7  Wings to Fly

You just started your internship at a big firm in New York, and your manager gave you an extensive file of flights that departed JFK, LGA, or EWR in 2013. From this data (which you can obtain in R) your manager wants you to answer some specific questions. :

  1. For each origin airport (JFK, EWR, LGA), which airline has the lowest 75th percentile of departure delay for flights scheduled to leave earlier than noon?
  2. Which origin airport is best to minimize my chances of a late arrival when I am using Delta Airlines?
  3. Which destination airport is the worst airport for arrival delays? You decide on the metric for “worst.”

The boss’ questions:

  • For each origin airport (JFK, EWR, LGA), which airline has the lowest 75th percentile of departure delay for flights scheduled to leave earlier than noon?

  • Which origin airport is best to minimize my chances of a late arrival when I am using Delta Airlines?

  • Which destination airport is the worst airport for arrival delays? You decide on the metric for “worst.”

  1. To get the data, first install the nycflights13 package. Then use library(nycflights13) to load the package. We will be using the flights dataset within the package. To learn more about the flights dataset, run ?flights in the console.

  2. Address two of the three questions from your manager. Each answer should contain at least one chart and a description where you state the answer.

    • At least one of your visualizations needs to show the complexity of the data (i.e. individual flights, and not only broad summaries).

  3. Create a report that has the graphs and an explanation of the answers to the boss’ questions mentioned in the background section..

  4. Render your .qmd. Push all the files created in the rendering process into your GitHub repository.

Submit

In I-learn submit a link to the .md file on GitHub.