---
title: "My awesome dashboard"
output: 
  flexdashboard::flex_dashboard:
    theme: journal
    orientation: rows
    source_code: embed
---

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

Tab ONE
================================================

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

### Total penguins
```{r}
valueBox(nrow(penguins), color = "cornsilk")
```

### Penguin species
```{r}
valueBox(length(unique(penguins$species)), color = "lightcyan")
```

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

### A nice scatterplot

```{r}
p <- ggplot(data = penguins, aes(x = flipper_length_mm, y = body_mass_g)) + geom_point(aes(color = species)) +
  scale_color_manual(values = c("coral", "cyan4", "gray30")) +
  theme_minimal()

ggplotly(p)
```

### A map?
```{r}
leaflet() %>%
  addTiles() %>%  # Add default OpenStreetMap map tiles
  addMarkers(lng=-119.702, lat=34.423, popup="NCEAS")
```

### A histogram of Chinstraps

```{r}
penguins %>% 
  filter(species == "Chinstrap") %>% 
  ggplot(aes(x = bill_depth_mm)) +
  geom_histogram() + 
  theme_minimal()
```


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

### Something else? 
```{r}
valueBox(length(unique(penguins$species)), color = "honeydew")
```


Tab TWO
=====================================

### Another graph
```{r}
penguins %>% 
  ggplot(aes(x = species, y = bill_depth_mm)) +
  geom_col(aes(fill = island)) +
  coord_polar() + 
  theme_minimal()
```

### Cool more plotly

```{r}
p <- penguins %>% 
  count(species) %>% 
  ggplot(aes(x = species, y = n)) +
  geom_col() +
  theme_minimal()

ggplotly(p)
```