A16

---
title: "A16 by Noah Perry & Andrew Hall"
output:
   flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
---

```{r setup, include=FALSE}
library(tidyverse)
library(flexdashboard)
library(ggthemes)
library(plotly)

#Read the Manheim data file <http://www.richardtwatson.com/data/manheim.csv> and create a 2x2 dashboard using flexdashboard showing.
manheim <- read_csv("http://www.richardtwatson.com/data/manheim.csv")
manheim <- as_tibble(manheim)
manheim$sale<-as.factor(manheim$sale)
manheim$model<-as.factor(manheim$model)
manheim
obsTable <- xtabs(~sale+model, data=manheim)

```


Row
-------------------------------------

### Frequency of each type of sale for each different model

```{r}
#A table with the number of observations for each combination of the sale and model factors (use xtabs).
ftable(obsTable)
```

### Box Plot showing Plotting distributions for type of sale and amount of sale

```{r}
#A boxplot of price by sale
g <- ggplot(manheim, aes(sale, price))
g + geom_boxplot(varwidth=T, fill="plum") +
    labs(title="Box plot: Price by sale",
         x="Sales",
         y="Sales")
ggplotly(p = ggplot2::last_plot())
```

Row
-------------------------------------

### Plotting price vs mileage for each type of sale

```{r}
#A scatter plot of miles by price for each model
ggplot(manheim, aes(x=miles, y=price, color = model)) +
  geom_point()
ggplotly(p = ggplot2::last_plot())
```

### Plotting price vs mileage for each type of sale

```{r}
#A scatter plot of miles by price for each sale
#Submit a pdf of the code and the dashboard.
ggplot(manheim, aes(x=miles, y=price, color = sale)) +
  geom_point()
ggplotly(p = ggplot2::last_plot())
```