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Python Feature Engineering Cookbook

You're reading from   Python Feature Engineering Cookbook A complete guide to crafting powerful features for your machine learning models

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835883587
Length 396 pages
Edition 3rd Edition
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Author (1):
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Soledad Galli Soledad Galli
Author Profile Icon Soledad Galli
Soledad Galli
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Toc

Table of Contents (14) Chapters Close

Preface 1. Chapter 1: Imputing Missing Data FREE CHAPTER 2. Chapter 2: Encoding Categorical Variables 3. Chapter 3: Transforming Numerical Variables 4. Chapter 4: Performing Variable Discretization 5. Chapter 5: Working with Outliers 6. Chapter 6: Extracting Features from Date and Time Variables 7. Chapter 7: Performing Feature Scaling 8. Chapter 8: Creating New Features 9. Chapter 9: Extracting Features from Relational Data with Featuretools 10. Chapter 10: Creating Features from a Time Series with tsfresh 11. Chapter 11: Extracting Features from Text Variables 12. Index 13. Other Books You May Enjoy

Automating the datetime feature extraction with Feature-engine

feature-engine is a Python library for feature engineering and selection that is well suited to working with pandas DataFrames. The DatetimeFeatures() class can extract features from date and time automatically by using pandas’ dt under the hood. DatetimeFeatures() allows you to extract the following features:

  • Month
  • Quarter
  • Semester
  • Year
  • Week
  • Day of the week
  • Day of the month
  • Day of the year
  • Weekend
  • Month start
  • Month end
  • Quarter start
  • Quarter end
  • Year start
  • Year end
  • Leap year
  • Days in a month
  • Hour
  • Minute
  • Second

In this recipe, we will automatically create features from date and time by utilizing feature-engine.

How to do it...

To showcase feature-engine’s functionality, we’ll create a sample DataFrame with a datetime variable:

  1. Let’s begin by importing pandas and DatetimeFeatures():
    import pandas...
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