mmc_surrounds.Rmd

---
title: "Choropleth - stroke by postcode"
output:
    html_document:
        toc: true
        toc_float: true
        number_sections: false
        theme: flatly
    md_document:
        variant: markdown_github
        number_sections: true
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  warning = TRUE,
  message = TRUE,
  width = 120,
  comment = "#>",
  fig.retina = 2,
  fig.path = "README-",
  fig.width = 10
)
knitr::read_chunk("mmc_surrounds.R")
```

Choropleths are a staple of geospatial visualization. The idea of this 
example is to introduced those basics in stroke context.

The example loads the data, estimates annual stroke incidence based on data 
from the NEMISIS study, performs a join, calculates some
geospatial measures, filters postcodes based on distance to the hospital and displays the results.


## 0. Package loading

```{r RPackageCheck, echo=FALSE}

```
```{r Libraries, message=FALSE}

```

## 1. Loading census and boundary data

```{r CensusData, message=FALSE, warning=FALSE}

```

## 2. Combine demographics and spatial data

```{r JoinCensusAndBoundaries}

```

## 3. Geocode hospital location

```{r MonashMedicalCentre}

```

## 4. Compute per-postcode stroke incidence

```{r StrokeIncidence}

```


## 5. Compute distance to hospital from postcode
```{r SpatialComputations}

```

## 6. Discard remote postcodes
```{r FilteringPostcodes}

```

## 7. Interactive display of the result
```{r InteractiveDisplay}

```