September 2024
Beginner to intermediate
456 pages
11h 53m
English
Content preview from Python Data Cleaning and Preparation Best Practices
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10
Handling Categorical Features
Handling categorical features involves representing and processing information that isn’t inherently numerical. Categorical features are attributes that can take on a limited, fixed number of values or categories, and they often define distinct categories or groups within a dataset, such as types of products, genres of books, or customer segments. Effectively managing categorical data is crucial because most machine learning (ML) algorithms require numerical inputs.
In this chapter, we will cover the following topics:
- Label encoding
- One-hot encoding
- Target encoding (mean encoding)
- Frequency encoding
- Binary encoding
Technical requirements
The complete code for this chapter can be found in the following GitHub ...
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