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pyecharts图表练习二

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pyecharts图表练习二

【实验目的】

熟练掌握pyecharts的各种图表，能够快速实现基本图表。

【实验原理】

Pyecharts常用的图表类型

  1. 饼图 Pie
  2. 折线图Line
  3. 涟漪散点图
  4. 水球图Liquid
  5. 桑基图 Sanky
  6. 主题河流
  7. 地图Map
  8. 地理坐标系Geo

【实验环境】

IE9 以上或Chrome（推荐）或Firefox等浏览器、pycharm 、Jupyter notebook等编程环境。

水球图Liquid

1.添加水球，并设置水球图的水波层数和水球的显示形状shape，至少生成三种 代码： from pyecharts import options as opts from pyecharts.charts import Liquid liquid_chart=( Liquid() .add("水球",[0.5,0.6],shape="rect") .set_global_opts( title_opts=opts.TitleOpts(title="水球图示例"), ) ) liquid_chart.render("liquid_chart.html")

桑基图Sankey

1.通过给定的数据集 nodes和links 绘制基本桑基图 nodes = [ {"name": "英国"}, {"name": "美国"}, {"name": "西班牙"}, {"name": "法国"}, {"name": "北京"}, {"name": "上海"}, {"name": "广东"}, {"name": "福建"}, {"name": "浙江"}, {"name": "深圳"}, {"name": "甘肃"}, {"name": "保定"}, {"name": "邯郸"}, {"name": "邢台"}, {"name": "衡水"}, {"name": "天津"}, ] links = [ {"source": "英国", "target": "北京", "value": 90}, {"source": "英国", "target": "上海", "value": 92}, {"source": "英国", "target": "广东", "value": 50}, {"source": "英国", "target": "深圳", "value": 13}, {"source": "英国", "target": "甘肃", "value": 20}, {"source": "英国", "target": "福建", "value": 15}, {"source": "美国", "target": "北京", "value": 44}, {"source": "美国", "target": "上海", "value": 46}, {"source": "美国", "target": "广东", "value": 93}, {"source": "西班牙", "target": "北京", "value": 56}, {"source": "西班牙", "target": "上海", "value": 20}, {"source": "西班牙", "target": "广东", "value": 2}, {"source": "西班牙", "target": "浙江", "value": 2}, {"source": "法国", "target": "北京", "value": 20}, {"source": "法国", "target": "上海", "value": 2}, {"source": "法国", "target": "广东", "value": 2}, {"source": "法国", "target": "福建", "value": 2}, {"source": "北京", "target": "保定", "value": 20}, {"source": "北京", "target": "衡水", "value": 22}, {"source": "北京", "target": "天津", "value": 88}, {"source": "北京", "target": "邢台", "value": 50}, {"source": "北京", "target": "邯郸", "value": 20}, {"source": "上海", "target": "保定", "value": 20}, {"source": "上海", "target": "衡水", "value": 50}, {"source": "上海", "target": "天津", "value": 60}, {"source": "上海", "target": "邢台", "value": 20}, {"source": "上海", "target": "邯郸", "value": 10}, ] 代码参考：.add( "sankey", nodes, links,) 2.设置桑基图的线条样式linestyle_opt，透明度opacity为0.2, 弯曲度curve为0.5, 颜色设置为"source" 代码： from pyecharts import options as opts from pyecharts.charts import Sankey nodes = [ {"name": "英国"}, {"name": "美国"}, {"name": "西班牙"}, {"name": "法国"}, {"name": "北京"}, {"name": "上海"}, {"name": "广东"}, {"name": "福建"}, {"name": "浙江"}, {"name": "深圳"}, {"name": "甘肃"}, {"name": "保定"}, {"name": "邯郸"}, {"name": "邢台"}, {"name": "衡水"}, {"name": "天津"}, ] links = [ {"source": "英国", "target": "北京", "value": 90}, {"source": "英国", "target": "上海", "value": 92}, {"source": "英国", "target": "广东", "value": 50}, {"source": "英国", "target": "深圳", "value": 13}, {"source": "美国", "target": "北京", "value": 44}, {"source": "美国", "target": "上海", "value": 46}, {"source": "美国", "target": "广东", "value": 93}, {"source": "西班牙", "target": "北京", "value": 56}, {"source": "西班牙", "target": "上海", "value": 20}, {"source": "西班牙", "target": "广东", "value": 2}, {"source": "法国", "target": "北京", "value": 20}, {"source": "法国", "target": "上海", "value": 2}, {"source": "法国", "target": "广东", "value": 2}, ] c= ( Sankey() .add( "sankey", nodes, links, linestyle_opt=opts.LineStyleOpts( opacity=0.2,curve=0.5,color="source"), label_opts=opts.LabelOpts(position="rigth"), ) .set_global_opts(title_opts=opts.TitleOpts(title="基本桑基图")) ) c.render("sankey_chart.html")

主题河流ThemeRiver

1.根据下面给定的数据，绘制主题河流 x_data = ["DQ", "TY", "SS", "QG", "SY", "DD"] y_data = [ ["2021/9/08", 10, "DQ"], ["2021/9/09", 15, "DQ"], ["2021/9/10", 35, "DQ"], ["2021/9/11", 38, "DQ"], ["2021/9/12", 22, "DQ"], ["2021/9/13", 16, "DQ"], ["2021/9/14", 7, "DQ"], ["2021/9/15", 2, "DQ"], ["2021/9/16", 17, "DQ"], ["2021/9/17", 33, "DQ"], ["2021/9/18", 40, "DQ"], ["2021/9/19", 32, "DQ"], ["2021/9/20", 26, "DQ"], ["2021/9/21", 35, "DQ"], ["2021/9/22", 40, "DQ"], ["2021/9/23", 32, "DQ"], ["2021/9/24", 26, "DQ"], ["2021/9/25", 22, "DQ"], ["2021/9/26", 16, "DQ"], ["2021/9/27", 22, "DQ"], ["2021/9/28", 10, "DQ"], ["2021/9/08", 35, "TY"], ["2021/9/09", 36, "TY"], ["2021/9/10", 37, "TY"], ["2021/9/11", 22, "TY"], ["2021/9/12", 24, "TY"], ["2021/9/13", 26, "TY"], ["2021/9/14", 34, "TY"], ["2021/9/15", 21, "TY"], ["2021/9/16", 18, "TY"], ["2021/9/17", 45, "TY"], ["2021/9/18", 32, "TY"], ["2021/9/19", 35, "TY"], ["2021/9/20", 30, "TY"], ["2021/9/21", 28, "TY"], ["2021/9/22", 27, "TY"], ["2021/9/23", 26, "TY"], ["2021/9/24", 15, "TY"], ["2021/9/25", 30, "TY"], ["2021/9/26", 35, "TY"], ["2021/9/27", 42, "TY"], ["2021/9/28", 42, "TY"], ["2021/9/08", 21, "SS"], ["2021/9/09", 25, "SS"], ["2021/9/10", 27, "SS"], ["2021/9/11", 23, "SS"], ["2021/9/12", 24, "SS"], ["2021/9/13", 21, "SS"], ["2021/9/14", 35, "SS"], ["2021/9/15", 39, "SS"], ["2021/9/16", 40, "SS"], ["2021/9/17", 36, "SS"], ["2021/9/18", 33, "SS"], ["2021/9/19", 43, "SS"], ["2021/9/20", 40, "SS"], ["2021/9/21", 34, "SS"], ["2021/9/22", 28, "SS"], ["2021/9/23", 26, "SS"], ["2021/9/24", 37, "SS"], ["2021/9/25", 41, "SS"], ["2021/9/26", 46, "SS"], ["2021/9/27", 47, "SS"], ["2021/9/28", 41, "SS"], ["2021/9/08", 10, "QG"], ["2021/9/09", 15, "QG"], ["2021/9/10", 35, "QG"], ["2021/9/11", 38, "QG"], ["2021/9/12", 22, "QG"], ["2021/9/13", 16, "QG"], ["2021/9/14", 7, "QG"], ["2021/9/15", 2, "QG"], ["2021/9/16", 17, "QG"], ["2021/9/17", 33, "QG"], ["2021/9/18", 40, "QG"], ["2021/9/19", 32, "QG"], ["2021/9/20", 26, "QG"], ["2021/9/21", 35, "QG"], ["2021/9/22", 40, "QG"], ["2021/9/23", 32, "QG"], ["2021/9/24", 26, "QG"], ["2021/9/25", 22, "QG"], ["2021/9/26", 16, "QG"], ["2021/9/27", 22, "QG"], ["2021/9/28", 10, "QG"], ["2021/9/08", 10, "SY"], ["2021/9/09", 15, "SY"], ["2021/9/10", 35, "SY"], ["2021/9/11", 38, "SY"], ["2021/9/12", 22, "SY"], ["2021/9/13", 16, "SY"], ["2021/9/14", 7, "SY"], ["2021/9/15", 2, "SY"], ["2021/9/16", 17, "SY"], ["2021/9/17", 33, "SY"], ["2021/9/18", 40, "SY"], ["2021/9/19", 32, "SY"], ["2021/9/20", 26, "SY"], ["2021/9/21", 35, "SY"], ["2021/9/22", 4, "SY"], ["2021/9/23", 32, "SY"], ["2021/9/24", 26, "SY"], ["2021/9/25", 22, "SY"], ["2021/9/26", 16, "SY"], ["2021/9/27", 22, "SY"], ["2021/9/28", 10, "SY"], ["2021/9/08", 10, "DD"], ["2021/9/09", 15, "DD"], ["2021/9/10", 35, "DD"], ["2021/9/11", 38, "DD"], ["2021/9/12", 22, "DD"], ["2021/9/13", 16, "DD"], ["2021/9/14", 7, "DD"], ["2021/9/15", 2, "DD"], ["2021/9/16", 17, "DD"], ["2021/9/17", 33, "DD"], ["2021/9/18", 4, "DD"], ["2021/9/19", 32, "DD"], ["2021/9/20", 26, "DD"], ["2021/9/21", 35, "DD"], ["2021/9/22", 40, "DD"], ["2021/9/23", 32, "DD"], ["2021/9/24", 26, "DD"], ["2021/9/25", 22, "DD"], ["2021/9/26", 16, "DD"], ["2021/9/27", 22, "DD"], ["2021/9/28", 10, "DD"], ] 2 设置图表的宽度width为800px 高度height为600px并为图表添加主题样式 代码： from pyecharts.charts import ThemeRiver from pyecharts import options as opts from pyecharts.globals import ThemeType x_data=["DQ", "TY", "SS", "QG", "SY", "DD"] y_data = [ ["2021/9/08", 10, "DQ"], ["2021/9/09", 15, "DQ"], ["2021/9/10", 35, "DQ"], ["2021/9/11", 38, "DQ"], ["2021/9/12", 22, "DQ"], ["2021/9/13", 16, "DQ"], ["2021/9/14", 7, "DQ"], ["2021/9/15", 2, "DQ"], ["2021/9/16", 17, "DQ"], ["2021/9/17", 33, "DQ"], ["2021/9/18", 40, "DQ"], ["2021/9/19", 32, "DQ"], ["2021/9/20", 26, "DQ"], ["2021/9/21", 35, "DQ"], ["2021/9/22", 40, "DQ"], ["2021/9/23", 32, "DQ"], ["2021/9/24", 26, "DQ"], ["2021/9/25", 22, "DQ"], ["2021/9/26", 16, "DQ"], ["2021/9/27", 22, "DQ"], ["2021/9/28", 10, "DQ"], ["2021/9/08", 35, "TY"], ["2021/9/09", 36, "TY"], ["2021/9/10", 37, "TY"], ["2021/9/11", 22, "TY"], ["2021/9/12", 24, "TY"], ["2021/9/13", 26, "TY"], ["2021/9/14", 34, "TY"], ["2021/9/15", 21, "TY"], ["2021/9/16", 18, "TY"], ["2021/9/17", 45, "TY"], ["2021/9/18", 32, "TY"], ["2021/9/19", 35, "TY"], ["2021/9/20", 30, "TY"], ["2021/9/21", 28, "TY"], ["2021/9/22", 27, "TY"], ["2021/9/23", 26, "TY"], ["2021/9/24", 15, "TY"], ["2021/9/25", 30, "TY"], ["2021/9/26", 35, "TY"], ["2021/9/27", 42, "TY"], ["2021/9/28", 42, "TY"], ["2021/9/08", 21, "SS"], ["2021/9/09", 25, "SS"], ["2021/9/10", 27, "SS"], ["2021/9/11", 23, "SS"], ["2021/9/12", 24, "SS"], ["2021/9/13", 21, "SS"], ["2021/9/14", 35, "SS"], ["2021/9/15", 39, "SS"], ["2021/9/16", 40, "SS"], ["2021/9/17", 36, "SS"], ["2021/9/18", 33, "SS"], ["2021/9/19", 43, "SS"], ["2021/9/20", 40, "SS"], ["2021/9/21", 34, "SS"], ["2021/9/22", 28, "SS"], ["2021/9/23", 26, "SS"], ["2021/9/24", 37, "SS"], ["2021/9/25", 41, "SS"], ["2021/9/26", 46, "SS"], ["2021/9/27", 47, "SS"], ["2021/9/28", 41, "SS"], ["2021/9/08", 10, "QG"], ["2021/9/09", 15, "QG"], ["2021/9/10", 35, "QG"], ["2021/9/11", 38, "QG"], ["2021/9/12", 22, "QG"], ["2021/9/13", 16, "QG"], ["2021/9/14", 7, "QG"], ["2021/9/15", 2, "QG"], ["2021/9/16", 17, "QG"], ["2021/9/17", 33, "QG"], ["2021/9/18", 40, "QG"], ["2021/9/19", 32, "QG"], ["2021/9/20", 26, "QG"], ["2021/9/21", 35, "QG"], ["2021/9/22", 40, "QG"], ["2021/9/23", 32, "QG"], ["2021/9/24", 26, "QG"], ["2021/9/25", 22, "QG"], ["2021/9/26", 16, "QG"], ["2021/9/27", 22, "QG"], ["2021/9/28", 10, "QG"], ["2021/9/08", 10, "SY"], ["2021/9/09", 15, "SY"], ["2021/9/10", 35, "SY"], ["2021/9/11", 38, "SY"], ["2021/9/12", 22, "SY"], ["2021/9/13", 16, "SY"], ["2021/9/14", 7, "SY"], ["2021/9/15", 2, "SY"], ["2021/9/16", 17, "SY"], ["2021/9/17", 33, "SY"], ["2021/9/18", 40, "SY"], ["2021/9/19", 32, "SY"], ["2021/9/20", 26, "SY"], ["2021/9/21", 35, "SY"], ["2021/9/22", 4, "SY"], ["2021/9/23", 32, "SY"], ["2021/9/24", 26, "SY"], ["2021/9/25", 22, "SY"], ["2021/9/26", 16, "SY"], ["2021/9/27", 22, "SY"], ["2021/9/28", 10, "SY"], ["2021/9/08", 10, "DD"], ["2021/9/09", 15, "DD"], ["2021/9/10", 35, "DD"], ["2021/9/11", 38, "DD"], ["2021/9/12", 22, "DD"], ["2021/9/13", 16, "DD"], ["2021/9/14", 7, "DD"], ["2021/9/15", 2, "DD"], ["2021/9/16", 17, "DD"], ["2021/9/17", 33, "DD"], ["2021/9/18", 4, "DD"], ["2021/9/19", 32, "DD"], ["2021/9/20", 26, "DD"], ["2021/9/21", 35, "DD"], ["2021/9/22", 40, "DD"], ["2021/9/23", 32, "DD"], ["2021/9/24", 26, "DD"], ["2021/9/25", 22, "DD"], ["2021/9/26", 16, "DD"], ["2021/9/27", 22, "DD"], ["2021/9/28", 10, "DD"], ] c=( ThemeRiver(init_opts=opts.InitOpts(width="800px",height="600px",theme=ThemeType.LIGHT)) .add( series_name=x_data, data=y_data, singleaxis_opts=opts.SingleAxisOpts( pos_top="50", pos_bottom="50", type_="time" ) ) .set_global_opts( title_opts=opts.TitleOpts(title="主题河流图"), toolbox_opts=opts.ToolboxOpts(), ) ) c.render("themeriver_chart.html")

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