library(nycflights13)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.0.4
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
View(flights) View(airlines) View(weather) View(planes) View(airports)
lga_to_xna_flights <- flights %>%
filter(origin == "LGA", dest == "XNA") %>%
select(flight, tailnum, origin, dest, carrier)
print(lga_to_xna_flights)
## # A tibble: 745 × 5
## flight tailnum origin dest carrier
## <int> <chr> <chr> <chr> <chr>
## 1 4534 N722MQ LGA XNA MQ
## 2 4525 N719MQ LGA XNA MQ
## 3 4413 N739MQ LGA XNA MQ
## 4 4534 N719MQ LGA XNA MQ
## 5 4525 N711MQ LGA XNA MQ
## 6 4413 N723MQ LGA XNA MQ
## 7 4534 N711MQ LGA XNA MQ
## 8 4525 N730MQ LGA XNA MQ
## 9 4413 N722MQ LGA XNA MQ
## 10 4534 N719MQ LGA XNA MQ
## # ℹ 735 more rows
flights_with_airline <- flights %>%
left_join(airlines, by = "carrier") %>%
select(flight, tailnum, origin, dest, carrier, name) # Adding airline name
print(flights_with_airline)
## # A tibble: 336,776 × 6
## flight tailnum origin dest carrier name
## <int> <chr> <chr> <chr> <chr> <chr>
## 1 1545 N14228 EWR IAH UA United Air Lines Inc.
## 2 1714 N24211 LGA IAH UA United Air Lines Inc.
## 3 1141 N619AA JFK MIA AA American Airlines Inc.
## 4 725 N804JB JFK BQN B6 JetBlue Airways
## 5 461 N668DN LGA ATL DL Delta Air Lines Inc.
## 6 1696 N39463 EWR ORD UA United Air Lines Inc.
## 7 507 N516JB EWR FLL B6 JetBlue Airways
## 8 5708 N829AS LGA IAD EV ExpressJet Airlines Inc.
## 9 79 N593JB JFK MCO B6 JetBlue Airways
## 10 301 N3ALAA LGA ORD AA American Airlines Inc.
## # ℹ 336,766 more rows
commercial_airports <- flights %>%
select(origin) %>%
distinct() %>%
rename(faa = origin)
airports_no_flights <- airports %>%
anti_join(commercial_airports, by = "faa") %>%
select(name) %>%
distinct()
print(airports_no_flights)
## # A tibble: 1,437 × 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
## 7 Williams County Airport
## 8 Finger Lakes Regional Airport
## 9 Shoestring Aviation Airfield
## 10 Jefferson County Intl
## # ℹ 1,427 more rows
airports_with_high_wind <- weather %>%
filter(wind_speed > 30) %>%
select(origin) %>%
distinct() %>%
rename(faa = origin) %>%
inner_join(airports, by = "faa") %>%
select(name) %>%
distinct()
print(airports_with_high_wind)
## # A tibble: 3 × 1
## name
## <chr>
## 1 Newark Liberty Intl
## 2 John F Kennedy Intl
## 3 La Guardia