delete_dashboard_R.qmd

---
title: "Palmer Penguins"
format: dashboard
---

```{r}
#| include: false

library(tidyverse)
library(palmerpenguins)
# data(package = 'palmerpenguins')

ojs_define(penguins_OJS = penguins)
```

```{ojs}
// | output: false
penguins = transpose(penguins_OJS)
```



# Page 1

## {.sidebar}
```{ojs}
viewof bill_length_min = Inputs.range(
  [32, 50], 
  {value: 35, step: 1, label: "Bill length (min):"}
)
viewof islands = Inputs.checkbox(
  ["Torgersen", "Biscoe", "Dream"], 
  { value: ["Torgersen", "Biscoe"], 
    label: "Islands:"
  }
)
```

```{ojs}
filtered = penguins.filter(function(penguin) {
  return bill_length_min < penguin.bill_length_mm &&
         islands.includes(penguin.island);
})
```

## Row

```{r}
#| content: valuebox
#| title: "Penguin Count"
#| color: primary
nrow(penguins)
```

```{r}
#| content: valuebox
#| title: "Penguin Count"
#| color: green
nrow(penguins)
```

::: {.card title="My Title"}
This text will be displayed within a card
:::


## Row 


```{ojs}
Plot.rectY(filtered, 
  Plot.binX(
    {y: "count"}, 
    {x: "body_mass_g", fill: "species", thresholds: 20}
  ))
  .plot({
    facet: {
      data: filtered,
      x: "sex",
      y: "species",
      marginRight: 80
    },
    marks: [
      Plot.frame(),
    ]
  }
)
```






# Page 2

## Row

```{r}
#| content: valuebox
#| title: "Penguin Count"
#| color: primary
nrow(penguins)
```

```{r}
#| content: valuebox
#| title: "Penguin Count"
#| color: green
nrow(penguins)
```

::: {.card title="My Title"}
This text will be displayed within a card
:::


## Row {height=70%}

```{r}
head(penguins)
```

```{r}
#| title: Option 2
knitr::kable(penguins)
```

## Row {height=30%}

### Column {.tabset}

```{ojs}
//| title: Chart 2
Plot.dot(
    penguins, 
    {x: "bill_length_mm", y: "bill_depth_mm", fill: "species"}
    ).plot()
```


```{r}
#| title: Chart 3
print("1")
```

### Column

```{r}
print("1")
```

::: {.card title="My Title"}
This text will be displayed within a card
:::


# Page 3

I'm thinking that if you use ggplot2 and you want interactivity, the solution is shiny. 

If you think shiny is a little silly and would prefer a more professional approach and still be in Quarto, use observable. It has plotting capabilities and interactive user input capabilities. The R/Python to ObservableJS connection is `ojs_define()`. I would not wrangle in observable though. 
At the same time, if you're in the R space, use R things!