675: Pandas for Data Analysis and Visualization

<p>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.</p><p>This episode is brought to you by <a href='https://posit.co'>Posit</a>, the open-source data science company, and by <a href='https://go.aws/3zWS0au'>AWS Inferentia</a>. Interested in sponsoring a SuperDataScience Podcast episode? Visit <a href='https://jonkrohn.com/podcast'>JonKrohn.com/podcast</a> for sponsorship information.<br/><br/></p><p>In this episode you will learn:<br/>• The advantages of using pandas over other libraries [07:55]<br/>• Why data wrangling in pandas is so helpful [12:05]<br/>• Stefanie’s Data Morph library [24:27]<br/>• When to use pandas, matplotlib, or seaborn [33:45]<br/>• Understanding the ticker module in matplotlib [36:48]<br/>• Where data analysts should start their learning journey [40:08]<br/>• What it’s like being a software engineer at Bloomberg [51:19]<br/><br/></p><p>Additional materials: <a href='https://www.superdatascience.com/675'>www.superdatascience.com/675</a></p>