Skip to main content
Books, videos, and music - all free from your public library!
LoginSign Up

Footer

Hoopla logo, Go to homepage
  • For Patrons
  • For Libraries (opens in new window)
  • For Vendors (opens in new window)
  • Facebook (opens in new window)
  • X (opens in new window)
  • Instagram (opens in new window)
  • YouTube (opens in new window)
  • TikTok (opens in new window)
  • LinkedIn (opens in new window)

Our Company

  • Our Story
  • Get Hoopla for your Library (opens in new window)
  • Get your content on hoopla (opens in new window)
  • Join our team (opens in new window)
  • Accessibility Statement

Our Content

  • Audiobooks
  • Ebooks
  • Movies
  • Television
  • Comics
  • BingePasses
  • Music
  • The Loop Blog

Help

  • Help Center
  • Submit Feedback
  • Facebook (opens in new window)
  • X (opens in new window)
  • Instagram (opens in new window)
  • YouTube (opens in new window)
  • TikTok (opens in new window)
  • LinkedIn (opens in new window)
  • Download on the App Store (opens in new window)
  • Get it on Google Play (opens in new window)
  • Available at Amazon Appstore (opens in new window)
© 2026 Midwest Tape, LLC. All rights reserved. Privacy Policy | Terms of Use
  • Hoopla logo
    Powered by Hoopla
  • Browse
  • My Hoopla
  • Log In
  1. Navigate Home
  2. Ebooks
  3. Python 3 and Data Analytics Pocket Primer

EBOOK

Python 3 and Data Analytics Pocket Primer

Mercury Learning and Information
(0)
sign up
Pages
258
Year
2024
Language
English
Publisher
Packt Publishing

About

This book, part of the best-selling Pocket Primer series, introduces readers to the fundamental concepts of data analytics using Python 3. The course begins with a concise introduction to Python, covering essential programming constructs and data manipulation techniques. This foundation sets the stage for deeper dives into data analytics, emphasizing the importance of data cleaning, a critical step in any data analysis process. Following the Python basics, the course explores powerful libraries such as NumPy and Pandas for efficient data handling and manipulation. It then delves into statistical concepts, providing the necessary background for understanding data distributions and analytical methods. The course culminates in data visualization techniques using Matplotlib and Seaborn, demonstrating how to effectively communicate insights through graphical representations. Throughout the course, numerous code samples and practical examples are provided, reinforcing learning and offering hands-on experience. Companion files with source code and figures are available online, supporting the learning journey. This comprehensive guide equips both beginners and seasoned professionals with the skills needed to excel in data analytics.

Related Subjects

  • Python
  • Languages
  • Computers
  • Adult Nonfiction
  • Data Visualization
  • Data Science
  • General

Artists

Mercury Learning and InformationAuthor
Oswald CampesatoAuthor