Data ที่นำมาเล่นวันนี้จะเป็นตัว Nycflights23 เป็นข้อมูลการบินของ New Yorks City Airport ในปี 2023 และข้อมูลสภาพอากาศ, ข้อมูล Airport, ข้อมูลของตัวเครื่องบิน
data("flights")
View(flights)
glimpse(flights)
glimpse(weather)
?flights
# 1.How many flight that delay between
# Nov - Dec group by day
flight_counts <- flights %>%
filter(month %in% c(11, 12) & dep_delay > 0) %>%
group_by(month, day) %>%
arrange(-day) %>%
summarise(count_total = n()) %>%
View()
# 2.top 5 flight that contain most distance
# flight start with (1,2,3)
top5flightdis <- flights %>%
filter(grepl("^[123]", flight)) %>%
select(flight, distance) %>%
group_by(flight) %>%
summarise(total_distance = sum(distance)) %>%
arrange(-total_distance) %>%
head(5) %>%
View()
# 3.How many flight that dest at LAS, LIT
# Departure between 14.00 - 16.00
flightdep <- flights %>%
select(flight, dest, dep_time) %>%
filter(dest %in% c("LAS","LIT")
& dep_time >= 1400
& dep_time <= 1600) %>%
group_by(dest) %>%
summarise(flight_count =n())
result3 <- flightdep %>%
inner_join(airports, by = c("dest" = "faa")) %>%
rename(airport = name) %>%
select(airport, flight_count) %>%
View()
# 4.Departed in Summer (July, August, September)
summer_carrier <- flights %>%
select(carrier,month) %>%
filter(month %in% c(7,8,9)) %>%
group_by(carrier,month) %>%
summarise(total = n())
result4 <- summer_carrier %>%
inner_join(airlines, by = "carrier") %>%
select(carrier, name, month, total) %>%
View()
# 5 Arrived more than 2 hours late but didn't leave late
# display On-Time or Early
result5 <- flights %>%
select(flight, arr_delay, dep_delay) %>%
filter(arr_delay > 120, dep_delay <= 0) %>%
mutate(status = if_else(dep_delay == 0,
"On-Time",
"Early")) %>%
View()
NokKrob นกกรอบ 
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