將 CSV 數據轉換為嵌套 JSON

Question

我的任務是使用 python 將 csv 文件中的數據轉換為嵌套的 JSON 文件，用於 Z2567A5EC9705EB7AC2DZ98403 用法。 我試過這篇文章中的 Python 代碼。 所需的 output 將是一個member_id在 JSON 文件中顯示一次，與一個member_id下的tag_name相同。 問題是，當我嘗試僅使用member_id的groupby時，例如tag_name 'm1' 會在 'abc123' 下顯示多次。 如果我同時使用member_id和tag_name嘗試groupby ，則標簽“m1”和“m2”會出現兩次“abc123”。 我已經用谷歌搜索了一段時間，但大多數分辨率只針對一個嵌套（不確定我是否使用了正確的術語）。 請讓我知道是否有任何可能的方法來做到這一點。

示例代碼：

import json
import pandas as pd
df = pd.read_csv('../detail.csv', sep=',', header=0
                 , index_col=False
                 , dtype = {'member_id':str,'tag_name':str,'detail_name':str,'detail_value':str} )
group = df.groupby(['member_id','tag_name'])

finalList, finalDict = [], {}
for key, value in group:
    dictionary, dictionary1, dictList, dictList1 = {}, {}, [], []
    j = group.get_group(key).reset_index(drop=True)
    dictionary['member_id'] = j.at[0,'member_id']
    dictionary1['tag_name'] = j.at[0,'tag_name']
    
    for i in j.index:
        anotherDict = {}
        anotherDict['detail_name'] = j.at[i,'detail_name']
        anotherDict['detail_value'] = j.at[i,'detail_value']
        dictList1.append(anotherDict.copy())
        dictionary1['detail'] = dictList1 
     
    dictList.append(dictionary1)
    dictionary['tag'] = dictList
    finalList.append(dictionary)

json.dumps(finalList,ensure_ascii = False)

詳細信息。csv：

member_id, tag_name, detail_name, detail_value
-------------------------------------------------------
abc123, m1, Service_A, 20
abc123, m1, Service_B, 20
abc123, m2, Service_C, 10
xyz456, m3, Service A, 5

所需的 Output JSON：

{   "member_id": "abc123",
    "tag"：[ {"tag_name": "m1",
            "detail":[{ "detail_name": "Service_A",
                        "detail_value": "20"},
                    {   "detail_name": "Service_B",
                        "detail_value": "20"}]},
            {"tag_name": "m2",
            "detail":[{ "detail_name": "Service_C",
                        "detail_value": "10"}]}]},
{   "member_id": "xyz456",
    "tag"：[{"tag_name": "m3",
            "detail":[{ "detail_name": "Service_A",
                        "detail_value": "5"}]}]}

Answer 1

我不知道 pandas 函數允許直接實現這一點。 此外，您引入的密鑰不屬於您的初始 dataframe（ tag 、 detail ）。 因此，實施通用解決方案似乎很困難。

但是，如果您的列數不超過問題中所述的列數，則可以通過 dataframe 將 go 逐列分組：

result = []

for member_id, member_df in df.groupby('member_id'):
    member_dict = {'member_id': member_id}
    member_dict['tag'] = []
    for tag_name, tag_df in member_df.groupby('tag_name'):
        tag_dict = {'tag_name': tag_name}
        tag_dict['detail'] = []
        for detail_name, detail_df in tag_df.groupby('detail_name'):
            detail_dict = {'detail_name': detail_name}
            detail_dict['detail_value'] = detail_df.detail_value.mean() # should be only one value, taking 'mean' just in case
            tag_dict['detail'].append(detail_dict)
        member_dict['tag'].append(tag_dict)
    result.append(member_dict)

print(json.dumps(result, indent=4))

Output：

[
    {
        "member_id": "abc123",
        "tag": [
            {
                "tag_name": "m1",
                "detail": [
                    {
                        "detail_name": "Service_A",
                        "detail_value": 20.0
                    },
                    {
                        "detail_name": "Service_B",
                        "detail_value": 20.0
                    }
                ]
            },
            {
                "tag_name": "m2",
                "detail": [
                    {
                        "detail_name": "Service_C",
                        "detail_value": 10.0
                    }
                ]
            }
        ]
    },
    {
        "member_id": "xyz456",
        "tag": [
            {
                "tag_name": "m3",
                "detail": [
                    {
                        "detail_name": "Service A",
                        "detail_value": 5.0
                    }
                ]
            }
        ]
    }
]