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
- 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
2.饼图
- 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
3.圆环图
- 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
4.散点图
- 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
5.仪表盘
- 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
6.热力图
- 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
高级图表
1.漏斗图
- 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")
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原文链接：https://blog.csdn.net/googgirl/article/details/80810322
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发表于 2020-03-08 16:26:36
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