I have a json data (coming from mongodb) containing thousands of records (so an array/list of json object) with a structure like the below one for each object:
{
import pandas as pd
import json
data = '''
[
{
"id":1,
"first_name":"Mead",
"last_name":"Lantaph",
"email":"mlantaph0@opensource.org",
"gender":"Male",
"ip_address":"231.126.209.31",
"nested_array_to_expand":[
{
"property":"Quaxo",
"json_obj":{
"prop1":"Chevrolet",
"prop2":"Mercy Streets"
}
},
{
"property":"Blogpad",
"json_obj":{
"prop1":"Hyundai",
"prop2":"Flashback"
}
},
{
"property":"Yabox",
"json_obj":{
"prop1":"Nissan",
"prop2":"Welcome Mr. Marshall (Bienvenido Mister Marshall)"
}
}
]
}
]
'''
data = json.loads(data)
result = pd.json_normalize(data, "nested_array_to_expand",
['email', 'first_name', 'gender', 'id', 'ip_address', 'last_name'])
result
property json_obj.prop1 json_obj.prop2 \
0 Quaxo Chevrolet Mercy Streets
1 Blogpad Hyundai Flashback
2 Yabox Nissan Welcome Mr. Marshall (Bienvenido Mister Marshall)
email first_name gender id ip_address last_name
0 mlantaph0@opensource.org Mead Male 1 231.126.209.31 Lantaph
1 mlantaph0@opensource.org Mead Male 1 231.126.209.31 Lantaph
2 mlantaph0@opensource.org Mead Male 1 231.126.209.31 Lantaph
More information about json_normalize
:
https://pandas.pydata.org/docs/reference/api/pandas.json_normalize.html