Ingesting JSON data with pandas

When developing a data pipeline, you may have to work with non-tabular data and data sources, such as APIs or JSON files. In this exercise, we'll practice extracting data from a JSON file using pandas.

pandas has been imported as pd, and the JSON file you'll ingest is stored at the path "testing_scores.json".

This exercise is part of the course

ETL and ELT in Python

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Exercise instructions

Update the extract() function read a JSON file into a pandas DataFrame, orienting by records.
Pass the path testing_scores.json to the extract() function, and store the output to a variable called raw_testing_scores.
Print the head of the raw_testing_scores DataFrame.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

def extract(file_path):
  # Read the JSON file into a DataFrame
  return pd.____(____, orient="____")

# Call the extract function with the appropriate path, assign to raw_testing_scores
____

# Output the head of the DataFrame
print(raw_testing_scores.____())

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