In the following project you’ll use what you’ve learned about summarizing categorical data to analyze a sample from a popular open source dataset. This dataset contains information on the cost and physical attributes of several thousand cars. Originally, this dataset was used for to train a classification model that assigned an acceptability score/category to cars based on these attributes.
The car evaluation dataset has been sourced from the UCI Machine Learning Repository and has been slightly modified for this project. Specifically, one additional field manufacturer_country has been simulated for illustrative purposes. You can read more about the details, features, and original uses of this dataset in research on the UCI data description page.