---
title: "Hints"
date: "2019-09-03"
publishDate: "2019-08-20"
output:
  html_document:
    highlight: default
    toc: false
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<div id="hints" class="section level1">
<h1>Hints</h1>
<ol start="0" style="list-style-type: decimal">
<li>Load packages <code>tidyverse</code>, <code>sf</code>, and <code>tmap</code>.</li>
<li>Use the <code>read_csv</code> function to load the health centre csv file.</li>
<li>Use the <code>st_read</code> function to load the shape files of the admin 2 boundaries.</li>
<li>Use the <code>st_as_sf</code> function, type <code>?st_as_sf</code> into the console to get more details. You will need to say which columns are the coordinates and tell the function what crs is needed.</li>
<li>Use <code>st_transform</code> to reproject the data. For Haiti, the EPSG code for UTM is either 44132 or 32618. Use the internet or trial and error in R to see which code it is.</li>
<li>Use <code>st_buffer</code> to create a buffer around the health centres locations.</li>
<li><code>st_union</code> can be used to turn many spatial object into a single spatial object.</li>
<li>Use the same process as in step six but on the admin 2 spatial data frame.</li>
<li><code>st_difference</code> will calculate the difference between two areas this will give you the regions that are further than 5km from a health facility.</li>
<li>Use <code>tmap</code> to create a map. <code>tm_shape()</code>, <code>tm_polygons()</code>, and <code>tm_dots()</code>.</li>
</ol>
<p><a href='/02_intro_spatial/intro_spatial_solutions/'>For further help see our solution</a>.</p>
<p><a href="../../intro_spatial/index.html">Return to the practical</a>.</p>
</div>