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You're reading from  Developing Kaggle Notebooks

Product typeBook
Published inDec 2023
Reading LevelIntermediate
PublisherPackt
ISBN-139781805128519
Edition1st Edition
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Gabriel Preda
Gabriel Preda
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Gabriel Preda

Dr. Gabriel Preda is a Principal Data Scientist for Endava, a major software services company. He has worked on projects in various industries, including financial services, banking, portfolio management, telecom, and healthcare, developing machine learning solutions for various business problems, including risk prediction, churn analysis, anomaly detection, task recommendations, and document information extraction. In addition, he is very active in competitive machine learning, currently holding the title of a three-time Kaggle Grandmaster and is well-known for his Kaggle Notebooks.
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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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Developing Kaggle Notebooks
Published in: Dec 2023Publisher: PacktISBN-13: 9781805128519

Author (1)

author image
Gabriel Preda

Dr. Gabriel Preda is a Principal Data Scientist for Endava, a major software services company. He has worked on projects in various industries, including financial services, banking, portfolio management, telecom, and healthcare, developing machine learning solutions for various business problems, including risk prediction, churn analysis, anomaly detection, task recommendations, and document information extraction. In addition, he is very active in competitive machine learning, currently holding the title of a three-time Kaggle Grandmaster and is well-known for his Kaggle Notebooks.
Read more about Gabriel Preda