基于条件python将JSON文件中的数据分配给变量

bt1cpqcv 于 2022-12-05 发布在 Python

关注(0)|答案(3)|浏览(169)

我尝试根据日期代表的季度从JSON文件中获取数据。我的目标是将数据分配给一个变量，这样我就应该有Q1、Q2、Q3、Q4变量来保存数据。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"
    }
}

下面是一个例子：

import json

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

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

我的理想输出应该是：

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

然后对其他季度重复相同的结构。但是，我的当前输出给我“[ ]”

JSON

来源：https://stackoverflow.com/questions/74666206/assign-data-in-json-file-to-a-variable-based-on-condition-python

3条答案

按热度按时间

vh0rcniy1#

有了Pandas，你可以阅读这个嵌套的字典，并将它转换成一个表格表示，然后你所需要的聚合就变得相当自然了。

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))

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

那么一个简单的group_by就可以了。

赞(0）回复(0）举报 2022-12-05

5lwkijsr2#

使用 * 字典理解 *：
第一个
输出量：

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

赞(0）回复(0）举报 2022-12-05

ar7v8xwq3#

感谢@FrancoMilanese提供关于Pandasgroup_by的信息，下面是答案：

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

赞(0）回复(0）举报 2022-12-05

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基于条件python将JSON文件中的数据分配给变量

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