Python application for flattening and mapping nested JSON keys

I am completely new to JSON and struggling with understanding the structure of a JSON file.

Here is an example of a JSON file I have:

{"employeeId":{"0":02100, "1":02101, "2":02102,... "1000000":021000000},
 "employeeName":{"0":"Smith", "1":"John", "2":"Mark",... "1000000":"Dave"},
 "employeeDept":{"0":"Work", "1":"Art", "2":"Mop",... "1000000":"Clean"},
 "employeeAddress":"0":"CA", "1":"TX", "2":"UT",... "1000000":"DC"}

I want to convert this JSON into a flattened format using Python. Each set of data should be mapped as follows:

{"employeeId": 02100,
 "employeeName":"Smith",
 "employeeDept":"Work",
 "employeeAddress":"CA"},

{"employeeId": 02101,
 "employeeName":"John",
 "employeeDept":"Art",
 "employeeAddress":"TX"},

{"employeeId": 02102,
 "employeeName":"Mark",
 "employeeDept":"Mop",
 "employeeAddress":"UT"},
.
.
.
{"employeeId": 021000000,
 "employeeName":"Dave",
 "employeeDept":"Clean",
 "employeeAddress":"DC"}

I attempted to achieve this using Python by first creating a sample object:

sample_object1 = {"employeeId":{"0":"02100", "1":"02101", "2":"02102", "1000000":"021000000"},
 "employeeName":{"0":"Smith", "1":"John", "2":"Mark", "1000000":"Dave"},
 "employeeDept":{"0":"Work", "1":"Art", "2":"Mop", "1000000":"Clean"},
 "employeeAddress":{"0":"CA", "1":"TX", "2":"UT", "1000000":"DC"}}

from pandas.io.json import json_normalize
json_normalize(sample_object1)

This resulted in the following output:


employeeAddress.0   employeeAddress.1   employeeAddress.1000000 employeeAddress.2   employeeDept.0  employeeDept.1  employeeDept.1000000    employeeDept.2  employeeId.0    employeeId.1    employeeId.1000000  employeeId.2    employeeName.0  employeeName.1  employeeName.1000000    employeeName.2
0   CA  TX  DC  UT  Work    Art Clean   Mop 02100   02101   021000000   02102   Smith   John    Dave    Mark
pythonjsondictionarykeyflat

Answer №1

Below is the solution provided:

details = {"studentId":{"0":"1066", "1":"1058", "2":"1047", "1000000":"1099"},
 "studentName":{"0":"Alice", "1":"Bob", "2":"Charlie", "1000000":"Daisy"},
 "studentSubject":{"0":"Math", "1":"Science", "2":"History", "1000000":"English"},
 "studentGrade":{"0":"A", "1":"B", "2":"C", "1000000":"A"}}

import pandas as pd
df = pd.DataFrame(details)
df.to_json(orient = "records")

Here is the expected outcome

'[{"studentId":"1066","studentName":"Alice","studentSubject":"Math","studentGrade":"A"},{"studentId":"1058","studentName":"Bob","studentSubject":"Science","studentGrade":"B"},{"studentId":"1099","studentName":"Daisy","studentSubject":"English","studentGrade":"A"},{"studentId":"1047","studentName":"Charlie","studentSubject":"History","studentGrade":"C"}]'

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