The project analysis aviation accidents from 1962 to 2023 to help understand which aircrafts are of the lowest risk. This will enable the company make informed decision on which aircraft to purchase.
Our company is looking to expand into new industry and is interested in purchasing and operating airplanes for commercial and private enterprises to diversify its portfolio. This will help the head of the new aviation division understand which aircraft have the lowest risk.
- Source of data - The dataset used is from the National Transportation Safety Board it contains data on aviation accidents from 1962 to 2023.
- Description of the data. The data contained 88889 rows and 31 columns.
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- Data Cleaning: Removed duplicates and null values in key columns (e.g., Make, Model).Standardized formats for dates and categorical fields . Filtered incomplete or irrelevant records .
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- Data analysis: Created calculated fields : Fatalities _ Rate = Total Fatalities / Total Accidents Grouped accidents by year, flight purpose.
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- Visualization Tools: Used Python (pandas, seaborn, matplotlib) for initial analysis. Visualized interactive dashboards using Tableau.
click here to view more interactive the tableau dashboard
- Investigate years with spikes in accidents to identify causes.
- Prioritize safety protocols for high-risk flight purposes.
- Enhance structural integrity to reduce fatalities during crashes.
- Focus maintenance efforts on aircraft with higher fatality rates.
- The organisation should consider venturing into commercial flights for it has the fewer accidents compared to personal.