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python可视化神器——pyecharts(词云图&雷达图&极坐标系)_pyechart词云图

作者：凡人多烦事01 | 2024-02-29 10:50:16

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pyechart词云图

与基本的Matplotlib绘图相比，pyecharts的交互以及可视化更为友好，更适合于项目开发、商业报告。

github.com/pyecharts/pyecharts

pyecharts 分为 v0.5.X 和 v1 两个大版本，v0.5.X 和 v1 间不兼容，v1 是一个全新的版本，很多函数的用法出现了变更

pip install pyecharts

第一个pyecharts程序

  • bar.add_x/yaxis() 添加横/纵坐标

  • bar.render() 存储文件，默认html文件

  1. #V1
  2.  
  3. from pyecharts.charts import Bar
  4.  
  5. bar = Bar()
  6. bar.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
  7. bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
  8. # render 会生成本地 HTML 文件，默认会在当前目录生成 render.html 文件
  9. # 也可以传入路径参数，如 bar.render("mycharts.html")
  10. bar.render()
  11. # render_notebook 则在notebook页面中直接显示
  12. bar.render_notebook()

常用图表绘制

v1就是正常的anaconda的python

v0.5的是pyecharts-v05的python环境     pyecharts==0.1.9.4

v1的样例：

https://github.com/pyecharts/pyecharts/tree/master/example

图云

  1. #V1
  2.  
  3. from pyecharts import options as opts
  4. from pyecharts.charts import Page, WordCloud
  5. from pyecharts.globals import SymbolType
  6.  
  7. words = [
  8.     ("花鸟市场", 1446),("汽车", 928),("视频", 906),("电视", 825),("家居饰品", 29),("家居日常用品", 10),("生活服务", 883),("物流配送", 536),("家政服务", 108),("摄影服务", 49),("搬家服务", 38),("物业维修", 37),("婚庆服务", 24),("二手回收", 24),("鲜花配送", 3),("维修服务", 3)
  9. ]
  10.  
  11. wordCloud = WordCloud()
  12. wordCloud.add("", words, word_size_range=[20, 100])
  13.  
  14. wordCloud.render()

word_size_range是设置字体大小

  1. #v0.5
  2. from pyecharts import WordCloud
  3.  
  4. name = ['Sam S Club', 'Macys', 'Amy Schumer', 'Jurassic World', 'Charter Communications',
  5.         'Chick Fil A', 'Planet Fitness', 'Pitch Perfect', 'Express', 'Home', 'Johnny Depp',
  6.         'Lena Dunham', 'Lewis Hamilton', 'KXAN', 'Mary Ellen Mark', 'Farrah Abraham',
  7.         'Rita Ora', 'Serena Williams', 'NCAA baseball tournament', 'Point Break']
  8. value = [10000, 6181, 4386, 4055, 2467, 2244, 1898, 1484, 1112, 965, 847, 582, 555,
  9.          550, 462, 366, 360, 282, 273, 265]
  10. wordcloud = WordCloud(width=1300, height=620)
  11. wordcloud.add("", name, value, word_size_range=[20, 100])
  12. wordcloud.show_config()
  13. wordcloud.render()

水滴球

  1. #v0.5
  2. from pyecharts import Liquid
  3.  
  4. liquid = Liquid("水球图示例")
  5. liquid.add("Liquid", [0.6, 0.5, 0.4, 0.3], is_liquid_animation=False, shape='diamond')
  6. #liquid.show_config()
  7. liquid.render()

  1. #v0.5
  2. from pyecharts import Liquid
  3.  
  4. liquid = Liquid("水球图示例")
  5. liquid.add("Liquid", [0.6])
  6. liquid.show_config()
  7. liquid.render()

这个是动态的，上面那个是静态的

  1. #v1
  2.  
  3. from pyecharts import options as opts
  4. from pyecharts.charts import Grid, Liquid, Page
  5. from pyecharts.commons.utils import JsCode
  6. from pyecharts.faker import Collector
  7. from pyecharts.globals import SymbolType
  8.  
  9. C = Collector()
  10.  
  11.  
  12. @C.funcs
  13. def liquid_base() -> Liquid:
  14.     c = (
  15.         Liquid()
  16.         .add("lq", [0.6, 0.7])
  17.         .set_global_opts(title_opts=opts.TitleOpts(title="Liquid-基本示例"))
  18.     )
  19.     return c
  20.  
  21.  
  22. @C.funcs
  23. def liquid_data_precision() -> Liquid:
  24.     c = (
  25.         Liquid()
  26.         .add(
  27.             "lq",
  28.             [0.3254],
  29.             label_opts=opts.LabelOpts(
  30.                 font_size=50,
  31.                 formatter=JsCode(
  32.                     """function (param) {
  33.                         return (Math.floor(param.value * 10000) / 100) + '%';
  34.                     }"""
  35.                 ),
  36.                 position="inside",
  37.             ),
  38.         )
  39.         .set_global_opts(title_opts=opts.TitleOpts(title="Liquid-数据精度"))
  40.     )
  41.     return c
  42.  
  43.  
  44. @C.funcs
  45. def liquid_without_outline() -> Liquid:
  46.     c = (
  47.         Liquid()
  48.         .add("lq", [0.6, 0.7, 0.8], is_outline_show=False)
  49.         .set_global_opts(title_opts=opts.TitleOpts(title="Liquid-无边框"))
  50.     )
  51.     return c
  52.  
  53.  
  54. @C.funcs
  55. def liquid_shape_diamond() -> Liquid:
  56.     c = (
  57.         Liquid()
  58.         .add("lq", [0.4, 0.7], is_outline_show=False, shape=SymbolType.DIAMOND)
  59.         .set_global_opts(title_opts=opts.TitleOpts(title="Liquid-Shape-diamond"))
  60.     )
  61.     return c
  62.  
  63.  
  64. @C.funcs
  65. def liquid_shape_arrow() -> Liquid:
  66.     c = (
  67.         Liquid()
  68.         .add("lq", [0.3, 0.7], is_outline_show=False, shape=SymbolType.ARROW)
  69.         .set_global_opts(title_opts=opts.TitleOpts(title="Liquid-Shape-arrow"))
  70.     )
  71.     return c
  72.  
  73.  
  74. @C.funcs
  75. def liquid_shape_rect() -> Liquid:
  76.     c = (
  77.         Liquid()
  78.         .add("lq", [0.3, 0.7], is_outline_show=False, shape=SymbolType.RECT)
  79.         .set_global_opts(title_opts=opts.TitleOpts(title="Liquid-Shape-rect"))
  80.     )
  81.     return c
  82.  
  83.  
  84. @C.funcs
  85. def multiple_liquid() -> Grid:
  86.     l1 = (
  87.         Liquid()
  88.         .add("lq", [0.6, 0.7], center=["60%", "50%"])
  89.         .set_global_opts(title_opts=opts.TitleOpts(title="多个 Liquid 显示"))
  90.     )
  91.  
  92.     l2 = Liquid().add(
  93.         "lq",
  94.         [0.3254],
  95.         center=["25%", "50%"],
  96.         label_opts=opts.LabelOpts(
  97.             font_size=50,
  98.             formatter=JsCode(
  99.                 """function (param) {
  100.                         return (Math.floor(param.value * 10000) / 100) + '%';
  101.                     }"""
  102.             ),
  103.             position="inside",
  104.         ),
  105.     )
  106.  
  107.     grid = Grid().add(l1, grid_opts=opts.GridOpts()).add(l2, grid_opts=opts.GridOpts())
  108.     return grid
  109.  
  110.  
  111. Page().add(*[fn() for fn, _ in C.charts]).render()

仪表盘

  1. #v0.5
  2. from pyecharts import Gauge
  3.  
  4. gauge = Gauge("仪表盘示例")
  5. gauge.add("业务指标", "完成率", 66.66)
  6. gauge.show_config()
  7. gauge.render()

  1. from pyecharts import options as opts
  2. from pyecharts.charts import Gauge, Page
  3. from pyecharts.faker import Collector
  4.  
  5. C = Collector()
  6.  
  7.  
  8. @C.funcs
  9. def gauge_base() -> Gauge:
  10.     c = (
  11.         Gauge()
  12.         .add("", [("完成率", 66.6)])
  13.         .set_global_opts(title_opts=opts.TitleOpts(title="Gauge-基本示例"))
  14.     )
  15.     return c
  16.  
  17.  
  18. @C.funcs
  19. def gauge_color() -> Gauge:
  20.     c = (
  21.         Gauge()
  22.         .add(
  23.             "业务指标",
  24.             [("完成率", 55.5)],
  25.             axisline_opts=opts.AxisLineOpts(
  26.                 linestyle_opts=opts.LineStyleOpts(
  27.                     color=[(0.3, "#67e0e3"), (0.7, "#37a2da"), (1, "#fd666d")], width=30
  28.                 )
  29.             ),
  30.         )
  31.         .set_global_opts(
  32.             title_opts=opts.TitleOpts(title="Gauge-不同颜色"),
  33.             legend_opts=opts.LegendOpts(is_show=False),
  34.         )
  35.     )
  36.     return c
  37.  
  38.  
  39. @C.funcs
  40. def gauge_splitnum_label() -> Gauge:
  41.     c = (
  42.         Gauge()
  43.         .add(
  44.             "业务指标",
  45.             [("完成率", 55.5)],
  46.             split_number=5,
  47.             axisline_opts=opts.AxisLineOpts(
  48.                 linestyle_opts=opts.LineStyleOpts(
  49.                     color=[(0.3, "#67e0e3"), (0.7, "#37a2da"), (1, "#fd666d")], width=30
  50.                 )
  51.             ),
  52.             detail_label_opts=opts.LabelOpts(formatter="{value}"),
  53.         )
  54.         .set_global_opts(
  55.             title_opts=opts.TitleOpts(title="Gauge-分割段数-Label"),
  56.             legend_opts=opts.LegendOpts(is_show=False),
  57.         )
  58.     )
  59.     return c
  60.  
  61.  
  62. @C.funcs
  63. def gauge_label_title_setting() -> Gauge:
  64.     c = (
  65.         Gauge()
  66.         .add(
  67.             "",
  68.             [("完成率", 66.6)],
  69.             title_label_opts=opts.LabelOpts(
  70.                 font_size=40, color="blue", font_family="Microsoft YaHei"
  71.             ),
  72.         )
  73.         .set_global_opts(title_opts=opts.TitleOpts(title="Gauge-改变轮盘内的字体"))
  74.     )
  75.     return c
  76.  
  77.  
  78. @C.funcs
  79. def gauge_change_radius() -> Gauge:
  80.     c = (
  81.         Gauge()
  82.         .add("", [("完成率", 66.6)], radius="50%")
  83.         .set_global_opts(title_opts=opts.TitleOpts(title="Gauge-修改 Radius 为 50%"))
  84.     )
  85.     return c
  86.  
  87.  
  88. Page().add(*[fn() for fn, _ in C.charts]).render()

雷达图

  1. #v0.5
  2. from pyecharts import Radar
  3.  
  4. schema = [ 
  5.     ("销售", 6500), ("管理", 16000), ("信息技术", 30000), ("客服", 38000), ("研发", 52000), ("市场", 25000)]
  6. v1 = [[4300, 10000, 28000, 35000, 50000, 19000]]
  7. v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]
  8. radar = Radar()
  9. radar.config(schema)
  10. radar.add("预算分配", v1, is_splitline=True, is_axisline_show=True)
  11. radar.add("实际开销", v2, label_color=["#4e79a7"], is_area_show=False)
  12. radar.show_config()
  13. radar.render()

点击上方的红蓝点还可以显示/隐藏图线

  1. #v0.5
  2. from pyecharts import Radar
  3. value_bj = [
  4.     [55, 9, 56, 0.46, 18, 6, 1], [25, 11, 21, 0.65, 34, 9, 2],
  5.     [56, 7, 63, 0.3, 14, 5, 3], [33, 7, 29, 0.33, 16, 6, 4]]
  6.  
  7. value_sh = [
  8.     [91, 45, 125, 0.82, 34, 23, 1], [65, 27, 78, 0.86, 45, 29, 2],
  9.     [83, 60, 84, 1.09, 73, 27, 3], [109, 81, 121, 1.28, 68, 51, 4]]
  10.  
  11. c_schema= [{"name": "AQI", "max": 300, "min": 5},
  12.            {"name": "PM2.5", "max": 250, "min": 20},
  13.            {"name": "PM10", "max": 300, "min": 5},
  14.            {"name": "CO", "max": 5},
  15.            {"name": "NO2", "max": 200},
  16.            {"name": "SO2", "max": 100}]
  17. radar = Radar()
  18. radar.config(c_schema=c_schema, shape='circle')
  19. radar.add("北京", value_bj, item_color="#f9713c", symbol=None)
  20. radar.add("上海", value_sh, item_color="#b3e4a1", symbol=None)
  21. radar.show_config()
  22. radar.render()

漏斗图

  1. #v0.5
  2. from pyecharts import Funnel
  3.  
  4. attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
  5. value = [20, 40, 60, 80, 100, 120]
  6. funnel = Funnel("漏斗图示例")
  7. funnel.add("商品", attr, value, is_label_show=True, label_pos="inside", label_text_color="#fff")
  8. funnel.render()

  1. #v1
  2. from pyecharts import options as opts
  3. from pyecharts.charts import Funnel, Page
  4. from pyecharts.faker import Collector, Faker
  5.  
  6. C = Collector()
  7.  
  8.  
  9. @C.funcs
  10. def funnel_base() -> Funnel:
  11.     c = (
  12.         Funnel()
  13.         .add("商品", [list(z) for z in zip(Faker.choose(), Faker.values())])
  14.         .set_global_opts(title_opts=opts.TitleOpts(title="Funnel-基本示例"))
  15.     )
  16.     return c
  17.  
  18.  
  19. @C.funcs
  20. def funnel_label_inside() -> Funnel:
  21.     c = (
  22.         Funnel()
  23.         .add(
  24.             "商品",
  25.             [list(z) for z in zip(Faker.choose(), Faker.values())],
  26.             label_opts=opts.LabelOpts(position="inside"),
  27.         )
  28.         .set_global_opts(title_opts=opts.TitleOpts(title="Funnel-Label（inside)"))
  29.     )
  30.     return c
  31.  
  32.  
  33. @C.funcs
  34. def funnel_sort_ascending() -> Funnel:
  35.     c = (
  36.         Funnel()
  37.         .add(
  38.             "商品",
  39.             [list(z) for z in zip(Faker.choose(), Faker.values())],
  40.             sort_="ascending",
  41.             label_opts=opts.LabelOpts(position="inside"),
  42.         )
  43.         .set_global_opts(title_opts=opts.TitleOpts(title="Funnel-Sort（ascending）"))
  44.     )
  45.     return c
  46.  
  47.  
  48. Page().add(*[fn() for fn, _ in C.charts]).render()

日历图

  1. import datetime
  2. import random
  3.  
  4. from pyecharts import options as opts
  5. from pyecharts.charts import Calendar, Page
  6. from pyecharts.faker import Collector
  7.  
  8. C = Collector()
  9.  
  10.  
  11. @C.funcs
  12. def calendar_base() -> Calendar:
  13.     begin = datetime.date(2017, 1, 1)
  14.     end = datetime.date(2017, 12, 31)
  15.     data = [
  16.         [str(begin + datetime.timedelta(days=i)), random.randint(1000, 25000)]
  17.         for i in range((end - begin).days + 1)
  18.     ]
  19.  
  20.     c = (
  21.         Calendar()
  22.         .add("", data, calendar_opts=opts.CalendarOpts(range_="2017"))
  23.         .set_global_opts(
  24.             title_opts=opts.TitleOpts(title="Calendar-2017年微信步数情况"),
  25.             visualmap_opts=opts.VisualMapOpts(
  26.                 max_=20000,
  27.                 min_=500,
  28.                 orient="horizontal",
  29.                 is_piecewise=True,
  30.                 pos_top="230px",
  31.                 pos_left="100px",
  32.             ),
  33.         )
  34.     )
  35.     return c
  36.  
  37.  
  38. @C.funcs
  39. def calendar_label_setting() -> Calendar:
  40.     begin = datetime.date(2017, 1, 1)
  41.     end = datetime.date(2017, 12, 31)
  42.     data = [
  43.         [str(begin + datetime.timedelta(days=i)), random.randint(1000, 25000)]
  44.         for i in range((end - begin).days + 1)
  45.     ]
  46.  
  47.     c = (
  48.         Calendar()
  49.         .add(
  50.             "",
  51.             data,
  52.             calendar_opts=opts.CalendarOpts(
  53.                 range_="2017",
  54.                 daylabel_opts=opts.CalendarDayLabelOpts(name_map="cn"),
  55.                 monthlabel_opts=opts.CalendarMonthLabelOpts(name_map="cn"),
  56.             ),
  57.         )
  58.         .set_global_opts(
  59.             title_opts=opts.TitleOpts(title="Calendar-2017年微信步数情况(中文 Label)"),
  60.             visualmap_opts=opts.VisualMapOpts(
  61.                 max_=20000,
  62.                 min_=500,
  63.                 orient="horizontal",
  64.                 is_piecewise=True,
  65.                 pos_top="230px",
  66.                 pos_left="100px",
  67.             ),
  68.         )
  69.     )
  70.     return c
  71.  
  72.  
  73. Page().add(*[fn() for fn, _ in C.charts]).render()

微博转发关系图

  1. #v0.5
  2. from pyecharts import Graph
  3. import json
  4. with open("weibo.json", "r", encoding="utf-8") as f:
  5.     j = json.load(f)
  6.     nodes, links, categories, cont, mid, userl = j
  7. graph = Graph("微博转发关系图", width=1200, height=600)
  8.  
  9. graph.add("", nodes, links, categories, label_pos="right", repulsion=50, is_legend_show=False,
  10.           line_curve=0.2, label_text_color=None)
  11. graph.show_config()
  12. graph.render()

weibo.json可以在这里下

github.com/pyecharts/pyecharts/tree/master/example/fixtures

  1. import json
  2. import os
  3.  
  4. from pyecharts.commons.utils import JsCode
  5.  
  6. #v1
  7.  
  8. from pyecharts import options as opts
  9. from pyecharts.charts import Graph, Page
  10. from pyecharts.faker import Collector
  11.  
  12. C = Collector()
  13.  
  14.  
  15. @C.funcs
  16. def graph_base() -> Graph:
  17.     nodes = [
  18.         {"name": "结点1", "symbolSize": 10},
  19.         {"name": "结点2", "symbolSize": 20},
  20.         {"name": "结点3", "symbolSize": 30},
  21.         {"name": "结点4", "symbolSize": 40},
  22.         {"name": "结点5", "symbolSize": 50},
  23.         {"name": "结点6", "symbolSize": 40},
  24.         {"name": "结点7", "symbolSize": 30},
  25.         {"name": "结点8", "symbolSize": 20},
  26.     ]
  27.     links = []
  28.     for i in nodes:
  29.         for j in nodes:
  30.             links.append({"source": i.get("name"), "target": j.get("name")})
  31.     c = (
  32.         Graph()
  33.         .add("", nodes, links, repulsion=8000)
  34.         .set_global_opts(title_opts=opts.TitleOpts(title="Graph-基本示例"))
  35.     )
  36.     return c
  37.  
  38.  
  39. @C.funcs
  40. def graph_with_opts() -> Graph:
  41.     nodes = [
  42.         opts.GraphNode(name="结点1", symbol_size=10),
  43.         opts.GraphNode(name="结点2", symbol_size=20),
  44.         opts.GraphNode(name="结点3", symbol_size=30),
  45.         opts.GraphNode(name="结点4", symbol_size=40),
  46.         opts.GraphNode(name="结点5", symbol_size=50),
  47.     ]
  48.     links = [
  49.         opts.GraphLink(source="结点1", target="结点2"),
  50.         opts.GraphLink(source="结点2", target="结点3"),
  51.         opts.GraphLink(source="结点3", target="结点4"),
  52.         opts.GraphLink(source="结点4", target="结点5"),
  53.         opts.GraphLink(source="结点5", target="结点1"),
  54.     ]
  55.     c = (
  56.         Graph()
  57.         .add("", nodes, links, repulsion=4000)
  58.         .set_global_opts(title_opts=opts.TitleOpts(title="Graph-GraphNode-GraphLink"))
  59.     )
  60.     return c
  61.  
  62.  
  63. @C.funcs
  64. def graph_with_edge_opts() -> Graph:
  65.     nodes_data = [
  66.         opts.GraphNode(name="结点1", symbol_size=10),
  67.         opts.GraphNode(name="结点2", symbol_size=20),
  68.         opts.GraphNode(name="结点3", symbol_size=30),
  69.         opts.GraphNode(name="结点4", symbol_size=40),
  70.         opts.GraphNode(name="结点5", symbol_size=50),
  71.         opts.GraphNode(name="结点6", symbol_size=60),
  72.     ]
  73.     links_data = [
  74.         opts.GraphLink(source="结点1", target="结点2", value=2),
  75.         opts.GraphLink(source="结点2", target="结点3", value=3),
  76.         opts.GraphLink(source="结点3", target="结点4", value=4),
  77.         opts.GraphLink(source="结点4", target="结点5", value=5),
  78.         opts.GraphLink(source="结点5", target="结点6", value=6),
  79.         opts.GraphLink(source="结点6", target="结点1", value=7),
  80.     ]
  81.     c = (
  82.         Graph()
  83.         .add(
  84.             "",
  85.             nodes_data,
  86.             links_data,
  87.             repulsion=4000,
  88.             edge_label=opts.LabelOpts(
  89.                 is_show=True, position="middle", formatter="{b} 的数据 {c}"
  90.             ),
  91.         )
  92.         .set_global_opts(
  93.             title_opts=opts.TitleOpts(title="Graph-GraphNode-GraphLink-WithEdgeLabel")
  94.         )
  95.     )
  96.     return c
  97.  
  98.  
  99. @C.funcs
  100. def graph_weibo() -> Graph:
  101.     with open(os.path.join("fixtures", "weibo.json"), "r", encoding="utf-8") as f:
  102.         j = json.load(f)
  103.         nodes, links, categories, cont, mid, userl = j
  104.     c = (
  105.         Graph()
  106.         .add(
  107.             "",
  108.             nodes,
  109.             links,
  110.             categories,
  111.             repulsion=50,
  112.             linestyle_opts=opts.LineStyleOpts(curve=0.2),
  113.             label_opts=opts.LabelOpts(is_show=False),
  114.         )
  115.         .set_global_opts(
  116.             legend_opts=opts.LegendOpts(is_show=False),
  117.             title_opts=opts.TitleOpts(title="Graph-微博转发关系图"),
  118.         )
  119.     )
  120.     return c
  121.  
  122.  
  123. @C.funcs
  124. def graph_les_miserables():
  125.     with open(
  126.         os.path.join("fixtures", "les-miserables.json"), "r", encoding="utf-8"
  127.     ) as f:
  128.         j = json.load(f)
  129.         nodes = j["nodes"]
  130.         links = j["links"]
  131.         categories = j["categories"]
  132.  
  133.     c = (
  134.         Graph(init_opts=opts.InitOpts(width="1000px", height="600px"))
  135.         .add(
  136.             "",
  137.             nodes=nodes,
  138.             links=links,
  139.             categories=categories,
  140.             layout="circular",
  141.             is_rotate_label=True,
  142.             linestyle_opts=opts.LineStyleOpts(color="source", curve=0.3),
  143.             label_opts=opts.LabelOpts(position="right"),
  144.         )
  145.         .set_global_opts(
  146.             title_opts=opts.TitleOpts(title="Graph-Les Miserables"),
  147.             legend_opts=opts.LegendOpts(
  148.                 orient="vertical", pos_left="2%", pos_top="20%"
  149.             ),
  150.         )
  151.     )
  152.     return c
  153.  
  154.  
  155. @C.funcs
  156. def graph_npm_dependencies() -> Graph:
  157.     with open(os.path.join("fixtures", "npmdepgraph.json"), "r", encoding="utf-8") as f:
  158.         j = json.load(f)
  159.     nodes = [
  160.         {
  161.             "x": node["x"],
  162.             "y": node["y"],
  163.             "id": node["id"],
  164.             "name": node["label"],
  165.             "symbolSize": node["size"],
  166.             "itemStyle": {"normal": {"color": node["color"]}},
  167.         }
  168.         for node in j["nodes"]
  169.     ]
  170.  
  171.     edges = [
  172.         {"source": edge["sourceID"], "target": edge["targetID"]} for edge in j["edges"]
  173.     ]
  174.  
  175.     c = (
  176.         Graph(init_opts=opts.InitOpts(width="1000px", height="600px"))
  177.         .add(
  178.             "",
  179.             nodes=nodes,
  180.             links=edges,
  181.             layout="none",
  182.             label_opts=opts.LabelOpts(is_show=False),
  183.             linestyle_opts=opts.LineStyleOpts(width=0.5, curve=0.3, opacity=0.7),
  184.         )
  185.         .set_global_opts(title_opts=opts.TitleOpts(title="Graph-NPM Dependencies"))
  186.     )
  187.     return c
  188.  
  189.  
  190. Page().add(*[fn() for fn, _ in C.charts]).render()

带有涟漪特效动画的散点图

  1. #v0.5
  2.  
  3. from pyecharts import EffectScatter
  4. es = EffectScatter("动态散点图各种图形示例")
  5. es.add("", [10], [10], symbol_size=20, effect_scale=3.5, effect_period=3, symbol="pin")
  6. es.add("", [20], [20], symbol_size=12, effect_scale=4.5, effect_period=4,symbol="rect")
  7. es.add("", [30], [30], symbol_size=30, effect_scale=5.5, effect_period=5,symbol="roundRect")
  8. es.add("", [40], [40], symbol_size=10, effect_scale=6.5, effect_brushtype='fill',symbol="diamond")
  9. es.add("", [50], [50], symbol_size=16, effect_scale=5.5, effect_period=3,symbol="arrow")
  10. es.add("", [60], [60], symbol_size=6, effect_scale=2.5, effect_period=3,symbol="triangle")
  11. es.render()

  1. #v0.5
  2. from pyecharts import EffectScatter
  3. es = EffectScatter('散点图举例',background_color = 'white',title_text_size = 25)
  4. v1 = [12,22,34,29,16,14,18]
  5. v2 = [23,45,68,58,32,28,36]
  6. es.add('', v1, v2,symbol = 'pin',effect_scale = 5.5,xaxis_min = 10)
  7. es.render()

  1. #v0.5
  2.  
  3. from pyecharts import EffectScatter
  4. v1 = [10, 20, 30, 40, 50, 60]
  5. v2 = [25, 20, 15, 10, 60, 33]
  6. es = EffectScatter("动态散点图示例")
  7. es.add("effectScatter", v1, v2)
  8. es.render()

关系图——力引导布局

  1. #v0.5
  2.  
  3. from pyecharts import Graph
  4. nodes = [{"name": "结点1", "symbolSize": 10},
  5.          {"name": "结点2", "symbolSize": 20},
  6.          {"name": "结点3", "symbolSize": 30},
  7.          {"name": "结点4", "symbolSize": 40},
  8.          {"name": "结点5", "symbolSize": 50},
  9.          {"name": "结点6", "symbolSize": 40},
  10.          {"name": "结点7", "symbolSize": 30},
  11.          {"name": "结点8", "symbolSize": 20}]
  12. links = []
  13. for i in nodes:
  14.     for j in nodes:
  15.         links.append({"source": i.get('name'), "target": j.get('name')})
  16. graph = Graph("关系图-环形布局示例")
  17. graph.add("", nodes, links, is_label_show=True, repulsion=8000, layout='circular', label_text_color=None)
  18. graph.show_config()
  19. graph.render()

饼图

  1. #v0.5
  2. from pyecharts import Pie
  3.  
  4. attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
  5. v1 = [11, 12, 13, 10, 10, 10]
  6. pie = Pie("饼图示例")
  7. pie.add("", attr, v1, is_label_show=True)
  8. pie.show_config()
  9. pie.render()

饼图—玫瑰图

  1. #v0.5
  2. from pyecharts import Pie
  3.  
  4. attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
  5. v1 = [11, 12, 13, 10, 10, 10]
  6. v2 = [19, 21, 32, 20, 20, 33]
  7. pie = Pie("饼图-玫瑰图示例", title_pos='center', width=900)
  8. pie.add("商品A", attr, v1, center=[25, 50], is_random=True, radius=[30, 75], rosetype='radius')
  9. pie.add("商品B", attr, v2, center=[75, 50], is_random=True, radius=[30, 75], rosetype='area',
  10.         is_legend_show=False, is_label_show=True)
  11. pie.show_config() 
  12. pie.render()

  1. #v0.5
  2. from pyecharts import Pie
  3. pie =Pie('各类电影中"好片"所占的比例', "数据来着豆瓣", title_pos='center')
  4. pie.add("", ["剧情", ""], [25, 75], center=[10, 30], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None, )
  5. pie.add("", ["奇幻", ""], [24, 76], center=[30, 30], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None, legend_pos='left')
  6. pie.add("", ["爱情", ""], [14, 86], center=[50, 30], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None)
  7. pie.add("", ["惊悚", ""], [11, 89], center=[70, 30], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None)
  8. pie.add("", ["冒险", ""], [27, 73], center=[90, 30], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None)
  9. pie.add("", ["动作", ""], [15, 85], center=[10, 70], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None)
  10. pie.add("", ["喜剧", ""], [54, 46], center=[30, 70], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None)
  11. pie.add("", ["科幻", ""], [26, 74], center=[50, 70], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None)
  12. pie.add("", ["悬疑", ""], [25, 75], center=[70, 70], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None)
  13. pie.add("", ["犯罪", ""], [28, 72], center=[90, 70], radius=[18, 24], label_pos='center', is_label_show=True, label_text_color=None, is_legend_show=True, legend_top="center")
  14. pie.show_config()
  15. pie.render()

极坐标系

  1. #v0.5
  2. from pyecharts import Polar
  3.  
  4. radius = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
  5. polar = Polar("极坐标系-堆叠柱状图示例", width=1200, height=600)
  6. polar.add("A", [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type='barRadius', is_stack=True)
  7. polar.add("B", [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type='barRadius', is_stack=True)
  8. polar.add("C", [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type='barRadius', is_stack=True)
  9. polar.show_config()
  10. polar.render()

  1. #v0.5
  2. from pyecharts import Polar
  3.  
  4. radius = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
  5. polar = Polar("极坐标系-堆叠柱状图示例", width=1200, height=600)
  6. polar.add("", [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type='barAngle', is_stack=True)
  7. polar.add("", [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type='barAngle', is_stack=True)
  8. polar.add("", [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type='barAngle', is_stack=True)
  9. polar.show_config()
  10. polar.render()

  1. #v1
  2.  
  3. import math
  4. import random
  5.  
  6. from pyecharts import options as opts
  7. from pyecharts.charts import Page, Polar
  8. from pyecharts.faker import Collector, Faker
  9.  
  10. C = Collector()
  11.  
  12.  
  13. @C.funcs
  14. def polar_scatter0() -> Polar:
  15.     data = [(i, random.randint(1, 100)) for i in range(101)]
  16.     c = (
  17.         Polar()
  18.         .add("", data, type_="scatter", label_opts=opts.LabelOpts(is_show=False))
  19.         .set_global_opts(title_opts=opts.TitleOpts(title="Polar-Scatter0"))
  20.     )
  21.     return c
  22.  
  23.  
  24. @C.funcs
  25. def polar_scatter1() -> Polar:
  26.     c = (
  27.         Polar()
  28.         .add("", [(10, random.randint(1, 100)) for i in range(300)], type_="scatter")
  29.         .add("", [(11, random.randint(1, 100)) for i in range(300)], type_="scatter")
  30.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  31.         .set_global_opts(title_opts=opts.TitleOpts(title="Polar-Scatter1"))
  32.     )
  33.  
  34.     return c
  35.  
  36.  
  37. @C.funcs
  38. def polar_effectscatter() -> Polar:
  39.     data = [(i, random.randint(1, 100)) for i in range(10)]
  40.     c = (
  41.         Polar()
  42.         .add(
  43.             "",
  44.             data,
  45.             type_="effectScatter",
  46.             effect_opts=opts.EffectOpts(scale=10, period=5),
  47.             label_opts=opts.LabelOpts(is_show=False),
  48.         )
  49.         .set_global_opts(title_opts=opts.TitleOpts(title="Polar-EffectScatter"))
  50.     )
  51.     return c
  52.  
  53.  
  54. @C.funcs
  55. def polar_radiusaxis() -> Polar:
  56.     c = (
  57.         Polar()
  58.         .add_schema(
  59.             radiusaxis_opts=opts.RadiusAxisOpts(data=Faker.week, type_="category"),
  60.             angleaxis_opts=opts.AngleAxisOpts(is_clockwise=True, max_=10),
  61.         )
  62.         .add("A", [1, 2, 3, 4, 3, 5, 1], type_="bar")
  63.         .set_global_opts(title_opts=opts.TitleOpts(title="Polar-RadiusAxis"))
  64.         .set_series_opts(label_opts=opts.LabelOpts(is_show=True))
  65.     )
  66.     return c
  67.  
  68.  
  69. @C.funcs
  70. def polar_angleaxis() -> Polar:
  71.     c = (
  72.         Polar()
  73.         .add_schema(
  74.             angleaxis_opts=opts.AngleAxisOpts(data=Faker.week, type_="category")
  75.         )
  76.         .add("A", [1, 2, 3, 4, 3, 5, 1], type_="bar", stack="stack0")
  77.         .add("B", [2, 4, 6, 1, 2, 3, 1], type_="bar", stack="stack0")
  78.         .add("C", [1, 2, 3, 4, 1, 2, 5], type_="bar", stack="stack0")
  79.         .set_global_opts(title_opts=opts.TitleOpts(title="Polar-AngleAxis"))
  80.     )
  81.     return c
  82.  
  83.  
  84. @C.funcs
  85. def polar_love() -> Polar:
  86.     data = []
  87.     for i in range(101):
  88.         theta = i / 100 * 360
  89.         r = 5 * (1 + math.sin(theta / 180 * math.pi))
  90.         data.append([r, theta])
  91.     hour = [i for i in range(1, 25)]
  92.     c = (
  93.         Polar()
  94.         .add_schema(
  95.             angleaxis_opts=opts.AngleAxisOpts(
  96.                 data=hour, type_="value", boundary_gap=False, start_angle=0
  97.             )
  98.         )
  99.         .add("love", data, label_opts=opts.LabelOpts(is_show=False))
  100.         .set_global_opts(title_opts=opts.TitleOpts(title="Polar-Love"))
  101.     )
  102.     return c
  103.  
  104.  
  105. @C.funcs
  106. def polar_flower() -> Polar:
  107.     data = []
  108.     for i in range(361):
  109.         t = i / 180 * math.pi
  110.         r = math.sin(2 * t) * math.cos(2 * t)
  111.         data.append([r, i])
  112.     c = (
  113.         Polar()
  114.         .add_schema(angleaxis_opts=opts.AngleAxisOpts(start_angle=0, min_=0))
  115.         .add("flower", data, label_opts=opts.LabelOpts(is_show=False))
  116.         .set_global_opts(title_opts=opts.TitleOpts(title="Polar-Flower"))
  117.     )
  118.     return c
  119.  
  120.  
  121. Page().add(*[fn() for fn, _ in C.charts]).render()

极坐标系画图案

  1. #v0.5
  2. import math 
  3. from pyecharts import Polar
  4. data =[]
  5. for i in range(101):
  6.     theta =i /100*360
  7.     r =5*(1+math.sin(theta /180*math.pi)) 
  8.     data.append([r, theta])
  9. hour =[i for i in range(1, 25)]
  10. polar =Polar("极坐标系示例", width=1200, height=600)
  11. polar.add("Love", data, angle_data=hour, boundary_gap=False,start_angle=0)
  12. polar.show_config()
  13. polar.render()

  1. #v0.5
  2. import math
  3. from pyecharts import Polar
  4. data =[]
  5. for i in range(361): 
  6.     t =i /180*math.pi 
  7.     r =math.sin(2*t) *math.cos(2*t) 
  8.     data.append([r, i])
  9. polar =Polar("极坐标系示例", width=1200, height=600)
  10. polar.add("Flower", data, start_angle=0, symbol=None, axis_range=[0, None])
  11. polar.show_config()
  12. polar.render()

  1. #v0.5
  2. import math
  3. from pyecharts import Polar
  4. data =[]
  5. for i in range(361): 
  6.     t =i /180*math.pi 
  7.     r =math.sin(2*t) *math.cos(2*t) 
  8.     data.append([r, i])
  9. polar =Polar("极坐标系示例", width=1200, height=600)
  10. polar.add("Color-Flower", data, start_angle=0, symbol=None, axis_range=[0, None], area_color="#f71f24", area_opacity=0.6)
  11. polar.show_config()
  12. polar.render()

  1. #v0.5
  2. import math
  3. from pyecharts import Polar
  4. data =[]
  5. for i in range(5): 
  6. 	for j in range(101): 
  7. 		theta =j /100*360
  8. 		alpha =i *360+theta 
  9. 		r =math.pow(math.e, 0.003*alpha) 
  10. 		data.append([r, theta])
  11.  
  12. polar =Polar("极坐标系示例")
  13. polar.add("", data, symbol_size=0, symbol='circle', start_angle=-25, is_radiusaxis_show=False, area_color="#f3c5b3", area_opacity=0.5, is_angleaxis_show=False)
  14. polar.show_config()
  15. polar.render()

折线/面积图

  1. #v0.5
  2. from pyecharts import Line
  3.  
  4. attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
  5. v1 = [5, 20, 36, 10, 10, 100]
  6. v2 = [55, 60, 16, 20, 15, 80]
  7. line = Line("折线图示例")
  8. line.add("商家A", attr, v1, mark_point=["average"])
  9. line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"])
  10. line.show_config()
  11. line.render()

  1. #v0.5
  2. from pyecharts import Line
  3.  
  4. attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
  5. v1 = [5, 20, 36, 10, 10, 100]
  6. line = Line("折线图-阶梯图示例")
  7. line.add("商家A", attr, v1, is_step=True, is_label_show=True)
  8. line.show_config()
  9. line.render()

  1. #v0.5
  2. from pyecharts import Line
  3.  
  4. attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
  5. v1 = [5, 20, 36, 10, 10, 100]
  6. v2 = [55, 60, 16, 20, 15, 80]
  7. line = Line("折线图-面积图示例")
  8. line.add("商家A", attr, v1, is_fill=True, line_opacity=0.2, area_opacity=0.4, symbol=None)
  9. line.add("商家B", attr, v2, is_fill=True, area_color='#000', area_opacity=0.3, is_smooth=True)
  10. line.show_config()
  11. line.render()

  1. #v1
  2.  
  3. import pyecharts.options as opts
  4. from pyecharts.charts import Line, Page
  5. from pyecharts.commons.utils import JsCode
  6. from pyecharts.faker import Collector, Faker
  7.  
  8. C = Collector()
  9.  
  10.  
  11. @C.funcs
  12. def line_base() -> Line:
  13.     c = (
  14.         Line()
  15.         .add_xaxis(Faker.choose())
  16.         .add_yaxis("商家A", Faker.values())
  17.         .add_yaxis("商家B", Faker.values())
  18.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例"))
  19.     )
  20.     return c
  21.  
  22.  
  23. @C.funcs
  24. def line_connect_null() -> Line:
  25.     y = Faker.values()
  26.     y[3], y[5] = None, None
  27.     c = (
  28.         Line()
  29.         .add_xaxis(Faker.choose())
  30.         .add_yaxis("商家A", y, is_connect_nones=True)
  31.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-连接空数据"))
  32.     )
  33.     return c
  34.  
  35.  
  36. @C.funcs
  37. def line_smooth() -> Line:
  38.     c = (
  39.         Line()
  40.         .add_xaxis(Faker.choose())
  41.         .add_yaxis("商家A", Faker.values(), is_smooth=True)
  42.         .add_yaxis("商家B", Faker.values(), is_smooth=True)
  43.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-smooth"))
  44.     )
  45.     return c
  46.  
  47.  
  48. @C.funcs
  49. def line_areastyle() -> Line:
  50.     c = (
  51.         Line()
  52.         .add_xaxis(Faker.choose())
  53.         .add_yaxis(
  54.             "商家A", Faker.values(), areastyle_opts=opts.AreaStyleOpts(opacity=0.5)
  55.         )
  56.         .add_yaxis(
  57.             "商家B", Faker.values(), areastyle_opts=opts.AreaStyleOpts(opacity=0.5)
  58.         )
  59.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-面积图"))
  60.     )
  61.     return c
  62.  
  63.  
  64. @C.funcs
  65. def line_areastyle_boundary_gap() -> Line:
  66.     c = (
  67.         Line()
  68.         .add_xaxis(Faker.choose())
  69.         .add_yaxis("商家A", Faker.values(), is_smooth=True)
  70.         .add_yaxis("商家B", Faker.values(), is_smooth=True)
  71.         .set_series_opts(
  72.             areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
  73.             label_opts=opts.LabelOpts(is_show=False),
  74.         )
  75.         .set_global_opts(
  76.             title_opts=opts.TitleOpts(title="Line-面积图（紧贴 Y 轴）"),
  77.             xaxis_opts=opts.AxisOpts(
  78.                 axistick_opts=opts.AxisTickOpts(is_align_with_label=True),
  79.                 is_scale=False,
  80.                 boundary_gap=False,
  81.             ),
  82.         )
  83.     )
  84.     return c
  85.  
  86.  
  87. @C.funcs
  88. def line_yaxis_log() -> Line:
  89.     c = (
  90.         Line()
  91.         .add_xaxis(xaxis_data=["一", "二", "三", "四", "五", "六", "七", "八", "九"])
  92.         .add_yaxis(
  93.             "2 的指数",
  94.             y_axis=[1, 2, 4, 8, 16, 32, 64, 128, 256],
  95.             linestyle_opts=opts.LineStyleOpts(width=2),
  96.         )
  97.         .add_yaxis(
  98.             "3 的指数",
  99.             y_axis=[1, 3, 9, 27, 81, 247, 741, 2223, 6669],
  100.             linestyle_opts=opts.LineStyleOpts(width=2),
  101.         )
  102.         .set_global_opts(
  103.             title_opts=opts.TitleOpts(title="Line-对数轴示例"),
  104.             xaxis_opts=opts.AxisOpts(name="x"),
  105.             yaxis_opts=opts.AxisOpts(
  106.                 type_="log",
  107.                 name="y",
  108.                 splitline_opts=opts.SplitLineOpts(is_show=True),
  109.                 is_scale=True,
  110.             ),
  111.         )
  112.     )
  113.     return c
  114.  
  115.  
  116. @C.funcs
  117. def line_markpoint_custom() -> Line:
  118.     x, y = Faker.choose(), Faker.values()
  119.     c = (
  120.         Line()
  121.         .add_xaxis(x)
  122.         .add_yaxis(
  123.             "商家A",
  124.             y,
  125.             markpoint_opts=opts.MarkPointOpts(
  126.                 data=[opts.MarkPointItem(name="自定义标记点", coord=[x[2], y[2]], value=y[2])]
  127.             ),
  128.         )
  129.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-MarkPoint（自定义）"))
  130.     )
  131.     return c
  132.  
  133.  
  134. @C.funcs
  135. def line_markpoint() -> Line:
  136.     c = (
  137.         Line()
  138.         .add_xaxis(Faker.choose())
  139.         .add_yaxis(
  140.             "商家A",
  141.             Faker.values(),
  142.             markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="min")]),
  143.         )
  144.         .add_yaxis(
  145.             "商家B",
  146.             Faker.values(),
  147.             markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max")]),
  148.         )
  149.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-MarkPoint"))
  150.     )
  151.     return c
  152.  
  153.  
  154. @C.funcs
  155. def line_markline() -> Line:
  156.     c = (
  157.         Line()
  158.         .add_xaxis(Faker.choose())
  159.         .add_yaxis(
  160.             "商家A",
  161.             Faker.values(),
  162.             markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]),
  163.         )
  164.         .add_yaxis(
  165.             "商家B",
  166.             Faker.values(),
  167.             markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]),
  168.         )
  169.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-MarkLine"))
  170.     )
  171.     return c
  172.  
  173.  
  174. @C.funcs
  175. def line_step() -> Line:
  176.     c = (
  177.         Line()
  178.         .add_xaxis(Faker.choose())
  179.         .add_yaxis("商家A", Faker.values(), is_step=True)
  180.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-阶梯图"))
  181.     )
  182.     return c
  183.  
  184.  
  185. @C.funcs
  186. def line_itemstyle() -> Line:
  187.     c = (
  188.         Line()
  189.         .add_xaxis(xaxis_data=Faker.choose())
  190.         .add_yaxis(
  191.             "商家A",
  192.             Faker.values(),
  193.             symbol="triangle",
  194.             symbol_size=20,
  195.             linestyle_opts=opts.LineStyleOpts(color="green", width=4, type_="dashed"),
  196.             itemstyle_opts=opts.ItemStyleOpts(
  197.                 border_width=3, border_color="yellow", color="blue"
  198.             ),
  199.         )
  200.         .set_global_opts(title_opts=opts.TitleOpts(title="Line-ItemStyle"))
  201.     )
  202.     return c
  203.  
  204.  
  205. @C.funcs
  206. def line_color_with_js_func() -> Line:
  207.     x_data = ["14", "15", "16", "17", "18", "19", "20", "21", "22", "23"]
  208.     y_data = [393, 438, 485, 631, 689, 824, 987, 1000, 1100, 1200]
  209.  
  210.     background_color_js = (
  211.         "new echarts.graphic.LinearGradient(0, 0, 0, 1, "
  212.         "[{offset: 0, color: '#c86589'}, {offset: 1, color: '#06a7ff'}], false)"
  213.     )
  214.     area_color_js = (
  215.         "new echarts.graphic.LinearGradient(0, 0, 0, 1, "
  216.         "[{offset: 0, color: '#eb64fb'}, {offset: 1, color: '#3fbbff0d'}], false)"
  217.     )
  218.  
  219.     c = (
  220.         Line(init_opts=opts.InitOpts(bg_color=JsCode(background_color_js)))
  221.         .add_xaxis(xaxis_data=x_data)
  222.         .add_yaxis(
  223.             series_name="注册总量",
  224.             y_axis=y_data,
  225.             is_smooth=True,
  226.             is_symbol_show=True,
  227.             symbol="circle",
  228.             symbol_size=6,
  229.             linestyle_opts=opts.LineStyleOpts(color="#fff"),
  230.             label_opts=opts.LabelOpts(is_show=True, position="top", color="white"),
  231.             itemstyle_opts=opts.ItemStyleOpts(
  232.                 color="red", border_color="#fff", border_width=3
  233.             ),
  234.             tooltip_opts=opts.TooltipOpts(is_show=False),
  235.             areastyle_opts=opts.AreaStyleOpts(color=JsCode(area_color_js), opacity=1),
  236.         )
  237.         .set_global_opts(
  238.             title_opts=opts.TitleOpts(
  239.                 title="OCTOBER 2015",
  240.                 pos_bottom="5%",
  241.                 pos_left="center",
  242.                 title_textstyle_opts=opts.TextStyleOpts(color="#fff", font_size=16),
  243.             ),
  244.             xaxis_opts=opts.AxisOpts(
  245.                 type_="category",
  246.                 boundary_gap=False,
  247.                 axislabel_opts=opts.LabelOpts(margin=30, color="#ffffff63"),
  248.                 axisline_opts=opts.AxisLineOpts(is_show=False),
  249.                 axistick_opts=opts.AxisTickOpts(
  250.                     is_show=True,
  251.                     length=25,
  252.                     linestyle_opts=opts.LineStyleOpts(color="#ffffff1f"),
  253.                 ),
  254.                 splitline_opts=opts.SplitLineOpts(
  255.                     is_show=True, linestyle_opts=opts.LineStyleOpts(color="#ffffff1f")
  256.                 ),
  257.             ),
  258.             yaxis_opts=opts.AxisOpts(
  259.                 type_="value",
  260.                 position="right",
  261.                 axislabel_opts=opts.LabelOpts(margin=20, color="#ffffff63"),
  262.                 axisline_opts=opts.AxisLineOpts(
  263.                     linestyle_opts=opts.LineStyleOpts(width=2, color="#fff")
  264.                 ),
  265.                 axistick_opts=opts.AxisTickOpts(
  266.                     is_show=True,
  267.                     length=15,
  268.                     linestyle_opts=opts.LineStyleOpts(color="#ffffff1f"),
  269.                 ),
  270.                 splitline_opts=opts.SplitLineOpts(
  271.                     is_show=True, linestyle_opts=opts.LineStyleOpts(color="#ffffff1f")
  272.                 ),
  273.             ),
  274.             legend_opts=opts.LegendOpts(is_show=False),
  275.         )
  276.     )
  277.     return c
  278.  
  279.  
  280. Page().add(*[fn() for fn, _ in C.charts]).render()

Parallel（平行坐标系）

  1. #v0.5
  2. from pyecharts import Parallel
  3.  
  4. c_schema = [
  5.     {"dim": 0, "name": "data"},
  6.     {"dim": 1, "name": "AQI"},
  7.     {"dim": 2, "name": "PM2.5"},
  8.     {"dim": 3, "name": "PM10"},
  9.     {"dim": 4, "name": "CO"},
  10.     {"dim": 5, "name": "NO2"},
  11.     {"dim": 6, "name": "CO2"},
  12.     {"dim": 7, "name": "等级",
  13.     "type": "category", "data": ['优', '良', '轻度污染', '中度污染', '重度污染', '严重污染']}
  14. ]
  15. data = [
  16.     [1, 91, 45, 125, 0.82, 34, 23, "良"],
  17.     [2, 65, 27, 78, 0.86, 45, 29, "良"],
  18.     [3, 83, 60, 84, 1.09, 73, 27, "良"],
  19.     [4, 109, 81, 121, 1.28, 68, 51, "轻度污染"],
  20.     [5, 106, 77, 114, 1.07, 55, 51, "轻度污染"],
  21.     [6, 109, 81, 121, 1.28, 68, 51, "轻度污染"],
  22.     [7, 106, 77, 114, 1.07, 55, 51, "轻度污染"],
  23.     [8, 89, 65, 78, 0.86, 51, 26, "良"],
  24.     [9, 53, 33, 47, 0.64, 50, 17, "良"],
  25.     [10, 80, 55, 80, 1.01, 75, 24, "良"],
  26.     [11, 117, 81, 124, 1.03, 45, 24, "轻度污染"],
  27.     [12, 99, 71, 142, 1.1, 62, 42, "良"],
  28.     [13, 95, 69, 130, 1.28, 74, 50, "良"],
  29.     [14, 116, 87, 131, 1.47, 84, 40, "轻度污染"]
  30. ]
  31. parallel = Parallel("平行坐标系-用户自定义指示器")
  32. parallel.config(c_schema=c_schema)
  33. parallel.add("parallel", data)
  34. parallel.show_config()
  35. parallel.render()

3d折线图

  1. import math
  2.  
  3. from pyecharts import options as opts
  4. from pyecharts.charts import Line3D, Page
  5. from pyecharts.faker import Collector, Faker
  6.  
  7. C = Collector()
  8.  
  9.  
  10. @C.funcs
  11. def line3d_base() -> Line3D:
  12.     data = []
  13.     for t in range(0, 25000):
  14.         _t = t / 1000
  15.         x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
  16.         y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
  17.         z = _t + 2.0 * math.sin(75 * _t)
  18.         data.append([x, y, z])
  19.     c = (
  20.         Line3D()
  21.         .add(
  22.             "",
  23.             data,
  24.             xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="value"),
  25.             yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="value"),
  26.             grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
  27.         )
  28.         .set_global_opts(
  29.             visualmap_opts=opts.VisualMapOpts(
  30.                 max_=30, min_=0, range_color=Faker.visual_color
  31.             ),
  32.             title_opts=opts.TitleOpts(title="Line3D-基本示例"),
  33.         )
  34.     )
  35.     return c
  36.  
  37.  
  38. @C.funcs
  39. def line3d_auto_rotate() -> Line3D:
  40.     data = []
  41.     for t in range(0, 25000):
  42.         _t = t / 1000
  43.         x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
  44.         y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
  45.         z = _t + 2.0 * math.sin(75 * _t)
  46.         data.append([x, y, z])
  47.     c = (
  48.         Line3D()
  49.         .add(
  50.             "",
  51.             data,
  52.             xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="value"),
  53.             yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="value"),
  54.             grid3d_opts=opts.Grid3DOpts(
  55.                 width=100, depth=100, rotate_speed=150, is_rotate=True
  56.             ),
  57.         )
  58.         .set_global_opts(
  59.             visualmap_opts=opts.VisualMapOpts(
  60.                 max_=30, min_=0, range_color=Faker.visual_color
  61.             ),
  62.             title_opts=opts.TitleOpts(title="Line3D-旋转的弹簧"),
  63.         )
  64.     )
  65.     return c
  66.  
  67.  
  68. Page().add(*[fn() for fn, _ in C.charts]).render()

surface3D

  1. #v1
  2.  
  3. import math
  4.  
  5. from pyecharts import options as opts
  6. from pyecharts.charts import Page, Surface3D
  7. from pyecharts.faker import Collector, Faker
  8.  
  9. C = Collector()
  10.  
  11.  
  12. @C.funcs
  13. def surface3d_base() -> Surface3D:
  14.     def surface3d_data():
  15.         for t0 in range(-60, 60, 1):
  16.             y = t0 / 60
  17.             for t1 in range(-60, 60, 1):
  18.                 x = t1 / 60
  19.                 if math.fabs(x) < 0.1 and math.fabs(y) < 0.1:
  20.                     z = "-"
  21.                 else:
  22.                     z = math.sin(x * math.pi) * math.sin(y * math.pi)
  23.                 yield [x, y, z]
  24.  
  25.     c = (
  26.         Surface3D()
  27.         .add(
  28.             "",
  29.             list(surface3d_data()),
  30.             xaxis3d_opts=opts.Axis3DOpts(type_="value"),
  31.             yaxis3d_opts=opts.Axis3DOpts(type_="value"),
  32.             grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
  33.         )
  34.         .set_global_opts(
  35.             title_opts=opts.TitleOpts(title="Surface3D-基本示例"),
  36.             visualmap_opts=opts.VisualMapOpts(
  37.                 max_=3, min_=-3, range_color=Faker.visual_color
  38.             ),
  39.         )
  40.     )
  41.     return c
  42.  
  43.  
  44. @C.funcs
  45. def surface3D_flower() -> Surface3D:
  46.     def surface3d_data():
  47.         for t0 in range(-30, 30, 1):
  48.             y = t0 / 10
  49.             for t1 in range(-30, 30, 1):
  50.                 x = t1 / 10
  51.                 z = math.sin(x * x + y * y) * x / 3.14
  52.                 yield [x, y, z]
  53.  
  54.     c = (
  55.         Surface3D()
  56.         .add(
  57.             "",
  58.             list(surface3d_data()),
  59.             xaxis3d_opts=opts.Axis3DOpts(type_="value"),
  60.             yaxis3d_opts=opts.Axis3DOpts(type_="value"),
  61.             grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
  62.         )
  63.         .set_global_opts(
  64.             title_opts=opts.TitleOpts(title="Surface3D-曲面波图"),
  65.             visualmap_opts=opts.VisualMapOpts(
  66.                 max_=1, min_=-1, range_color=Faker.visual_color
  67.             ),
  68.         )
  69.     )
  70.     return c
  71.  
  72.  
  73. Page().add(*[fn() for fn, _ in C.charts]).render()

河流图

  1. #v1
  2.  
  3. from pyecharts import options as opts
  4. from pyecharts.charts import Page, ThemeRiver
  5. from pyecharts.faker import Collector
  6.  
  7. C = Collector()
  8.  
  9.  
  10. @C.funcs
  11. def themeriver_example() -> ThemeRiver:
  12.     data = [
  13.         ["2015/11/08", 10, "DQ"],
  14.         ["2015/11/09", 15, "DQ"],
  15.         ["2015/11/10", 35, "DQ"],
  16.         ["2015/11/14", 7, "DQ"],
  17.         ["2015/11/15", 2, "DQ"],
  18.         ["2015/11/16", 17, "DQ"],
  19.         ["2015/11/17", 33, "DQ"],
  20.         ["2015/11/18", 40, "DQ"],
  21.         ["2015/11/19", 32, "DQ"],
  22.         ["2015/11/20", 26, "DQ"],
  23.         ["2015/11/08", 35, "TY"],
  24.         ["2015/11/09", 36, "TY"],
  25.         ["2015/11/10", 37, "TY"],
  26.         ["2015/11/11", 22, "TY"],
  27.         ["2015/11/12", 24, "TY"],
  28.         ["2015/11/13", 26, "TY"],
  29.         ["2015/11/14", 34, "TY"],
  30.         ["2015/11/15", 21, "TY"],
  31.         ["2015/11/16", 18, "TY"],
  32.         ["2015/11/17", 45, "TY"],
  33.         ["2015/11/18", 32, "TY"],
  34.         ["2015/11/19", 35, "TY"],
  35.         ["2015/11/20", 30, "TY"],
  36.         ["2015/11/08", 21, "SS"],
  37.         ["2015/11/09", 25, "SS"],
  38.         ["2015/11/10", 27, "SS"],
  39.         ["2015/11/11", 23, "SS"],
  40.         ["2015/11/12", 24, "SS"],
  41.         ["2015/11/13", 21, "SS"],
  42.         ["2015/11/14", 35, "SS"],
  43.         ["2015/11/15", 39, "SS"],
  44.         ["2015/11/16", 40, "SS"],
  45.         ["2015/11/17", 36, "SS"],
  46.         ["2015/11/18", 33, "SS"],
  47.         ["2015/11/19", 43, "SS"],
  48.         ["2015/11/20", 40, "SS"],
  49.         ["2015/11/14", 7, "QG"],
  50.         ["2015/11/15", 2, "QG"],
  51.         ["2015/11/16", 17, "QG"],
  52.         ["2015/11/17", 33, "QG"],
  53.         ["2015/11/18", 40, "QG"],
  54.         ["2015/11/19", 32, "QG"],
  55.         ["2015/11/20", 26, "QG"],
  56.         ["2015/11/21", 35, "QG"],
  57.         ["2015/11/22", 40, "QG"],
  58.         ["2015/11/23", 32, "QG"],
  59.         ["2015/11/24", 26, "QG"],
  60.         ["2015/11/25", 22, "QG"],
  61.         ["2015/11/08", 10, "SY"],
  62.         ["2015/11/09", 15, "SY"],
  63.         ["2015/11/10", 35, "SY"],
  64.         ["2015/11/11", 38, "SY"],
  65.         ["2015/11/12", 22, "SY"],
  66.         ["2015/11/13", 16, "SY"],
  67.         ["2015/11/14", 7, "SY"],
  68.         ["2015/11/15", 2, "SY"],
  69.         ["2015/11/16", 17, "SY"],
  70.         ["2015/11/17", 33, "SY"],
  71.         ["2015/11/18", 40, "SY"],
  72.         ["2015/11/19", 32, "SY"],
  73.         ["2015/11/20", 26, "SY"],
  74.         ["2015/11/21", 35, "SY"],
  75.         ["2015/11/22", 4, "SY"],
  76.         ["2015/11/23", 32, "SY"],
  77.         ["2015/11/24", 26, "SY"],
  78.         ["2015/11/25", 22, "SY"],
  79.         ["2015/11/08", 10, "DD"],
  80.         ["2015/11/09", 15, "DD"],
  81.         ["2015/11/10", 35, "DD"],
  82.         ["2015/11/11", 38, "DD"],
  83.         ["2015/11/12", 22, "DD"],
  84.         ["2015/11/13", 16, "DD"],
  85.         ["2015/11/14", 7, "DD"],
  86.         ["2015/11/15", 2, "DD"],
  87.         ["2015/11/16", 17, "DD"],
  88.         ["2015/11/17", 33, "DD"],
  89.         ["2015/11/18", 4, "DD"],
  90.         ["2015/11/19", 32, "DD"],
  91.         ["2015/11/20", 26, "DD"],
  92.     ]
  93.     c = (
  94.         ThemeRiver()
  95.         .add(
  96.             ["DQ", "TY", "SS", "QG", "SY", "DD"],
  97.             data,
  98.             singleaxis_opts=opts.SingleAxisOpts(type_="time", pos_bottom="10%"),
  99.         )
  100.         .set_global_opts(title_opts=opts.TitleOpts(title="ThemeRiver-基本示例"))
  101.     )
  102.     return c
  103.  
  104.  
  105. Page().add(*[fn() for fn, _ in C.charts]).render()

树形图

  1. #v1
  2.  
  3. import json
  4. import os
  5.  
  6. from pyecharts import options as opts
  7. from pyecharts.charts import Page, Tree
  8. from pyecharts.faker import Collector
  9.  
  10. C = Collector()
  11.  
  12.  
  13. @C.funcs
  14. def tree_base() -> Tree:
  15.     data = [
  16.         {
  17.             "children": [
  18.                 {"name": "B"},
  19.                 {
  20.                     "children": [
  21.                         {"children": [{"name": "I"}], "name": "E"},
  22.                         {"name": "F"},
  23.                     ],
  24.                     "name": "C",
  25.                 },
  26.                 {
  27.                     "children": [
  28.                         {"children": [{"name": "J"}, {"name": "K"}], "name": "G"},
  29.                         {"name": "H"},
  30.                     ],
  31.                     "name": "D",
  32.                 },
  33.             ],
  34.             "name": "A",
  35.         }
  36.     ]
  37.     c = (
  38.         Tree()
  39.         .add("", data)
  40.         .set_global_opts(title_opts=opts.TitleOpts(title="Tree-基本示例"))
  41.     )
  42.     return c
  43.  
  44.  
  45. @C.funcs
  46. def tree_lr() -> Tree:
  47.     with open(os.path.join("fixtures", "flare.json"), "r", encoding="utf-8") as f:
  48.         j = json.load(f)
  49.     c = (
  50.         Tree()
  51.         .add("", [j], collapse_interval=2)
  52.         .set_global_opts(title_opts=opts.TitleOpts(title="Tree-左右方向"))
  53.     )
  54.     return c
  55.  
  56.  
  57. @C.funcs
  58. def tree_rl() -> Tree:
  59.     with open(os.path.join("fixtures", "flare.json"), "r", encoding="utf-8") as f:
  60.         j = json.load(f)
  61.     c = (
  62.         Tree()
  63.         .add("", [j], collapse_interval=2, orient="RL")
  64.         .set_global_opts(title_opts=opts.TitleOpts(title="Tree-右左方向"))
  65.     )
  66.     return c
  67.  
  68.  
  69. @C.funcs
  70. def tree_tb() -> Tree:
  71.     with open(os.path.join("fixtures", "flare.json"), "r", encoding="utf-8") as f:
  72.         j = json.load(f)
  73.     c = (
  74.         Tree()
  75.         .add(
  76.             "",
  77.             [j],
  78.             collapse_interval=2,
  79.             orient="TB",
  80.             label_opts=opts.LabelOpts(
  81.                 position="top",
  82.                 horizontal_align="right",
  83.                 vertical_align="middle",
  84.                 rotate=-90,
  85.             ),
  86.         )
  87.         .set_global_opts(title_opts=opts.TitleOpts(title="Tree-上下方向"))
  88.     )
  89.     return c
  90.  
  91.  
  92. @C.funcs
  93. def tree_bt() -> Tree:
  94.     with open(os.path.join("fixtures", "flare.json"), "r", encoding="utf-8") as f:
  95.         j = json.load(f)
  96.     c = (
  97.         Tree()
  98.         .add(
  99.             "",
  100.             [j],
  101.             collapse_interval=2,
  102.             orient="BT",
  103.             label_opts=opts.LabelOpts(
  104.                 position="top",
  105.                 horizontal_align="right",
  106.                 vertical_align="middle",
  107.                 rotate=-90,
  108.             ),
  109.         )
  110.         .set_global_opts(title_opts=opts.TitleOpts(title="Tree-下上方向"))
  111.     )
  112.     return c
  113.  
  114.  
  115. @C.funcs
  116. def tree_layout() -> Tree:
  117.     with open(os.path.join("fixtures", "flare.json"), "r", encoding="utf-8") as f:
  118.         j = json.load(f)
  119.     c = (
  120.         Tree()
  121.         .add("", [j], collapse_interval=2, layout="radial")
  122.         .set_global_opts(title_opts=opts.TitleOpts(title="Tree-Layout"))
  123.     )
  124.     return c
  125.  
  126.  
  127. Page().add(*[fn() for fn, _ in C.charts]).render()

TreeMap

  1. #v1
  2.  
  3. import json
  4. import os
  5.  
  6. from pyecharts import options as opts
  7. from pyecharts.charts import Page, TreeMap
  8. from pyecharts.faker import Collector
  9.  
  10. C = Collector()
  11.  
  12.  
  13. @C.funcs
  14. def treemap_base() -> TreeMap:
  15.     data = [
  16.         {"value": 40, "name": "我是A"},
  17.         {
  18.             "value": 180,
  19.             "name": "我是B",
  20.             "children": [
  21.                 {
  22.                     "value": 76,
  23.                     "name": "我是B.children",
  24.                     "children": [
  25.                         {"value": 12, "name": "我是B.children.a"},
  26.                         {"value": 28, "name": "我是B.children.b"},
  27.                         {"value": 20, "name": "我是B.children.c"},
  28.                         {"value": 16, "name": "我是B.children.d"},
  29.                     ],
  30.                 }
  31.             ],
  32.         },
  33.     ]
  34.  
  35.     c = (
  36.         TreeMap()
  37.         .add("演示数据", data)
  38.         .set_global_opts(title_opts=opts.TitleOpts(title="TreeMap-基本示例"))
  39.     )
  40.     return c
  41.  
  42.  
  43. @C.funcs
  44. def treemap_official():
  45.     with open(os.path.join("fixtures", "treemap.json"), "r", encoding="utf-8") as f:
  46.         data = json.load(f)
  47.     c = (
  48.         TreeMap()
  49.         .add("演示数据", data)
  50.         .set_global_opts(title_opts=opts.TitleOpts(title="TreeMap-官方示例"))
  51.     )
  52.     return c
  53.  
  54.  
  55. Page().add(*[fn() for fn, _ in C.charts]).render()

条形图

  1. #v0.5
  2. from pyecharts import Bar
  3.  
  4. bar = Bar('设置堆叠效果')
  5.  
  6. attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
  7. v1 = [5, 20, 36, 10, 75, 90]
  8. v2 = [10, 25, 8, 60, 20, 80]
  9.  
  10. bar.add('商家A', attr, v1, is_stack=True)
  11. bar.add("商家B", attr, v2, is_stack=True)
  12. bar.render()

  1. #v0.5
  2. from pyecharts import Bar
  3. #configure(output_image=True)
  4. bar = Bar('各个城市的人口','虚构的',background_color = 'white',title_text_size = 25,subtitle_text_size = 15)
  5. attr = ['惠州','东莞','广州','深圳','佛山','江门','珠海']
  6. v1 = [23,45,68,58,32,28,36]
  7. v2 = [12,22,34,29,16,14,18]
  8. bar.add('举例数字1',attr,v1,is_label_show = True,mark_point = ['min','max'],
  9.          mark_point_symbol = 'diamond',xaxis_rotate = 30,xaxis_label_textsize = 15,yaxis_label_textsize = 15)
  10. bar.add('举例数字2',attr,v2,is_label_show = True,mark_point = ['min','max'],
  11.          mark_point_symbol = 'triangle',xaxis_rotate = 30,xaxis_label_textsize = 15,yaxis_label_textsize = 15)
  12. bar.render()

  1. #v1
  2.  
  3. from pyecharts.commons.utils import JsCode # 导入js代码库，可以调用一些js方法
  4. from pyecharts.faker import Faker
  5. from pyecharts import options as opts
  6. from pyecharts.charts import Bar, Grid # 导入网格库
  7. from pyecharts.globals import ThemeType # 导入主题库
  8.  
  9.  
  10. # 例2 渐变圆柱
  11. bar2=(
  12.         Bar()
  13.         .add_xaxis(Faker.choose())
  14.         .add_yaxis("数据1",Faker.values(),category_gap="60%")
  15. # category_gap是同一系列的柱间距离，默认为类目间距的 20%，可设固定值
  16.         .set_series_opts(itemstyle_opts={# set_series_opts设置系列配置
  17.             "normal":{ # normal代表一般、正常情况
  18. # LinearGradient 设置线性渐变，offset为0是柱子0%处颜色，为1是100%处颜色
  19.                 "color": JsCode("""new echarts.graphic.LinearGradient(0, 0, 0, 1, [{
  20.                     offset: 0, 
  21.                     color: 'rgba(0, 233, 245, 1)'
  22.                 }, {
  23.                     offset: 1, 
  24.                     color: 'rgba(0, 45, 187, 1)'
  25.                 }], false)"""),
  26.                 "barBorderRadius": [30, 30, 30, 30],# 设置柱子4个角为30变成圆柱
  27.                 "shadowColor": 'red',# 阴影颜色
  28.             }})
  29.         .set_global_opts(title_opts=opts.TitleOpts(title="Bar-渐变圆柱"))
  30.     )
  31. bar2.render()

注意是v1版本

  1. #v1
  2.  
  3. from pyecharts.commons.utils import JsCode # 导入js代码库，可以调用一些js方法
  4. from pyecharts.faker import Faker
  5. from pyecharts import options as opts
  6. from pyecharts.charts import Bar, Grid # 导入网格库
  7. from pyecharts.globals import ThemeType # 导入主题库
  8.  
  9.  
  10. # 例4 背景图基本示例
  11. bar4=(
  12.         Bar(
  13.             init_opts=opts.InitOpts(
  14.                 bg_color={
  15.                     "type":"pattern",
  16.                     "image":JsCode("img"),
  17.                     "repeat":"no-repeat",
  18.                 }# bg_color是设置背景颜色，这里image是设置图片背景，repeat设置no-repeat不重复
  19.             )
  20.         )
  21.         .add_xaxis(Faker.choose())
  22.         .add_yaxis("数据1",Faker.values())
  23.         .add_yaxis("数据2",Faker.values())
  24.         .set_global_opts(
  25.             title_opts=opts.TitleOpts(
  26.                 title="Bar-背景图基本示例",
  27.                 subtitle="副标题",
  28.                 title_textstyle_opts=opts.TextStyleOpts(color='red'),
  29.             )
  30.         )
  31.     )
  32. # 这里添加图片src连接，也可以换其他图片的网址
  33. bar4.add_js_funcs(
  34.         '''  
  35.         var img=new Image();img.src='https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1571897969384&di=e417611ecd20f69eee6c549ef44e357e&imgtype=0&src=http%3A%2F%2Fimg8.zol.com.cn%2Fbbs%2Fupload%2F18863%2F18862812.JPG';
  36.         '''
  37.     )
  38. bar4.render()

3D柱状图

blog.csdn.net/HHG20171226/article/details/103113923

  1. #v0.5
  2. from pyecharts import Bar3D
  3.  
  4. bar3d = Bar3D("3D 柱状图示例", width=1200, height=600)
  5. x_axis = [
  6.     "12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a", "11a",
  7.     "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p", "10p", "11p"
  8.     ]
  9. y_axis = [
  10.     "Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"
  11.     ]
  12. data = [
  13.     [0, 0, 5], [0, 1, 1], [0, 2, 0], [0, 3, 0], [0, 4, 0], [0, 5, 0],
  14.     [0, 6, 0], [0, 7, 0], [0, 8, 0], [0, 9, 0], [0, 10, 0], [0, 11, 2],
  15.     [0, 12, 4], [0, 13, 1], [0, 14, 1], [0, 15, 3], [0, 16, 4], [0, 17, 6],
  16.     [0, 18, 4], [0, 19, 4], [0, 20, 3], [0, 21, 3], [0, 22, 2], [0, 23, 5],
  17.     [1, 0, 7], [1, 1, 0], [1, 2, 0], [1, 3, 0], [1, 4, 0], [1, 5, 0],
  18.     [1, 6, 0], [1, 7, 0], [1, 8, 0], [1, 9, 0], [1, 10, 5], [1, 11, 2],
  19.     [1, 12, 2], [1, 13, 6], [1, 14, 9], [1, 15, 11], [1, 16, 6], [1, 17, 7],
  20.     [1, 18, 8], [1, 19, 12], [1, 20, 5], [1, 21, 5], [1, 22, 7], [1, 23, 2],
  21.     [2, 0, 1], [2, 1, 1], [2, 2, 0], [2, 3, 0], [2, 4, 0], [2, 5, 0],
  22.     [2, 6, 0], [2, 7, 0], [2, 8, 0], [2, 9, 0], [2, 10, 3], [2, 11, 2],
  23.     [2, 12, 1], [2, 13, 9], [2, 14, 8], [2, 15, 10], [2, 16, 6], [2, 17, 5],
  24.     [2, 18, 5], [2, 19, 5], [2, 20, 7], [2, 21, 4], [2, 22, 2], [2, 23, 4],
  25.     [3, 0, 7], [3, 1, 3], [3, 2, 0], [3, 3, 0], [3, 4, 0], [3, 5, 0],
  26.     [3, 6, 0], [3, 7, 0], [3, 8, 1], [3, 9, 0], [3, 10, 5], [3, 11, 4],
  27.     [3, 12, 7], [3, 13, 14], [3, 14, 13], [3, 15, 12], [3, 16, 9], [3, 17, 5],
  28.     [3, 18, 5], [3, 19, 10], [3, 20, 6], [3, 21, 4], [3, 22, 4], [3, 23, 1],
  29.     [4, 0, 1], [4, 1, 3], [4, 2, 0], [4, 3, 0], [4, 4, 0], [4, 5, 1],
  30.     [4, 6, 0], [4, 7, 0], [4, 8, 0], [4, 9, 2], [4, 10, 4], [4, 11, 4],
  31.     [4, 12, 2], [4, 13, 4], [4, 14, 4], [4, 15, 14], [4, 16, 12], [4, 17, 1],
  32.     [4, 18, 8], [4, 19, 5], [4, 20, 3], [4, 21, 7], [4, 22, 3], [4, 23, 0],
  33.     [5, 0, 2], [5, 1, 1], [5, 2, 0], [5, 3, 3], [5, 4, 0], [5, 5, 0],
  34.     [5, 6, 0], [5, 7, 0], [5, 8, 2], [5, 9, 0], [5, 10, 4], [5, 11, 1],
  35.     [5, 12, 5], [5, 13, 10], [5, 14, 5], [5, 15, 7], [5, 16, 11], [5, 17, 6],
  36.     [5, 18, 0], [5, 19, 5], [5, 20, 3], [5, 21, 4], [5, 22, 2], [5, 23, 0],
  37.     [6, 0, 1], [6, 1, 0], [6, 2, 0], [6, 3, 0], [6, 4, 0], [6, 5, 0],
  38.     [6, 6, 0], [6, 7, 0], [6, 8, 0], [6, 9, 0], [6, 10, 1], [6, 11, 0],
  39.     [6, 12, 2], [6, 13, 1], [6, 14, 3], [6, 15, 4], [6, 16, 0], [6, 17, 0],
  40.     [6, 18, 0], [6, 19, 0], [6, 20, 1], [6, 21, 2], [6, 22, 2], [6, 23, 6]
  41.     ]
  42. range_color = ['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
  43.                '#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026']
  44. bar3d.add(
  45.     "",
  46.     x_axis,
  47.     y_axis,
  48.     [[d[1], d[0], d[2]] for d in data],
  49.     is_visualmap=True,
  50.     visual_range=[0, 20],
  51.     visual_range_color=range_color,
  52.     grid3d_width=200,
  53.     grid3d_depth=80,
  54. )
  55. bar3d.render()

拖动鼠标还可以转动坐标轴

桑基图

  1. #v1
  2. import json
  3. import os
  4.  
  5. from pyecharts import options as opts
  6. from pyecharts.charts import Page, Sankey
  7. from pyecharts.faker import Collector
  8.  
  9. C = Collector()
  10.  
  11.  
  12. @C.funcs
  13. def sankey_base() -> Sankey:
  14.     nodes = [
  15.         {"name": "category1"},
  16.         {"name": "category2"},
  17.         {"name": "category3"},
  18.         {"name": "category4"},
  19.         {"name": "category5"},
  20.         {"name": "category6"},
  21.     ]
  22.  
  23.     links = [
  24.         {"source": "category1", "target": "category2", "value": 10},
  25.         {"source": "category2", "target": "category3", "value": 15},
  26.         {"source": "category3", "target": "category4", "value": 20},
  27.         {"source": "category5", "target": "category6", "value": 25},
  28.     ]
  29.     c = (
  30.         Sankey()
  31.         .add(
  32.             "sankey",
  33.             nodes,
  34.             links,
  35.             linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
  36.             label_opts=opts.LabelOpts(position="right"),
  37.         )
  38.         .set_global_opts(title_opts=opts.TitleOpts(title="Sankey-基本示例"))
  39.     )
  40.     return c
  41.  
  42.  
  43. @C.funcs
  44. def sankey_offical() -> Sankey:
  45.     with open(os.path.join("fixtures", "energy.json"), "r", encoding="utf-8") as f:
  46.         j = json.load(f)
  47.     c = (
  48.         Sankey()
  49.         .add(
  50.             "sankey",
  51.             nodes=j["nodes"],
  52.             links=j["links"],
  53.             linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
  54.             label_opts=opts.LabelOpts(position="right"),
  55.         )
  56.         .set_global_opts(title_opts=opts.TitleOpts(title="Sankey-官方示例"))
  57.     )
  58.     return c
  59.  
  60.  
  61. @C.funcs
  62. def sankey_vertical() -> Sankey:
  63.     colors = [
  64.         "#67001f",
  65.         "#b2182b",
  66.         "#d6604d",
  67.         "#f4a582",
  68.         "#fddbc7",
  69.         "#d1e5f0",
  70.         "#92c5de",
  71.         "#4393c3",
  72.         "#2166ac",
  73.         "#053061",
  74.     ]
  75.     nodes = [
  76.         {"name": "a"},
  77.         {"name": "b"},
  78.         {"name": "a1"},
  79.         {"name": "b1"},
  80.         {"name": "c"},
  81.         {"name": "e"},
  82.     ]
  83.     links = [
  84.         {"source": "a", "target": "a1", "value": 5},
  85.         {"source": "e", "target": "b", "value": 3},
  86.         {"source": "a", "target": "b1", "value": 3},
  87.         {"source": "b1", "target": "a1", "value": 1},
  88.         {"source": "b1", "target": "c", "value": 2},
  89.         {"source": "b", "target": "c", "value": 1},
  90.     ]
  91.     c = (
  92.         Sankey()
  93.         .set_colors(colors)
  94.         .add(
  95.             "sankey",
  96.             nodes=nodes,
  97.             links=links,
  98.             pos_bottom="10%",
  99.             focus_node_adjacency="allEdges",
  100.             orient="vertical",
  101.             linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
  102.             label_opts=opts.LabelOpts(position="top"),
  103.         )
  104.         .set_global_opts(
  105.             title_opts=opts.TitleOpts(title="Sankey-Vertical"),
  106.             tooltip_opts=opts.TooltipOpts(trigger="item", trigger_on="mousemove"),
  107.         )
  108.     )
  109.     return c
  110.  
  111.  
  112. @C.funcs
  113. def sankey_with_level_setting() -> Sankey:
  114.     with open(os.path.join("fixtures", "product.json"), "r", encoding="utf-8") as f:
  115.         j = json.load(f)
  116.     c = (
  117.         Sankey()
  118.         .add(
  119.             "sankey",
  120.             nodes=j["nodes"],
  121.             links=j["links"],
  122.             pos_top="10%",
  123.             focus_node_adjacency=True,
  124.             levels=[
  125.                 opts.SankeyLevelsOpts(
  126.                     depth=0,
  127.                     itemstyle_opts=opts.ItemStyleOpts(color="#fbb4ae"),
  128.                     linestyle_opts=opts.LineStyleOpts(color="source", opacity=0.6),
  129.                 ),
  130.                 opts.SankeyLevelsOpts(
  131.                     depth=1,
  132.                     itemstyle_opts=opts.ItemStyleOpts(color="#b3cde3"),
  133.                     linestyle_opts=opts.LineStyleOpts(color="source", opacity=0.6),
  134.                 ),
  135.                 opts.SankeyLevelsOpts(
  136.                     depth=2,
  137.                     itemstyle_opts=opts.ItemStyleOpts(color="#ccebc5"),
  138.                     linestyle_opts=opts.LineStyleOpts(color="source", opacity=0.6),
  139.                 ),
  140.                 opts.SankeyLevelsOpts(
  141.                     depth=3,
  142.                     itemstyle_opts=opts.ItemStyleOpts(color="#decbe4"),
  143.                     linestyle_opts=opts.LineStyleOpts(color="source", opacity=0.6),
  144.                 ),
  145.             ],
  146.             linestyle_opt=opts.LineStyleOpts(curve=0.5),
  147.         )
  148.         .set_global_opts(
  149.             title_opts=opts.TitleOpts(title="Sankey-Level Settings"),
  150.             tooltip_opts=opts.TooltipOpts(trigger="item", trigger_on="mousemove"),
  151.         )
  152.     )
  153.     return c
  154.  
  155.  
  156. Page().add(*[fn() for fn, _ in C.charts]).render()

3D散点图

  1. #v1
  2.  
  3. import random
  4.  
  5. from pyecharts import options as opts
  6. from pyecharts.charts import Page, Scatter3D
  7. from pyecharts.faker import Collector, Faker
  8.  
  9. C = Collector()
  10.  
  11.  
  12. @C.funcs
  13. def scatter3d_base() -> Scatter3D:
  14.     data = [
  15.         [random.randint(0, 100), random.randint(0, 100), random.randint(0, 100)]
  16.         for _ in range(80)
  17.     ]
  18.     c = (
  19.         Scatter3D()
  20.         .add("", data)
  21.         .set_global_opts(
  22.             title_opts=opts.TitleOpts("Scatter3D-基本示例"),
  23.             visualmap_opts=opts.VisualMapOpts(range_color=Faker.visual_color),
  24.         )
  25.     )
  26.     return c
  27.  
  28.  
  29. @C.funcs
  30. def scatter3d_muti_visualmap_channel():
  31.     data = [
  32.         [random.randint(0, 100), random.randint(0, 100), random.randint(0, 100)]
  33.         for _ in range(80)
  34.     ]
  35.     c = (
  36.         Scatter3D()
  37.         .add("", data)
  38.         .set_global_opts(
  39.             title_opts=opts.TitleOpts("Scatter3D-多视觉映射通道"),
  40.             visualmap_opts=[
  41.                 opts.VisualMapOpts(range_color=Faker.visual_color),
  42.                 opts.VisualMapOpts(type_="size", range_size=[10, 50], pos_top="20%"),
  43.             ],
  44.         )
  45.     )
  46.     return c
  47.  
  48.  
  49. Page().add(*[fn() for fn, _ in C.charts]).render()

旭日图

  1. #v1
  2.  
  3. import json
  4. import os
  5.  
  6. from pyecharts import options as opts
  7. from pyecharts.charts import Page, Sunburst
  8. from pyecharts.faker import Collector
  9.  
  10. C = Collector()
  11.  
  12.  
  13. @C.funcs
  14. def sunburst_base() -> Sunburst:
  15.     data = [
  16.         opts.SunburstItem(
  17.             name="Grandpa",
  18.             children=[
  19.                 opts.SunburstItem(
  20.                     name="Uncle Leo",
  21.                     value=15,
  22.                     children=[
  23.                         opts.SunburstItem(name="Cousin Jack", value=2),
  24.                         opts.SunburstItem(
  25.                             name="Cousin Mary",
  26.                             value=5,
  27.                             children=[opts.SunburstItem(name="Jackson", value=2)],
  28.                         ),
  29.                         opts.SunburstItem(name="Cousin Ben", value=4),
  30.                     ],
  31.                 ),
  32.                 opts.SunburstItem(
  33.                     name="Father",
  34.                     value=10,
  35.                     children=[
  36.                         opts.SunburstItem(name="Me", value=5),
  37.                         opts.SunburstItem(name="Brother Peter", value=1),
  38.                     ],
  39.                 ),
  40.             ],
  41.         ),
  42.         opts.SunburstItem(
  43.             name="Nancy",
  44.             children=[
  45.                 opts.SunburstItem(
  46.                     name="Uncle Nike",
  47.                     children=[
  48.                         opts.SunburstItem(name="Cousin Betty", value=1),
  49.                         opts.SunburstItem(name="Cousin Jenny", value=2),
  50.                     ],
  51.                 )
  52.             ],
  53.         ),
  54.     ]
  55.  
  56.     c = (
  57.         Sunburst(init_opts=opts.InitOpts(width="1000px", height="600px"))
  58.         .add(series_name="", data_pair=data, radius=[0, "90%"])
  59.         .set_global_opts(title_opts=opts.TitleOpts(title="Sunburst-基本示例"))
  60.         .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}"))
  61.     )
  62.     return c
  63.  
  64.  
  65. @C.funcs
  66. def sunburst_official() -> Sunburst:
  67.     with open(os.path.join("fixtures", "drink.json"), "r", encoding="utf-8") as f:
  68.         j = json.load(f)
  69.  
  70.     c = (
  71.         Sunburst(init_opts=opts.InitOpts(width="1000px", height="600px"))
  72.         .add(
  73.             "",
  74.             data_pair=j,
  75.             highlight_policy="ancestor",
  76.             radius=[0, "95%"],
  77.             sort_="null",
  78.             levels=[
  79.                 {},
  80.                 {
  81.                     "r0": "15%",
  82.                     "r": "35%",
  83.                     "itemStyle": {"borderWidth": 2},
  84.                     "label": {"rotate": "tangential"},
  85.                 },
  86.                 {"r0": "35%", "r": "70%", "label": {"align": "right"}},
  87.                 {
  88.                     "r0": "70%",
  89.                     "r": "72%",
  90.                     "label": {"position": "outside", "padding": 3, "silent": False},
  91.                     "itemStyle": {"borderWidth": 3},
  92.                 },
  93.             ],
  94.         )
  95.         .set_global_opts(title_opts=opts.TitleOpts(title="Sunburst-官方示例"))
  96.         .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}"))
  97.     )
  98.     return c
  99.  
  100.  
  101. Page().add(*[fn() for fn, _ in C.charts]).render()

Geo（地理坐标系）

  1. #v0.5
  2. from pyecharts import Geo
  3.  
  4. data = [
  5.     ("海门", 90),("鄂尔多斯", 150),("招远", 12),("舟山", 122),("齐齐哈尔", 14),("盐城", 15),
  6.     ("赤峰", 16),("青岛", 18),("乳山", 180),("金昌", 19),("泉州", 21),("莱西", 21),
  7.     ("日照", 21),("胶南", 220),("南通", 23),("拉萨", 100),("云浮", 24),("梅州", 25)]
  8. geo = Geo("全国主要城市空气质量", "data from pm2.5", title_color="#fff", title_pos="center",
  9. width=1200, height=600, background_color='#404a59')
  10. attr, value = geo.cast(data)
  11. geo.add("", attr, value, visual_range=[0, 200], visual_text_color="#fff", symbol_size=15, is_visualmap=True)
  12. geo.show_config()
  13. geo.render()

左下角可以上下拖动

  1. #v0.5
  2. from pyecharts import Geo
  3.  
  4. data = [("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14), ("盐城", 15)]
  5. geo = Geo("全国主要城市空气质量", "data from pm2.5", title_color="#fff", title_pos="center",
  6.           width=1200, height=600, background_color='#404a59')
  7. attr, value = geo.cast(data)
  8. geo.add("", attr, value, type="effectScatter", is_random=True, effect_scale=5)
  9. geo.show_config()
  10. geo.render()

  1. #v1
  2. from pyecharts import options as opts
  3. from pyecharts.charts import Geo, Page
  4. from pyecharts.faker import Collector, Faker
  5. from pyecharts.globals import ChartType, SymbolType
  6.  
  7. C = Collector()
  8.  
  9.  
  10. @C.funcs
  11. def geo_base() -> Geo:
  12.     c = (
  13.         Geo()
  14.         .add_schema(maptype="china")
  15.         .add("geo", [list(z) for z in zip(Faker.provinces, Faker.values())])
  16.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  17.         .set_global_opts(
  18.             visualmap_opts=opts.VisualMapOpts(),
  19.             title_opts=opts.TitleOpts(title="Geo-基本示例"),
  20.         )
  21.     )
  22.     return c
  23.  
  24.  
  25. @C.funcs
  26. def geo_visualmap_piecewise() -> Geo:
  27.     c = (
  28.         Geo()
  29.         .add_schema(maptype="china")
  30.         .add("geo", [list(z) for z in zip(Faker.provinces, Faker.values())])
  31.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  32.         .set_global_opts(
  33.             visualmap_opts=opts.VisualMapOpts(is_piecewise=True),
  34.             title_opts=opts.TitleOpts(title="Geo-VisualMap（分段型）"),
  35.         )
  36.     )
  37.     return c
  38.  
  39.  
  40. @C.funcs
  41. def geo_effectscatter() -> Geo:
  42.     c = (
  43.         Geo()
  44.         .add_schema(maptype="china")
  45.         .add(
  46.             "geo",
  47.             [list(z) for z in zip(Faker.provinces, Faker.values())],
  48.             type_=ChartType.EFFECT_SCATTER,
  49.         )
  50.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  51.         .set_global_opts(title_opts=opts.TitleOpts(title="Geo-EffectScatter"))
  52.     )
  53.     return c
  54.  
  55.  
  56. @C.funcs
  57. def geo_heatmap() -> Geo:
  58.     c = (
  59.         Geo()
  60.         .add_schema(maptype="china")
  61.         .add(
  62.             "geo",
  63.             [list(z) for z in zip(Faker.provinces, Faker.values())],
  64.             type_=ChartType.HEATMAP,
  65.         )
  66.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  67.         .set_global_opts(
  68.             visualmap_opts=opts.VisualMapOpts(),
  69.             title_opts=opts.TitleOpts(title="Geo-HeatMap"),
  70.         )
  71.     )
  72.     return c
  73.  
  74.  
  75. @C.funcs
  76. def geo_guangdong() -> Geo:
  77.     c = (
  78.         Geo()
  79.         .add_schema(maptype="广东")
  80.         .add(
  81.             "geo",
  82.             [list(z) for z in zip(Faker.guangdong_city, Faker.values())],
  83.             type_=ChartType.HEATMAP,
  84.         )
  85.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  86.         .set_global_opts(
  87.             visualmap_opts=opts.VisualMapOpts(),
  88.             title_opts=opts.TitleOpts(title="Geo-广东地图"),
  89.         )
  90.     )
  91.     return c
  92.  
  93.  
  94. @C.funcs
  95. def geo_lines() -> Geo:
  96.     c = (
  97.         Geo()
  98.         .add_schema(maptype="china")
  99.         .add(
  100.             "",
  101.             [("广州", 55), ("北京", 66), ("杭州", 77), ("重庆", 88)],
  102.             type_=ChartType.EFFECT_SCATTER,
  103.             color="white",
  104.         )
  105.         .add(
  106.             "geo",
  107.             [("广州", "上海"), ("广州", "北京"), ("广州", "杭州"), ("广州", "重庆")],
  108.             type_=ChartType.LINES,
  109.             effect_opts=opts.EffectOpts(
  110.                 symbol=SymbolType.ARROW, symbol_size=6, color="blue"
  111.             ),
  112.             linestyle_opts=opts.LineStyleOpts(curve=0.2),
  113.         )
  114.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  115.         .set_global_opts(title_opts=opts.TitleOpts(title="Geo-Lines"))
  116.     )
  117.     return c
  118.  
  119.  
  120. @C.funcs
  121. def geo_lines_background() -> Geo:
  122.     c = (
  123.         Geo()
  124.         .add_schema(
  125.             maptype="china",
  126.             itemstyle_opts=opts.ItemStyleOpts(color="#323c48", border_color="#111"),
  127.         )
  128.         .add(
  129.             "",
  130.             [("广州", 55), ("北京", 66), ("杭州", 77), ("重庆", 88)],
  131.             type_=ChartType.EFFECT_SCATTER,
  132.             color="white",
  133.         )
  134.         .add(
  135.             "geo",
  136.             [("广州", "上海"), ("广州", "北京"), ("广州", "杭州"), ("广州", "重庆")],
  137.             type_=ChartType.LINES,
  138.             effect_opts=opts.EffectOpts(
  139.                 symbol=SymbolType.ARROW, symbol_size=6, color="blue"
  140.             ),
  141.             linestyle_opts=opts.LineStyleOpts(curve=0.2),
  142.         )
  143.         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
  144.         .set_global_opts(title_opts=opts.TitleOpts(title="Geo-Lines-background"))
  145.     )
  146.     return c
  147.  
  148.  
  149. Page().add(*[fn() for fn, _ in C.charts]).render()

  1. #v1
  2.  
  3. import json
  4. import os
  5.  
  6. from pyecharts import options as opts
  7. from pyecharts.charts import BMap, Page
  8. from pyecharts.commons.utils import JsCode
  9. from pyecharts.faker import Collector, Faker
  10. from pyecharts.globals import BMapType, ChartType
  11.  
  12. C = Collector()
  13. BAIDU_MAP_AK = os.environ.get("BAIDU_MAP_AK", "FAKE_AK")
  14.  
  15.  
  16. @C.funcs
  17. def bmap_base() -> BMap:
  18.     c = (
  19.         BMap()
  20.         .add_schema(baidu_ak=BAIDU_MAP_AK, center=[120.13066322374, 30.240018034923])
  21.         .add(
  22.             "bmap",
  23.             [list(z) for z in zip(Faker.provinces, Faker.values())],
  24.             label_opts=opts.LabelOpts(formatter="{b}"),
  25.         )
  26.         .set_global_opts(title_opts=opts.TitleOpts(title="BMap-基本示例"))
  27.     )
  28.     return c
  29.  
  30.  
  31. @C.funcs
  32. def bmap_heatmap() -> BMap:
  33.     c = (
  34.         BMap()
  35.         .add_schema(baidu_ak=BAIDU_MAP_AK, center=[120.13066322374, 30.240018034923])
  36.         .add(
  37.             "bmap",
  38.             [list(z) for z in zip(Faker.provinces, Faker.values())],
  39.             type_="heatmap",
  40.             label_opts=opts.LabelOpts(formatter="{b}"),
  41.         )
  42.         .set_global_opts(
  43.             title_opts=opts.TitleOpts(title="BMap-热力图"),
  44.             visualmap_opts=opts.VisualMapOpts(),
  45.         )
  46.     )
  47.     return c
  48.  
  49.  
  50. @C.funcs
  51. def bmap_lines() -> BMap:
  52.     with open(
  53.         os.path.join("fixtures", "hangzhou-tracks.json"), "r", encoding="utf-8"
  54.     ) as f:
  55.         j = json.load(f)
  56.     c = (
  57.         BMap()
  58.         .add_schema(
  59.             baidu_ak=BAIDU_MAP_AK,
  60.             center=[120.13066322374, 30.240018034923],
  61.             zoom=14,
  62.             is_roam=True,
  63.             map_style={
  64.                 "styleJson": [
  65.                     {
  66.                         "featureType": "water",
  67.                         "elementType": "all",
  68.                         "stylers": {"color": "#d1d1d1"},
  69.                     },
  70.                     {
  71.                         "featureType": "land",
  72.                         "elementType": "all",
  73.                         "stylers": {"color": "#f3f3f3"},
  74.                     },
  75.                     {
  76.                         "featureType": "railway",
  77.                         "elementType": "all",
  78.                         "stylers": {"visibility": "off"},
  79.                     },
  80.                     {
  81.                         "featureType": "highway",
  82.                         "elementType": "all",
  83.                         "stylers": {"color": "#fdfdfd"},
  84.                     },
  85.                     {
  86.                         "featureType": "highway",
  87.                         "elementType": "labels",
  88.                         "stylers": {"visibility": "off"},
  89.                     },
  90.                     {
  91.                         "featureType": "arterial",
  92.                         "elementType": "geometry",
  93.                         "stylers": {"color": "#fefefe"},
  94.                     },
  95.                     {
  96.                         "featureType": "arterial",
  97.                         "elementType": "geometry.fill",
  98.                         "stylers": {"color": "#fefefe"},
  99.                     },
  100.                     {
  101.                         "featureType": "poi",
  102.                         "elementType": "all",
  103.                         "stylers": {"visibility": "off"},
  104.                     },
  105.                     {
  106.                         "featureType": "green",
  107.                         "elementType": "all",
  108.                         "stylers": {"visibility": "off"},
  109.                     },
  110.                     {
  111.                         "featureType": "subway",
  112.                         "elementType": "all",
  113.                         "stylers": {"visibility": "off"},
  114.                     },
  115.                     {
  116.                         "featureType": "manmade",
  117.                         "elementType": "all",
  118.                         "stylers": {"color": "#d1d1d1"},
  119.                     },
  120.                     {
  121.                         "featureType": "local",
  122.                         "elementType": "all",
  123.                         "stylers": {"color": "#d1d1d1"},
  124.                     },
  125.                     {
  126.                         "featureType": "arterial",
  127.                         "elementType": "labels",
  128.                         "stylers": {"visibility": "off"},
  129.                     },
  130.                     {
  131.                         "featureType": "boundary",
  132.                         "elementType": "all",
  133.                         "stylers": {"color": "#fefefe"},
  134.                     },
  135.                     {
  136.                         "featureType": "building",
  137.                         "elementType": "all",
  138.                         "stylers": {"color": "#d1d1d1"},
  139.                     },
  140.                     {
  141.                         "featureType": "label",
  142.                         "elementType": "labels.text.fill",
  143.                         "stylers": {"color": "#999999"},
  144.                     },
  145.                 ]
  146.             },
  147.         )
  148.         .add(
  149.             "",
  150.             type_="lines",
  151.             data_pair=j,
  152.             is_polyline=True,
  153.             is_large=True,
  154.             linestyle_opts=opts.LineStyleOpts(color="purple", opacity=0.6, width=1),
  155.         )
  156.         .add_control_panel(
  157.             maptype_control_opts=opts.BMapTypeControlOpts(
  158.                 type_=BMapType.MAPTYPE_CONTROL_DROPDOWN
  159.             ),
  160.             scale_control_opts=opts.BMapScaleControlOpts(),
  161.             overview_map_opts=opts.BMapOverviewMapControlOpts(is_open=True),
  162.         )
  163.         .set_global_opts(title_opts=opts.TitleOpts(title="BMap-杭州热门步行路线"))
  164.     )
  165.     return c
  166.  
  167.  
  168. @C.funcs
  169. def bmap_custom() -> BMap:
  170.     with open(
  171.         os.path.join("fixtures", "bmap-custom-data.json"), "r", encoding="utf-8"
  172.     ) as f:
  173.         j = json.load(f)
  174.     color_list = ["#070093", "#1c3fbf", "#1482e5", "#70b4eb", "#b4e0f3", "#ffffff"]
  175.     c = (
  176.         BMap()
  177.         .add_schema(
  178.             baidu_ak=BAIDU_MAP_AK,
  179.             center=[116.46, 39.92],
  180.             zoom=11.8,
  181.             is_roam=True,
  182.             map_style={
  183.                 "styleJson": [
  184.                     {
  185.                         "featureType": "water",
  186.                         "elementType": "all",
  187.                         "stylers": {"color": "#d1d1d1"},
  188.                     },
  189.                     {
  190.                         "featureType": "land",
  191.                         "elementType": "all",
  192.                         "stylers": {"color": "#f3f3f3"},
  193.                     },
  194.                     {
  195.                         "featureType": "railway",
  196.                         "elementType": "all",
  197.                         "stylers": {"visibility": "off"},
  198.                     },
  199.                     {
  200.                         "featureType": "highway",
  201.                         "elementType": "all",
  202.                         "stylers": {"color": "#999999"},
  203.                     },
  204.                     {
  205.                         "featureType": "highway",
  206.                         "elementType": "labels",
  207.                         "stylers": {"visibility": "off"},
  208.                     },
  209.                     {
  210.                         "featureType": "arterial",
  211.                         "elementType": "geometry",
  212.                         "stylers": {"color": "#fefefe"},
  213.                     },
  214.                     {
  215.                         "featureType": "arterial",
  216.                         "elementType": "geometry.fill",
  217.                         "stylers": {"color": "#fefefe"},
  218.                     },
  219.                     {
  220.                         "featureType": "poi",
  221.                         "elementType": "all",
  222.                         "stylers": {"visibility": "off"},
  223.                     },
  224.                     {
  225.                         "featureType": "green",
  226.                         "elementType": "all",
  227.                         "stylers": {"visibility": "off"},
  228.                     },
  229.                     {
  230.                         "featureType": "subway",
  231.                         "elementType": "all",
  232.                         "stylers": {"visibility": "off"},
  233.                     },
  234.                     {
  235.                         "featureType": "manmade",
  236.                         "elementType": "all",
  237.                         "stylers": {"color": "#d1d1d1"},
  238.                     },
  239.                     {
  240.                         "featureType": "local",
  241.                         "elementType": "all",
  242.                         "stylers": {"color": "#d1d1d1"},
  243.                     },
  244.                     {
  245.                         "featureType": "arterial",
  246.                         "elementType": "labels",
  247.                         "stylers": {"visibility": "off"},
  248.                     },
  249.                     {
  250.                         "featureType": "boundary",
  251.                         "elementType": "all",
  252.                         "stylers": {"color": "#fefefe"},
  253.                     },
  254.                     {
  255.                         "featureType": "building",
  256.                         "elementType": "all",
  257.                         "stylers": {"color": "#d1d1d1"},
  258.                     },
  259.                     {
  260.                         "featureType": "label",
  261.                         "elementType": "labels.text.fill",
  262.                         "stylers": {"color": "rgba(0,0,0,0)"},
  263.                     },
  264.                 ]
  265.             },
  266.         )
  267.         .add_js_funcs(
  268.             """
  269.         var lngExtent = [39.5, 40.6];
  270.         var latExtent = [115.9, 116.8];
  271.         var cellCount = [50, 50];
  272.         var cellSizeCoord = [
  273.             (lngExtent[1] - lngExtent[0]) / cellCount[0],
  274.             (latExtent[1] - latExtent[0]) / cellCount[1]
  275.         ];
  276.         var gapSize = 0;
  278.         function renderItem(params, api) {
  279.             var lngIndex = api.value(0);
  280.             var latIndex = api.value(1);
  281.             var pointLeftTop = getCoord(params, api, lngIndex, latIndex);
  282.             var pointRightBottom = getCoord(params, api, lngIndex + 1, latIndex + 1);
  284.             return {
  285.                 type: 'rect',
  286.                 shape: {
  287.                     x: pointLeftTop[0],
  288.                     y: pointLeftTop[1],
  289.                     width: pointRightBottom[0] - pointLeftTop[0],
  290.                     height: pointRightBottom[1] - pointLeftTop[1]
  291.                 },
  292.                 style: api.style({
  293.                     stroke: 'rgba(0,0,0,0.1)'
  294.                 }),
  295.                 styleEmphasis: api.styleEmphasis()
  296.             };
  297.         }
  299.         function getCoord(params, api, lngIndex, latIndex) {
  300.             var coords = params.context.coords || (params.context.coords = []);
  301.             var key = lngIndex + '-' + latIndex;
  302.             return coords[key] || (coords[key] = api.coord([
  303.                 +(latExtent[0] + lngIndex * cellSizeCoord[0]).toFixed(6),
  304.                 +(lngExtent[0] + latIndex * cellSizeCoord[1]).toFixed(6)
  305.             ]));
  306.         }
  307.         """
  308.         )
  309.         .add(
  310.             series_name="",
  311.             data_pair=j["data"],
  312.             type_=ChartType.CUSTOM,
  313.             render_item=JsCode("renderItem"),
  314.             itemstyle_opts=opts.ItemStyleOpts(color="yellow"),
  315.             encode={"tooltip": 2},
  316.         )
  317.         .set_global_opts(
  318.             title_opts=opts.TitleOpts(title="BMap-Custom 图"),
  319.             tooltip_opts=opts.TooltipOpts(is_show=True, formatter=None),
  320.             visualmap_opts=opts.VisualMapOpts(
  321.                 is_piecewise=True,
  322.                 pos_top="10",
  323.                 pos_left="10",
  324.                 is_inverse=True,
  325.                 pieces=[
  326.                     {"value": i, "color": color_list[i]} for i in range(len(color_list))
  327.                 ],
  328.                 dimension=2,
  329.                 border_color="#ccc",
  330.                 border_width=2,
  331.                 background_color="#eee",
  332.                 range_opacity=0.7,
  333.             ),
  334.             graphic_opts=[
  335.                 opts.GraphicGroup(
  336.                     graphic_item=opts.GraphicItem(
  337.                         rotation=JsCode("Math.PI / 4"),
  338.                         bounding="raw",
  339.                         right=110,
  340.                         bottom=110,
  341.                         z=100,
  342.                     ),
  343.                     children=[
  344.                         opts.GraphicRect(
  345.                             graphic_item=opts.GraphicItem(
  346.                                 left="center", top="center", z=100
  347.                             ),
  348.                             graphic_shape_opts=opts.GraphicShapeOpts(
  349.                                 width=400, height=50
  350.                             ),
  351.                             graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
  352.                                 fill="rgba(0,0,0,0.3)"
  353.                             ),
  354.                         ),
  355.                         opts.GraphicText(
  356.                             graphic_item=opts.GraphicItem(
  357.                                 left="center", top="center", z=100
  358.                             ),
  359.                             graphic_textstyle_opts=opts.GraphicTextStyleOpts(
  360.                                 text="Made by pyecharts",
  361.                                 font="bold 26px Microsoft YaHei",
  362.                                 graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
  363.                                     fill="#fff"
  364.                                 ),
  365.                             ),
  366.                         ),
  367.                     ],
  368.                 )
  369.             ],
  370.         )
  371.     )
  372.     return c
  373.  
  374.  
  375. Page().add(*[fn() for fn, _ in C.charts]).render()

地图热力图

  1. #v0.5
  2. from pyecharts import Map
  3.  
  4. value = [155, 10, 66, 78, 33, 80, 190, 53, 49.6]
  5. attr = ["福建", "山东", "北京", "上海", "甘肃", "新疆", "河南", "广西", "西藏"]
  6. map = Map("Map 结合 VisualMap 示例", width=1200, height=600)
  7. map.add("", attr, value, maptype='china', is_visualmap=True, visual_text_color='#000')
  8. map.show_config()
  9. map.render()

左下角可以上下拖动

  1. #v0.5
  2. from pyecharts import Geo,Map
  3.  
  4. value = [95.1, 23.2, 43.3, 66.4, 88.5]
  5. attr= ["China", "Canada", "Brazil", "Russia", "United States"]
  6. map = Map("世界地图示例", width=1200, height=600)
  7. map.add("", attr, value, maptype="world", is_visualmap=True, visual_text_color='#000') 
  8. map.render()

广东地图

  1. #v0.5
  2. from pyecharts import Map
  3.  
  4. value = [20, 190, 253, 77, 65]
  5. attr = ['汕头市', '汕尾市', '揭阳市', '阳江市', '肇庆市']
  6. map = Map("广东地图示例", width=1200, height=600)
  7. map.add("", attr, value, maptype='广东', is_visualmap=True, visual_text_color='#000')
  8. map.show_config()
  9. map.render()

  1. #v1
  2. import pyecharts.options as opts
  3. from pyecharts.charts import MapGlobe
  4. from pyecharts.faker import POPULATION
  5.  
  6.  
  7. def map_globe_base():
  8.     data = [x for _, x in POPULATION[1:]]
  9.     low, high = min(data), max(data)
  10.  
  11.     mg = (
  12.         MapGlobe()
  13.         .add_schema()
  14.         .add(
  15.             maptype="world",
  16.             series_name="World Population",
  17.             data_pair=POPULATION[1:],
  18.             is_map_symbol_show=False,
  19.             label_opts=opts.LabelOpts(is_show=False),
  20.         )
  21.         .set_global_opts(
  22.             visualmap_opts=opts.VisualMapOpts(
  23.                 min_=low,
  24.                 max_=high,
  25.                 range_text=["max", "min"],
  26.                 is_calculable=True,
  27.                 range_color=["lightskyblue", "yellow", "orangered"],
  28.             )
  29.         )
  30.     )
  31.     mg.render()
  32.     
  33. map_globe_base()

能旋转

  1. #v1
  2.  
  3. from pyecharts import options as opts
  4. from pyecharts.charts import Map3D, Page
  5. from pyecharts.faker import Collector
  6. from pyecharts.globals import ChartType
  7. from pyecharts.commons.utils import JsCode
  8.  
  9. C = Collector()
  10.  
  11.  
  12. @C.funcs
  13. def map3d_china_base() -> Map3D:
  14.     c = (
  15.         Map3D()
  16.         .add_schema(
  17.             itemstyle_opts=opts.ItemStyleOpts(
  18.                 color="rgb(5,101,123)",
  19.                 opacity=1,
  20.                 border_width=0.8,
  21.                 border_color="rgb(62,215,213)",
  22.             ),
  23.             map3d_label=opts.Map3DLabelOpts(
  24.                 is_show=True,
  25.                 text_style=opts.TextStyleOpts(
  26.                     color="#fff", font_size=16, background_color="rgba(0,0,0,0)"
  27.                 ),
  28.             ),
  29.             emphasis_label_opts=opts.LabelOpts(is_show=True),
  30.             light_opts=opts.Map3DLightOpts(
  31.                 main_color="#fff",
  32.                 main_intensity=1.2,
  33.                 is_main_shadow=False,
  34.                 main_alpha=55,
  35.                 main_beta=10,
  36.                 ambient_intensity=0.3,
  37.             ),
  38.         )
  39.         .add(series_name="", data_pair="", maptype=ChartType.MAP3D)
  40.         .set_global_opts(
  41.             title_opts=opts.TitleOpts(title="全国行政区划地图-Base"),
  42.             visualmap_opts=opts.VisualMapOpts(is_show=False),
  43.             tooltip_opts=opts.TooltipOpts(is_show=True),
  44.         )
  45.     )
  46.     return c
  47.  
  48.  
  49. @C.funcs
  50. def map3d_with_bar3d() -> Map3D:
  51.     example_data = [
  52.         ("黑龙江", [127.9688, 45.368, 100]),
  53.         ("内蒙古", [110.3467, 41.4899, 300]),
  54.         ("吉林", [125.8154, 44.2584, 300]),
  55.         ("辽宁", [123.1238, 42.1216, 300]),
  56.         ("河北", [114.4995, 38.1006, 300]),
  57.         ("天津", [117.4219, 39.4189, 300]),
  58.         ("山西", [112.3352, 37.9413, 300]),
  59.         ("陕西", [109.1162, 34.2004, 300]),
  60.         ("甘肃", [103.5901, 36.3043, 300]),
  61.         ("宁夏", [106.3586, 38.1775, 300]),
  62.         ("青海", [101.4038, 36.8207, 300]),
  63.         ("新疆", [87.9236, 43.5883, 300]),
  64.         ("西藏", [91.11, 29.97, 300]),
  65.         ("四川", [103.9526, 30.7617, 300]),
  66.         ("重庆", [108.384366, 30.439702, 300]),
  67.         ("山东", [117.1582, 36.8701, 300]),
  68.         ("河南", [113.4668, 34.6234, 300]),
  69.         ("江苏", [118.8062, 31.9208, 300]),
  70.         ("安徽", [117.29, 32.0581, 300]),
  71.         ("湖北", [114.3896, 30.6628, 300]),
  72.         ("浙江", [119.5313, 29.8773, 300]),
  73.         ("福建", [119.4543, 25.9222, 300]),
  74.         ("江西", [116.0046, 28.6633, 300]),
  75.         ("湖南", [113.0823, 28.2568, 300]),
  76.         ("贵州", [106.6992, 26.7682, 300]),
  77.         ("广西", [108.479, 23.1152, 300]),
  78.         ("海南", [110.3893, 19.8516, 300]),
  79.         ("上海", [121.4648, 31.2891, 1300]),
  80.     ]
  81.  
  82.     c = (
  83.         Map3D()
  84.         .add_schema(
  85.             itemstyle_opts=opts.ItemStyleOpts(
  86.                 color="rgb(5,101,123)",
  87.                 opacity=1,
  88.                 border_width=0.8,
  89.                 border_color="rgb(62,215,213)",
  90.             ),
  91.             map3d_label=opts.Map3DLabelOpts(
  92.                 is_show=False,
  93.                 formatter=JsCode(
  94.                     "function(data){return data.name + " " + data.value[2];}"
  95.                 ),
  96.             ),
  97.             emphasis_label_opts=opts.LabelOpts(
  98.                 is_show=False,
  99.                 color="#fff",
  100.                 font_size=10,
  101.                 background_color="rgba(0,23,11,0)",
  102.             ),
  103.             light_opts=opts.Map3DLightOpts(
  104.                 main_color="#fff",
  105.                 main_intensity=1.2,
  106.                 main_shadow_quality="high",
  107.                 is_main_shadow=False,
  108.                 main_beta=10,
  109.                 ambient_intensity=0.3,
  110.             ),
  111.         )
  112.         .add(
  113.             series_name="bar3D",
  114.             data_pair=example_data,
  115.             type_=ChartType.BAR3D,
  116.             bar_size=1,
  117.             shading="lambert",
  118.             label_opts=opts.LabelOpts(
  119.                 is_show=False,
  120.                 formatter=JsCode(
  121.                     "function(data){return data.name + ' ' + data.value[2];}"
  122.                 ),
  123.             ),
  124.         )
  125.         .set_global_opts(title_opts=opts.TitleOpts(title="Map3D-Bar3D"))
  126.     )
  127.     return c
  128.  
  129.  
  130. @C.funcs
  131. def map3d_with_lines3d() -> Map3D:
  132.     example_data = [
  133.         [[119.107078, 36.70925, 1000], [116.587245, 35.415393, 1000]],
  134.         [[117.000923, 36.675807], [120.355173, 36.082982]],
  135.         [[118.047648, 36.814939], [118.66471, 37.434564]],
  136.         [[121.391382, 37.539297], [119.107078, 36.70925]],
  137.         [[116.587245, 35.415393], [122.116394, 37.509691]],
  138.         [[119.461208, 35.428588], [118.326443, 35.065282]],
  139.         [[116.307428, 37.453968], [115.469381, 35.246531]],
  140.     ]
  141.     c = (
  142.         Map3D()
  143.         .add_schema(
  144.             maptype="山东",
  145.             itemstyle_opts=opts.ItemStyleOpts(
  146.                 color="rgb(5,101,123)",
  147.                 opacity=1,
  148.                 border_width=0.8,
  149.                 border_color="rgb(62,215,213)",
  150.             ),
  151.             light_opts=opts.Map3DLightOpts(
  152.                 main_color="#fff",
  153.                 main_intensity=1.2,
  154.                 is_main_shadow=False,
  155.                 main_alpha=55,
  156.                 main_beta=10,
  157.                 ambient_intensity=0.3,
  158.             ),
  159.             view_control_opts=opts.Map3DViewControlOpts(center=[-10, 0, 10]),
  160.             post_effect_opts=opts.Map3DPostEffectOpts(is_enable=False),
  161.         )
  162.         .add(
  163.             series_name="",
  164.             data_pair=example_data,
  165.             type_=ChartType.LINES3D,
  166.             effect=opts.Lines3DEffectOpts(
  167.                 is_show=True,
  168.                 period=4,
  169.                 trail_width=3,
  170.                 trail_length=0.5,
  171.                 trail_color="#f00",
  172.                 trail_opacity=1,
  173.             ),
  174.             linestyle_opts=opts.LineStyleOpts(is_show=False, color="#fff", opacity=0),
  175.         )
  176.         .set_global_opts(title_opts=opts.TitleOpts(title="Map3D-Lines3D"))
  177.     )
  178.     return c
  179.  
  180.  
  181. @C.funcs
  182. def map3d_with_scatter3d() -> Map3D:
  183.     example_data = [
  184.         ("黑龙江", [127.9688, 45.368, 100]),
  185.         ("内蒙古", [110.3467, 41.4899, 100]),
  186.         ("吉林", [125.8154, 44.2584, 100]),
  187.         ("辽宁", [123.1238, 42.1216, 100]),
  188.         ("河北", [114.4995, 38.1006, 100]),
  189.         ("天津", [117.4219, 39.4189, 100]),
  190.         ("山西", [112.3352, 37.9413, 100]),
  191.         ("陕西", [109.1162, 34.2004, 100]),
  192.         ("甘肃", [103.5901, 36.3043, 100]),
  193.         ("宁夏", [106.3586, 38.1775, 100]),
  194.         ("青海", [101.4038, 36.8207, 100]),
  195.         ("新疆", [87.9236, 43.5883, 100]),
  196.         ("西藏", [91.11, 29.97, 100]),
  197.         ("四川", [103.9526, 30.7617, 100]),
  198.         ("重庆", [108.384366, 30.439702, 100]),
  199.         ("山东", [117.1582, 36.8701, 100]),
  200.         ("河南", [113.4668, 34.6234, 100]),
  201.         ("江苏", [118.8062, 31.9208, 100]),
  202.         ("安徽", [117.29, 32.0581, 100]),
  203.         ("湖北", [114.3896, 30.6628, 100]),
  204.         ("浙江", [119.5313, 29.8773, 100]),
  205.         ("福建", [119.4543, 25.9222, 100]),
  206.         ("江西", [116.0046, 28.6633, 100]),
  207.         ("湖南", [113.0823, 28.2568, 100]),
  208.         ("贵州", [106.6992, 26.7682, 100]),
  209.         ("广西", [108.479, 23.1152, 100]),
  210.         ("海南", [110.3893, 19.8516, 100]),
  211.         ("上海", [121.4648, 31.2891, 100]),
  212.     ]
  213.  
  214.     c = (
  215.         Map3D()
  216.         .add_schema(
  217.             itemstyle_opts=opts.ItemStyleOpts(
  218.                 color="rgb(5,101,123)",
  219.                 opacity=1,
  220.                 border_width=0.8,
  221.                 border_color="rgb(62,215,213)",
  222.             ),
  223.             map3d_label=opts.Map3DLabelOpts(
  224.                 is_show=False,
  225.                 formatter=JsCode(
  226.                     "function(data){return data.name + " " + data.value[2];}"
  227.                 ),
  228.             ),
  229.             emphasis_label_opts=opts.LabelOpts(
  230.                 is_show=False,
  231.                 color="#fff",
  232.                 font_size=10,
  233.                 background_color="rgba(0,23,11,0)",
  234.             ),
  235.             light_opts=opts.Map3DLightOpts(
  236.                 main_color="#fff",
  237.                 main_intensity=1.2,
  238.                 main_shadow_quality="high",
  239.                 is_main_shadow=False,
  240.                 main_beta=10,
  241.                 ambient_intensity=0.3,
  242.             ),
  243.         )
  244.         .add(
  245.             series_name="Scatter3D",
  246.             data_pair=example_data,
  247.             type_=ChartType.SCATTER3D,
  248.             bar_size=1,
  249.             shading="lambert",
  250.             label_opts=opts.LabelOpts(
  251.                 is_show=False,
  252.                 formatter=JsCode(
  253.                     "function(data){return data.name + ' ' + data.value[2];}"
  254.                 ),
  255.             ),
  256.         )
  257.         .set_global_opts(title_opts=opts.TitleOpts(title="Map3D-Scatter3D"))
  258.     )
  259.     return c
  260.  
  261.  
  262. Page().add(*[fn() for fn, _ in C.charts]).render()

自定义

  1. #v1
  2.  
  3. import json
  4. import os
  5.  
  6. from pyecharts import options as opts
  7. from pyecharts.charts import Page, PictorialBar
  8. from pyecharts.faker import Collector
  9. from pyecharts.globals import SymbolType
  10.  
  11. C = Collector()
  12.  
  13.  
  14. location = ["山西", "四川", "西藏", "北京", "上海", "内蒙古", "云南", "黑龙江", "广东", "福建"]
  15. values = [13, 42, 67, 81, 86, 94, 166, 220, 249, 262]
  16.  
  17. with open(os.path.join("fixtures", "symbol.json"), "r", encoding="utf-8") as f:
  18.     symbols = json.load(f)
  19.  
  20.  
  21. @C.funcs
  22. def pictorialbar_base() -> PictorialBar:
  23.     c = (
  24.         PictorialBar()
  25.         .add_xaxis(location)
  26.         .add_yaxis(
  27.             "",
  28.             values,
  29.             label_opts=opts.LabelOpts(is_show=False),
  30.             symbol_size=18,
  31.             symbol_repeat="fixed",
  32.             symbol_offset=[0, 0],
  33.             is_symbol_clip=True,
  34.             symbol=SymbolType.ROUND_RECT,
  35.         )
  36.         .reversal_axis()
  37.         .set_global_opts(
  38.             title_opts=opts.TitleOpts(title="PictorialBar-各省份人口数量（虚假数据）"),
  39.             xaxis_opts=opts.AxisOpts(is_show=False),
  40.             yaxis_opts=opts.AxisOpts(
  41.                 axistick_opts=opts.AxisTickOpts(is_show=False),
  42.                 axisline_opts=opts.AxisLineOpts(
  43.                     linestyle_opts=opts.LineStyleOpts(opacity=0)
  44.                 ),
  45.             ),
  46.         )
  47.     )
  48.     return c
  49.  
  50.  
  51. @C.funcs
  52. def pictorialbar_custom_symbol() -> PictorialBar:
  53.     c = (
  54.         PictorialBar()
  55.         .add_xaxis(location)
  56.         .add_yaxis(
  57.             "",
  58.             values,
  59.             label_opts=opts.LabelOpts(is_show=False),
  60.             symbol_size=22,
  61.             symbol_repeat="fixed",
  62.             symbol_offset=[0, -5],
  63.             is_symbol_clip=True,
  64.             symbol=symbols["boy"],
  65.         )
  66.         .reversal_axis()
  67.         .set_global_opts(
  68.             title_opts=opts.TitleOpts(title="PictorialBar-自定义 Symbol"),
  69.             xaxis_opts=opts.AxisOpts(is_show=False),
  70.             yaxis_opts=opts.AxisOpts(
  71.                 axistick_opts=opts.AxisTickOpts(is_show=False),
  72.                 axisline_opts=opts.AxisLineOpts(
  73.                     linestyle_opts=opts.LineStyleOpts(opacity=0)
  74.                 ),
  75.             ),
  76.         )
  77.     )
  78.     return c
  79.  
  80.  
  81. @C.funcs
  82. def pictorialbar_multi_custom_symbols() -> PictorialBar:
  83.     c = (
  84.         PictorialBar()
  85.         .add_xaxis(["reindeer", "ship", "plane", "train", "car"])
  86.         .add_yaxis(
  87.             "2015",
  88.             [
  89.                 {"value": 157, "symbol": symbols["reindeer"]},
  90.                 {"value": 21, "symbol": symbols["ship"]},
  91.                 {"value": 66, "symbol": symbols["plane"]},
  92.                 {"value": 78, "symbol": symbols["train"]},
  93.                 {"value": 123, "symbol": symbols["car"]},
  94.             ],
  95.             label_opts=opts.LabelOpts(is_show=False),
  96.             symbol_size=22,
  97.             symbol_repeat="fixed",
  98.             symbol_offset=[0, 5],
  99.             is_symbol_clip=True,
  100.         )
  101.         .add_yaxis(
  102.             "2016",
  103.             [
  104.                 {"value": 184, "symbol": symbols["reindeer"]},
  105.                 {"value": 29, "symbol": symbols["ship"]},
  106.                 {"value": 73, "symbol": symbols["plane"]},
  107.                 {"value": 91, "symbol": symbols["train"]},
  108.                 {"value": 95, "symbol": symbols["car"]},
  109.             ],
  110.             label_opts=opts.LabelOpts(is_show=False),
  111.             symbol_size=22,
  112.             symbol_repeat="fixed",
  113.             symbol_offset=[0, -25],
  114.             is_symbol_clip=True,
  115.         )
  116.         .reversal_axis()
  117.         .set_global_opts(
  118.             title_opts=opts.TitleOpts(title="PictorialBar-Vehicles in X City"),
  119.             xaxis_opts=opts.AxisOpts(is_show=False),
  120.             yaxis_opts=opts.AxisOpts(
  121.                 axistick_opts=opts.AxisTickOpts(is_show=False),
  122.                 axisline_opts=opts.AxisLineOpts(
  123.                     linestyle_opts=opts.LineStyleOpts(opacity=0)
  124.                 ),
  125.             ),
  126.         )
  127.     )
  128.     return c
  129.  
  130.  
  131. Page().add(*[fn() for fn, _ in C.charts]).render()

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