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The Python Workshop Second Edition

You're reading from   The Python Workshop Second Edition Write Python code to solve challenging real-world problems

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781804610619
Length 600 pages
Edition 2nd Edition
Languages
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Authors (5):
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Mario Corchero Jiménez Mario Corchero Jiménez
Author Profile Icon Mario Corchero Jiménez
Mario Corchero Jiménez
Andrew Bird Andrew Bird
Author Profile Icon Andrew Bird
Andrew Bird
Corey Wade Corey Wade
Author Profile Icon Corey Wade
Corey Wade
Graham Lee Graham Lee
Author Profile Icon Graham Lee
Graham Lee
Dr. Lau Cher Han Dr. Lau Cher Han
Author Profile Icon Dr. Lau Cher Han
Dr. Lau Cher Han
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Toc

Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Python Fundamentals – Math, Strings, Conditionals, and Loops 2. Chapter 2: Python Data Structures FREE CHAPTER 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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