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ariera
V2EX  ›  Python

如何把如下这样一个 Json tree 转换成如何 dataframe

  •  
  •   ariera · 2022-01-04 21:12:33 +08:00 · 1289 次点击
    这是一个创建于 1045 天前的主题,其中的信息可能已经有所发展或是发生改变。
    import json
    
    str_json = '{"id":"S0","label":"部门","child":[{"id":"S1","label":"管理层","child":[]},{"id":"S2","label":"人力资源部","child":[{"id":"S21","label":"招聘组","child":[{"id":"S210","label":"上海组","child":[{"id":"S2101","label":"上海其他","child":[]},{"id":"S2102","label":"陆家嘴","child":[]}]},{"id":"S211","label":"深圳组","child":[]},{"id":"S212","label":"北京组","child":[]}]},{"id":"S22","label":"考核组","child":[]},{"id":"S23","label":"制度组","child":[]}]},{"id":"S3","label":"行政管理部","child":[{"id":"S31","label":"后勤组","child":[]},{"id":"S31","label":"食堂组","child":[]}]},{"id":"S4","label":"信息技术部","child":[{"id":"S41","label":"运行部","child":[{"id":"S411","label":"运维组","child":[]}]}]}]}'
    js = json.loads(str_json)
    

    https://imgur.com/OwfYUme

    以上只是个示例,实际中最深可能有 6 层。 将上图的 js 转成如下 dataframe ( id 列在第一列也行),求赐教

    id
    部门 管理层 S1
    部门 人力资源部 招聘组 上海组 上海其他 S2101
    部门 人力资源部 招聘组 上海组 陆家嘴 S2102
    部门 人力资源部 招聘组 深圳组 S211
    部门 人力资源部 招聘组 北京组 S212
    部门 人力资源部 考核组 S22
    部门 人力资源部 制度组 S23
    部门 行政管理部 后勤组 S31
    部门 行政管理部 食堂组 S32
    部门 行政管理部 设施组 S33
    部门 信息技术部 运行部 运维组 S411
    第 1 条附言  ·  2022-01-04 22:14:45 +08:00
    ![js 对象]( )
    9 条回复    2022-01-04 23:12:12 +08:00
    Donahue
        1
    Donahue  
       2022-01-04 22:19:17 +08:00
    import json
    from typing import List
    import pandas as pd

    class People():
    def __init__(self, js_data, label_prefix:List=None):
    self.id = js_data['id']

    if label_prefix == None:
    self.label = [js_data['label']]
    else:
    self.label = label_prefix + [js_data['label']]

    self.child = [People(child_js, self.label) for child_js in js_data['child']]

    def get_label_i(self, i:int):
    if i >= len(self.label):
    return ''
    else:
    return self.label[i]

    def get_all_instance(p:People):
    result = []
    result.append(p)
    for child in p.child:
    result += get_all_instance(child)
    return result



    str_json = '{"id":"S0","label":"部门","child":[{"id":"S1","label":"管理层","child":[]},{"id":"S2","label":"人力资源部","child":[{"id":"S21","label":"招聘组","child":[{"id":"S210","label":"上海组","child":[{"id":"S2101","label":"上海其他","child":[]},{"id":"S2102","label":"陆家嘴","child":[]}]},{"id":"S211","label":"深圳组","child":[]},{"id":"S212","label":"北京组","child":[]}]},{"id":"S22","label":"考核组","child":[]},{"id":"S23","label":"制度组","child":[]}]},{"id":"S3","label":"行政管理部","child":[{"id":"S31","label":"后勤组","child":[]},{"id":"S31","label":"食堂组","child":[]}]},{"id":"S4","label":"信息技术部","child":[{"id":"S41","label":"运行部","child":[{"id":"S411","label":"运维组","child":[]}]}]}]}'
    js = json.loads(str_json)

    root_instance = People(js)
    all_instance = get_all_instance(root_instance)

    df = pd.DataFrame()
    df['id'] = [i.id for i in all_instance]

    max_depth_people = max(all_instance, key=lambda x: len(x.label))
    label_depth = len(max_depth_people.label)

    for label_num in range(label_depth):
    df[f"label{label_num}"] = [i.get_label_i(label_num) for i in all_instance]

    print(df)
    Donahue
        2
    Donahue  
       2022-01-04 22:19:53 +08:00
    ps: 不要吐槽代码写得烂 hh
    Donahue
        3
    Donahue  
       2022-01-04 22:24:38 +08:00
    就是递归建立对象,然后把所有对象保存到列表里
    fkdog
        4
    fkdog  
       2022-01-04 22:29:42 +08:00
    本质上就是树结构的遍历算法。
    BFS 请用队列
    DFS 请用递归 or 栈
    ariera
        5
    ariera  
    OP
       2022-01-04 22:31:39 +08:00
    ariera
        6
    ariera  
    OP
       2022-01-04 22:32:56 +08:00
    @Donahue #1 好像无法运行,可能是缩进有问题。呜呜呜.... 能不能用 三个点``` 圈一下代码
    Donahue
        7
    Donahue  
       2022-01-04 22:38:20 +08:00
    Donahue
        8
    Donahue  
       2022-01-04 22:40:46 +08:00
    ariera
        9
    ariera  
    OP
       2022-01-04 23:12:12 +08:00
    @Donahue #8 赞!
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