ggplot(by_hour, aes(x = date, y = hour, fill = count)) +geom_tile() +scale_fill_viridis_c(option ="A") +labs(title ="Flight Frequency Heatmap in December 2023",caption ="Source: FAA Aircraft registry",x ="Date",y ="Hour of Day",fill ="Flight Frequency #") +theme_minimal()
My Heatmap is to visualize the frequency of flights in December 2023 out of NYC alongside the hour of day flights departed. When creating my heatmap, I thought of the winter season, flights to and from home for the holidays, end of semester travelling, etc, any events that could influence a spike or drop in flight frequency out of NYC. As a result, we can see the trend of little late-night flights, and some outliters for dates such as December 3/10/17 had a drop in flights because of being a Sunday (can be associated with inconvenience). Approaching the holiday weekend season around December 21, there is a drop in flight frequency with a darker gradient, most likely due to less demand (already flying out prior to the holidays), or weather conditions due to NYC’s climate and likely snow forecasts.
I acknowledge the use of ChatGPT(https://chat.openai.com/) to search for the “scale_fill_viridis_c(option =”A”)” and “format(time_hour,”%H”)” option in order to add better color and solve the issue of adding dates to my heatmap.