【NLP舆情分析】基于python微博舆情分析可视化系统(flask+pandas+echarts) 视频教程 - 微博评论数据可视化分析-点赞区间折线图实现
大家好,我是java1234_小锋老师,最近写了一套【NLP舆情分析】基于python微博舆情分析可视化系统(flask+pandas+echarts)视频教程,持续更新中,计划月底更新完,感谢支持。今天讲解微博评论数据可视化分析-点赞区间折线图实现
视频在线地址:
2026版【NLP舆情分析】基于python微博舆情分析可视化系统(flask+pandas+echarts+爬虫) 视频教程 (火爆连载更新中..)_哔哩哔哩_bilibili
课程简介:
本课程采用主流的Python技术栈实现,Mysql8数据库,Flask后端,Pandas数据分析,前端可视化图表采用echarts,以及requests库,snowNLP进行情感分析,词频统计,包括大量的数据统计及分析技巧。
实现了,用户登录,注册,爬取微博帖子和评论信息,进行了热词统计以及舆情分析,以及基于echarts实现了数据可视化,包括微博文章分析,微博IP分析,微博评论分析,微博舆情分析。最后也基于wordcloud库实现了词云图,包括微博内容词云图,微博评论词云图,微博评论用户词云图等功能。
微博评论数据可视化分析-点赞区间折线图实现
首先准备好微博评论数据分析静态网页模版commentDataAnalysis.html,放到templates下;
{% extends 'base.html' %}
{% block title %}微博评论分析{% endblock %}
{% block content %}<div class="container-fluid"><div class="row"><div class="col-md-12 mb-4 mt-1"><div class="d-flex flex-wrap justify-content-between align-items-center"><h4 class="font-weight-bold">微博评论分析</h4>
</div></div>
</div>
<div class="row"><div class="col-lg-12"><div class="card"><div class="card-header d-flex justify-content-between"><div class="header-title"><h4 class="card-title">评论点赞次数区间图</h4></div></div><div class="card-body"><div id="dzMain" style="width:100%;height:450px">
</div></div></div>
</div><div class="col-lg-6"><div class="card"><div class="card-header d-flex justify-content-between"><div class="header-title"><h4 class="card-title">评论用户性别占比</h4></div></div><div class="card-body"><div id="xbMain" style="width:100%;height:450px">
</div></div></div></div><div class="col-lg-6"><div class="card"><div class="card-header d-flex justify-content-between"><div class="header-title"><h4 class="card-title">用户评论词云图</h4></div></div><div class="card-body"><div id="commentCloudMain" style="width:100%;height:450px;text-align:center"><img style="width:60%" src="/static/comment_cloud.jpg" alt=""></div></div></div></div></div>
</div>
{% endblock %}
{% block echarts %}
{% endblock %}
page.py实现commentDataAnalysis方法:
@pb.route('/commentDataAnalysis')
def commentDataAnalysis():"""微博评论数据分析:return:"""commentList = commentDao.getAllComment()xDzData = [] # 点赞x轴数据rangeNum = 5for item in range(0, 20):xDzData.append(str(rangeNum * item) + '-' + str(rangeNum * (item + 1)))xDzData.append('1百+')yDzData = [0 for x in range(len(xDzData))] # 点赞y数据for comment in commentList:for item in range(len(xDzData)):if int(comment[4] < rangeNum * (item + 1)):yDzData[item] += 1breakelif int(comment[4]) > 100:yDzData[len(xDzData) - 1] += 1return render_template('commentDataAnalysis.html',xDzData=xDzData,yDzData=yDzData)
前端commentDataAnalysis.html实现折线图代码:
<script>var chartDom = document.getElementById('dzMain');var myChart = echarts.init(chartDom);var option = {title: {text: '评论点赞量区间折线图',left: '1%'},legend: {},tooltip: {trigger: 'axis'},grid: {left: '5%',right: '15%',bottom: '10%'},xAxis: {data: {{ xDzData |tojson }}},yAxis: {},toolbox: {right: 10,feature: {dataZoom: {yAxisIndex: 'none'},restore: {},saveAsImage: {}}},dataZoom: [{show: true,start: 10,end: 60},],visualMap: {top: 50,right: 10,pieces: [{gt: 0,lte: 20,color: '#93CE07'},{gt: 20,lte: 40,color: '#FBDB0F'},{gt: 40,lte: 60,color: '#FC7D02'},{gt: 60,lte: 80,color: '#FD0100'},{gt: 80,lte: 100,color: '#AA069F'},{gt: 100,color: '#AC3B2A'}],outOfRange: {color: '#999'}},series: {name: '点赞区间个数',type: 'line',data: {{ yDzData }},markLine: {silent: true,lineStyle: {color: '#333'},data: [{yAxis: 50},{yAxis: 100},{yAxis: 150},{yAxis: 200},{yAxis: 300}]}}}option && myChart.setOption(option);</script>