My data looks like this: Key1: [Key2:[{},{},...{}]] The code something like this: dict_={} dict_['Key2']=all_items dict_fin={} dict_fin['Ke1']=[dict_] df=pd.DataFrame(dict_fin) df.to_json(filepath, orient="records",lines=True) I would like to have saved json like this: { "Key1": [{"Key2" : [{},{},...,{}]}] } Instead, I get it like this:…
I have a dataframe which contains nested columns as below when converted in to json format. {"id" : 1, "address": {"adress1":"", "city" : "TX", "zip": "" }, "gender": "", "code": 999 } The dataframe is normalized and will be written…
I webscraped a site which has an url such as this: https://takipcimerkezi.net/services I tried to get every information of the table except "aciklama" This is my code : from bs4 import BeautifulSoup import requests import pandas as pd import numpy…
I have the following nested dictionary with lists inside: [{ "id": 467, "status": 2, "leavePeriod": { "owner": { "employeeNumber": "2620", "firstName": "fn_467", "lastName": "ln_467" }, "ownerId": 46, "leaves": [ { "leaveAccount": { "id": 1121, "name": "Vacation days 2021/2022", "url": "https://some_link/1121"…
It should be a simple line of code using pd.json_normalize function but it's working only with a single string and it's not batch processing my whole column Orginial dataframe df['addresses'][0] [{'addressLine1': '124 Main Street', 'addressLine2': '', 'addressLine3': '', 'city': 'Portland',…
I have an API with student data like this, for every student id there will be a corresponding API link with mark details. for example: https://api.school.com/2020/students.json { "Students": [ { "StudentName": "AAA", "Sid": 1020, "Saddress": "st.aaa", "Sdob": "10-11-1999" }, {…
I have data like this which represents hierarchical tree structure: [ { "level":0, "name":"python" }, { "level":1, "name":"food" }, { "level":2, "name":"banana" }, { "level":3, "name":"protein" }, { "level":2, "name":"apple" }, { "level":1, "name":"fuel" } ] I want to transform…
My part of code is js_file = response.text filename = [x for x in df['col1']] for names in filename: with open(names, 'w') as outfile: json.dump(js_file,outfile) What i need to do is to export to specific folder which doesn't exist and…
I wrote a script which updates some fields in a database via an API. fields = [{ "fieldId": "101", "fieldValues": [{"value": df["A"].item()}]}, { "fieldId": "102", "fieldValues": [{"value": df["B"].item()}]}, { "fieldId": "103", "fieldValues": [{"value": df["C"].item()}]}, { "fieldId": "104", "fieldValues": [{"value": df["D"].item()}]},…
I'm trying add a column to my dataframe that contains the information from the other columns as a json object My dataframe looks like this: col_1 col_2 1 1 2 2 I'm then trying to add the json column using…