Why read Cleaning Data for Effective Data Science?

Book cover of Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools

Book description

Think about your data intelligently and ask the right questions

Key Features Master data cleaning techniques necessary to perform real-world data science and machine learning tasks Spot common problems with dirty data and develop flexible solutions from first principles Test and refine your newly acquired skills through detailed exercises at…

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Why read it?

1 author picked Cleaning Data for Effective Data Science as one of their favorite books. Why do they recommend it?

Naomi R. Ceder

Author

I like this book not just because it’s a complete guide to the many ins and outs of data cleaning with Python, but also because David lays out the types of problems and the issues behind them. There are always trade-offs in data cleaning and this book lays out those trade-offs better than any other I’ve seen. This is one of the few books that as I go through it, I struggle to think of anything that could have been said better.

From Naomi's list on The best books to level up your Python skills.