Explore the latest books of this year!
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Sarah Bay-Cheng

    Python for SAS Users
    Staying Clean
    Dandelions
    Practice as Research in the Arts (and Beyond)
    From Foal to Horse
    • How does a foal grow into a horse? Follow each step in nature's cycle-from birth to stallion or mare-in this fascinating book!

      From Foal to Horse
      4.0
    • Practice as Research in the Arts (and Beyond)

      Principles, Processes, Contexts, Achievements

      This project addresses the contexts of Practice as Research and how to undertake it. A comparison is made between Artistic Research and Practice Research recognizing that research through practices with being-doing-knowing is central to both.

      Practice as Research in the Arts (and Beyond)
      3.0
    • Dandelions

      • 24 pages
      • 1 hour of reading

      Get a close-up view of the life of a dandelion.

      Dandelions
      3.8
    • Staying Clean

      • 32 pages
      • 2 hours of reading

      Why is staying clean so important? Staying clean by washing hands, taking baths, brushing teeth, and keeping cuts clean helps prevent people from getting sick. Staying clean keeps people healthy.

      Staying Clean
    • Python for SAS Users

      A SAS-Oriented Introduction to Python

      • 452 pages
      • 16 hours of reading

      Business users familiar with Base SAS programming can learn Python through practical examples that translate SAS coding constructs into their Python equivalents. The focus is primarily on pandas and data management for data analysis. With over three million SAS users globally, many are transitioning to open-source software like Python and need to update their skills. Most SAS users lack formal computer science training and have learned through on-the-job experience, making traditional Python resources often too technical for their needs. This guide offers a comprehensive collection of over 200 Python scripts alongside approximately 75 corresponding SAS programs, making it a valuable resource. The initial chapters emphasize Python, while later sections provide SAS examples that align with Python scripts to tackle common data analysis tasks, such as reading multiple data sources, detecting and imputing missing values, merging data, and generating outputs. This book serves as an essential resource for integrating SAS and Python workflows, enabling users to quickly master Python for data analysis, understand the nuances between Base SAS and Python, and choose the appropriate language for their specific needs. It is ideal for SAS users, programmers, data scientists, and those needing to bridge the gap between SAS and Python.

      Python for SAS Users