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Pyecharts

本文主要是介绍Pyecharts,对大家解决编程问题具有一定的参考价值,需要的程序猿们随着小编来一起学习吧!

Pyecharts

绘制一个柱状图

from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.charts import Bar  # 实例化

bar = Bar()
# x,y 内添加的必须是list, list类型必须是python基础类型
bar.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
bar.add_yaxis("商家A", [114, 55, 27, 101, 125, 27, 105])
bar.add_yaxis("商家B", [57, 134, 137, 129, 145, 60, 49])
bar.set_global_opts(title_opts=opts.TitleOpts(title="某商场销售情况"))
bar.render('this is a test html.html')

堆叠柱状图

  • 切换皮肤
  • 旋转轴标签
  • stack堆叠
  • 添加mark点, line辅助线
  • x轴y轴交换
from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.globals import ThemeType  # 主题颜色
from pyecharts.charts import Bar  # 实例化

# 改变皮肤, 尺寸
bar = Bar(init_opts=opts.InitOpts(
                                theme=ThemeType.DARK,
                                width='800px',
                                height="600px"))
# x,y 内添加的必须是list, list内数据类型必须是python基础类型, 如果是numpy数组需要转成list
bar.add_xaxis(Faker.choose())
# 堆叠柱状图 stack='stack1'表示堆叠在stack1这一组里面
bar.add_yaxis('商家A',Faker.values(),stack='stack1')
bar.add_yaxis('商家B',Faker.values(),stack='stack1')
bar.add_yaxis('商家C',Faker.values(),stack='stack2')
bar.add_yaxis('商家D',Faker.values(),stack='stack2')
# 添加标题 副标题
bar.set_global_opts(title_opts=opts.TitleOpts(title="Bar_基本示例",subtitle="我是副标题"),
                    # 旋转x轴角度
                    xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=30)))
# 添加最大,最小点, 平均线
bar.set_series_opts(
    label_opts=opts.LabelOpts(is_show=False),
    markpoint_opts=opts.MarkPointOpts(
        data=[
            opts.MarkPointItem(type_='max',name="最大值"),
            opts.MarkPointItem(type_='min',name="最小值"),
        ]
    ),
    markline_opts=opts.MarkLineOpts(
        data=[
            opts.MarkLineItem(type_="average",name="平均值"),
        ]
    )
)
# x,y轴交换
bar.reversal_axis()
bar.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

窗口滑块

from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.globals import ThemeType  # 主题颜色
from pyecharts.charts import Bar  # 实例化



# 改变皮肤, 尺寸
bar = Bar(init_opts=opts.InitOpts(
    theme=ThemeType.DARK,
    width='800px',
    height="600px"))
bar.add_xaxis(Faker.days_attrs)
bar.add_yaxis("商家A",Faker.days_values)
bar.set_global_opts(
    title_opts=opts.TitleOpts(
        title="Bar_基本示例",
        subtitle="我是副标题"),
    # 添加窗口滑块效果
    datazoom_opts=[opts.DataZoomOpts()]
    )
bar.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

3D柱状图

import random
from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.charts import Bar3D  # 实例化


bar3d = Bar3D()
# 需要三维的数据 ,
data = [(i,j,random.randint(0,12)) for i in range(24) for j in range(6)]
bar3d.add(
    "",
    data,
    xaxis3d_opts=opts.Axis3DOpts(Faker.clock,type_='category'),
    yaxis3d_opts=opts.Axis3DOpts(Faker.week_en,type_='category'),
    zaxis3d_opts=opts.Axis3DOpts(type_='value'),
)
bar3d.set_global_opts(
    visualmap_opts=opts.VisualMapOpts(max_=20),
    title_opts=opts.TitleOpts(title="Bar3D_基本示例")
    )
bar3d.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

折线 / 面积图

from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.charts import Line  # 实例化


line = Line()
line.add_xaxis(Faker.choose())
# is_smooth 折现变平滑
line.add_yaxis("商家A",Faker.values(),
               is_smooth=True,
               areastyle_opts=opts.AreaStyleOpts(
                   # opacity 透明度
                   opacity=0.2,
                   # color 填充区域颜色
                   color='#000'
               ))
line.add_yaxis("商家B",Faker.values())
line.set_global_opts(title_opts=opts.TitleOpts(title='Line_基本示例'))
line.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

饼图

from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.charts import Pie  # 实例化


pie = Pie()
# radius 内环和外环半径, 列表类型
# rosetype 玫瑰饼图
# resetype = 'area' , 所有扇区圆心角相同, 仅通过半径展现圆心角大小
#          = 'radius' , 圆心角展现百分比 , 
pie.add("",[list(z) for z in zip(Faker.choose(),Faker.values())],
        radius=["40%","75%"],
        rosetype='radius')
pie.set_global_opts(title_opts=opts.TitleOpts(title='Pie_基本示例'))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter='{b}:{c}'))
pie.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

涟漪效果散点图

from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.charts import EffectScatter  # 实例化
from pyecharts.globals import SymbolType

effect_scatter = EffectScatter()
effect_scatter.add_xaxis(Faker.choose())
effect_scatter.add_yaxis("",
                         Faker.values(),
                         symbol=SymbolType.ARROW)
effect_scatter.set_global_opts(title_opts=opts.TitleOpts(title="EffectScatter_基本示例"))
effect_scatter.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

漏斗图

from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.charts import Funnel  # 实例化

funnel = Funnel()
funnel.add(
    "用户转化率",
    [list(z) for z in zip(Faker.choose(),Faker.values())],
    # position = 'inside' 图例名放在图形中间
    label_opts=opts.LabelOpts(position='inside')
)
funnel.set_global_opts(title_opts=opts.TitleOpts(title="Funnel_基本示例"))
funnel.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

地理坐标系

from pyecharts.faker import Faker  # 数据集
from pyecharts import options as opts  # 配置
from pyecharts.charts import Geo  # 实例化

geo = Geo()
geo.add_schema(maptype="china")
geo.add('geo',[list(z) for z in zip(Faker.provinces,Faker.values())],
        type_='heatmap')
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo.set_global_opts(
    visualmap_opts=opts.VisualMapOpts(),
    title_opts=opts.TitleOpts(title="Geo_基本示例")
)
geo.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

水球图

from pyecharts import options as opts  # 配置
from pyecharts.charts import Liquid  # 实例化

liquid = Liquid()
liquid.add('Liquid',[0.7,0.6,0.5])
liquid.set_global_opts(title_opts=opts.TitleOpts(title="Liquid_基本示例"))
liquid.render(R'F:\1000篇技术博客\pyecharts\chart1.html')

雷达图

词云图

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