Pyecharts之饼图(Pie)
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} <br/>{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} <br/>{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()
