网站制作ppt,网站开发者兼容模式出错,好省推广100种方法,建设银行公司官网pyecharts 是一个用于生成Echarts图表的Python库。Echarts是百度开源的一个数据可视化JS库#xff0c;可以生成一些非常酷炫的图表。 环境安装 pip install pyecharts 检查版本
import pyecharts print(pyecharts.version) 2.0.3
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from pyecharts.charts impor…pyecharts 是一个用于生成Echarts图表的Python库。Echarts是百度开源的一个数据可视化JS库可以生成一些非常酷炫的图表。 环境安装 pip install pyecharts 检查版本
import pyecharts print(pyecharts.version) 2.0.3
柱状图绘制
from pyecharts.charts import Bar from pyecharts import options as opts from pyecharts.globals import ThemeType
#v1版本开始支持链式调用 bar (Bar(init_opts opts.InitOpts(theme ThemeType.WESTEROS)) .add_xaxis([“Apple”,“Huawei”,“Xiaomi”,“Oppo”,“Vivo”,“Meizu”]) #指定x轴 #可以指定多个y轴 .add_yaxis(“电商渠道”,[133,163,99,117,108,33]) .add_yaxis(“门店”,[66,87,103,78,55,77]) #全局配置操作 .set_global_opts(title_optsopts.TitleOpts(title“Bar-基本示例”,subtitle“我是副标题”)) ) #在juputer notebook中渲染 bar.render_notebook()
添加工具箱配置 在全局配置set_global_opts中添加 toolbox_optsopts.ToolboxOpts()
from pyecharts.charts import Bar from pyecharts import options as opts
#示例数据 cate [‘Apple’,‘Huawei’,‘Xiaomi’,‘Oppo’,‘Vivo’,‘Meizu’] data1 [133,163,99,117,108,33] data2 [66,87,103,78,55,77]
#1.x版本支持链式调用 bar (Bar() .add_xaxis(cate) #指定x轴 #可以指定多个y轴 .add_yaxis(‘电商渠道’,data1) .add_yaxis(‘门店’,data2) .set_global_opts(title_optsopts.TitleOpts(title“Bar-基本示例”,subtitle“我是副标题”) ,toolbox_optsopts.ToolboxOpts() #添加工具箱代码 ) ) #在jupyter notebook中渲染 bar.render_notebook()
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cate [‘Apple’, ‘Huawei’, ‘Xiaomi’, ‘Oppo’, ‘Vivo’, ‘Meizu’] data [163, 134, 117, 109, 99, 56]
[list(z) for z in zip(cate,data)]
from pyecharts.charts import Pie from pyecharts import options as opts
#示例数据 cate [‘Apple’, ‘Huawei’, ‘Xiaomi’, ‘Oppo’, ‘Vivo’, ‘Meizu’] data [163, 134, 117, 109, 99, 56]
pie (Pie() .add(‘’,[list(z) for z in zip(cate,data)], radius[“30%”,“75%”], #设置半径内外圈半径 rosetype“radius” #半径形式的玫瑰型样式经典 ) .set_global_opts(title_optsopts.TitleOpts(title“Pie-基本示例”,subtitle“我是副标题”)) .set_series_opts(label_optsopts.LabelOpts(formatter“{b}:{d}%”)) )
pie.render_notebook()
折线图
from pyecharts.charts import Line from pyecharts import options as opts
#示例数据 cate [‘Apple’, ‘Huawei’, ‘Xiaomi’, ‘Oppo’, ‘Vivo’, ‘Meizu’] data1 [133,163,99,117,108,33] data2 [66,87,103,78,55,77]
“” 折线图示例:
is_smooth 折线 OR 平滑markline_opts 标记线 OR 标记点 “” line (Line() .add_xaxis(cate) .add_yaxis(‘电商渠道’,data1, #均值标记线 markline_optsopts.MarkLineOpts(data[opts.MarkAreaItem(type_“average”)])) .add_yaxis(‘门店’,data2, is_smoothTrue, markline_optsopts.MarkLineOpts(data[opts.MarkLineItem(type_“average”)]) ) .set_global_opts(title_optsopts.TitleOpts(title“Line-基本示例”,subtitle“我是副标题”)) )
line.render_notebook()
漏斗图
from pyecharts.charts import Funnel from pyecharts import options as opts
示例数据
cate [‘访问’, ‘注册’, ‘加入购物车’, ‘提交订单’, ‘付款成功’] data [30408, 15240, 10055, 8119, 5708]
“” 漏斗图示例
sort_控制排序默认降序label_opts标签显示位置 “” funnel (Funnel() .add(“用户数”,[list(z) for z in zip(cate,data)], sort_‘ascending’, label_optsopts.LabelOpts(position“inside”) ) .set_global_opts(title_optsopts.TitleOpts(title“Funnel-基本示例”,subtitle“我是副标题”)) )
funnel.render_notebook()
MapGlobe
import pyecharts.options as opts from pyecharts.charts import MapGlobe from pyecharts.faker import POPULATION
data [x for _, x in POPULATION[1:]] low, high min(data), max(data)
m ( MapGlobe() .add_schema() .add( maptype“world”, series_name“World Population”, data_pairPOPULATION[1:], is_map_symbol_showFalse, label_optsopts.LabelOpts(is_showFalse), ) .set_global_opts( visualmap_optsopts.VisualMapOpts( min_low, max_high, range_text[“max”, “min”], is_calculableTrue, range_color[“lightskyblue”, “yellow”, “green”], ) ) ) m.render_notebook()
仪表盘
import pyecharts.options as opts from pyecharts.charts import Gauge
g ( Gauge() .add(series_name“业务指标”, data_pair[[“完成率”, 59.5]]) .set_global_opts( legend_optsopts.LegendOpts(is_showFalse), tooltip_optsopts.TooltipOpts(is_showTrue, formatter“{a} {b} : {c}%”), ) ) g.render_notebook()
关系图
from pyecharts import options as opts from pyecharts.charts import Graph
nodes [ {“name”: “结点1”, “symbolSize”: 20}, {“name”: “结点2”, “symbolSize”: 30}, {“name”: “结点3”, “symbolSize”: 40}, {“name”: “结点4”, “symbolSize”: 50}, {“name”: “结点5”, “symbolSize”: 60}, {“name”: “结点6”, “symbolSize”: 50}, {“name”: “结点7”, “symbolSize”: 40}, {“name”: “结点8”, “symbolSize”: 30}, ] links [] for i in nodes: for j in nodes: links.append({“source”: i.get(“name”), “target”: j.get(“name”)}) g ( Graph() .add(“”, nodes, links, repulsion8000) .set_global_opts(title_optsopts.TitleOpts(title“我是关系图”)) ) g.render_notebook()
水球图
from pyecharts import options as opts from pyecharts.charts import Grid, Liquid from pyecharts.commons.utils import JsCode
l1 ( Liquid() .add(“lq”, [0.7, 0.8], center[“70%”, “60%”]) .set_global_opts(title_optsopts.TitleOpts(title“我们是水球图”)) )
l2 Liquid().add( “lq”, [0.4318], center[“35%”, “60%”], label_optsopts.LabelOpts( font_size50, formatterJsCode( “”“function (param) { return (Math.floor(param.value * 10000) / 100) ‘%’; }”“” ), position“inside”, ), )
grid Grid().add(l1, grid_optsopts.GridOpts()).add(l2, grid_optsopts.GridOpts()) grid.render_notebook() 源文件可在这里下载 https://download.csdn.net/download/ak2111/89039929?spm1001.2014.3001.5501
