Exploring Simulated Annealing and Data Visualization Techniques

Wrangling data in Pandas, when to use Pandas, Matplotlib or Seaborn, and why you should learn to create Python packages: Jon Krohn speaks with guest Stefanie Molin, author of Hands-On Data Analysis with Pandas.

This episode is brought to you by Posit, the open-source data science company, and by AWS Inferentia. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• The advantages of using pandas over other libraries [07:55]
• Why data wrangling in pandas is so helpful [12:05]
• Stefanie’s Data Morph library [24:27]
• When to use pandas, matplotlib, or seaborn [33:45]
• Understanding the ticker module in matplotlib [36:48]
• Where data analysts should start their learning journey [40:08]
• What it’s like being a software engineer at Bloomberg [51:19]

Additional materials: www.superdatascience.com/675