Pandas Recipes for New Python Users

Often programmers find themselves in need of an effective way of working with “labeled” data. In the case of Python, Pandas is the most mature and reliable package that interacts effectively with other well known packages such as NumPy, and TensorFlow. As a package, Pandas is said to provide “fast, flexible, and expressive data structures” for what is known as “labeled data”. Features include: easy handling of missing data points, grouping functionality, simple indexing, time series support, numerous conversion functions, and more. This webinar will provide a basic introduction on how to install Pandas, a discussion of its strengths and various use cases, and lastly a demonstration of various common operations (recipes) that occur with labeled data. Experience with beginner Python concepts will be expected, while familiarity with Jupyter notebooks will be helpful. Webinar material and code will be made available on GitHub for future reference. _______________________________________­________ This webinar was presented by Tyler Collins (SHARCNET) on May 5, 2021, as a part of a series of regular biweekly General Interest webinars ran by SHARCNET. The webinars cover different high performance computing (HPC) topics, are approximately 45 minutes in length, and are delivered by experts in the relevant fields. Further details can be found on this web page: www.sharcnet.ca/help/index.php/Online_Seminars . Subscribe to our twitter account (@SHARCNET) to stay updated about our upcoming webinars. SHARCNET is a consortium of 19 Canadian academic institutions who share a network of high performance computers (www.sharcnet.ca/). SHARCNET is a part of Compute Ontario (computeontario.ca/) and Compute Canada (computecanada.ca/).