##Load the CSV file FlightsWithAirlines.csv containing into a data frame called df.flights. Do not load the text (strings) attributes (columns) as factors, so use stringsAsFactors = FALSE as a parameter in your function that loads the data; load them as text. Load the file from the URL rather than downloading the file to your computer. To get the URL for the CSV, right-click on the link and then select “Copy Link Address” or a similar menu option for your browser; do not click on the link as that will cause the browser to attempt to download and display the file.##
df.flights <- read.csv ("FlightsWithAirlines.csv")##Use the R function str() to understand the structure of the data frame.##
str(df.flights)## 'data.frame': 18 obs. of 14 variables:
## $ year : int 2022 2022 2022 2022 2022 2022 2022 2022 2022 2022 ...
## $ month : int 9 2 1 6 1 5 5 10 6 8 ...
## $ day : int 18 14 7 7 30 2 5 24 16 18 ...
## $ dep_hr : int 2 12 13 22 24 11 5 20 5 2 ...
## $ dep_min : int 38 25 56 56 2 2 50 23 31 38 ...
## $ dep_delay: int 0 13 9 7 14 49 13 50 30 20 ...
## $ carrier : chr "UA" "AA" "AA" "B6" ...
## $ airline : chr "United" "American Airlines" "American Airlines" "JetBlue" ...
## $ country : chr "USA" "USA" "USA" "USA" ...
## $ flight : int 1545 441 1141 725 461 1696 507 5708 411 1545 ...
## $ equip : chr "B737-8" "B777" "A321" "A321" ...
## $ tailnum : chr "N14228" "N24211" "N619AA" "N804JB" ...
## $ origin : chr "EWR" "MIA" "JFK" "JFK" ...
## $ dest : chr "IAH" "GRU" "MIA" "BQN" ...##Use the R function str() to understand the structure of the data frame.##
head(df.flights,4)## year month day dep_hr dep_min dep_delay carrier airline country
## 1 2022 9 18 2 38 0 UA United USA
## 2 2022 2 14 12 25 13 AA American Airlines USA
## 3 2022 1 7 13 56 9 AA American Airlines USA
## 4 2022 6 7 22 56 7 B6 JetBlue USA
## flight equip tailnum origin dest
## 1 1545 B737-8 N14228 EWR IAH
## 2 441 B777 N24211 MIA GRU
## 3 1141 A321 N619AA JFK MIA
## 4 725 A321 N804JB JFK BQN##Use the R function str() to understand the structure of the data frame.##
tail(df.flights,5)## year month day dep_hr dep_min dep_delay carrier airline country
## 14 2023 2 30 24 2 0 DL Delta Airlines USA
## 15 2023 6 2 11 2 68 UA United USA
## 16 2023 6 5 5 50 850 B6 JetBlue USA
## 17 2023 11 24 20 23 20 NK Spirit Airways USA
## 18 2024 7 16 5 31 18 LH Lufthansa Germany
## flight equip tailnum origin dest
## 14 461 B757-2 N668DN LGA ATL
## 15 1696 B737-MAX N39463 EWR ORD
## 16 507 A321 N516JB EWR FLL
## 17 5708 A321 N829AS BOS PBI
## 18 411 B747-4 N593JB CLT MUC##Display only the carrier, flight, origin, and destination columns from the dataframe.##
df.flights [c(7, 10, 13, 14)]## carrier flight origin dest
## 1 UA 1545 EWR IAH
## 2 AA 441 MIA GRU
## 3 AA 1141 JFK MIA
## 4 B6 725 JFK BQN
## 5 DL 461 LGA ATL
## 6 UA 1696 EWR ORD
## 7 B6 507 EWR FLL
## 8 NK 5708 BOS PBI
## 9 LH 411 CLT MUC
## 10 UA 1545 EWR IAH
## 11 AA 441 MIA GRU
## 12 AA 1141 JFK MIA
## 13 B6 725 JFK BQN
## 14 DL 461 LGA ATL
## 15 UA 1696 EWR ORD
## 16 B6 507 EWR FLL
## 17 NK 5708 BOS PBI
## 18 LH 411 CLT MUC##Calculate the average (mean) departure delay (column named dep_delay) and display the result in R using the cat() function. Hint: Look up functions in Help in R Studio or online.##
mean = mean(df.flights [,"dep_delay"])
cat("average departure delay =" , round(mean, 1))## average departure delay = 69.7##Add a new column ‘tod’ to the data frame with a value of “am” or “pm” depending whether the departure time was AM (before 12 noon) or PM (on or after 12 noon). The time in the data file is in 24-hour format. Hint: Look up how to use the ifelse function. Use the dep_hr column. Print the dataframe to ensure the new column is there and is correct, but only display the carrier, flight, dep_hr, and the new tod columns.##
df.flights$tod = ifelse(df.flights$dep_hr <12, "am", "pm")
head(df.flights[c("dep_hr", "tod", "carrier", "flight")])## dep_hr tod carrier flight
## 1 2 am UA 1545
## 2 12 pm AA 441
## 3 13 pm AA 1141
## 4 22 pm B6 725
## 5 24 pm DL 461
## 6 11 am UA 1696##For each flight, display the carrier, flight number, and the actual departure time (scheduled departure plus departure delay) for flights that were delayed. Display the time in the format hh:mm in 24-hour format, e.g., display 23:20 rather than 11:20 or 11:20PM.##
df.flights$actualtime <- (df.flights$dep_hr * 60 + df.flights$dep_min + df.flights$dep_delay)
df.flights$actualtime <- df.flights$actualtime %% 1440
df.flights$actualtime <- sprintf(
"%02d:%02d",
df.flights$actualtime %/% 60,
df.flights$actualtime %% 60)
df.flights[df.flights$dep_delay > 0, c("carrier", "equip", "actualtime")]## carrier equip actualtime
## 2 AA B777 12:38
## 3 AA A321 14:05
## 4 B6 A321 23:03
## 5 DL B757-2 00:16
## 6 UA B737-MAX 11:51
## 7 B6 A321 06:03
## 8 NK A321 21:13
## 9 LH B747-4 06:01
## 10 UA B737-8 02:58
## 11 AA B777 13:56
## 13 B6 A321 22:58
## 15 UA B737-MAX 12:10
## 16 B6 A321 20:00
## 17 NK A321 20:43
## 18 LH B747-4 05:49