利用Pyecharts绘制15个超实用精美图表~

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· 2021-10-21

什么是pyecharts？pyecharts是Python与ECharts的结合，Python是我们所熟知的语言，而ECharts是百度开源的数据可视化图表设计，这两者的有效结合，使得图表可视化更加绚丽多彩。

本文使用Python语言，借助pyecharts库，绘制常用的柱形图、折线图、饼图、散点图等，使用pyecharts库的交互功能实现动态可视化功能，对于里面的代码都可以修改进行复用，下面一起学习。

条形图

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Faker
c = (    Bar()    .add_xaxis(Faker.choose())    .add_yaxis("商家A", Faker.values())    .add_yaxis("商家B", Faker.values())    .set_global_opts(title_opts=opts.TitleOpts(title="Bar-MarkLine（自定义）"))    .set_series_opts(        label_opts=opts.LabelOpts(is_show=False),        markline_opts=opts.MarkLineOpts(            data=[opts.MarkLineItem(y=50, name="yAxis=50")]        ),    ))c.render_notebook()

水平条形图动图

from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.commons.utils import JsCodefrom pyecharts.faker import Faker
c = (        Bar()        .add_xaxis(Faker.days_attrs)        .add_yaxis("商家A", Faker.days_values,itemstyle_opts=opts.ItemStyleOpts(color="#d14a61"))        .set_global_opts(            title_opts=opts.TitleOpts(title="Bar-DataZoom（slider-水平）"),            datazoom_opts=[opts.DataZoomOpts()],        )    )c.render_notebook()

折线图

from pyecharts.charts import Linefrom 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]
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()

面积图

import pyecharts.options as optsfrom pyecharts.charts import Linefrom pyecharts.faker import Faker
c = (    Line()    .add_xaxis(Faker.choose())    .add_yaxis("商家A", Faker.values(), areastyle_opts=opts.AreaStyleOpts(opacity=0.5))    .add_yaxis("商家B", Faker.values(), areastyle_opts=opts.AreaStyleOpts(opacity=0.5))    .set_global_opts(title_opts=opts.TitleOpts(title="Line-面积图")))c.render_notebook()

饼图

from pyecharts.charts import Piefrom 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()

玫瑰图

from pyecharts import options as optsfrom pyecharts.charts import Piefrom pyecharts.faker import Faker
v = Faker.choose()c = (    Pie()    .add(        "",        [list(z) for z in zip(v, Faker.values())],        radius=["30%", "75%"],        center=["25%", "50%"],        rosetype="radius",        label_opts=opts.LabelOpts(is_show=False),    )    .add(        "",        [list(z) for z in zip(v, Faker.values())],        radius=["30%", "75%"],        center=["75%", "50%"],        rosetype="area",    )    .set_global_opts(title_opts=opts.TitleOpts(title="Pie-玫瑰图示例")))c.render_notebook()

漏斗图

import pyecharts.options as optsfrom pyecharts.charts import Funnel
x_data = ["展现", "点击", "访问", "咨询", "订单"]y_data = [100, 80, 60, 40, 20]
data = [[x_data[i], y_data[i]] for i in range(len(x_data))]
(    Funnel()    .add(        series_name="",        sort_='ascending',        data_pair=data,        gap=2,        tooltip_opts=opts.TooltipOpts(trigger="item", formatter="{a} 
{b} : {c}%"),        label_opts=opts.LabelOpts(is_show=True, position="inside"),        itemstyle_opts=opts.ItemStyleOpts(border_color="#fff", border_width=1),    )    .set_global_opts(title_opts=opts.TitleOpts(title="漏斗图", subtitle="纯属虚构"))).render_notebook()

热力图

from pyecharts.charts import HeatMapfrom pyecharts import options as optsfrom pyecharts.faker import Fakerimport random
# 示例数据data = [[i, j, random.randint(0, 100)] 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()

散点图

from pyecharts import options as optsfrom pyecharts.charts import Scatterfrom pyecharts.faker import Faker
c = (    Scatter()    .add_xaxis(Faker.choose())    .add_yaxis("商家A", Faker.values())    .add_yaxis("商家B", Faker.values())    .set_global_opts(        title_opts=opts.TitleOpts(title="Scatter-VisualMap(Size)"),        visualmap_opts=opts.VisualMapOpts(type_="size", max_=150, min_=20),    ))c.render_notebook()

三维散点图

from pyecharts import options as optsfrom pyecharts.charts import Scatter3Dimport random

data = [[random.randint(0, 150), random.randint(0, 100), random.randint(0, 100)]        for _ in range(1000)]
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()

箱线图

from pyecharts import options as optsfrom pyecharts.charts import Boxplot
v1 = [    [850, 740, 900, 1070, 930, 850, 950, 980, 980, 880, 1000, 980],    [960, 940, 960, 940, 880, 800, 850, 880, 900, 840, 830, 790],]v2 = [    [890, 810, 810, 820, 800, 770, 760, 740, 750, 760, 910, 920],    [890, 840, 780, 810, 760, 810, 790, 810, 820, 850, 870, 870],]c = Boxplot()c.add_xaxis(["expr1", "expr2"])c.add_yaxis("A", c.prepare_data(v1))c.add_yaxis("B", c.prepare_data(v2))c.set_global_opts(title_opts=opts.TitleOpts(title="BoxPlot-基本示例"))c.render_notebook()

地图

from pyecharts import options as optsfrom pyecharts.charts import Mapimport 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()

区域热力图

from pyecharts import options as optsfrom pyecharts.charts import Geofrom pyecharts.globals import ChartTypeimport random
province = ['杭州', '宁波', '温州', '嘉兴', '丽水', '衢州', '绍兴', '台州', '湖州','金华','舟山']data = [(i, random.randint(50, 150)) for i in province]
geo = (Geo()        .add_schema(maptype="浙江")        .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-浙江热力地图"))      )
geo.render_notebook()

世界地图

from pyecharts.charts import Map  # 注意这里与老版本pyecharts调用的区别from pyecharts import options as optsimport randomcountry = ['China', 'Canada', 'France', 'Japan', 'Russia', 'USA']data_world = [(i, random.randint(100, 200)) for i in country]world = (    Map()    .add('', # 此处没取名，所以空着      data_world, # 数据      'world') # 地图类型    .set_global_opts(        title_opts=opts.TitleOpts(title='World Map'),        visualmap_opts=opts.VisualMapOpts(            max_=200,            min_=100,            is_piecewise=True)  # 定义图例为分段型，默认为连续的图例    )    .set_series_opts(label_opts=opts.LabelOpts(is_show=False)))world.render_notebook()

词云图

import pyecharts.options as optsfrom pyecharts.charts import WordCloud
data = [    ("生活资源", "999"),    ("供热管理", "888"),    ("供气质量", "777"),    ("生活用水管理", "688"),    ("一次供水问题", "588"),    ("交通运输", "516"),    ("城市交通", "515"),    ("环境保护", "683"),    ("房地产管理", "662"),    ("城乡建设", "649"),    ("社会保障与福利", "429"),    ("社会保障", "707"),    ("文体与教育管理", "506"),    ("公共安全", "506"),    ("公交运输管理", "586"),    ("出租车运营管理", "585"),]
(    WordCloud()    .add(series_name="热点分析", data_pair=data, word_size_range=[6, 66])    .set_global_opts(        title_opts=opts.TitleOpts(            title="热点分析", title_textstyle_opts=opts.TextStyleOpts(font_size=23)        ),        tooltip_opts=opts.TooltipOpts(is_show=True),    )).render_notebook()

组合图

from pyecharts import options as optsfrom pyecharts.charts import Bar,Line,Gridfrom pyecharts.commons.utils import JsCodefrom pyecharts.faker import Faker
x_data = ["{}月".format(i) for i in range(1, 13)]bar = (        Bar()        .add_xaxis(x_data)        .add_yaxis(            "蒸发量",            [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3],            yaxis_index=0,            color="#d14a61",        )        .add_yaxis(            "降水量",            [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3],            yaxis_index=1,            color="#5793f3",        )        .extend_axis(            yaxis=opts.AxisOpts(                name="蒸发量",                type_="value",                min_=0,                max_=250,                position="right",                axisline_opts=opts.AxisLineOpts(                    linestyle_opts=opts.LineStyleOpts(color="#d14a61")                ),                axislabel_opts=opts.LabelOpts(formatter="{value} ml"),            )        )        .extend_axis(            yaxis=opts.AxisOpts(                type_="value",                name="温度",                min_=0,                max_=25,                position="left",                axisline_opts=opts.AxisLineOpts(                    linestyle_opts=opts.LineStyleOpts(color="#675bba")                ),                axislabel_opts=opts.LabelOpts(formatter="{value} °C"),                splitline_opts=opts.SplitLineOpts(                    is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)                ),            )        )        .set_global_opts(            yaxis_opts=opts.AxisOpts(                name="降水量",                min_=0,                max_=250,                position="right",                offset=50,                axisline_opts=opts.AxisLineOpts(                    linestyle_opts=opts.LineStyleOpts(color="#5793f3")                ),                axislabel_opts=opts.LabelOpts(formatter="{value} ml"),            ),            title_opts=opts.TitleOpts(title="Grid-多 Y 轴示例"),            tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),        )    )
line = (        Line()        .add_xaxis(x_data)        .add_yaxis(            "平均温度",            [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],            yaxis_index=2,            color="#675bba",            label_opts=opts.LabelOpts(is_show=False),        )    )bar.overlap(line)bar.render_notebook()