Assignment 5 Joins and More

library(nycflights13)
library(tidyverse)

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1. join + filter - Which airplanes fly LGA to XNA (1 POINT)

q1 <- flights %>%
  filter(origin == "LGA", dest == "XNA") %>%
  left_join(planes, by = "tailnum") %>%
  select(carrier, flight, tailnum)

head(q1)

## # A tibble: 6 × 3
##   carrier flight tailnum
##   <chr>    <int> <chr>  
## 1 MQ        4534 N722MQ 
## 2 MQ        4525 N719MQ 
## 3 MQ        4413 N739MQ 
## 4 MQ        4534 N719MQ 
## 5 MQ        4525 N711MQ 
## 6 MQ        4413 N723MQ

2. join - Add the airline name to the flights table (1 POINT)

q2 <- flights %>%
  left_join(airlines, by = c("carrier" = "carrier")) %>%
  select(year, month, day, dep_time, arr_time, flight, name)
head(q2)

## # A tibble: 6 × 7
##    year month   day dep_time arr_time flight name                  
##   <int> <int> <int>    <int>    <int>  <int> <chr>                 
## 1  2013     1     1      517      830   1545 United Air Lines Inc. 
## 2  2013     1     1      533      850   1714 United Air Lines Inc. 
## 3  2013     1     1      542      923   1141 American Airlines Inc.
## 4  2013     1     1      544     1004    725 JetBlue Airways       
## 5  2013     1     1      554      812    461 Delta Air Lines Inc.  
## 6  2013     1     1      554      740   1696 United Air Lines Inc.

3. join + select + distinct() - Which airports have no commercial flights (1 POINT)

q3 <- airports %>%
  anti_join(flights, by = c("faa" = "origin")) %>%
  anti_join(flights, by = c("faa" = "dest")) %>%
  select(faa, name) %>%
  distinct()
head(q3)

## # A tibble: 6 × 2
##   faa   name                          
##   <chr> <chr>                         
## 1 04G   Lansdowne Airport             
## 2 06A   Moton Field Municipal Airport 
## 3 06C   Schaumburg Regional           
## 4 06N   Randall Airport               
## 5 09J   Jekyll Island Airport         
## 6 0A9   Elizabethton Municipal Airport