pyecharts简单使用示例

刺骨的言语ヽ痛彻心扉 2022-05-11 08:40 217阅读 0赞

pyecharts 相对matplotlib库生成图像更加美观，方便，可以增加各种动态效果，显示效果多样，比较建议学习一下。

这里做几个常用简单的实例：

from pyecharts import WordCloud,Pie,Bar,EffectScatter,Gauge,Line,Grid,Timeline  
import random

from pyecharts import WordCloud,Pie,Bar,EffectScatter,Gauge,Line,Grid,Timeline
    import random
    attr =["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
    v1 =[11, 12, 13, 10, 10, 10]
    v2=[12,24,13,16,14,14]
    pie =Pie("饼图示例")
    pie.add("",attr,v2,is_label_show=True)
    pie

attr =["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
    v1=[5,20,36,10,75,90]
    v2=[10,25,10,60,20,80]
    bar=Bar('柱状图数据堆叠示例')
    bar.add('商家A',attr,v1,mark_point=['average'],is_stack=True)
    bar.add('商家B',attr,v2,mark_line=['max','min'],is_stack=True)
    bar

![70][]

# 词云图
    name=['乾卦','元始','亨通','和谐','有利','贞正坚固','巨龙','潜伏','水中','施展才用',
          '坤卦','雌马','守持正固','君子','有所前往','抢先居首','迷入歧途','随从','做主','安顺']
    value=[10000,6181,4378,4054,2468,2214,1969,1479,1123,3210,
           9988,4563,866,563,3345,2306,785,653,126,345]
    wordcloud=WordCloud(width=1200,height=620)
    wordcloud.add('',name,value,word_size_range=[20,100])
    wordcloud

![70 1][]

import random
    attr=["{}天".format(i) for i in range(30)]
    v1=[random.randint(1,30) for _ in range(30)]
    bar=Bar('Bar - datazoom -slider')
    bar.add("",attr,v1,is_label_show=True,is_datazoom_show=True)
    bar

![70 2][]

gauge=Gauge('仪表盘实例')
    gauge.add('业务指标','完成率',66.66)
    
    gauge.render('gauge.html')
    gauge

![70 3][]

v1=[10,20,30,40,50,60]
    v2=[25,20,15,10,60,33]
    es=EffectScatter('动态散点图',width=600,height=300)
    es.add('effectScatter',v1,v2)
    es

![70 4][]

attr =["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
    v1 =[11, 12, 13, 10, 10, 100]
    pie=Pie('饼状示意图')
    pie.add('',attr,v1,is_label_show=True)
    pie

![70 5][]

value=[120,110,130]
    attr=['河南','山西','辽宁']
    map=Map('Map 结合 VisualMap 实例',width=800,height=400)
    map.add('',attr,value,maptype='china',is_visualmap=True,visual_text_color='#000')
    map

![70 6][]

attr =["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
    v1=[5,20,36,10,75,90]
    v2=[10,25,10,60,20,80]
    bar=Bar('柱状图数据堆叠示例',height=720)
    bar.add('商家A',attr,v1,is_stack=True)
    bar.add('商家B',attr,v2,is_stack=True)
    line=Line('折线图实例',title_top='50%')
    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,-1,2,5,2,3,0],mark_point=['max','min'],mark_line=['average'],legend_top='50%',)
    
    grid=Grid()
    grid.add(bar,grid_bottom='60%')
    grid.add(line,grid_top='60%')
    grid

![70 7][]

attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
    pie_1 = Pie("2012 年销量比例", "数据纯属虚构")
    pie_1.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
              is_label_show=True, radius=[30, 55], rosetype='radius')
    
    pie_2 = Pie("2013 年销量比例", "数据纯属虚构")
    pie_2.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
              is_label_show=True, radius=[30, 55], rosetype='radius')
    
    pie_3 = Pie("2014 年销量比例", "数据纯属虚构")
    pie_3.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
              is_label_show=True, radius=[30, 55], rosetype='radius')
    
    pie_4 = Pie("2015 年销量比例", "数据纯属虚构")
    pie_4.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
              is_label_show=True, radius=[30, 55], rosetype='radius')
    
    pie_5 = Pie("2016 年销量比例", "数据纯属虚构")
    pie_5.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
              is_label_show=True, radius=[30, 55], rosetype='radius')
    
    timeline = Timeline(is_auto_play=True, timeline_bottom=0)
    timeline.add(pie_1, '2012 年')
    timeline.add(pie_2, '2013 年')
    timeline.add(pie_3, '2014 年')
    timeline.add(pie_4, '2015 年')
    timeline.add(pie_5, '2016 年')
    timeline

![70 8][]

这几个图是一起画的所以这里只导入了一次，另外，这些图片是静态的，实际的生成的图片是动态的。

[70]: /images/20220511/d174049d7ffe4156a42bbf692083a2c7.png
[70 1]: /images/20220511/1aa54f9d155d4f7381df1832db7e9179.png
[70 2]: /images/20220511/78e3f6e708e948548670540780eb968b.png
[70 3]: /images/20220511/23b8cd7596ab4643b7c3b571b67d8d99.png
[70 4]: /images/20220511/8dcdcc2e198b4c39883dbf23419064f3.png
[70 5]: /images/20220511/9061abb2f32344f89bd687201dabad7b.png
[70 6]: /images/20220511/d439a4ced0ab4b8bb74d0c0eb9d46011.png
[70 7]: /images/20220511/40e08ce7329446d8be449175381c61a5.png
[70 8]: /images/20220511/f1e3e1b6a25041759faec4134a84b161.png