数据可视化第二版-03部分-12章-网络
总结
本系列博客为基于《数据可视化第二版》一书的教学资源博客。本文主要是第12章，网络案例相关。
可视化视角-相关
代码实现
安装依赖
代码语言：javascript复制pip install scikit-learn -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install seaborn -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install tushare==1.2.89 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install mplfinance==0.12.9b7 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install pyheatmap==0.1.12 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install networkx==3.1网络图
参考:基于NetworkX构建复杂网络的应用案例
网络图1-networkx
代码语言：javascript复制# 网络图
from matplotlib import pyplot as plt
import networkx as nx
G = nx.Graph()
G.add_nodes_from(["A", "B", "C", "D", "E", "F"])
G.add_edges_from([("A", "B"), ("A", "C"), ("A", "D"), ("B", "C"), ("B", "F"), ("C", "E"), ("D", "F")])
# with_labels是否显示标签，node_size节点大小，node_color节点颜色，node_shape节点形状，alpha透明度，linewidths线条宽度
# 左：跳跃式布局
nx.draw(G, with_labels=True, node_size=400, node_color="skyblue", node_shape="o", alpha=1, width=1, font_size=12,
font_color="black")
plt.show()
# 中：环形布局
nx.draw(G, with_labels=True, node_size=400, node_color="skyblue", node_shape="o", alpha=1, width=1, font_size=12,
font_color="black", pos=nx.circular_layout(G))
plt.show()
# 右：随机布局
nx.draw(G, with_labels=True, node_size=400, node_color="skyblue", node_shape="o", alpha=1, width=1, font_size=12,
font_color="black", pos=nx.random_layout(G))
plt.show()
'''
networkx 画图参数：
- node_size: 指定节点的尺寸大小(默认是300)
- node_color: 指定节点的颜色 (默认是红色，可以用字符串简单标识颜色，例如'r'为红色，'b'为绿色等，具体可查看手册)，用“数据字典”赋值的时候必须对字典取值（.values()）后再赋值
- node_shape: 节点的形状（默认是圆形，用字符串'o'标识，具体可查看手册）
- alpha: 透明度 (默认是1.0，不透明，0为完全透明)
- width: 边的宽度 (默认为1.0)
- edge_color: 边的颜色(默认为黑色)
- style: 边的样式(默认为实现，可选： solid|dashed|dotted,dashdot)
- with_labels: 节点是否带标签（默认为True）
- font_size: 节点标签字体大小 (默认为12)
- font_color: 节点标签字体颜色（默认为黑色）
e.g. nx.draw(G,node_size = 30, with_label = False)
绘制节点的尺寸为30，不带标签的网络图。
布局指定节点排列形式
pos = nx.spring_layout
建立布局，对图进行布局美化，networkx 提供的布局方式有：
- circular_layout：节点在一个圆环上均匀分布
- random_layout：节点随机分布
- shell_layout：节点在同心圆上分布
- spring_layout： 用Fruchterman-Reingold算法排列节点
- spectral_layout：根据图的拉普拉斯特征向量排列节
布局也可用pos参数指定，例如，nx.draw(G, pos = spring_layout(G)) 这样指定了networkx上以中心放射状分布.
'''输出为：
弧形图
环形弧形长链接图
代码语言：javascript复制# -*- coding: utf-8 -*-
"""
@reference
https://gallery.pyecharts.org/#/Graph/graph_les_miserables
https://github.com/pyecharts/pyecharts-gallery/blob/master/Graph/les-miserables.json
"""
import json
from pyecharts import options as opts
from pyecharts.charts import Graph
import os
os.chdir(os.path.dirname(__file__))
with open("les-miserables.json", "r", encoding="utf-8") as f:
j = json.load(f)
nodes = j["nodes"]
links = j["links"]
categories = j["categories"]
c = (
Graph(init_opts=opts.InitOpts(width="1000px", height="600px"))
.add(
"",
nodes=nodes,
links=links,
categories=categories,
layout="circular",
is_rotate_label=True,
linestyle_opts=opts.LineStyleOpts(color="source", curve=0.3),
label_opts=opts.LabelOpts(position="right"),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="Graph-Les Miserables"),
legend_opts=opts.LegendOpts(orient="vertical", pos_left="2%", pos_top="20%"),
)
.render("graph_les_miserables.html")
)
import os
os.system("graph_les_miserables.html")输出为：
桑基图
桑基图1-
代码语言：javascript复制# -*- coding: utf-8 -*-
"""
@reference:
https://pyecharts.org/#/zh-cn/basic_charts?id=sankey：桑基图
https://gallery.pyecharts.org/#/Sankey/sankey_base
"""
from pyecharts import options as opts
from pyecharts.charts import Sankey
# 内置主题类型可查看 pyecharts.globals.ThemeType
"""
from pyecharts.globals import ThemeType
"""
nodes = [
{"name": "category1"},
{"name": "category2"},
{"name": "category3"},
{"name": "category4"},
{"name": "category5"},
{"name": "category6"},
]
links = [
{"source": "category1", "target": "category3", "value": 10},
{"source": "category1", "target": "category4", "value": 15},
{"source": "category2", "target": "category3", "value": 10},
{"source": "category2", "target": "category4", "value": 10},
{"source": "category3", "target": "category5", "value": 20},
{"source": "category4", "target": "category5", "value": 10},
{"source": "category4", "target": "category6", "value": 15},
]
# pyecharts V1 版本开始所有方法均支持链式调用。
sankey = (
Sankey() # 试试变换主题：Sankey(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))，参考：进阶话题-定制主题
.add(
"sankey",
nodes,
links,
linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
label_opts=opts.LabelOpts(position="right"), # 节点标签位置可选，参考:配置项-系列配置项-标签配置项
)
.set_global_opts(title_opts=opts.TitleOpts(title="Sankey-基本示例"))
# 或者直接使用字典参数
# .set_global_opts(title_opts={"text": "主标题", "subtext": "副标题"})
.render("sankey_base_2.html")
# render 会生成本地 HTML 文件，默认会在当前目录生成 render.html 文件
# 也可以传入路径参数，如 Sankey.render("sankey_base.html")
)
import os
os.system("sankey_base_2.html")
# 不习惯链式调用的开发者依旧可以单独调用方法
"""
sankey = Sankey()
sankey.add("sankey",
nodes,
links,
linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
label_opts=opts.LabelOpts(position="right"),
)
sankey.set_global_opts(title_opts=opts.TitleOpts(title="Sankey-基本示例"))
sankey.render("sankey_base.html")
"""
# 渲染成图片文件
"""
from pyecharts.render import make_snapshot
# 使用 snapshot-selenium 渲染图片（需安装）
from snapshot_selenium import snapshot
make_snapshot(snapshot, sankey, "sankey_base.png")#sankey为html文件
#snapshot-selenium 报错处理可参考：https://blog.csdn.net/snwang_miss/article/details/117728949
"""
桑基图2-
代码语言：javascript复制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": "category3", "value": 10},
{"source": "category1", "target": "category4", "value": 15},
{"source": "category2", "target": "category3", "value": 10},
{"source": "category2", "target": "category4", "value": 10},
{"source": "category3", "target": "category5", "value": 20},
{"source": "category4", "target": "category5", "value": 10},
{"source": "category4", "target": "category6", "value": 15},
]
sankey = (
Sankey()
.add(
"sankey",
nodes,
links,
linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
label_opts=opts.LabelOpts(position="right"),#节点标签位置
)
.set_global_opts(title_opts=opts.TitleOpts(title="Sankey-基本示例"))
.render("sankey_base.html")
)
import os
os.system("sankey_base.html")
桑基图3-
代码语言：javascript复制from pyecharts import options as opts
from pyecharts.charts import Sankey
# 内置主题类型可查看 pyecharts.globals.ThemeType
from pyecharts.globals import ThemeType
nodes = [
{"name": "category1"},
{"name": "category2"},
{"name": "category3"},
{"name": "category4"},
{"name": "category5"},
{"name": "category6"},
]
links = [
{"source": "category1", "target": "category3", "value": 10},
{"source": "category1", "target": "category4", "value": 15},
{"source": "category2", "target": "category3", "value": 10},
{"source": "category2", "target": "category4", "value": 10},
{"source": "category3", "target": "category5", "value": 20},
{"source": "category4", "target": "category5", "value": 10},
{"source": "category4", "target": "category6", "value": 15},
]
sankey_vertical = (
Sankey(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add(
"sankey",
nodes,
links,
# Sankey 组件离容器外侧的距离 types.Union[str, types.Numeric]：默认值：pos_left="5%",pos_right="20%",
pos_left="20%",
orient="vertical",
linestyle_opt=opts.LineStyleOpts(opacity=0.2, curve=0.5, color="source"),
label_opts=opts.LabelOpts(position="inside"),#节点标签位置可选，参考:配置项-系列配置项-标签配置项
)
.set_global_opts(title_opts=opts.TitleOpts(title="Sankey-Vertical"))
.render("sankey_vertical.html")
)
import os
os.system("sankey_vertical.html")
有趣的可视化
https://plotapi.com/#billing_interval
教材截图
