---
title: "Choropleth Maps and Heatmaps"
author: "Prof. Eric A. Suess"
date: "November 9, 2022"
output:
  ioslides_presentation: default
  beamer_presentation: default
---

## Chloropleth maps and Heatmaps

Today we will discuss the use of choropleth maps and heatmaps.

**Choropleth** maps add color to states relative to a variable.

**Heatmaps** visual the values in a matrix by add color relative to a variable(s), usually down columns.

## Choropleth maps

The R packages *choroplethr* and *choroplethrMaps* can be used to make choropleth maps.

To learn about this package consider taking the [free course](https://arilamstein.com/open-source/)

## Choropleth maps
```{r message=FALSE}
library(tidyverse)
library(choroplethr)
library(choroplethrMaps)

data(df_pop_state)
head(df_pop_state, 15)
```

## Choropleth maps
```{r}
state_choropleth(df_pop_state, 
                 title  = "US 2012 State Population Estimates", 
                 legend = "Population")
```

## Heatmap
```{r}
data(df_state_demographics)
# head(df_state_demographics)

df_state_demographics <- df_state_demographics %>% arrange(total_population)

X <- data.matrix(df_state_demographics[,2:8])

row.names(X) <- df_state_demographics[,1]

head(X)
```

## Heatmap using base R

```{r}
heatmap(X, Rowv=NA, Colv=NA, col = cm.colors(256), scale = "column")
```

## Heatmap using base R

```{r}
heatmap(X, Rowv=NA, Colv=NA, col = heat.colors(256), scale = "column")
```

## Heatmap using base R

```{r}
library(RColorBrewer)

heatmap(X, Rowv=NA, Colv=NA, col = brewer.pal(9, "Blues"), scale = "column")
```

## Heatmaply, using plotyly

```{r message=FALSE}
library(plotly)
library(heatmaply)

heatmaply(X,scale = "col")
```

## shinyHeatmaply, using plotyly

```{r eval=FALSE}
library(shinyHeatmaply)

launch_heatmaply(X)

```

## Shiny Heatmap

Check out the [shinyheatmap](http://shinyheatmap.com/) webpage.