```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


##Instructions
Complete this assignment in RStudio. Run all of the chunks, then Knit the markdown file to html. Upload that HTML file to the HW6 assignment on Sakai.

###Load the tidyverse package(s)
```{r}
#install.packages("tidyverse")
library(tidyverse)
```


### Load the data
If you have not already loaded the MLB salary data into R, run the following code chunk. WARNING: If you run this chunk and you already have a dataframe called "MLBPayrolls" then this will overwrite it. That probably won't be a big deal, but I just wanted to make you aware for future cases where it might be a big deal.

```{r}
library(readxl)
#download.file("https://mjwebster.github.io/DataJ/spreadsheets/MLBpayrolls.xls", "MLBPayrolls.xls")
MLBpayrolls <- read_excel("../data/MLBpayrolls.xls", sheet = "MLB Payrolls", na = "n/a", .name_repair = "universal")
MLBpayrolls
```


### 1. How much more (or less) did the Arizona Diamondbacks pay its players in 2016 than it paid in 2011?
```{r}

```


### 2. What team had the largest percent increase in payroll between 2011 and 2016? What was the rate of increase?
```{r}

```


### 3. What was the average change in teams' payroll between 2011 and 2016?
```{r}

```

### 4. What team accounted for the largest percentage of MLB payroll in 2016, and what was the percent? (Hint: You can use either mutate() and arrange() or mutate() and select() and filter())
```{r}

```

```{r}

```

