雷達圖是以從同一點開始的軸上表示的三個或更多個定量變量的二維圖表的形式顯示多變量數(shù)據的圖形方法,雷達圖通常用于綜合分析多個指標，具有完整，清晰和直觀的優(yōu)點。
import pyecharts.options as opts
from pyecharts.charts import Radar
v1 = [[110, 9.7, 6.2, 56, 150, 1610]]
v2 = [[174, 6.9, 6.8, 66, 237, 1540]]
c=(
Radar(init_opts=opts.InitOpts(bg_color="#3CB371")) #設置背景顏色
.add_schema(
schema=[
opts.RadarIndicatorItem(name="最大功率率（KW）", max_=200),
opts.RadarIndicatorItem(name="百米提速（秒）", max_=12),
opts.RadarIndicatorItem(name="綜合油耗（L/100KM）", max_=20),
opts.RadarIndicatorItem(name="油箱容積（L）", max_=100),
opts.RadarIndicatorItem(name="馬力(Ps)", max_=300),
opts.RadarIndicatorItem(name="整車質量KG（）", max_=2000),
],
splitarea_opt=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1) #是否顯示分隔區(qū)域，透明度設置為1
),
textstyle_opts=opts.TextStyleOpts(color="#fff"),
)
.add(
series_name="奧迪A4L時尚動感型",
data=v1,
linestyle_opts=opts.LineStyleOpts(color="#8B008B",width=2), #線的顏色、寬度
)
.add(
series_name="凱迪拉克CT4精英型",
data=v2,
linestyle_opts=opts.LineStyleOpts(color="#FFA500",width=2), #線的顏色、寬度
)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False)) #不顯示數(shù)字
.set_global_opts(
title_opts=opts.TitleOpts(title="汽車性能比較"), legend_opts=opts.LegendOpts()
)
)
c.render_notebook()
from pyecharts import options as opts
from pyecharts.charts import Radar
value_bj = [
[55, 9, 56, 0.46, 18, 6, 1],
[25, 11, 21, 0.65, 34, 9, 2],
[56, 7, 63, 0.3, 14, 5, 3],
[33, 7, 29, 0.33, 16, 6, 4],
[42, 24, 44, 0.76, 40, 16, 5],
[82, 58, 90, 1.77, 68, 33, 6],
[74, 49, 77, 1.46, 48, 27, 7],
[78, 55, 80, 1.29, 59, 29, 8],
[267, 216, 280, 4.8, 108, 64, 9],
[185, 127, 216, 2.52, 61, 27, 10],
[39, 19, 38, 0.57, 31, 15, 11],
[41, 11, 40, 0.43, 21, 7, 12],
]
value_sh = [
[91, 45, 125, 0.82, 34, 23, 1],
[65, 27, 78, 0.86, 45, 29, 2],
[83, 60, 84, 1.09, 73, 27, 3],
[109, 81, 121, 1.28, 68, 51, 4],
[106, 77, 114, 1.07, 55, 51, 5],
[109, 81, 121, 1.28, 68, 51, 6],
[106, 77, 114, 1.07, 55, 51, 7],
[89, 65, 78, 0.86, 51, 26, 8],
[53, 33, 47, 0.64, 50, 17, 9],
[80, 55, 80, 1.01, 75, 24, 10],
[117, 81, 124, 1.03, 45, 24, 11],
[99, 71, 142, 1.1, 62, 42, 12],
]
c_schema = [
{"name": "AQI", "max": 300, "min": 5},
{"name": "PM2.5", "max": 250, "min": 20},
{"name": "PM10", "max": 300, "min": 5},
{"name": "CO", "max": 5},
{"name": "NO2", "max": 200},
{"name": "SO2", "max": 100},
]
c = (
Radar(init_opts=opts.InitOpts(bg_color="#8B658B"))
.add_schema(schema=c_schema, shape="polygon")
.add("北京", value_bj,color="#8B008B",linestyle_opts=opts.LineStyleOpts(width=2))
.add("上海", value_sh,color="#FF4500",linestyle_opts=opts.LineStyleOpts(width=2))
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(title_opts=opts.TitleOpts(title="一線城市空氣質量比較"))
)
c.render_notebook()
