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Developing Kaggle Notebooks

You're reading from   Developing Kaggle Notebooks Pave your way to becoming a Kaggle Notebooks Grandmaster

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781805128519
Length 370 pages
Edition 1st Edition
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Author (1):
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Gabriel Preda Gabriel Preda
Author Profile Icon Gabriel Preda
Gabriel Preda
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Table of Contents (14) Chapters Close

Preface 1. Introducing Kaggle and Its Basic Functions FREE CHAPTER 2. Getting Ready for Your Kaggle Environment 3. Starting Our Travel – Surviving the Titanic Disaster 4. Take a Break and Have a Beer or Coffee in London 5. Get Back to Work and Optimize Microloans for Developing Countries 6. Can You Predict Bee Subspecies? 7. Text Analysis Is All You Need 8. Analyzing Acoustic Signals to Predict the Next Simulated Earthquake 9. Can You Find Out Which Movie Is a Deepfake? 10. Unleash the Power of Generative AI with Kaggle Models 11. Closing Our Journey: How to Stay Relevant and on Top 12. Other Books You May Enjoy
13. Index

Extracting meaningful information from passenger names

We continue now with our analysis, including analyzing the passengers’ names to extract meaningful information. As you will remember from the beginning of this chapter, the Name column also contains some additional information. After our preliminary visual analysis, it became apparent that all names follow a similar structure. They begin with a Family Name, followed by a comma, then a Title (short version, followed by a period), then a Given Name, and, in cases where a new name was acquired through marriage, the previous or Maiden Name. Let’s process the data to extract this information. The code to extract this information will be:

def parse_names(row):
    try:
        text = row["Name"]
        split_text = text.split(",")
        family_name = split_text[0]
        next_text = split_text[1]
        split_text = next_text.split(".")
        title =  (split_text[0] + ".&quot...
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