕呜呜鱼 448 | /playlist?id=2467758690,魅惑软饮‖Downtempo/Lounge music,19621,亦喂亦EVEPHY 449 | /playlist?id=9385273,Norah Jones 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/playlist?id=7766363129,欧美电音：输出强电醒脑空间站,1472,陌森喵 710 | /playlist?id=2948442022,适合学习英语词汇/值得单曲循环,53万,37号元素 711 | /playlist?id=717848220,Trap Remix丨当欧美热单遇上毒性低音,2339万,避难所Shelter 712 | /playlist?id=2570147233,【私人甄选】切歌算你厉害,93万,Hoosler 713 | /playlist?id=7636641366,梦幻流行（Dream Pop）｜日落渐匿 梦境星河,1418,夏日与晚安君 714 | /playlist?id=473746517,『欧美经典1000首』还是老歌有味道,24719,音乐想象家 715 | /playlist?id=32360446,收集向~英文集锦,73万,zaneqi 716 | /playlist?id=147531927,西海岸 G-Funk,34万,Groovie 717 | /playlist?id=2033946678,『R&B 精选』节奏音律中，总有适合的调调¶,225万,生活委员 718 | /playlist?id=2115404761,一秒上瘾的小众英文歌,218万,TOUGHCORN 719 | /playlist?id=7227046292,史上最全英文歌,22万,ruiRuishy 720 | /playlist?id=7635185174,「欧美」听一遍就会跟着和的英文歌,2409,永远ok丨 721 | /playlist?id=498581255,R&B节奏布鲁斯||SOUL,137万,LEEHIP-CN 722 | /playlist?id=6960249538,Alternative R&B | 慵懒与优雅的碰撞,77011,LoveYouForAges 723 | /playlist?id=2333731148,海盐风味｜浪漫迷幻°新鲜度100%,679万,猫头罐与六便士 724 | /playlist?id=7582065028,1小时骑行：耳膜冲刺！燃脂能力Max,50335,Martin网易云Carlos 725 | 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742 | /playlist?id=5343839811,孤独药剂 • 雨季中一个人的音乐小屋,42万,OmenTwwnmfm 743 | /playlist?id=7698172274,孟菲斯嘻哈纯走疯狂｜MEMPHIS HIPHOP,1300,嘻望HIPHOPE_OFFICIAL 744 | /playlist?id=2972056119,开一间小店，贩卖美好,111万,张颜齐天大圣啊 745 | /playlist?id=6912934424,BOOM | Black night,25万,LBOOM_ 746 | /playlist?id=7519918200,Tropical海岛☀清新旋律与解压美学,13万,Martin网易云Carlos 747 | /playlist?id=94064401,纵享丝滑，慵懒性感的咖啡味女声,485万,朴露修夏 748 | /playlist?id=69514417,Pop Music 欧美流行歌曲【TOP】,41547,DJuncle-鸟叔 749 | /playlist?id=467058152,精选 | 百听不厌的英文歌,5190万,艾琳艾德勒丶 750 | /playlist?id=2206750454,花店营业歌单florist花艺师必备,114万,花工汉钠 751 | /playlist?id=5072140498,小众温柔的英文歌｜神仙嗓音,138万,池塬泽浅 752 | /playlist?id=7504585045,女嗓珍藏馆：迷失于电韵音海之中,69500,Martin网易云Carlos 753 | /playlist?id=2487144149,主播都在用的超燃宝藏歌单还不快来听听,838万,ZJevo 754 | /playlist?id=378213166,『舒缓向 | 欧美』迷幻空灵，温暖人心,1530万,柠檬味海风Sound 755 | /playlist?id=6925784129,夜色微醺｜思绪陷入云海，月亮落在肩上,32万,Evelauren 756 | /playlist?id=2245123862,你是我漫长黑夜里的迷恋与遗忘,315万,抑郁爱人 757 | /playlist?id=94059576,【励志】困境让你更强壮,249万,烈雨 758 | /playlist?id=7567415651,欧美｜人们终将落俗，但浪漫至死不渝,49421,夏日与晚安君 759 | /playlist?id=889960888,「欧美流行」那些你想找又找不到的歌曲,6379万,G00d9T 760 | /playlist?id=2091256206,【LOUNGE BAR】舒缓放松减压微醺迷幻系列,71184,PEachhhh0624 761 | /playlist?id=325993939,⚡️ HIPHOP | Hey Is Life $$$,487万,-GIRLHOODH- 762 | /playlist?id=35148937,前奏入耳、后劲十足的攻气女声,147万,mercurius-穷途 763 | /playlist?id=430941731,电音 | 减肥的动力,236万,这条平凡的狗_QwQ 764 | /playlist?id=7452834423,安静|耳机党的专属福利,24306,Feng丶-Ge 765 | /playlist?id=6851616292,温柔药剂 • 不适合恋爱的社恐人员,40万,OmenTwwnmfm 766 | /playlist?id=6919723625,对 方 已 向 你 开 启 枕 边 共 享,71万,夏日与晚安君 767 | /playlist?id=3042446515,极致幻境｜坠入浪漫宇宙的低沉旋律,99万,Bzstrive 768 | /playlist?id=2220081292,安静细腻的欧美小调，献给失眠的你,1325万,SuperMan-LEE 769 | /playlist?id=111007328,Jᴀᴢᴢ｜好听的爵士人声精选,294万,Nokop 770 | /playlist?id=7455379429,Acoustic丨温暖纯净 浪漫到入骨的温柔,18197,丨IIIIIIIIII丨 771 | /playlist?id=2544563570,仙女精致化妆BGM,488万,愿愿很ok 772 | /playlist?id=123243715,[声线] 空 灵 女 声,2498万,BeTheOG 773 | /playlist?id=5394515165,浪潮美学Synthwave| 梦幻霓虹，温情时光,96万,夕日向暖 774 | /playlist?id=6695427788,2021欧美|billboard百冠音乐,47万,籣秋廿五 775 | /playlist?id=7033356182,欧美R&B 丨或甜或欲的女声,86万,傲娇霉说你泰矮i 776 | /playlist?id=151294356,清吧抒情英文歌曲,483万,我只身一人游过心海 777 | /playlist?id=7405817995,心动旋律丨虚幻荒诞下的另类浪漫,31万,丨IIIIIIIIII丨 778 | /playlist?id=2538119796,Trap Rap|陷阱说唱的低音冲击,317万,卧室坐家 779 | /playlist?id=913708064,Lemon Tree:)惊艳的英文歌曲,89万,谁在屋顶上唱歌 780 | /playlist?id=617942586,Swing摇摆舞会歌曲指南,73万,江河故人 781 | /playlist?id=7442133980,欧美流行风，沦陷其中无法自拔,21389,Martin网易云Carlos 782 | /playlist?id=363654077,天籁之音 | 此曲只应天上有☁️,915万,-解忧杂货店 783 | /playlist?id=6799998255,2022Billboard公告牌年终单曲Top100,172万,十三逆旅Cobain 784 | /playlist?id=4920405293,安静|那些自带高级感的英文歌,1091万,知鱼__Carrie 785 | /playlist?id=7036572151,欧美说唱 | 戴上耳机感受flow的轰炸,294万,腻鹿嘢 786 | /playlist?id=2411726083,复古电子Music |『致敬80s~』,41万,时间旅行者TIMES 787 | /playlist?id=368734733,『贾斯汀·比伯』百首必听盘点,242万,布兰妳 788 | /playlist?id=2449584784,好听到爆的欧美歌,92万,安风诺良奈 789 | /playlist?id=485099398,❉圣诞精选•Christmas is near❉,37万,我像只鱼儿在喝你的汤 790 | /playlist?id=4930606612,万有或虚无｜浪漫主义式的追寻,533万,为实现中华民族伟大复兴而听歌 791 | /playlist?id=2785836714,情书簿｜你是拥有山川河海的神明,36万,薄荷奶啵啵 792 | /playlist?id=7377252381,周末登山Party | 斑斓电嗓，追寻自在,39781,Martin网易云Carlos 793 | /playlist?id=606848009,好好生活，慢慢相遇,18万,渐无言语 794 | /playlist?id=6974835249,慵懒卧室——氛围感,18万,LadyLuna_ 795 | /playlist?id=2852805110,E标【禁 止 收 藏】,417万,TENET-V 796 | /playlist?id=5351538447,编辑精选Vol.93｜朝霞烂漫,23万,云音乐说唱专区 797 | /playlist?id=5381877263,「打游戏必备歌单」收藏最新超燃歌曲,150万,_云端上的鱼 798 | /playlist?id=5229770965,弹性低音/Slap House&Brazillian Bass,81058,Silenc_su 799 | /playlist?id=118788911,街角咖啡店播放的慵懒小时光,234万,yin雪燕 800 | /playlist?id=2916282498,<秋日微醺>想来点舒适度100%的微风吗,439万,ROMANCE-KNIGHT 801 | /playlist?id=143646240,【欧美经典】 任岁月肆虐都无法超越的经典,193万,怡语芸 802 | /playlist?id=6724722210,欧陆迪斯科 | 红男绿女的都市舞会,10万,弄潮儿电台 803 | /playlist?id=7760233263,历界世界杯主题曲大盘点,405,chelife 804 | /playlist?id=7641555801,每日来“电”｜耳机下的狂欢盛宴,738,嘿-Tedua 805 | /playlist?id=4949924773,冬天的第一个烤红薯 要和喜欢的人一人一半,80万,大笨zhu- 806 | /playlist?id=2744545170,Helens海伦司小酒馆,65万,沉溺66666 807 | /playlist?id=2503202287,怀旧旋律 · 旧时光里的天马行空,213万,shakemyhead 808 | /playlist?id=98209679,作业专属【刷题BGM】,5964万,橘子可樂限定 809 | /playlist?id=2442349721,「惊艳电子·旋律控」一听倾心 爱不释耳❷,681万,塔希提岛的月亮 810 | /playlist?id=113925019,【梦工厂】长篇动画音乐合集,36996,莎士比亚书店 811 | /playlist?id=7752685139,想跳舞就听这个吧｜Comeon Dance with me,177,alwaysbeROMANTIC 812 | /playlist?id=168375719,Urban | Swag Dance 适合跳舞节奏HipHop,66万,VEEZiE_WYGD 813 | /playlist?id=7750492442,第65届格莱美最佳传统/当代蓝调专辑提名,150,来我厨房 814 | /playlist?id=461288992,欧美 | 开口即跪，窒息嗓音,95万,ZaleLes 815 | /playlist?id=3010384274,欧美 | 精选1w~10w热评 | 爆好听的英文歌,11435,沈星辰co 816 | /playlist?id=6962582540,【私藏歌单】巨巨有感觉的英文歌！超酥！,26万,佛系音乐藏家 817 | /playlist?id=2812409523,小众却很惊艳‖欧美篇,441万,ClairoToday 818 | /playlist?id=2513570815,佛罗里达最硬的黑人,380万,POSITIVEENERGYXXX 819 | /playlist?id=6944248020,[欧美推荐] 宝藏歌单 超级奶斯,68万,朾也香一 820 | /playlist?id=2550277551,小众英文歌歌单（！却意外的好听）,3399万,咕咕Kvalley 821 | /playlist?id=5042045636,清新小调 | 风中有春天的味道了,168万,-TRTan- 822 | /playlist?id=146513028,REMIX｜惊艳涅槃于电子氛围,250万,下一颗巧克力 823 | /playlist?id=125106789,约翰列侬John Lennon最经典的200首,15万,城小巷 824 | /playlist?id=7650548926,通勤减压 | 下班好心情 疲劳快走开,55212,Dream_d7 825 | /playlist?id=7514744502,杀戮开启☣节奏续航，称霸战场,83679,Martin网易云Carlos 826 | /playlist?id=309562578,1000首好听英文歌：心中有爱 脚下生风,28万,misslilyann 827 | /playlist?id=306397077,【节奏控】那些超带感的音乐,29270万,原点FM 828 | /playlist?id=146852233,【绝美人声+完美电音】，触电节奏一秒倾心~,1684万,莫小懒_ 829 | /playlist?id=715662722,婚礼暖场 | 你很有天赋 跟我结婚好了,22万,咕噜咀嚼C 830 | /playlist?id=2320144876,炸了 ！炸了 ！炸了 ！Swag极品,418万,Rootskool 831 | /playlist?id=399136850,迷幻-盯鞋-dream pop-后朋,45万,fake-ophelia 832 | /playlist?id=2871863641,睡眠治愈曲 | 慵懒撩人，聆听入境,716万,后原 833 | /playlist?id=7297818158,来自野生面包的溜车播放列表Vol.01,94234,野生面包本人 834 | /playlist?id=2469559434,【欧美风】碧梨/霉霉/戳爷/比伯/萌德/断眉,398万,温柔叉烧 835 | /playlist?id=2956701226,☄Jazz Piano☄经典爵士钢琴百首精选,59781,Gondor-Modor 836 | /playlist?id=7635360476,欧美慵懒R&B｜夕阳挂在海岸上空,1229,永远ok丨 837 | /playlist?id=7701440920,重金属硬摇滚｜在咆哮中颤栗,1346,夏日与晚安君 838 | /playlist?id=6684024967,橘味汽水°旋律中弥漫着柑橘清香,103万,樱桃味音乐 839 | /playlist?id=7636463730,假期攻略 | 如何把旅行玩出仪式感,13938,Dream_d7 840 | /playlist?id=7752276645,2022世界杯 | 用音乐感受足球的热血澎湃,349万,Justin爱吃水煮鱼 841 | /playlist?id=3233910969,美国魔力红乐队,11万,山东-老刘 842 | /playlist?id=3026238005,慵懒爵士乐：享受懒床瘫家好时光,257万,鱼饼好吃耶 843 | /playlist?id=4872825924,洗澡.收拾房间.打扫卫生.化妆.护肤,231万,lalinmoon--w 844 | /playlist?id=2819596401,夏日清爽的响指节奏，给心情好好放个假吧,886万,原点FM 845 | /playlist?id=7433846767,惬意时光丨做个浪漫的白日梦想家,14万,Bzstrive 846 | /playlist?id=2954657473,下辈子做一只咖啡馆的猫，听着音乐扭着懒腰,106万,olly的牙缝 847 | /playlist?id=7547375593,林肯公园主唱去世五周年，致敬曾经闪耀的星,13万,Justin爱吃水煮鱼 848 | /playlist?id=7642881939,电子Hi-Fi｜晨练时刻〄热身 精神清新剂,1170,蛋壳Maxd 849 | /playlist?id=7769294822,踢球专用|踢球专用超燃bgm,107,Just-7ccc 850 | /playlist?id=6911164439,醇法语·爵士味老派奇趣复古趴,55万,Doksana 851 | /playlist?id=6880840869,少年感||保持热爱，阳光也能变得温柔,81万,JealousBoy 852 | /playlist?id=2388670214,「什么该被聆听? 」——在夜晚的青年大街,152万,_FURTUR_ 853 | /playlist?id=23266907,随身携带咖啡馆～惬意无限循环,73万,会跳的咖啡豆 854 | 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/playlist?id=6984793894,独立民谣｜拂去喧嚣，追逐内心的宁静,77316,summermidnights 871 | /playlist?id=939581816,每一首都能单曲循环的欧美经典流行歌曲,429万,Ricardo_YLY 872 | /playlist?id=59570166,布鲁斯殿堂级大师,84万,YouTube热门日推 873 | /playlist?id=2484415186,起床/健身/洗澡/醒脑/开车/跑步/通勤,618万,三韦三 874 | /playlist?id=4901099218,欧美HipHop当下流行RAP(建议随机播放）,66万,阿天不钓鱼 875 | /playlist?id=2101476924,NEFFEX 超燃神曲,131万,在下林凡 876 | /playlist?id=58916643,唱歌的诗人，独自优雅,48万,YouTube热门日推 877 | /playlist?id=2122279649,那些曾经在Billboard上爆红的HipHop———,1352万,火属 878 | /playlist?id=24344383,[ 运动音乐 ] 脂肪与美貌不可兼得,700万,柠檬酸自知 879 | /playlist?id=5361129558,【欧美】让你一秒倾心的神级电音❤️,63万,RuHIgeKatze 880 | /playlist?id=316587388,Jazz•最舒缓的咖啡伴侣,251万,yin雪燕 881 | /playlist?id=2175493416,「食色盛宴」极诱心扉，撩红耳根的性感旋律,508万,PEachhhh0624 882 | /playlist?id=4946118590,Alec Benjamin (斑鸠),50万,飞快的耶芙 883 | /playlist?id=53558869,当春风吹进民谣里【欧美篇】,160万,Sunshine-Miss-lin 884 | /playlist?id=12981779,复 古 浪 潮 时 间,96万,雰川水也 885 | /playlist?id=7751965724,疲惫的成年人，值得拥有自己的“游乐场”,21683,吃鳗鱼饭嘛_ 886 | 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/playlist?id=60378509,欧美系百听不厌的神曲「节奏控精选」,1662万,lightsV 902 | /playlist?id=5017409561,沙发音乐｜慵懒惬意的小资格调,494万,Rhaast 903 | /playlist?id=7588082450,小众微醺 | 于日暮轻拾细碎温柔,17697,Dream_d7 904 | /playlist?id=2877430180,「民谣/欧美」 温柔治愈英文歌 收藏向♡,111万,安以然养成计划 905 | /playlist?id=482798821,最爱骚蓝（各个风格布鲁斯以及老摇滚）,30万,Digos_Huggoo 906 | /playlist?id=7703107112,欧美Rap说唱神曲｜奏战歌，全体起立！,2396,夏日与晚安君 907 | /playlist?id=2097947168,玫瑰全都给你 可不可以把你给我？,903万,NickyRomero 908 | /playlist?id=2140976267,99°C耳朵怀孕系列,3036万,三月咖喱 909 | /playlist?id=89520378,随节奏悦动哼唱的R&B,59万,生活委员 910 | /playlist?id=2078306916,【游戏bgm】中 单 の 处 刑 曲.,280万,超天酱真的太棒啦 911 | /playlist?id=4969008301,另类R&B | 私藏 杂食性取向,62420,神的少女灬 912 | /playlist?id=560017896,欧美|百听不厌的英文歌,273万,然叔的旅行听歌日记 913 | /playlist?id=5142266799,蜜桃慕斯✘诱人嗓音与清甜质感,174万,樱桃味音乐 914 | /playlist?id=2968982695,【黑胶vip专属】欧美会员歌单,153万,_豆腐花_ 915 | /playlist?id=5219028932,复古潮流|文艺青年狂想曲,100万,Spectual 916 | /playlist?id=939320758,深情布鲁斯，浓情老酒馆。,2068万,帐号已注销 917 | /playlist?id=5205862998,落叶之秋 微风徐来 所有美好不期而至,65万,樱桃味音乐 918 | /playlist?id=813527004,California dreaming | 悠闲惬意的慵懒曲调,255万,最渣男友 919 | /playlist?id=92889121,德语歌曲精选集,52万,Schwarzwaelder-Kirschtoertchen 920 | /playlist?id=5817888,Westlife (西城男孩）经典单曲,460万,随风入梦 921 | /playlist?id=709889148,打游戏bgm 丨 什么运营节奏，我只想gank,1098万,元量空处 922 | /playlist?id=2825077157,宝藏电音 | 清新电音与惊艳女声的完美融合,178万,樱桃味音乐 923 | /playlist?id=4877064917,音乐时光机 | 黑人乐团进化史,33万,Keung13 924 | /playlist?id=813333839,打游戏必备| 感受这场听觉盛宴!,2655万,chaz1 925 | /playlist?id=560609382,『加州公路』皮卡夕阳与微风，生活不止苟且,2086万,帐号已注销 926 | /playlist?id=40468930,超级好听的英文歌,185万,real晓龙 927 | /playlist?id=106135633,设计师工作时爱听的歌,1070万,CeciliaHsin 928 | /playlist?id=4894076787,欧美慵懒向｜ 独行的人总会遇到有趣的人,278万,懒瑟不懒 929 | /playlist?id=5377394548,圣诞月的歌 | 把雪花和星星都挂在圣诞树上,105万,与银河对视 930 | /playlist?id=7754546335,「After Lounge」天台音乐歌单,519,金汤力电台 931 | /playlist?id=2514136633,[安德烈波切利Andrea Bocelli演唱合集],17万,属七先生 932 | /playlist?id=2524826899,前奏控 | 三秒沉沦 先声夺人,641万,塔希提岛的月亮 933 | /playlist?id=5482520359,Acoustic | 柔和纯净，清澈自然,75万,月光唱片 934 | 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/playlist?id=104533395,「欧美说唱」殿堂级欧美hip hop,68万,Leonsamiz 1195 | /playlist?id=532342423,20年155首最动听的格莱美金曲,332万,楼下二狗家的橘猫 1196 | /playlist?id=7575209471,酷酷的歌 ♡ 要悄悄努力 然后惊艳所有人,59827,月亮藏不住的小情绪 1197 | /playlist?id=962525610,[欧美]燃爆性强节奏踩点歌曲（不定期更新）,141万,谢顶墨少爷 1198 | /playlist?id=2581499900,2018欧美精选节奏｜满载而归的音乐盛宴,492万,原点FM 1199 | /playlist?id=7764166708,玫瑰情调 | 浪漫 至死不渝 温柔 绝对臣服,28,月亮藏不住的小情绪 1200 | /playlist?id=2101635690,清新电子丨柠檬汽水般夏日心情,374万,摇滾乌托邦 1201 | /playlist?id=7587903972,健身进行时：澎湃电音，高效燃脂♕,15538,Martin网易云Carlos 1202 | /playlist?id=6688006416,R&B/Hip-Hop/旋律/氛围/节奏/律动,763万,Wizme伍子木 1203 | /playlist?id=2261004329,【欧美】单曲循环的欧美慢摇,110万,想去西南吹風 1204 | /playlist?id=7768593296,电子夜游企划✰步入空灵赛博幻想,96,Martin网易云Carlos 1205 | /playlist?id=5220741653,音乐剧中念念不忘的对唱,60万,楼船夜雪天 1206 | /playlist?id=7238482918,2022全年抖腿指南，愿信仰的火光洒满人间,31431,NickyRomero 1207 | /playlist?id=3009720097,「慵懒午后」一朵花的欢颜与一剪流光的浪漫,228万,后原 1208 | /playlist?id=5053782850,欧美缱绻 | 于日暮轻拾细碎温柔,197万,衾琳儿 1209 | /playlist?id=2483048351,说唱风格-匪帮说唱（Gangsta 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1226 | /playlist?id=7776895320,『世界杯主题曲』用音乐感受足球的热血澎湃,78,知心0316 1227 | /playlist?id=2564248252,【心动模式】i see your monster.,422万,也不再计较灵魂 1228 | /playlist?id=7447020140,晨跑专享｜燃脂节奏，甩掉卡路里,17411,Martin网易云Carlos 1229 | /playlist?id=7748368327,全民运动｜让汗水挥洒赛道 让热爱永不停歇,246,ClairoToday 1230 | /playlist?id=2866624523,运动打球必备/节奏控,2929万,Sunhope_ 1231 | /playlist?id=36283027,俄罗斯乐队大赏丨后朋*冷潮*盯鞋*梦泡,53万,非正常人類研究員 1232 | /playlist?id=7501985279,SUMMER TIME！畅饮清新电子☀,40289,Martin网易云Carlos 1233 | /playlist?id=7762785663,【阿尔巴尼亚流行歌曲】精选火爆热歌分享,880,Falling_you_babe 1234 | /playlist?id=12367803,欧美·乡村民谣精选集,16万,墨_子陳 1235 | /playlist?id=310106794,【英文歌】让人陶醉的美妙旋律,671万,原点FM 1236 | /playlist?id=7734231540,Bedroom Pop:探寻那些从卧室走出的宝藏之声,47,ClairoToday 1237 | /playlist?id=7748789171,太空主题配乐 | 漫游浩瀚宇宙空间,94,迷藏lb 1238 | /playlist?id=466636631,『健身必备』有氧运动跑步歌单,109万,HUMAN00 1239 | /playlist?id=7777823500,北欧民谣 | 庭院里的午后阳光,140,常迷道故 1240 | /playlist?id=313654205,天涯小酒馆，听时光流淌的声音。,399万,风滚核桃 1241 | /playlist?id=890571828,点击突破10亿MV，每首都是经典,322万,s洛小可 1242 | /playlist?id=116760200,欧美深情男声，极致男声盛宴。,399万,意清风 1243 | /playlist?id=7697816586,白日梦想家：清新电子の秋日漫游,103,Martin网易云Carlos 1244 | /playlist?id=484565722,深夜做作业听点安静的歌(欧美为主),224万,韩酒黔 1245 | /playlist?id=2631594249,音乐钓鱼平台,48万,由J教主 1246 | /playlist?id=7303904039,节奏控 | R&B/Hip-Hop/旋律/节奏/律动,10759,LBOOM_ 1247 | /playlist?id=4725256,奥斯卡金曲精选,152万,雷击天下 1248 | /playlist?id=1997166218,「骨子里的 Old School」,452万,重慶二流仔 1249 | /playlist?id=740322272,神级Remix | 歌曲的重生,963万,怪兽Sound 1250 | /playlist?id=2840343300,爵士柔情，你我氤氲漫舞,27万,冷空气yu琉璃 1251 | /playlist?id=7294643985,苏翊鸣的宝藏曲库|恭喜小苏冬奥夺冠,278万,Ari非官方指定美黑师 1252 | /playlist?id=367632186,「爵士女伶」咖啡馆的微醺慵懒,245万,如花一般绽放丶 1253 | /playlist?id=566300165,车载音乐酒吧（每日更新）,122万,平平爱吃牛肉 1254 | /playlist?id=2253271412,Leave me alone丨谁都有想消失独处的时候吧,411万,下次陪我看月亮 1255 | /playlist?id=2089326276,『Eminem』 姆爷全集无重复ﾉ☀,27万,Chloris-Cc 1256 | /playlist?id=3228481862,Progressive House| 梦幻渐进，即刻陷落,80万,夕日向暖 1257 | /playlist?id=7771069451,浪漫主义 | 近在咫尺的温柔不止于此,20,月亮藏不住的小情绪 1258 | /playlist?id=6598065320,坠入欧美音海 沉溺每个心动瞬间,568万,桜珩 1259 | /playlist?id=7769865625,【节奏控】那些超带感的音乐（小众版）,127,执剑稳 1260 | /playlist?id=2050976156,Beautiful Now【音乐的力量·电音】,2295万,Damons_Xsw 1261 | /playlist?id=75950020,梦龙，林肯公园，魔力红，共和，酷玩，翻闹,770万,DTake-it 1262 | /playlist?id=533360996,J.Fla（最美侧颜）小姐姐翻唱,1083万,你弹吉他的样子很好看 1263 | /playlist?id=6846722392,MoodShop R&B歌曲推荐,28004,CoraZuo 1264 | /playlist?id=307288515,【英文】五十首最好听的英文歌曲,87万,逝水月夜流 1265 | /playlist?id=831028363,PotPvP,19万,Ayearr 1266 | /playlist?id=2158769818,吟 游 记 ‖只 想 做 个 堕 落 的 诗 人,388万,猫头罐与六便士 1267 | /playlist?id=500262668,【开口就醉倒】电子极致人声,1392万,ModernTony 1268 | /playlist?id=6702660581,【旋律控】超级好听的欧美良曲,1078万,kasim-zz 1269 | /playlist?id=2988424860,享受极致的温柔【欧美】,57万,52Hertzzz- 1270 | /playlist?id=2769139351,欧美R&B ：耳畔划过爱情的轻语,145万,蜜糖男孩 1271 | /playlist?id=508920727,气场全开，黑人音乐 就是这么拽,971万,GossipNeverEnds 1272 | /playlist?id=2880742579,ɴɪɢʜᴛ ᴠɪʙᴇ·今夜，一起坠入温柔的浪漫海洋,445万,Kaleidoscott 1273 | /playlist?id=7716344240,欧美情歌 | 奔赴一场浪漫的邀约,232,迷藏lb 1274 | /playlist?id=124092915,【毒 • 魇 • 瘾】箱底私藏，无限循环。,2270万,LE_CHAT 1275 | /playlist?id=7463646845,Future Bass｜空灵氛围，希冀梦幻曙光,11万,Martin网易云Carlos 1276 | /playlist?id=2704384438,「欧美·女声」令你的多巴胺跳起舞来,144万,_稀粥- 1277 | /playlist?id=867929764,全球大型电音节万人齐蹦迪炸场神曲,46万,Rootskool 1278 | /playlist?id=79216964,【欧美】慵懒嗓音，迷上复古,147万,烈雨 1279 | /playlist?id=515852041,《玩游戏》节奏满满，秀麻全场,631万,An_ovo- 1280 | /playlist?id=57241932,♬ 随心远行 完美公路音乐,58万,-安玥冉 1281 | /playlist?id=2167735496,西海岸说唱(G-Funk，硬核，拉美）,37万,K-arot 1282 | /playlist?id=3019716374,【欧美说唱歌单】英文说唱欧美hiphop精选,11万,kyrielong8 1283 | /playlist?id=47654223,【爵士】穿上西装，欢快抖腿,32万,生活委员 1284 | /playlist?id=803289718,Progressive Trance丨坠入浩瀚的星辰大海,14万,Shamania_Hermesavic_Raven 1285 | /playlist?id=6939992949,那些超燃超带感的英文歌【精选合集no.4】,113万,梅赛德斯XS 1286 | /playlist?id=6593498389,•欧美 | 日落余晖 静听女声醉耳,58万,不考上武大不改名 1287 | /playlist?id=3111369145,抱歉 我天生很酷 走路带风,369万,鹿白川 1288 | /playlist?id=416676558,那些好听不知道名字的神曲｛持续更新｝,1004万,胡英俊o 1289 | /playlist?id=5429892797,周末宅家必备：慵懒午后降躁指南,342万,轻漫故事社 1290 | /playlist?id=2986748152,月亮今天不营业啦，所以我来对你说晚安,282万,BAEK-J 1291 | /playlist?id=534193762,⚡️ EDM | 欧美女声与电音的极致碰撞,70万,-GIRLHOODH- 1292 | /playlist?id=7597165886,管阿姨的开车歌单|私藏小众歌,15万,管阿姨AUNTGUAN 1293 | /playlist?id=5289527048,『迷幻空灵』泠泠历历，恰似你给我的幻想,10427,W-沙丁鱼罐头 1294 | /playlist?id=7750042402,2023年第65届格莱美提名名单,66万,Ari非官方指定美黑师 1295 | /playlist?id=328055539,「欧美女声」十秒爱上系列①,1057万,包子慧灬 1296 | /playlist?id=7086047234,【rap】拽姐化妆时听的歌,125万,PURPLECOLDAIR 1297 | /playlist?id=7495901995,沉浸女电律动，沁入霓虹秘境,33560,Martin网易云Carlos 1298 | /playlist?id=7585481452,边走边听丨越过人海 追赶一场落日,34560,丨IIIIIIIIII丨 1299 | /playlist?id=7394906170,微醺唱片|遇到快餐时代里小火慢炖的粥了吗,36万,流萤与诗 1300 | /playlist?id=2813508916,音乐诗集｜ 静似风悠扬，淡如水潺湲,71万,野寁 1301 | /playlist?id=128621523,吟游北欧古谣，聆听岁月悠长。,109万,格调时代 1302 | /playlist?id=308388512,「奇怪的坏品味」,195万,郑丁禾 1303 | /playlist?id=2215062828,英文燃曲/燃向剪辑专用/踩点,372万,专业捅哥一千年 1304 | /playlist?id=11962860,经典英文歌曲之此情可待,101万,云梦的天空 1305 | /playlist?id=7375073896,慵懒微醺苦橙酒 | 沉浸式小众pop,38787,迷藏lb 1306 | /playlist?id=833435091,欧美说唱|好货私藏,312万,AkashiAshes 1307 | /playlist?id=2423552205,复古派对|一起跳欢乐的舞蹈吗,48万,卧室坐家 1308 | /playlist?id=6753617354,2021年全英音乐奖获奖及表演曲目,30万,Keung13 1309 | /playlist?id=66568325,「 DEEP/BASS/FUTURE 深夜低音 」,125万,G4LIFE-AK 1310 | /playlist?id=768288955,【西语】听说是与上帝交流的语言(滑稽）,395万,爱音乐的suri 1311 | /playlist?id=383337783,【现代乡村音乐】你不能错过的好音乐,396万,Romantic丶Notes 1312 | /playlist?id=2658719297,Billie Eilish-私藏的小精灵藏不住了,863万,pseudoephedrine 1313 | /playlist?id=580609099,【节奏控】开口脆，节奏跪,161万,救救小C 1314 | /playlist?id=7677636852,We Fell In Love In October,469,BillieEilishCJD 1315 | /playlist?id=7536942402,高燃时刻｜节奏卡点☢丝血反杀！,67484,Martin网易云Carlos 1316 | /playlist?id=19292229,那些温暖的沧桑声音,112万,杰子DJie 1317 | /playlist?id=95589265,商演活动暖场专用歌单,376万,游歌日记 1318 | /playlist?id=6724978342,『欧美流行』始于前奏—开口跪,830万,达达乌帕谷 1319 | /playlist?id=5257653220,Funky Party | 放克复古狂欢夜·Funk,26万,来我厨房 1320 | /playlist?id=837456,听一句就会喜欢上的英文歌,5134万,山北大洋 1321 | /playlist?id=450916650,欧美｜感受异国民谣带来的温柔,364万,赋魅 1322 | /playlist?id=7661054939,Midtempo♢如镜星空 灵动至璨中速绽放,191,内啡肽_Fentany丨 1323 | /playlist?id=7701925626,【车载舞曲｜混合系列】最新歌曲推荐,2333,UzmirOffical 1324 | /playlist?id=116617957,带电的时装走Show配乐~,128万,桔橘不甜 1325 | /playlist?id=2439826061,精选轻柔英文歌 【睡觉专用】,478万,日进斗金___ 1326 | /playlist?id=7781874285,电子星空游侠♠热身/放松/散步Style,46,Martin网易云Carlos 1327 | /playlist?id=7744249457,【欧美节奏控】醒脑节奏，压力释放剂,3133,coderlzq 1328 | /playlist?id=798130521,「电子•女声」惊艳耳际，一秒倾心,5231万,佛山李嘉欣 1329 | /playlist?id=5138657,如陈年老酒般醇厚的大叔音。,174万,徊梦 1330 | /playlist?id=148489369,越冬越运动•好身材虐出来,1049万,yin雪燕 1331 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/music_detail.py: -------------------------------------------------------------------------------- 1 | """数据获取，获取歌单详情页的信息""" 2 | from bs4 import BeautifulSoup 3 | import pandas as pd 4 | import requests 5 | import time 6 | 7 | 8 | def get_data_of_music_list_detail_page(): 9 | """获取歌单详情页的信息""" 10 | df = pd.read_csv('./music_data/music_list.csv', header=None, on_bad_lines=None, names=['url', 'title', 'play', 11 | 'user']) 12 | 13 | headers = { 14 | 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' 15 | 'Chrome/63.0.3239.132 Safari/537.36 ' 16 | } 17 | 18 | print("正在获取歌单详情页的信息...") 19 | 20 | # 输出进度条 21 | t = 60 22 | start = time.perf_counter() 23 | 24 | for i in range(t + 1): 25 | finsh = "▓" * i 26 | need_do = "-" * (t - i) 27 | progress = (i / t) * 100 28 | dur = time.perf_counter() - start 29 | 30 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 31 | 32 | time.sleep(0.02) 33 | 34 | for i in df['url']: 35 | time.sleep(2) 36 | 37 | url = 'https://music.163.com' + i 38 | response = requests.get(url=url, headers=headers) 39 | html = response.text 40 | soup = BeautifulSoup(html, 'html.parser') 41 | 42 | # 获取歌单标题 43 | title = soup.select('h2')[0].get_text().replace(',', '，') 44 | 45 | # 获取标签 46 | tags = [] 47 | tags_message = soup.select('.u-tag i') 48 | 49 | for p in tags_message: 50 | tags.append(p.get_text()) 51 | 52 | # 对标签进行格式化 53 | if len(tags) > 1: 54 | tag = '-'.join(tags) 55 | else: 56 | tag = tags[0] 57 | 58 | # 获取歌单介绍 59 | if soup.select('#album-desc-more'): 60 | text = soup.select('#album-desc-more')[0].get_text().replace('\n', '').replace(',', '，') 61 | else: 62 | text = '无' 63 | 64 | # 获取歌单收藏量 65 | collection = soup.select('#content-operation i')[1].get_text().replace('(', '').replace(')', '') 66 | 67 | # 歌单播放量 68 | play = soup.select('.s-fc6')[0].get_text() 69 | 70 | # 歌单内歌曲数 71 | songs = soup.select('#playlist-track-count')[0].get_text() 72 | 73 | # 歌单评论数 74 | comments = soup.select('#cnt_comment_count')[0].get_text() 75 | 76 | # 输出歌单详情页信息 77 | print('\r', title, tag, text, collection, play, songs, comments, end='', flush=True) 78 | 79 | # 将详情页信息写入CSV文件中 80 | with open('./music_data/music_detail.csv', 'a+', encoding='utf-8-sig') as f: 81 | f.write(title + ',' + tag + ',' + text + ',' + collection + ',' + play + ',' + songs + ',' + comments + 82 | '\n') 83 | 84 | # 获取歌单内歌曲名称 85 | li = soup.select('.f-hide li a') 86 | 87 | for j in li: 88 | with open('./music_data/music_name.csv', 'a+', encoding='utf-8-sig') as f: 89 | f.write(j.get_text() + '\n') 90 | 91 | print("\n已获取歌单详情页的信息，保存至 music_data/music_name.csv") 92 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/music_image/background_image.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MYXHcode/Python-data-analysis-preliminary-project-data-visualization-music-list-analysis-system-TUST-2022/dced390c5181b10233757e8a15b5a2a08daf91b8/Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/music_image/background_image.jpg -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- 1 | """数据获取，获取歌单索引页的信息""" 2 | from bs4 import BeautifulSoup 3 | import requests 4 | import time 5 | 6 | 7 | def get_data_of_music_list_index_page(): 8 | """获取歌单索引页的信息""" 9 | headers = { 10 | 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' 11 | 'Chrome/63.0.3239.132 Safari/537.36 ' 12 | } 13 | 14 | print("正在获取歌单索引页的信息...") 15 | 16 | # 输出进度条 17 | t = 60 18 | start = time.perf_counter() 19 | 20 | for i in range(t + 1): 21 | finsh = "▓" * i 22 | need_do = "-" * (t - i) 23 | progress = (i / t) * 100 24 | dur = time.perf_counter() - start 25 | 26 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 27 | 28 | time.sleep(0.02) 29 | 30 | for i in range(0, 1330, 35): 31 | # print('\r', i, end='', flush=True) 32 | 33 | time.sleep(2) 34 | 35 | url = 'https://music.163.com/discover/playlist/?cat=欧美&order=hot&limit=35&offset=' + str(i) 36 | response = requests.get(url=url, headers=headers) 37 | html = response.text 38 | soup = BeautifulSoup(html, 'html.parser') 39 | 40 | # 获取包含歌单详情页网址的标签 41 | ids = soup.select('.dec a') 42 | 43 | # 获取包含歌单索引页信息的标签 44 | lis = soup.select('#m-pl-container li') 45 | # print('\r', len(lis), end='', flush=True) 46 | 47 | for j in range(len(lis)): 48 | # 获取歌单详情页地址 49 | url = ids[j]['href'] 50 | 51 | # 获取歌单标题,替换英文分割符 52 | title = ids[j]['title'].replace(',', '，') 53 | 54 | # 获取歌单播放量 55 | play = lis[j].select('.nb')[0].get_text() 56 | 57 | # 获取歌单贡献者名字 58 | user = lis[j].select('p')[1].select('a')[0].get_text() 59 | 60 | # 输出歌单索引页信息 61 | print('\r', url, title, play, user, end='', flush=True) 62 | 63 | # 将索引页写入CSV文件中 64 | with open('./music_data/music_list.csv', 'a+', encoding='utf-8-sig') as f: 65 | f.write(url + ',' + title + ',' + play + ',' + user + '\n') 66 | 67 | print("\n已获取歌单索引页的信息，保存至 music_data/music_list.csv") 68 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/music_wordcloud.py: -------------------------------------------------------------------------------- 1 | """数据可视化，歌单介绍词云图""" 2 | from wordcloud import WordCloud, ImageColorGenerator 3 | import matplotlib.pyplot as plt 4 | import pandas as pd 5 | import jieba 6 | import time 7 | 8 | 9 | def data_visualization_of_music_wordcloud(): 10 | """歌单介绍词云图""" 11 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 12 | text = '' 13 | 14 | print("正在生成歌单介绍词云图片...") 15 | 16 | # 输出进度条 17 | t = 60 18 | start = time.perf_counter() 19 | 20 | for i in range(t + 1): 21 | finsh = "▓" * i 22 | need_do = "-" * (t - i) 23 | progress = (i / t) * 100 24 | dur = time.perf_counter() - start 25 | 26 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 27 | 28 | time.sleep(0.02) 29 | 30 | for line in df[2]: 31 | text += ' '.join(jieba.cut(line, cut_all=False)) 32 | 33 | background_image = plt.imread('./music_image/background_image.jpg') 34 | 35 | stopwords = set('') 36 | stopwords.update( 37 | ['封面', 'none介绍', '介绍', '歌单', '歌曲', '我们', '自己', '没有', '就是', '可以', '知道', '一起', '不是', 38 | '因为', '什么', '时候', '还是', '如果', '不要', '那些', '那么', '那个', '所有', '一样', '一直', '不会', '现在', 39 | '他们', '这样', '最后', '这个', '只是', '有些', '其实', '开始', '曾经', '所以', '不能', '你们', '已经', '后来', 40 | '一切', '一定', '这些', '一些', '只有', '还有']) 41 | 42 | wc = WordCloud( 43 | background_color='white', 44 | mask=background_image, 45 | font_path='./font_resources/STZHONGS.ttf', 46 | max_words=2000, 47 | max_font_size=150, 48 | random_state=30, 49 | stopwords=stopwords 50 | ) 51 | wc.generate_from_text(text) 52 | 53 | # 看看词频高的有哪些,把无用信息去除 54 | process_word = WordCloud.process_text(wc, text) 55 | sort = sorted(process_word.items(), key=lambda e: e[1], reverse=True) 56 | # print(sort[:50]) 57 | 58 | img_colors = ImageColorGenerator(background_image) 59 | wc.recolor(color_func=img_colors) 60 | plt.imshow(wc) 61 | plt.axis('off') 62 | 63 | # 保存图片 64 | wc.to_file("./music_image/music_wordcloud.png") 65 | 66 | # 显示图片 67 | plt.show() 68 | 69 | print("\n已生成歌单介绍词云图片，保存至 music_image/music_wordcloud.png") 70 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/netease_cloud_music_data_analysis.py: -------------------------------------------------------------------------------- 1 | import os 2 | 3 | from music_index import get_data_of_music_list_index_page 4 | from music_detail import get_data_of_music_list_detail_page 5 | from top_10_song import data_visualization_of_top_10_song 6 | from top_10_song_up import data_visualization_of_top_10_song_up 7 | from top_10_ea_song_playlists import data_visualization_of_top_10_ea_song_playlists 8 | from top_10_of_ea_song_collection import data_visualization_of_top_10_of_ea_song_collection 9 | from top_10_of_ea_song_comment import data_visualization_of_top_10_of_ea_song_comment 10 | from top_10_ea_song_collection_distribution import data_visualization_of_top_10_ea_song_collection_distribution 11 | from top_10_ea_song_playlists_distribution import data_visualization_of_top_10_ea_song_playlists_distribution 12 | from label_ea_song import data_visualization_of_label_ea_song 13 | from music_wordcloud import data_visualization_of_music_wordcloud 14 | 15 | 16 | def menu(): 17 | """网易云音乐数据分析系统菜单""" 18 | print("欢迎使用网易云音乐数据分析系统！(^▽^ )") 19 | print("---------------------------------------------") 20 | print("") 21 | print(" 【网易云音乐数据分析系统】 ") 22 | print("") 23 | print(" A.获取歌单索引页的信息") 24 | print(" B.获取歌单详情页的信息") 25 | print(" C.生成歌曲出现次数 Top10 图片") 26 | print(" D.生成歌单贡献 UP 主 TOP10 图片") 27 | print(" E.生成网易云音乐欧美歌单播放 TOP10 图片") 28 | print(" F.生成网易云音乐欧美歌单收藏 TOP10 图片") 29 | print(" G.生成网易云音乐欧美歌单评论 TOP10 图片") 30 | print(" H.生成欧美歌单收藏数量分布情况图片") 31 | print(" I.生成欧美歌单播放数量分布情况图片") 32 | print(" J.生成网易云音乐欧美歌单标签图片") 33 | print(" K.生成歌单介绍词云图片") 34 | print("") 35 | print("---------------------------------------------") 36 | print("请输入您要进行的操作（输入 quit 退出！）：") 37 | 38 | 39 | def key_down(): 40 | """网易云音乐数据分析系统功能交互""" 41 | option = input() 42 | 43 | if option == 'quit' or option == 'QUIT': 44 | print("已退出！\n\n") 45 | input() 46 | 47 | exit(0) 48 | elif option == 'a' or option == 'A': 49 | # 获取歌单索引页的信息 50 | get_data_of_music_list_index_page() 51 | 52 | return 53 | elif option == 'b' or option == 'B': 54 | # 获取歌单详情页的信息 55 | get_data_of_music_list_detail_page() 56 | 57 | return 58 | elif option == 'c' or option == 'C': 59 | # 生成歌曲出现次数 Top10 图片 60 | data_visualization_of_top_10_song() 61 | 62 | return 63 | elif option == 'd' or option == 'D': 64 | # 生成歌单贡献 UP 主 TOP10 图片 65 | data_visualization_of_top_10_song_up() 66 | 67 | return 68 | elif option == 'e' or option == 'E': 69 | # 生成网易云音乐欧美歌单播放 TOP10 图片 70 | data_visualization_of_top_10_ea_song_playlists() 71 | 72 | return 73 | elif option == 'f' or option == 'F': 74 | # 生成网易云音乐欧美歌单收藏 TOP10 图片 75 | data_visualization_of_top_10_of_ea_song_collection() 76 | 77 | return 78 | elif option == 'g' or option == 'G': 79 | # 生成网易云音乐欧美歌单评论 TOP10 图片 80 | data_visualization_of_top_10_of_ea_song_comment() 81 | 82 | return 83 | elif option == 'h' or option == 'H': 84 | # 生成欧美歌单收藏数量分布情况图片 85 | data_visualization_of_top_10_ea_song_collection_distribution() 86 | 87 | return 88 | elif option == 'i' or option == 'I': 89 | # 生成欧美歌单播放数量分布情况图片 90 | data_visualization_of_top_10_ea_song_playlists_distribution() 91 | 92 | return 93 | elif option == 'j' or option == 'J': 94 | # 生成网易云音乐欧美歌单标签图片 95 | data_visualization_of_label_ea_song() 96 | 97 | return 98 | elif option == 'k' or option == 'K': 99 | # 生成歌单介绍词云图片 100 | data_visualization_of_music_wordcloud() 101 | 102 | return 103 | else: 104 | print("选择错误，请重新输入！\n\n") 105 | input() 106 | 107 | return 108 | 109 | 110 | if __name__ == '__main__': 111 | """运行界面及功能代码""" 112 | while True: 113 | menu() 114 | key_down() 115 | 116 | # 清屏 117 | os.system('cls') 118 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/top_10_ea_song_collection_distribution.py: -------------------------------------------------------------------------------- 1 | """数据可视化，欧美歌单收藏数量分布情况""" 2 | import numpy as np 3 | import pandas as pd 4 | import matplotlib.pyplot as plt 5 | import time 6 | 7 | 8 | def data_visualization_of_top_10_ea_song_collection_distribution(): 9 | """欧美歌单收藏数量分布情况""" 10 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 11 | 12 | print("正在生成欧美歌单收藏数量分布情况图片...") 13 | 14 | # 输出进度条 15 | t = 60 16 | start = time.perf_counter() 17 | 18 | for i in range(t + 1): 19 | finsh = "▓" * i 20 | need_do = "-" * (t - i) 21 | progress = (i / t) * 100 22 | dur = time.perf_counter() - start 23 | 24 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 25 | 26 | time.sleep(0.02) 27 | 28 | # 对收藏数取对数 29 | dom = [] 30 | for i in df[3]: 31 | dom.append(np.log(int(i.replace('万', '0000')))) 32 | 33 | df['collection'] = dom 34 | 35 | # 设置图片显示属性,字体及大小 36 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 37 | plt.rcParams['font.size'] = 12 38 | plt.rcParams['axes.unicode_minus'] = False 39 | 40 | # 设置图片显示属性 41 | plt.figure(figsize=(16, 8), dpi=80) 42 | ax = plt.subplot(1, 1, 1) 43 | ax.patch.set_color('white') 44 | 45 | # 设置坐标轴属性 46 | lines = plt.gca() 47 | 48 | # 设置坐标轴颜色 49 | lines.spines['right'].set_color('none') 50 | lines.spines['top'].set_color('none') 51 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 52 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 53 | lines.xaxis.set_ticks_position('none') 54 | lines.yaxis.set_ticks_position('none') 55 | 56 | # 绘制直方图,设置直方图颜色 57 | ax.hist(df['collection'], bins=30, alpha=0.7, color=(21/255, 47/255, 71/255)) 58 | ax.set_title('欧美歌单收藏数量分布情况', fontsize=20) 59 | 60 | # 保存图片 61 | plt.savefig('./music_image/top_10_ea_song_collection_distribution.png', dpi=None) 62 | 63 | # 显示图片 64 | plt.show() 65 | 66 | print("\n已生成欧美歌单收藏数量分布情况图片，保存至 music_image/top_10_ea_song_collection_distribution.png") 67 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/top_10_ea_song_playlists.py: -------------------------------------------------------------------------------- 1 | """数据可视化，网易云音乐欧美歌单播放 TOP10""" 2 | import pandas as pd 3 | import matplotlib.pyplot as plt 4 | import time 5 | 6 | 7 | def data_visualization_of_top_10_ea_song_playlists(): 8 | """网易云音乐欧美歌单播放 TOP10""" 9 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 10 | df['play'] = df[4] 11 | 12 | print("正在生成网易云音乐欧美歌单播放 TOP10 图片...") 13 | 14 | # 输出进度条 15 | t = 60 16 | start = time.perf_counter() 17 | 18 | for i in range(t + 1): 19 | finsh = "▓" * i 20 | need_do = "-" * (t - i) 21 | progress = (i / t) * 100 22 | dur = time.perf_counter() - start 23 | 24 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 25 | 26 | time.sleep(0.02) 27 | 28 | # 数据排序 29 | names = df.sort_values(by='play', ascending=False)[0][:10] 30 | plays = df.sort_values(by='play', ascending=False)['play'][:10] 31 | 32 | # 设置显示数据 33 | names = [i for i in names] 34 | names.reverse() 35 | plays = [i for i in plays] 36 | plays.reverse() 37 | data = pd.Series(plays, index=names) 38 | 39 | # 设置图片显示属性,字体及大小 40 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 41 | plt.rcParams['font.size'] = 8 42 | plt.rcParams['axes.unicode_minus'] = False 43 | 44 | # 设置图片显示属性 45 | plt.figure(figsize=(16, 8), dpi=80) 46 | ax = plt.subplot(1, 1, 1) 47 | ax.patch.set_color('white') 48 | 49 | # 设置坐标轴属性 50 | lines = plt.gca() 51 | 52 | # 设置坐标轴颜色 53 | lines.spines['right'].set_color('none') 54 | lines.spines['top'].set_color('none') 55 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 56 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 57 | 58 | # 设置坐标轴刻度 59 | lines.xaxis.set_ticks_position('none') 60 | lines.yaxis.set_ticks_position('none') 61 | 62 | # 绘制柱状图,设置柱状图颜色 63 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(136/255, 43/255, 48/255)) 64 | 65 | # 添加标题,设置字体属性 66 | ax.set_title('网易云音乐欧美歌单播放 TOP10', fontsize=18, fontweight='light') 67 | 68 | # 添加歌单收藏数量文本 69 | for x, y in enumerate(data.values): 70 | num = str(int(y / 10000)) 71 | plt.text(y+1800000, x-0.08, '%s' % (num + '万'), ha='center') 72 | 73 | # 保存图片 74 | plt.savefig('./music_image/top_10_ea_song_playlists.png', dpi=None) 75 | 76 | # 显示图片 77 | plt.show() 78 | 79 | print("\n已生成网易云音乐欧美歌单播放 TOP10 图片，保存至 music_image/top_10_ea_song_playlists.png") 80 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/top_10_ea_song_playlists_distribution.py: -------------------------------------------------------------------------------- 1 | """数据可视化，欧美歌单播放数量分布情况""" 2 | import numpy as np 3 | import pandas as pd 4 | import matplotlib.pyplot as plt 5 | import time 6 | 7 | 8 | def data_visualization_of_top_10_ea_song_playlists_distribution(): 9 | """欧美歌单播放数量分布情况""" 10 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 11 | 12 | print("正在生成欧美歌单播放数量分布情况图片...") 13 | 14 | # 输出进度条 15 | t = 60 16 | start = time.perf_counter() 17 | 18 | for i in range(t + 1): 19 | finsh = "▓" * i 20 | need_do = "-" * (t - i) 21 | progress = (i / t) * 100 22 | dur = time.perf_counter() - start 23 | 24 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 25 | 26 | time.sleep(0.02) 27 | 28 | # 对播放数取对数 29 | dom = [] 30 | for i in df[4]: 31 | dom.append(np.log(i)) 32 | 33 | df['collection'] = dom 34 | 35 | # 设置图片显示属性,字体及大小 36 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 37 | plt.rcParams['font.size'] = 12 38 | plt.rcParams['axes.unicode_minus'] = False 39 | 40 | # 设置图片显示属性 41 | plt.figure(figsize=(16, 8), dpi=80) 42 | ax = plt.subplot(1, 1, 1) 43 | ax.patch.set_color('white') 44 | 45 | # 设置坐标轴属性 46 | lines = plt.gca() 47 | 48 | # 设置坐标轴颜色 49 | lines.spines['right'].set_color('none') 50 | lines.spines['top'].set_color('none') 51 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 52 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 53 | lines.xaxis.set_ticks_position('none') 54 | lines.yaxis.set_ticks_position('none') 55 | 56 | # 绘制直方图,设置直方图颜色 57 | ax.hist(df['collection'], bins=30, alpha=0.7, color=(255/255, 153/255, 0/255)) 58 | ax.set_title('欧美歌单播放数量分布情况', fontsize=20) 59 | 60 | # 保存图片 61 | plt.savefig('./music_image/top_10_ea_song_playlists_distribution.png', dpi=None) 62 | 63 | # 显示图片 64 | plt.show() 65 | 66 | print("\n已生成欧美歌单播放数量分布情况图片，保存至 music_image/top_10_ea_song_playlists_distribution.png") 67 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/top_10_of_ea_song_collection.py: -------------------------------------------------------------------------------- 1 | """数据可视化，网易云音乐欧美歌单收藏 TOP10""" 2 | import pandas as pd 3 | import matplotlib.pyplot as plt 4 | import time 5 | 6 | 7 | def data_visualization_of_top_10_of_ea_song_collection(): 8 | """网易云音乐欧美歌单收藏 TOP10""" 9 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 10 | 11 | print("正在生成网易云音乐欧美歌单收藏 TOP10 图片...") 12 | 13 | # 输出进度条 14 | t = 60 15 | start = time.perf_counter() 16 | 17 | for i in range(t + 1): 18 | finsh = "▓" * i 19 | need_do = "-" * (t - i) 20 | progress = (i / t) * 100 21 | dur = time.perf_counter() - start 22 | 23 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, 24 | finsh, need_do, dur), end="") 25 | 26 | time.sleep(0.02) 27 | 28 | # 数据清洗 29 | dom = [] 30 | for i in df[3]: 31 | dom.append(int(i.replace('万', '0000'))) 32 | 33 | df['collection'] = dom 34 | 35 | # 数据排序 36 | names = df.sort_values(by='collection', ascending=False)[0][:10] 37 | collections = df.sort_values(by='collection', ascending=False)[ 38 | 'collection'][:10] 39 | 40 | # 设置显示数据 41 | names = [i for i in names] 42 | names.reverse() 43 | collections = [i for i in collections] 44 | collections.reverse() 45 | data = pd.Series(collections, index=names) 46 | 47 | # 设置图片显示属性,字体及大小 48 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 49 | plt.rcParams['font.size'] = 8 50 | plt.rcParams['axes.unicode_minus'] = False 51 | 52 | # 设置图片显示属性 53 | plt.figure(figsize=(16, 8), dpi=80) 54 | ax = plt.subplot(1, 1, 1) 55 | ax.patch.set_color('white') 56 | 57 | # 设置坐标轴属性 58 | lines = plt.gca() 59 | 60 | # 设置坐标轴颜色 61 | lines.spines['right'].set_color('none') 62 | lines.spines['top'].set_color('none') 63 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 64 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 65 | 66 | # 设置坐标轴刻度 67 | lines.xaxis.set_ticks_position('none') 68 | lines.yaxis.set_ticks_position('none') 69 | 70 | # 绘制柱状图,设置柱状图颜色 71 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(8/255, 88/255, 121/255)) 72 | 73 | # 添加标题,设置字体属性 74 | ax.set_title('网易云音乐欧美歌单收藏 TOP10', fontsize=18, fontweight='light') 75 | 76 | # 添加歌单收藏数量文本 77 | for x, y in enumerate(data.values): 78 | num = str(y/10000) 79 | plt.text(y+20000, x-0.08, '%s' % (num + '万'), ha='center') 80 | 81 | # 保存图片 82 | plt.savefig('./music_image/top_10_of_ea_song_collection.png', dpi=None) 83 | 84 | # 显示图片 85 | plt.show() 86 | 87 | print("\n已生成网易云音乐欧美歌单收藏 TOP10 图片，保存至 music_image/top_10_of_ea_song_collection.png") 88 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/top_10_of_ea_song_comment.py: -------------------------------------------------------------------------------- 1 | """数据可视化，网易云音乐欧美歌单评论 TOP10""" 2 | import pandas as pd 3 | import matplotlib.pyplot as plt 4 | import time 5 | 6 | 7 | def data_visualization_of_top_10_of_ea_song_comment(): 8 | """网易云音乐欧美歌单评论 TOP10""" 9 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 10 | 11 | print("正在生成网易云音乐欧美歌单评论 TOP10 图片...") 12 | 13 | # 输出进度条 14 | t = 60 15 | start = time.perf_counter() 16 | 17 | for i in range(t + 1): 18 | finsh = "▓" * i 19 | need_do = "-" * (t - i) 20 | progress = (i / t) * 100 21 | dur = time.perf_counter() - start 22 | 23 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 24 | 25 | time.sleep(0.02) 26 | 27 | # 数据清洗 28 | df['love'] = [int(i.replace('评论', '0')) for i in df[6]] 29 | 30 | # 数据排序 31 | names = df.sort_values(by='love', ascending=False)[0][:10] 32 | comments = df.sort_values(by='love', ascending=False)['love'][:10] 33 | 34 | # 设置显示数据 35 | names = [i for i in names] 36 | names.reverse() 37 | comments = [i for i in comments] 38 | comments.reverse() 39 | data = pd.Series(comments, index=names) 40 | 41 | # 设置图片显示属性,字体及大小 42 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 43 | plt.rcParams['font.size'] = 8 44 | plt.rcParams['axes.unicode_minus'] = False 45 | 46 | # 设置图片显示属性 47 | plt.figure(figsize=(16, 8), dpi=80) 48 | ax = plt.subplot(1, 1, 1) 49 | ax.patch.set_color('white') 50 | 51 | # 设置坐标轴属性 52 | lines = plt.gca() 53 | 54 | # 设置坐标轴颜色 55 | lines.spines['right'].set_color('none') 56 | lines.spines['top'].set_color('none') 57 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 58 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 59 | 60 | # 设置坐标轴刻度 61 | lines.xaxis.set_ticks_position('none') 62 | lines.yaxis.set_ticks_position('none') 63 | 64 | # 绘制柱状图,设置柱状图颜色 65 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(160/255, 102/255, 50/255)) 66 | ax.set_title('网易云音乐欧美歌单评论 TOP10', fontsize=18, fontweight='light') 67 | 68 | # 添加歌单评论数量文本 69 | for x, y in enumerate(data.values): 70 | plt.text(y+200, x-0.08, '%s' % y, ha='center') 71 | 72 | # 保存图片 73 | plt.savefig('./music_image/top_10_of_ea_song_comment.png', dpi=None) 74 | 75 | # 显示图片 76 | plt.show() 77 | 78 | print("\n已生成网易云音乐欧美歌单评论 TOP10 图片，保存至 music_image/top_10_of_ea_song_comment.png") 79 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/top_10_song.py: -------------------------------------------------------------------------------- 1 | """数据可视化，歌曲出现次数 Top10""" 2 | import pandas as pd 3 | import matplotlib.pyplot as plt 4 | import time 5 | 6 | 7 | def data_visualization_of_top_10_song(): 8 | """歌曲出现次数 Top10""" 9 | df = pd.read_csv('./music_data/music_detail.csv', header=None, names=['title'], encoding='utf-8-sig') 10 | 11 | print("正在生成歌曲出现次数 Top10 图片...") 12 | 13 | # 输出进度条 14 | t = 60 15 | start = time.perf_counter() 16 | 17 | for i in range(t + 1): 18 | finsh = "▓" * i 19 | need_do = "-" * (t - i) 20 | progress = (i / t) * 100 21 | dur = time.perf_counter() - start 22 | 23 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 24 | 25 | time.sleep(0.02) 26 | 27 | # 数据聚合分组 28 | place_message = df.groupby(['title']) 29 | place_com = place_message['title'].agg(['count']) 30 | place_com.reset_index(inplace=True) 31 | place_com_last = place_com.sort_index() 32 | dom = place_com_last.sort_values('count', ascending=False)[0:10] 33 | 34 | # 设置显示数据 35 | names = [i for i in dom.title] 36 | names.reverse() 37 | nums = [i for i in dom['count']] 38 | nums.reverse() 39 | data = pd.Series(nums, index=names) 40 | 41 | # 设置图片显示属性,字体及大小 42 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 43 | plt.rcParams['font.size'] = 10 44 | plt.rcParams['axes.unicode_minus'] = False 45 | 46 | # 设置图片显示属性 47 | plt.figure(figsize=(16, 8), dpi=80) 48 | ax = plt.subplot(1, 1, 1) 49 | ax.patch.set_color('white') 50 | 51 | # 设置坐标轴属性 52 | lines = plt.gca() 53 | 54 | # 设置坐标轴颜色 55 | lines.spines['right'].set_color('none') 56 | lines.spines['top'].set_color('none') 57 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 58 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 59 | 60 | # 设置坐标轴刻度 61 | lines.xaxis.set_ticks_position('none') 62 | lines.yaxis.set_ticks_position('none') 63 | 64 | # 绘制柱状图,设置柱状图颜色 65 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(16/255, 152/255, 168/255)) 66 | 67 | # 添加标题,设置字体大小 68 | ax.set_title('网易云音乐欧美歌单歌曲 TOP10', fontsize=18, fontweight='light') 69 | 70 | # 添加歌曲出现次数文本 71 | for x, y in enumerate(data.values): 72 | plt.text(y+3.5, x-0.12, '%s' % y, ha='center') 73 | 74 | # 保存图片 75 | plt.savefig('./music_image/top_10_song.png', dpi=None) 76 | 77 | # 显示图片 78 | plt.show() 79 | 80 | print("\n已生成歌曲出现次数 Top10 图片，保存至 music_image/top_10_song.png") 81 | -------------------------------------------------------------------------------- /Python数据分析初探结课项目/NeteaseCloudMusicDataAnalysis/top_10_song_up.py: -------------------------------------------------------------------------------- 1 | """数据可视化，歌单贡献 UP 主 TOP10""" 2 | import pandas as pd 3 | import matplotlib.pyplot as plt 4 | import time 5 | 6 | 7 | def data_visualization_of_top_10_song_up(): 8 | """歌单贡献 UP 主 TOP10""" 9 | df = pd.read_csv('./music_data/music_name.csv', header=None, on_bad_lines=None, names=['url', 'title', 'play', 10 | 'user']) 11 | 12 | print("正在生成歌单贡献 UP 主 TOP10 图片...") 13 | 14 | # 输出进度条 15 | t = 60 16 | start = time.perf_counter() 17 | 18 | for i in range(t + 1): 19 | finsh = "▓" * i 20 | need_do = "-" * (t - i) 21 | progress = (i / t) * 100 22 | dur = time.perf_counter() - start 23 | 24 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 25 | 26 | time.sleep(0.02) 27 | 28 | # 数据聚合分组 29 | place_message = df.groupby(['user']) 30 | place_com = place_message['user'].agg(['count']) 31 | place_com.reset_index(inplace=True) 32 | place_com_last = place_com.sort_index() 33 | dom = place_com_last.sort_values('count', ascending=False)[0:10] 34 | 35 | # 设置显示数据 36 | names = [i for i in dom.user] 37 | names.reverse() 38 | nums = [i for i in dom['count']] 39 | nums.reverse() 40 | data = pd.Series(nums, index=names) 41 | 42 | # 设置图片显示属性,字体及大小 43 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 44 | plt.rcParams['font.size'] = 10 45 | plt.rcParams['axes.unicode_minus'] = False 46 | 47 | # 设置图片显示属性 48 | plt.figure(figsize=(16, 8), dpi=80) 49 | ax = plt.subplot(1, 1, 1) 50 | ax.patch.set_color('white') 51 | 52 | # 设置坐标轴属性 53 | lines = plt.gca() 54 | 55 | # 设置坐标轴颜色 56 | lines.spines['right'].set_color('none') 57 | lines.spines['top'].set_color('none') 58 | lines.spines['left'].set_color((64 / 255, 64 / 255, 64 / 255)) 59 | lines.spines['bottom'].set_color((64 / 255, 64 / 255, 64 / 255)) 60 | 61 | # 设置坐标轴刻度 62 | lines.xaxis.set_ticks_position('none') 63 | lines.yaxis.set_ticks_position('none') 64 | 65 | # 绘制柱状图,设置柱状图颜色 66 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(153 / 255, 0 / 255, 102 / 255)) 67 | 68 | # 添加标题,设置字体大小 69 | ax.set_title('歌单贡献UP主 TOP10', fontsize=18, fontweight='light') 70 | 71 | # 添加歌曲出现次数文本 72 | for x, y in enumerate(data.values): 73 | plt.text(y + 0.3, x - 0.12, '%s' % y, ha='center') 74 | 75 | # 保存图片 76 | plt.savefig('./music_image/top_10_song_up.png', dpi=None) 77 | 78 | # 显示图片 79 | plt.show() 80 | 81 | print("\n已生成歌单贡献 UP 主 TOP10 图片，保存至 music_image/top_10_song_up.png") 82 | -------------------------------------------------------------------------------- /Python数据分析初探项目 基于Python数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022年）.md: -------------------------------------------------------------------------------- 1 |  2 | 3 | # Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022 年） 4 | 5 | 6 | 7 | - [Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022 年）](#python-数据分析初探项目-基于-python-数据可视化的网易云音乐歌单分析系统-大学编程作业tust-天津科技大学-2022-年) 8 | - [一、项目简介](#一-项目简介) 9 | - [二、交流学习](#二-交流学习) 10 | - [Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统](#python-数据分析初探项目-基于-python-数据可视化的网易云音乐歌单分析系统) 11 | - [一、项目简介](#一-项目简介-1) 12 | - [（一）项目背景](#一项目背景) 13 | - [（二）项目过程](#二项目过程) 14 | - [二、项目设计流程图](#二-项目设计流程图) 15 | - [（一）基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构](#一基于-python-数据可视化的网易云音乐歌单分析系统的整体架构) 16 | - [（二）获取歌单索引页的信息](#二获取歌单索引页的信息) 17 | - [（三）获取歌单详情页的信息](#三获取歌单详情页的信息) 18 | - [（四）歌曲出现次数 TOP10](#四歌曲出现次数-top10) 19 | - [（五）网易云音乐欧美歌单播放 TOP10](#五网易云音乐欧美歌单播放-top10) 20 | - [（六）网易云音乐欧美歌单评论 TOP10](#六网易云音乐欧美歌单评论-top10) 21 | - [（七）欧美歌单播放数量分布情况](#七欧美歌单播放数量分布情况) 22 | - [（八）网易云音乐欧美歌单标签图](#八网易云音乐欧美歌单标签图) 23 | - [（九）歌单介绍词云图](#九歌单介绍词云图) 24 | - [三、项目实现代码](#三-项目实现代码) 25 | - [（一）netease_cloud_music_data_analysis.py](#一netease_cloud_music_data_analysispy) 26 | - [（二）music_index.py](#二music_indexpy) 27 | - [（三）music_detail.py](#三music_detailpy) 28 | - [（四）top_10_song.py](#四top_10_songpy) 29 | - [（五）top_10_ea_song_playlists.py](#五top_10_ea_song_playlistspy) 30 | - [（六）top_10_of_ea_song_collection.py](#六top_10_of_ea_song_collectionpy) 31 | - [（七）top_10_of_ea_song_comment.py](#七top_10_of_ea_song_commentpy) 32 | - [（八）top_10_ea_song_collection_distribution.py](#八top_10_ea_song_collection_distributionpy) 33 | - [（九）top_10_ea_song_playlists_distribution.py](#九top_10_ea_song_playlists_distributionpy) 34 | - [（十）label_ea_song.py](#十label_ea_songpy) 35 | - [（十一）music_wordcloud.py](#十一music_wordcloudpy) 36 | - [四、项目分析结果](#四-项目分析结果) 37 | - [（一）歌曲出现次数 TOP10](#一歌曲出现次数-top10) 38 | - [（二）网易云音乐欧美歌单播放 TOP10](#二网易云音乐欧美歌单播放-top10) 39 | - [（三）网易云音乐欧美歌单评论 TOP10](#三网易云音乐欧美歌单评论-top10) 40 | - [（四）欧美歌单播放数量分布情况](#四欧美歌单播放数量分布情况) 41 | - [（五）网易云音乐欧美歌单标签图](#五网易云音乐欧美歌单标签图) 42 | - [（六）歌单介绍词云图](#六歌单介绍词云图) 43 | - [（七）音乐歌单运营分析](#七音乐歌单运营分析) 44 | - [（八）歌单数据可视化的商业价值](#八歌单数据可视化的商业价值) 45 | 46 | 47 | 48 | ## 一、项目简介 49 | 50 | 本基于 Python 数据可视化的网易云音乐歌单分析系统，我使用了 Python 丰富的第三方开源模块，如 numpy, pandas, matplotlib, time, requests, squarify, jieba, wordcloud, bs4 等来制作，实现了对网易云音乐歌单数据的获取，对歌单数据进行可视化分析，得出歌单的评论、收藏、播放、贡献、分布的数量图以及词云，并提出歌单优化的建议。通过这次 Python 数据分析初探项目的实践，我巩固了 Python 的语法知识，熟练应用了各个第三方开源模块，为之后的 Python 数据分析学习打下基础。 51 | 52 | 这个项目是我大三写的，现在回顾已经非常粗糙，分享出来一方面希望可以帮助初学者，另一方面希望能让同学们可以从目前大学中普遍毫无价值的形式主义作业中解脱出来，更加高效地学习优质计算机知识和主流编程技术，一起发扬开源精神，感受互联网技术的美好愿景。 53 | 54 | ## 二、交流学习 55 | 56 | 互联网开源精神需要大家一起互相交流学习，互相支持奉献。欢迎大家与我友好交流。 57 | 58 | 加我 QQ 好友获取所有项目源码和项目文档，感谢大家的支持！ 59 | 60 | # Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统 61 | 62 | ## 一、项目简介 63 | 64 | ### （一）项目背景 65 | 66 | 随着音乐软件的普及，海量的相关数据被创造。在大数据的时代，任何大量的数据一旦被利用起来，将会产生巨大的价值。利用 Python 分析歌曲的相关数据来挖掘客户的需求并更进一步的扩大用户量的例子比比皆是。 67 | 68 | 考虑到现实的可操作性以及 Python 在数据分析和交互、探索性计算以及数据可视化等方面都有非常成熟的库。且经过小组测试可行性，决定利用 Python 对音乐软件歌单进行分析。 69 | 70 | ### （二）项目过程 71 | 72 | 此次项目利用 Python 对网易云音乐歌单数据的获取，对歌单数据进行可视化分析。得出歌单的评论、收藏、播放、贡献、分布的数量图以及词云，并提出歌单优化的建议。 73 | 74 | 项目利用爬虫对数据获取，后对其进行数据清洗，最终进行数据可视化。在分析过程中使用 numpy, pandas, matplotlib, time, requests, squarify, jieba, wordcloud, bs4 第三方模块，最后以柱状图，词云图 以及标签图来展示歌曲收藏量，播放量等相关分析结果并结合相关数据优化歌单播放量。 75 | 76 | 最后我们实现了项目，并对项目进行了测试。 77 | 78 | ![歌单索引网页调试分析](https://img-blog.csdnimg.cn/c6276a3a0331453dae158f1572f1cf54.png) 79 | 80 | _图 1 歌单索引网页调试分析_ 81 | 82 | ![歌单详情网页调试分析](https://img-blog.csdnimg.cn/26ff6304d0d848dab8261210d1856654.png) 83 | 84 | _图 2 歌单详情网页调试分析_ 85 | 86 | ## 二、项目设计流程图 87 | 88 | ### （一）基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构 89 | 90 | ![基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构图](https://img-blog.csdnimg.cn/02217f4369b349c782114e840233cb28.png) 91 | 92 | _图 3 基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构图_ 93 | 94 | ### （二）获取歌单索引页的信息 95 | 96 | ![获取歌单索引页的信息的流程图](https://img-blog.csdnimg.cn/a61f009c068b4993b79db59403e3f001.png) 97 | 98 | _图 4 获取歌单索引页的信息的流程图_ 99 | 100 | ### （三）获取歌单详情页的信息 101 | 102 | ![获取歌单详情页的信息的流程图](https://img-blog.csdnimg.cn/e8a4a784439d401f93a5d0fa17385c12.png) 103 | 104 | _图 5 获取歌单详情页的信息的流程图_ 105 | 106 | ### （四）歌曲出现次数 TOP10 107 | 108 | ![歌曲出现次数 TOP10 的流程图](https://img-blog.csdnimg.cn/5cb4e04b1b084f29be41b9336bfe844b.png) 109 | 110 | _图 6 歌曲出现次数 TOP10 的流程图_ 111 | 112 | ### （五）网易云音乐欧美歌单播放 TOP10 113 | 114 | ![网易云音乐欧美歌单播放 TOP10 的流程图](https://img-blog.csdnimg.cn/7a57fcaf67ce4165b680159d8cda0c45.png) 115 | 116 | _图 7 网易云音乐欧美歌单播放 TOP10 的流程图_ 117 | 118 | ### （六）网易云音乐欧美歌单评论 TOP10 119 | 120 | ![网易云音乐欧美歌单评论 TOP10 的流程图](https://img-blog.csdnimg.cn/44776c5c03cc4f6abb67f970b0de6b69.png) 121 | 122 | _图 8 网易云音乐欧美歌单评论 TOP10 的流程图_ 123 | 124 | ### （七）欧美歌单播放数量分布情况 125 | 126 | ![欧美歌单播放数量分布情况的流程图](https://img-blog.csdnimg.cn/ead274d7704848cc97d233575a1ac18a.png) 127 | 128 | _图 9 欧美歌单播放数量分布情况的流程图_ 129 | 130 | ## （八）网易云音乐欧美歌单标签图 131 | 132 | ![网易云音乐欧美歌单标签图的流程图](https://img-blog.csdnimg.cn/21cbe8d1f80b48d0a01d7610676482fa.png) 133 | 134 | _图 10 网易云音乐欧美歌单标签图的流程图_ 135 | 136 | ### （九）歌单介绍词云图 137 | 138 | ![歌单介绍词云图的流程图](https://img-blog.csdnimg.cn/6f6486015c0443a18fb9bf88af5f0946.png) 139 | 140 | 图 11 歌单介绍词云图的流程图 141 | 142 | ## 三、项目实现代码 143 | 144 | ### （一）netease_cloud_music_data_analysis.py 145 | 146 | ```python 147 | import os 148 | 149 | from music_index import get_data_of_music_list_index_page 150 | from music_detail import get_data_of_music_list_detail_page 151 | from top_10_song import data_visualization_of_top_10_song 152 | from top_10_song_up import data_visualization_of_top_10_song_up 153 | from top_10_ea_song_playlists import data_visualization_of_top_10_ea_song_playlists 154 | from top_10_of_ea_song_collection import data_visualization_of_top_10_of_ea_song_collection 155 | from top_10_of_ea_song_comment import data_visualization_of_top_10_of_ea_song_comment 156 | from top_10_ea_song_collection_distribution import data_visualization_of_top_10_ea_song_collection_distribution 157 | from top_10_ea_song_playlists_distribution import data_visualization_of_top_10_ea_song_playlists_distribution 158 | from label_ea_song import data_visualization_of_label_ea_song 159 | from music_wordcloud import data_visualization_of_music_wordcloud 160 | 161 | 162 | def menu(): 163 | """网易云音乐数据分析系统菜单""" 164 | print("欢迎使用网易云音乐数据分析系统！(^▽^ )") 165 | print("---------------------------------------------") 166 | print("") 167 | print(" 【网易云音乐数据分析系统】 ") 168 | print("") 169 | print(" A.获取歌单索引页的信息") 170 | print(" B.获取歌单详情页的信息") 171 | print(" C.生成歌曲出现次数 Top10 图片") 172 | print(" D.生成歌单贡献 UP 主 TOP10 图片") 173 | print(" E.生成网易云音乐欧美歌单播放 TOP10 图片") 174 | print(" F.生成网易云音乐欧美歌单收藏 TOP10 图片") 175 | print(" G.生成网易云音乐欧美歌单评论 TOP10 图片") 176 | print(" H.生成欧美歌单收藏数量分布情况图片") 177 | print(" I.生成欧美歌单播放数量分布情况图片") 178 | print(" J.生成网易云音乐欧美歌单标签图片") 179 | print(" K.生成歌单介绍词云图片") 180 | print("") 181 | print("---------------------------------------------") 182 | print("请输入您要进行的操作（输入 quit 退出！）：") 183 | 184 | 185 | def key_down(): 186 | """网易云音乐数据分析系统功能交互""" 187 | option = input() 188 | 189 | if option == 'quit' or option == 'QUIT': 190 | print("已退出！\n\n") 191 | input() 192 | 193 | exit(0) 194 | elif option == 'a' or option == 'A': 195 | # 获取歌单索引页的信息 196 | get_data_of_music_list_index_page() 197 | 198 | return 199 | elif option == 'b' or option == 'B': 200 | # 获取歌单详情页的信息 201 | get_data_of_music_list_detail_page() 202 | 203 | return 204 | elif option == 'c' or option == 'C': 205 | # 生成歌曲出现次数 Top10 图片 206 | data_visualization_of_top_10_song() 207 | 208 | return 209 | elif option == 'd' or option == 'D': 210 | # 生成歌单贡献 UP 主 TOP10 图片 211 | data_visualization_of_top_10_song_up() 212 | 213 | return 214 | elif option == 'e' or option == 'E': 215 | # 生成网易云音乐欧美歌单播放 TOP10 图片 216 | data_visualization_of_top_10_ea_song_playlists() 217 | 218 | return 219 | elif option == 'f' or option == 'F': 220 | # 生成网易云音乐欧美歌单收藏 TOP10 图片 221 | data_visualization_of_top_10_of_ea_song_collection() 222 | 223 | return 224 | elif option == 'g' or option == 'G': 225 | # 生成网易云音乐欧美歌单评论 TOP10 图片 226 | data_visualization_of_top_10_of_ea_song_comment() 227 | 228 | return 229 | elif option == 'h' or option == 'H': 230 | # 生成欧美歌单收藏数量分布情况图片 231 | data_visualization_of_top_10_ea_song_collection_distribution() 232 | 233 | return 234 | elif option == 'i' or option == 'I': 235 | # 生成欧美歌单播放数量分布情况图片 236 | data_visualization_of_top_10_ea_song_playlists_distribution() 237 | 238 | return 239 | elif option == 'j' or option == 'J': 240 | # 生成网易云音乐欧美歌单标签图片 241 | data_visualization_of_label_ea_song() 242 | 243 | return 244 | elif option == 'k' or option == 'K': 245 | # 生成歌单介绍词云图片 246 | data_visualization_of_music_wordcloud() 247 | 248 | return 249 | else: 250 | print("选择错误，请重新输入！\n\n") 251 | input() 252 | 253 | return 254 | 255 | 256 | if __name__ == '__main__': 257 | """运行界面及功能代码""" 258 | while True: 259 | menu() 260 | key_down() 261 | 262 | # 清屏 263 | os.system('cls') 264 | ``` 265 | 266 | ### （二）music_index.py 267 | 268 | ```python 269 | """数据获取，获取歌单索引页的信息""" 270 | from bs4 import BeautifulSoup 271 | import requests 272 | import time 273 | 274 | 275 | def get_data_of_music_list_index_page(): 276 | """获取歌单索引页的信息""" 277 | headers = { 278 | 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' 279 | 'Chrome/63.0.3239.132 Safari/537.36 ' 280 | } 281 | 282 | print("正在获取歌单索引页的信息...") 283 | 284 | # 输出进度条 285 | t = 60 286 | start = time.perf_counter() 287 | 288 | for i in range(t + 1): 289 | finsh = "▓" * i 290 | need_do = "-" * (t - i) 291 | progress = (i / t) * 100 292 | dur = time.perf_counter() - start 293 | 294 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 295 | 296 | time.sleep(0.02) 297 | 298 | for i in range(0, 1330, 35): 299 | # print('\r', i, end='', flush=True) 300 | 301 | time.sleep(2) 302 | 303 | url = 'https://music.163.com/discover/playlist/?cat=欧美&order=hot&limit=35&offset=' + str(i) 304 | response = requests.get(url=url, headers=headers) 305 | html = response.text 306 | soup = BeautifulSoup(html, 'html.parser') 307 | 308 | # 获取包含歌单详情页网址的标签 309 | ids = soup.select('.dec a') 310 | 311 | # 获取包含歌单索引页信息的标签 312 | lis = soup.select('#m-pl-container li') 313 | # print('\r', len(lis), end='', flush=True) 314 | 315 | for j in range(len(lis)): 316 | # 获取歌单详情页地址 317 | url = ids[j]['href'] 318 | 319 | # 获取歌单标题,替换英文分割符 320 | title = ids[j]['title'].replace(',', '，') 321 | 322 | # 获取歌单播放量 323 | play = lis[j].select('.nb')[0].get_text() 324 | 325 | # 获取歌单贡献者名字 326 | user = lis[j].select('p')[1].select('a')[0].get_text() 327 | 328 | # 输出歌单索引页信息 329 | print('\r', url, title, play, user, end='', flush=True) 330 | 331 | # 将索引页写入CSV文件中 332 | with open('./music_data/music_list.csv', 'a+', encoding='utf-8-sig') as f: 333 | f.write(url + ',' + title + ',' + play + ',' + user + '\n') 334 | 335 | print("\n已获取歌单索引页的信息，保存至 music_data/music_list.csv") 336 | ``` 337 | 338 | ### （三）music_detail.py 339 | 340 | ```python 341 | """数据获取，获取歌单详情页的信息""" 342 | from bs4 import BeautifulSoup 343 | import pandas as pd 344 | import requests 345 | import time 346 | 347 | 348 | def get_data_of_music_list_detail_page(): 349 | """获取歌单详情页的信息""" 350 | df = pd.read_csv('./music_data/music_list.csv', header=None, on_bad_lines=None, names=['url', 'title', 'play', 351 | 'user']) 352 | 353 | headers = { 354 | 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' 355 | 'Chrome/63.0.3239.132 Safari/537.36 ' 356 | } 357 | 358 | print("正在获取歌单详情页的信息...") 359 | 360 | # 输出进度条 361 | t = 60 362 | start = time.perf_counter() 363 | 364 | for i in range(t + 1): 365 | finsh = "▓" * i 366 | need_do = "-" * (t - i) 367 | progress = (i / t) * 100 368 | dur = time.perf_counter() - start 369 | 370 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 371 | 372 | time.sleep(0.02) 373 | 374 | for i in df['url']: 375 | time.sleep(2) 376 | 377 | url = 'https://music.163.com' + i 378 | response = requests.get(url=url, headers=headers) 379 | html = response.text 380 | soup = BeautifulSoup(html, 'html.parser') 381 | 382 | # 获取歌单标题 383 | title = soup.select('h2')[0].get_text().replace(',', '，') 384 | 385 | # 获取标签 386 | tags = [] 387 | tags_message = soup.select('.u-tag i') 388 | 389 | for p in tags_message: 390 | tags.append(p.get_text()) 391 | 392 | # 对标签进行格式化 393 | if len(tags) > 1: 394 | tag = '-'.join(tags) 395 | else: 396 | tag = tags[0] 397 | 398 | # 获取歌单介绍 399 | if soup.select('#album-desc-more'): 400 | text = soup.select('#album-desc-more')[0].get_text().replace('\n', '').replace(',', '，') 401 | else: 402 | text = '无' 403 | 404 | # 获取歌单收藏量 405 | collection = soup.select('#content-operation i')[1].get_text().replace('(', '').replace(')', '') 406 | 407 | # 歌单播放量 408 | play = soup.select('.s-fc6')[0].get_text() 409 | 410 | # 歌单内歌曲数 411 | songs = soup.select('#playlist-track-count')[0].get_text() 412 | 413 | # 歌单评论数 414 | comments = soup.select('#cnt_comment_count')[0].get_text() 415 | 416 | # 输出歌单详情页信息 417 | print('\r', title, tag, text, collection, play, songs, comments, end='', flush=True) 418 | 419 | # 将详情页信息写入CSV文件中 420 | with open('./music_data/music_detail.csv', 'a+', encoding='utf-8-sig') as f: 421 | f.write(title + ',' + tag + ',' + text + ',' + collection + ',' + play + ',' + songs + ',' + comments + 422 | '\n') 423 | 424 | # 获取歌单内歌曲名称 425 | li = soup.select('.f-hide li a') 426 | 427 | for j in li: 428 | with open('./music_data/music_name.csv', 'a+', encoding='utf-8-sig') as f: 429 | f.write(j.get_text() + '\n') 430 | 431 | print("\n已获取歌单详情页的信息，保存至 music_data/music_name.csv") 432 | ``` 433 | 434 | ### （四）top_10_song.py 435 | 436 | ```python 437 | """数据可视化，歌曲出现次数 Top10""" 438 | import pandas as pd 439 | import matplotlib.pyplot as plt 440 | import time 441 | 442 | 443 | def data_visualization_of_top_10_song(): 444 | """歌曲出现次数 Top10""" 445 | df = pd.read_csv('./music_data/music_detail.csv', header=None, names=['title'], encoding='utf-8-sig') 446 | 447 | print("正在生成歌曲出现次数 Top10 图片...") 448 | 449 | # 输出进度条 450 | t = 60 451 | start = time.perf_counter() 452 | 453 | for i in range(t + 1): 454 | finsh = "▓" * i 455 | need_do = "-" * (t - i) 456 | progress = (i / t) * 100 457 | dur = time.perf_counter() - start 458 | 459 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 460 | 461 | time.sleep(0.02) 462 | 463 | # 数据聚合分组 464 | place_message = df.groupby(['title']) 465 | place_com = place_message['title'].agg(['count']) 466 | place_com.reset_index(inplace=True) 467 | place_com_last = place_com.sort_index() 468 | dom = place_com_last.sort_values('count', ascending=False)[0:10] 469 | 470 | # 设置显示数据 471 | names = [i for i in dom.title] 472 | names.reverse() 473 | nums = [i for i in dom['count']] 474 | nums.reverse() 475 | data = pd.Series(nums, index=names) 476 | 477 | # 设置图片显示属性,字体及大小 478 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 479 | plt.rcParams['font.size'] = 10 480 | plt.rcParams['axes.unicode_minus'] = False 481 | 482 | # 设置图片显示属性 483 | plt.figure(figsize=(16, 8), dpi=80) 484 | ax = plt.subplot(1, 1, 1) 485 | ax.patch.set_color('white') 486 | 487 | # 设置坐标轴属性 488 | lines = plt.gca() 489 | 490 | # 设置坐标轴颜色 491 | lines.spines['right'].set_color('none') 492 | lines.spines['top'].set_color('none') 493 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 494 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 495 | 496 | # 设置坐标轴刻度 497 | lines.xaxis.set_ticks_position('none') 498 | lines.yaxis.set_ticks_position('none') 499 | 500 | # 绘制柱状图,设置柱状图颜色 501 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(16/255, 152/255, 168/255)) 502 | 503 | # 添加标题,设置字体大小 504 | ax.set_title('网易云音乐欧美歌单歌曲 TOP10', fontsize=18, fontweight='light') 505 | 506 | # 添加歌曲出现次数文本 507 | for x, y in enumerate(data.values): 508 | plt.text(y+3.5, x-0.12, '%s' % y, ha='center') 509 | 510 | # 保存图片 511 | plt.savefig('./music_image/top_10_song.png', dpi=None) 512 | 513 | # 显示图片 514 | plt.show() 515 | 516 | print("\n已生成歌曲出现次数 Top10 图片，保存至 music_image/top_10_song.png") 517 | ``` 518 | 519 | ### （五）top_10_ea_song_playlists.py 520 | 521 | ```python 522 | """数据可视化，网易云音乐欧美歌单播放 TOP10""" 523 | import pandas as pd 524 | import matplotlib.pyplot as plt 525 | import time 526 | 527 | 528 | def data_visualization_of_top_10_ea_song_playlists(): 529 | """网易云音乐欧美歌单播放 TOP10""" 530 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 531 | df['play'] = df[4] 532 | 533 | print("正在生成网易云音乐欧美歌单播放 TOP10 图片...") 534 | 535 | # 输出进度条 536 | t = 60 537 | start = time.perf_counter() 538 | 539 | for i in range(t + 1): 540 | finsh = "▓" * i 541 | need_do = "-" * (t - i) 542 | progress = (i / t) * 100 543 | dur = time.perf_counter() - start 544 | 545 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 546 | 547 | time.sleep(0.02) 548 | 549 | # 数据排序 550 | names = df.sort_values(by='play', ascending=False)[0][:10] 551 | plays = df.sort_values(by='play', ascending=False)['play'][:10] 552 | 553 | # 设置显示数据 554 | names = [i for i in names] 555 | names.reverse() 556 | plays = [i for i in plays] 557 | plays.reverse() 558 | data = pd.Series(plays, index=names) 559 | 560 | # 设置图片显示属性,字体及大小 561 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 562 | plt.rcParams['font.size'] = 8 563 | plt.rcParams['axes.unicode_minus'] = False 564 | 565 | # 设置图片显示属性 566 | plt.figure(figsize=(16, 8), dpi=80) 567 | ax = plt.subplot(1, 1, 1) 568 | ax.patch.set_color('white') 569 | 570 | # 设置坐标轴属性 571 | lines = plt.gca() 572 | 573 | # 设置坐标轴颜色 574 | lines.spines['right'].set_color('none') 575 | lines.spines['top'].set_color('none') 576 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 577 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 578 | 579 | # 设置坐标轴刻度 580 | lines.xaxis.set_ticks_position('none') 581 | lines.yaxis.set_ticks_position('none') 582 | 583 | # 绘制柱状图,设置柱状图颜色 584 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(136/255, 43/255, 48/255)) 585 | 586 | # 添加标题,设置字体属性 587 | ax.set_title('网易云音乐欧美歌单播放 TOP10', fontsize=18, fontweight='light') 588 | 589 | # 添加歌单收藏数量文本 590 | for x, y in enumerate(data.values): 591 | num = str(int(y / 10000)) 592 | plt.text(y+1800000, x-0.08, '%s' % (num + '万'), ha='center') 593 | 594 | # 保存图片 595 | plt.savefig('./music_image/top_10_ea_song_playlists.png', dpi=None) 596 | 597 | # 显示图片 598 | plt.show() 599 | 600 | print("\n已生成网易云音乐欧美歌单播放 TOP10 图片，保存至 music_image/top_10_ea_song_playlists.png") 601 | ``` 602 | 603 | ### （六）top_10_of_ea_song_collection.py 604 | 605 | ```python 606 | """数据可视化，网易云音乐欧美歌单收藏 TOP10""" 607 | import pandas as pd 608 | import matplotlib.pyplot as plt 609 | import time 610 | 611 | 612 | def data_visualization_of_top_10_of_ea_song_collection(): 613 | """网易云音乐欧美歌单收藏 TOP10""" 614 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 615 | 616 | print("正在生成网易云音乐欧美歌单收藏 TOP10 图片...") 617 | 618 | # 输出进度条 619 | t = 60 620 | start = time.perf_counter() 621 | 622 | for i in range(t + 1): 623 | finsh = "▓" * i 624 | need_do = "-" * (t - i) 625 | progress = (i / t) * 100 626 | dur = time.perf_counter() - start 627 | 628 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, 629 | finsh, need_do, dur), end="") 630 | 631 | time.sleep(0.02) 632 | 633 | # 数据清洗 634 | dom = [] 635 | for i in df[3]: 636 | dom.append(int(i.replace('万', '0000'))) 637 | 638 | df['collection'] = dom 639 | 640 | # 数据排序 641 | names = df.sort_values(by='collection', ascending=False)[0][:10] 642 | collections = df.sort_values(by='collection', ascending=False)[ 643 | 'collection'][:10] 644 | 645 | # 设置显示数据 646 | names = [i for i in names] 647 | names.reverse() 648 | collections = [i for i in collections] 649 | collections.reverse() 650 | data = pd.Series(collections, index=names) 651 | 652 | # 设置图片显示属性,字体及大小 653 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 654 | plt.rcParams['font.size'] = 8 655 | plt.rcParams['axes.unicode_minus'] = False 656 | 657 | # 设置图片显示属性 658 | plt.figure(figsize=(16, 8), dpi=80) 659 | ax = plt.subplot(1, 1, 1) 660 | ax.patch.set_color('white') 661 | 662 | # 设置坐标轴属性 663 | lines = plt.gca() 664 | 665 | # 设置坐标轴颜色 666 | lines.spines['right'].set_color('none') 667 | lines.spines['top'].set_color('none') 668 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 669 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 670 | 671 | # 设置坐标轴刻度 672 | lines.xaxis.set_ticks_position('none') 673 | lines.yaxis.set_ticks_position('none') 674 | 675 | # 绘制柱状图,设置柱状图颜色 676 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(8/255, 88/255, 121/255)) 677 | 678 | # 添加标题,设置字体属性 679 | ax.set_title('网易云音乐欧美歌单收藏 TOP10', fontsize=18, fontweight='light') 680 | 681 | # 添加歌单收藏数量文本 682 | for x, y in enumerate(data.values): 683 | num = str(y/10000) 684 | plt.text(y+20000, x-0.08, '%s' % (num + '万'), ha='center') 685 | 686 | # 保存图片 687 | plt.savefig('./music_image/top_10_of_ea_song_collection.png', dpi=None) 688 | 689 | # 显示图片 690 | plt.show() 691 | 692 | print("\n已生成网易云音乐欧美歌单收藏 TOP10 图片，保存至 music_image/top_10_of_ea_song_collection.png") 693 | ``` 694 | 695 | ### （七）top_10_of_ea_song_comment.py 696 | 697 | ```python 698 | """数据可视化，网易云音乐欧美歌单评论 TOP10""" 699 | import pandas as pd 700 | import matplotlib.pyplot as plt 701 | import time 702 | 703 | 704 | def data_visualization_of_top_10_of_ea_song_comment(): 705 | """网易云音乐欧美歌单评论 TOP10""" 706 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 707 | 708 | print("正在生成网易云音乐欧美歌单评论 TOP10 图片...") 709 | 710 | # 输出进度条 711 | t = 60 712 | start = time.perf_counter() 713 | 714 | for i in range(t + 1): 715 | finsh = "▓" * i 716 | need_do = "-" * (t - i) 717 | progress = (i / t) * 100 718 | dur = time.perf_counter() - start 719 | 720 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 721 | 722 | time.sleep(0.02) 723 | 724 | # 数据清洗 725 | df['love'] = [int(i.replace('评论', '0')) for i in df[6]] 726 | 727 | # 数据排序 728 | names = df.sort_values(by='love', ascending=False)[0][:10] 729 | comments = df.sort_values(by='love', ascending=False)['love'][:10] 730 | 731 | # 设置显示数据 732 | names = [i for i in names] 733 | names.reverse() 734 | comments = [i for i in comments] 735 | comments.reverse() 736 | data = pd.Series(comments, index=names) 737 | 738 | # 设置图片显示属性,字体及大小 739 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 740 | plt.rcParams['font.size'] = 8 741 | plt.rcParams['axes.unicode_minus'] = False 742 | 743 | # 设置图片显示属性 744 | plt.figure(figsize=(16, 8), dpi=80) 745 | ax = plt.subplot(1, 1, 1) 746 | ax.patch.set_color('white') 747 | 748 | # 设置坐标轴属性 749 | lines = plt.gca() 750 | 751 | # 设置坐标轴颜色 752 | lines.spines['right'].set_color('none') 753 | lines.spines['top'].set_color('none') 754 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 755 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 756 | 757 | # 设置坐标轴刻度 758 | lines.xaxis.set_ticks_position('none') 759 | lines.yaxis.set_ticks_position('none') 760 | 761 | # 绘制柱状图,设置柱状图颜色 762 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(160/255, 102/255, 50/255)) 763 | ax.set_title('网易云音乐欧美歌单评论 TOP10', fontsize=18, fontweight='light') 764 | 765 | # 添加歌单评论数量文本 766 | for x, y in enumerate(data.values): 767 | plt.text(y+200, x-0.08, '%s' % y, ha='center') 768 | 769 | # 保存图片 770 | plt.savefig('./music_image/top_10_of_ea_song_comment.png', dpi=None) 771 | 772 | # 显示图片 773 | plt.show() 774 | 775 | print("\n已生成网易云音乐欧美歌单评论 TOP10 图片，保存至 music_image/top_10_of_ea_song_comment.png") 776 | ``` 777 | 778 | ### （八）top_10_ea_song_collection_distribution.py 779 | 780 | ```python 781 | """数据可视化，欧美歌单收藏数量分布情况""" 782 | import numpy as np 783 | import pandas as pd 784 | import matplotlib.pyplot as plt 785 | import time 786 | 787 | 788 | def data_visualization_of_top_10_ea_song_collection_distribution(): 789 | """欧美歌单收藏数量分布情况""" 790 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 791 | 792 | print("正在生成欧美歌单收藏数量分布情况图片...") 793 | 794 | # 输出进度条 795 | t = 60 796 | start = time.perf_counter() 797 | 798 | for i in range(t + 1): 799 | finsh = "▓" * i 800 | need_do = "-" * (t - i) 801 | progress = (i / t) * 100 802 | dur = time.perf_counter() - start 803 | 804 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 805 | 806 | time.sleep(0.02) 807 | 808 | # 对收藏数取对数 809 | dom = [] 810 | for i in df[3]: 811 | dom.append(np.log(int(i.replace('万', '0000')))) 812 | 813 | df['collection'] = dom 814 | 815 | # 设置图片显示属性,字体及大小 816 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 817 | plt.rcParams['font.size'] = 12 818 | plt.rcParams['axes.unicode_minus'] = False 819 | 820 | # 设置图片显示属性 821 | plt.figure(figsize=(16, 8), dpi=80) 822 | ax = plt.subplot(1, 1, 1) 823 | ax.patch.set_color('white') 824 | 825 | # 设置坐标轴属性 826 | lines = plt.gca() 827 | 828 | # 设置坐标轴颜色 829 | lines.spines['right'].set_color('none') 830 | lines.spines['top'].set_color('none') 831 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 832 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 833 | lines.xaxis.set_ticks_position('none') 834 | lines.yaxis.set_ticks_position('none') 835 | 836 | # 绘制直方图,设置直方图颜色 837 | ax.hist(df['collection'], bins=30, alpha=0.7, color=(21/255, 47/255, 71/255)) 838 | ax.set_title('欧美歌单收藏数量分布情况', fontsize=20) 839 | 840 | # 保存图片 841 | plt.savefig('./music_image/top_10_ea_song_collection_distribution.png', dpi=None) 842 | 843 | # 显示图片 844 | plt.show() 845 | 846 | print("\n已生成欧美歌单收藏数量分布情况图片，保存至 music_image/top_10_ea_song_collection_distribution.png") 847 | ``` 848 | 849 | ### （九）top_10_ea_song_playlists_distribution.py 850 | 851 | ```python 852 | """数据可视化，欧美歌单播放数量分布情况""" 853 | import numpy as np 854 | import pandas as pd 855 | import matplotlib.pyplot as plt 856 | import time 857 | 858 | 859 | def data_visualization_of_top_10_ea_song_playlists_distribution(): 860 | """欧美歌单播放数量分布情况""" 861 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 862 | 863 | print("正在生成欧美歌单播放数量分布情况图片...") 864 | 865 | # 输出进度条 866 | t = 60 867 | start = time.perf_counter() 868 | 869 | for i in range(t + 1): 870 | finsh = "▓" * i 871 | need_do = "-" * (t - i) 872 | progress = (i / t) * 100 873 | dur = time.perf_counter() - start 874 | 875 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 876 | 877 | time.sleep(0.02) 878 | 879 | # 对播放数取对数 880 | dom = [] 881 | for i in df[4]: 882 | dom.append(np.log(i)) 883 | 884 | df['collection'] = dom 885 | 886 | # 设置图片显示属性,字体及大小 887 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 888 | plt.rcParams['font.size'] = 12 889 | plt.rcParams['axes.unicode_minus'] = False 890 | 891 | # 设置图片显示属性 892 | plt.figure(figsize=(16, 8), dpi=80) 893 | ax = plt.subplot(1, 1, 1) 894 | ax.patch.set_color('white') 895 | 896 | # 设置坐标轴属性 897 | lines = plt.gca() 898 | 899 | # 设置坐标轴颜色 900 | lines.spines['right'].set_color('none') 901 | lines.spines['top'].set_color('none') 902 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 903 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 904 | lines.xaxis.set_ticks_position('none') 905 | lines.yaxis.set_ticks_position('none') 906 | 907 | # 绘制直方图,设置直方图颜色 908 | ax.hist(df['collection'], bins=30, alpha=0.7, color=(255/255, 153/255, 0/255)) 909 | ax.set_title('欧美歌单播放数量分布情况', fontsize=20) 910 | 911 | # 保存图片 912 | plt.savefig('./music_image/top_10_ea_song_playlists_distribution.png', dpi=None) 913 | 914 | # 显示图片 915 | plt.show() 916 | 917 | print("\n已生成欧美歌单播放数量分布情况图片，保存至 music_image/top_10_ea_song_playlists_distribution.png") 918 | ``` 919 | 920 | ### （十）label_ea_song.py 921 | 922 | ```python 923 | """数据可视化，网易云音乐欧美歌单标签图""" 924 | import squarify 925 | import pandas as pd 926 | import matplotlib.pyplot as plt 927 | import time 928 | 929 | 930 | def data_visualization_of_label_ea_song(): 931 | """网易云音乐欧美歌单标签图""" 932 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 933 | 934 | print("正在生成网易云音乐欧美歌单标签图片...") 935 | 936 | # 输出进度条 937 | t = 60 938 | start = time.perf_counter() 939 | 940 | for i in range(t + 1): 941 | finsh = "▓" * i 942 | need_do = "-" * (t - i) 943 | progress = (i / t) * 100 944 | dur = time.perf_counter() - start 945 | 946 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 947 | 948 | time.sleep(0.02) 949 | 950 | # 处理标签信息 951 | tags = [] 952 | dom2 = [] 953 | 954 | for i in df[1]: 955 | c = i.split('-') 956 | 957 | for j in c: 958 | if j not in tags: 959 | tags.append(j) 960 | else: 961 | continue 962 | 963 | for item in tags: 964 | num = 0 965 | 966 | for i in df[1]: 967 | type2 = i.split('-') 968 | 969 | for j in range(len(type2)): 970 | if type2[j] == item: 971 | num += 1 972 | else: 973 | continue 974 | 975 | dom2.append(num) 976 | 977 | # 数据创建 978 | data = {'tags': tags, 'num': dom2} 979 | frame = pd.DataFrame(data) 980 | df1 = frame.sort_values(by='num', ascending=False) 981 | name = df1['tags'][:10] 982 | income = df1['num'][:10] 983 | 984 | # 绘图 details 985 | colors = ['#993333', '#CC9966', '#333333', '#663366', '#003366', '#009966', '#FF6600', '#FF0033', '#009999', 986 | '#333366'] 987 | plot = squarify.plot(sizes=income, label=name, color=colors, alpha=1, value=income, edgecolor='white', 988 | linewidth=1.5) 989 | 990 | # 设置图片显示属性,字体及大小 991 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 992 | plt.rcParams['font.size'] = 8 993 | plt.rcParams['axes.unicode_minus'] = False 994 | 995 | # 设置标签大小为 1 996 | plt.rc('font', size=6) 997 | 998 | # 设置标题大小 999 | plot.set_title('网易云音乐欧美歌单标签图', fontsize=13, fontweight='light') 1000 | 1001 | # 除坐标轴 1002 | plt.axis('off') 1003 | 1004 | # 除上边框和右边框刻度 1005 | plt.tick_params(top=False, right=False) 1006 | 1007 | # 保存图片 1008 | plt.savefig('./music_image/label_ea_song.png', dpi=None) 1009 | 1010 | # 显示图片 1011 | plt.show() 1012 | 1013 | print("\n已生成网易云音乐欧美歌单标签图片，保存至 music_image/label_ea_song.png") 1014 | ``` 1015 | 1016 | ### （十一）music_wordcloud.py 1017 | 1018 | ```python 1019 | """数据可视化，歌单介绍词云图""" 1020 | from wordcloud import WordCloud, ImageColorGenerator 1021 | import matplotlib.pyplot as plt 1022 | import pandas as pd 1023 | import jieba 1024 | import time 1025 | 1026 | 1027 | def data_visualization_of_music_wordcloud(): 1028 | """歌单介绍词云图""" 1029 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 1030 | text = '' 1031 | 1032 | print("正在生成歌单介绍词云图片...") 1033 | 1034 | # 输出进度条 1035 | t = 60 1036 | start = time.perf_counter() 1037 | 1038 | for i in range(t + 1): 1039 | finsh = "▓" * i 1040 | need_do = "-" * (t - i) 1041 | progress = (i / t) * 100 1042 | dur = time.perf_counter() - start 1043 | 1044 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 1045 | 1046 | time.sleep(0.02) 1047 | 1048 | for line in df[2]: 1049 | text += ' '.join(jieba.cut(line, cut_all=False)) 1050 | 1051 | background_image = plt.imread('./music_image/background_image.jpg') 1052 | 1053 | stopwords = set('') 1054 | stopwords.update( 1055 | ['封面', 'none介绍', '介绍', '歌单', '歌曲', '我们', '自己', '没有', '就是', '可以', '知道', '一起', '不是', 1056 | '因为', '什么', '时候', '还是', '如果', '不要', '那些', '那么', '那个', '所有', '一样', '一直', '不会', '现在', 1057 | '他们', '这样', '最后', '这个', '只是', '有些', '其实', '开始', '曾经', '所以', '不能', '你们', '已经', '后来', 1058 | '一切', '一定', '这些', '一些', '只有', '还有']) 1059 | 1060 | wc = WordCloud( 1061 | background_color='white', 1062 | mask=background_image, 1063 | font_path='./font_resources/STZHONGS.ttf', 1064 | max_words=2000, 1065 | max_font_size=150, 1066 | random_state=30, 1067 | stopwords=stopwords 1068 | ) 1069 | wc.generate_from_text(text) 1070 | 1071 | # 看看词频高的有哪些,把无用信息去除 1072 | process_word = WordCloud.process_text(wc, text) 1073 | sort = sorted(process_word.items(), key=lambda e: e[1], reverse=True) 1074 | # print(sort[:50]) 1075 | 1076 | img_colors = ImageColorGenerator(background_image) 1077 | wc.recolor(color_func=img_colors) 1078 | plt.imshow(wc) 1079 | plt.axis('off') 1080 | 1081 | # 保存图片 1082 | wc.to_file("./music_image/music_wordcloud.png") 1083 | 1084 | # 显示图片 1085 | plt.show() 1086 | 1087 | print("\n已生成歌单介绍词云图片，保存至 music_image/music_wordcloud.png") 1088 | ``` 1089 | 1090 | ## 四、项目分析结果 1091 | 1092 | 网易云用户是很习惯创建歌单的一个用户群体，很多用户也是通过歌单了解到一些歌曲。一个网易云用户甚至自己一个人就创建上百个歌单，我们爬取了网易云欧美歌单的数据，制作了以下表格。 1093 | 1094 | ### （一）歌曲出现次数 TOP10 1095 | 1096 | ![网易云音乐欧美歌单歌曲 TOP10](https://img-blog.csdnimg.cn/60848bcfa7604d2a94cf971c53c45271.png) 1097 | 1098 | _图 12 网易云音乐欧美歌单歌曲 TOP10_ 1099 | 1100 | 我们获得了网易云音乐欧美歌单中的 TOP10 歌曲，相信熟悉欧美歌曲的小伙伴们对这些歌都很熟悉，他们曾经或许就出现在推荐给你的歌单中。 1101 | 1102 | ### （二）网易云音乐欧美歌单播放 TOP10 1103 | 1104 | ![网易云音乐欧美歌单播放 TOP10](https://img-blog.csdnimg.cn/b9f0a6ad102945b1bd3464ef34b3464b.png) 1105 | 1106 | _图 13 网易云音乐欧美歌单播放 TOP10_ 1107 | 1108 | 这是欧美歌单播放量前十排行榜，第一名拥有高达 4 亿的播放量，可见欧美歌曲是非常令人欢迎的。在歌单中统计中我们可以看到旋律和节奏是很多欧美音乐爱好者们比较看重和喜欢的。 1109 | 1110 | ### （三）网易云音乐欧美歌单评论 TOP10 1111 | 1112 | ![网易云音乐欧美歌单评论 TOP10](https://img-blog.csdnimg.cn/28a770d38dda4011bccecd6c92892df0.png) 1113 | 1114 | _图 14 网易云音乐欧美歌单评论 TOP10_ 1115 | 1116 | 可以看到歌单【定制 最懂你的欧美推荐 每日更新 35 首】的评论数量最多。这可能与他日更与定制的性质有关。可以看到，很多热门的歌单其评论通常也很多。这个榜单中的歌单在上一个热门歌单的榜单也能找到。 1117 | 1118 | ### （四）欧美歌单播放数量分布情况 1119 | 1120 | ![欧美歌单播放数量分布情况](https://img-blog.csdnimg.cn/82261d3f81c44b43a124c326498484f1.png) 1121 | 1122 | _图 15 欧美歌单播放数量分布情况_ 1123 | 1124 | 将播放数做对数处理，使得能直观看出歌单播放数的分布。 1125 | 1126 | 歌单播放数主要分布在 0-1000 万。 1127 | 1128 | 其中 ln(10000000) = 16。 1129 | 1130 | ### （五）网易云音乐欧美歌单标签图 1131 | 1132 | ![网易云音乐欧美歌单标签图](https://img-blog.csdnimg.cn/b3f608d308fd4e1b81bb9fccddcb4141.png) 1133 | 1134 | _图 16 网易云音乐欧美歌单标签图_ 1135 | 1136 | 我们还找到了这些歌单的标签情况，既然是欧美歌单，【欧美】自然就占大头，几乎一半。我们还可以看到【电子】和【流行】这两大类也是非常多，【欧美流行】和【欧美电子】近两年在网易云用户中越来越火爆，特别是【欧美电子】，不少青年已经是电子音乐的忠实粉丝。 1137 | 1138 | ### （六）歌单介绍词云图 1139 | 1140 | ![歌单介绍词云图](https://img-blog.csdnimg.cn/934472aff3b6407fba8ba73b6b1bd7fe.png) 1141 | 1142 | _图 17 歌单介绍词云图_ 1143 | 1144 | 歌单介绍词云图，这些词包括一个歌单的风格，背景还有故事。或许你曾经是因为哪一个词打动了你，让你收藏的这份歌单。与歌曲产生共鸣。 1145 | 1146 | ### （七）音乐歌单运营分析 1147 | 1148 | 歌单有两种形式，一种是由官方创建的歌单，另一种是由用户自主创建的歌单，在网易云中，我们收藏倾听的大多来自个人用户。而歌单的运营不论是对个人还是官方都是有意义的。 1149 | 1150 | 很多用户是以歌单作为入口来了解音乐的，很少主动的的持续的去搜索音乐，所以歌单是否丰富，歌单的品质是否足够好，决定了用户使用的频率和时间。用户能够获取到越多越好的好歌单，就意味着这个音乐平台更有价值。 1151 | 1152 | 对于个人而言，创造令很多人满意的歌单，让个人获得关注，更高的成就感，进而创造更好的精品歌单。 1153 | 1154 | 所以我们基于以上的分析，做出了一个关于欧美歌单的运营分析： 1155 | 1156 | 在歌单内容方面，图 15 网易云音乐欧美歌单标签图里，我们可以看出，流行类标签和电子标签占比大约 50%。以标签分类实行个性化推荐，可以让歌单更容易被找到，曝光，便于管理。 1157 | 1158 | 另外我们的歌单可以向这两个热门的方向靠拢，面向受众面广的人群，可以获得可观的流量。再加上电子音乐的兴起，越来越优秀的电子音乐出现，可以丰富我们的歌单。 1159 | 1160 | 在歌单标题方面，歌单相当于一篇文章，歌单的标题可以吸引听众的注意力，让他们进来了解歌单，收听歌单。在歌单播放量 TOP10 和歌单评论数量 TOP10 中，我们区分出以下几类： 1161 | 1162 | 在特殊标志式方面，在前十的几个歌单名称中我们可以看到"【】"，"|"等特殊字符，这些特殊字符可以吸引听众的目光，强调自己歌单的亮点。 1163 | 1164 | 在强吸引式方面，使用"精选"，"10w+"，"专属"等字眼，驱使听众点击。 1165 | 1166 | 在结论式方面使用，"热血燃向 | 提神醒脑防嗜睡型 BGM" 等字眼，驱使听众点击。 1167 | 1168 | 综上所述，一份歌单成功离不开标题、歌曲风格、乃至歌曲数。只有平衡好其中的因素，才能使其播放量达到预期。 1169 | 1170 | ### （八）歌单数据可视化的商业价值 1171 | 1172 | 歌单数据可视化可以帮助音乐公司更好地理解消费者喜好，并为消费者提供更符合他们喜好的歌单。 1173 | 1174 | 此外，歌单数据可视化还可以帮助音乐公司更好地分析歌单中的信息，并利用这些信息来决定如何定价、营销和分销音乐。 1175 | 1176 | 因此，歌单数据可视化具有一定的商业价值，可以为音乐公司提供重要的市场信息。 1177 | -------------------------------------------------------------------------------- /Python数据分析初探项目 基于Python数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022年）.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MYXHcode/Python-data-analysis-preliminary-project-data-visualization-music-list-analysis-system-TUST-2022/dced390c5181b10233757e8a15b5a2a08daf91b8/Python数据分析初探项目 基于Python数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022年）.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | 3 | # Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022 年） 4 | 5 | 6 | 7 | - [Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统 大学编程作业（TUST 天津科技大学 2022 年）](#python-数据分析初探项目-基于-python-数据可视化的网易云音乐歌单分析系统-大学编程作业tust-天津科技大学-2022-年) 8 | - [一、项目简介](#一-项目简介) 9 | - [二、交流学习](#二-交流学习) 10 | - [Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统](#python-数据分析初探项目-基于-python-数据可视化的网易云音乐歌单分析系统) 11 | - [一、项目简介](#一-项目简介-1) 12 | - [（一）项目背景](#一项目背景) 13 | - [（二）项目过程](#二项目过程) 14 | - [二、项目设计流程图](#二-项目设计流程图) 15 | - [（一）基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构](#一基于-python-数据可视化的网易云音乐歌单分析系统的整体架构) 16 | - [（二）获取歌单索引页的信息](#二获取歌单索引页的信息) 17 | - [（三）获取歌单详情页的信息](#三获取歌单详情页的信息) 18 | - [（四）歌曲出现次数 TOP10](#四歌曲出现次数-top10) 19 | - [（五）网易云音乐欧美歌单播放 TOP10](#五网易云音乐欧美歌单播放-top10) 20 | - [（六）网易云音乐欧美歌单评论 TOP10](#六网易云音乐欧美歌单评论-top10) 21 | - [（七）欧美歌单播放数量分布情况](#七欧美歌单播放数量分布情况) 22 | - [（八）网易云音乐欧美歌单标签图](#八网易云音乐欧美歌单标签图) 23 | - [（九）歌单介绍词云图](#九歌单介绍词云图) 24 | - [三、项目实现代码](#三-项目实现代码) 25 | - [（一）netease_cloud_music_data_analysis.py](#一netease_cloud_music_data_analysispy) 26 | - [（二）music_index.py](#二music_indexpy) 27 | - [（三）music_detail.py](#三music_detailpy) 28 | - [（四）top_10_song.py](#四top_10_songpy) 29 | - [（五）top_10_ea_song_playlists.py](#五top_10_ea_song_playlistspy) 30 | - [（六）top_10_of_ea_song_collection.py](#六top_10_of_ea_song_collectionpy) 31 | - [（七）top_10_of_ea_song_comment.py](#七top_10_of_ea_song_commentpy) 32 | - [（八）top_10_ea_song_collection_distribution.py](#八top_10_ea_song_collection_distributionpy) 33 | - [（九）top_10_ea_song_playlists_distribution.py](#九top_10_ea_song_playlists_distributionpy) 34 | - [（十）label_ea_song.py](#十label_ea_songpy) 35 | - [（十一）music_wordcloud.py](#十一music_wordcloudpy) 36 | - [四、项目分析结果](#四-项目分析结果) 37 | - [（一）歌曲出现次数 TOP10](#一歌曲出现次数-top10) 38 | - [（二）网易云音乐欧美歌单播放 TOP10](#二网易云音乐欧美歌单播放-top10) 39 | - [（三）网易云音乐欧美歌单评论 TOP10](#三网易云音乐欧美歌单评论-top10) 40 | - [（四）欧美歌单播放数量分布情况](#四欧美歌单播放数量分布情况) 41 | - [（五）网易云音乐欧美歌单标签图](#五网易云音乐欧美歌单标签图) 42 | - [（六）歌单介绍词云图](#六歌单介绍词云图) 43 | - [（七）音乐歌单运营分析](#七音乐歌单运营分析) 44 | - [（八）歌单数据可视化的商业价值](#八歌单数据可视化的商业价值) 45 | 46 | 47 | 48 | ## 一、项目简介 49 | 50 | 本基于 Python 数据可视化的网易云音乐歌单分析系统，我使用了 Python 丰富的第三方开源模块，如 numpy, pandas, matplotlib, time, requests, squarify, jieba, wordcloud, bs4 等来制作，实现了对网易云音乐歌单数据的获取，对歌单数据进行可视化分析，得出歌单的评论、收藏、播放、贡献、分布的数量图以及词云，并提出歌单优化的建议。通过这次 Python 数据分析初探项目的实践，我巩固了 Python 的语法知识，熟练应用了各个第三方开源模块，为之后的 Python 数据分析学习打下基础。 51 | 52 | 这个项目是我大三写的，现在回顾已经非常粗糙，分享出来一方面希望可以帮助初学者，另一方面希望能让同学们可以从目前大学中普遍毫无价值的形式主义作业中解脱出来，更加高效地学习优质计算机知识和主流编程技术，一起发扬开源精神，感受互联网技术的美好愿景。 53 | 54 | ## 二、交流学习 55 | 56 | 互联网开源精神需要大家一起互相交流学习，互相支持奉献。欢迎大家与我友好交流。 57 | 58 | 加我 QQ 好友获取所有项目源码和项目文档，感谢大家的支持！ 59 | 60 | # Python 数据分析初探项目 基于 Python 数据可视化的网易云音乐歌单分析系统 61 | 62 | ## 一、项目简介 63 | 64 | ### （一）项目背景 65 | 66 | 随着音乐软件的普及，海量的相关数据被创造。在大数据的时代，任何大量的数据一旦被利用起来，将会产生巨大的价值。利用 Python 分析歌曲的相关数据来挖掘客户的需求并更进一步的扩大用户量的例子比比皆是。 67 | 68 | 考虑到现实的可操作性以及 Python 在数据分析和交互、探索性计算以及数据可视化等方面都有非常成熟的库。且经过小组测试可行性，决定利用 Python 对音乐软件歌单进行分析。 69 | 70 | ### （二）项目过程 71 | 72 | 此次项目利用 Python 对网易云音乐歌单数据的获取，对歌单数据进行可视化分析。得出歌单的评论、收藏、播放、贡献、分布的数量图以及词云，并提出歌单优化的建议。 73 | 74 | 项目利用爬虫对数据获取，后对其进行数据清洗，最终进行数据可视化。在分析过程中使用 numpy, pandas, matplotlib, time, requests, squarify, jieba, wordcloud, bs4 第三方模块，最后以柱状图，词云图 以及标签图来展示歌曲收藏量，播放量等相关分析结果并结合相关数据优化歌单播放量。 75 | 76 | 最后我们实现了项目，并对项目进行了测试。 77 | 78 | ![歌单索引网页调试分析](https://img-blog.csdnimg.cn/c6276a3a0331453dae158f1572f1cf54.png) 79 | 80 | _图 1 歌单索引网页调试分析_ 81 | 82 | ![歌单详情网页调试分析](https://img-blog.csdnimg.cn/26ff6304d0d848dab8261210d1856654.png) 83 | 84 | _图 2 歌单详情网页调试分析_ 85 | 86 | ## 二、项目设计流程图 87 | 88 | ### （一）基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构 89 | 90 | ![基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构图](https://img-blog.csdnimg.cn/02217f4369b349c782114e840233cb28.png) 91 | 92 | _图 3 基于 Python 数据可视化的网易云音乐歌单分析系统的整体架构图_ 93 | 94 | ### （二）获取歌单索引页的信息 95 | 96 | ![获取歌单索引页的信息的流程图](https://img-blog.csdnimg.cn/a61f009c068b4993b79db59403e3f001.png) 97 | 98 | _图 4 获取歌单索引页的信息的流程图_ 99 | 100 | ### （三）获取歌单详情页的信息 101 | 102 | ![获取歌单详情页的信息的流程图](https://img-blog.csdnimg.cn/e8a4a784439d401f93a5d0fa17385c12.png) 103 | 104 | _图 5 获取歌单详情页的信息的流程图_ 105 | 106 | ### （四）歌曲出现次数 TOP10 107 | 108 | ![歌曲出现次数 TOP10 的流程图](https://img-blog.csdnimg.cn/5cb4e04b1b084f29be41b9336bfe844b.png) 109 | 110 | _图 6 歌曲出现次数 TOP10 的流程图_ 111 | 112 | ### （五）网易云音乐欧美歌单播放 TOP10 113 | 114 | ![网易云音乐欧美歌单播放 TOP10 的流程图](https://img-blog.csdnimg.cn/7a57fcaf67ce4165b680159d8cda0c45.png) 115 | 116 | _图 7 网易云音乐欧美歌单播放 TOP10 的流程图_ 117 | 118 | ### （六）网易云音乐欧美歌单评论 TOP10 119 | 120 | ![网易云音乐欧美歌单评论 TOP10 的流程图](https://img-blog.csdnimg.cn/44776c5c03cc4f6abb67f970b0de6b69.png) 121 | 122 | _图 8 网易云音乐欧美歌单评论 TOP10 的流程图_ 123 | 124 | ### （七）欧美歌单播放数量分布情况 125 | 126 | ![欧美歌单播放数量分布情况的流程图](https://img-blog.csdnimg.cn/ead274d7704848cc97d233575a1ac18a.png) 127 | 128 | _图 9 欧美歌单播放数量分布情况的流程图_ 129 | 130 | ## （八）网易云音乐欧美歌单标签图 131 | 132 | ![网易云音乐欧美歌单标签图的流程图](https://img-blog.csdnimg.cn/21cbe8d1f80b48d0a01d7610676482fa.png) 133 | 134 | _图 10 网易云音乐欧美歌单标签图的流程图_ 135 | 136 | ### （九）歌单介绍词云图 137 | 138 | ![歌单介绍词云图的流程图](https://img-blog.csdnimg.cn/6f6486015c0443a18fb9bf88af5f0946.png) 139 | 140 | 图 11 歌单介绍词云图的流程图 141 | 142 | ## 三、项目实现代码 143 | 144 | ### （一）netease_cloud_music_data_analysis.py 145 | 146 | ```python 147 | import os 148 | 149 | from music_index import get_data_of_music_list_index_page 150 | from music_detail import get_data_of_music_list_detail_page 151 | from top_10_song import data_visualization_of_top_10_song 152 | from top_10_song_up import data_visualization_of_top_10_song_up 153 | from top_10_ea_song_playlists import data_visualization_of_top_10_ea_song_playlists 154 | from top_10_of_ea_song_collection import data_visualization_of_top_10_of_ea_song_collection 155 | from top_10_of_ea_song_comment import data_visualization_of_top_10_of_ea_song_comment 156 | from top_10_ea_song_collection_distribution import data_visualization_of_top_10_ea_song_collection_distribution 157 | from top_10_ea_song_playlists_distribution import data_visualization_of_top_10_ea_song_playlists_distribution 158 | from label_ea_song import data_visualization_of_label_ea_song 159 | from music_wordcloud import data_visualization_of_music_wordcloud 160 | 161 | 162 | def menu(): 163 | """网易云音乐数据分析系统菜单""" 164 | print("欢迎使用网易云音乐数据分析系统！(^▽^ )") 165 | print("---------------------------------------------") 166 | print("") 167 | print(" 【网易云音乐数据分析系统】 ") 168 | print("") 169 | print(" A.获取歌单索引页的信息") 170 | print(" B.获取歌单详情页的信息") 171 | print(" C.生成歌曲出现次数 Top10 图片") 172 | print(" D.生成歌单贡献 UP 主 TOP10 图片") 173 | print(" E.生成网易云音乐欧美歌单播放 TOP10 图片") 174 | print(" F.生成网易云音乐欧美歌单收藏 TOP10 图片") 175 | print(" G.生成网易云音乐欧美歌单评论 TOP10 图片") 176 | print(" H.生成欧美歌单收藏数量分布情况图片") 177 | print(" I.生成欧美歌单播放数量分布情况图片") 178 | print(" J.生成网易云音乐欧美歌单标签图片") 179 | print(" K.生成歌单介绍词云图片") 180 | print("") 181 | print("---------------------------------------------") 182 | print("请输入您要进行的操作（输入 quit 退出！）：") 183 | 184 | 185 | def key_down(): 186 | """网易云音乐数据分析系统功能交互""" 187 | option = input() 188 | 189 | if option == 'quit' or option == 'QUIT': 190 | print("已退出！\n\n") 191 | input() 192 | 193 | exit(0) 194 | elif option == 'a' or option == 'A': 195 | # 获取歌单索引页的信息 196 | get_data_of_music_list_index_page() 197 | 198 | return 199 | elif option == 'b' or option == 'B': 200 | # 获取歌单详情页的信息 201 | get_data_of_music_list_detail_page() 202 | 203 | return 204 | elif option == 'c' or option == 'C': 205 | # 生成歌曲出现次数 Top10 图片 206 | data_visualization_of_top_10_song() 207 | 208 | return 209 | elif option == 'd' or option == 'D': 210 | # 生成歌单贡献 UP 主 TOP10 图片 211 | data_visualization_of_top_10_song_up() 212 | 213 | return 214 | elif option == 'e' or option == 'E': 215 | # 生成网易云音乐欧美歌单播放 TOP10 图片 216 | data_visualization_of_top_10_ea_song_playlists() 217 | 218 | return 219 | elif option == 'f' or option == 'F': 220 | # 生成网易云音乐欧美歌单收藏 TOP10 图片 221 | data_visualization_of_top_10_of_ea_song_collection() 222 | 223 | return 224 | elif option == 'g' or option == 'G': 225 | # 生成网易云音乐欧美歌单评论 TOP10 图片 226 | data_visualization_of_top_10_of_ea_song_comment() 227 | 228 | return 229 | elif option == 'h' or option == 'H': 230 | # 生成欧美歌单收藏数量分布情况图片 231 | data_visualization_of_top_10_ea_song_collection_distribution() 232 | 233 | return 234 | elif option == 'i' or option == 'I': 235 | # 生成欧美歌单播放数量分布情况图片 236 | data_visualization_of_top_10_ea_song_playlists_distribution() 237 | 238 | return 239 | elif option == 'j' or option == 'J': 240 | # 生成网易云音乐欧美歌单标签图片 241 | data_visualization_of_label_ea_song() 242 | 243 | return 244 | elif option == 'k' or option == 'K': 245 | # 生成歌单介绍词云图片 246 | data_visualization_of_music_wordcloud() 247 | 248 | return 249 | else: 250 | print("选择错误，请重新输入！\n\n") 251 | input() 252 | 253 | return 254 | 255 | 256 | if __name__ == '__main__': 257 | """运行界面及功能代码""" 258 | while True: 259 | menu() 260 | key_down() 261 | 262 | # 清屏 263 | os.system('cls') 264 | ``` 265 | 266 | ### （二）music_index.py 267 | 268 | ```python 269 | """数据获取，获取歌单索引页的信息""" 270 | from bs4 import BeautifulSoup 271 | import requests 272 | import time 273 | 274 | 275 | def get_data_of_music_list_index_page(): 276 | """获取歌单索引页的信息""" 277 | headers = { 278 | 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' 279 | 'Chrome/63.0.3239.132 Safari/537.36 ' 280 | } 281 | 282 | print("正在获取歌单索引页的信息...") 283 | 284 | # 输出进度条 285 | t = 60 286 | start = time.perf_counter() 287 | 288 | for i in range(t + 1): 289 | finsh = "▓" * i 290 | need_do = "-" * (t - i) 291 | progress = (i / t) * 100 292 | dur = time.perf_counter() - start 293 | 294 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 295 | 296 | time.sleep(0.02) 297 | 298 | for i in range(0, 1330, 35): 299 | # print('\r', i, end='', flush=True) 300 | 301 | time.sleep(2) 302 | 303 | url = 'https://music.163.com/discover/playlist/?cat=欧美&order=hot&limit=35&offset=' + str(i) 304 | response = requests.get(url=url, headers=headers) 305 | html = response.text 306 | soup = BeautifulSoup(html, 'html.parser') 307 | 308 | # 获取包含歌单详情页网址的标签 309 | ids = soup.select('.dec a') 310 | 311 | # 获取包含歌单索引页信息的标签 312 | lis = soup.select('#m-pl-container li') 313 | # print('\r', len(lis), end='', flush=True) 314 | 315 | for j in range(len(lis)): 316 | # 获取歌单详情页地址 317 | url = ids[j]['href'] 318 | 319 | # 获取歌单标题,替换英文分割符 320 | title = ids[j]['title'].replace(',', '，') 321 | 322 | # 获取歌单播放量 323 | play = lis[j].select('.nb')[0].get_text() 324 | 325 | # 获取歌单贡献者名字 326 | user = lis[j].select('p')[1].select('a')[0].get_text() 327 | 328 | # 输出歌单索引页信息 329 | print('\r', url, title, play, user, end='', flush=True) 330 | 331 | # 将索引页写入CSV文件中 332 | with open('./music_data/music_list.csv', 'a+', encoding='utf-8-sig') as f: 333 | f.write(url + ',' + title + ',' + play + ',' + user + '\n') 334 | 335 | print("\n已获取歌单索引页的信息，保存至 music_data/music_list.csv") 336 | ``` 337 | 338 | ### （三）music_detail.py 339 | 340 | ```python 341 | """数据获取，获取歌单详情页的信息""" 342 | from bs4 import BeautifulSoup 343 | import pandas as pd 344 | import requests 345 | import time 346 | 347 | 348 | def get_data_of_music_list_detail_page(): 349 | """获取歌单详情页的信息""" 350 | df = pd.read_csv('./music_data/music_list.csv', header=None, on_bad_lines=None, names=['url', 'title', 'play', 351 | 'user']) 352 | 353 | headers = { 354 | 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' 355 | 'Chrome/63.0.3239.132 Safari/537.36 ' 356 | } 357 | 358 | print("正在获取歌单详情页的信息...") 359 | 360 | # 输出进度条 361 | t = 60 362 | start = time.perf_counter() 363 | 364 | for i in range(t + 1): 365 | finsh = "▓" * i 366 | need_do = "-" * (t - i) 367 | progress = (i / t) * 100 368 | dur = time.perf_counter() - start 369 | 370 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 371 | 372 | time.sleep(0.02) 373 | 374 | for i in df['url']: 375 | time.sleep(2) 376 | 377 | url = 'https://music.163.com' + i 378 | response = requests.get(url=url, headers=headers) 379 | html = response.text 380 | soup = BeautifulSoup(html, 'html.parser') 381 | 382 | # 获取歌单标题 383 | title = soup.select('h2')[0].get_text().replace(',', '，') 384 | 385 | # 获取标签 386 | tags = [] 387 | tags_message = soup.select('.u-tag i') 388 | 389 | for p in tags_message: 390 | tags.append(p.get_text()) 391 | 392 | # 对标签进行格式化 393 | if len(tags) > 1: 394 | tag = '-'.join(tags) 395 | else: 396 | tag = tags[0] 397 | 398 | # 获取歌单介绍 399 | if soup.select('#album-desc-more'): 400 | text = soup.select('#album-desc-more')[0].get_text().replace('\n', '').replace(',', '，') 401 | else: 402 | text = '无' 403 | 404 | # 获取歌单收藏量 405 | collection = soup.select('#content-operation i')[1].get_text().replace('(', '').replace(')', '') 406 | 407 | # 歌单播放量 408 | play = soup.select('.s-fc6')[0].get_text() 409 | 410 | # 歌单内歌曲数 411 | songs = soup.select('#playlist-track-count')[0].get_text() 412 | 413 | # 歌单评论数 414 | comments = soup.select('#cnt_comment_count')[0].get_text() 415 | 416 | # 输出歌单详情页信息 417 | print('\r', title, tag, text, collection, play, songs, comments, end='', flush=True) 418 | 419 | # 将详情页信息写入CSV文件中 420 | with open('./music_data/music_detail.csv', 'a+', encoding='utf-8-sig') as f: 421 | f.write(title + ',' + tag + ',' + text + ',' + collection + ',' + play + ',' + songs + ',' + comments + 422 | '\n') 423 | 424 | # 获取歌单内歌曲名称 425 | li = soup.select('.f-hide li a') 426 | 427 | for j in li: 428 | with open('./music_data/music_name.csv', 'a+', encoding='utf-8-sig') as f: 429 | f.write(j.get_text() + '\n') 430 | 431 | print("\n已获取歌单详情页的信息，保存至 music_data/music_name.csv") 432 | ``` 433 | 434 | ### （四）top_10_song.py 435 | 436 | ```python 437 | """数据可视化，歌曲出现次数 Top10""" 438 | import pandas as pd 439 | import matplotlib.pyplot as plt 440 | import time 441 | 442 | 443 | def data_visualization_of_top_10_song(): 444 | """歌曲出现次数 Top10""" 445 | df = pd.read_csv('./music_data/music_detail.csv', header=None, names=['title'], encoding='utf-8-sig') 446 | 447 | print("正在生成歌曲出现次数 Top10 图片...") 448 | 449 | # 输出进度条 450 | t = 60 451 | start = time.perf_counter() 452 | 453 | for i in range(t + 1): 454 | finsh = "▓" * i 455 | need_do = "-" * (t - i) 456 | progress = (i / t) * 100 457 | dur = time.perf_counter() - start 458 | 459 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 460 | 461 | time.sleep(0.02) 462 | 463 | # 数据聚合分组 464 | place_message = df.groupby(['title']) 465 | place_com = place_message['title'].agg(['count']) 466 | place_com.reset_index(inplace=True) 467 | place_com_last = place_com.sort_index() 468 | dom = place_com_last.sort_values('count', ascending=False)[0:10] 469 | 470 | # 设置显示数据 471 | names = [i for i in dom.title] 472 | names.reverse() 473 | nums = [i for i in dom['count']] 474 | nums.reverse() 475 | data = pd.Series(nums, index=names) 476 | 477 | # 设置图片显示属性,字体及大小 478 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 479 | plt.rcParams['font.size'] = 10 480 | plt.rcParams['axes.unicode_minus'] = False 481 | 482 | # 设置图片显示属性 483 | plt.figure(figsize=(16, 8), dpi=80) 484 | ax = plt.subplot(1, 1, 1) 485 | ax.patch.set_color('white') 486 | 487 | # 设置坐标轴属性 488 | lines = plt.gca() 489 | 490 | # 设置坐标轴颜色 491 | lines.spines['right'].set_color('none') 492 | lines.spines['top'].set_color('none') 493 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 494 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 495 | 496 | # 设置坐标轴刻度 497 | lines.xaxis.set_ticks_position('none') 498 | lines.yaxis.set_ticks_position('none') 499 | 500 | # 绘制柱状图,设置柱状图颜色 501 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(16/255, 152/255, 168/255)) 502 | 503 | # 添加标题,设置字体大小 504 | ax.set_title('网易云音乐欧美歌单歌曲 TOP10', fontsize=18, fontweight='light') 505 | 506 | # 添加歌曲出现次数文本 507 | for x, y in enumerate(data.values): 508 | plt.text(y+3.5, x-0.12, '%s' % y, ha='center') 509 | 510 | # 保存图片 511 | plt.savefig('./music_image/top_10_song.png', dpi=None) 512 | 513 | # 显示图片 514 | plt.show() 515 | 516 | print("\n已生成歌曲出现次数 Top10 图片，保存至 music_image/top_10_song.png") 517 | ``` 518 | 519 | ### （五）top_10_ea_song_playlists.py 520 | 521 | ```python 522 | """数据可视化，网易云音乐欧美歌单播放 TOP10""" 523 | import pandas as pd 524 | import matplotlib.pyplot as plt 525 | import time 526 | 527 | 528 | def data_visualization_of_top_10_ea_song_playlists(): 529 | """网易云音乐欧美歌单播放 TOP10""" 530 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 531 | df['play'] = df[4] 532 | 533 | print("正在生成网易云音乐欧美歌单播放 TOP10 图片...") 534 | 535 | # 输出进度条 536 | t = 60 537 | start = time.perf_counter() 538 | 539 | for i in range(t + 1): 540 | finsh = "▓" * i 541 | need_do = "-" * (t - i) 542 | progress = (i / t) * 100 543 | dur = time.perf_counter() - start 544 | 545 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 546 | 547 | time.sleep(0.02) 548 | 549 | # 数据排序 550 | names = df.sort_values(by='play', ascending=False)[0][:10] 551 | plays = df.sort_values(by='play', ascending=False)['play'][:10] 552 | 553 | # 设置显示数据 554 | names = [i for i in names] 555 | names.reverse() 556 | plays = [i for i in plays] 557 | plays.reverse() 558 | data = pd.Series(plays, index=names) 559 | 560 | # 设置图片显示属性,字体及大小 561 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 562 | plt.rcParams['font.size'] = 8 563 | plt.rcParams['axes.unicode_minus'] = False 564 | 565 | # 设置图片显示属性 566 | plt.figure(figsize=(16, 8), dpi=80) 567 | ax = plt.subplot(1, 1, 1) 568 | ax.patch.set_color('white') 569 | 570 | # 设置坐标轴属性 571 | lines = plt.gca() 572 | 573 | # 设置坐标轴颜色 574 | lines.spines['right'].set_color('none') 575 | lines.spines['top'].set_color('none') 576 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 577 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 578 | 579 | # 设置坐标轴刻度 580 | lines.xaxis.set_ticks_position('none') 581 | lines.yaxis.set_ticks_position('none') 582 | 583 | # 绘制柱状图,设置柱状图颜色 584 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(136/255, 43/255, 48/255)) 585 | 586 | # 添加标题,设置字体属性 587 | ax.set_title('网易云音乐欧美歌单播放 TOP10', fontsize=18, fontweight='light') 588 | 589 | # 添加歌单收藏数量文本 590 | for x, y in enumerate(data.values): 591 | num = str(int(y / 10000)) 592 | plt.text(y+1800000, x-0.08, '%s' % (num + '万'), ha='center') 593 | 594 | # 保存图片 595 | plt.savefig('./music_image/top_10_ea_song_playlists.png', dpi=None) 596 | 597 | # 显示图片 598 | plt.show() 599 | 600 | print("\n已生成网易云音乐欧美歌单播放 TOP10 图片，保存至 music_image/top_10_ea_song_playlists.png") 601 | ``` 602 | 603 | ### （六）top_10_of_ea_song_collection.py 604 | 605 | ```python 606 | """数据可视化，网易云音乐欧美歌单收藏 TOP10""" 607 | import pandas as pd 608 | import matplotlib.pyplot as plt 609 | import time 610 | 611 | 612 | def data_visualization_of_top_10_of_ea_song_collection(): 613 | """网易云音乐欧美歌单收藏 TOP10""" 614 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 615 | 616 | print("正在生成网易云音乐欧美歌单收藏 TOP10 图片...") 617 | 618 | # 输出进度条 619 | t = 60 620 | start = time.perf_counter() 621 | 622 | for i in range(t + 1): 623 | finsh = "▓" * i 624 | need_do = "-" * (t - i) 625 | progress = (i / t) * 100 626 | dur = time.perf_counter() - start 627 | 628 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, 629 | finsh, need_do, dur), end="") 630 | 631 | time.sleep(0.02) 632 | 633 | # 数据清洗 634 | dom = [] 635 | for i in df[3]: 636 | dom.append(int(i.replace('万', '0000'))) 637 | 638 | df['collection'] = dom 639 | 640 | # 数据排序 641 | names = df.sort_values(by='collection', ascending=False)[0][:10] 642 | collections = df.sort_values(by='collection', ascending=False)[ 643 | 'collection'][:10] 644 | 645 | # 设置显示数据 646 | names = [i for i in names] 647 | names.reverse() 648 | collections = [i for i in collections] 649 | collections.reverse() 650 | data = pd.Series(collections, index=names) 651 | 652 | # 设置图片显示属性,字体及大小 653 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 654 | plt.rcParams['font.size'] = 8 655 | plt.rcParams['axes.unicode_minus'] = False 656 | 657 | # 设置图片显示属性 658 | plt.figure(figsize=(16, 8), dpi=80) 659 | ax = plt.subplot(1, 1, 1) 660 | ax.patch.set_color('white') 661 | 662 | # 设置坐标轴属性 663 | lines = plt.gca() 664 | 665 | # 设置坐标轴颜色 666 | lines.spines['right'].set_color('none') 667 | lines.spines['top'].set_color('none') 668 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 669 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 670 | 671 | # 设置坐标轴刻度 672 | lines.xaxis.set_ticks_position('none') 673 | lines.yaxis.set_ticks_position('none') 674 | 675 | # 绘制柱状图,设置柱状图颜色 676 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(8/255, 88/255, 121/255)) 677 | 678 | # 添加标题,设置字体属性 679 | ax.set_title('网易云音乐欧美歌单收藏 TOP10', fontsize=18, fontweight='light') 680 | 681 | # 添加歌单收藏数量文本 682 | for x, y in enumerate(data.values): 683 | num = str(y/10000) 684 | plt.text(y+20000, x-0.08, '%s' % (num + '万'), ha='center') 685 | 686 | # 保存图片 687 | plt.savefig('./music_image/top_10_of_ea_song_collection.png', dpi=None) 688 | 689 | # 显示图片 690 | plt.show() 691 | 692 | print("\n已生成网易云音乐欧美歌单收藏 TOP10 图片，保存至 music_image/top_10_of_ea_song_collection.png") 693 | ``` 694 | 695 | ### （七）top_10_of_ea_song_comment.py 696 | 697 | ```python 698 | """数据可视化，网易云音乐欧美歌单评论 TOP10""" 699 | import pandas as pd 700 | import matplotlib.pyplot as plt 701 | import time 702 | 703 | 704 | def data_visualization_of_top_10_of_ea_song_comment(): 705 | """网易云音乐欧美歌单评论 TOP10""" 706 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 707 | 708 | print("正在生成网易云音乐欧美歌单评论 TOP10 图片...") 709 | 710 | # 输出进度条 711 | t = 60 712 | start = time.perf_counter() 713 | 714 | for i in range(t + 1): 715 | finsh = "▓" * i 716 | need_do = "-" * (t - i) 717 | progress = (i / t) * 100 718 | dur = time.perf_counter() - start 719 | 720 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 721 | 722 | time.sleep(0.02) 723 | 724 | # 数据清洗 725 | df['love'] = [int(i.replace('评论', '0')) for i in df[6]] 726 | 727 | # 数据排序 728 | names = df.sort_values(by='love', ascending=False)[0][:10] 729 | comments = df.sort_values(by='love', ascending=False)['love'][:10] 730 | 731 | # 设置显示数据 732 | names = [i for i in names] 733 | names.reverse() 734 | comments = [i for i in comments] 735 | comments.reverse() 736 | data = pd.Series(comments, index=names) 737 | 738 | # 设置图片显示属性,字体及大小 739 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 740 | plt.rcParams['font.size'] = 8 741 | plt.rcParams['axes.unicode_minus'] = False 742 | 743 | # 设置图片显示属性 744 | plt.figure(figsize=(16, 8), dpi=80) 745 | ax = plt.subplot(1, 1, 1) 746 | ax.patch.set_color('white') 747 | 748 | # 设置坐标轴属性 749 | lines = plt.gca() 750 | 751 | # 设置坐标轴颜色 752 | lines.spines['right'].set_color('none') 753 | lines.spines['top'].set_color('none') 754 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 755 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 756 | 757 | # 设置坐标轴刻度 758 | lines.xaxis.set_ticks_position('none') 759 | lines.yaxis.set_ticks_position('none') 760 | 761 | # 绘制柱状图,设置柱状图颜色 762 | data.plot.barh(ax=ax, width=0.7, alpha=0.7, color=(160/255, 102/255, 50/255)) 763 | ax.set_title('网易云音乐欧美歌单评论 TOP10', fontsize=18, fontweight='light') 764 | 765 | # 添加歌单评论数量文本 766 | for x, y in enumerate(data.values): 767 | plt.text(y+200, x-0.08, '%s' % y, ha='center') 768 | 769 | # 保存图片 770 | plt.savefig('./music_image/top_10_of_ea_song_comment.png', dpi=None) 771 | 772 | # 显示图片 773 | plt.show() 774 | 775 | print("\n已生成网易云音乐欧美歌单评论 TOP10 图片，保存至 music_image/top_10_of_ea_song_comment.png") 776 | ``` 777 | 778 | ### （八）top_10_ea_song_collection_distribution.py 779 | 780 | ```python 781 | """数据可视化，欧美歌单收藏数量分布情况""" 782 | import numpy as np 783 | import pandas as pd 784 | import matplotlib.pyplot as plt 785 | import time 786 | 787 | 788 | def data_visualization_of_top_10_ea_song_collection_distribution(): 789 | """欧美歌单收藏数量分布情况""" 790 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 791 | 792 | print("正在生成欧美歌单收藏数量分布情况图片...") 793 | 794 | # 输出进度条 795 | t = 60 796 | start = time.perf_counter() 797 | 798 | for i in range(t + 1): 799 | finsh = "▓" * i 800 | need_do = "-" * (t - i) 801 | progress = (i / t) * 100 802 | dur = time.perf_counter() - start 803 | 804 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 805 | 806 | time.sleep(0.02) 807 | 808 | # 对收藏数取对数 809 | dom = [] 810 | for i in df[3]: 811 | dom.append(np.log(int(i.replace('万', '0000')))) 812 | 813 | df['collection'] = dom 814 | 815 | # 设置图片显示属性,字体及大小 816 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 817 | plt.rcParams['font.size'] = 12 818 | plt.rcParams['axes.unicode_minus'] = False 819 | 820 | # 设置图片显示属性 821 | plt.figure(figsize=(16, 8), dpi=80) 822 | ax = plt.subplot(1, 1, 1) 823 | ax.patch.set_color('white') 824 | 825 | # 设置坐标轴属性 826 | lines = plt.gca() 827 | 828 | # 设置坐标轴颜色 829 | lines.spines['right'].set_color('none') 830 | lines.spines['top'].set_color('none') 831 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 832 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 833 | lines.xaxis.set_ticks_position('none') 834 | lines.yaxis.set_ticks_position('none') 835 | 836 | # 绘制直方图,设置直方图颜色 837 | ax.hist(df['collection'], bins=30, alpha=0.7, color=(21/255, 47/255, 71/255)) 838 | ax.set_title('欧美歌单收藏数量分布情况', fontsize=20) 839 | 840 | # 保存图片 841 | plt.savefig('./music_image/top_10_ea_song_collection_distribution.png', dpi=None) 842 | 843 | # 显示图片 844 | plt.show() 845 | 846 | print("\n已生成欧美歌单收藏数量分布情况图片，保存至 music_image/top_10_ea_song_collection_distribution.png") 847 | ``` 848 | 849 | ### （九）top_10_ea_song_playlists_distribution.py 850 | 851 | ```python 852 | """数据可视化，欧美歌单播放数量分布情况""" 853 | import numpy as np 854 | import pandas as pd 855 | import matplotlib.pyplot as plt 856 | import time 857 | 858 | 859 | def data_visualization_of_top_10_ea_song_playlists_distribution(): 860 | """欧美歌单播放数量分布情况""" 861 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 862 | 863 | print("正在生成欧美歌单播放数量分布情况图片...") 864 | 865 | # 输出进度条 866 | t = 60 867 | start = time.perf_counter() 868 | 869 | for i in range(t + 1): 870 | finsh = "▓" * i 871 | need_do = "-" * (t - i) 872 | progress = (i / t) * 100 873 | dur = time.perf_counter() - start 874 | 875 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 876 | 877 | time.sleep(0.02) 878 | 879 | # 对播放数取对数 880 | dom = [] 881 | for i in df[4]: 882 | dom.append(np.log(i)) 883 | 884 | df['collection'] = dom 885 | 886 | # 设置图片显示属性,字体及大小 887 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 888 | plt.rcParams['font.size'] = 12 889 | plt.rcParams['axes.unicode_minus'] = False 890 | 891 | # 设置图片显示属性 892 | plt.figure(figsize=(16, 8), dpi=80) 893 | ax = plt.subplot(1, 1, 1) 894 | ax.patch.set_color('white') 895 | 896 | # 设置坐标轴属性 897 | lines = plt.gca() 898 | 899 | # 设置坐标轴颜色 900 | lines.spines['right'].set_color('none') 901 | lines.spines['top'].set_color('none') 902 | lines.spines['left'].set_color((64/255, 64/255, 64/255)) 903 | lines.spines['bottom'].set_color((64/255, 64/255, 64/255)) 904 | lines.xaxis.set_ticks_position('none') 905 | lines.yaxis.set_ticks_position('none') 906 | 907 | # 绘制直方图,设置直方图颜色 908 | ax.hist(df['collection'], bins=30, alpha=0.7, color=(255/255, 153/255, 0/255)) 909 | ax.set_title('欧美歌单播放数量分布情况', fontsize=20) 910 | 911 | # 保存图片 912 | plt.savefig('./music_image/top_10_ea_song_playlists_distribution.png', dpi=None) 913 | 914 | # 显示图片 915 | plt.show() 916 | 917 | print("\n已生成欧美歌单播放数量分布情况图片，保存至 music_image/top_10_ea_song_playlists_distribution.png") 918 | ``` 919 | 920 | ### （十）label_ea_song.py 921 | 922 | ```python 923 | """数据可视化，网易云音乐欧美歌单标签图""" 924 | import squarify 925 | import pandas as pd 926 | import matplotlib.pyplot as plt 927 | import time 928 | 929 | 930 | def data_visualization_of_label_ea_song(): 931 | """网易云音乐欧美歌单标签图""" 932 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 933 | 934 | print("正在生成网易云音乐欧美歌单标签图片...") 935 | 936 | # 输出进度条 937 | t = 60 938 | start = time.perf_counter() 939 | 940 | for i in range(t + 1): 941 | finsh = "▓" * i 942 | need_do = "-" * (t - i) 943 | progress = (i / t) * 100 944 | dur = time.perf_counter() - start 945 | 946 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 947 | 948 | time.sleep(0.02) 949 | 950 | # 处理标签信息 951 | tags = [] 952 | dom2 = [] 953 | 954 | for i in df[1]: 955 | c = i.split('-') 956 | 957 | for j in c: 958 | if j not in tags: 959 | tags.append(j) 960 | else: 961 | continue 962 | 963 | for item in tags: 964 | num = 0 965 | 966 | for i in df[1]: 967 | type2 = i.split('-') 968 | 969 | for j in range(len(type2)): 970 | if type2[j] == item: 971 | num += 1 972 | else: 973 | continue 974 | 975 | dom2.append(num) 976 | 977 | # 数据创建 978 | data = {'tags': tags, 'num': dom2} 979 | frame = pd.DataFrame(data) 980 | df1 = frame.sort_values(by='num', ascending=False) 981 | name = df1['tags'][:10] 982 | income = df1['num'][:10] 983 | 984 | # 绘图 details 985 | colors = ['#993333', '#CC9966', '#333333', '#663366', '#003366', '#009966', '#FF6600', '#FF0033', '#009999', 986 | '#333366'] 987 | plot = squarify.plot(sizes=income, label=name, color=colors, alpha=1, value=income, edgecolor='white', 988 | linewidth=1.5) 989 | 990 | # 设置图片显示属性,字体及大小 991 | plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] 992 | plt.rcParams['font.size'] = 8 993 | plt.rcParams['axes.unicode_minus'] = False 994 | 995 | # 设置标签大小为 1 996 | plt.rc('font', size=6) 997 | 998 | # 设置标题大小 999 | plot.set_title('网易云音乐欧美歌单标签图', fontsize=13, fontweight='light') 1000 | 1001 | # 除坐标轴 1002 | plt.axis('off') 1003 | 1004 | # 除上边框和右边框刻度 1005 | plt.tick_params(top=False, right=False) 1006 | 1007 | # 保存图片 1008 | plt.savefig('./music_image/label_ea_song.png', dpi=None) 1009 | 1010 | # 显示图片 1011 | plt.show() 1012 | 1013 | print("\n已生成网易云音乐欧美歌单标签图片，保存至 music_image/label_ea_song.png") 1014 | ``` 1015 | 1016 | ### （十一）music_wordcloud.py 1017 | 1018 | ```python 1019 | """数据可视化，歌单介绍词云图""" 1020 | from wordcloud import WordCloud, ImageColorGenerator 1021 | import matplotlib.pyplot as plt 1022 | import pandas as pd 1023 | import jieba 1024 | import time 1025 | 1026 | 1027 | def data_visualization_of_music_wordcloud(): 1028 | """歌单介绍词云图""" 1029 | df = pd.read_csv('./music_data/music_detail.csv', header=None) 1030 | text = '' 1031 | 1032 | print("正在生成歌单介绍词云图片...") 1033 | 1034 | # 输出进度条 1035 | t = 60 1036 | start = time.perf_counter() 1037 | 1038 | for i in range(t + 1): 1039 | finsh = "▓" * i 1040 | need_do = "-" * (t - i) 1041 | progress = (i / t) * 100 1042 | dur = time.perf_counter() - start 1043 | 1044 | print("\r{:^3.0f}%[{}->{}]{:.2f}s".format(progress, finsh, need_do, dur), end="") 1045 | 1046 | time.sleep(0.02) 1047 | 1048 | for line in df[2]: 1049 | text += ' '.join(jieba.cut(line, cut_all=False)) 1050 | 1051 | background_image = plt.imread('./music_image/background_image.jpg') 1052 | 1053 | stopwords = set('') 1054 | stopwords.update( 1055 | ['封面', 'none介绍', '介绍', '歌单', '歌曲', '我们', '自己', '没有', '就是', '可以', '知道', '一起', '不是', 1056 | '因为', '什么', '时候', '还是', '如果', '不要', '那些', '那么', '那个', '所有', '一样', '一直', '不会', '现在', 1057 | '他们', '这样', '最后', '这个', '只是', '有些', '其实', '开始', '曾经', '所以', '不能', '你们', '已经', '后来', 1058 | '一切', '一定', '这些', '一些', '只有', '还有']) 1059 | 1060 | wc = WordCloud( 1061 | background_color='white', 1062 | mask=background_image, 1063 | font_path='./font_resources/STZHONGS.ttf', 1064 | max_words=2000, 1065 | max_font_size=150, 1066 | random_state=30, 1067 | stopwords=stopwords 1068 | ) 1069 | wc.generate_from_text(text) 1070 | 1071 | # 看看词频高的有哪些,把无用信息去除 1072 | process_word = WordCloud.process_text(wc, text) 1073 | sort = sorted(process_word.items(), key=lambda e: e[1], reverse=True) 1074 | # print(sort[:50]) 1075 | 1076 | img_colors = ImageColorGenerator(background_image) 1077 | wc.recolor(color_func=img_colors) 1078 | plt.imshow(wc) 1079 | plt.axis('off') 1080 | 1081 | # 保存图片 1082 | wc.to_file("./music_image/music_wordcloud.png") 1083 | 1084 | # 显示图片 1085 | plt.show() 1086 | 1087 | print("\n已生成歌单介绍词云图片，保存至 music_image/music_wordcloud.png") 1088 | ``` 1089 | 1090 | ## 四、项目分析结果 1091 | 1092 | 网易云用户是很习惯创建歌单的一个用户群体，很多用户也是通过歌单了解到一些歌曲。一个网易云用户甚至自己一个人就创建上百个歌单，我们爬取了网易云欧美歌单的数据，制作了以下表格。 1093 | 1094 | ### （一）歌曲出现次数 TOP10 1095 | 1096 | ![网易云音乐欧美歌单歌曲 TOP10](https://img-blog.csdnimg.cn/60848bcfa7604d2a94cf971c53c45271.png) 1097 | 1098 | _图 12 网易云音乐欧美歌单歌曲 TOP10_ 1099 | 1100 | 我们获得了网易云音乐欧美歌单中的 TOP10 歌曲，相信熟悉欧美歌曲的小伙伴们对这些歌都很熟悉，他们曾经或许就出现在推荐给你的歌单中。 1101 | 1102 | ### （二）网易云音乐欧美歌单播放 TOP10 1103 | 1104 | ![网易云音乐欧美歌单播放 TOP10](https://img-blog.csdnimg.cn/b9f0a6ad102945b1bd3464ef34b3464b.png) 1105 | 1106 | _图 13 网易云音乐欧美歌单播放 TOP10_ 1107 | 1108 | 这是欧美歌单播放量前十排行榜，第一名拥有高达 4 亿的播放量，可见欧美歌曲是非常令人欢迎的。在歌单中统计中我们可以看到旋律和节奏是很多欧美音乐爱好者们比较看重和喜欢的。 1109 | 1110 | ### （三）网易云音乐欧美歌单评论 TOP10 1111 | 1112 | ![网易云音乐欧美歌单评论 TOP10](https://img-blog.csdnimg.cn/28a770d38dda4011bccecd6c92892df0.png) 1113 | 1114 | _图 14 网易云音乐欧美歌单评论 TOP10_ 1115 | 1116 | 可以看到歌单【定制 最懂你的欧美推荐 每日更新 35 首】的评论数量最多。这可能与他日更与定制的性质有关。可以看到，很多热门的歌单其评论通常也很多。这个榜单中的歌单在上一个热门歌单的榜单也能找到。 1117 | 1118 | ### （四）欧美歌单播放数量分布情况 1119 | 1120 | ![欧美歌单播放数量分布情况](https://img-blog.csdnimg.cn/82261d3f81c44b43a124c326498484f1.png) 1121 | 1122 | _图 15 欧美歌单播放数量分布情况_ 1123 | 1124 | 将播放数做对数处理，使得能直观看出歌单播放数的分布。 1125 | 1126 | 歌单播放数主要分布在 0-1000 万。 1127 | 1128 | 其中 ln(10000000) = 16。 1129 | 1130 | ### （五）网易云音乐欧美歌单标签图 1131 | 1132 | ![网易云音乐欧美歌单标签图](https://img-blog.csdnimg.cn/b3f608d308fd4e1b81bb9fccddcb4141.png) 1133 | 1134 | _图 16 网易云音乐欧美歌单标签图_ 1135 | 1136 | 我们还找到了这些歌单的标签情况，既然是欧美歌单，【欧美】自然就占大头，几乎一半。我们还可以看到【电子】和【流行】这两大类也是非常多，【欧美流行】和【欧美电子】近两年在网易云用户中越来越火爆，特别是【欧美电子】，不少青年已经是电子音乐的忠实粉丝。 1137 | 1138 | ### （六）歌单介绍词云图 1139 | 1140 | ![歌单介绍词云图](https://img-blog.csdnimg.cn/934472aff3b6407fba8ba73b6b1bd7fe.png) 1141 | 1142 | _图 17 歌单介绍词云图_ 1143 | 1144 | 歌单介绍词云图，这些词包括一个歌单的风格，背景还有故事。或许你曾经是因为哪一个词打动了你，让你收藏的这份歌单。与歌曲产生共鸣。 1145 | 1146 | ### （七）音乐歌单运营分析 1147 | 1148 | 歌单有两种形式，一种是由官方创建的歌单，另一种是由用户自主创建的歌单，在网易云中，我们收藏倾听的大多来自个人用户。而歌单的运营不论是对个人还是官方都是有意义的。 1149 | 1150 | 很多用户是以歌单作为入口来了解音乐的，很少主动的的持续的去搜索音乐，所以歌单是否丰富，歌单的品质是否足够好，决定了用户使用的频率和时间。用户能够获取到越多越好的好歌单，就意味着这个音乐平台更有价值。 1151 | 1152 | 对于个人而言，创造令很多人满意的歌单，让个人获得关注，更高的成就感，进而创造更好的精品歌单。 1153 | 1154 | 所以我们基于以上的分析，做出了一个关于欧美歌单的运营分析： 1155 | 1156 | 在歌单内容方面，图 15 网易云音乐欧美歌单标签图里，我们可以看出，流行类标签和电子标签占比大约 50%。以标签分类实行个性化推荐，可以让歌单更容易被找到，曝光，便于管理。 1157 | 1158 | 另外我们的歌单可以向这两个热门的方向靠拢，面向受众面广的人群，可以获得可观的流量。再加上电子音乐的兴起，越来越优秀的电子音乐出现，可以丰富我们的歌单。 1159 | 1160 | 在歌单标题方面，歌单相当于一篇文章，歌单的标题可以吸引听众的注意力，让他们进来了解歌单，收听歌单。在歌单播放量 TOP10 和歌单评论数量 TOP10 中，我们区分出以下几类： 1161 | 1162 | 在特殊标志式方面，在前十的几个歌单名称中我们可以看到"【】"，"|"等特殊字符，这些特殊字符可以吸引听众的目光，强调自己歌单的亮点。 1163 | 1164 | 在强吸引式方面，使用"精选"，"10w+"，"专属"等字眼，驱使听众点击。 1165 | 1166 | 在结论式方面使用，"热血燃向 | 提神醒脑防嗜睡型 BGM" 等字眼，驱使听众点击。 1167 | 1168 | 综上所述，一份歌单成功离不开标题、歌曲风格、乃至歌曲数。只有平衡好其中的因素，才能使其播放量达到预期。 1169 | 1170 | ### （八）歌单数据可视化的商业价值 1171 | 1172 | 歌单数据可视化可以帮助音乐公司更好地理解消费者喜好，并为消费者提供更符合他们喜好的歌单。 1173 | 1174 | 此外，歌单数据可视化还可以帮助音乐公司更好地分析歌单中的信息，并利用这些信息来决定如何定价、营销和分销音乐。 1175 | 1176 | 因此，歌单数据可视化具有一定的商业价值，可以为音乐公司提供重要的市场信息。 1177 | --------------------------------------------------------------------------------