1 快速開始

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 會生成本地 HTML 文件，默認會在當前目錄生成 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

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="主標題", subtitle="副標題"))
#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="主標題", subtitle="副標題"))
#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)務指標",[("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="{b}:{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="{b}:{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", max_=25000),
                ])
base_radar.add("預算分配",v1,color="#f9713c")
base_radar.add("實際開銷",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="雷達圖-基本示例"))
base_radar.render_notebook()

雷達圖

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-默認取消顯示某Series",subtitle="此處是副標題"))
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-指定類型標記點"))
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="自定義標記點",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-指定類型標記點"))
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([
                "名字很長的X軸標簽1",
                "名字很長的X軸標簽2",
                "名字很長的X軸標簽3",
                "名字很長的X軸標簽4",
                "名字很長的X軸標簽5",
                "名字很長的X軸標簽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軸標簽",subtitle="解決標簽過長問題"))
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="漣漪特效散點圖-基本示例"))
effect_scatter.render_notebook()

散點圖

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-標記點"))
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-標記點"))
line_base.render_notebook()

折線圖

2.2.5 散點圖

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="散點圖-基本示例"))
scatter.render_notebook()

散點圖

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="散點圖-VisualMap"),
                       visualmap_opts=opts.VisualMapOpts(max_=150))
scatter.render_notebook()

散點圖

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="散點圖-VisualMap"),
                       visualmap_opts=opts.VisualMapOpts(type_="size",max_=150,min_=20))
scatter.render_notebook()

散點圖

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()

選項卡多圖

2.4.4 Timeline：時間線輪播多圖

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{}年營業(yè)額".format(i)))
    tl.add(bar, "{}年".format(i))
tl.render_notebook()

時間線輪播多圖

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-我是主標題", subtitle="我是副標題支持換行哦"))
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="我是副標題支持換行哦"))
image.render()

主題風格

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

pyecharts官方文檔：https://pyecharts.org/
代碼全文點擊pyecharts_practice查看。

三个男躁一个女,国精产品一区一手机的秘密,麦子交换系列最经典十句话,欧美国产综合欧美视频

Pyecharts Practice

Pyecharts Practice

1 快速開始

1.1 繪制圖表

1.2 使用options配置項

1.3 渲染圖片

1.4 使用主題

2 圖表類型

2.1 基本圖表

2.1.1 漏斗圖

2.1.2 儀表盤

2.1.3 水球圖

2.1.4 餅圖

2.1.5 雷達圖

2.1.6 主題河流圖

2.1.7 詞云圖

2.2 直角坐標系圖表

2.2.1 柱狀圖/條形圖

2.2.2 箱型圖

2.2.3 漣漪特效散點圖

2.2.4 折線圖/面積圖

2.2.5 散點圖

2.3 地理圖表

2.4 組合圖表

2.4.1 Grid：并行多圖

2.4.2 Page：順序多圖

2.4.3 Tab：選項卡多圖

2.4.4 Timeline：時間線輪播多圖

2.5 HTML組件

2.5.1 表格

2.5.2 圖像

主題風格

三个男躁一个女,国精产品一区一手机的秘密,麦子交换系列最经典十句话,欧美 国产 综合 欧美 视频

Pyecharts Practice

1 快速開始

1.1 繪制圖表

1.2 使用options配置項

1.3 渲染圖片

1.4 使用主題

2 圖表類型

2.1 基本圖表

2.1.1 漏斗圖

2.1.2 儀表盤

2.1.3 水球圖

2.1.4 餅圖

2.1.5 雷達圖

2.1.6 主題河流圖

2.1.7 詞云圖

2.2 直角坐標系圖表

2.2.1 柱狀圖/條形圖

2.2.2 箱型圖

2.2.3 漣漪特效散點圖

2.2.4 折線圖/面積圖

2.2.5 散點圖

2.3 地理圖表

2.4 組合圖表

2.4.1 Grid：并行多圖

2.4.2 Page：順序多圖

2.4.3 Tab：選項卡多圖

2.4.4 Timeline：時間線輪播多圖

2.5 HTML組件

2.5.1 表格

2.5.2 圖像

主題風格

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