NYFlights13 Assignment

library(tidyverse)

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library(nycflights13)

data <- nycflights13::flights

data("flights")

head(flights)

## # A tibble: 6 × 19
##    year month   day dep_time sched_dep…¹ dep_d…² arr_t…³ sched…⁴ arr_d…⁵ carrier
##   <int> <int> <int>    <int>       <int>   <dbl>   <int>   <int>   <dbl> <chr>  
## 1  2013     1     1      517         515       2     830     819      11 UA     
## 2  2013     1     1      533         529       4     850     830      20 UA     
## 3  2013     1     1      542         540       2     923     850      33 AA     
## 4  2013     1     1      544         545      -1    1004    1022     -18 B6     
## 5  2013     1     1      554         600      -6     812     837     -25 DL     
## 6  2013     1     1      554         558      -4     740     728      12 UA     
## # … with 9 more variables: flight <int>, tailnum <chr>, origin <chr>,
## #   dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>,
## #   time_hour <dttm>, and abbreviated variable names ¹​sched_dep_time,
## #   ²​dep_delay, ³​arr_time, ⁴​sched_arr_time, ⁵​arr_delay

dist <- (flights$distance)

airtime <- (flights$air_time)

data1 <- mutate(data, speed = dist / (airtime / 60))

ggplot(data1, aes_string(x = "airtime", y = "speed",color = "carrier")) +
geom_point(na.rm = TRUE) +
ggtitle("Speed Vs Time in Air") +
xlab("Amount of time in air") +
ylab("Speed")

## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation ideoms with `aes()`

My graph is Speed Vs. Amount of time in the air. I used the mutate command to create “speed” and compared how fast the planes go and how long they’re in the mood. To get “speed,” I divided distance over time divided by 60. I want to highlight all the data is very consistent except for a few outliers. I had trouble getting rid of NAs but used a command in Geompoint to get rid of NAs.I also made the color from where the planes were landing, their seems to be some correlation between this.