目录

PyEcharts 简介

Bar图

Line图

Pie图

Scatter图 

 Boxplot图

 heatmap图

 Kline图

funne图

WordCloud图

 Radar图

Map图

 组合图

Timeline图

PyEcharts 简介

Echarts 是一个由百度开源的数据可视化，凭借着良好的交互性，精巧的图表设计，得到了众 多开发者的认可。而 Python 是一门富有表达力的语言，很适合用于数据处理。当数据分析遇 上数据可视化时，pyecharts 诞生了。

特性

• 简洁的 API 设计，使用如丝滑般流畅，支持链式调用

• 囊括了 30+ 种常见图表，应有尽有

• 支持主流 Notebook 环境，Jupyter Notebook 和 JupyterLab

• 可轻松集成至 Flask，Django 等主流 Web 框架

• 高度灵活的配置项，可轻松搭配出精美的图表

• 详细的文档和示例，帮助开发者更快的上手项目

• 多达 400+ 地图文件以及原生的百度地图，为地理数据可视化提供强有力的支持

Bar图


from pyecharts.charts import Bar
from pyecharts.faker import Faker
from pyecharts import options as opts bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis(&＃39;销售团队A&＃39;,Faker.values())
bar.add_yaxis(&＃39;销售团队B&＃39;,Faker.values())
bar.set_series_opts(markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_=&＃39;max&＃39;,name=&＃39;最大值&＃39;)]
))
bar.render_notebook()


from pyecharts.charts import Bar
from pyecharts.faker import Faker
from pyecharts import options as opts bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis(&＃39;销售团队A&＃39;,Faker.values())
bar.add_yaxis(&＃39;销售团队B&＃39;,Faker.values())
bar.reversal_axis()
bar.set_series_opts(label_opts=opts.LabelOpts(position="right"))
bar.set_global_opts(title_opts=opts.TitleOpts(title="XY翻转"))
bar.render_notebook()

from pyecharts.charts import Bar
from pyecharts.faker import Faker
from pyecharts import options as opts bar = Bar()
bar.add_xaxis(Faker.choose())
bar.add_yaxis(&＃39;销售团队A&＃39;,Faker.values(),stack=&＃39;stack&＃39;)
bar.add_yaxis(&＃39;销售团队B&＃39;,Faker.values(),stack=&＃39;stack&＃39;)
bar.set_global_opts(title_opts=opts.TitleOpts(title="堆叠图"))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.render_notebook()

Line图

from pyecharts.charts import Line
from pyecharts import options as opts
from pyecharts.faker import Fakerline = Line()line.add_xaxis(xaxis_data=Faker.choose())
line.add_yaxis(&＃39;商家A&＃39;,y_axis=Faker.values())
line.add_yaxis(&＃39;商家B&＃39;,y_axis=Faker.values())line.set_global_opts(xaxis_opts=opts.AxisOpts(splitline_opts = opts.SplitLineOpts(is_show=True)))
line.render_notebook()

from pyecharts.charts import Line
from pyecharts import options as opts
from pyecharts.faker import Fakerline = Line()line.add_xaxis(xaxis_data=Faker.choose())
line.add_yaxis(&＃39;商家A&＃39;,y_axis=Faker.values(),is_smooth = True)
line.add_yaxis(&＃39;商家B&＃39;,y_axis=Faker.values(),is_smooth = True)line.set_global_opts(xaxis_opts=opts.AxisOpts(splitline_opts = opts.SplitLineOpts(is_show=True)))
line.render_notebook()

from pyecharts.charts import Line
from pyecharts import options as opts
from pyecharts.faker import Fakerline = Line()
x_values = Faker.choose()
line.add_xaxis(x_values)
line.add_yaxis(series_name=x_values[0],y_axis=Faker.values(),stack="总量",label_opts= opts.LabelOpts(is_show=False),areastyle_opts = opts.AreaStyleOpts(opacity=0.5))
line.add_yaxis(series_name=x_values[1],y_axis=Faker.values(),stack="总量",label_opts= opts.LabelOpts(is_show=False),areastyle_opts = opts.AreaStyleOpts(opacity=0.5))
line.add_yaxis(series_name=x_values[2],y_axis=Faker.values(),stack="总量",label_opts= opts.LabelOpts(is_show=False),areastyle_opts = opts.AreaStyleOpts(opacity=0.5))
line.add_yaxis(
series_name=x_values[3],
y_axis=Faker.values(),
stack="总量",label_opts= opts.LabelOpts(is_show=False),areastyle_opts = opts.AreaStyleOpts(opacity=0.5))
line.add_yaxis(series_name=x_values[4],y_axis=Faker.values(),stack="总量",label_opts= opts.LabelOpts(is_show=False),areastyle_opts = opts.AreaStyleOpts(opacity=0.5))
line.set_global_opts(xaxis_opts=opts.AxisOpts(boundary_gap=False))
line.render_notebook()

Pie图

from pyecharts.charts import Pie
from pyecharts import options as opts
from pyecharts.faker import Fakerpie = Pie()
pie.add(&＃39;&＃39;,[list(z) for z in zip(Faker.choose(),Faker.values())])
pie.set_global_opts(title_opts=opts.TitleOpts(title="Pie的基本图表"))
pie.render_notebook()

from pyecharts.charts import Pie
from pyecharts import options as opts
from pyecharts.faker import Fakerpie = Pie()
pie.add(&＃39;&＃39;,[list(z) for z in zip(Faker.choose(),Faker.values())],radius=[&＃39;50%&＃39;,&＃39;70%&＃39;])
pie.set_global_opts(title_opts=opts.TitleOpts(title="Pie的基本图表"))
pie.render_notebook()

pie = Pie()
pie.add(&＃39;&＃39;,[list(z) for z in zip(Faker.choose(),Faker.values())],rosetype=&＃39;radius&＃39;)
pie.set_global_opts(title_opts=opts.TitleOpts(title="Pie的基本图表"))
pie.render_notebook()

Scatter图 

from pyecharts.charts import Scatter
from pyecharts import options as opts
from random import random,randintx = [randint(0,100) for i in range(100)]
y = [randint(0,100) for i in range(100)]sca = Scatter()
sca.add_xaxis(xaxis_data=x)
sca.add_yaxis(&＃39;&＃39;,y_axis=y,label_opts=opts.LabelOpts(is_show=False),symbol_size=10,symbol=&＃39;rect&＃39;)
sca.set_global_opts(xaxis_opts=opts.AxisOpts(type_=&＃39;value&＃39;))
sca.render_notebook()

from pyecharts.charts import Scatter
from pyecharts import options as opts
from random import random,randintx = [randint(0,100) for i in range(10)]
y = [randint(0,100) for i in range(10)]sca = Scatter()
sca.add_xaxis(xaxis_data=x)
sca.add_yaxis(&＃39;&＃39;,y_axis=y,label_opts=opts.LabelOpts(is_show=True))
sca.set_global_opts(xaxis_opts=opts.AxisOpts(type_=&＃39;value&＃39;)
,visualmap_opts=opts.VisualMapOpts(type_=&＃39;size&＃39;))
sca.render_notebook()

 Boxplot图

from pyecharts.charts import Boxplot
from pyecharts import options as opts
from random import randintbox = Boxplot()
box.add_xaxis([f&＃39;{i}月&＃39; for i in range(1,5)])
box.add_yaxis(&＃39;A&＃39;,box.prepare_data([[randint(50,80) for i in range(50)],[randint(70,100) for i in range(50)],[randint(50,90) for i in range(50)],[randint(50,120) for i in range(50)],]))
box.set_global_opts(title_opts=opts.TitleOpts(title=&＃39;箱图的基本案例&＃39;))
box.render_notebook()

 heatmap图

from pyecharts.charts import HeatMap
from pyecharts import options as opts
from pyecharts.faker import Faker
from random import randintfrom pyecharts.types import VisualMap
value = [[i,j, randint(0,40)] for i in range(24) for j in range(7)]hm = HeatMap()
hm.add_xaxis(Faker.clock)
hm.add_yaxis(&＃39;&＃39;,Faker.week,value,label_opts=opts.LabelOpts(is_show=True,position=&＃39;inside&＃39;))
hm.set_global_opts(title_opts=opts.TitleOpts(title=&＃39;热力图&＃39;),
visualmap_opts= opts.VisualMapOpts()
)
hm.render_notebook()

 Kline图

from pyecharts import options as opts
from pyecharts.charts import Klinedata = [[2320.26, 2320.26, 2287.3, 2362.94],[2300, 2291.3, 2288.26, 2308.38],[2295.35, 2346.5, 2295.35, 2345.92],[2347.22, 2358.98, 2337.35, 2363.8],[2360.75, 2382.48, 2347.89, 2383.76],[2383.43, 2385.42, 2371.23, 2391.82],[2377.41, 2419.02, 2369.57, 2421.15],[2425.92, 2428.15, 2417.58, 2440.38],[2411, 2433.13, 2403.3, 2437.42],[2432.68, 2334.48, 2427.7, 2441.73],[2430.69, 2418.53, 2394.22, 2433.89],[2416.62, 2432.4, 2414.4, 2443.03],[2441.91, 2421.56, 2418.43, 2444.8],[2420.26, 2382.91, 2373.53, 2427.07],[2383.49, 2397.18, 2370.61, 2397.94],[2378.82, 2325.95, 2309.17, 2378.82],[2322.94, 2314.16, 2308.76, 2330.88],[2320.62, 2325.82, 2315.01, 2338.78],[2313.74, 2293.34, 2289.89, 2340.71],[2297.77, 2313.22, 2292.03, 2324.63],[2322.32, 2365.59, 2308.92, 2366.16],[2364.54, 2359.51, 2330.86, 2369.65],[2332.08, 2273.4, 2259.25, 2333.54],[2274.81, 2326.31, 2270.1, 2328.14],[2333.61, 2347.18, 2321.6, 2351.44],[2340.44, 2324.29, 2304.27, 2352.02],[2326.42, 2318.61, 2314.59, 2333.67],[2314.68, 2310.59, 2296.58, 2320.96],[2309.16, 2286.6, 2264.83, 2333.29],[2282.17, 2263.97, 2253.25, 2286.33],[2255.77, 2270.28, 2253.31, 2276.22],
]kline = Kline()
kline.add_xaxis([f&＃39;2030/10/{i+1}&＃39; for i in range(len(data))])
kline.add_yaxis(&＃39;&＃39;,data,
itemstyle_opts=opts.ItemStyleOpts(color=&＃39;red&＃39;,color0=&＃39;green&＃39;)
)
kline.set_global_opts(title_opts=opts.TitleOpts(title=&＃39;Kline的基本图&＃39;))
kline.render_notebook()

funne图

from pyecharts.charts import Funnel
from pyecharts.faker import Faker
from pyecharts import options as optsfunnel = Funnel()
funnel.add(&＃39;&＃39;,[list(z) for z in zip(Faker.choose(),Faker.values())])
funnel.set_global_opts(title_opts=opts.TitleOpts(title=&＃39;漏斗图&＃39;))
funnel.render_notebook()

WordCloud图

from pyecharts.charts import WordCloud
from pyecharts import options as optswc = WordCloud()
data = [[&＃39;ThinkPad&＃39;,&＃39;15.7&＃39;],[&＃39;联想&＃39;,&＃39;14.5&＃39;],[&＃39;惠普&＃39;,&＃39;14.4&＃39;],[&＃39;华为&＃39;,&＃39;11.7&＃39;],[&＃39;华硕&＃39;,&＃39;8.2&＃39;],[&＃39;戴尔&＃39;,&＃39;8.1&＃39;],[&＃39;Acer宏碁&＃39;,&＃39;4.5&＃39;],[&＃39;苹果&＃39;,&＃39;3.5&＃39;],[&＃39;神舟&＃39;,&＃39;3.2&＃39;],[&＃39;ROG&＃39;,&＃39;3.1&＃39;],[&＃39;机械革命&＃39;,&＃39;2.4&＃39;],[&＃39;msi微星&＃39;,&＃39;1.8&＃39;],[&＃39;外星人&＃39;,&＃39;1.5&＃39;],[&＃39;微软&＃39;,&＃39;1.4&＃39;],[&＃39;荣耀&＃39;,&＃39;1.2&＃39;],[&＃39;雷神&＃39;,&＃39;1&＃39;],[&＃39;三星&＃39;,&＃39;0.7&＃39;],[&＃39;红米&＃39;,&＃39;0.6&＃39;],[&＃39;机械师&＃39;,&＃39;0.5&＃39;],[&＃39;小米&＃39;,&＃39;0.5&＃39;],[&＃39;炫龙&＃39;,&＃39;0.4&＃39;],[&＃39;雷蛇&＃39;,&＃39;0.2&＃39;],[&＃39;壹号本&＃39;,&＃39;0.1&＃39;],[&＃39;a豆&＃39;,&＃39;0.1&＃39;],[&＃39;未来人类&＃39;,&＃39;0.1&＃39;],[&＃39;技嘉&＃39;,&＃39;0.1&＃39;],[&＃39;中柏&＃39;,&＃39;0.1&＃39;],[&＃39;VAIO&＃39;,&＃39;0.1&＃39;],[&＃39;火影&＃39;,&＃39;0.1&＃39;],[&＃39;LG&＃39;,&＃39;0.1&＃39;],[&＃39;松下&＃39;,&＃39;0&＃39;],[&＃39;麦本本&＃39;,&＃39;0&＃39;],[&＃39;吾空&＃39;,&＃39;0&＃39;],[&＃39;长城&＃39;,&＃39;0&＃39;],[&＃39;GPD&＃39;,&＃39;0&＃39;],[&＃39;清华同方&＃39;,&＃39;0&＃39;],[&＃39;神基&＃39;,&＃39;0&＃39;],[&＃39;爱尔轩&＃39;,&＃39;0&＃39;],[&＃39;酷比魔方&＃39;,&＃39;0&＃39;],[&＃39;海尔&＃39;,&＃39;0&＃39;],[&＃39;谷歌&＃39;,&＃39;0&＃39;],[&＃39;台电&＃39;,&＃39;0&＃39;],[&＃39;iru&＃39;,&＃39;0&＃39;],[&＃39;攀升IPASON&＃39;,&＃39;0&＃39;],[&＃39;NEC&＃39;,&＃39;0&＃39;],[&＃39;夏普&＃39;,&＃39;0&＃39;],[&＃39;京东京造&＃39;,&＃39;0&＃39;],[&＃39;锡恩帝&＃39;,&＃39;0&＃39;],[&＃39;皓勤&＃39;,&＃39;0&＃39;],[&＃39;Intel&＃39;,&＃39;0&＃39;],
]
wc.add(&＃39;&＃39;,data)
wc.set_global_opts(title_opts=opts.TitleOpts(&＃39;词云图&＃39;))
wc.render_notebook()

 Radar图

from pyecharts.charts import Radar
from pyecharts import options as optsradar = Radar()data1 = [[8,7,8,8,9,7]]
data2 = [[9,5,7,8,6,7]]radar.add_schema(schema=[opts.RadarIndicatorItem(name=&＃39;拍照&＃39;,max_=10),opts.RadarIndicatorItem(name=&＃39;外观&＃39;,max_=10),opts.RadarIndicatorItem(name=&＃39;性能&＃39;,max_=10),opts.RadarIndicatorItem(name=&＃39;屏幕&＃39;,max_=10),opts.RadarIndicatorItem(name=&＃39;内存&＃39;,max_=10),opts.RadarIndicatorItem(name=&＃39;系统&＃39;,max_=10)]
)
radar.add(&＃39;OPPO&＃39;,data1)
radar.add(&＃39;华为&＃39;,data2)
radar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
radar.set_global_opts(title_opts=opts.TitleOpts(&＃39;雷达图&＃39;))
radar.render_notebook()

Map图

from pyecharts.charts import Map
from pyecharts import options as optsmap = Map()
map.add(&＃39;&＃39;,[[&＃39;河北&＃39;,10],[&＃39;四川&＃39;,20]],is_map_symbol_show=False)
map.set_global_opts(title_opts=opts.TitleOpts(&＃39;地图&＃39;),visualmap_opts=opts.VisualMapOpts()
)
map.render_notebook()

from pyecharts.charts import Map
from pyecharts import options as optsmap = Map()
map.add(&＃39;&＃39;,
[[&＃39;西安市&＃39;,10],[&＃39;安康市&＃39;,20]],
maptype=&＃39;陕西&＃39;,
is_map_symbol_show=False,
label_opts=opts.LabelOpts(is_show=True))
map.set_global_opts(title_opts=opts.TitleOpts(&＃39;陕西省&＃39;),visualmap_opts=opts.VisualMapOpts()
)
map.render_notebook()

 组合图


from pyecharts.charts import Bar,Line
from pyecharts import options as optsx = [&＃39;1月&＃39;, &＃39;2月&＃39;, &＃39;3月&＃39;, &＃39;4月&＃39;, &＃39;5月&＃39;, &＃39;6月&＃39;, &＃39;7月&＃39;, &＃39;8月&＃39;, &＃39;9月&＃39;, &＃39;10月&＃39;, &＃39;11月&＃39;, &＃39;12月&＃39;]
bar =Bar()
bar.add_xaxis(x)
bar.add_yaxis(&＃39;蒸发量&＃39;,
[2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3],
label_opts=opts.LabelOpts(is_show=False))
bar.add_yaxis(&＃39;降水量&＃39;,
[2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3],
label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(title_opts=opts.TitleOpts(&＃39;混合图&＃39;),tooltip_opts=opts.TooltipOpts(is_show=True,trigger=&＃39;axis&＃39;,axis_pointer_type=&＃39;cross&＃39;),xaxis_opts= opts.AxisOpts(type_=&＃39;category&＃39;,axispointer_opts=opts.AxisPointerOpts(is_show=True,type_=&＃39;shadow&＃39;)))bar.extend_axis(yaxis=opts.AxisOpts(name=&＃39;温度&＃39;,min_=0,max_= 25,interval = 5,axislabel_opts = opts.LabelOpts(formatter=&＃39;{value} °C&＃39;)
))line = Line()
line.add_xaxis(x)
line.add_yaxis(&＃39;平均温度&＃39;,
[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=1,
label_opts=opts.LabelOpts(is_show=False)
)bar.overlap(line) # 合并图
bar.render_notebook()

Timeline图

from pyecharts.charts import Bar,Timeline
from pyecharts import options as opts
from pyecharts.faker import Fakerx = Faker.choose()
tl = Timeline()
for i in range(2000,2006):bar = Bar()bar.add_xaxis(x)bar.add_yaxis(&＃39;A&＃39;,Faker.values())bar.add_yaxis(&＃39;B&＃39;,Faker.values())bar.set_global_opts(title_opts=opts.TitleOpts(f&＃39;{i}年的数据表&＃39;))tl.add(bar,f&＃39;{i}年&＃39;)
tl.render_notebook()