In this project, we analyze a dataset containing 566,996 observations of commercial flights from the FAA data for the month of December 2009. The dataset is sourced from the Research and Innovation Technology Administration at the Bureau of Transportation Statistics. The aim of the project is to conduct a performance analysis of a commercial airline company using R programming.
The dataset used in this analysis contains detailed information about commercial flights, including flight numbers, departure and arrival times, origin and destination airports, flight distances, and various performance metrics such as delays, cancellations, and diversions (https://www.bts.gov/).
The project is implemented in R, a popular programming language for data analysis and visualization. We use various data manipulation and visualization techniques in R to explore the dataset and gain insights into the performance of the airline company. The analysis includes descriptive statistics, data visualization using plots and charts, and hypothesis testing to evaluate the performance of the airline company.
The findings of this analysis provide valuable insights into the performance of the airline company during the month of December 2009. The results include key performance indicators such as on-time performance, delays, cancellations, and diversions. The analysis also identifies potential patterns or trends in flight performance and provides recommendations for improving the airline's operations.
This project presents a comprehensive performance analysis of a commercial airline company using R programming. The analysis of the FAA flight data provides valuable insights into the airline's performance during the month of December 2009. The results and recommendations from this analysis can be used by the airline company to make data-driven decisions and optimize their operations for better performance in the future.