Analyzing US airport and airline data

We collected data regarding US airline and airport delay statistics from the United States Department of Transportation's Bureau of Transportation Statistics website.

The data spans from January 2016 to March 2021. The data includes information on total number and delayed number of flights per airline per airport per month. Note that the data only includes US airlines that lands in US airports.
We examined the following delay types:

Air Carrier: Delay due to circumstances within airline's control, e.g. maintenance problems, fueling, etc.
Extreme Weather: Significant meteorological conditions (actual or forecasted) delay/prevent flight operation.
National Aviation System (NAS): Delays/cancellations attributable to NAS-defined conditions, e.g. non-extreme weather conditions, airport operations, heavy traffic volume, and air traffic control.
Late-arriving aircraft: A previous flight with same aircraft arrived late, causing the present flight to depart late.
Security: Delays or cancellations caused by terminal/concourse evacuation, re-boarding of aircraft because of security breach, inoperative screening equipment and/or long lines in excess of 29 minutes at screening areas.

we are going to explore the data from three different perspectives.

Where are airports around the United States and how many arrivals does each get? This visualization shows the total number of arrivals at each airport since 2016. Hover over different bubbles to see details and zoom and pan to focus in on smaller areas.

We listed several delay types earlier, but what's the breakdown? What's slowing down flights the most around the country?

And how are these delays distributed around different airports? Click on a cause to explore the distribution around the country.

We examined each airline's monthly reported number of delayed flights between January 2016 and March 2021. To better compare the proportion of delayed flights across airlines, we normalized the delay counts by the total number of arriving flights per airline.

This visualization shows the number of delays per 10,000 arriving flights. To explore changes in delay counts and causes over time, select an airline from the dropdown. Brush to zoom into a time period or double-click to reset the time scale. You can also hover over the legend buttons to highlight a delay cause or click on one of them to view a cause individually.

This clip focuses on the flight delays reported between January 2019 and December 2020. Understandably, as the number of flights within the United States (and globally) plummeted with the onset of the COVID-19 pandemic, so did the number of flight delays.

This line graph displays the total delayed flights per 10,000 arrivals each month for the years 2016 through 2020. Note the uptick in flight delays (implying more flights) starting after September 2020. As people in the United States started traveling for the holidays in November and December of 2020, the number of arrivals and delayed flights rose.

In this section, we will focus on comparing between airlines.

Specifically, we are curious in finding out which airlines are the worse in terms of delays

So firstly, we calculated the % of flights that are delayed per airlines over the years. Click around to explore.

We also calculated the expected duration of delay for each airline.

Expected duration of delay is calculated by dividing total duration of delay by total number of flights of a particular airline. The units are in minutes.

Aggregating data from 2016, we get a summary of airlines' % percentage flights delayed and expected time over the years.

What airlines are worst than others?

Based on these explorations, which air carriers do you think had the worst performances? What about airports--did any stand out to you, whether for the frequency of certain delay types or for the sheer number of delays? Perhaps after examining the geographic- and time-based data, you expected to see certain air carriers in the top 5 of our rankings of worst airlines by delay percentages and durations.

We hope that through your exploration of this visualization, you not only learned more about the air transportation sector and delays in air travel, but also had the opportunity to relate your personal experiences with certain air carriers to the visualizations we presented.

In many ways, the most interesting time period for this dataset is about to happen. Air travel has been heavily impacted by COVID-19, and as vaccinations lead to a lessening on social distancing precautions, air travel will become an interesting indicator. The airline industry will be much smaller for years to come, but there may also be other interesting changes. Will there be a sudden jump in flights for leisure, leading to more delays with the reduced number of airlines? Will the confined space of an airplane cabin remain a strong enough deterrent that flights stay infrequent for a longer period of time?