Car Price Data - Introduction
Using R to understand used car price depreciation.
Understanding what factors affect the depreciation in the value of a car can help to determine the best vehicle to purchase and to give an indication of how much depreciation to expect for a particular configuration of vehicle.
In these notebooks I attempt to understand what drives the used car price of a Mazda CX-30 in the UK using car price data collected in a spreadsheet. The first task is to convert the data from its rough format into one that is suitable for analysis with R.
Code is developed in R to first clean and prepare the data and then to examine it using a combination of data plots and tables. Linear regression and regression tree models are then fitted to the data to give numerical estimates of how much vehicle specifications contribute to their depreciation.
Heavy use is made of the opinionated collection of R packages known as the Tidyverse which make for a more enjoyable and consistent programming experience.
| Related Notebooks |
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| Car Price Data - Preparation |
| Car Price Data - Visualisation |
| Car Price Data - Modelling |
| Car Price Data - Tabulation |