Handle deeply nested data

Last exercise, you flattened data nested down one level. Here, you'll unpack more deeply nested data.

The categories attribute in the Yelp API response contains lists of objects. To flatten this data, you'll employ json_normalize() arguments to specify the path to categories and pick other attributes to include in the data frame. You should also change the separator to facilitate column selection and prefix the other attributes to prevent column name collisions. We'll work through this in steps.

pandas (as pd) and json_normalize() have been imported. JSON-formatted Yelp data on cafes in NYC is stored as data.

Use json_normalize() to flatten records under the businesses key in data, setting underscores (_) as separators.

Exercise

Handle deeply nested data

Instructions 1/3