Car Data, Webscrape and Analysis with python
This project aims to answer a question, what price should I sell a used Hyundai made in 2009 with 90837 kms on the ODO? This projects uses a combination of webscraping and data analysis to answer this question with python.
First I imported the required libraries and then put together the data frame from the information scraped.
After turning the dataframe into a csv, we use a new cell to read that csv, this is done so that we don't have to keep using the webscraper. We do some data manipulation for later and then visualise the data with a scatter plot.
Some quick maths on the dataset reveals that on average, a used car from 2009 is worth 2 cents per kilometer, but that isn't quite right.
This is confirmed by the car only being worth $2355, odd since cars with lower kilometers are usually of higher value. So next we try to determine the average price of cars with kilometers under 100,000, like the one we want to sell.
This time we get a much more reasonable $4508!