── 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
library(nycflights23)data(flights)data(airlines)
Visualization of the data
library(dplyr)any(is.na(flights))
[1] TRUE
summary(flights)
year month day dep_time sched_dep_time
Min. :2023 Min. : 1.000 Min. : 1.00 Min. : 1 Min. : 500
1st Qu.:2023 1st Qu.: 3.000 1st Qu.: 8.00 1st Qu.: 931 1st Qu.: 930
Median :2023 Median : 6.000 Median :16.00 Median :1357 Median :1359
Mean :2023 Mean : 6.423 Mean :15.74 Mean :1366 Mean :1364
3rd Qu.:2023 3rd Qu.: 9.000 3rd Qu.:23.00 3rd Qu.:1804 3rd Qu.:1759
Max. :2023 Max. :12.000 Max. :31.00 Max. :2400 Max. :2359
NA's :10738
dep_delay arr_time sched_arr_time arr_delay
Min. : -50.00 Min. : 1 Min. : 1 Min. : -97.000
1st Qu.: -6.00 1st Qu.:1105 1st Qu.:1135 1st Qu.: -22.000
Median : -2.00 Median :1519 Median :1551 Median : -10.000
Mean : 13.84 Mean :1497 Mean :1552 Mean : 4.345
3rd Qu.: 10.00 3rd Qu.:1946 3rd Qu.:2007 3rd Qu.: 9.000
Max. :1813.00 Max. :2400 Max. :2359 Max. :1812.000
NA's :10738 NA's :11453 NA's :12534
carrier flight tailnum origin
Length:435352 Min. : 1.0 Length:435352 Length:435352
Class :character 1st Qu.: 364.0 Class :character Class :character
Mode :character Median : 734.0 Mode :character Mode :character
Mean : 785.2
3rd Qu.:1188.0
Max. :1972.0
dest air_time distance hour
Length:435352 Min. : 18.0 Min. : 80.0 Min. : 5.00
Class :character 1st Qu.: 77.0 1st Qu.: 479.0 1st Qu.: 9.00
Mode :character Median :121.0 Median : 762.0 Median :13.00
Mean :141.8 Mean : 977.5 Mean :13.35
3rd Qu.:177.0 3rd Qu.:1182.0 3rd Qu.:17.00
Max. :701.0 Max. :4983.0 Max. :23.00
NA's :12534
minute time_hour
Min. : 0.00 Min. :2023-01-01 05:00:00.00
1st Qu.:10.00 1st Qu.:2023-03-30 20:00:00.00
Median :29.00 Median :2023-06-27 08:00:00.00
Mean :28.53 Mean :2023-06-29 10:02:22.39
3rd Qu.:45.00 3rd Qu.:2023-09-27 11:00:00.00
Max. :59.00 Max. :2023-12-31 23:00:00.00
Most flights from JFK and LAX, and the Average arrival delay
results <- flights %>%filter(origin =="JFK", dest =="LAX") %>%group_by(carrier) %>%summarize(num_flights =n(),avg_arr_delay =mean(arr_delay, na.rm =TRUE) ) %>%inner_join(airlines, by ="carrier") %>%arrange(desc(num_flights))results
# A tibble: 3 × 4
carrier num_flights avg_arr_delay name
<chr> <int> <dbl> <chr>
1 B6 3584 4.68 JetBlue Airways
2 AA 3246 -5.74 American Airlines Inc.
3 DL 3215 6.23 Delta Air Lines Inc.
library(ggplot2) Visual <-ggplot(data = combined_data,aes(x= name, y = flight, fill = carrier)) +geom_col() +coord_flip() +labs(title ="Number of Flights by Airline from NYC 2023",x ="Airline",y ="Number of Flights ",fill ="Airline code",caption ="Source: nycflights23 dataset (flights & airlines tables)" ) +scale_fill_brewer(palette ="Set3") +theme_minimal() Visual
Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette Set3 is 12
Returning the palette you asked for with that many colors
#Recognition of ChatGPT for the line scale_fil_brewer.
