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Simplifying Data Preprocessing with ColumnTransformer in Python: A Step-by-Step Guide
Data Analysis   Data Science   Latest   Machine Learning

Simplifying Data Preprocessing with ColumnTransformer in Python: A Step-by-Step Guide

Last Updated on September 3, 2024 by Editorial Team

Author(s): Souradip Pal

Originally published on Towards AI.

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Imagine you’re in a busy kitchen, trying to prepare a gourmet meal. You’ve got various ingredients laid out, each needing a different cooking method β€” some need boiling, others frying, and a few should be baked. Now, what if you had to manage all of this without a recipe or a proper plan? It would be a chaotic mess, right? That’s precisely how data preprocessing feels when you’re dealing with different data types and multiple encoders β€” each requiring its own special treatment.

But, just like how a well-organized kitchen can turn chaos into culinary art, Python’s ColumnTransformer can simplify your data preprocessing tasks, turning a tangled mess into a streamlined process. In this blog, we'll explore how to handle data without ColumnTransformerβ€”the β€˜Traditional’ wayβ€”and then see how the magic of ColumnTransformerβ€”the β€˜Smart’ wayβ€”can make our life so much easier. Along the way, we’ll work with a dummy dataset to make everything crystal clear. Ready to transform your data game? Let’s dive in!

Left: Before ColumnTransformer, Right: After ColumnTransformer. Source: Image generated by Dall-E

Before we get into the wonders of ColumnTransformer, let’s look at how we traditionally handle preprocessing when working… Read the full blog for free on Medium.

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