Pyecharts Practice

1 快速開(kāi)始

import pyecharts
# 查看pyecharts版本
print(pyecharts.__version__)

1.1 繪制圖表

from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(["襯衫", "羊毛衫", "雪紡衫", "褲子", "高跟鞋", "襪子"])
bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
# render 會(huì)生成本地 HTML 文件，默認(rèn)會(huì)在當(dāng)前目錄生成 render.html 文件
# 也可以傳入路徑參數(shù)，如 bar.render("mycharts.html")
# bar.render()用于在本地生成html文件
# bar,render_notebook()只在notebook里生成圖片
bar.render_notebook()
柱狀圖

1.2 使用options配置項(xiàng)

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

bar = Bar()
bar.add_xaxis(["襯衫", "羊毛衫", "雪紡衫", "褲子", "高跟鞋", "襪子"])
bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
bar.set_global_opts(title_opts=opts.TitleOpts(title="主標(biāo)題", subtitle="副標(biāo)題"))
#bar.render()
bar.render_notebook()
柱狀圖

1.3 渲染圖片

from pyecharts.charts import Bar
from pyecharts.render import make_snapshot

# 使用 snapshot-selenium 渲染圖片
from snapshot_selenium import snapshot

bar = Bar()
bar.add_xaxis(["襯衫", "羊毛衫", "雪紡衫", "褲子", "高跟鞋", "襪子"])
bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
# 將網(wǎng)頁(yè)保存成圖片存在本地
make_snapshot(snapshot, bar.render(), "bar.png")

1.4 使用主題

from pyecharts.charts import Bar
from pyecharts import options as opts
# 內(nèi)置主題類型可查看 pyecharts.globals.ThemeType
from pyecharts.globals import ThemeType

bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
bar.add_xaxis(["襯衫", "羊毛衫", "雪紡衫", "褲子", "高跟鞋", "襪子"])
bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
bar.add_yaxis("商家B", [15, 6, 45, 20, 35, 66])
bar.set_global_opts(title_opts=opts.TitleOpts(title="主標(biāo)題", subtitle="副標(biāo)題"))
#bar.render()
bar.render_notebook()
柱狀圖

2 圖表類型

2.1 基本圖表

2.1.1 漏斗圖

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Funnel, Page

funnel = Funnel()
funnel.add("商品", [list(z) for z in zip(Faker.choose(), Faker.values())])
funnel.set_global_opts(title_opts=opts.TitleOpts(title="漏斗圖-基本示例"))
funnel.render_notebook()
漏斗圖
# 標(biāo)簽內(nèi)置
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Funnel, Page

funnel = Funnel()
funnel.add("商品", [list(z) for z in zip(Faker.choose(), Faker.values())],label_opts=opts.LabelOpts(position="inside"))
funnel.set_global_opts(title_opts=opts.TitleOpts(title="漏斗圖(標(biāo)簽內(nèi)置)"))
funnel.render_notebook()
漏斗圖
# 倒置
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Funnel, Page

funnel = Funnel()
funnel.add("商品", [list(z) for z in zip(Faker.choose(), Faker.values())],sort_="ascending",label_opts=opts.LabelOpts(position="inside"))
funnel.set_global_opts(title_opts=opts.TitleOpts(title="漏斗圖(倒置)"))
funnel.render_notebook()
漏斗圖

2.1.2 儀表盤

from pyecharts import options as opts
from pyecharts.charts import Gauge, Page

base_gauge = Gauge()
base_gauge.add("", [("完成率", 66.6)])
base_gauge.render_notebook()
儀表盤
from pyecharts import options as opts
from pyecharts.charts import Gauge, Page

base_gauge = Gauge()
base_gauge.add("業(yè)務(wù)指標(biāo)",[("完成率", 55.5)],axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color=[(0.3, "#67e0e3"), (0.7, "#37a2da"), (1, "#fd666d")], width=30)))
base_gauge.set_global_opts(title_opts=opts.TitleOpts(title="Gauge-不同顏色"),legend_opts=opts.LegendOpts(is_show=False))
base_gauge.render_notebook()
儀表盤

2.1.3 水球圖

from pyecharts import options as opts
from pyecharts.charts import Liquid, Page

liquid_base = Liquid()
liquid_base.add('lq',[0.6,0.7])
liquid_base.set_global_opts(title_opts=opts.TitleOpts(title="水球圖-基本示例"))
liquid_base.render_notebook()
水球圖

2.1.4 餅圖

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

base_pie = Pie()
base_pie.add("", [list(z) for z in zip(Faker.choose(), Faker.values())])
base_pie.set_global_opts(title_opts=opts.TitleOpts(title="餅圖-基本示例"))
base_pie.set_series_opts(label_opts=opts.LabelOpts(formatter=":{c}"))
base_pie.render_notebook()
餅圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Pie

base_pie = Pie()
base_pie.add("", [list(z) for z in zip(Faker.choose(), Faker.values())],radius=["40%","75"])
base_pie.set_global_opts(title_opts=opts.TitleOpts(title="餅圖-圓環(huán)圖")
                         ,legend_opts=opts.LegendOpts(orient="vertical", pos_top="15%", pos_left="2%"))
base_pie.set_series_opts(label_opts=opts.LabelOpts(formatter=":{c}"))
base_pie.render_notebook()
圓環(huán)圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Pie

rose_pie = Pie()
rose_pie.add(
            "",
            [list(z) for z in zip(Faker.choose(), Faker.values())],
            radius=["30%", "75%"],
            center=["25%", "50%"],
            rosetype="radius",
            label_opts=opts.LabelOpts(is_show=False),
        )
rose_pie.render_notebook()
玫瑰圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Pie

rose_pie = Pie()
rose_pie.add(
            "",
            [list(z) for z in zip(Faker.choose(), Faker.values())],
            radius=["30%", "75%"],
            center=["25%", "50%"],
            rosetype="area",
        )
rose_pie.set_global_opts(title_opts=opts.TitleOpts(title="玫瑰圖示例"))
rose_pie.render_notebook()
玫瑰圖

2.1.5 雷達(dá)圖

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

v1 = [[4300, 10000, 28000, 35000, 50000, 19000]]
v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]
base_radar = Radar()
base_radar.add_schema(schema=[
                opts.RadarIndicatorItem(name="銷售", max_=6500),
                opts.RadarIndicatorItem(name="管理", max_=16000),
                opts.RadarIndicatorItem(name="信息技術(shù)", max_=30000),
                opts.RadarIndicatorItem(name="客服", max_=38000),
                opts.RadarIndicatorItem(name="研發(fā)", max_=52000),
                opts.RadarIndicatorItem(name="市場(chǎng)", max_=25000),
                ])
base_radar.add("預(yù)算分配",v1,color="#f9713c")
base_radar.add("實(shí)際開(kāi)銷",v2,color="#b3e4a1")
base_radar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
base_radar.set_global_opts(title_opts=opts.TitleOpts(title="雷達(dá)圖-基本示例"))
base_radar.render_notebook()
雷達(dá)圖

2.1.6 主題河流圖

from pyecharts import options as opts
from pyecharts.charts import Page, ThemeRiver

data = [
        ["2015/11/08", 10, "DQ"],
        ["2015/11/09", 15, "DQ"],
        ["2015/11/10", 35, "DQ"],
        ["2015/11/14", 7, "DQ"],
        ["2015/11/15", 2, "DQ"],
        ["2015/11/16", 17, "DQ"],
        ["2015/11/17", 33, "DQ"],
        ["2015/11/18", 40, "DQ"],
        ["2015/11/19", 32, "DQ"],
        ["2015/11/20", 26, "DQ"],
        ["2015/11/08", 35, "TY"],
        ["2015/11/09", 36, "TY"],
        ["2015/11/10", 37, "TY"],
        ["2015/11/11", 22, "TY"],
        ["2015/11/12", 24, "TY"],
        ["2015/11/13", 26, "TY"],
        ["2015/11/14", 34, "TY"],
        ["2015/11/15", 21, "TY"],
        ["2015/11/16", 18, "TY"],
        ["2015/11/17", 45, "TY"],
        ["2015/11/18", 32, "TY"],
        ["2015/11/19", 35, "TY"],
        ["2015/11/20", 30, "TY"],
        ["2015/11/08", 21, "SS"],
        ["2015/11/09", 25, "SS"],
        ["2015/11/10", 27, "SS"],
        ["2015/11/11", 23, "SS"],
        ["2015/11/12", 24, "SS"],
        ["2015/11/13", 21, "SS"],
        ["2015/11/14", 35, "SS"],
        ["2015/11/15", 39, "SS"],
        ["2015/11/16", 40, "SS"],
        ["2015/11/17", 36, "SS"],
        ["2015/11/18", 33, "SS"],
        ["2015/11/19", 43, "SS"],
        ["2015/11/20", 40, "SS"],
        ["2015/11/14", 7, "QG"],
        ["2015/11/15", 2, "QG"],
        ["2015/11/16", 17, "QG"],
        ["2015/11/17", 33, "QG"],
        ["2015/11/18", 40, "QG"],
        ["2015/11/19", 32, "QG"],
        ["2015/11/20", 26, "QG"],
        ["2015/11/21", 35, "QG"],
        ["2015/11/22", 40, "QG"],
        ["2015/11/23", 32, "QG"],
        ["2015/11/24", 26, "QG"],
        ["2015/11/25", 22, "QG"],
        ["2015/11/08", 10, "SY"],
        ["2015/11/09", 15, "SY"],
        ["2015/11/10", 35, "SY"],
        ["2015/11/11", 38, "SY"],
        ["2015/11/12", 22, "SY"],
        ["2015/11/13", 16, "SY"],
        ["2015/11/14", 7, "SY"],
        ["2015/11/15", 2, "SY"],
        ["2015/11/16", 17, "SY"],
        ["2015/11/17", 33, "SY"],
        ["2015/11/18", 40, "SY"],
        ["2015/11/19", 32, "SY"],
        ["2015/11/20", 26, "SY"],
        ["2015/11/21", 35, "SY"],
        ["2015/11/22", 4, "SY"],
        ["2015/11/23", 32, "SY"],
        ["2015/11/24", 26, "SY"],
        ["2015/11/25", 22, "SY"],
        ["2015/11/08", 10, "DD"],
        ["2015/11/09", 15, "DD"],
        ["2015/11/10", 35, "DD"],
        ["2015/11/11", 38, "DD"],
        ["2015/11/12", 22, "DD"],
        ["2015/11/13", 16, "DD"],
        ["2015/11/14", 7, "DD"],
        ["2015/11/15", 2, "DD"],
        ["2015/11/16", 17, "DD"],
        ["2015/11/17", 33, "DD"],
        ["2015/11/18", 4, "DD"],
        ["2015/11/19", 32, "DD"],
        ["2015/11/20", 26, "DD"],
    ]
theme_river = ThemeRiver()
theme_river.add(["DQ", "TY", "SS", "QG", "SY", "DD"],data,
            singleaxis_opts=opts.SingleAxisOpts(type_="time", pos_bottom="10%"))
theme_river.set_global_opts(title_opts=opts.TitleOpts(title="主題河流圖-基本示例"))
theme_river.render_notebook()
主題河流圖

2.1.7 詞云圖

from pyecharts import options as opts
from pyecharts.charts import Page, WordCloud
from pyecharts.globals import SymbolType


words = [
    ("Sam S Club", 10000),
    ("Macys", 6181),
    ("Amy Schumer", 4386),
    ("Jurassic World", 4055),
    ("Charter Communications", 2467),
    ("Chick Fil A", 2244),
    ("Planet Fitness", 1868),
    ("Pitch Perfect", 1484),
    ("Express", 1112),
    ("Home", 865),
    ("Johnny Depp", 847),
    ("Lena Dunham", 582),
    ("Lewis Hamilton", 555),
    ("KXAN", 550),
    ("Mary Ellen Mark", 462),
    ("Farrah Abraham", 366),
    ("Rita Ora", 360),
    ("Serena Williams", 282),
    ("NCAA baseball tournament", 273),
    ("Point Break", 265),
]
base_wordcloud = WordCloud()
base_wordcloud.add("", words, word_size_range=[20, 100])
base_wordcloud.set_global_opts(title_opts=opts.TitleOpts(title="詞云圖-基本示例"))
base_wordcloud.render_notebook()
詞云圖
from pyecharts import options as opts
from pyecharts.charts import Page, WordCloud
from pyecharts.globals import SymbolType


words = [
    ("Sam S Club", 10000),
    ("Macys", 6181),
    ("Amy Schumer", 4386),
    ("Jurassic World", 4055),
    ("Charter Communications", 2467),
    ("Chick Fil A", 2244),
    ("Planet Fitness", 1868),
    ("Pitch Perfect", 1484),
    ("Express", 1112),
    ("Home", 865),
    ("Johnny Depp", 847),
    ("Lena Dunham", 582),
    ("Lewis Hamilton", 555),
    ("KXAN", 550),
    ("Mary Ellen Mark", 462),
    ("Farrah Abraham", 366),
    ("Rita Ora", 360),
    ("Serena Williams", 282),
    ("NCAA baseball tournament", 273),
    ("Point Break", 265),
]
base_wordcloud = WordCloud()
base_wordcloud.add("", words, word_size_range=[20, 100],shape=SymbolType.DIAMOND)
base_wordcloud.set_global_opts(title_opts=opts.TitleOpts(title="詞云圖-基本示例"))
base_wordcloud.render_notebook()
鉆石型詞云圖

2.2 直角坐標(biāo)系圖表

2.2.1 柱狀圖/條形圖

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

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-基本示例",subtitle="此處是副標(biāo)題"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values(),is_selected=False)
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-默認(rèn)取消顯示某Series",subtitle="此處是副標(biāo)題"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-顯示ToolBox",subtitle="此處是副標(biāo)題"),
                   toolbox_opts=opts.ToolboxOpts(),
                   legend_opts=opts.LegendOpts(is_show=False))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values(),category_gap="40%")
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-單系列柱間距離"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-Y 軸 formatter"),
                   yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}/月")))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-XY軸名稱"),
                   xaxis_opts=opts.AxisOpts(name="此處是X軸"),
                   yaxis_opts=opts.AxisOpts(name="此處是Y軸"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.reversal_axis()
bar.set_series_opts(label_opts=opts.LabelOpts(position="right"))
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-翻轉(zhuǎn)XY軸"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values(),stack="stack1")
bar.add_yaxis("商家B",Faker.values(),stack="stack1")
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(title_opts=opts.TitleOpts(title="堆疊柱狀圖"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values(),stack="stack1")
bar.add_yaxis("商家B",Faker.values(),stack="stack1")
bar.add_yaxis("商家C",Faker.values())
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(title_opts=opts.TitleOpts(title="(部分系列)堆疊柱狀圖"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
                   markpoint_opts=opts.MarkPointOpts(
                   data=[
                       opts.MarkPointItem(type_="max",name="最大值"),
                       opts.MarkPointItem(type_="min",name="最小值")
                   ]))
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-指定類型標(biāo)記點(diǎn)"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
x,y = Faker.choose(),Faker.values()
bar.add_xaxis(x)
bar.add_yaxis("商家A",y,markpoint_opts=opts.MarkPointOpts(
                   data=[
                       opts.MarkPointItem(name="自定義標(biāo)記點(diǎn)",coord=[x[2],y[2]],value=y[2])
                   ]))
bar.add_yaxis("商家B",Faker.values())
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-指定類型標(biāo)記點(diǎn)"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
                   markline_opts=opts.MarkLineOpts(
                   data=[
                       opts.MarkLineItem(type_="max",name="最大值"),
                       opts.MarkLineItem(type_="min",name="最小值")
                   ]))
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-指定類型標(biāo)記線"))
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.days_attrs)
bar.add_yaxis("商家A",Faker.days_values)
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-水平數(shù)據(jù)縮放"),
                   datazoom_opts=opts.DataZoomOpts())
bar.render_notebook()
柱狀圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis(Faker.days_attrs)
bar.add_yaxis("商家A",Faker.days_values)
bar.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-水平數(shù)據(jù)縮放"),
                   datazoom_opts=opts.DataZoomOpts(orient="vertical"))
bar.render_notebook()
柱狀圖
from pyecharts import options as opts
from pyecharts.charts import Bar

bar = Bar()
bar.add_xaxis([
                "名字很長(zhǎng)的X軸標(biāo)簽1",
                "名字很長(zhǎng)的X軸標(biāo)簽2",
                "名字很長(zhǎng)的X軸標(biāo)簽3",
                "名字很長(zhǎng)的X軸標(biāo)簽4",
                "名字很長(zhǎng)的X軸標(biāo)簽5",
                "名字很長(zhǎng)的X軸標(biāo)簽6",
            ])
bar.add_yaxis("商家A", [10, 20, 30, 40, 50, 40])
bar.add_yaxis("商家B", [20, 10, 40, 30, 40, 50])
bar.set_global_opts(xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
                   title_opts=opts.TitleOpts(title="柱狀圖-旋轉(zhuǎn)x軸標(biāo)簽",subtitle="解決標(biāo)簽過(guò)長(zhǎng)問(wèn)題"))
bar.render_notebook()
柱狀圖

2.2.2 箱型圖

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

v1 = [
        [850, 740, 900, 1070, 930, 850, 950, 980, 980, 880]
        + [1000, 980, 930, 650, 760, 810, 1000, 1000, 960, 960],
        [960, 940, 960, 940, 880, 800, 850, 880, 900]
        + [840, 830, 790, 810, 880, 880, 830, 800, 790, 760, 800],
    ]
v2 = [
        [890, 810, 810, 820, 800, 770, 760, 740, 750, 760]
        + [910, 920, 890, 860, 880, 720, 840, 850, 850, 780],
        [890, 840, 780, 810, 760, 810, 790, 810, 820, 850, 870]
        + [870, 810, 740, 810, 940, 950, 800, 810, 870],
    ]

box_plot = Boxplot()
box_plot.add_xaxis(["expr1", "expr2"])
box_plot.add_yaxis("A", box_plot.prepare_data(v1))
box_plot.add_yaxis("B", box_plot.prepare_data(v2))
box_plot.set_global_opts(title_opts=opts.TitleOpts(title="箱型圖-基本示例"))
box_plot.render_notebook()
箱型圖

2.2.3 漣漪特效散點(diǎn)圖

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import EffectScatter
from pyecharts.globals import SymbolType

effect_scatter = EffectScatter()
effect_scatter.add_xaxis(Faker.choose())
effect_scatter.add_yaxis("",Faker.values())
effect_scatter.set_global_opts(title_opts=opts.TitleOpts(title="漣漪特效散點(diǎn)圖-基本示例"))
effect_scatter.render_notebook()
散點(diǎn)圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import EffectScatter
from pyecharts.globals import SymbolType

effect_scatter = EffectScatter()
effect_scatter.add_xaxis(Faker.choose())
effect_scatter.add_yaxis("",Faker.values())
effect_scatter.set_global_opts(title_opts=opts.TitleOpts(title="漣漪特效散點(diǎn)圖-顯示網(wǎng)格線"),
                              xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(is_show=True)),
                              yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(is_show=True)))
effect_scatter.render_notebook()
散點(diǎn)圖

2.2.4 折線圖/面積圖

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

line_base = Line()
line_base.add_xaxis(Faker.choose())
line_base.add_yaxis("商家A",Faker.values())
line_base.add_yaxis("商家B",Faker.values())
line_base.set_global_opts(title_opts=opts.TitleOpts(title="折線圖-基本示例"))
line_base.render_notebook()
折線圖
import pyecharts.options as opts
from pyecharts.faker import  Faker
from pyecharts.charts import Line

line = Line()
y =Faker.values()
y[3],y[6]=None,None
line.add_xaxis(Faker.choose())
line.add_yaxis("商家A",y,is_connect_nones=True)
line.set_global_opts(title_opts=opts.TitleOpts(title="折線圖-連接空值"))
line.render_notebook()
折線圖
import pyecharts.options as opts
from pyecharts.faker import  Faker
from pyecharts.charts import Line

line_base = Line()
line_base.add_xaxis(Faker.choose())
line_base.add_yaxis("商家A",Faker.values(),is_smooth=True)
line_base.add_yaxis("商家B",Faker.values(),is_smooth=True)
line_base.set_global_opts(title_opts=opts.TitleOpts(title="折線圖-平滑曲線"))
line_base.render_notebook()
折線圖
import pyecharts.options as opts
from pyecharts.faker import  Faker
from pyecharts.charts import Line

line_base = Line()
line_base.add_xaxis(Faker.choose())
line_base.add_yaxis("商家A",Faker.values(),areastyle_opts=opts.AreaStyleOpts(opacity=0.5))
line_base.add_yaxis("商家B",Faker.values(),areastyle_opts=opts.AreaStyleOpts(opacity=0.5))
line_base.set_global_opts(title_opts=opts.TitleOpts(title="折線圖-m面積圖"))
line_base.render_notebook()
面積圖
import pyecharts.options as opts
from pyecharts.faker import  Faker
from pyecharts.charts import Line

line_base = Line()
line_base.add_xaxis(Faker.choose())
line_base.add_yaxis("商家A",Faker.values(),markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="min")]))
line_base.add_yaxis("商家B",Faker.values(),markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max")]))
line_base.set_global_opts(title_opts=opts.TitleOpts(title="折線圖-標(biāo)記點(diǎn)"))
line_base.render_notebook()
折線圖
import pyecharts.options as opts
from pyecharts.faker import  Faker
from pyecharts.charts import Line

line_base = Line()
line_base.add_xaxis(Faker.choose())
line_base.add_yaxis("商家A",Faker.values(),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]))
line_base.add_yaxis("商家B",Faker.values(),)
line_base.set_global_opts(title_opts=opts.TitleOpts(title="折線圖-標(biāo)記點(diǎn)"))
line_base.render_notebook()
折線圖

2.2.5 散點(diǎn)圖

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Scatter

scatter = Scatter()
scatter.add_xaxis(Faker.choose())
scatter.add_yaxis("商家A",Faker.values())
scatter.set_global_opts(title_opts=opts.TitleOpts(title="散點(diǎn)圖-基本示例"))
scatter.render_notebook()
散點(diǎn)圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Scatter

scatter = Scatter()
scatter.add_xaxis(Faker.choose())
scatter.add_yaxis("商家A",Faker.values())
scatter.set_global_opts(title_opts=opts.TitleOpts(title="散點(diǎn)圖-顯示網(wǎng)格線"),
                       xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(is_show=True)),
                       yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(is_show=True)))
scatter.render_notebook()
散點(diǎn)圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Scatter

scatter = Scatter()
scatter.add_xaxis(Faker.choose())
scatter.add_yaxis("商家A",Faker.values())
scatter.set_global_opts(title_opts=opts.TitleOpts(title="散點(diǎn)圖-VisualMap"),
                       visualmap_opts=opts.VisualMapOpts(max_=150))
scatter.render_notebook()
散點(diǎn)圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Scatter

scatter = Scatter()
scatter.add_xaxis(Faker.choose())
scatter.add_yaxis("商家A",Faker.values())
scatter.add_yaxis("商家B",Faker.values())
scatter.set_global_opts(title_opts=opts.TitleOpts(title="散點(diǎn)圖-VisualMap"),
                       visualmap_opts=opts.VisualMapOpts(type_="size",max_=150,min_=20))
scatter.render_notebook()
散點(diǎn)圖

2.3 地理圖表

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType

geo_base = Geo()
geo_base.add_schema(maptype="china")
geo_base.add("geo",[list(z) for z in zip(Faker.provinces,Faker.values())])
geo_base.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo_base.set_global_opts(title_opts=opts.TitleOpts(title="地理圖表-基本示例"),
                        visualmap_opts=opts.VisualMapOpts())
geo_base.render_notebook()
地理圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType

geo_base = Geo()
geo_base.add_schema(maptype="china")
geo_base.add("geo",[list(z) for z in zip(Faker.provinces,Faker.values())])
geo_base.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo_base.set_global_opts(title_opts=opts.TitleOpts(title="地理圖表-Visual(分段型)"),
                        visualmap_opts=opts.VisualMapOpts(is_piecewise=True))
geo_base.render_notebook()
地理圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType

geo_base = Geo()
geo_base.add_schema(maptype="china")
geo_base.add("geo",[list(z) for z in zip(Faker.provinces,Faker.values())],type_=ChartType.EFFECT_SCATTER)
geo_base.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo_base.set_global_opts(title_opts=opts.TitleOpts(title="地理圖表-漣漪特效圖"))
geo_base.render_notebook()
地理圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType

geo_base = Geo()
geo_base.add_schema(maptype="china")
geo_base.add("geo",[list(z) for z in zip(Faker.provinces,Faker.values())],type_=ChartType.HEATMAP)
geo_base.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo_base.set_global_opts(title_opts=opts.TitleOpts(title="地理圖表-基本示例"),
                        visualmap_opts=opts.VisualMapOpts())
geo_base.render_notebook()
地理圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType

geo_base = Geo()
geo_base.add_schema(maptype="廣東")
geo_base.add("geo",[list(z) for z in zip(Faker.guangdong_city,Faker.values())],type_=ChartType.HEATMAP)
geo_base.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo_base.set_global_opts(title_opts=opts.TitleOpts(title="地理圖表-廣東地圖"),
                        visualmap_opts=opts.VisualMapOpts())
geo_base.render_notebook()
地理圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType

geo_line = Geo()
geo_line.add_schema(maptype="china")
geo_line.add("",[("廣州", 55), ("北京", 66), ("杭州", 77), ("重慶", 88)],
            type_=ChartType.EFFECT_SCATTER,color="green")
geo_line.add( "geo",[("廣州", "上海"), ("廣州", "北京"), ("廣州", "杭州"), ("廣州", "重慶")],
            type_=ChartType.LINES,
            effect_opts=opts.EffectOpts(symbol=SymbolType.ARROW, symbol_size=6, color="blue"),
            linestyle_opts=opts.LineStyleOpts(curve=0.2))
geo_line.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo_line.set_global_opts(title_opts=opts.TitleOpts(title="地理圖表-指示線"))
geo_line.render_notebook()
地理圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType

geo_line = Geo()
geo_line.add_schema(maptype="china",itemstyle_opts=opts.ItemStyleOpts(color="#323c48", border_color="#111"))
geo_line.add("",[("廣州", 55), ("北京", 66), ("杭州", 77), ("重慶", 88)],
            type_=ChartType.EFFECT_SCATTER,color="white")
geo_line.add( "geo",[("廣州", "上海"), ("廣州", "北京"), ("廣州", "杭州"), ("廣州", "重慶")],
            type_=ChartType.LINES,
            effect_opts=opts.EffectOpts(symbol=SymbolType.ARROW, symbol_size=6, color="blue"),
            linestyle_opts=opts.LineStyleOpts(curve=0.2))
geo_line.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo_line.set_global_opts(title_opts=opts.TitleOpts(title="地理圖表-指示線-背景"))
geo_line.render_notebook()
地理圖

2.4 組合圖表

2.4.1 Grid：并行多圖

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar, Grid, Line,Scatter

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_global_opts(title_opts=opts.TitleOpts(title="Grid_柱狀圖"))

line = Line()
line.add_xaxis(Faker.choose())
line.add_yaxis("商家A",Faker.values())
line.add_yaxis("商家B",Faker.values())
line.set_global_opts(title_opts=opts.TitleOpts(title="Grid_折線圖",pos_top="48%"),
                    legend_opts=opts.LegendOpts(pos_top="48%"))

grid = Grid()
grid.add(bar,grid_opts=opts.GridOpts(pos_bottom="60%"))
grid.add(line,grid_opts=opts.GridOpts(pos_top="60%"))
grid.render_notebook()
并行多圖
from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar, Grid, Line,Scatter

scatter = Scatter()
scatter.add_xaxis(Faker.choose())
scatter.add_yaxis("商家A",Faker.values())
scatter.add_yaxis("商家B",Faker.values())
scatter.set_global_opts(title_opts=opts.TitleOpts(title="Grid_散點(diǎn)圖"),
                       legend_opts=opts.LegendOpts(pos_left="20%"))

line = Line()
line.add_xaxis(Faker.choose())
line.add_yaxis("商家A",Faker.values())
line.add_yaxis("商家B",Faker.values())
line.set_global_opts(title_opts=opts.TitleOpts(title="Grid_折線圖",pos_right="5%"),
                    legend_opts=opts.LegendOpts(pos_right="20%"))

grid = Grid()
grid.add(scatter,grid_opts=opts.GridOpts(pos_left="55%"))
grid.add(line,grid_opts=opts.GridOpts(pos_right="55%"))
grid.render_notebook()
并行多圖

2.4.2 Page：順序多圖

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar, Line, Page

bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis("商家A",Faker.values())
bar.add_yaxis("商家B",Faker.values())
bar.set_global_opts(title_opts=opts.TitleOpts(title="Page-柱狀圖"))

line = Line()
line.add_xaxis(Faker.choose())
line.add_yaxis("商家A",Faker.values())
line.add_yaxis("商家B",Faker.values())
line.set_global_opts(title_opts=opts.TitleOpts(title="Page-折線圖"))

page = Page()
page.add(bar,line)
page.render_notebook()
順序多圖

2.4.3 Tab：選項(xiàng)卡多圖

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar, Tab, Pie, Line
from pyecharts.components import Table

bar = Bar()
bar.add_xaxis(Faker.days_attrs)
bar.add_yaxis("商家A", Faker.days_values)
bar.set_global_opts(title_opts=opts.TitleOpts(title="Bar-DataZoom（slider-水平）"),
            datazoom_opts=[opts.DataZoomOpts()])

line = Line()
line.add_xaxis(Faker.choose())
line.add_yaxis("商家A",Faker.values(),markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="min")]))
line.add_yaxis("商家B",Faker.values(),markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max")]))
line.set_global_opts(title_opts=opts.TitleOpts(title="Line-MarkPoint"))

v = Faker.choose()
pie = Pie()
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),
        )
pie.add("",
        [list(z) for z in zip(v, Faker.values())],
        radius=["30%", "75%"],
        center=["75%", "50%"],
        rosetype="area",
        )
pie.set_global_opts(title_opts=opts.TitleOpts(title="Pie-玫瑰圖示例"))

table = Table()
headers = ["City name", "Area", "Population", "Annual Rainfall"]
rows = [
        ["Brisbane", 5905, 1857594, 1146.4],
        ["Adelaide", 1295, 1158259, 600.5],
        ["Darwin", 112, 120900, 1714.7],
        ["Hobart", 1357, 205556, 619.5],
        ["Sydney", 2058, 4336374, 1214.8],
        ["Melbourne", 1566, 3806092, 646.9],
        ["Perth", 5386, 1554769, 869.4],
    ]
table.add(headers, rows).set_global_opts(title_opts=opts.ComponentTitleOpts(title="Table"))

tab = Tab()
tab.add(bar, "柱狀圖")
tab.add(line, "折線圖")
tab.add(pie, "玫瑰圖")
tab.add(table, "表格")
tab.render_notebook()
選項(xiàng)卡多圖

2.4.4 Timeline：時(shí)間線輪播多圖

from pyecharts.faker import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar, Page, Pie, Timeline

x = Faker.choose()
tl = Timeline()
for i in range(2015, 2020):
    bar = Bar()
    bar.add_xaxis(x)
    bar.add_yaxis("商家A", Faker.values())
    bar.add_yaxis("商家B", Faker.values())
    bar.set_global_opts(title_opts=opts.TitleOpts("某商店{}年?duì)I業(yè)額".format(i)))
    tl.add(bar, "{}年".format(i))
tl.render_notebook()
時(shí)間線輪播多圖

2.5 HTML組件

2.5.1 表格

from pyecharts.components import Table
from pyecharts.options import ComponentTitleOpts

table = Table()
headers = ["City name", "Area", "Population", "Annual Rainfall"]
rows = [
    ["Brisbane", 5905, 1857594, 1146.4],
    ["Adelaide", 1295, 1158259, 600.5],
    ["Darwin", 112, 120900, 1714.7],
    ["Hobart", 1357, 205556, 619.5],
    ["Sydney", 2058, 4336374, 1214.8],
    ["Melbourne", 1566, 3806092, 646.9],
    ["Perth", 5386, 1554769, 869.4],
]
table.add(headers, rows)
table.set_global_opts(title_opts=ComponentTitleOpts(title="Table-我是主標(biāo)題", subtitle="我是副標(biāo)題支持換行哦"))
table.render()
表格

2.5.2 圖像

from pyecharts.components import Image
from pyecharts.options import ComponentTitleOpts

image = Image()
img_src = "https://user-images.githubusercontent.com/19553554/39612358-499eb2ae-4f91-11e8-8f56-179c4f0bf2df.png"
image.add(src=img_src,
    style_opts={"width": "200px", "height": "200px", "style": "margin-top: 20px"},)
image.set_global_opts(
    title_opts=ComponentTitleOpts(title="Image-基本示例", subtitle="我是副標(biāo)題支持換行哦"))
image.render()

主題風(fēng)格

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

def theme_bar(theme_name):
    bar = Bar(init_opts=opts.InitOpts(theme=theme_name))
    bar.add_xaxis(Faker.choose())
    bar.add_yaxis("商家A",Faker.values())
    bar.add_yaxis("商家B",Faker.values())
    bar.add_yaxis("商家C",Faker.values())
    bar.add_yaxis("商家D",Faker.values())
    bar.set_global_opts(title_opts=opts.TitleOpts(title=theme_name))
    return bar.render_notebook()

# 默認(rèn)主題WHITE
theme_bar(theme_name=ThemeType.WHITE)
white
# LIGHT
theme_bar(theme_name=ThemeType.LIGHT)
light
# DARK
theme_bar(theme_name=ThemeType.DARK)
dark
# CHALK
theme_bar(theme_name=ThemeType.CHALK)
chalk
# ESSOS
theme_bar(theme_name=ThemeType.ESSOS)
essos
# INFOGRAPHIC
theme_bar(theme_name=ThemeType.INFOGRAPHIC)
infographic
# MACARONS
theme_bar(theme_name=ThemeType.MACARONS)
macarons
# PURPLE_PASSION
theme_bar(theme_name=ThemeType.PURPLE_PASSION)
pupple_passion
# ROMA
theme_bar(theme_name=ThemeType.ROMA)
roma
# ROMANTIC
theme_bar(theme_name=ThemeType.ROMANTIC)
romantic
# SHINE
theme_bar(theme_name=ThemeType.SHINE)
shine
# VINTAGE
theme_bar(theme_name=ThemeType.VINTAGE)
vintage
# WALDEN
theme_bar(theme_name=ThemeType.WALDEN)
walden
# WESTEROS
theme_bar(theme_name=ThemeType.WESTEROS)
westeros
# WONDERLAND
theme_bar(theme_name=ThemeType.WONDERLAND)
wonderland
最后編輯于 ：
?著作權(quán)歸作者所有,轉(zhuǎn)載或內(nèi)容合作請(qǐng)聯(lián)系作者
【社區(qū)內(nèi)容提示】社區(qū)部分內(nèi)容疑似由AI輔助生成，瀏覽時(shí)請(qǐng)結(jié)合常識(shí)與多方信息審慎甄別。
平臺(tái)聲明：文章內(nèi)容（如有圖片或視頻亦包括在內(nèi)）由作者上傳并發(fā)布，文章內(nèi)容僅代表作者本人觀點(diǎn)，簡(jiǎn)書(shū)系信息發(fā)布平臺(tái)，僅提供信息存儲(chǔ)服務(wù)。

友情鏈接更多精彩內(nèi)容