Data visualization is one of the most marketable and desirable data science skills out there. Given its visible and tangible results, hiring managers often look for individuals who can communicate their findings easily and to people who aren’t data-savvy. We recently had the chance to speak with Teddy Petrou, founder of Dunder Data and author of Pandas Cookbook, about data visualization, Seaborn, and Dash 2.0.
What made you so interested in data visualization?
I was first drawn to data visualization as a kid watching ESPN’s Sports Center. I didn’t know the terms “data” or “visualization” but I loved the way the statistics were displayed on the screen. Even simple bar graphs made the information easier for me to digest. When I grew older, I discovered baseball was a game suited for modern data analysis techniques. I began reading books on real-life applications of data analysis and visualization on a sport that I loved. I pursued degrees in math and statistics, and ultimately found my way into the Python data science ecosystem.
What are some interesting use cases you’ve been involved in using data visualization?
During the onset of the ongoing coronavirus situation, I became fascinated with the models and predictions of future outbreaks. I proceeded to build a coronavirus forecasting dashboard, which is updated daily and available at coronavirus.dunderdata.com. It shows historical and predicted values for covid cases and deaths for all countries in the world and US states.
Why go with Seaborn over other libraries?
Seaborn is a good choice when you want to produce static, two-dimensional data visualizations with tidy data stored in a pandas DataFrame. It is not suitable for animation or three-dimensional visualizations. If you like using an intuitive API, easily setting new styles, automatically grouping and aggregating tidy data, and customizing your plots, then Seaborn can be a great tool to create the visualizations you desire.
Is there anything new or trending related to data visualization or data science in general that you’re excited about heading into 2022?
I’m looking forward to working with and exploring Dash 2.0, which is an interactive data visualization library for the web.
How to Learn More About Seaborn
This December 1st and 8th, Teddy Petrou will be presenting two sessions on our Ai+ Training platform, “Data Visualization with Seaborn.” Key points include:
- Learn the fundamentals of using the Seaborn data visualization library and how it integrates with Pandas DataFrames.
- Understand the different categories of Seaborn plotting functions and the return type (Grid or Axes) of each.
- Learn how tidy data provides the best structure to take advantage of the Seaborn plotting functions.
- Learn how to choose grouping and aggregating variables, and how to customize plots with all the other available parameters.
- Learn how to create grids of plots.