折线图

from pyecharts import options as opts
from pyecharts.charts import Line
c = (Line().add_xaxis(Faker.choose()).add_yaxis("商家1", Faker.values()).add_yaxis("商家2", Faker.values()).set_global_opts(title_opts=opts.TitleOpts(title="折线图-基本示例")).render("line_test.html")
)

柱状图

from pyecharts.charts import Bar
from pyecharts import options as opts
bar = Bar()
bar.add_xaxis(['毛衣','寸衫',"领带",'裤子',"风衣","高跟鞋","袜子"])
bar.add_yaxis('商家A',[114,55,27,101,125,27,105])
bar.add_yaxis('商家B',[57,134,101,22,69,90,129])
bar.set_global_opts(title_opts=opts.TitleOpts(title="某商场销售情况",subtitle='A和B公司'),toolbox_opts=opts.ToolboxOpts(is_show=True))
bar.set_series_opts(label_opts=opts.LabelOpts(position="top"))
bar.render_notebook()    # 在 notebook 中展示
# bar.render(r"D:\桌面\snapshot.html") 生成 html 文件

from pyecharts.charts import Bar
from pyecharts import options as opts
bar = Bar()
bar.add_xaxis(['毛衣','寸衫',"领带",'裤子',"风衣","高跟鞋","袜子"])
bar.add_yaxis('商家A',[114,55,27,101,125,27,105])
bar.add_yaxis('商家B',[57,134,101,22,69,90,129])
bar.set_global_opts(title_opts=opts.TitleOpts(title="某商场销售情况",subtitle='A和B公司'),toolbox_opts=opts.ToolboxOpts(is_show=True))
bar.set_series_opts(label_opts=opts.LabelOpts(position="right"))
bar.reversal_axis()
bar.render_notebook()

from pyecharts.charts import Bar
from pyecharts import options as opts
bar5=(Bar().add_xaxis(['键盘','耳机','鼠标','显示器']).add_yaxis("店铺一",Faker.values(),stack="K").add_yaxis("店铺二",Faker.values(),stack="K").add_yaxis("店铺三",Faker.values(),stack="C").add_yaxis("店铺四",Faker.values(),stack="C").add_yaxis("店铺五",Faker.values(),stack="L").add_yaxis("店铺六",Faker.values(),stack="L").add_yaxis("店铺七",Faker.values(),stack="L").reversal_axis()#水平颠倒 若启用工具盒，可能出现堆叠超出数据的情况
)
bar5.render_notebook()

饼图

普通饼图

from pyecharts.charts import Pie
from pyecharts import options as opts
L1 = ["教授","副教授","讲师","助教","其他"]
num = [20,30,10,12,8]
c = Pie()
c.add("",[list(z) for z in zip(L1,num)])
c.set_global_opts(title_opts = opts.TitleOpts(title="Pie-职称比例"),toolbox_opts = opts.ToolboxOpts(is_show=True))
c.set_series_opts(label_opts = opts.LabelOpts(formatter="{b}:{c}"))
c.render_notebook()

环形图

from pyecharts.charts import Pie
from pyecharts import options as opts
c = Pie()
L1 = ["教授","副教授","讲师","助教","其他"]
num = [20,30,10,12,8]
c.add("",[list(z) for z in zip(L1,num)],radius=["40%","75%"])
c.set_global_opts(title_opts=opts.TitleOpts(title='Pie圆环'),legend_opts=opts.LegendOpts(orient='vertical',pos_top='5%',pos_left="2%"))
c.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c}"))
c.render_notebook()

玫瑰图

from pyecharts.charts import Pie
from pyecharts import options as opts
c = Pie()
L1 = ["教授","副教授","讲师","助教","其他"]
num = [20,30,10,12,8]
c.add("",[list(z) for z in zip(L1,num)],radius=["40%","75%"],rosetype="area")
c.set_global_opts(title_opts = opts.TitleOpts(title="玫瑰图"),toolbox_opts = opts.ToolboxOpts(is_show=True),legend_opts=opts.LegendOpts(orient='vertical',pos_top="5%",pos_left="2%"))
c.set_series_opts(label_opts=opts.LabelOpts(formatter='{b}:{c}'))
c.render_notebook()

散点图

from pyecharts.charts import Scatter
from pyecharts import options as opts
s = Scatter()
week = ['Mon','Thur','Wed','Tues','Fri','Sar','Sun']
s.add_xaxis(week)
s.add_yaxis('商家A',[11,22,33,44,55,66,77])
s.add_yaxis('商家B',[0,10,20,30,40,50,60])
s.set_global_opts(title_opts=opts.TitleOpts(title='散点图'),toolbox_opts = opts.ToolboxOpts(is_show=True),legend_opts = opts.LegendOpts(orient='vertical',pos_top='5%',pos_left="2%"))
s.set_series_opts(label_opts=opts.LabelOpts(position='top'))
s.render_notebook()

桑基图

import pandas as pd
from pyecharts import options as opts
from pyecharts.charts import Sankeydf = pd.DataFrame({'性别':['男','男','男','女','女','女'],"熬夜原因":['打游戏','看剧','加班','打游戏','看剧','加班'],'人数':[40,20,40,8,25,36]})
display(df)
def transForm(df):nodes = []links = []for i in range(2):values = df.iloc[:,i].unique()for value in values:dic = {}dic['name']=valuenodes.append(dic)for i in df.values:dic = {}dic['source'] = i[0]dic['target'] = i[1]dic['value'] = i[2]links.append(dic)return nodes,linksnodes,links = transForm(df)
print(nodes)
print(links)
sankey = Sankey()
sankey.add("桑基图",nodes,links,linestyle_opt = opts.LineStyleOpts(opacity=0.2,curve=0.5,color="source"),label_opts = opts.LabelOpts(position='right'))
sankey.set_global_opts(title_opts=opts.TitleOpts(title='桑基图示例'))
sankey.render_notebook()

词云

from pyecharts import options as opts
from pyecharts.charts import Page,WordCloud
from pyecharts.globals import SymbolType
words = [("牛肉面",7800),("黄河",6181),("《读者》",4386),("水晶饺子",3055),("雨燕中学",4244),("碣石文化广场",2055),("玄武山",8067),("华工",1868),("十一孔",3483),("宋瘄寮",1122),("石洲",980),("红白",1111),("Beautyleg",3000),("Winnie",6666),("toxic_妲己",2222),("绯月樱",4444)
]
c = WordCloud()
c.add("",words,word_size_range=[10,70])
c.set_global_opts(title_opts=opts.TitleOpts(title="词云"))
c.render_notebook()

地图

from pyecharts import options as optsfrom
from pyecharts.charts import Map#数据截至 2020/2/29 22:14 现存确诊
data = [['湖北', 34617], ['广东', 366], ['山东', 332], ['浙江', 188], ['四川', 184],         ['湖南', 170], ['黑龙江', 166], ['重庆', 148],['北京', 132], ['江西', 123],        ['安徽', 116], ['江苏', 108], ['河南', 81], ['广西', 74], ['香港', 62],         ['福建', 53],['上海', 47], ['陕西', 37], ['贵州', 32], ['河北', 31],         ['台湾', 29], ['内蒙古', 26], ['辽宁', 25], ['天津', 24],['山西', 20],         ['吉林', 17], ['海南', 16], ['云南', 15], ['新疆', 11], ['甘肃', 7],         ['宁夏', 4], ['澳门', 2],        ['青海', 0], ['西藏', 0]]
map = (        Map()        .add("现存确诊", data, "china")        .set_global_opts(            title_opts=opts.TitleOpts(title="现存确诊疫情地图"),            visualmap_opts=opts.VisualMapOpts(max_=35000, is_piecewise=True,            pieces=[                {"min": 10000, "label": '>10000人', "color": "#6666CC"},                {"min": 1000, "max": 10000, "label": '1001-10000人', "color": "#9999FF"},                {"min": 500, "max": 999, "label": '999-1000人', "color": "#CCCCFF"},                {"min": 100, "max": 499, "label": '100-499人', "color": "#FF9999"},                {"min": 10, "max": 99, "label": '10-99人', "color": "#FFCCCC"},                {"min": 1, "max": 9, "label": '0-9人', "color": "#CCCCCC"},                {"min": 0, "max": 0, "label": '0人', "color": "#ffffff"},            ],),        )    )
map.render(r"C:\Users\ldw\Desktop\demo\snapshot10.html")

销售转化漏斗

from pyecharts import options as optsfrom
from pyecharts.charts import Funnel
from pyecharts.globals import ThemeType
labels = ['浏览人数', '加购人数', '购买人数']
data = [100, 50, 30]
funnel = (        Funnel(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))        .add("", [list(z) for z in zip(labels, data)],            label_opts=opts.LabelOpts(position="inside"))        .set_global_opts(title_opts=opts.TitleOpts(title="销售转化漏斗"))    )
funnel.render(r"C:\Users\ldw\Desktop\demo\snapshot11.html")

多维散点图

from pyecharts import options as opts
from pyecharts.charts import Scatter
from pyecharts.faker import Faker
from pyecharts.globals import ThemeType
from pyecharts.commons.utils import JsCode
Scatter = (        Scatter(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))        .add_xaxis(Faker.choose())        .add_yaxis(            "商家A",            [list(z) for z in zip(Faker.values(), Faker.choose())],            label_opts=opts.LabelOpts(                formatter=JsCode(                    "function(params){return params.value[1] +' : '+ params.value[2];}"                ),                #position="inside"            ),        )         .set_global_opts(            title_opts=opts.TitleOpts(title="Scatter-多维度数据"),            tooltip_opts=opts.TooltipOpts(                formatter=JsCode(                    "function (params) {return params.name + ' : ' + params.value[2];}"                )),            visualmap_opts=opts.VisualMapOpts(                type_="size", max_=150, min_=20, dimension=1            ),)    )
Scatter.render(r"C:\Users\ldw\Desktop\demo\snapshot12.html")

多饼图

from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.commons.utils import JsCode
fn = """    function(params) {        if(params.name == '其他')            return '\\n\\n\\n' + params.name + ' : ' + params.value + '%';        return params.name + ' : ' + params.value + '%';    }    """
def new_label_opts():        return opts.LabelOpts(formatter=JsCode(fn), position="center")
c = (Pie()        .add(            "",            [list(z) for z in zip(["剧情", "其他"], [25, 75])],            center=["20%", "30%"],            radius=[60, 80],            label_opts=new_label_opts(),        )        .add(            "",            [list(z) for z in zip(["奇幻", "其他"], [24, 76])],            center=["55%", "30%"],            radius=[60, 80],            label_opts=new_label_opts(),        )        .add(            "",            [list(z) for z in zip(["爱情", "其他"], [14, 86])],            center=["20%", "70%"],           radius=[60, 80],            label_opts=new_label_opts(),        )        .add(            "",            [list(z) for z in zip(["惊悚", "其他"], [11, 89])],            center=["55%", "70%"],            radius=[60, 80],            label_opts=new_label_opts(),        )        .set_global_opts(            title_opts=opts.TitleOpts(title="Pie-多饼图示例"),            legend_opts=opts.LegendOpts(                type_="scroll", pos_top="20%", pos_left="80%", orient="vertical"            ),        )    )
c.render(r"C:\Users\ldw\Desktop\demo\snapshot13.html")

K线图

from pyecharts import options as opts
from pyecharts.charts import Kline
c = (Kline(init_opts=opts.InitOpts(theme=ThemeType.ESSOS)).add_xaxis(["2020/7/{}".format(i + 1) for i in range(31)]).add_yaxis("kline", data).set_global_opts(yaxis_opts=opts.AxisOpts(is_scale=True),xaxis_opts=opts.AxisOpts(is_scale=True),title_opts=opts.TitleOpts(title="K线图-基本示例"),).render("kline_test.html")
)

漏斗图

from pyecharts.charts import Funnelc = (Funnel().add("类目", [list(z) for z in zip(Faker.choose(), Faker.values())]).set_global_opts(title_opts=opts.TitleOpts(title="漏斗图-基本示例")).render("funnel_test.html")
)

多图绘制

from pyecharts import options as opts
from pyecharts.charts import Bar,Line,Grid
A = ["小米","三星","华为","苹果","魅族","VIVO","OPPO"]
CA = [100,125,87,90,78,98,118]
B = ["草莓","芒果","葡萄","雪梨","西瓜","柠檬","车厘子"]
CB = [78,95,120,102,88,108,98]
bar = Bar()
bar.add_xaxis(A)
bar.add_yaxis("商家A",CA)
bar.add_yaxis("商家B",CB)
bar.set_global_opts(title_opts=opts.TitleOpts(title="多图绘制"))
bar.render(r"C:\Users\ldw\Desktop\demo\snapshot6.html")line = Line()
line.add_xaxis(B)
line.add_yaxis("商家A",CA)
line.add_yaxis("商家B",CB)
line.set_global_opts(title_opts=opts.TitleOpts(title="2图",pos_top="48%"),legend_opts=opts.LegendOpts(pos_top="48%"))
line.render_notebook()grid = Grid()
grid.add(bar,grid_opts=opts.GridOpts(pos_bottom="60%"))
grid.add(line,grid_opts=opts.GridOpts(pos_top="60%"))
grid.render(r"C:\Users\ldw\Desktop\demo\snapshot6.html")

bar = (Bar().add_xaxis(month_data).add_yaxis("降水量",precipitation_data).add_yaxis("蒸发量",evaporation_data).extend_axis(yaxis=opts.AxisOpts(name="温度",type_="value",min_=0,max_=25,interval=5,axislabel_opts=opts.LabelOpts(formatter="{value} °C"),)).set_global_opts(tooltip_opts=opts.TooltipOpts(is_show=True, trigger="axis", axis_pointer_type="cross"),xaxis_opts=opts.AxisOpts(type_="category",axispointer_opts=opts.AxisPointerOpts(is_show=True, type_="shadow"),),yaxis_opts=opts.AxisOpts(name="水量",type_="value",min_=0,max_=250,interval=50,axislabel_opts=opts.LabelOpts(formatter="{value} ml"),axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),),)
)
line = (Line().add_xaxis(month_data).add_yaxis(series_name="平均温度",yaxis_index=1,y_axis=average_temperature,label_opts=opts.LabelOpts(is_show=False),)
)
bar.overlap(line).render_notebook()

标记线

from pyecharts import options as opts
from pyecharts.charts import Bar
import random
l1=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']
l2=[100,200,300,400,500,400,300]
bar = (Bar().add_xaxis(l1).add_yaxis("l2", l2).set_global_opts(title_opts=opts.TitleOpts(title="标记线柱状图")).set_series_opts(label_opts=opts.LabelOpts(is_show=False),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="min", name="最小值"),opts.MarkLineItem(type_="max", name="最大值"),opts.MarkLineItem(type_="average", name="平均值"),]),)
)
bar.render_notebook()

标记点

from pyecharts import options as opts
from pyecharts.charts import Bar
import random
l1=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']
l2=[100,200,300,400,500,400,300]
bar = (Bar().add_xaxis(l1).add_yaxis("l2", l2).set_global_opts(title_opts=opts.TitleOpts(title="标记线柱状图")).set_series_opts(label_opts=opts.LabelOpts(is_show=False),markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="min", name="最小值"),opts.MarkPointItem(type_="max", name="最大值"),opts.MarkPointItem(type_="average", name="平均值"),]),)
)
bar.render_notebook()

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Autoleaders-可视化pyecharts

折线图

柱状图

饼图

普通饼图

环形图

玫瑰图

散点图

桑基图

词云

地图

销售转化漏斗

多维散点图

多饼图

K线图

漏斗图

多图绘制

标记线

标记点

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