Pyecharts可视化

echarts想必大家都不陌生，一个非常优秀的可视化工具；今天要记录和介绍的是python的一款工具包，pyecharts，能够在python文件中实现可视化哦~

1、包导入

from pyecharts.charts import *
from pyecharts.components import Table
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
import random
import datetime
from pyecharts.globals import CurrentConfig

CurrentConfig.ONLINE_HOST = "https://cdn.kesci.com/lib/pyecharts_assets/"

2、条形图

# 虚假数据
x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
y_data = [123, 153, 89, 107, 98, 23]


bar = (Bar()
       .add_xaxis(x_data)
       .add_yaxis('数量', y_data)
       .set_global_opts(title_opts=opts.TitleOpts(title="第一个条形图"),
                       legend_opts=opts.LegendOpts(type_="scroll",orient="verticle"))
      )

bar.render_notebook()

3、折线图

# 虚假数据
x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
y_data = [123, 153, 89, 107, 98, 23]

line = (Line()
       .add_xaxis(x_data)
       .add_yaxis('', y_data)
      )

line.render_notebook()

 4、箱形图

# 虚假数据
x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
y_data = [[random.randint(100, 200) for i in range(10)] for item in x_data]

Box = Boxplot()
Box.add_xaxis(x_data)
Box.add_yaxis("", Box.prepare_data(y_data))
Box.render_notebook()

5、散点图

# 虚假数据
x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
y_data = [123, 153, 89, 107, 98, 23]

scatter = (Scatter()
           .add_xaxis(x_data)
           .add_yaxis('', y_data)
           )

scatter.render_notebook()

 6、热力图

# 虚假数据
data = [[i, j, random.randint(0, 100)] for i in range(24) for j in range(7)]
hour_list = [str(i) for i in range(24)]
week_list = ['周日', '周一', '周二', '周三', '周四', '周五', '周六']

heat = (HeatMap()
        .add_xaxis(hour_list)
        .add_yaxis("", week_list, data)
        )

heat.render_notebook()

 

7、层叠图

# 虚假数据
x_data = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
y_data_bar = [123, 153, 89, 107, 98, 23]
y_data_line = [153, 107, 23, 89, 123, 107]


bar = (Bar()
       .add_xaxis(x_data)
       .add_yaxis('', y_data_bar)
       )

line = (Line()
        .add_xaxis(x_data)
        .add_yaxis('', y_data_line)
        )

overlap = bar.overlap(line)
overlap.render_notebook()

8、饼图

# 虚假数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data = [123, 153, 89, 107, 98, 23]

pie = (Pie()
       .add('', [list(z) for z in zip(cate, data)])
       )

pie.render_notebook()

 

9、漏斗图

# 虚假数据
cate = ['访问', '注册', '加入购物车', '提交订单', '付款成功']
data = [30398, 15230, 10045, 3109, 1698]

funnel = (Funnel()
          .add("", [list(z) for z in zip(cate, data)])
          )

funnel.render_notebook()

 

10、地图

# 虚假数据
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]

geo = (
    Geo()
    .add_schema(maptype="china")
    .add("", data)
)
geo.render_notebook()

 

 11、水球图

liquid = (Liquid()
          .add("", [0.52, 0.44])
          )

liquid.render_notebook()

 12、雷达图

# 虚假数据
data = [
    [78, 91, 123, 78, 82, 67],
    [89, 101, 127, 88, 86, 75],
    [86, 93, 101, 84, 90, 73],
]


radar = (Radar()
         .add_schema(schema=[
             opts.RadarIndicatorItem(name="语文", max_=150),
             opts.RadarIndicatorItem(name="数学", max_=150),
             opts.RadarIndicatorItem(name="英语", max_=150),
             opts.RadarIndicatorItem(name="物理", max_=100),
             opts.RadarIndicatorItem(name="生物", max_=100),
             opts.RadarIndicatorItem(name="化学", max_=100),
         ]
)
    .add('', data)
)
radar.render_notebook()

13、加入样式图

from pyecharts.charts import Bar
from pyecharts.faker import Faker
bar = Bar()
bar.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
bar.add_yaxis("商家B", [15, 10, 33, 88, 45, 7])
bar.set_global_opts(title_opts=opts.TitleOpts("我的第一个图表"),
                   legend_opts=opts.LegendOpts(),
                   toolbox_opts=opts.ToolboxOpts(orient='verticle',pos_left='right',pos_top='middle',
                                                 feature=opts.ToolBoxFeatureOpts(save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(),
                                                                                restore=opts.ToolBoxFeatureRestoreOpts(),
                                                                                data_view=opts.ToolBoxFeatureDataViewOpts(),
                                                                                data_zoom=opts.ToolBoxFeatureDataZoomOpts(),
                                                                                magic_type=opts.ToolBoxFeatureMagicTypeOpts(),
                                                                                brush=opts.ToolBoxFeatureBrushOpts())),)
bar.render("toolbox.html")
bar.render_notebook()

 

 参考资源：【pyecharts教程】应该是全网最全的教程了～ - Heywhale.com