桑基图
桑基图系列模板
第一个桑基图
复杂桑基图
桑基图桑基图(Sankey diagram),即桑基能量分流图,也叫桑基能量平衡图。它是一种特定类型的流程图,图中延伸的分支的宽度对应数据流量的大小,通常应用于 能源、材料成分、 金融等数据的可视化分析。因1898年Matthew Henry Phineas Riall Sankey绘制的“ 蒸汽机的能源效率图”而闻名,此后便以其名字命名为“桑基图”。
桑基图最明显的特征就是,始末端的分支宽度总和相等,即所有主支宽度的总和应与所有分出去的分支宽度的总和相等,保持能量的平衡。
桑基图系列模板 第一个桑基图from pyecharts import options as opts
from pyecharts.charts import Sankey
nodes = [
{"name": "category1"},
{"name": "category2"},
{"name": "category3"},
{"name": "category4"},
{"name": "category5"},
{"name": "category6"},
]
links = [
{"source": "category1", "target": "category2", "value": 10},
{"source": "category2", "target": "category3", "value": 15},
{"source": "category3", "target": "category4", "value": 20},
{"source": "category5", "target": "category6", "value": 25},
]
c = (
Sankey()
.add(
"sankey",
nodes,
links,
linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
label_opts=opts.LabelOpts(position="right"),
)
.set_global_opts(title_opts=opts.TitleOpts(title="标题"))
.render("桑基图.html")
)
复杂桑基图
from pyecharts import options as opts
from pyecharts.charts import Sankey
colors = [
"#67001f",
"#b2182b",
"#d6604d",
"#f4a582",
"#fddbc7",
"#d1e5f0",
"#92c5de",
"#4393c3",
"#2166ac",
"#053061",
]
nodes = [
{"name": "a"},
{"name": "b"},
{"name": "a1"},
{"name": "b1"},
{"name": "c"},
{"name": "e"},
]
links = [
{"source": "a", "target": "a1", "value": 5},
{"source": "e", "target": "b", "value": 3},
{"source": "a", "target": "b1", "value": 3},
{"source": "b1", "target": "a1", "value": 1},
{"source": "b1", "target": "c", "value": 2},
{"source": "b", "target": "c", "value": 1},
]
c = (
Sankey()
.set_colors(colors)
.add(
"sankey",
nodes=nodes,
links=links,
pos_bottom="10%",
focus_node_adjacency="allEdges",
orient="vertical",
linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
label_opts=opts.LabelOpts(position="top"),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="标题"),
tooltip_opts=opts.TooltipOpts(trigger="item", trigger_on="mousemove"),
)
.render("复杂桑基图.html")
)
这个桑基图的案例已经可以完成你的可视化工作量了,其实一般研究桑基图的还是相对于比较少。
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