Craigslist Delaware Used Cars By Owner – This blog post is part of an undergraduate data science course. Our team selected a dataset of used cars from Kaggle. This dataset spans the period from 1923 to 2020 and contains data on used car ads on the Craigslist website. The data set is limited to ads in the US.
Our inspiration was that the biggest advantage of buying a used car is that the original owner takes care of most of the wear and tear on the vehicle. A new car loses most of its value in the first few years. Anyone can get more bang for their buck by having the right information at their fingertips.
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Through our analysis, we hope to find interesting trends and correlations between different characteristics of used car sales.
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2. The correlation between price and condition is further enhanced by model year, current vehicle location, number of cylinders in the vehicle, and vehicle mileage.
The data set before cleaning contains 423,857 records with 24 columns. The dataset has the following columns: URL, City, City URL, Price, Year, Make, Manufacturer, Condition, Cylinder, Fuel, Odometer, Title Status, Transmission, VIN, Drive, Size, Type, Paint Color. , image URL, description, latitude, longitude. Austin Reese obtained this data set by hacking the Craigslist website. According to Austin’s brief introduction on his Kaggle page, the dataset is shared and updated every few months.
Cylinders – The number of cylinders in a car engine varies from 3 to 12. There is also an “Other” category.
Status — The car also had six different statues. “Cleaning”, “Seizure”, “Return”, “Salvage”, “Parts only”, “Lost”.
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Drive – There are three types of drive transmissions. “4VD”, “FVD”, “RVD”. (4 wheel drive, front wheel drive, rear wheel drive)
Type – This feature determines whether the vehicle is an SUV or a minivan. This function has 13 unique values.
Country – A country is a political territory and is represented in the dataset in abbreviated form. This is similar to how “fl” is used in the state of Florida.
Latitude, Latitude – Both functions together indicate where the vehicle will be sold.
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2) Check if you can replace NaN values and remove non-fillable columns, such as the country column which was completely empty.
3) Remove redundant columns that provide the same information, such as region and county, and you get the vehicle’s location and state, latitude, and longitude coordinates.
9) Changed the data type of the column to match the value. The data type for the number of cylinders in the vehicle has been changed from string to integer.
10) The condition of the car was converted from the tag to a numerical scale of 0 to 5, with 5 being new and 0 being saved, which made it easier to see the correlation between the condition and the price of the car.
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EDA wanted to visualize the interrelationship of different features and, in particular, the relationship with the price of a used car. We also visualized different trends in used car sales.
Several linear relationships are evident from the correlation matrix, such as vehicle condition and year of manufacture. Cars produced in the following year are expected to be in better condition than cars produced in the previous year. To further analyze, we used different methods to visualize the features.
To begin our journey with EDA, we decided to start by looking at where and how used cars are sold in the United States. For this purpose, we used the latitude and longitude coordinates of each vehicle and plotted them on an interactive map of the United States. Each point on the map represents a used car and its make, model and price. This shows that the frequency of car sales is higher on the East Coast of the United States than on the West Coast. This may be due to data set limitations. For demonstration purposes, below is a chart of the top 10% of used cars available for sale in the dataset.
California and Florida lead the charts in terms of sales volume, but the prices of these cars tell a different story.
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Our hypothesis was that there is an inverse relationship between the average car price and the number of cars available for sale. The average car price is highest in Wyoming, the least populated state in the United States. This may be due to the very few cars available in this region. Another important observation is that although California sells more cars than Florida, cars are relatively cheaper in Florida than in California. Delaware has few cars for sale, but the average car price is second only to Washington. Both of the above cases clearly violate our hypothesis.
Ford leads the group with the most vehicles sold by the manufacturer. That’s no surprise, since Ford’s F-Series pickup line has been America’s best-selling truck for 43 consecutive years. For the past 38 years, Ford F-Series trucks have also been America’s best-selling vehicles. Since electric cars are relatively new, it is clear that the cars produced by Tesla have a higher average price compared to other manufacturers. Both Porsche and Aston Martin are manufacturers that produce expensive supercars with premium features, so it makes sense that they have expensive cars.
The graph shows that the trend of hybrid and electric cars is developing slowly, especially for hatchbacks and sedans. No progress has yet been made in heavy duty vehicles such as trucks, SUVs and pickups. The main energy sources for these vehicles remain diesel and gasoline.
Since 2009, a downward trend in the number of vehicles available for sale indicates that fewer vehicles were produced in 2009. This may be due to the financial crisis of 2009. The decrease after 2014 may be attributed to the temporal proximity of the data collection dates. As the sharp decline since 2015 shows, the cars are unlikely to be sold because there are already new buyers.
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The graph above reveals the fact that the average price and price range of a car increases every year due to inflation and other external factors.
If you plot the condition of the car and the year of manufacture on a violin, you will see that the older cars are in worse condition. The condition of your vehicle will improve as you upgrade to a newer model. The lower the condition, the lower the price, which will increase the price compared to the annual lot. .
Relationship between price and mileage, car engine type, condition, number of cylinders, drive type and car condition:
Many conclusions can be drawn by looking at frames with different features and prices. Hybrid technology achieves economies of scale, meaning that the average price of hybrid and gasoline cars is about the same. In addition, electric cars are more expensive than hybrid or gasoline cars. Diesel vehicles are generally the most expensive, primarily because large utility vehicles such as trucks use diesel engines. As the condition of the car improves, the upper quartile range tends to increase. This indicates that cars in better condition are worth more. You will get different results depending on the number of cylinders in your car, but 5 cylinder cars are the cheapest. Average prices are similar for cars with 3, 4 and 6 cylinders. Front-wheel drive cars are cheaper than four-wheel or rear-wheel drive cars. This may be because four-wheel drive vehicles are usually larger and consist of SUVs, pickup trucks, and trucks. Rear-wheel drive cars are usually luxury cars or sports cars that are expensive because they have premium features. Lien cars have a higher average price, but this is considered an anomaly because lien cars require a down payment before the lender can take full ownership of the car.
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This diagram shows the relationship between the mileage reading and the price of the car. A downward trend can be observed. The chart also shows the relationship between year of manufacture and price and the odometer reading as the chart lights up.
The lower right shows that older cars have lower selling prices and higher mileage. Also, the left side of the graph is less dense, indicating that there are fewer new car models.
Our goal during the machine learning phase was to train a model that takes into account the car’s specifications and provides an estimated price. To do this, we first converted all the columns into a single hotcoded column. For the odometer, we normalized the values so that the range is not too wide. The price will remain the same as it is used.
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