KeyError: "Key 'fields' not found. If specifying a record_path, all elements of data should have the path."

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I am getting very nested json for different items through an API and am then trying to convert some of the received information into a dataframe.

I have worked with this line to get the dataframe I want:

 df = pd.json_normalize(result, record_path=['fields'],errors='ignore')

This works sometimes, but other times I either get a KeyError for the record-path:

KeyError: "Key 'fields' not found. If specifying a record_path, all elements of data should have the path."

I assume that this is because the json I receive is not always exactly the same but can vary according to the type of item that information about is requested.

My question now is, if there is a way to skip data which doesn't have any of these keys? Or if there are other options to ignore the data that doesn't have those keys in it?

pandas python json
1 Answers

Thanks for the well written question. To do this, you want to learn about "Exception Handling".

Its worth learning a bit more about it, but here is the tl/dr:

try:
    df = pd.json_normalize(result, record_path=['fields'],,errors='ignore')
except KeyError as e:
    print(f"Unable to normalize json: {json.dumps(result, indent=4)}")
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