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") ) 

讯享网

柱状图

讯享网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() 

讯享网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

讯享网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

讯享网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 Sankey df = 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']=value nodes.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,links nodes,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

讯享网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

讯享网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

讯享网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

讯享网from pyecharts.charts import Funnel c = ( 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") 

讯享网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

讯享网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()