I got stuck converting a especific dictionary to a pandas dataframe - pandas

Question

I have a dictionary and I got stuck while trying to convert to a pandas dataframe.
It's a result of scoring an IBM ML model. The result comes in this format and I would like to transform this dictionary to a pandas dataframe in order to merge later with the original dataframe that was scored.
Dictionary:
{'predictions': [{'fields': ['prediction', 'probability'], 'values': [['Creditworthy', [0.5522992460276774, 0.4477007539723226]]]}]}
image of the code which generated this dictionary
I would like a pandas dataframe like this:
index predictions prediction probability
0 Creditworthy 0.552299 0.447701

Answer 1

Assume that the source dictionary is in value named dct.
Start from reading column names:
cols = dct['predictions'][0]['fields']
Then create DataFrame in a form which can be read from this dictionary:
df = pd.DataFrame(dct['predictions'][0]['values'],
columns=['predictions', 'val'])
For the time being, values are in val column, as a list:
predictions val
0 Creditworthy [0.5522992460276774, 0.4477007539723226]
Then break val column into separate columns, setting at the same time
proper column names (read before):
df[cols] = pd.DataFrame(df.val.values.tolist())
And the only thing to do is to drop val columns:
df.drop(columns=['val'], inplace=True)
The result is:
predictions prediction probability
0 Creditworthy 0.552299 0.447701
Just as it should be.