In this post, I’m going to analyze Thanksgiving dinner in the US using python by working on a dataset that contains 1058 responses to an online survey about what Americans eat for Thanksgiving dinner. That dataset contains 65 columns, and 1058 rows. Most of the column names are questions, and most of the column values are string responses to the questions.

There won’t be visualization in this post, only numerical analysis. In real-life, we can use better functions and support it with visualization. However, in this blog post, and previous ones to-date, my python codes have been covering the basic functionality, but as we move forward, I’ll be introducing more interesting functionalities and modules to work with.

I’ve used mainly Pandas module to complete this exercise.

NOTE: This is not a tutorial, advanced topic nor a “how-to” guide, just a completed exercise that I’m sharing.

To make this more practical and realistic, I’ve used Jupyter notebook and uploaded it into my github repository. You’ll be able to download the dataset from there as well, if you wish to practice it.

NOTE: github won’t display pretty page output if you’re on mobile. Please use either tablet/computer, or request “desktop” version on your mobile device.

Click here to jump into the notebook.