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  3. Introduction to Data Pipelines

Exercise

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".

Instructions

100 XP
  • 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.