Return left.assign(key=1).merge(right.assign(key=1), on='key', how='outer').drop('key', 1)ĭf = cross_join(df, to_frame(data, prev_key + '.' + key))ĭf = ncat(, prev_key)])ĭf = pandas.DataFrame(, This is an older question, but I struggled the entire night to get a satisfactory result for a similar situation, and I came up with this: import json Please scroll down for the newer, faster solution Note that this is just the short version. The desired output should be something like this: company_number, address_line_1, locality, country_of_residence, kind,ġ2345678, Address 1, Henley-On-Thamed, England, individual-person-with-significant-control I know that this is easy to accomplish with pandas module but I am not familiar with it. "self": "/company/12345678/persons-with-significant-control/individual/bIhuKnFctSnjrDjUG8n3NgOrl" "kind": "individual-person-with-significant-control", I have a large nested JSON file (1.4GB) and I would like to make it flat and then convert it to a CSV file. I tried several solutions but I couldn't solve my problem.
I know this question has been asked many times.
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