我有一个从SalesForce（SOQL）查询返回的JSON文件，如下例所示，我想使用“json_normalize”来转换pandas dataFrame。
以open（'SOQL_RESULT.json'）作为data_file： data = json.load（data_file）
df = json_normalize（data）
SOQL_RESULT.json 文件：
[
{
"attributes": {
"type": "Opp_Product_Item__c",
"url": "/services/data/v38.0/sobjects/Opp_Product_Item__c/a0L40000007M7ViEAK"
},
"Id": "a0L40000007M7ViEAK",
"Name": "OPI-273731",
"Opportunity__c": "0064000000LlgMZAAZ",
"Opportunity_Solution__c": "a0M400000038XGeEAM",
"Product__c": "01t400000013pTyAAI",
"Product_Sales_Team__r": {
"totalSize": 3,
"done": true,
"records": [
{
"attributes": {
"type": "Product_Sales_Team__c",
"url": "/services/data/v38.0/sobjects/Product_Sales_Team__c/a0X40000001xZfLEAU"
},
"Id": "a0X40000001xZfLEAU",
"Name": "PIT-120844",
"Team_Role__c": "Specialist - CPS",
"Access__c": "Read/Write",
"Product__c": "a0L40000007M7ViEAK"
},
{
"attributes": {
"type": "Product_Sales_Team__c",
"url": "/services/data/v38.0/sobjects/Product_Sales_Team__c/a0X40000001xZfQEAU"
},
"Id": "a0X40000001xZfQEAU",
"Name": "PIT-120845",
"Team_Role__c": "CSE",
"Access__c": "Read/Write",
"Product__c": "a0L40000007M7ViEAK"
},
{
"attributes": {
"type": "Product_Sales_Team__c",
"url": "/services/data/v38.0/sobjects/Product_Sales_Team__c/a0X40000001xdkbEAA"
},
"Id": "a0X40000001xdkbEAA",
"Name": "PIT-121462",
"Team_Role__c": "CSE - Collaboration",
"Access__c": "Read",
"Product__c": "a0L40000007M7ViEAK"
}
]
}
},
{
"attributes": {
"type": "Opp_Product_Item__c",
"url": "/services/data/v38.0/sobjects/Opp_Product_Item__c/a0L40000009fnUPEAY"
},
"Id": "a0L40000009fnUPEAY",
"Name": "OPI-372996",
"Opportunity__c": "0064000000QlQmsAAF",
"Opportunity_Solution__c": "a0M40000004IyUqEAK",
"Product__c": "01t400000013pTdAAI",
"Product_Sales_Team__r": {
"totalSize": 1,
"done": true,
"records": [
{
"attributes": {
"type": "Product_Sales_Team__c",
"url": "/services/data/v38.0/sobjects/Product_Sales_Team__c/a0X40000004N1LlEAK"
},
"Id": "a0X40000004N1LlEAK",
"Name": "PIT-150866",
"Team_Role__c": "CSE",
"Access__c": "Read/Write",
"Product__c": "a0L40000009fnUPEAY"
}
]
}
}
]
但不是在 Product_sales_team __。r.records列中有一行嵌套数据，而不是这样：
Id Name Opportunity_Solution__c ... Product_Sales_Team__r.records
a... OP... a0M... [{'attributes': {'type': 'Product_Sales_Team__c', …
a... OP... a0M... [{'attributes': {'type': 'Product_Sales_Team__c', …
我想在Product_Sales_Team__r下添加3个新列（Team_Role__c，Acces__c和Product__c）。记录在最终的dataFrame中。
我尝试过：
df = json_normalize(data, 'Product_Sales_Team__r[records]', ['Id'], ['Name'], ['Opportunity__c'], record_prefix='Product_Sales_Team__r_records_Name')
但它没有用，基于Google的例子和官方的“json_normalize”文档，我不明白为什么？
以下是所需数据框架的外观：
Id Name Opportunit... Team_Role__c Acces__c Product__c
a1... OP... a0M... A... B... P1...
a1... OP... a0M... A... B... P2...
a1... OP... a0M... A... B... P3...
a2... OP... a0M... A... B... P1...
a2... OP... a0M... A... B... P2...
a2... OP... a0M... A... B... P3...
...
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肯