Json.NET Custom Serializing

I’m trying to serialize a array to become object format. Example: { “country”: “USA”. “date”: “2019-6-30”, “Speaker” : [ { “id”: “name”, “value”: “Tiger” }, { “id”: “age”, “value”: “35” }, { “id”: “topic”, “value”: “.NET” }, ] } want to convert to: { “country”: “USA”. “date”: “2019-6-30”, “name”, “Tiger”, “age”, 35, “topic” “.NET” }…

Get value JSON to create a nested in golang

I’m trying to create dynamically nested json from value FIELD_QUESTION and FIELD_ANSWER in golang. my result json { “jumlahdata”: 2, “result”: [ { “QUICK_DATA_H_ID”: “1”, “ORDER_TRX_H_ID”: “1”, “FIELD_QUESTION”: “FULLNAME”, “FIELD_ANSWER”: “RUBEN”, “DTM_CRT”: “2019-08-28T16:25:15.757Z” }, { “QUICK_DATA_H_ID”: “2”, “ORDER_TRX_H_ID”: “1”, “FIELD_QUESTION”: “ALAMAT_KTP”, “FIELD_ANSWER”: “jalandisana”, “DTM_CRT”: “2019-08-28T16:25:15.757Z” } ], “statusdb”: 200, “statusload”: 200, “statusquery”: 200 } expected…

Read CSV with json feature in Pandas

I am trying to read a large CSV which includes json features (location here). For the first, say 100 lines, the file looks like this: Time,location,labelA,labelB 2019-09-10,{“lng”:12.9,”alt”:413.0,”time”:”2019-09-10″,”error”:7.0,”lat”:17.8},nan,nan I follow this question to parse the location column. The solution basically defines a helper as: def CustomParser(data): import json j1 = json.loads(data) return j1 and then df=pd.read_csv(‘data.csv’,…