How to perform One-Hot Encoding using sklearn?

by | Nov 16, 2022 | Data Preprocessing, Machine Learning Using Python, Python Scikit-learn

What is One-Hot Encoding?

Let’s say a column in a dataset contains categorical values. There are three different values in the categorical column. Let’s say, these values are “A”, “B”, and “C”. If we perform One Hot Encoding on the data of the column, then three different columns will be added to the dataset, as there are three different values for the column. Let’s call these columns “A”, “B”, and “C.” Now, rows that have “A” in the original column, will have 1 in the “A” column, and 0s in the “B” and “C” columns.

One-Hot Encoding Using Sklearn-1

Similarly, rows that have “B” in the original column, will have 1 in the “B” column of the One Hot encoded table. And columns “A” and “C” will contain 0s for those rows.

If we look closely, we do not need to add three columns in the One-Hot Encoded table. Adding two columns will be sufficient. Rows that have 0s in both the “A” and “B” columns, will definitely have 1 in the “C” column. So, adding only columns “A” and “B” will be sufficient in this case.

One-Hot Encoding Using Sklearn-2

How to perform One Hot Encoding using sklearn?

Let’s read the titanic dataset. The dataset contains various information, such as age, gender, embark town of the passengers, …

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Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

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