The descriptive analysis could be used to find the trends and patterns in historical data. In this project, we will use the descriptive analysis to describe the car accidents in Washington, D.C, between 2009 to 2020. The dataset was downloaded from the District Department of Transportation (DDOT), the department responsible for car accidents in Washington D.C. We have applied multiple analytics and statistical models to find the relationships between different variables and the patterns and trends among the data, such as correlation analysis, confidence interval, One-Way-ANOVA, decision tree, and visualizations. The project aims to find the common reasons for the accident and help DDOT find ways to reduce and eliminate the accidents in the area. The statistical and analytical tools examine multiple features to find the patterns and trends among the datasets. Four main findings were found after analyzing the data. First, the main reason for most crashes is drunk people, either drivers or pedestrians. The second finding is that the top reason which causes deadly accidents is speed. Also, we have found that most of the accidents are not dangerous. In addition, we found the top ten streets that contain the highest accident number, and we found that they are located on the north side of the town.
- Dataset webpage: https://opendata.dc.gov/datasets/DCGIS::crashes-in-dc/about
- Dataset : https://opendata.dc.gov/datasets/crashes-in-dc/explore
- prepare data 21 nov: contains clean, explore and prepare the data.
- analyze data 26 nov: contains the analytics and statistical models.
- Visualizaitons_nov21: Tableau file contains multiple charts.
- Nov21_datasset: Final cleaned dataset
- Please replace the data link in all files.
- To download the all data and work system follow the link: https://u.pcloud.link/publink/show?code=kZ9JxAXZmEIjwmvrtEBhQAdqQMAsi8WppwLy
Zaid Altukhi zaid@altukhizm.com
Please do not hesitate to contact me if you faced any issues.
02 December 2021
Thank you ..