This ipython notebook is my effort at exploring the vehicle dataset of sweden for the past 12 years based on registration/deregistration and in_use and not_in_use patterns.
In this analysis we try to see if the new registration of cars, trucks and buses have had an impact due to this new regulation. We also try to understand if there is any evident pattern in the new purchasers’ choice of vehicles.
Summary of findings
The Bonus Malus as a regulation, undoubtedly has both positive and negative aspects to it. But in this analysis, we look at the new vehicle in use, unused, registered and deregistration numbers for the past 12 years, under different categories like cars, buses, trucks, mopeds, motor cycles, trailers and terrain scooters. We also look at the fuel emission type and class that are used the most over these years and understand if consumers have shown a reaction to the law after it came into effect in July 2018.
The dataset contains only 4 months of data after the rule came into effect (between July 2018 to Oct 2018), yet we can see some reflections of the regulation.
The effort here is to see if the regulation is making an impact and what sort of impact does it look like.
The Ipython notebook is more trying to do a stastical understanding, finding outliers and see patterns using line graphs.