The repository showcases an analysis of a car dataset using the Python Pandas library.
I used data from Kaggle and three libraries: Pandas, Seaborn, and Matplotlib. I focused on data cleaning and created some basic charts to show the most expensive car brands, the highest average margins, and the differences between fuel consumption in the city and on the highway.
I also analyzed if there are correlations between the amount of horsepower and fuel consumption - both in the city and on the highway.