Summarise Tables R

Summarise Tables.R

# Code 2 — Adjust for “bad airports”: rank carriers by delay relative to each destination’s average
library(dplyr)

dest_avg <- flights %>%
  group_by(dest) %>%
  summarise(
    dest_avg_delay = mean(arr_delay, na.rm = TRUE),
    .groups = "drop"
  )

flights %>%
  left_join(dest_avg, by = "dest") %>%
  mutate(rel_delay = arr_delay - dest_avg_delay) %>%
  group_by(carrier) %>%
  summarise(
    "n(delay)" = n(),
    avg_rel_delay = mean(rel_delay, na.rm = TRUE),
    .groups = "drop"
  ) %>%
  mutate(rank = min_rank(desc(avg_rel_delay))) %>%
  arrange(rank)
  
  
  
flights %>% 
  select(tailnum, year, month, day, dep_delay,arr_delay) %>% 
  mutate(bi_delays = arr_delay + dep_delay) %>% 
  filter(
    dep_delay > 60 |
    arr_delay > 60 |
    bi_delays > 60
  ) %>%
  arrange(arr_delay, dep_delay, bi_delays)