The raw data behind the story "Should Travelers Avoid Flying Airlines That Have Had Crashes in the Past?" https://fivethirtyeight.com/features/should-travelers-avoid-flying-airlines-that-have-had-crashes-in-the-past/.

airline_safety

Format

A data frame with 56 rows representing airlines and 9 variables:

airline

airline

incl_reg_subsidiaries

indicates that regional subsidiaries are included

avail_seat_km_per_week

available seat kilometers flown every week

incidents_85_99

Total number of incidents, 1985-1999

fatal_accidents_85_99

Total number of fatal accidents, 1985-1999

fatalities_85_99

Total number of fatalities, 1985-1999

incidents_00_14

Total number of incidents, 2000-2014

fatal_accidents_00_14

Total number of fatal accidents, 2000-2014

fatalities_00_14

Total number of fatalities, 2000-2014

Source

Aviation Safety Network http://aviation-safety.net.

Examples

# To convert data frame to tidy data (long) format, run: library(dplyr) library(tidyr) library(stringr) airline_safety_tidy <- airline_safety %>% gather(type, count, -c(airline, incl_reg_subsidiaries, avail_seat_km_per_week)) %>% mutate( period = str_sub(type, start=-5), period = str_replace_all(period, "_", "-"), type = str_sub(type, end=-7) )