1) Using R to replicate the dataframe, icecreamShop, and its structure below using your knowledge of dataframes, row names, and ordered factors and dates.Your output should exactly match the following two lines of R code.

> icecreamShop # (LINE 1)

firstNamelastNameagejobLeveljobTitlestartDate

1702ClutchMountainhawk35bossCEO2017-05-18

1603MadelineDoe26fulltimeProgrammer2017-05-29

1604AbbyJohnson22parttimeSecretary2018-01-02

1705BenBaker31fulltimeBusiness MGR2017-11-13

1709LafayetteLeopard23parttimeIntern2019-05-29

> str(icecreamShop) # (LINE 2)

'data.frame': 5 obs. of6 variables:

$ firstName: Factor w/ 5 levels "Abby","Ben","Clutch",..

$ lastName : Factor w/ 5 levels "Baker","Doe",..

$ age: num35 26 22 31 23

$ jobLevel : Ord.factor w/ 3 levels "parttime"<"fulltime"<..

$ jobTitle : Factor w/ 5 levels "Business MGR",..

$ startDate: Date, format: "2017-05-18" "2017-05-29" ...

```{r}

```

2) Write code to create new vector in the same dataframe as question #1 containing the number of years older each person is than the youngest person in icecreamShop.That is, the youngest person would have an entry in this vector with the value 0, and everyone older would have a larger entry value.

```{r}

```

3) Write expression (meaning only one line and no semicolons) that counts the number of people in icecreamShop who work part time.

```{r}

```