使用 json_normalize 对带有嵌套数组的 json 进行规范化
我想规范化以下 JSON：
[
{
"studentId": 1,
"studentName": "James",
"schools": [
{
"schoolId": 1,
"classRooms": [
{
"classRoomId": {
"id": 1,
"floor": 2
}
},
{
"classRoomId": {
"id": 3
}
},
],
"teachers": [
{
"teacherId": 1,
"teacherName": "Tom"
},
{
"teacherId": 2,
"teacherName": "Sarah"
}
]
},
{
"schoolId": 2,
"classRooms": [
{
"classRoomId": {
"id": 4
}
}
],
"teachers": [
{
"teacherId": 1,
"teacherName": "Tom"
},
{
"teacherId": 2,
"teacherName": "Sarah"
},
{
"teacherId": 3,
"teacherName": "Tara"
}
]
}
]
}
]
我试过像这样使用 Pandas json_normalize 函数：
df1 = json_normalize(test1, ["schools","teachers"], ["studentId", "studentName",["schools","teachers"]])
df2 = json_normalize(test1, ["schools","classRooms"], ["studentId", "studentName",["schools","classRooms"]])
df = pd.concat([df1,df2],axis=1)
但这并没有给我我需要的结构。
它不必在 Pandas 中，Python 中的任何其他库或代码都可以。任何帮助都将不胜感激。谢谢你。
largeQ1回答
-
函数式编程
因为classRooms并teachers形成了 JSON 的两个不同子树，您将不得不解析它们两次：classrooms = pd.io.json.json_normalize(json_data, ['schools', 'classRooms'], meta=[ 'studentId', 'studentName', ['schools', 'schoolId']])teachers = pd.io.json.json_normalize(json_data, ['schools', 'teachers'], meta=[ 'studentId', ['schools', 'schoolId']])# Merge and rearrange the columns in the order of your sample outputclassrooms.merge(teachers, on=['schools.schoolId', 'studentId']) \ [['studentId', 'studentName', 'schools.schoolId', 'classRoomId.id', 'classRoomId.floor', 'teacherId', 'teacherName']]
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Python