This project was done as a part of Udacity's Data Analyst Nanodegree program. The objective of this project was to use Python visualization libraries to explore a dataset systematically. The analysis begins with exploring single variables followed by bivariate and multivariate analysis.
This analysis is followed by a short presentation to convey and highlight important findings using explanatory data analysis. A slide deck was prepared that followed the major path of exploration and a story was constructed for the readers to understand what was discovered.
This data provide details about the circumstances of personal injury road accidents in Great Britain from 2005 to 2014, the types of vehicles involved, and the consequential casualties. The statistics relate only to personal injury accidents on public roads that are reported to the police and subsequently recorded, using the STATS19 accident reporting form. Information on damage-only accidents, with no human casualties or accidents on private roads or car parks, is not included in this data.
This Data is available on Kaggle.
In this investigation, I wanted to look at what causes Serious and Not Serious accidents. The main focus was on: road type, time, age of driver, age of the vehicle, Driver IMD deprivation, speed limit...
In the exploration, I found that The distribution of drivers' ages involved in accidents clumped up between 15-35. And people from 15 to 45 have a higher percentage of serious accidents than others.
Also, in Great Britain, speed limit and type of road have a strong influence on the seriousness of accidents rate. So slip roads and dual carriageways are more deadly within high-speed driving.
interestingly I found that even though the total annual accident during the investigation period was mostly declined, from 2011 to 2014 There was a slight spike in the percentage of serious accidents than slight accidents.
It seems that people without pressure do not get involved in accidents, that's why weekends has The minimum occurrence of accidents compared to other weekdays.
