Pyecharts手把手教你做动态可视化---收藏好喽！！！

案例一：

from pyecharts.charts import Bar
from pyecharts import options as opts

# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]
# 1.x版本支持链式调用
bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('电商渠道', data1)
       .add_yaxis('门店', data2)
       .set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副标题"))
      )

bar.render_notebook()

案例二：

from pyecharts.charts import Pie
from pyecharts import options as opts

# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data = [153, 124, 107, 99, 89, 46]
pie = (Pie()
       .add('', [list(z) for z in zip(cate, data)],
            radius=["30%", "75%"],
            rosetype="radius")
       .set_global_opts(title_opts=opts.TitleOpts(title="Pie-基本示例", subtitle="我是副标题"))
       .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {d}%"))
      )

pie.render_notebook()

案例三：

from pyecharts.charts import Line
from pyecharts import options as opts

# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]
"""
折线图示例:
1. is_smooth 折线 OR 平滑
2. markline_opts 标记线 OR 标记点
"""
line = (Line()
       .add_xaxis(cate)
       .add_yaxis('电商渠道', data1, 
                  markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]))
       .add_yaxis('门店', data2, 
                  is_smooth=True, 
                  markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(name="自定义标记点", 
                                                                             coord=[cate[2], data2[2]], value=data2[2])]))
       .set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例", subtitle="我是副标题"))
      )

line.render_notebook()

案例四：

from pyecharts.charts import Funnel
from pyecharts import options as opts

# 示例数据
cate = ['访问', '注册', '加入购物车', '提交订单', '付款成功']
data = [30398, 15230, 10045, 8109, 5698]
"""
漏斗图示例：
1. sort_控制排序，默认降序；
2. 标签显示位置
"""
funnel = (Funnel()
          .add("用户数", [list(z) for z in zip(cate, data)], 
               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"))
         )

funnel.render_notebook()

案例五：热力图

from pyecharts.charts import HeatMap
from pyecharts import options as opts
from pyecharts.faker import Faker
import random

# 示例数据
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heat = (HeatMap()
        .add_xaxis(Faker.clock)
        .add_yaxis("访客数", 
                   Faker.week, 
                   data,
                   label_opts=opts.LabelOpts(is_show=True, position="inside"))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="HeatMap-基本示例", subtitle="我是副标题"),
            visualmap_opts=opts.VisualMapOpts(),
            legend_opts=opts.LegendOpts(is_show=False))
       )

heat.render_notebook()

案例六：日历图

from pyecharts.charts import Calendar
from pyecharts import options as opts
import random
import datetime

# 示例数据
begin = datetime.date(2019, 1, 1)
end = datetime.date(2019, 12, 31)
data = [[str(begin + datetime.timedelta(days=i)), random.randint(1000, 25000)]
        for i in range((end - begin).days + 1)]
"""
日历图示例：
"""
calendar = (
        Calendar()
        .add("微信步数", data, calendar_opts=opts.CalendarOpts(range_="2019"))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="Calendar-基本示例", subtitle="我是副标题"),
            legend_opts=opts.LegendOpts(is_show=False),
            visualmap_opts=opts.VisualMapOpts(
                max_=25000,
                min_=1000,
                orient="horizontal",
                is_piecewise=True,
                pos_top="230px",
                pos_left="100px",
            )
        )
    )

calendar.render_notebook()

案例七：地理图

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="Map-基本示例"),
            legend_opts=opts.LegendOpts(is_show=False),
            visualmap_opts=opts.VisualMapOpts(max_=200, is_piecewise=True),
        )
    )

_map.render_notebook()

案例八：地理热点图

from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType
import random

province = ['武汉', '十堰', '鄂州', '宜昌', '荆州', '孝感', '黄石', '咸宁', '仙桃']
data = [(i, random.randint(50, 150)) for i in province]
geo = (Geo().
        add_schema(maptype="湖北")
        .add("门店数", data,type_=ChartType.HEATMAP)
        .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        .set_global_opts(
            visualmap_opts=opts.VisualMapOpts(),
            legend_opts=opts.LegendOpts(is_show=False),
            title_opts=opts.TitleOpts(title="Geo-湖北热力地图"))
      )

geo.render_notebook()

案例九：3D散点图

from pyecharts import options as opts
from pyecharts.charts import Scatter3D
from pyecharts.faker import Faker
import random


data = [(random.randint(0, 100), random.randint(0, 100), random.randint(0, 100))
        for _ in range(80)]
scatter3D = (Scatter3D()
             .add("", data)
             .set_global_opts(
                 title_opts=opts.TitleOpts("Scatter3D-基本示例"),
                 visualmap_opts=opts.VisualMapOpts(range_color=Faker.visual_color))
            )

scatter3D.render_notebook()

案例十：

from pyecharts.charts import Bar
from pyecharts import options as opts

# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]
bar = (Bar()
       .add_xaxis(cate)
       .add_yaxis('电商渠道', data1)
       .add_yaxis('门店', data2)
       .set_global_opts(title_opts=opts.TitleOpts(title="XY轴翻转-基本示例", subtitle="我是副标题"))
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
       .reversal_axis()
      )

bar.render_notebook()

案例十一：

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType

# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]
"""
主题设置：
默认white
"""
bar = (Bar(init_opts=opts.InitOpts(theme=ThemeType.ROMANTIC))
       .add_xaxis(cate)
       .add_yaxis('电商渠道', data1)
       .add_yaxis('门店', data2)
       .set_series_opts(label_opts=opts.LabelOpts(is_show=False),
                        markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max", name="最大值"),]))
       .set_global_opts(title_opts=opts.TitleOpts(title="Theme-ROMANTIC"))
      )

bar.render_notebook()

案例十二：

from pyecharts import options as opts
from pyecharts.charts import Bar, Timeline
from pyecharts.globals import ThemeType

# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
tl = Timeline()
for i in range(2015, 2020):
    bar = (
        Bar()
        .add_xaxis(cate)
        .add_yaxis("线上", [random.randint(50, 150) for _ in cate])
        .add_yaxis("门店", [random.randint(100, 200) for _ in cate])
        .set_global_opts(title_opts=opts.TitleOpts("手机品牌{}年营业额".format(i)))
    )
    tl.add(bar, "{}年".format(i))

tl.render_notebook()

本文来自公众号：邯郸路220号子彬院 ，作者少年吉