Pyecharts之饼图(Pie)

#Pyecharts之饼图(Pie)| 来源: 网络整理| 查看: 265

Pyecharts之饼图(Pie) from snapshot_selenium import snapshot as driver from pyecharts import options as opts from pyecharts.charts import Pie from pyecharts.render import make_snapshot from pyecharts.globals import CurrentConfig,NotebookType CurrentConfig.NOTEBOOK_TYPE=NotebookType.JUPYTER_LAB 一.基本概念

class pyecharts.charts.Pie

class Pie( # 初始化配置项，参考 `global_options.InitOpts` init_opts: opts.InitOpts = opts.InitOpts() )

func pyecharts.charts.Pie.add

def add( # 系列名称，用于 tooltip 的显示，legend 的图例筛选。 series_name: str, # 系列数据项，格式为 [(key1, value1), (key2, value2)] data_pair: Sequence, # 系列 label 颜色 color: Optional[str] = None, # 饼图的半径，数组的第一项是内半径，第二项是外半径 # 默认设置成百分比，相对于容器高宽中较小的一项的一半 radius: Optional[Sequence] = None, # 饼图的中心（圆心）坐标，数组的第一项是横坐标，第二项是纵坐标 # 默认设置成百分比，设置成百分比时第一项是相对于容器宽度，第二项是相对于容器高度 center: Optional[Sequence] = None, # 是否展示成南丁格尔图，通过半径区分数据大小，有'radius'和'area'两种模式。 # radius：扇区圆心角展现数据的百分比，半径展现数据的大小 # area：所有扇区圆心角相同，仅通过半径展现数据大小 rosetype: Optional[str] = None, # 饼图的扇区是否是顺时针排布。 is_clockwise: bool = True, # 标签配置项，参考 `series_options.LabelOpts` label_opts: Union[opts.LabelOpts, dict] = opts.LabelOpts(), # 提示框组件配置项，参考 `series_options.TooltipOpts` tooltip_opts: Union[opts.TooltipOpts, dict, None] = None, # 图元样式配置项，参考 `series_options.ItemStyleOpts` itemstyle_opts: Union[opts.ItemStyleOpts, dict, None] = None, # 可以定义 data 的哪个维度被编码成什么。 encode: types.Union[types.JSFunc, dict, None] = None, ) 二.代码示例 from pyecharts import options as opts from pyecharts.charts import Pie from pyecharts.faker import Faker p = ( Pie() .add("", [list(z) for z in zip(Faker.choose(), Faker.values())]) .set_colors(["blue", "green", "yellow", "red", "pink", "orange", "purple"]) .set_global_opts(title_opts=opts.TitleOpts(title="Pie-设置颜色")) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")) #.render("pie_set_color.html") ) #make_snapshot(driver,g.render("gauge.html"),"gauge.png") p.load_javascript() p.render_notebook() import pyecharts.options as opts from pyecharts.charts import Pie x_data = ["直接访问", "邮件营销", "联盟广告", "视频广告", "搜索引擎"] y_data = [335, 310, 274, 235, 400] data_pair = [list(z) for z in zip(x_data, y_data)] data_pair.sort(key=lambda x: x[1]) p=( Pie(init_opts=opts.InitOpts(width="1000px", height="600px", bg_color="#2c343c")) .add( series_name="访问来源", data_pair=data_pair, rosetype="radius", radius="55%", center=["50%", "50%"], label_opts=opts.LabelOpts(is_show=False, position="center"), ) .set_global_opts( title_opts=opts.TitleOpts( title="Customized Pie", pos_left="center", pos_top="20", title_textstyle_opts=opts.TextStyleOpts(color="#fff"), ), legend_opts=opts.LegendOpts(is_show=False), ) .set_series_opts( tooltip_opts=opts.TooltipOpts( trigger="item", formatter="{a} {b}: {c} ({d}%)" ), label_opts=opts.LabelOpts(color="rgba(255, 255, 255, 0.3)"), ) #.render("customized_pie.html") ) #make_snapshot(driver,g.render("gauge.html"),"gauge.png") p.load_javascript() p.render_notebook() from pyecharts import options as opts from pyecharts.charts import Pie from pyecharts.faker import Faker p = ( Pie() .add( "", [list(z) for z in zip(Faker.choose(), Faker.values())], radius=["40%", "55%"], label_opts=opts.LabelOpts( position="outside", formatter="{a|{a}}{abg|}\n{hr|}\n {b|{b}: }{c} {per|{d}%} ", background_color="#eee", border_color="#aaa", border_width=1, border_radius=4, rich={ "a": {"color": "#999", "lineHeight": 22, "align": "center"}, "abg": { "backgroundColor": "#e3e3e3", "width": "100%", "align": "right", "height": 22, "borderRadius": [4, 4, 0, 0], }, "hr": { "borderColor": "#aaa", "width": "100%", "borderWidth": 0.5, "height": 0, }, "b": {"fontSize": 16, "lineHeight": 33}, "per": { "color": "#eee", "backgroundColor": "#334455", "padding": [2, 4], "borderRadius": 2, }, }, ), ) .set_global_opts(title_opts=opts.TitleOpts(title="Pie-富文本示例"), #legend_opts=opts.LegendOpts(type_="scroll",pos_left="80%",orient="vertical") ) #.render("pie_rich_label.html") ) #make_snapshot(driver,g.render("gauge.html"),"gauge.png") p.load_javascript() p.render_notebook() from pyecharts import options as opts from pyecharts.charts import Pie from pyecharts.faker import Faker p = ( Pie() .add( "", [ list(z) for z in zip( Faker.choose() + Faker.choose() + Faker.choose(), Faker.values() + Faker.values() + Faker.values(), ) ], center=["40%", "50%"], ) .set_global_opts( title_opts=opts.TitleOpts(title="Pie-Legend 滚动"), legend_opts=opts.LegendOpts(type_="scroll", pos_left="80%", orient="vertical"), ) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")) #.render("pie_scroll_legend.html") ) #make_snapshot(driver,g.render("gauge.html"),"gauge.png") p.load_javascript() p.render_notebook() 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") p = ( 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-多饼图基本示例"), legend_opts=opts.LegendOpts( type_="scroll", pos_top="20%", pos_left="80%", orient="vertical" ), ) #.render("mutiple_pie.html") ) p.load_javascript() p.render_notebook() 三.示例演示

数据具体处理过程链接：去哪儿

1.数据处理与获取 import pandas as pd data=pd.read_csv("travel2.csv") import re def Look(e): if '万' in e: num=re.findall('(.*?)万',e) return float(num[0])*10000 else: return float(e) data['浏览次数']=data['浏览量'].apply(Look) data.drop(['浏览量'],axis=1,inplace=True) data['浏览次数']=data['浏览次数'].astype(int) data1=data.head(7) data.head(7) 地点短评出发时间天数人均费用人物玩法浏览次数 0 婺源春天的婺源，油菜花开，宛如一幅诗情画意的水墨画 /2020/04/01 5 3000 三五好友第一次美食 9055 1 阿联酋阿联酋｜小狮妹和父母的新年迪拜之旅 /2019/12/10 8 - - - 3860 2 AguadePau 来自《一个女生的古巴独行记》（11日自由行攻略） /2019/09/27 11 20000 独自一人深度游美食摄影国庆 261 3 建水云南│我什么也没忘，但有些事只适合收藏 /2019/10/10 8 4000 三五好友穷游摄影古镇赏秋国庆 6176 4 日本日本｜东京の72小时 /2019/09/21 8 - - - 12000 5 海宁海洪宁静，盐潮入官，百里钱塘，春暖花开--驾“浙”观大潮访金庸、赏樱花睡房车 /2020/03/23 2 900 情侣自驾赏樱踏春清明 22000 6 敦煌甘青│到远方去，到那个山野苍茫的远方，熟悉的地方没有景色 /2019/05/10 10 3500 三五好友环游毕业游穷游 14000 datas=[list(z) for z in zip(data1["地点"].tolist(),data1["浏览次数"].tolist())] datas.sort(key=lambda x:x[1]) datas [['AguadePau', 261], ['阿联酋', 3860], ['建水', 6176], ['婺源', 9055], ['日本', 12000], ['敦煌', 14000], ['海宁', 22000]] 2.展示 import pyecharts.options as opts from pyecharts.charts import Pie p=( Pie(init_opts=opts.InitOpts(width="1000px", height="600px", bg_color="#2c343c")) .add( series_name="旅游浏览", data_pair=datas, rosetype="radius", radius="55%", center=["50%", "50%"], label_opts=opts.LabelOpts(is_show=False, position="center"), ) .set_global_opts( title_opts=opts.TitleOpts( title="旅游 Pie", pos_left="center", pos_top="20", title_textstyle_opts=opts.TextStyleOpts(color="#fff"), ), legend_opts=opts.LegendOpts(is_show=False), ) .set_series_opts( tooltip_opts=opts.TooltipOpts( trigger="item", formatter="{a} {b}: {c} ({d}%)" ), label_opts=opts.LabelOpts(color="rgba(255, 255, 255, 0.3)"), ) #.render("customized_pie.html") ) #make_snapshot(driver,g.render("gauge.html"),"gauge.png") p.load_javascript() p.render_notebook()

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