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’,…

How do you parse a nested JSON file like below using Processing JSON object?

How do you parse a nested JSON file like below using Processing JSON object? I am trying to figure out how to parse JSON that is multi-level. { “info”: { “description”: “COCO 2014 Dataset”, “url”: “http://cocodataset.org”, “version”: “1.0”, “year”: 2014, “contributor”: “COCO Consortium”, “date_created”: “2017/09/01” }, “images”: [ { “license”: 5, “file_name”: “COCO_train2014_000000057870.jpg”, “coco_url”: “http://images.cocodataset.org/train2014/COCO_train2014_000000057870.jpg”,…

jquery autocomplete with callback ajax json elasticsearch

When is make a response to Elasticsearch this is happening: http://localhost:9200/hobbie/_search?callback=jQuery112407134696443551507_1568816372627&term=hobby&_=1568816372628. I really don’t know why the callback is in the request. Those anyone knows what i did wrong? It would be a great help. $( function() { function log( message ) { $( “<div>” ).text( message ).prependTo( “#log” ); $( “#log” ).scrollTop( 0 );…

Unsorted list into nested json with children

I have an unsorted list (more precisley a list of LDAP DNs) like so: ou=org02,ou=org,dc=example,dc=com ou=org,dc=example,dc=com ou=org01,ou=org,dc=example,dc=com ou=suborg01,ou=org01,ou=org,dc=example,dc=com ou=suborg02,ou=org01,ou=org,dc=example,dc=com ou=org03,ou=org,dc=example,dc=com ou=subsuborg01,ou=suborg01,ou=org01,ou=org,dc=example,dc=com ou=suborg03,ou=org01,ou=org,dc=example,dc=com And i would like to transform this list into a nested json structure like so: { “key”: “ou=org,dc=example,dc=com”, “children”: [ { “key”: “ou=org01,ou=org,dc=example,dc=com” “children”: [ { “key”: “ou=suborg01,ou=org01,ou=org,dc=example,dc=com” “children”: [ { “key”: “ou=subsuborg01,ou=suborg01,ou=org01,ou=org,dc=example,dc=com”…