可视化效果对比

在这里插入图片描述

柱状图

可视化展示

代码展示

option = {
       xAxis: {
           type: 'category',        data: ['北京', '上海', '广东', '青海', '云南', '辽宁', '内蒙古']    },    yAxis: {
           type: 'value'    },    series: [{
           data: [929, 732, 1650, 18, 188, 164, 249],        type: 'bar',        showBackground: true,        backgroundStyle: {
               color: 'rgba(220, 220, 220, 0.8)'        }    }]};

# 柱状图from pyecharts.charts import Barbar = Bar()bar.add_xaxis(['北京', '上海', '广东', '青海', '云南', '辽宁', '内蒙古'])bar.add_yaxis("疫情数据可视化", [929, 732, 1650, 18, 188, 164, 249])# render会生成本地html文件，默认会在当前目录生成 render.html 文件# 也可以传入路径参数 Exam : bar.render(mycharts.html")bar.render('YiQingPyecharts.html')    # 生成本地 HTML 文件

# 柱状图import pandas as pdimport matplotlib.pyplot as plt# 读取数据news = pd.read_csv("ripe_chinese_news.csv")# 类别数量分布c = news["tag"].value_counts()print(c)c.plot(kind='bar')plt.title("新闻联播内容分布")plt.show()

import plotly.graph_objects as gofig = go.Figure(    data=[go.Bar(x=['详细全文', '国内', '国外'], y=[11529, 6186, 3018])],    layout=go.Layout(        title=go.layout.Title(text="新闻联播内容分布")    ))fig.show()

饼状图

可视化展示

代码展示

option = {
       title: {
           text: '网站点用户访问来源',        left: 'center'    },    tooltip: {
           trigger: 'item',        formatter: '{a} 
{b} : {c} ({d}%)'    },    legend: {
           orient: 'vertical',        left: 'left',        data: ['直接访问', '邮件营销', '联盟广告', '视频广告', '搜索引擎']    },    series: [        {
               name: '访问来源',            type: 'pie',            radius: '55%',            center: ['50%', '60%'],            data: [                {
   value: 335, name: '直接访问'},                {
   value: 310, name: '邮件营销'},                {
   value: 234, name: '联盟广告'},                {
   value: 135, name: '视频广告'},                {
   value: 1548, name: '搜索引擎'}            ],            emphasis: {
                   itemStyle: {
                       shadowBlur: 10,                    shadowOffsetX: 0,                    shadowColor: 'rgba(0, 0, 0, 0.5)'                }            }        }    ]};

# 饼状图from pyecharts import options as optsfrom pyecharts.charts import Piefrom pyecharts.faker import Fakerx_data = ["直接访问", "邮件营销", "联盟广告", "视频广告", "搜索引擎"]y_data = [335, 310, 274, 235, 400]data_pair = [list(z) for z in zip(x_data, y_data)]data_pair.sort(key=lambda x: x[1])c = (    Pie()    .add(        series_name="访问来源",        data_pair=data_pair,    )    .set_global_opts(title_opts=opts.TitleOpts(title="网站用户访问来源"))    .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))    .render("pie_base.html"))

折线图

可视化展示

代码展示

option = {
       xAxis: {
           type: 'category',        data: ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']    },    yAxis: {
           type: 'value'    }, title: {
               text: '微信运动',            left: 'center'        },    series: [{
           data: [820, 932, 901, 934, 1290, 1330, 1320],        type: 'line'    }]};

# 折线图import pyecharts.options as optsfrom pyecharts.charts import Line"""Gallery 使用 pyecharts 1.1.0参考地址: https://echarts.baidu.com/examples/editor.html?c=line-simple目前无法实现的功能:暂无"""x_data = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]y_data = [820, 932, 901, 934, 1290, 1330, 1320](    Line()    .set_global_opts(        title_opts=opts.TitleOpts(title="微信运动"),        tooltip_opts=opts.TooltipOpts(is_show=False),        xaxis_opts=opts.AxisOpts(type_="category"),        yaxis_opts=opts.AxisOpts(            type_="value",            axistick_opts=opts.AxisTickOpts(is_show=True),            splitline_opts=opts.SplitLineOpts(is_show=True),        ),    )    .add_xaxis(xaxis_data=x_data)    .add_yaxis(        series_name="",        y_axis=y_data,        symbol="emptyCircle",        is_symbol_show=True,        label_opts=opts.LabelOpts(is_show=False),    )    .render("basic_line_chart.html"))

地图可视化

可视化展示

代码展示

      QQ音乐播放量地图可视化

# -*- encoding: utf-8 -*-"""@File    :   COVID19.py    @Contact :   ag@team-ag.club@License :   (C)Copyright 2019-2020, CodingPark@Modify Time      @Author    @Version    @Desciption------------      -------    --------    -----------2020-07-17 15:22   AG         1.0         None"""import pandas as pdfrom pyecharts import options as optsfrom pyecharts.charts import Mapdf = pd.read_excel('Covid_China.xls')# 1 根据Excel绘制国内总疫情图（确诊）data = df.groupby(by='province', as_index=False).sum()data_list = list(zip(data['province'].values.tolist(), data['total_confirm'].values.tolist()))def map_china():    c = (        Map()            .add(series_name='确诊病例', data_pair=data_list, maptype="china")            .set_global_opts(            title_opts=opts.TitleOpts(title='疫情地图'),            visualmap_opts=opts.VisualMapOpts(is_piecewise=True,                                             pieces=[{
   "max": 9, "min": 0, "lavel": "0-9", "color": "#FFE4E1"},                                                     {
   "max": 99, "min": 10, "lavel": "10-99", "color": "#FF7F50"},                                                     {
   "max": 499, "min": 100, "lavel": "100-499", "color": "#F08080"},                                                     {
   "max": 999, "min": 500, "lavel": "500-999", "color": "#CD5C5C"},                                                     {
   "max": 9999, "min": 1000, "lavel": "1000-9999",                                                      "color": "#990000"},                                                     {
   "max": 99999, "min": 10000, "lavel": ">10000",                                                      "color": "#660000"}]                                             )        )    )    return cd_map = map_china()d_map.render('COVID-19.html')print('\n=== 成功 ===')