How to flatten nested json that has dict in a column after using json normalize?

Question

This is the flattened version of the column. I still need the keys as column titles for the dataframe and the values as values for the corresponding column.

reaction
{ "veddra_term_code": "99026", "veddra_version": "3", "veddra_term_name": "Tablets, Abnormal" }

I want my data to look like this so I can add it to the dataframe.

veddra_term_code    veddra_version  veddra_term_name
99026                       3            'Tablets, Abnormal'

Very similar to https://stackoverflow.com/questions/38231591/splitting-dictionary-list-inside-a-pandas-column-into-separate-columns?noredirect=1&lq=1 — Nick ODell, Jan 16 '21 at 06:45

score 0 · Answer 1 · answered Jan 15 '21 at 23:22

Use f-strings. Theyre made for creating strings formatted like you want:

d = { "veddra_term_code": "99026", "veddra_version": "3", "veddra_term_name": "Tablets, Abnormal" }
s = f'veddra_term_code veddra_version veddra_term_name {d["veddra_term_code"]} {d["veddra_version"]} \'{d["veddra_term_name"]}\''
print(s) # prints veddra_term_code veddra_version veddra_term_name 99026 3 'Tablets, Abnormal'

How to flatten nested json that has dict in a column after using json normalize?

1 Answers1