the json object in figure - depicts fairly nested structure that contains values of stringnumericand array type json also supports objectsbooleansand other data types as values as well the following snippet reads the contents of the file and then utilizes json loads(utility to parse and convert it into standard python dict json_filedata open(file_nameread(json_data json loads(json_filedatajson_data is python dict with keys and values of the json file parsed and type casted as python data types the json library also provides utilities to write back python dictionaries as json files with capabilities of error checking and typecasting the output of the previous operation is as follows outer_col_ nested_inner_col_ val_ nested_inner_col_ nested_inner_col_ val_ nested_inner_col_ outer_col_ inner_col_ outer_col_ before we move on to our next formatit is worth noting that pandas also provides utilities to parse jsons the pandas read_json(is very powerful utility that provides multiple options to handle jsons created in different styles figure - depicts sample json representing multiple data pointseach with two attributes listed as col_ and col_