This project aimed to examine NYC airport data from 2013 to better understand what factors contribute to airport delays. To view the performance of the airports we wanted to show the percentage of how many delayed flights each airport had, to give an indication on how each airport is performing and if there are certain hours of the day that contribute to more delays.

We also showed the relationship between the delays and the destination airport to see if there is a pattern of delays in certain destinations or certain areas of the country. We also included a marker (indicated by the star) of the top 30 busiest airports in 2013 to see if there is any correlation. It is worth noting that EWR, JFK and LGA are also part of the 2013 busiest airports.

Next we examined the airplanes in the dataset to see if there was a relationship between certain variables associated with the plane and the flight delays. We chose to examine the year the plane was built, manufacturer and number of seats. We thought the number of seats would be a good indicator to also allow us to get the general size of the airplane. We compared the top 5 manufacturers by total flights and delayed flights by plane year to see if any patterns can be formed.

We showed if certain airline carriers were contributing to a higher number of delays by creating a heat map that shows the number of delays each airline had throughout the year. We also showed the top 5 carriers with delays and took a closer look at the manufacturers they are using in their fleet to see if the carriers have any similarities in manufacturers that are causing delays.