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The Python Workshop Second Edition - Second Edition

You're reading from  The Python Workshop Second Edition - Second Edition

Product type Book
Published in Nov 2022
Publisher Packt
ISBN-13 9781804610619
Pages 600 pages
Edition 2nd Edition
Languages
Authors (5):
Corey Wade Corey Wade
Profile icon Corey Wade
Mario Corchero Jiménez Mario Corchero Jiménez
Profile icon Mario Corchero Jiménez
Andrew Bird Andrew Bird
Profile icon Andrew Bird
Dr. Lau Cher Han Dr. Lau Cher Han
Profile icon Dr. Lau Cher Han
Graham Lee Graham Lee
Profile icon Graham Lee
View More author details

Table of Contents (16) Chapters

Preface 1. Chapter 1: Python Fundamentals – Math, Strings, Conditionals, and Loops 2. Chapter 2: Python Data Structures 3. Chapter 3: Executing Python – Programs, Algorithms, and Functions 4. Chapter 4: Extending Python, Files, Errors, and Graphs 5. Chapter 5: Constructing Python – Classes and Methods 6. Chapter 6: The Standard Library 7. Chapter 7: Becoming Pythonic 8. Chapter 8: Software Development 9. Chapter 9: Practical Python – Advanced Topics 10. Chapter 10: Data Analytics with pandas and NumPy 11. Chapter 11: Machine Learning 12. Chapter 12: Deep Learning with Python 13. Chapter 13: The Evolution of Python – Discovering New Python Features 14. Index 15. Other Books You May Enjoy

Null values

You need to do something about the null values. They will break machine learning algorithms (see Chapter 11, Machine Learning) that rely on numerical values as input. There are several popular choices when dealing with null values:

  • Eliminate the rows. This is a respectable approach if null values are a very small percentage – that is, around 1% of the total dataset.
  • Replace the null value with a significant value, such as the median or the mean. This is a great approach if the rows are valuable, and the column itself is reasonably balanced.
  • Replace the null value with the most likely value, perhaps a 0 or 1. This is preferable to averages when the median or mean might be unrealistic based on other factors.

Note

Mode is the official term for the value that occurs the greatest number of times.

As you can see, which option you choose depends on the data. That’s a general theme that rings true for data science: no one method fits all...

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