QST:

[phan480]

QST:

[RamMarthi9]

Hi phan480,

Use this piece of code: I think this should help u. Ping me if this is working.
import pandas as pd

data = [{
"id": 1039835,
"status": "on_track",
"development_plan": {
"id": 23858,
"items": [{
"id": 176498,
"item_name": "itemname 1"
}, {
"id": 172450,
"item_name": "itemname 2"
}, {
"id": 172451,
"item_name": "itemname 3"
}
]
},
"user": {
"id": 714067
}
}
]

Extract data

records = []
for entry in data:
status = entry['status']
user_id = entry['user']['id']
development_plan_id = entry['development_plan']['id']
for item in entry['development_plan']['items']:
record = {
'id': item['id'],
'item_name': item['item_name'],
'development_plan_id': development_plan_id,
'status': status,
'user_id': user_id
}
records.append(record)

Create DataFrame

df = pd.DataFrame(records)

print(df)

I got the following result:
id item_name development_plan_id status user_id
0 176498 itemname 1 23858 on_track 714067
1 172450 itemname 2 23858 on_track 714067
2 172451 itemname 3 23858 on_track 714067

[phan480]

Thank you for your response, yes it works. But doesn't use the json_normalize functionality? I am using this function to parse a multitude of api's and their responses. I configure their record_path and meta data columns in configuration data.

I would like to avoid creating a unique way to parse every API.