Introduction to Categorical Data
Hello, Space Voyager! Today, we're venturing through a fascinating territory: Categorical Data Encoding! Categorical Data consist of groups or traits such as "gender", "marital status", or "hometown". We convert categories into numbers using Label and One-Hot Encoding techniques for our machine-learning mates.
Concept of Label Encoding
Label Encoding maps categories to numbers ranging from 0 through N-1, where N represents the unique category count. It's beneficial for ordered data like "Small", "Medium", and "Large".
To illustrate, here is a Python list of shirt sizes:
Python's Pandas library can be used to assign 0 to "Small", 1 to "Medium", and 2 to "Large":
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