#Pandas #DataAnalysis #DataVisualization Wrangling data in Pandas, when to use Pandas, Matplotlib or Seaborn, and why you should learn to create Python packages: @JonKrohnLearns 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 (https://posit.co), and by AWS Inferentia (https://go.aws/3zWS0au). Interested in sponsoring a SuperDataScience Podcast episode? Visit https://jonkrohn.com/podcast for sponsorship information. In this episode you will learn: • [00:00:00] Introduction and Stefanie's book "Hands-on Data Analysis with Pandas" • [00:06:08] The advantages of using pandas over other libraries • [00:10:20] Why data wrangling in pandas is so helpful • [00:22:50] Stefanie’s Data Morph library • [00:31:58] When to use pandas, matplotlib, or seaborn • [00:35:02] Understanding the ticker module in matplotlib • [00:38:21] Where data analysts should start their learning journey • [00:49:30] What it’s like being a software engineer at Bloomberg Additional materials: https://www.superdatascience.com/675