total_distance <- flights %>% group_by(dest) %>% summarise(total_distance = sum(distance, na.rm = TRUE)) total_distance

flights <- flights %>% mutate(month = recode(month, 1 = “January”, 2 = “February”, 3 = “March”, 4 = “April”, 5 = “May”, 6 = “June”, 7 = “July”, 8 = “August”, 9 = “September”, 10 = “October”, 11 = “November”, 12 = “December”)) head(flights)

flights <- flights %>% mutate(air_time_hours = air_time / 60) head(flights)

penguins_summary <- penguins %>% group_by(species, sex) %>% summarise(mean_bill_length_mm = mean(bill_length_mm, na.rm = TRUE)) %>% pivot_wider(names_from = sex, values_from = mean_bill_length_mm) %>% filter(!is.na(female) & !is.na(male)) penguins_summary

total_distance <- flights %>% group_by(dest) %>% summarise(total_distance = sum(distance, na.rm = TRUE)) total_distance

flights <- flights %>% mutate(month = recode(month, 1 = “January”, 2 = “February”, 3 = “March”, 4 = “April”, 5 = “May”, 6 = “June”, 7 = “July”, 8 = “August”, 9 = “September”, 10 = “October”, 11 = “November”, 12 = “December”)) head(flights)

flights <- flights %>% mutate(air_time_hours = air_time / 60) head(flights)

penguins_summary <- penguins %>% group_by(species, sex) %>% summarise(mean_bill_length_mm = mean(bill_length_mm, na.rm = TRUE)) %>% pivot_wider(names_from = sex, values_from = mean_bill_length_mm) %>% filter(!is.na(female) & !is.na(male)) penguins_summary