library(data.table)

df = fread("2008.csv") 

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# df[rows, columns, by]

df[Origin == "JFK",]  # select flights from JFK

df[, .(Origin, Distance)] # select columns

df[, .N, by = UniqueCarrier] # count flights per carrier

df[, date := {
  date = paste(Year, Month, DayofMonth, sep = "-")
  date = ymd(date)
}]

# get weekday and day of the year
df[, `:=` (
  week.day = wday(date, label = T, abbr = T),
  year.day = yday(date)
)]

df[, `:=` (
  distance = Distance * 1.852,
  hr = AirTime / 60
)]

# calculate speed and condense dataframe
dfx = df[, speed := distance / hr]
dfx = dfx[ , .(date, distance, hr, speed, TailNum, 
               UniqueCarrier, Origin, Dest)]

dfx[is.na(speed), speed := 0]
dfx[is.infinite(speed), speed := 0]

data(airports, package = "nycflights13")
setDT(airports)

dest.counts = df[Origin == "JFK", .N, by = Dest]

dest.counts = merge(dest.counts, 
                    airports, 
                    by.x = "Dest", by.y = "faa", 
                    all.x = T)