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Developing Kaggle Notebooks

You're reading from  Developing Kaggle Notebooks

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781805128519
Pages 370 pages
Edition 1st Edition
Languages
Author (1):
Gabriel Preda Gabriel Preda
Profile icon Gabriel Preda

Table of Contents (14) Chapters

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

Pubs in England

The dataset contains data about 51,566 pubs in England, including the pub name, the address, the postal code, the geographical position (both by easting and northing and by latitude and longitude) and the local authority. I created a Notebook, Every Pub in England – Data Exploration to investigate this data.

Data quality check

For the data quality check, we will use info() and describe() to get a first glimpse. Then, we can also use our custom data quality statistics functions. We saw in the previous chapter these functions, will not repeat here. Because we will keep using them, we will group them in a utility script. I called this utility script data_quality_stats and I defined in this module the functions missing_data, most_frequent_values and unique_values. To use the functions defined in this utility script, we need to first add it to the Notebook. From File menu, we select Add utility script menu item. Then, we add the import in one of the first Notebook cells...

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