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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
Languages
Tools
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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

Starbucks in the World

We start the analysis of Starbucks Locations Worldwide dataset with a detailed exploratory data analysis (EDA) in the notebook Starbucks Location Worldwide - Data Exploration. The tools used in this dataset are imported from data_quality_stats and from plot_style_utils utility scripts. Before starting our analysis, it is important to explain that the dataset used for this analysis is from Kaggle and was collected 6 years ago. Meantime, Starbucks business expanded very much and therefore the number of shops, the geographical distribution of the shops, all this information is not up to date.

Preliminary data analysis

The dataset has 25,600 rows, with only 1 latitude and longitude values missing, 2 Street Addresses, 15 Cities. The fields that have the most missing data are Postcode (5.9%) and Phone Number (26.8%). In Figure 3.16 we can see few a sample of the data.

Figure 4.16. First rows of Starbucks dataset

Looking to the most frequent values report, we can learn...

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