Convert Json to table format

[python_student]

Use json_normalize for this.
Example.

import pandas as pd

lst = [
	{
		"id": "179328741654819",
		"t_values": [
			{
				"t_id": "963852456741",
				"value": "499.66",
				"date_timestamp": "2020-09-22T15:18:17",
				"type": "in"
			},
			{
				"t_id": "852951753456",
				"value": "1386.78",
				"date_timestamp": "2020-10-31T14:46:44",
				"type": "in"
			}
		]
	},
	{
		"id": "823971648264792",
		"t_values": [
			{
				"t_id": "753958561456",
				"value": "672.06",
				"date_timestamp": "2020-03-16T22:41:16",
				"type": "in"
			},
			{
				"t_id": "321147951753",
				"value": "773.88",
				"date_timestamp": "2020-05-08T18:29:31",
				"type": "out"
			},
			{
				"t_id": "258951753852",
				"value": "733.13",
				"date_timestamp": 'null',
				"type": "in"
			}
		]
	}
]

>>> df = pd.json_normalize(lst, meta=['id'], record_path='t_values')
>>> df
           t_id    value       date_timestamp type               id
0  963852456741   499.66  2020-09-22T15:18:17   in  179328741654819
1  852951753456  1386.78  2020-10-31T14:46:44   in  179328741654819
2  753958561456   672.06  2020-03-16T22:41:16   in  823971648264792
3  321147951753   773.88  2020-05-08T18:29:31  out  823971648264792
4  258951753852   733.13                 null   in  823971648264792

>>> df = df.reindex(['id', 't_id', 'value', 'date_timestamp', 'type'], axis=1)
>>> df
                id          t_id    value       date_timestamp type
0  179328741654819  963852456741   499.66  2020-09-22T15:18:17   in
1  179328741654819  852951753456  1386.78  2020-10-31T14:46:44   in
2  823971648264792  753958561456   672.06  2020-03-16T22:41:16   in
3  823971648264792  321147951753   773.88  2020-05-08T18:29:31  out
4  823971648264792  258951753852   733.13                 null   in

Thank you so much. This was I needed