从列 headers 中删除整数列表键

Question

我有一个 Python 脚本，它使用了之前 Stack Overflow solution 中的函数。

from pandas import json_normalize
from collections.abc import MutableMapping as mm
def flatten(dictionary, parent_key=False, separator='.'):
    items = []
    for key, value in dictionary.items():
        new_key = str(parent_key) + separator + key if parent_key else key
        if isinstance(value, mm):
            items.extend(flatten(value, new_key, separator).items())
        elif isinstance(value, list):
            for k, v in enumerate(value):
                items.extend(flatten({str(k): v}, new_key).items())
        else:
            items.append((new_key, value))
    return dict(items)

d = { 
    "_id" : 1, 
    "labelId" : [
        6422
    ], 
    "levels" : [
        {
            "active" : "true", 
            "level" : 3, 
            "actions" : [
                {
                    "isActive" : "true"
                }]
        }]
}

x = flatten(d)

x = json_normalize(x)

print(x)

当前输出：

   _id  labelId.0 levels.0.active  levels.0.level levels.0.actions.0.isActive 
0    1       6422            true               3                        true

我遇到的问题是列名称中包含数字键。有什么方法可以修改我的代码以获得我想要的输出吗？

期望输出：

   _id    labelId   levels.active    levels.level     levels.actions.isActive 
0    1       6422            true               3                        true

Answer 1

首先将 parent_key 用作 bool，然后为其分配其他类型的值并不是最佳做法。它有效但会变得混乱。我稍微修改了一段代码，添加了单独的参数来跟踪 parent_key status 作为 bool，而 p_key 带有你想要的字符串。这是片段

from pandas import json_normalize
from collections.abc import MutableMapping as mm
def flatten(dictionary, p_key=None, parent_key=False, separator='.'):
    items = []
    for key, value in dictionary.items():
        if parent_key:
            new_key = f"{str(p_key)}{separator}{key}"
        else:
            new_key = p_key if p_key else key
        if isinstance(value, mm):
            items.extend(flatten(
                dictionary=value,
                p_key=new_key,
                parent_key=True,
                separator=separator).items())
        elif isinstance(value, list):
            for k, v in enumerate(value):
                items.extend(flatten(
                    dictionary={str(k): v},
                    p_key=new_key,
                    parent_key=False,
                    separator=separator).items())
        else:
            items.append((new_key, value))
    return dict(items)

d = { 
    "_id" : 1, 
    "labelId" : [
        6422
    ], 
    "levels" : [
        {
            "active" : "true", 
            "level" : 3, 
            "actions" : [
                {
                    "isActive" : "true"
                }]
        }]
}

x = flatten(d)

x = json_normalize(x)

print(x)

从列 headers 中删除整数列表键

Remove integer list keys from column headers

python

pandas

json-normalize