根據條件python將JSON文件中的數據賦值給一個變量

Question

我正在嘗試根據日期代表的季度從 JSON 文件中獲取數據。 我的目標是將數據分配給一個變量，所以我應該有 Q1、Q2、Q3、Q4 變量來保存數據。 下面是JSON：

{
    "lastDate":{
        "0":"2022Q4",
        "1":"2022Q4",
        "2":"2022Q4",
        "7":"2022Q4",
        "8":"2022Q4",
        "9":"2022Q4",
        "18":"2022Q3",
        "19":"2022Q3",
        "22":"2022Q3",
        "24":"2022Q2"
    },
    "transactionType":{
        "0":"Sell",
        "1":"Automatic Sell",
        "2":"Automatic Sell",
        "7":"Automatic Sell",
        "8":"Sell",
        "9":"Automatic Sell",
        "18":"Automatic Sell",
        "19":"Automatic Sell",
        "22":"Automatic Sell",
        "24":"Automatic Sell"
    },
    "sharesTraded":{
        "0":"20,200",
        "1":"176,299",
        "2":"8,053",
        "7":"167,889",
        "8":"13,250",
        "9":"176,299",
        "18":"96,735",
        "19":"15,366",
        "22":"25,000",
        "24":"25,000"
    }
}

現在，如果我嘗試使用以下代碼：

import json

data = json.load(open("AAPL22data.json"))

Q2data = [item for item in data if '2022Q2' in data['lastDate']]
print(Q2data)

我理想中的output應該是：

{
    "lastDate":{
        "24":"2022Q2"
    },
    "transactionType":{
        "24":"Automatic Sell"
    },
    "sharesTraded":{
        "24":"25,000"
    }
}

然后對其他區域重復相同的結構。 但是，我當前的 output 給了我“[]”

Answer 1

使用 pandas，您可以閱讀此嵌套字典並將其轉換為表格表示形式。 那么你需要的聚合就變得很自然了。

import pandas as pd 

sample_dict = {
    "lastDate":{
        "0":"2022Q4",
        "1":"2022Q4",
        "2":"2022Q4",
        "7":"2022Q4",
        "8":"2022Q4",
        "9":"2022Q4",
        "18":"2022Q3",
        "19":"2022Q3",
        "22":"2022Q3",
        "24":"2022Q2"
    },
    "transactionType":{
        "0":"Sell",
        "1":"Automatic Sell",
        "2":"Automatic Sell",
        "7":"Automatic Sell",
        "8":"Sell",
        "9":"Automatic Sell",
        "18":"Automatic Sell",
        "19":"Automatic Sell",
        "22":"Automatic Sell",
        "24":"Automatic Sell"
    },
    "sharesTraded":{
        "0":"20,200",
        "1":"176,299",
        "2":"8,053",
        "7":"167,889",
        "8":"13,250",
        "9":"176,299",
        "18":"96,735",
        "19":"15,366",
        "22":"25,000",
        "24":"25,000"
    }
}

print(pd.DataFrame.from_dict(sample_dict))

回報

Output:

   lastDate transactionType sharesTraded
0    2022Q4            Sell       20,200
1    2022Q4  Automatic Sell      176,299
2    2022Q4  Automatic Sell        8,053
7    2022Q4  Automatic Sell      167,889
8    2022Q4            Sell       13,250
9    2022Q4  Automatic Sell      176,299
18   2022Q3  Automatic Sell       96,735
19   2022Q3  Automatic Sell       15,366
22   2022Q3  Automatic Sell       25,000
24   2022Q2  Automatic Sell       25,000

那么一個簡單的group_by就可以解決問題。

Answer 2

使用字典理解：

import json

my_json = """{
    "lastDate":{
        "0":"2022Q4",
        "1":"2022Q4",
        "2":"2022Q4",
        "7":"2022Q4",
        "8":"2022Q4",
        "9":"2022Q4",
        "18":"2022Q3",
        "19":"2022Q3",
        "22":"2022Q3",
        "24":"2022Q2"
    },
    "transactionType":{
        "0":"Sell",
        "1":"Automatic Sell",
        "2":"Automatic Sell",
        "7":"Automatic Sell",
        "8":"Sell",
        "9":"Automatic Sell",
        "18":"Automatic Sell",
        "19":"Automatic Sell",
        "22":"Automatic Sell",
        "24":"Automatic Sell"
    },
    "sharesTraded":{
        "0":"20,200",
        "1":"176,299",
        "2":"8,053",
        "7":"167,889",
        "8":"13,250",
        "9":"176,299",
        "18":"96,735",
        "19":"15,366",
        "22":"25,000",
        "24":"25,000"
    }
}"""

data = json.loads(my_json)

var = "24" #This corresponds to 2022 Q2 in your example

data = {k:{var: v[var]} for k, v in data.items()}
data = json.dumps(data, indent = 2)

print(data)

Output：

{
  "lastDate": {
    "24": "2022Q2"
  },
  "transactionType": {
    "24": "Automatic Sell"
  },
  "sharesTraded": {
    "24": "25,000"
  }
}

Answer 3

感謝@FrancoMilanese 提供有關 Pandas group_by的信息，以下是答案：

import json
import pandas as pd 

data = json.load(open("AAPL22data.json"))

df = pd.DataFrame.from_dict(data)

q2df = df.groupby('lastDate')

q2df.get_group('2022Q2') #change '2022q2' for others & assign to a different variable