Episode 190: Great Starting Points for Contributing to Open Source

What's it like to sit down for your first developer sprint at a conference? How do you find an appropriate issue to work on as a new open-source contributor? This week on the show, author and software engineer Stefanie Molin is here to discuss starting to contribute to open-source projects. (This description comes from the episode summary.)

See also:5 Ways to Get Started in Open Source

1h 19m listen
SDS 675: Pandas for Data Analysis and Visualization

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 description comes from the episode summary.)

See also:Introducing Data Morph

1h 09m listen
PyDev of the Week: Stefanie Molin

In her feature as PyDev of the Week, Stefanie Molin discusses how she got started with Python, her favorite Python libraries, and what projects she is working on. She also discusses the top 3 lessons she learned while writing Hands-On Data Analysis with Pandas.

See also:Workshops

6 min read

Ken's Nearest Neighbors Podcast

Writing the Book on Pandas - KNN Ep. 58

During her guest episode on the Ken's Nearest Neighbor's Podcast, Stefanie Molin talks about how she got started in data, the importance of domain knowledge, and what data professionals could learn from software engineers. On a personal side, Ken and Stefanie discuss balancing work and studies, the process of writing a book, and the importance of accountability and seeking feedback.

1h 17m listen
Interview with Stefanie Molin

In this written interview, Stefanie Molin shares her experience writing the second edition of Hands-On Data Analysis with Pandas (published by Packt on April 29, 2021).

4 min read
A Conversation with Bloomberg's Stefanie Molin about her new book on Data Science, Python and Pandas

Stefanie Molin recently wrote the technical book Hands-On Data Analysis with Pandas (published by Packt on July 26, 2019). Her work shows readers how to analyze data and get started with machine learning in Python using the powerful pandas library. She's a software engineer and data scientist, and a member of the Security Data Science team at Bloomberg that researches and develops solutions using data and machine learning to help improve and automate Bloomberg's information security processes. In her job, Stefanie focuses on identifying and answering security-related questions using data and developing software to solve them. She holds a bachelor's degree in Operations Research from Columbia University's Fu Foundation School of Engineering and Applied Science (CUSEAS), with minors in Economics, and Entrepreneurship and Innovation. (This description comes from the article introduction.)

7 min read