Pandas and NumPy Tips, Tricks, and Techniques [Video]

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  • Get a NumPy refresher with lessons you can reuse in general data settings
  • Take a deeper dive into NumPy to learn how to leverage the power of ndim arrays
  • Get a pandas functionality refresher covering everyday data handling concepts
  • Review how to process Excel data quickly and automatically with pandas and re-import into Excel
  • See how to work with complex data using merging and data-joining with pandas
  • Discover the functionality of pandas to help you sub-set, split, and aggregate data
  • Create a Capstone project with NumPy and pandas to produce a data analysis tool for stock prices as a working model

This course will empower you with new possibilities using NumPy and pandas that you probably never knew existed, and tips to use them to increase your efficiency and productivity in your daily tasks. Each section will cover key tips, tricks, and techniques for efficient data analysis in NumPy and pandas that you can apply in your own real-world scenarios to increase your output and efficiency. You’ll learn how to make your data more meaningful and contextual by adding customization. We’ll also cover the new features introduced in NumPy and pandas and leverage them to simplify the way you use them for your data science requirements. By the end of this course, you will be able to get the best out of your code much faster and and more efficiently.

The Github Link to this video course is:

  • Practical and proven techniques focused on the key aspects of pandas and NumPy that can really enhance your daily work
  • A fast-paced course filled with best practices to help you manage your pandas and NumPy applications efficiently
  • Easy-to-implement solutions to simplify your day-to-day programming tasks
Course Length 4 hours 31 minutes
ISBN 9781838825638
Date Of Publication 17 Oct 2019


Matthew Macarty

Matthew Macarty has taught graduate and undergraduate business school students for over 15 years and currently teaches at Bentley University. He has taught courses in statistics, quantitative methods, information systems, and database design. His technical expertise in Python, NumPy, and pandas stretches back more than five years, and he has created and implemented tutorials on data analysis and statistics, including educational videos to promote a proprietary machine learning and analytics platform. In addition, his knowledge portfolio includes SciPy, R, SPSS, Java, Palisades' Decision Tools risk analysis suite, and the Crystal Ball risk analysis suite, along with HTML, CSS, JavaScript, SQL, and Visual Basic for applications.