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python报表可视化(使用Python快速制作可视化报表的方法)

更多 时间:2022-04-03 12:38:42 类别:脚本大全 浏览量:2361

python报表可视化

使用Python快速制作可视化报表的方法

我们可以试用可视化包——pyechart。

echarts是百度开源的一个数据可视化js库,主要用于数据可视化。

pyecharts是一个用于生成echarts图标的类库。实际就是echarts与python的对接。

安装

pyecharts兼容python2和python3。执行代码:

pip install pyecharts(快捷键windows+r——输入cmd)

初级图表

1.柱状图/条形图

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  • from pyecharts import bar
  • attr=["衬衫","羊毛衫","雪纺衫","裤子","高跟鞋","袜子"]
  • v1=[5,20,36,10,75,90]
  • v2=[10,25,8,60,20,80]
  • bar=bar("各商家产品销售情况")
  • bar.add("商家a",attr,v1,is_stack=true)
  • bar.add("商家b",attr,v2,is_stack=true)
  • bar#bar.render()
  • python报表可视化(使用Python快速制作可视化报表的方法)

    2.饼图

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  • from pyecharts import pie
  • attr=["衬衫","羊毛衫","雪纺衫","裤子","高跟鞋","鞋子"]
  • v1=[11,12,13,10,10,10]
  • pie=pie("各产品销售情况")
  • pie.add("",attr,v1,is_label_show=true)
  • pie  #pie.render()
  • python报表可视化(使用Python快速制作可视化报表的方法)

    3.圆环图

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  • from pyecharts import pie
  • attr=["衬衫","羊毛衫","雪纺衫","裤子","高跟鞋","鞋子"]
  • v1=[11,12,13,10,10,10]
  • pie=pie("饼图—圆环图示例",title_pos="center")
  • pie.add("",attr,v1,radius=[40,75],label_text_color=none,
  •   is_label_show=true,legend_orient="vertical",
  •   legend_pos="left")
  • pie
  • python报表可视化(使用Python快速制作可视化报表的方法)

    4.散点图

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  • from pyecharts import scatter
  • v1=[10,20,30,40,50,60]
  • v2=[10,20,30,40,50,60]
  • scatter=scatter("散点图示例")
  • scatter.add("a",v1,v2)
  • scatter.add("b",v1[::-1],v2)
  • scatter
  • python报表可视化(使用Python快速制作可视化报表的方法)

    5.仪表盘

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  • from pyecharts import gauge
  • gauge=gauge("业务指标完成率—仪表盘")
  • gauge.add("业务指标","完成率",66.66)
  • gauge
  • python报表可视化(使用Python快速制作可视化报表的方法)

    6.热力图

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  • import random
  • from pyecharts import heatmap
  • x_axis=[
  •  "12a","1a","2a","3a","4a","5a","6a","7a","8a","9a","10a","11a",
  •  "12p","1p","2p","3p","4p","5p","6p","7p","8p","9p","10p","11p",]
  • y_axis=[
  •  "saturday","friday","thursday","wednesday","tuesday","monday","sunday"]
  • data=[[i,j,random.randint(0,50)] for i in range(24) for j in range(7)]
  • heatmap=heatmap()
  • heatmap.add("热力图直角坐标系",x_axis,y_axis,data,is_visualmap=true,
  •    visual_text_color="#000",visual_orient="horizontal")
  • heatmap
  • python报表可视化(使用Python快速制作可视化报表的方法)

    高级图表

    1.漏斗图

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  • from pyecharts import funnel
  • attr=["潜在","接触","意向","明确","投入","谈判","成交"]
  • value=[140,120,100,80,60,40,20]
  • funnel=funnel("销售管理分析漏斗图")
  • funnel.add("商品",attr,value,is_label_show=true,
  •    label_pos="inside",label_text_color="#fff")
  • funnel
  • 2.词云图

    python报表可视化(使用Python快速制作可视化报表的方法)

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  • from pyecharts import wordcloud
  • name=[
  •  "sam s club","macys","amy schumer","jurassic world","charter communications",
  •  "chick fil a","planet fitness","pitch perfect","express","home","johnny depp",
  •  "lena dunham","lewis hamilton","kxan","mary ellen mark","farrah abraham",
  •  "rita ora","serena williams","ncaa baseball tournament","point break"
  • ]
  • value=[
  •  10000,6181,4386,4055,2467,2244,1898,1484,1112,
  •  965,847,582,555,550,462,366,360,282,273,265]
  • wordcloud=wordcloud(width=1300,height=620)
  • wordcloud.add("",name,value,word_size_range=[20,100])
  • wordcloud
  • python报表可视化(使用Python快速制作可视化报表的方法)

    3.组合图

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  • from pyecharts import line,pie,grid
  • line=line("折线图",width=1200)
  • attr=["周一","周二","周三","周四","周五","周六","周日"]
  • line.add("最高气温",attr,[11,11,15,13,12,13,10],
  •   mark_point=["max","min"],mark_line=["average"])
  • line.add("最低气温",attr,[1,-2,2,5,3,2,0],
  •   mark_point=["max","min"],mark_line=["average"],
  •   legend_pos="20%")
  • attr=["衬衫","羊毛衫","雪纺衫","裤子","高跟鞋","袜子"]
  • v1=[11,12,13,10,10,10]
  • pie=pie("饼图",title_pos="55%")
  • pie.add("",attr,v1,radius=[45,65],center=[65,50],
  •   legend_pos="80%",legend_orient="vertical")
  • grid=grid()
  • grid.add(line,grid_right="55%")
  • grid.add(pie,grid_left="60%")
  • grid
  • python报表可视化(使用Python快速制作可视化报表的方法)

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    原文链接:https://blog.csdn.net/weixin_41774060/article/details/79419315