---
title: "Data Visualization: Alluvial Plot"
output: 
  flexdashboard::flex_dashboard:
    storyboard: true
    orientation: columns
    source_code: embed
    vertical_layout: fill
    theme: simplex
---



```{r setup, include=FALSE}


# PACKAGES / LIBRARIES:

library(flexdashboard)
library(tidyverse)
library(easyalluvial)
library(parcats)
library(ggthemr)

df_penguins <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-28/penguins.csv') 

df_penguins <- df_penguins %>%
  na.omit() %>%
  select(Species = species, 
         Island = island, 
         Sex = sex, 
         `Bill Length` = bill_length_mm, 
         `Flipper Length` = flipper_length_mm, 
         `Body Mass` = body_mass_g)
  

```


Basic Alluvial Plot 
=================================================================================================


```{r, out.width="100%", fig.width=10, fig.height=7}

palette = c('#8DD3C7', '#FDBF6F', "#FB9A99")


alluvial_wide( data = df_penguins, 
               max_variables = 6, 
               fill_by = 'first_variable',
               col_vector_flow = palette, 
               col_vector_value = palette) +
  labs(title = "Palmer Penguins",
       subtitle = "Tidytuesday 2020, Week 31",
       caption = "HH: High, High, MH: Medium High, M: Medium, ML: Medium Low, LL: Low Low") +
  theme_dark()



```




Alluvial Plot with Marginal Histogram
=================================================================================================

```{r, out.width="100%", fig.width=10, fig.height=7}

x <- alluvial_wide( data = df_penguins, 
               max_variables = 6, 
               fill_by = 'first_variable',
               col_vector_flow = palette, 
               col_vector_value = palette) +
  theme_dark()

x %>% add_marginal_histograms(df_penguins) 

```



Interactive Alluvial Plot
=================================================================================================

```{r, out.width="100%", fig.width=10, fig.height=7}

parcats(x, marginal_histograms = TRUE, data_input = df_penguins)

```