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基于python的歌手数据爬虫和可视化分析 技术栈:python网络爬虫 + 文本预处理 + 文本关键词抽取 + 词云分析 + Echarts 可视化 本项目利用 python 的 request + beautifulsoup 抓取某在线音乐网站的歌手数据,包括歌手的基本简介信息、发行专辑信息、每首歌的歌词文本等内容,格式化后存储到文件系统或数据库中,后台通过中文分词和关键词抽取算法,实现对该歌手所有歌词的关键词的抽取,并利用情感分析算法实现对每首歌词的情感极性分析,分析该歌手的整体情感基调。利用 flask 搭建后台,构建标准的 restful 接口,前端利用 bootstrap + echarts + jquery 调用后台接口,并进行前端的渲染可视化。
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基于python的歌手数据爬虫和可视化分析.zip (51个子文件)
MusicAnalysis
app.py 13KB
config.py 56B
static
css
bootstrap.min.css 118KB
close.png 4KB
shCoreDefault.css 9KB
pick-a-color-1.2.3.min.css 26KB
barrager.css 1KB
dashboard.css 2KB
style.css 6KB
bootstrap-theme.min.css 23KB
fonts
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glyphicons-halflings-regular.woff 23KB
glyphicons-halflings-regular.ttf 44KB
glyphicons-halflings-regular.woff2 18KB
glyphicons-halflings-regular.eot 20KB
pick-a-color
css
pick-a-color-1.2.3.min.css 26KB
js
pick-a-color-1.2.3.min.js 24KB
.DS_Store 6KB
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spider_info.png 477KB
js
jquery.barrager.min.js 2KB
worldcloud.js 28KB
npm.js 484B
tinycolor-0.9.15.min.js 14KB
shBrushJScript.js 2KB
shAutoloader.js 1KB
jquery.barrager.js 2KB
ecStat.min.js 10KB
bootstrap.min.js 36KB
echarts-wordcloud.min.js 125KB
echarts.js 2.83MB
shCore.js 16KB
shBrushPhp.js 5KB
shLegacy.js 2KB
jquery.min.js 95KB
.DS_Store 6KB
user-agent.txt 415KB
util.py 2KB
geshou_lyric_info.db 3.14MB
__pycache__
config.cpython-37.pyc 214B
requirements.txt 54B
.idea
.gitignore 176B
workspace.xml 7KB
misc.xml 288B
modules.xml 278B
inspectionProfiles
Project_Default.xml 500B
MusicAnalysis.iml 398B
.DS_Store 6KB
stopwords.txt 5KB
templates
layout.html 2KB
index.html 10KB
基于python的歌手数据分析.mov 89.23MB
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