python - 如何将熊猫数据框转换为嵌套的 json

问题描述

目前有一个包含笔记本电脑信息的数据框，目的是将数据转换为嵌套的 json 结构。由于笔记本电脑的品牌、价格和重量是相关信息，因此想将它们归为笔记本电脑字段下。任何有关如何转换数据帧的指针将不胜感激。

data frame

Target json structure

标签： pythonpython-3.xpandasdataframe

考虑df：

In [2729]: df = pd.DataFrame({'Store code':[1, 12, 132], 'Laptop brand':['Lenovo', 'Apple', 'HP'], 'Laptop price':[1000, 2000, 1200], 'Laptop weight':[1.2, 1.5, 1.4], 'star':[3, 5, 4]})

In [2730]: df
Out[2730]: 
   Store code Laptop brand  Laptop price  Laptop weight  star
0           1       Lenovo          1000            1.2     3
1          12        Apple          2000            1.5     5
2         132           HP          1200            1.4     4

df._to_dict与一起使用orient='records'：

In [2734]: x = df.to_dict('records') # Create a list of dicts from df
In [2738]: l = [] # Empty list for storing your output

In [2763]: for i in x: # Iterate every item in list of dicts
      ...:     d = {}
      ...:     d1 = {}
      ...:     for k,v in i.items(): # Iterate each individual dict
      ...:         if 'Laptop' in k: # Check if word `Laptop` is present in key 
      ...:             d1[k] = v     # If yes, create a separate dict for all laptop keys
      ...:         else:
      ...:             d[k] = v      
      ...:     d['Laptop'] = [d1]    # Add another key `Laptop` which holds a `list` of dicts of Laptop
      ...:     l.append(d)           # Append this dict in list
      ...:

输出：

In [2774]: print(json.dumps(l, indent=2))
[
  {
    "Store code": 1,
    "star": 3,
    "Laptop": [
      {
        "Laptop brand": "Lenovo",
        "Laptop price": 1000,
        "Laptop weight": 1.2
      }
    ]
  },
  {
    "Store code": 12,
    "star": 5,
    "Laptop": [
      {
        "Laptop brand": "Apple",
        "Laptop price": 2000,
        "Laptop weight": 1.5
      }
    ]
  },
  {
    "Store code": 132,
    "star": 4,
    "Laptop": [
      {
        "Laptop brand": "HP",
        "Laptop price": 1200,
        "Laptop weight": 1.4
      }
    ]
  }
]

python - 如何将熊猫数据框转换为嵌套的 json

问题描述

解决方案

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