I tried different ways to get this done, but unable to do so. Please help here. I am trying to explode a nested json list using python pd.json_normalize. After exploding the output is coming in two rows causing duplicate PKeys.…
I hace a big json file data and I want to convert it in to tabular form. I am trying to flatten the data in to dataframe using json_nomalise. so Far I have this : code so far I want…
I am trying to create a dataframe from nested json file but running into trouble. [ { "rec_id": "1", "user": { "id": "12414", "name": "Steve" }, "addresses": [ { "address_type": "Home", "street1": "100 Main St", "street2": null, "city": "Chicago" },…
I have this JSON list in Python: [{'id': 'TC2-FFA', 'shortCode': 'TC2-FFA', 'dataSet': {'datumPrecision': 2, 'id': 'TC2_37', 'shortCode': 'TC2_37', 'shortDescription': 'Clean Continent to US Atlantic coast', 'displayGroup': 'BCTI', 'datumUnit': 'Worldscale', 'data': [{'value': 156.11, 'date': '2023-03-06'}], 'apiIdentifier': 'RDSX9KRCHQI9TVGID5O7XQGBP1KKBZ0F'}, 'datumUnit': 'WS', 'datumPrecision': 3,…
I have a data structure which is a very complex/nested JSON. After reading other solutions on SO, I am comfortable with the fact that I may need to make multiple DFs and merge them together (e.g json_normalize with multiple record…
I need some help on using json_normalizer to create multiple subcolumns from main columns ? The below code is able to generate an output file but its puts everything in one column however i need something seperate columns with heading…
I've been using pandas' json_normalize for a bit but ran into a problem with specific json file, similar to the one seen here: https://github.com/pandas-dev/pandas/issues/37783#issuecomment-1148052109 I'm trying to find a way to retrieve the data within the Ats -> Ats dict…
I have a script that collects JSON data from Twitter's API. This script collects data and parses it with jq every minute. This data gets collected into a single file that ends up looking like the following: [ {"text": "Tweet…