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
人工智能训练4 小时前
【极速部署】Ubuntu24.04+CUDA13.0 玩转 VLLM 0.15.0:预编译 Wheel 包 GPU 版安装全攻略
运维·前端·人工智能·python·ai编程·cuda·vllm
yaoming1684 小时前
python性能优化方案研究
python·性能优化
码云数智-大飞5 小时前
使用 Python 高效提取 PDF 中的表格数据并导出为 TXT 或 Excel
python
biuyyyxxx6 小时前
Python自动化办公学习笔记(一) 工具安装&教程
笔记·python·学习·自动化
极客数模7 小时前
【2026美赛赛题初步翻译F题】2026_ICM_Problem_F
大数据·c语言·python·数学建模·matlab
小鸡吃米…8 小时前
机器学习中的代价函数
人工智能·python·机器学习
Li emily9 小时前
如何通过外汇API平台快速实现实时数据接入?
开发语言·python·api·fastapi·美股
m0_561359679 小时前
掌握Python魔法方法(Magic Methods)
jvm·数据库·python
Ulyanov9 小时前
顶层设计——单脉冲雷达仿真器的灵魂蓝图
python·算法·pyside·仿真系统·单脉冲
2401_8384725110 小时前
使用Python进行图像识别:CNN卷积神经网络实战
jvm·数据库·python