数据大屏可视化3-通用数据大屏模版

数据大屏可视化1-pyecharts库说明（python）
数据大屏可视化2-超全的基础图形模板（基础模版）
数据大屏可视化3-通用数据大屏模版

简单设计：

1.简单折线图显示变化趋势

import random
import pyecharts.options as opts
from pyecharts.charts import Line
from pyecharts.commons.utils import JsCode
line = (
    Line()
    .add_xaxis(['1月','2月','3月','4月','5月'])  # 1-5月
    .add_yaxis('产品1', [20，22，21，18，19])
    .add_yaxis('产品2', [21，25，27，25，22])
    .add_yaxis('产品3', [26，28，28，27，30])
    .set_series_opts(title_opts=opts.TitleOpts(title='近两季度三个产品的销售'))     
    )

2.横向条形图进行数据对比

from pyecharts.charts import Bar
from pyecharts import options as opts
bar = (
    Bar()
    .add_xaxis(["产品1", "产品2", "产品3"])
    .add_yaxis("一季度",[63,73,82])
    .add_yaxis("二季度",[37,47,57])
    .reversal_axis()
    .set_global_opts(title_opts=opts.TitleOpts("rever")
                       ,toolbox_opts = opts.ToolboxOpts(is_show = True))
    .set_series_opts(title_opts=opts.TitleOpts(title='近两季度三个产品的销售'),label_opts=opts.LabelOpts(position = "right"))
)

3.环形图进行查看占比

from pyecharts import options as opts
from pyecharts.charts import Pie
pie = (
    Pie()
    .add(
        '销售：',
        [list(z) for z in zip(["产品1", "产品2", "产品3"],[100,120,139])],
        radius=['50%', '75%'],          #设置内径外径           
        label_opts=opts.LabelOpts(is_show=True)        
    )
    .set_global_opts(title_opts=opts.TitleOpts(title='近两季度三个产品的销售'),
                     legend_opts=opts.LegendOpts(is_show=False))
)

4.地理图显示各个区域的门店的销售情况

from pyecharts import options as opts
from pyecharts.charts import Map
import random
province = ['广东', '湖北', '湖南', '四川', '重庆', '黑龙江', '浙江', '山西', '河北', '安徽', '河南', '山东', '西藏']
data = [(i, random.randint(50, 150)) for i in province]
map = (
        Map()
        .add("销售额", data, "china")
        .set_global_opts(
            title_opts=opts.TitleOpts(title="近两个季度各地门店销售情况"),
            legend_opts=opts.LegendOpts(is_show=False),
            visualmap_opts=opts.VisualMapOpts(max_=200, is_piecewise=True),
        )
    )

5.雷达图显示多维度信息的影响度

import random
from pyecharts import options as opts
from pyecharts.charts import Page, Radar
def radar_simple() -> Radar:
    c = (
        Radar()
        .add_schema(
            # 各项的max_值可以不同
            schema=[
                opts.RadarIndicatorItem(name='款式', max_=100),
                opts.RadarIndicatorItem(name='颜色', max_=100),
                opts.RadarIndicatorItem(name='码数', max_=100),
                opts.RadarIndicatorItem(name='材质', max_=100),
                opts.RadarIndicatorItem(name='质量', max_=100),
                opts.RadarIndicatorItem(name='价格', max_=100),
            ]
        )
        .add('产品1', [[random.randint(10, 101) for _ in range(6)]],           
             color='red',           
             areastyle_opts = opts.AreaStyleOpts(  #设置填充的属性
                 opacity = 0.5,                  
                 color='red'                     
         ),)
        .add('产品2', [[random.randint(10, 101) for _ in range(6)]],
             color='blue',
             areastyle_opts = opts.AreaStyleOpts(
                 opacity = 0.5,#透明度
                 color='blue'
         ),)
        .set_series_opts(label_opts=opts.LabelOpts(is_show=True))
        .set_global_opts(title_opts=opts.TitleOpts(title='款色码质价对产品影响度'))
    )
    return c
#radar_simple()



from pyecharts.charts import Funnel
from pyecharts import options as opts
funnel = (Funnel()
          .add("用户数", [list(z) for z in zip(['访问', '注册', '加入购物车', '提交订单', '付款成功'], [30398, 15230, 10045, 8109, 5698])], 
               sort_='ascending',
               label_opts=opts.LabelOpts(position="inside"))
          .set_global_opts(title_opts=opts.TitleOpts(title="Funnel-基本示例", subtitle="我是副标题"))
         )

最后得到一个比较丑的数据大屏

全篇代码

import random
from pyecharts.commons.utils import JsCode
from pyecharts.charts import Bar,Pie,Map,Page, Radar,Funnel,Line,Grid
from pyecharts import options as opts
from pyecharts.globals import ThemeType


line1 = (
    Line()
    .add_xaxis(['1月','2月','3月','4月','5月'])  # 1-5月
    .add_yaxis('产品1', [20,22,21,18,19])
    .add_yaxis('产品2', [21,25,27,25,22])
    .add_yaxis('产品3', [26,28,28,27,30])
    .set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-30)), # 设置x轴标签旋转角度
                     yaxis_opts=opts.AxisOpts(name='销售额', min_=3), 
                     title_opts=opts.TitleOpts(title='近两季度销售'))     
    )
line1.theme = ThemeType.PURPLE_PASSION

bar1 = (
    Bar()
    .add_xaxis(["产品1", "产品2", "产品3"])
    .add_yaxis("一季度",[63,73,82])
    .add_yaxis("二季度",[37,47,57])
    .reversal_axis()
    # .set_global_opts(title_opts=opts.TitleOpts("rever")
    #                    ,toolbox_opts = opts.ToolboxOpts(is_show = True))
    .set_series_opts(title_opts=opts.TitleOpts(title='近两季度三个产品的销售'),label_opts=opts.LabelOpts(position = "right"))
)
bar1.theme = ThemeType.PURPLE_PASSION


pie = (
    Pie()
    .add(
        '销售：',
        [list(z) for z in zip(["产品1", "产品2", "产品3"],[100,120,139])],
        radius=['50%', '75%'],          #设置内径外径           
        label_opts=opts.LabelOpts(is_show=True)        
    )
    .set_global_opts(title_opts=opts.TitleOpts(title='近两季度三个产品的销售\n'),
                     legend_opts=opts.LegendOpts(is_show=False))
)
pie.theme = ThemeType.PURPLE_PASSION



province = ['广东', '湖北', '湖南', '四川', '重庆', '黑龙江', '浙江', '山西', '河北', '安徽', '河南', '山东', '西藏']
data = [(i, random.randint(50, 150)) for i in province]
map1 = (
        Map()
        .add("销售额", data, "china")
        .set_global_opts(
            title_opts=opts.TitleOpts(title="近两个季度各地门店销售情况"),
            legend_opts=opts.LegendOpts(is_show=False),
            visualmap_opts=opts.VisualMapOpts(max_=200, is_piecewise=True),
        )
    )
map1.theme = ThemeType.PURPLE_PASSION


radar1 = (
    Radar()
    .add_schema(
        # 各项的max_值可以不同
        schema=[
            opts.RadarIndicatorItem(name='款式', max_=100),
            opts.RadarIndicatorItem(name='颜色', max_=100),
            opts.RadarIndicatorItem(name='码数', max_=100),
            opts.RadarIndicatorItem(name='材质', max_=100),
            opts.RadarIndicatorItem(name='质量', max_=100),
            opts.RadarIndicatorItem(name='价格', max_=100),
        ]
    )
    .add('产品1', [[random.randint(10, 101) for _ in range(6)]],           
            color='red',           
            areastyle_opts = opts.AreaStyleOpts(  #设置填充的属性
                opacity = 0.5,                  
                color='red'                     
        ),)
    .add('产品2', [[random.randint(10, 101) for _ in range(6)]],
            color='blue',
            areastyle_opts = opts.AreaStyleOpts(
                opacity = 0.5,#透明度
                color='blue'
        ),)
    .set_series_opts(label_opts=opts.LabelOpts(is_show=True))
    .set_global_opts(title_opts=opts.TitleOpts(title='款色码质价影响'))
)
radar1.theme = ThemeType.PURPLE_PASSION



x_data = ["{}月".format(i) for i in range(1, 13)]
zengfaliang =  [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
jiangshuiliang = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
average_wendu = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]
grid = Grid()
bar = Bar()
grid.theme = ThemeType.PURPLE_PASSION
line = Line()
bar.add_xaxis(x_data)
bar.add_yaxis("产品A销售量",zengfaliang)
bar.add_yaxis("产品B销售量",jiangshuiliang)
bar.set_global_opts(title_opts=opts.TitleOpts("天气影响")
                   ,tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross") # 交叉指向工具
                   )
bar.extend_axis(yaxis=opts.AxisOpts(type_="value",
                                     name="温度",
                                     min_=0,
                                     max_=25,
                                     position="right",                    
                                     axislabel_opts=opts.LabelOpts(formatter="{value} °C"),
                                     ))
# 在bar上增加Y轴,在line图上选择对应的轴向
line.add_xaxis(x_data)
line.add_yaxis("平均温度",average_wendu,yaxis_index = 1)
# 把line添加到bar上
bar.overlap(line)
# 这里如果不需要grid也可以,直接设置bar的格式,然后显示bar即可
#bar.render_notebook()
grid.add(chart = bar,grid_opts = opts.GridOpts(),is_control_axis_index = True)



funnel = (Funnel()
          .add("用户数", [list(z) for z in zip(['访问', '注册', '加入购物车', '提交订单', '付款成功'], [30398, 15230, 10045, 8109, 5698])], 
               sort_='ascending',
               label_opts=opts.LabelOpts(position="inside"))
          .set_global_opts(title_opts=opts.TitleOpts(title=" ", subtitle="线上交易用户数据分析"))
         )
funnel.theme = ThemeType.PURPLE_PASSION

#拼合所有图表
page = (Page().add(line1).add(bar1).add(pie).add(map1).add(radar1).add(grid).add(funnel))
page.render('产品销售情况大屏幕数据显示.html')



#调整图表位置
from bs4 import BeautifulSoup
with open("产品销售情况大屏幕数据显示.html", "r+", encoding='utf-8') as html:
    html_bf = BeautifulSoup(html, 'lxml')
    divs = html_bf.select('.chart-container')
    #宽度：500px；高度：250像素；位置：绝对；顶部：50像素；左：0px；边框样式：纯色；边框颜色：#444444；边框-宽度：3px；
    divs[0]["style"] = "width:500px;height:300px;position:absolute;top:50px;left:50px;border-style:solid;border-color:#444444;border-width:0px;"
    divs[1]['style'] = "width:500px;height:300px;position:absolute;top:350px;left:50px;border-style:solid;border-color:#444444;border-width:0px;"
    divs[2]["style"] = "width:500px;height:300px;position:absolute;top:650px;left:50px;border-style:solid;border-color:#444444;border-width:0px;"
    divs[3]["style"] = "width:600px;height:600px;position:absolute;top:150px;left:650px;border-style:solid;border-color:#444444;border-width:0px;"
    divs[4]["style"] = "width:500px;height:300px;position:absolute;top:50px;left:1350px;border-style:solid;border-color:#444444;border-width:0px;"
    divs[5]["style"] = "width:500px;height:300px;position:absolute;top:350px;left:1350px;border-style:solid;border-color:#444444;border-width:0px;"
    divs[6]["style"] = "width:500px;height:300px;position:absolute;top:650px;left:1350px;border-style:solid;border-color:#444444;border-width:0px;"
    body = html_bf.find("body")
    body["style"] = "background-color:rgb(91 92 110);"
    div_title="
\n产品销售情况大屏幕数据显示
"  
    #修改页面背景色、追加标题
    body.insert(0,BeautifulSoup(div_title,"lxml").div)
    html_new = str(html_bf)
    html.seek(0, 0)
    html.truncate()
    html.write(html_new)
    html.close()