pycharm——树状图

复制代码
from pyecharts import options as opts
from pyecharts.charts import Tree


data = [
    {
        "children": [
            {"name": "计算机"},
            {
                "children": [{"children": [{"name": "主机"}], "name": "硬盘"}, {"name": "鼠标和键盘"}],
                "name": "硬件",
            },
            {
                "children": [
                    {"children": [{"name": "操作系统"}, {"name": "数据结构"}], "name": "组成原理"},
                    {"name": "基础"},
                ],
                "name": "软件",
            },
        ],
        "name": "数学",
    }
]
c = (
    Tree()
    .add("", data)
    .set_global_opts(title_opts=opts.TitleOpts(title="Tree-基本示例"))
    .render("tree_base.html")
)
复制代码
import json

from pyecharts import options as opts
from pyecharts.charts import Tree

with open("flare.json", "r", encoding="utf-8") as f:
    j = json.load(f)
c = (
    Tree()
    .add("", [j], collapse_interval=2, layout="radial")
    .set_global_opts(title_opts=opts.TitleOpts(title="Tree-Layout"))
    .render("tree_layout.html")
)

flare.json文件

复制代码
 {
    "name": "My Library",
    "children": [
        {
            "name": "Book",
            "children": [
                {"name": "Title", "value": "The Great Gatsby"},
                {"name": "Author", "value": "F. Scott Fitzgerald"},
                {"name": "Publication Date", "value": "1925-04-10"}
            ]
        },
        {
            "name": "Library",
            "children": [
                {"name": "Name", "value": "Central Library"},
                {"name": "Location", "value": "New York"}
            ]
        },
        {
            "name": "Characters",
            "children": [
                {"name": "Jay Gatsby", "value": "Wealthy Gambler"},
                {"name": "Nick Carraway", "value": "Narrator"},
                {"name": "Daisy Buchanan", "value": "Socialite"}
            ]
        },
        {
          "name": "competer",
          "children": [
            {"name": "数据结构","value": "50"},
            {"name": "数据库原理","value": "60"},
            {"name": "计算机组成网络","value": "40"}
          ]
         }
    ]
}
相关推荐
隐擎fox4 小时前
解构无感人机验证底层机制:行为生物轨迹采样、环境评分模型与自动化对抗实战
自动化测试·python·网络协议·tcp/ip·网络爬虫
haidao0315 小时前
氙灯光源技术特性及其在光催化实验中的标准化应用研究
人工智能·python·能源
用户0332126663675 小时前
使用 Python 设置 Excel 行列自适应 【代码示例】
python·excel
Ticnix5 小时前
RAG 的坑不在检索,在"对齐":pgvector 实战手记
python·agent·全栈
kyrie_sakura5 小时前
python学习笔记14 -- FastAPI
笔记·python·学习·fastapi
春涧草茶5 小时前
慢就是快12-2三种访问权限|getter与setter|魔法方法
开发语言·python
夜雪一千6 小时前
如何使用Python做舆情分析
人工智能·python·数据分析
Ticnix7 小时前
MCP 工具拿不到 user_id?用 contextvars 做请求级用户隔离
python·agent·mcp
gb42152877 小时前
WPS 里的 Word快速合成照片
python