Photo by Haley Owens on Unsplash
In this data exploration, you will practice the following:
- Data exploration and visualization.
- Calculating summary statistics.
- Feature engineering.
Throughout this exploration, when you're asked to use a new function or library, we'll usually provide a link to that function's documentation, or a tutorial related to it.
As with our previous data explorations, this assignment uses Google Colab. For more information on using Google Colab, including how to submit assignments with it, please see the information in Data Exploration 01
You're working as a data analyst at a cereal marketing company in New York.
In a strategy meeting, the marketing director tells you that in 2018, the US weight loss industry was worth over $72 Billion dollars, growing 4% compared to the previous year. 1
In contrast, sales of cold cereal fell 6% to $8.5 billion during the same time period. 2
Cereal executives have approached the marketing company asking how they can somehow tap into the weight loss market growth to boost the sales of their cereal brands.
Your assignment is to analyze a dataset of nutritional information for major US cereals, and calculate some metrics that can be used by the marketing team.
Click on the
Open In Colab button below to open a Google Colab notebook with the template for this assignment. Once you've completed the assignment, don't forget to take the corresponding quiz in Canvas.
Once you have absolutely exhausted all of your best efforts in solving the data exploration problems, and you are stuck on where to go next, you can view the teacher's solution here.