1. join + filter - Which airplanes fly LGA to XNA (1 POINT)
q1 <- flights %>%
filter(origin =="LGA", dest=="XNA") %>%
inner_join(planes, by = "tailnum") %>%
select(tailnum, manufacturer, model) %>%
distinct()
head(q1)
## # A tibble: 4 × 3
## tailnum manufacturer model
## <chr> <chr> <chr>
## 1 N711MQ GULFSTREAM AEROSPACE G1159B
## 2 N737MQ CESSNA 172N
## 3 N840MQ CANADAIR LTD CF-5D
## 4 N713EV BOMBARDIER INC CL-600-2C10
2. join - Add the airline name to the flights table (1 POINT)
q2 <- flights %>%
left_join(airlines, by = "carrier")
head(q2)
## # A tibble: 6 × 20
## year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time
## <int> <int> <int> <int> <int> <dbl> <int> <int>
## 1 2013 1 1 517 515 2 830 819
## 2 2013 1 1 533 529 4 850 830
## 3 2013 1 1 542 540 2 923 850
## 4 2013 1 1 544 545 -1 1004 1022
## 5 2013 1 1 554 600 -6 812 837
## 6 2013 1 1 554 558 -4 740 728
## # ℹ 12 more variables: arr_delay <dbl>, carrier <chr>, flight <int>,
## # tailnum <chr>, origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>,
## # hour <dbl>, minute <dbl>, time_hour <dttm>, name <chr>
3. join + select + distinct() - Which airports have no commercial
flights (1 POINT)
q3part1 <- flights %>%
select(origin, dest) %>%
pivot_longer(cols = c(origin, dest), values_to = "faa") %>%
distinct(faa)
q3part2 <- airports %>%
anti_join(q3part1, by = "faa") %>%
select(name)
head(q3part2)
## # A tibble: 6 × 1
## name
## <chr>
## 1 Lansdowne Airport
## 2 Moton Field Municipal Airport
## 3 Schaumburg Regional
## 4 Randall Airport
## 5 Jekyll Island Airport
## 6 Elizabethton Municipal Airport