Some of the most useful Pandas tricks. You Should Know
Although this format works well for storing and exchanging data, it needs to be converted into a tabular form for further analysis. You are likely to deal with 2 types of JSON structure, a JSON object or a list of JSON objects. In internal Python lingo, you are most likely to deal with a dict or a list of dicts.
A dictionary and a list of dictionaries (Image by author)
In this article, you’ll learn how to use Pandas’s built-in function
json_normalize() to flatten those 2 types of JSON into Pandas DataFrames. This article is structured as follows:
Please check out Notebook for the source code.
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Learn to group the data and summarize in several different ways, to use aggregate functions, data transformation, filter, map.