I am trying to create a pandas multi-indexed DataFrame from a double-nested dictionary but am quite stumped as to how to do this.

As some background I have scraped some data from a website and put it into this nested dictionary form as I thought it would be easiest to work with (but I appear to be wrong :D)…

The nested dictionary currently looks like this and I want to put this into a DataFrame that has the ID of the fighter as the column so that in the case of multiple fighters, each column would represent a new fighter, the fight number (0 or 1 in this example as the first row index) with the inner level being the fight details (e.g., date, fighter weight etc).

{'ID': {0: {'date ↕': '2024-05-23',
   'Fighter Weight': '',
   'Opponent': 'fighter_1',
   'Opponent Weight': '',
   'w-l-d': ('11', '0', '0'),
   'result': 'VS',
   'rounds': '12'},
  1: {'date ↕': '2022-08-28',
   'Fighter Weight': '227¾',
   'Opponent': 'Fighter_2',
   'Opponent Weight': '211',
   'result': 'W-SD',
   'rounds': '12/12'}}}

On the initial run when I ran DataFrame.from_dict(data) this yields an output where the values of the DataFrame is the inner dictionary.

479205
0   {'date ↕': '2024-05-18', 'Fighter Weight': '',...
1   {'date ↕': '2023-10-28', 'Fighter 

If you think it would be better to store the data into something other than a nested dictionary then also please let me know as I am open to making changes to the scraper as well.

Thanks so much!