Pyecharts基础绘图

1.Pyecharts模块常用配置

Pyecharts模块常见的配置项有以下几种：

• 初始化配置项(InitOpts)
• 标题配置项(TitleOpts)
• 图例配置项(LegendOpts)
• 工具箱配置项(ToolboxOpts)
• 视觉映射配置项(VisualMapOpts)
• 提示框配置项(TooltipOpts)
• 区域缩放配置项(DataZoomOpts)

全局配置：通过set_global_opts()方法进行设置，可以修改图表的默认配置，如：主题、自动调整大小、宽度、高度等。

系列配置：通过set_series_opts()方法进行设置，用于控制每个系列的图表样式和数据，如线条样式、柱状图颜色、标签格式等。

可通过全局配置项控制以下区域：

本文所有内容基于Pyecharts2.0.9版本，Pyecharts版本查询方式如下：

import pyecharts
print(pyecharts.__version__)

本文所有图片均在Jupyter Lab中完成，在Jupyter Lab中显示图片需要在代码前面添加以下内容：

from pyecharts.globals import CurrentConfig,NotebookType
CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB

2.柱状图

from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.charts import Bar
import pyecharts.options as opts

cate =['华为', '小米', '苹果', 'OPPO', 'ViVo', '魅族']
data1 = [143, 155, 200, 100, 88, 50]
data2 = [100, 120, 400, 110, 94, 30]

bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('电商渠道', data1)
       .add_yaxis('门店',data2)
       .set_global_opts(
           title_opts=opts.TitleOpts(title='Bar-示例',subtitle='Bar'),
           legend_opts=opts.LegendOpts(is_show=True))
       .set_series_opts(
           label_opts=opts.LabelOpts(position='top'))
      )
bar.load_javascript()

# 静态图片的展示需要单独使用一个cell
bar.render_notebook()

3.饼图

from pyecharts.charts import Pie
import pyecharts.options as opts

cate =['华为', '小米', '苹果', 'OPPO', 'ViVo', '魅族']
data1 = [143, 155, 200, 100, 88, 50]
data2 = [100, 120, 400, 110, 94, 30]

pie = (Pie()
       .add("",[list(z) for z in zip(cate,data1)],
            radius=['30%','75%'],
            rosetype='radius')
       .set_global_opts(title_opts=opts.TitleOpts(title='Pie-示例',subtitle='副标题'))
       .set_series_opts(label_opts=opts.LabelOpts(formatter='{a}:{d}%'))
       )
pie.load_javascript()

pie.render_notebook()

4.折线图

from pyecharts.charts import Line
import pyecharts.options as opts

cate =['华为', '小米', '苹果', 'OPPO', 'ViVo', '魅族']
data1 = [143, 155, 200, 100, 88, 50]
data2 = [100, 120, 400, 110, 94, 30]

line = (Line()
        .add_xaxis(cate)
        .add_yaxis('电商渠道',data1,
                   markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_='average')]))
        .add_yaxis('门店',data2,
                   is_smooth=True,
                   markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(name='自定义标记点',
                                                                            coord=[cate[2],data2[2]],value=data2[2])])
                  )
        .set_global_opts(title_opts=opts.TitleOpts(title='Line-示例',subtitle='副标题'))
       )
line.load_javascript()

line.render_notebook()

5.漏斗图

from pyecharts.charts import Funnel

cate = ['访问', '注册', '加入购物车', '提交订单', '付款成功']
data = [99999, 50000,  30000, 15000, 5000]

funnel = (Funnel()
          .add('用户数',[list(z) for z in zip(cate,data)],
               sort_='descending',
               min_= 0,
               max_= 99999,
               label_opts=opts.LabelOpts(position='inside', formatter="{b}:{c}"))
          .set_global_opts(title_opts=opts.TitleOpts(title='漏斗图',subtitle='副标题'))
         )
funnel.load_javascript()

funnel.render_notebook()

6.热度图

from pyecharts.charts import HeatMap
from pyecharts.faker import Faker
import random

data = [[i, j,random.randint(0, 50)] for i in range(24) for j in range(7)]
heat = (HeatMap()
        .add_xaxis(Faker.clock)
        .add_yaxis('访客数',
                   Faker.week,
                   data,
                   label_opts=opts.LabelOpts(is_show=True,position='inside'))
        .set_global_opts(
            title_opts=opts.TitleOpts(title='HeatMap-示例',subtitle='副标题'),
            visualmap_opts=opts.VisualMapOpts(),
            legend_opts=opts.LegendOpts(is_show=False))
       )
heat.load_javascript()

heat.render_notebook()

7.日历图

from pyecharts.charts import Calendar
import datetime

begin = datetime.date(2025, 1, 1)
end = datetime.date(2025, 12, 31)
data = [[str(begin + datetime.timedelta(days=i)),random.randint(1000,30000)] 
        for i in range((end-begin).days + 1)]

calendar = (Calendar()
            .add('微信步数',data,
                 calendar_opts=opts.CalendarOpts(range_='2025'))
            .set_global_opts(
                title_opts=opts.TitleOpts(title='Calendar-示例', subtitle='副标题'),
                legend_opts=opts.LegendOpts(is_show=False),
                visualmap_opts=opts.VisualMapOpts(
                    max_= 30000,
                    min_=1000,
                    orient='horizontal',
                    is_piecewise=True,
                    pos_top='230px',
                    pos_left= '100px'
                )
            )
           )
calendar.load_javascript()

calendar.render_notebook()

8.3D散点图

from pyecharts.charts import Scatter3D
from pyecharts import options as opts
from pyecharts.faker import Faker
import random

data = [[random.randint(0,100),random.randint(0,100),random.randint(0,100)] for _ in range(1000)]

scatter3D = (Scatter3D()
             .add('',data)
             .set_global_opts(
                 title_opts=opts.TitleOpts(title='Scatter3D-示例',subtitle='副标题'),
                 visualmap_opts=opts.VisualMapOpts(range_color=Faker.visual_color))
            )
scatter3D.load_javascript()

scatter3D.render_notebook()

9.XY轴翻转

bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('电商渠道', data1)
       .add_yaxis('门店', data2)
       .set_global_opts(title_opts=opts.TitleOpts(title='XY轴翻转-示例', subtitle='副标题'))
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
       .reversal_axis()
      )
bar.load_javascript()

bar.render_notebook()

10.组合图表

province = ['武汉', '十堰', '鄂州', '宜昌', '荆州', '孝感', '黄石', '咸宁', '仙桃']
data = [324, 125, 145, 216, 241, 244, 156, 278, 169]

bar = (Bar()
       .add_xaxis(province)
       .add_yaxis('营业额', data)
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
       .set_global_opts(
           title_opts=opts.TitleOpts(title='Grid-Bar')
       )
      )
line = (Line()
        .add_xaxis(province)
        .add_yaxis('营业额', data,
                   markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_='average')]))
        .set_global_opts(title_opts=opts.TitleOpts(title='Grid-Line', pos_top='48%'))
       )
grid = (Grid()
        .add(bar, grid_opts=opts.GridOpts(pos_bottom="60%"))
        .add(line,grid_opts=opts.GridOpts(pos_top='60%'))
       )
grid.load_javascript()

grid.render_notebook()

11.时间轴图

from pyecharts.charts import Bar,Timeline
import pyecharts.options as opts
import random

cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Meizu']
tl = Timeline()
for i in range(2015, 2025):
    bar = (Bar()
           .add_xaxis(cate)
           .add_yaxis('电商渠道', [random.randint(50,200) for _ in cate])
           .add_yaxis('门店', [random.randint(100, 300) for _ in cate])
           .set_global_opts(title_opts=opts.TitleOpts("各品牌手机{}年销量".format(i)))
          )
    tl.add(bar,"{}年".format(i))
tl.load_javascript()

tl.render_notebook()