```{r message=FALSE, warning=FALSE}
#LOAD PACKAGES 
library(tidyverse)
library(lubridate)

#LOAD DATA
library(nycflights13)
data("flights")
```


# 1.
Create a new column in the flights dataset called `departure_datetime` which displays the departure datetime (for example, 2013-01-01 05:15:00)

```{r}

```


# 2. 
Create a new column in the flights dataset called  `sched_departure_datetime` which displays the scheduled departure datetime (for example, 2013-01-01 05:15:00)

```{r}

```

# 3.
Use an appropriate function to calculate the difference, in minutes, between the scheduled departure and the actual departure time. Save your results in a new column called `calc_dep_delay`. Note that your new column `calc_dep_delay` should have the same values as `dep_delay`.  

```{r}

```


# 4.
Create a new column called `overnight` which displays a 1 if the flights is overnight and 0 if the flight is not overnight. Hint: If the flight is overnight, the arrival time will be before the departure time. 

```{r}

```


# 5.
Calculate a new column called `calc_arriv_datetime` which is calculated by taking the `departure_datetime` and adding the `airtime`. Note that `airtime` is given in minutes.  The time in the `calc_arrive_datetime` should match up with the time in the `arr_time` column.  *Note: this might not match up perfectly with the actual arrival time*

```{r}

```


