This article is part of a series of practical guides for using the Python data processing library pandas. To see view all the available parts, click here.
When we are working with data in software development or when the data comes from APIs, it is often not provided in a tabular form. Instead it is provided in some combination of key-value stores and arrays broadly denoted as JavaScript Object Notation (JSON). So how do we read this type of non-tabular data into a tabular format like a pandas DataFrame?
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