ting massive amounts of data. But this data isn't valuable until someone analyzes it to gain insights that can be used to make decisions. That's why the US Bureau of Labor Statistics (BLS) predicts that the demand for data analysts will continue to grow for the rest of the decade.

Now, with Murach's Python for Data Science as your guide, you'll learn how to use Python libraries to get, clean, prepare, and analyze data at a professional level. To start, you'll learn how to use Pandas for data analysis and Seaborn for data visualization. Then, you'll learn how to use Scikit-learn to create regression models that you can use to make predictions.

To tie everything together, this book contains four realistic analyses that use real-world data. That's because studying analyses like these is critical to the learning process.