With increasing flight connections to the United States and Europe, South American based flights are often faced with departure delays. [1] Although South American flights are no more likely to be delayed than other flights across the world, we think that it will be interesting to analyze the flight delay trends and patterns on flights departing from this continent. [2]

The side benefit of more incoming flights is the convenience of taking direct flights to exotic places. For instance, Santiago residents can fly to and from Melbourne and Sydney just in case they want to catch waves on the other side of the world. Ecuadoreans now go direct to Amsterdam (from Quito).

To measure South American flight delays, we calculated the average delay time for departing South American flights (scheduled departure time – actual departure time) ranging from Buenos Aires to Mexico City from mid-afternoon Wednesday, February 13th through early Friday morning February 15th local time.

First, let’s take a look at a histogram of South American departure delays over this timeframe.

Figure 1: Histogram of 236 delayed flights from South American* airports.

Source: FlightAware.com

The above histogram is skewed slightly to the right. It is clear that South American flights tend to experience moderate delays (12:52 minutes on average).

One extreme outlier in our histogram is a lone flight between Rio de Janeiro and Paris (341-minute delay) and a 139-minute delay on a flight traveling from Bogota to Mexico City. On the flip side, a flight from Los Angeles to Mexico City left 60 minutes before the expected takeoff!

Figure 2: Average delays (minutes) from sampled South American* airports.

Source: FlightAware.com

The beeswarm plot below plot shows that the majority of our sampled flights are delayed between 0 to 25 minutes, which is a pattern mimicked in airports from Africa to Australia.

Figure 3: Plot of delayed flights (minutes) from South American* airports.

Does Bogota Have Significantly Less Delays than Sao Paulo?

Since the majority of scraped data did not contain the actual departure time (only scheduled and estimated arrival times) we will compare if Bogota and Sao Paulo delay times are significantly different from each other. Each of these cities had at least 60 observations, which is a large enough sample for statistical testing. [3] For reference, Sao Paulo and Bogota’s departures were delayed by an average of 12:06 and 12:42 minutes respectively from our sampled flights.

Sao Paulo, a sprawling concrete jungle south of Rio de Janeiro, has over 4 million more residents than Bogota yet the former city outpaced the latter by 24 takeoffs from mid-afternoon through midnight on February 13th.

Sao Paulo’s flight traffic is dominated by Recife (10.2% of all flights) alongside Santiago Chile (6.1%), and Brasilia (6.1%). Interestingly, the highest percentage of flights into and out of Bogota stemmed from Madrid (8.8%) followed by six cities that each controlled a 5.9% share of overall flight traffic. [4]

Sao Paulo and Bogota offer flights to wide range of destinations unlike other cities like Guadalajara, Medellin, and Havana where flyers have more limited options.

To compare the delayed flights between the Sao Paulo and Bogota, we first want to check if our data (delayed flight times) are normality distributed, which will determine the types of statistical tests we will use.

A Shapiro test on the flight delay data gives us a p-value less than 0.01, which is a strong indicator that the data follows a non-normal distribution.

Instead we will use a Wilcoxon test to measure the statistical significance between the delayed flight times in Sao Paulo and Bogota. Unlike t-tests or Welch’s t-tests, Wilcoxon tests only require that the data’s distribution samples are randomly representative of a population (in our case all flights from Sao Paulo and Bogota) and that the samples are independent of each other.

Our Wilcoxon test gives us a p-value of 0.79 suggesting that there is no significant difference between the flight delay times in Sao Paulo and Bogota. These statistical tests can be carried out on South American airports to find outliers that are slower or faster in terms of taking off into the sky.

[1] Buenos Aires, Santiago, Sao Paulo, Rio de Janeiro, Bogota, Lima, Medellin, Quito, Montevideo, Caracas, Curitiba, Belo Horizonte, and San Salvador.

[2] Non South American cities including Monterrey, Panama City, Mexico City, Guadalajara, and Havana are also featured in this analysis.

[3] The entire dataset is 2246 unique flights.

[4] These cities include Miami as well as the Colombian cities of Chachagüí and Atlantico.

Github: https://github.com/Fremont28/Flight_Analyzer-

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