In India the used car market is segmented by vehicle type (hatchbacks, sedan, and sports utility vehicles), fuel type (petrol, diesel, electric, CNG, LPG). The increased sale of used car is mainly found in metro cities and also a rise in online sales platforms, such as CarDekho, Cars24 etc.
Pandas is a powerful Python data analysis toolkit for :
- Reading different varieties of data
- Functions for filtering, selecting and manipulating the data
- Plotting data for visualization and exploration purposes
- pandas
- numpy
- matplotlib
- stats
- seaborn
- The dataset is about the the pre-owned cars from 1998 to 2019.
- There are 6019 rows and 13 columns in this dataset. The first 5 observations from the dataset is displayed.
- The columns in the dataset are 'Name', 'Location', 'Year', 'Kilometers_Driven', 'Fuel_Type','Transmission', 'Owner_Type', 'Mileage', 'Engine', 'Power', 'Seats','New_Price', 'Price'.
- The dataset consist of the pre-owned cars in 11 different states in India (ie) 'Mumbai' 'Pune' 'Chennai' 'Coimbatore' 'Hyderabad' 'Jaipur' 'Kochi','Kolkata' 'Delhi' 'Bangalore' 'Ahmedabad'.
- We see that Mumbai,Hyderabad ,Kochi ,Coimbatore have the majority pre-owned cars. Mumbai has about 790 preowned cars followed by Hyderabad with 742. Kochi and Coimbatore has 651 and 636 pre-owned cars.
Jupyter Notebook