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<h1 class="quarto-secondary-nav-title">Exercice</h1>
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<li><a href="#create-your-working-environment" id="toc-create-your-working-environment" class="nav-link active" data-scroll-target="#create-your-working-environment">Create your working environment</a></li>
<li><a href="#load-and-visualize-the-data" id="toc-load-and-visualize-the-data" class="nav-link" data-scroll-target="#load-and-visualize-the-data">Load and visualize the data</a>
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<li><a href="#steps" id="toc-steps" class="nav-link" data-scroll-target="#steps">Steps</a></li>
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<li><a href="#merge-data-with-shapefiles" id="toc-merge-data-with-shapefiles" class="nav-link" data-scroll-target="#merge-data-with-shapefiles">Merge data with shapefiles</a>
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<li><a href="#solution-1" id="toc-solution-1" class="nav-link" data-scroll-target="#solution-1">Solution</a></li>
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<li><a href="#map-the-count-data" id="toc-map-the-count-data" class="nav-link" data-scroll-target="#map-the-count-data">Map the count data</a>
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<li><a href="#steps-2" id="toc-steps-2" class="nav-link" data-scroll-target="#steps-2">Steps</a></li>
<li><a href="#solution-2" id="toc-solution-2" class="nav-link" data-scroll-target="#solution-2">Solution</a></li>
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<li><a href="#transform-data-to-incidence" id="toc-transform-data-to-incidence" class="nav-link" data-scroll-target="#transform-data-to-incidence">Transform data to incidence</a>
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<li><a href="#steps-3" id="toc-steps-3" class="nav-link" data-scroll-target="#steps-3">Steps</a></li>
<li><a href="#solution-3" id="toc-solution-3" class="nav-link" data-scroll-target="#solution-3">Solution</a></li>
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<li><a href="#work-with-averaged-incidence" id="toc-work-with-averaged-incidence" class="nav-link" data-scroll-target="#work-with-averaged-incidence">Work with averaged incidence</a></li>
<li><a href="#let-look-at-hospital-distribution" id="toc-let-look-at-hospital-distribution" class="nav-link" data-scroll-target="#let-look-at-hospital-distribution">Let look at hospital distribution</a></li>
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<p>This exercice aims at summarizing what was shown througout the training. It includes dealing with shapefile and epidemiological data in “almost real” conditions. The data represents the number of cases of an imaginary disease across Cambodia called R infections from 2018 to 2022. This infection spread rapidly and started during a training in Phnom Penh. Symptoms are very specific and includes installing Rstudio, loading data and using R software for spatial analysis and mapping.</p>
<p>In R, it exist many differents implementation solution that lead to the same results. The solution presented here just provides one implementation among thousands of possibilities.</p>
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<ol type="1">
<li><p>Comment your code ! (<code># important informations on the code</code>)</p></li>
<li><p>Check your R objects ! (<code>plot()</code>, <code>print()</code>, <code>View()</code> , …)</p></li>
<li><p>Listen to R outputs ! (Errors AND Warnings)</p></li>
<li><p>Get help ! (<code>?name_of_function</code>, internet, other users)</p></li>
<li><p>Keep calm and take a break !</p></li>
</ol>
</div>
</div>
<section id="create-your-working-environment" class="level2">
<h2 class="anchored" data-anchor-id="create-your-working-environment">Create your working environment</h2>
<ol type="1">
<li><p>Create a R project called “RGeotraining”</p></li>
<li><p>Download and unzip the training data into a directory called “data/”.</p></li>
</ol>
<p><a href="https://e1.pcloud.link/publink/show?code=XZjIQYZvgGOVnUBzVYonPJugrNDLfWSscXk" class="btn btn-primary btn-sm" role="button">Download example data</a></p>
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<ol start="3" type="1">
<li><p>Create a directory called “img” for image outputs</p></li>
<li><p>Download and unzip shapefile of Cambodian provinces in the ‘data/’ directory: <a href="https://data.humdata.org/dataset/wfp-geonode-cambodia-admin-boundaries-level-1-provinces">Province shapefile</a></p></li>
<li><p>Check your working directory using <code>getwd()</code></p></li>
</ol>
</section>
<section id="load-and-visualize-the-data" class="level2">
<h2 class="anchored" data-anchor-id="load-and-visualize-the-data">Load and visualize the data</h2>
<section id="steps" class="level3">
<h3 class="anchored" data-anchor-id="steps">Steps</h3>
<ol type="1">
<li><p>Load R libraries <code>sf</code> and <code>mapsf</code>,</p></li>
<li><p>Load province shapefile with <code>st_read()</code> and set the projection <code>st_transform()</code>,</p></li>
<li><p>Load population data with <code>read.table()</code> and sum the counts over provinces using <code>aggregate()</code>,</p></li>
<li><p>Load the number of cases per province from the csv file.</p></li>
</ol>
</section>
<section id="solution" class="level3">
<h3 class="anchored" data-anchor-id="solution">Solution</h3>
<div class="cell" data-nm="true">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co">#============================================</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="co"># 2. Load and visualize the data</span></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="co">#============================================</span></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="do">### 2.1 Load R libraries</span></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="co">#-----------------------</span></span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="co"># library(dplyr) # deals with dataframes</span></span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(sf) <span class="co"># spatial objects</span></span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(mapsf) <span class="co"># Plot </span></span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a><span class="do">### 2.2 Spatial data</span></span>
<span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a><span class="co">#----------------------</span></span>
<span id="cb1-14"><a href="#cb1-14" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-15"><a href="#cb1-15" aria-hidden="true" tabindex="-1"></a><span class="co"># Load data</span></span>
<span id="cb1-16"><a href="#cb1-16" aria-hidden="true" tabindex="-1"></a>province_sf <span class="ot"><-</span> <span class="fu">st_read</span>(<span class="st">"data/khm_admbnda_adm1_gov_20181004.shp"</span>, <span class="at">quiet =</span> <span class="cn">TRUE</span>)</span>
<span id="cb1-17"><a href="#cb1-17" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(province_sf) <span class="co"># We need to define the projection</span></span>
<span id="cb1-18"><a href="#cb1-18" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-19"><a href="#cb1-19" aria-hidden="true" tabindex="-1"></a><span class="co"># set crs</span></span>
<span id="cb1-20"><a href="#cb1-20" aria-hidden="true" tabindex="-1"></a>province_sf <span class="ot"><-</span> <span class="fu">st_transform</span>(province_sf, <span class="at">crs =</span> <span class="dv">32648</span>)</span>
<span id="cb1-21"><a href="#cb1-21" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-22"><a href="#cb1-22" aria-hidden="true" tabindex="-1"></a><span class="co"># Visualize</span></span>
<span id="cb1-23"><a href="#cb1-23" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(province_sf) <span class="co"># type of R object</span></span>
<span id="cb1-24"><a href="#cb1-24" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(province_sf) <span class="co"># dimensions of the object = n columns + 1 geometry</span></span>
<span id="cb1-25"><a href="#cb1-25" aria-hidden="true" tabindex="-1"></a><span class="fu">summary</span>(province_sf) <span class="co"># Summarize the information of the object</span></span>
<span id="cb1-26"><a href="#cb1-26" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(province_sf[,<span class="dv">1</span>]) <span class="co"># Plot the first column to look at geometry </span></span>
<span id="cb1-27"><a href="#cb1-27" aria-hidden="true" tabindex="-1"></a><span class="co"># (if you plot all of column it is sometimes too long)</span></span>
<span id="cb1-28"><a href="#cb1-28" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-29"><a href="#cb1-29" aria-hidden="true" tabindex="-1"></a><span class="do">### 2.3 Population data</span></span>
<span id="cb1-30"><a href="#cb1-30" aria-hidden="true" tabindex="-1"></a><span class="co">#--------------------------</span></span>
<span id="cb1-31"><a href="#cb1-31" aria-hidden="true" tabindex="-1"></a><span class="co"># Load </span></span>
<span id="cb1-32"><a href="#cb1-32" aria-hidden="true" tabindex="-1"></a>population_df <span class="ot"><-</span> <span class="fu">read.table</span>(<span class="at">file =</span> <span class="st">"data/Population_district_Cambodia.csv"</span>,</span>
<span id="cb1-33"><a href="#cb1-33" aria-hidden="true" tabindex="-1"></a> <span class="at">sep =</span> <span class="st">','</span>, <span class="at">header =</span> <span class="cn">TRUE</span>)</span>
<span id="cb1-34"><a href="#cb1-34" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-35"><a href="#cb1-35" aria-hidden="true" tabindex="-1"></a><span class="co"># Visualize</span></span>
<span id="cb1-36"><a href="#cb1-36" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(population_df)</span>
<span id="cb1-37"><a href="#cb1-37" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(population_df)</span>
<span id="cb1-38"><a href="#cb1-38" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(population_df)</span>
<span id="cb1-39"><a href="#cb1-39" aria-hidden="true" tabindex="-1"></a><span class="fu">colnames</span>(population_df)</span>
<span id="cb1-40"><a href="#cb1-40" aria-hidden="true" tabindex="-1"></a><span class="fu">summary</span>(population_df)</span>
<span id="cb1-41"><a href="#cb1-41" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-42"><a href="#cb1-42" aria-hidden="true" tabindex="-1"></a><span class="co"># Because we work on province we need to aggregate the values</span></span>
<span id="cb1-43"><a href="#cb1-43" aria-hidden="true" tabindex="-1"></a><span class="co"># Tips: ?aggregate</span></span>
<span id="cb1-44"><a href="#cb1-44" aria-hidden="true" tabindex="-1"></a>pop_by_district_df <span class="ot"><-</span> <span class="fu">aggregate</span>(population_df<span class="sc">$</span>T_POP, </span>
<span id="cb1-45"><a href="#cb1-45" aria-hidden="true" tabindex="-1"></a> <span class="at">by =</span> <span class="fu">list</span>(<span class="at">ADM1_PCODE =</span> population_df<span class="sc">$</span>ADM1_PCODE),</span>
<span id="cb1-46"><a href="#cb1-46" aria-hidden="true" tabindex="-1"></a> <span class="at">FUN =</span> sum)</span>
<span id="cb1-47"><a href="#cb1-47" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-48"><a href="#cb1-48" aria-hidden="true" tabindex="-1"></a><span class="fu">colnames</span>(pop_by_district_df) <span class="ot"><-</span> <span class="fu">c</span>(<span class="st">"ADM1_PCODE"</span>, <span class="st">"pop"</span>) <span class="co"># rename column for later</span></span>
<span id="cb1-49"><a href="#cb1-49" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-50"><a href="#cb1-50" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-51"><a href="#cb1-51" aria-hidden="true" tabindex="-1"></a><span class="do">### 2.4 Cases</span></span>
<span id="cb1-52"><a href="#cb1-52" aria-hidden="true" tabindex="-1"></a><span class="co">#-------------------------</span></span>
<span id="cb1-53"><a href="#cb1-53" aria-hidden="true" tabindex="-1"></a><span class="co"># Load number of cases</span></span>
<span id="cb1-54"><a href="#cb1-54" aria-hidden="true" tabindex="-1"></a>cases_df <span class="ot"><-</span> <span class="fu">read.table</span>(<span class="at">file =</span> <span class="st">"data/R_infection_monthly_cases.csv"</span>, </span>
<span id="cb1-55"><a href="#cb1-55" aria-hidden="true" tabindex="-1"></a> <span class="at">header =</span> <span class="cn">TRUE</span>, <span class="at">sep =</span> <span class="st">";"</span>)</span>
<span id="cb1-56"><a href="#cb1-56" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-57"><a href="#cb1-57" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(cases_df)</span>
<span id="cb1-58"><a href="#cb1-58" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(cases_df)</span>
<span id="cb1-59"><a href="#cb1-59" aria-hidden="true" tabindex="-1"></a><span class="fu">colnames</span>(cases_df)</span>
<span id="cb1-60"><a href="#cb1-60" aria-hidden="true" tabindex="-1"></a><span class="fu">summary</span>(cases_df)</span>
<span id="cb1-61"><a href="#cb1-61" aria-hidden="true" tabindex="-1"></a><span class="co"># What are these data ? </span></span>
<span id="cb1-62"><a href="#cb1-62" aria-hidden="true" tabindex="-1"></a><span class="co"># What represents each row ? each column ? </span></span>
<span id="cb1-63"><a href="#cb1-63" aria-hidden="true" tabindex="-1"></a><span class="co"># What is the time span ? </span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
</section>
<section id="merge-data-with-shapefiles" class="level2">
<h2 class="anchored" data-anchor-id="merge-data-with-shapefiles">Merge data with shapefiles</h2>
<section id="steps-1" class="level3">
<h3 class="anchored" data-anchor-id="steps-1">Steps</h3>
<ol type="1">
<li><p>Merge population with sf polygon using <code>merge()</code>,</p></li>
<li><p>Merge the new sf object with number of cases,</p></li>
<li><p>Identify the merging issues and correct the datasets, you can compares columns of the datasets using boolean (<code>TRUE</code>/<code>FALSE</code>) operation as <code>==</code> (is equal to), <code>%in%</code> (appear in at least once), <code>!</code> (negate, invert <code>TRUE</code> and <code>FALSE</code> values) and extract row of interest using <code>[row_selection, column_selection]</code>.</p></li>
</ol>
</section>
<section id="solution-1" class="level3">
<h3 class="anchored" data-anchor-id="solution-1">Solution</h3>
<div class="cell" data-nm="true">
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co">#=======================================================</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="co"># 3. Merge all data</span></span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a><span class="co">#=======================================================</span></span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a><span class="do">### 3.1 Merge population with sf polygons to prepare for mapping</span></span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a><span class="co">#---------------------------------------------------------------</span></span>
<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a><span class="co"># What is the key column to merge the objects (column with IDs) ?</span></span>
<span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a>province_pop_sf <span class="ot"><-</span> <span class="fu">merge</span>(pop_by_district_df, province_sf, <span class="at">by =</span> <span class="st">"ADM1_PCODE"</span>)</span>
<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(province_pop_sf) <span class="co"># What a mess !!! We lost the geometry !</span></span>
<span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a>province_pop_sf <span class="ot"><-</span> <span class="fu">merge</span>(province_sf, pop_by_district_df, <span class="at">by =</span> <span class="st">"ADM1_PCODE"</span>)</span>
<span id="cb2-13"><a href="#cb2-13" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(province_pop_sf) <span class="co"># Much better !!!</span></span>
<span id="cb2-14"><a href="#cb2-14" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-15"><a href="#cb2-15" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(province_pop_sf)</span>
<span id="cb2-16"><a href="#cb2-16" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-17"><a href="#cb2-17" aria-hidden="true" tabindex="-1"></a><span class="co"># Create a maps to represent population</span></span>
<span id="cb2-18"><a href="#cb2-18" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_export</span>(province_pop_sf, <span class="at">filename =</span> <span class="st">'img/Population_province.png'</span>, <span class="at">width =</span> <span class="dv">500</span>, <span class="at">res =</span> <span class="dv">100</span>)</span>
<span id="cb2-19"><a href="#cb2-19" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_sf)</span>
<span id="cb2-20"><a href="#cb2-20" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_sf,</span>
<span id="cb2-21"><a href="#cb2-21" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="st">"pop"</span> , </span>
<span id="cb2-22"><a href="#cb2-22" aria-hidden="true" tabindex="-1"></a> <span class="at">inches =</span> .<span class="dv">2</span>,</span>
<span id="cb2-23"><a href="#cb2-23" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"prop"</span>,</span>
<span id="cb2-24"><a href="#cb2-24" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"#000066"</span>,</span>
<span id="cb2-25"><a href="#cb2-25" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="st">"Population"</span>)</span>
<span id="cb2-26"><a href="#cb2-26" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_layout</span>(<span class="at">title =</span> <span class="st">"Population in cambodian provinces"</span>)</span>
<span id="cb2-27"><a href="#cb2-27" aria-hidden="true" tabindex="-1"></a><span class="fu">dev.off</span>()</span>
<span id="cb2-28"><a href="#cb2-28" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-29"><a href="#cb2-29" aria-hidden="true" tabindex="-1"></a><span class="do">### 3.2 Merge polygon with number of cases</span></span>
<span id="cb2-30"><a href="#cb2-30" aria-hidden="true" tabindex="-1"></a><span class="co">#---------------------------------------------------------------</span></span>
<span id="cb2-31"><a href="#cb2-31" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-32"><a href="#cb2-32" aria-hidden="true" tabindex="-1"></a><span class="co"># What is (are) the key column(s) ?</span></span>
<span id="cb2-33"><a href="#cb2-33" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf <span class="ot"><-</span> <span class="fu">merge</span>(province_pop_sf, cases_df, <span class="at">by.x =</span> <span class="st">'ADM1_EN'</span>, <span class="at">by.y =</span> <span class="st">"Province"</span>)</span>
<span id="cb2-34"><a href="#cb2-34" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(province_pop_cases_sf) <span class="co"># Perfect !</span></span>
<span id="cb2-35"><a href="#cb2-35" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(province_pop_cases_sf) <span class="co"># Why do I have only 18 province instead of 25 ? 7 missing values </span></span>
<span id="cb2-36"><a href="#cb2-36" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-37"><a href="#cb2-37" aria-hidden="true" tabindex="-1"></a><span class="co"># detect names from cases_df that do not match names in province_pop_sf</span></span>
<span id="cb2-38"><a href="#cb2-38" aria-hidden="true" tabindex="-1"></a><span class="sc">!</span>(cases_df<span class="sc">$</span>Province <span class="sc">%in%</span> province_pop_sf<span class="sc">$</span>ADM1_EN) <span class="co"># We have 6 provinces that do not match the names (FALSE value)!</span></span>
<span id="cb2-39"><a href="#cb2-39" aria-hidden="true" tabindex="-1"></a><span class="fu">sum</span>(<span class="sc">!</span>(cases_df<span class="sc">$</span>Province <span class="sc">%in%</span> province_pop_sf<span class="sc">$</span>ADM1_EN))</span>
<span id="cb2-40"><a href="#cb2-40" aria-hidden="true" tabindex="-1"></a><span class="co"># which ones ?</span></span>
<span id="cb2-41"><a href="#cb2-41" aria-hidden="true" tabindex="-1"></a>cases_df<span class="sc">$</span>Province[<span class="sc">!</span>(cases_df<span class="sc">$</span>Province <span class="sc">%in%</span> province_pop_sf<span class="sc">$</span>ADM1_EN)]</span>
<span id="cb2-42"><a href="#cb2-42" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-43"><a href="#cb2-43" aria-hidden="true" tabindex="-1"></a><span class="co"># What are the names of these provinces in the sf file ?</span></span>
<span id="cb2-44"><a href="#cb2-44" aria-hidden="true" tabindex="-1"></a>province_pop_sf<span class="sc">$</span>ADM1_EN[<span class="sc">!</span>(province_pop_sf<span class="sc">$</span>ADM1_EN <span class="sc">%in%</span> cases_df<span class="sc">$</span>Province)]</span>
<span id="cb2-45"><a href="#cb2-45" aria-hidden="true" tabindex="-1"></a><span class="co"># Some names do not have the same spelling ...</span></span>
<span id="cb2-46"><a href="#cb2-46" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-47"><a href="#cb2-47" aria-hidden="true" tabindex="-1"></a><span class="do">### 3.4 Correct the province names</span></span>
<span id="cb2-48"><a href="#cb2-48" aria-hidden="true" tabindex="-1"></a><span class="co">#----------------------------------------------------------</span></span>
<span id="cb2-49"><a href="#cb2-49" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-50"><a href="#cb2-50" aria-hidden="true" tabindex="-1"></a><span class="do">## OPTION 1 : Open the csv file and change the names one by one </span></span>
<span id="cb2-51"><a href="#cb2-51" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-52"><a href="#cb2-52" aria-hidden="true" tabindex="-1"></a><span class="do">## OPTION 2 (advanced R): Change the names using R </span></span>
<span id="cb2-53"><a href="#cb2-53" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-54"><a href="#cb2-54" aria-hidden="true" tabindex="-1"></a><span class="co"># What are the names in the cases files ?</span></span>
<span id="cb2-55"><a href="#cb2-55" aria-hidden="true" tabindex="-1"></a><span class="fu">dput</span>(cases_df<span class="sc">$</span>Province[<span class="sc">!</span>(cases_df<span class="sc">$</span>Province <span class="sc">%in%</span> province_pop_sf<span class="sc">$</span>ADM1_EN)])</span>
<span id="cb2-56"><a href="#cb2-56" aria-hidden="true" tabindex="-1"></a><span class="co"># correct the names</span></span>
<span id="cb2-57"><a href="#cb2-57" aria-hidden="true" tabindex="-1"></a>cases_df<span class="sc">$</span>Province[<span class="sc">!</span>(cases_df<span class="sc">$</span>Province <span class="sc">%in%</span> province_pop_sf<span class="sc">$</span>ADM1_EN)] <span class="ot"><-</span> <span class="fu">c</span>(<span class="st">"Ratanak Kiri"</span>, </span>
<span id="cb2-58"><a href="#cb2-58" aria-hidden="true" tabindex="-1"></a> <span class="st">"Banteay Meanchey"</span>,</span>
<span id="cb2-59"><a href="#cb2-59" aria-hidden="true" tabindex="-1"></a> <span class="st">"Siemreap"</span>, </span>
<span id="cb2-60"><a href="#cb2-60" aria-hidden="true" tabindex="-1"></a> <span class="st">"Mondul Kiri"</span>, </span>
<span id="cb2-61"><a href="#cb2-61" aria-hidden="true" tabindex="-1"></a> <span class="st">"Preah Sihanouk"</span>,</span>
<span id="cb2-62"><a href="#cb2-62" aria-hidden="true" tabindex="-1"></a> <span class="st">"Tboung Khmum"</span>)</span>
<span id="cb2-63"><a href="#cb2-63" aria-hidden="true" tabindex="-1"></a><span class="co"># Be careful of the order of the provinces names !!!</span></span>
<span id="cb2-64"><a href="#cb2-64" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-65"><a href="#cb2-65" aria-hidden="true" tabindex="-1"></a><span class="co"># Merge again</span></span>
<span id="cb2-66"><a href="#cb2-66" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf <span class="ot"><-</span> <span class="fu">merge</span>(province_pop_sf, cases_df, <span class="at">by.x =</span> <span class="st">'ADM1_EN'</span>, <span class="at">by.y =</span> <span class="st">"Province"</span>)</span>
<span id="cb2-67"><a href="#cb2-67" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(province_pop_cases_sf) <span class="co"># Perfect !</span></span>
<span id="cb2-68"><a href="#cb2-68" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(province_pop_cases_sf) <span class="co"># One province is still missing ! </span></span>
<span id="cb2-69"><a href="#cb2-69" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-70"><a href="#cb2-70" aria-hidden="true" tabindex="-1"></a><span class="co"># Which one ? </span></span>
<span id="cb2-71"><a href="#cb2-71" aria-hidden="true" tabindex="-1"></a>province_pop_sf<span class="sc">$</span>ADM1_EN[<span class="sc">!</span>(province_pop_sf<span class="sc">$</span>ADM1_EN <span class="sc">%in%</span> cases_df<span class="sc">$</span>Province)]</span>
<span id="cb2-72"><a href="#cb2-72" aria-hidden="true" tabindex="-1"></a><span class="co"># This province does not exists in our cases data. </span></span>
<span id="cb2-73"><a href="#cb2-73" aria-hidden="true" tabindex="-1"></a><span class="co"># We need to keep it as a NA value in the merged file </span></span>
<span id="cb2-74"><a href="#cb2-74" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-75"><a href="#cb2-75" aria-hidden="true" tabindex="-1"></a><span class="co"># Merge again</span></span>
<span id="cb2-76"><a href="#cb2-76" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf <span class="ot"><-</span> <span class="fu">merge</span>(province_pop_sf, cases_df, </span>
<span id="cb2-77"><a href="#cb2-77" aria-hidden="true" tabindex="-1"></a> <span class="at">by.x =</span> <span class="st">'ADM1_EN'</span>, <span class="at">by.y =</span> <span class="st">"Province"</span>, </span>
<span id="cb2-78"><a href="#cb2-78" aria-hidden="true" tabindex="-1"></a> <span class="at">all.x =</span> <span class="cn">TRUE</span> ) </span>
<span id="cb2-79"><a href="#cb2-79" aria-hidden="true" tabindex="-1"></a><span class="co"># We can use all.x = TRUE to keep all rows from x object event if it is not in the y object</span></span>
<span id="cb2-80"><a href="#cb2-80" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(province_pop_cases_sf) <span class="co"># Perfect !</span></span>
<span id="cb2-81"><a href="#cb2-81" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(province_pop_cases_sf) <span class="co"># YEAH !!!! Wonderful !!!</span></span>
<span id="cb2-82"><a href="#cb2-82" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-83"><a href="#cb2-83" aria-hidden="true" tabindex="-1"></a><span class="co"># what happen to Pailin ? Let extract the row to look at it :</span></span>
<span id="cb2-84"><a href="#cb2-84" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf[province_pop_cases_sf<span class="sc">$</span>ADM1_EN <span class="sc">==</span> <span class="st">"Pailin"</span>,] </span>
<span id="cb2-85"><a href="#cb2-85" aria-hidden="true" tabindex="-1"></a><span class="co"># NA values have been set for the missing data</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
</section>
<section id="map-the-count-data" class="level2">
<h2 class="anchored" data-anchor-id="map-the-count-data">Map the count data</h2>
<section id="steps-2" class="level3">
<h3 class="anchored" data-anchor-id="steps-2">Steps</h3>
<ol type="1">
<li><p>Map the number of cases from 2018 to 2022 (<code>mf_map()</code>) in the same figure (you can split your plotting windows with <code>par(mfrow=c(number_of_line, number_of_columns))</code>) and save it (<code>png()</code>),</p></li>
<li><p>Add NA values on the map with <code>mf_map(type = "symb")</code>.</p></li>
</ol>
</section>
<section id="solution-2" class="level3">
<h3 class="anchored" data-anchor-id="solution-2">Solution</h3>
<div class="cell" data-nm="true">
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co">#=======================================================</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="co"># 4. Map the count data per year</span></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="co">#=======================================================</span></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a><span class="do">### 4.1 Create a maps to represent the number of cases</span></span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a><span class="co">#---------------------------------------------------</span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a><span class="co"># Save the map in img/ directory</span></span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a><span class="fu">png</span>(<span class="at">filename =</span> <span class="st">"img/Count_R_infections.png"</span>, </span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a> <span class="at">width =</span> <span class="dv">700</span>, <span class="at">res =</span> <span class="dv">100</span>) <span class="co"># Run the code until "dev.off()" function</span></span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a><span class="fu">par</span>(<span class="at">mfrow =</span> <span class="fu">c</span>(<span class="dv">2</span>,<span class="dv">2</span>)) <span class="co"># create subplots</span></span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-15"><a href="#cb3-15" aria-hidden="true" tabindex="-1"></a><span class="co"># Count from 2018</span></span>
<span id="cb3-16"><a href="#cb3-16" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf)</span>
<span id="cb3-17"><a href="#cb3-17" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf,</span>
<span id="cb3-18"><a href="#cb3-18" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="st">"X2018"</span> , </span>
<span id="cb3-19"><a href="#cb3-19" aria-hidden="true" tabindex="-1"></a> <span class="at">inches =</span> .<span class="dv">2</span>,</span>
<span id="cb3-20"><a href="#cb3-20" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"prop"</span>,</span>
<span id="cb3-21"><a href="#cb3-21" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"#000066"</span>,</span>
<span id="cb3-22"><a href="#cb3-22" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="st">"Cases"</span>)</span>
<span id="cb3-23"><a href="#cb3-23" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_layout</span>(<span class="at">title =</span> <span class="st">"Number of cases per province (2018)"</span>)</span>
<span id="cb3-24"><a href="#cb3-24" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-25"><a href="#cb3-25" aria-hidden="true" tabindex="-1"></a><span class="co"># Count from 2019</span></span>
<span id="cb3-26"><a href="#cb3-26" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf)</span>
<span id="cb3-27"><a href="#cb3-27" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf,</span>
<span id="cb3-28"><a href="#cb3-28" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="st">"X2019"</span> , </span>
<span id="cb3-29"><a href="#cb3-29" aria-hidden="true" tabindex="-1"></a> <span class="at">inches =</span> .<span class="dv">2</span>,</span>
<span id="cb3-30"><a href="#cb3-30" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"prop"</span>,</span>
<span id="cb3-31"><a href="#cb3-31" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"#000066"</span>,</span>
<span id="cb3-32"><a href="#cb3-32" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="st">"Cases"</span>)</span>
<span id="cb3-33"><a href="#cb3-33" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_layout</span>(<span class="at">title =</span> <span class="st">"Number of cases per province (2019)"</span>)</span>
<span id="cb3-34"><a href="#cb3-34" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-35"><a href="#cb3-35" aria-hidden="true" tabindex="-1"></a><span class="co"># Count from 2020</span></span>
<span id="cb3-36"><a href="#cb3-36" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf)</span>
<span id="cb3-37"><a href="#cb3-37" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf,</span>
<span id="cb3-38"><a href="#cb3-38" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="st">"X2020"</span> , </span>
<span id="cb3-39"><a href="#cb3-39" aria-hidden="true" tabindex="-1"></a> <span class="at">inches =</span> .<span class="dv">2</span>,</span>
<span id="cb3-40"><a href="#cb3-40" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"prop"</span>,</span>
<span id="cb3-41"><a href="#cb3-41" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"#000066"</span>,</span>
<span id="cb3-42"><a href="#cb3-42" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="st">"Cases"</span>)</span>
<span id="cb3-43"><a href="#cb3-43" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_layout</span>(<span class="at">title =</span> <span class="st">"Number of cases per province (2020)"</span>)</span>
<span id="cb3-44"><a href="#cb3-44" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-45"><a href="#cb3-45" aria-hidden="true" tabindex="-1"></a><span class="co"># Count from 2021</span></span>
<span id="cb3-46"><a href="#cb3-46" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf)</span>
<span id="cb3-47"><a href="#cb3-47" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf,</span>
<span id="cb3-48"><a href="#cb3-48" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="st">"X2021"</span> , </span>
<span id="cb3-49"><a href="#cb3-49" aria-hidden="true" tabindex="-1"></a> <span class="at">inches =</span> .<span class="dv">2</span>,</span>
<span id="cb3-50"><a href="#cb3-50" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"prop"</span>,</span>
<span id="cb3-51"><a href="#cb3-51" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"#000066"</span>,</span>
<span id="cb3-52"><a href="#cb3-52" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="st">"Cases"</span>)</span>
<span id="cb3-53"><a href="#cb3-53" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_layout</span>(<span class="at">title =</span> <span class="st">"Number of cases per province (2021)"</span>)</span>
<span id="cb3-54"><a href="#cb3-54" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-55"><a href="#cb3-55" aria-hidden="true" tabindex="-1"></a><span class="fu">dev.off</span>()</span>
<span id="cb3-56"><a href="#cb3-56" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-57"><a href="#cb3-57" aria-hidden="true" tabindex="-1"></a><span class="co"># What about Pailin ? It is treated as a zero instead of NA value and this is a big issue ! </span></span>
<span id="cb3-58"><a href="#cb3-58" aria-hidden="true" tabindex="-1"></a><span class="co"># How can we add it as a NA values ? </span></span>
<span id="cb3-59"><a href="#cb3-59" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-60"><a href="#cb3-60" aria-hidden="true" tabindex="-1"></a><span class="co"># 4.2 Deals with NA values</span></span>
<span id="cb3-61"><a href="#cb3-61" aria-hidden="true" tabindex="-1"></a><span class="co">#-----------------------------------------------</span></span>
<span id="cb3-62"><a href="#cb3-62" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-63"><a href="#cb3-63" aria-hidden="true" tabindex="-1"></a><span class="co"># There is no easy solution design for it yet ... </span></span>
<span id="cb3-64"><a href="#cb3-64" aria-hidden="true" tabindex="-1"></a><span class="co"># What do you think ? We can try to do it by hand. Here is just a suggestions : </span></span>
<span id="cb3-65"><a href="#cb3-65" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-66"><a href="#cb3-66" aria-hidden="true" tabindex="-1"></a><span class="co"># Baseline map</span></span>
<span id="cb3-67"><a href="#cb3-67" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf)</span>
<span id="cb3-68"><a href="#cb3-68" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-69"><a href="#cb3-69" aria-hidden="true" tabindex="-1"></a><span class="co"># Add symbol for Pailin</span></span>
<span id="cb3-70"><a href="#cb3-70" aria-hidden="true" tabindex="-1"></a>pailin_sf <span class="ot"><-</span> province_pop_cases_sf[province_pop_cases_sf<span class="sc">$</span>ADM1_EN <span class="sc">==</span> <span class="st">"Pailin"</span>,] <span class="co"># select row</span></span>
<span id="cb3-71"><a href="#cb3-71" aria-hidden="true" tabindex="-1"></a>pailin_sf<span class="sc">$</span>data_avail <span class="ot"><-</span> <span class="st">"No data"</span> <span class="co"># Define no data value for pailin</span></span>
<span id="cb3-72"><a href="#cb3-72" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(pailin_sf ,</span>
<span id="cb3-73"><a href="#cb3-73" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="st">"data_avail"</span>,</span>
<span id="cb3-74"><a href="#cb3-74" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="cn">NULL</span>, </span>
<span id="cb3-75"><a href="#cb3-75" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"black"</span>,</span>
<span id="cb3-76"><a href="#cb3-76" aria-hidden="true" tabindex="-1"></a> <span class="at">cex =</span> <span class="fl">1.5</span>,</span>
<span id="cb3-77"><a href="#cb3-77" aria-hidden="true" tabindex="-1"></a> <span class="at">pch =</span> <span class="dv">22</span>,</span>
<span id="cb3-78"><a href="#cb3-78" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"symb"</span>)</span>
<span id="cb3-79"><a href="#cb3-79" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-80"><a href="#cb3-80" aria-hidden="true" tabindex="-1"></a><span class="co"># Count from 2021</span></span>
<span id="cb3-81"><a href="#cb3-81" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_map</span>(province_pop_cases_sf,</span>
<span id="cb3-82"><a href="#cb3-82" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="st">"X2021"</span> , </span>
<span id="cb3-83"><a href="#cb3-83" aria-hidden="true" tabindex="-1"></a> <span class="at">inches =</span> .<span class="dv">2</span>,</span>
<span id="cb3-84"><a href="#cb3-84" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"prop"</span>,</span>
<span id="cb3-85"><a href="#cb3-85" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"#000066"</span>,</span>
<span id="cb3-86"><a href="#cb3-86" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="st">"Cases"</span>)</span>
<span id="cb3-87"><a href="#cb3-87" aria-hidden="true" tabindex="-1"></a><span class="fu">mf_layout</span>(<span class="at">title =</span> <span class="st">"Number of cases per province (2021)"</span>)</span>
<span id="cb3-88"><a href="#cb3-88" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-89"><a href="#cb3-89" aria-hidden="true" tabindex="-1"></a><span class="co"># How can I improve this map ? change colors ? fix the scale for all subplot ?</span></span>
<span id="cb3-90"><a href="#cb3-90" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-91"><a href="#cb3-91" aria-hidden="true" tabindex="-1"></a><span class="co"># These count are not really informative since it depends on the population.</span></span>
<span id="cb3-92"><a href="#cb3-92" aria-hidden="true" tabindex="-1"></a><span class="co"># We can compute incidence instead of cases in a new column</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
</section>
<section id="transform-data-to-incidence" class="level2">
<h2 class="anchored" data-anchor-id="transform-data-to-incidence">Transform data to incidence</h2>
<section id="steps-3" class="level3">
<h3 class="anchored" data-anchor-id="steps-3">Steps</h3>
<ol type="1">
<li><p>Compute incidence for each column (number of cases/ population * 100,000)</p></li>
<li><p>Compute incidence using <code>apply()</code> and by creating a <code>function(){}</code>,</p></li>
<li><p>Merge incidences with shapefile,</p></li>
<li><p>Map incidence for each year in the same figure (<code>par(mfrow)</code>) using a loop <code>for(variable in vector){}</code>, you can call help with <code>?for (variable in vector) {}</code></p></li>
</ol>
</section>
<section id="solution-3" class="level3">
<h3 class="anchored" data-anchor-id="solution-3">Solution</h3>
<div class="cell" data-nm="true">
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co">#=======================================================</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="do">### 5. Transform to incidence</span></span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a><span class="co">#=======================================================</span></span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a><span class="do">### 5.1 Compute incidence</span></span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a><span class="co">#---------------------------------------------------------</span></span>
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a><span class="co"># OPTION 1 : compute columns by columns</span></span>
<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf<span class="sc">$</span>incidence_2017 <span class="ot"><-</span> province_pop_cases_sf<span class="sc">$</span>X2017<span class="sc">/</span>province_pop_cases_sf<span class="sc">$</span>pop <span class="sc">*</span> <span class="dv">100000</span></span>
<span id="cb4-10"><a href="#cb4-10" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf<span class="sc">$</span>incidence_2018 <span class="ot"><-</span> province_pop_cases_sf<span class="sc">$</span>X2018<span class="sc">/</span>province_pop_cases_sf<span class="sc">$</span>pop <span class="sc">*</span> <span class="dv">100000</span></span>
<span id="cb4-11"><a href="#cb4-11" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf<span class="sc">$</span>incidence_2019 <span class="ot"><-</span> province_pop_cases_sf<span class="sc">$</span>X2019<span class="sc">/</span>province_pop_cases_sf<span class="sc">$</span>pop <span class="sc">*</span> <span class="dv">100000</span></span>
<span id="cb4-12"><a href="#cb4-12" aria-hidden="true" tabindex="-1"></a>province_pop_cases_sf<span class="sc">$</span>incidence_2018 <span class="ot"><-</span> province_pop_cases_sf<span class="sc">$</span>X2020<span class="sc">/</span>province_pop_cases_sf<span class="sc">$</span>pop <span class="sc">*</span> <span class="dv">100000</span></span>
<span id="cb4-13"><a href="#cb4-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-14"><a href="#cb4-14" aria-hidden="true" tabindex="-1"></a><span class="co"># OPTION 2 : use "apply" function (?apply)</span></span>
<span id="cb4-15"><a href="#cb4-15" aria-hidden="true" tabindex="-1"></a><span class="co"># remove geometry to work on dataframe</span></span>
<span id="cb4-16"><a href="#cb4-16" aria-hidden="true" tabindex="-1"></a>attribute_df <span class="ot"><-</span> <span class="fu">st_drop_geometry</span>(province_pop_cases_sf)</span>
<span id="cb4-17"><a href="#cb4-17" aria-hidden="true" tabindex="-1"></a><span class="co"># set rownames</span></span>
<span id="cb4-18"><a href="#cb4-18" aria-hidden="true" tabindex="-1"></a><span class="fu">row.names</span>(attribute_df) <span class="ot"><-</span> attribute_df<span class="sc">$</span>ADM1_PCODE <span class="co"># easier to use the ID</span></span>
<span id="cb4-19"><a href="#cb4-19" aria-hidden="true" tabindex="-1"></a><span class="co"># remove useless column</span></span>
<span id="cb4-20"><a href="#cb4-20" aria-hidden="true" tabindex="-1"></a><span class="fu">colnames</span>(attribute_df) <span class="co"># show the column names of our dataframe</span></span>
<span id="cb4-21"><a href="#cb4-21" aria-hidden="true" tabindex="-1"></a>attribute_cases_df <span class="ot"><-</span> attribute_df[, <span class="dv">15</span><span class="sc">:</span><span class="dv">20</span>] <span class="co"># select columns 15 to 20 (contains cases values)</span></span>
<span id="cb4-22"><a href="#cb4-22" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-23"><a href="#cb4-23" aria-hidden="true" tabindex="-1"></a><span class="co"># Create your own function to compute incidence</span></span>
<span id="cb4-24"><a href="#cb4-24" aria-hidden="true" tabindex="-1"></a>compute_incidence <span class="ot"><-</span> <span class="cf">function</span>(cases, population){ </span>
<span id="cb4-25"><a href="#cb4-25" aria-hidden="true" tabindex="-1"></a> <span class="co"># cases and population are parameters of the function</span></span>
<span id="cb4-26"><a href="#cb4-26" aria-hidden="true" tabindex="-1"></a> <span class="co"># case is a numerical values of a number of cases (can be a single value or a vector)</span></span>
<span id="cb4-27"><a href="#cb4-27" aria-hidden="true" tabindex="-1"></a> <span class="co"># population is a numerical values of population count (can be a single value or a vector)</span></span>
<span id="cb4-28"><a href="#cb4-28" aria-hidden="true" tabindex="-1"></a> <span class="co"># Both parameters must have the same length</span></span>
<span id="cb4-29"><a href="#cb4-29" aria-hidden="true" tabindex="-1"></a> incidence <span class="ot"><-</span> cases<span class="sc">/</span>population <span class="sc">*</span> <span class="dv">100000</span></span>
<span id="cb4-30"><a href="#cb4-30" aria-hidden="true" tabindex="-1"></a> <span class="fu">return</span>(incidence)</span>
<span id="cb4-31"><a href="#cb4-31" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb4-32"><a href="#cb4-32" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-33"><a href="#cb4-33" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(compute_incidence)</span>
<span id="cb4-34"><a href="#cb4-34" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(compute_incidence)</span>
<span id="cb4-35"><a href="#cb4-35" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-36"><a href="#cb4-36" aria-hidden="true" tabindex="-1"></a><span class="co">#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++</span></span>
<span id="cb4-37"><a href="#cb4-37" aria-hidden="true" tabindex="-1"></a><span class="co"># example:</span></span>
<span id="cb4-38"><a href="#cb4-38" aria-hidden="true" tabindex="-1"></a>incidence_by_hand <span class="ot"><-</span> province_pop_cases_sf<span class="sc">$</span>X2017<span class="sc">/</span>province_pop_cases_sf<span class="sc">$</span>pop <span class="sc">*</span> <span class="dv">100000</span></span>
<span id="cb4-39"><a href="#cb4-39" aria-hidden="true" tabindex="-1"></a>incidence_with_function <span class="ot"><-</span> <span class="fu">compute_incidence</span>(<span class="at">cases =</span> province_pop_cases_sf<span class="sc">$</span>X2017, <span class="at">population =</span> province_pop_cases_sf<span class="sc">$</span>pop)</span>
<span id="cb4-40"><a href="#cb4-40" aria-hidden="true" tabindex="-1"></a>incidence_by_hand <span class="sc">==</span> incidence_with_function <span class="co"># It gives the same results </span></span>
<span id="cb4-41"><a href="#cb4-41" aria-hidden="true" tabindex="-1"></a><span class="co">#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++</span></span>
<span id="cb4-42"><a href="#cb4-42" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-43"><a href="#cb4-43" aria-hidden="true" tabindex="-1"></a><span class="co"># Apply the same function to each column of the dataframe</span></span>
<span id="cb4-44"><a href="#cb4-44" aria-hidden="true" tabindex="-1"></a>attribute_inc_mat <span class="ot"><-</span> <span class="fu">apply</span>(attribute_cases_df, <span class="dv">2</span>, compute_incidence, <span class="at">population =</span> attribute_df<span class="sc">$</span>pop)</span>
<span id="cb4-45"><a href="#cb4-45" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(attribute_inc_mat) <span class="co"># apply return a matrix (table of numerical values only)</span></span>
<span id="cb4-46"><a href="#cb4-46" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-47"><a href="#cb4-47" aria-hidden="true" tabindex="-1"></a><span class="co"># turn it to dataframe to add a column of character</span></span>
<span id="cb4-48"><a href="#cb4-48" aria-hidden="true" tabindex="-1"></a>attribute_inc_df <span class="ot"><-</span> <span class="fu">as.data.frame</span>(attribute_inc_mat)</span>
<span id="cb4-49"><a href="#cb4-49" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(attribute_inc_df)</span>
<span id="cb4-50"><a href="#cb4-50" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-51"><a href="#cb4-51" aria-hidden="true" tabindex="-1"></a><span class="co"># Change the columns names to inform on data</span></span>
<span id="cb4-52"><a href="#cb4-52" aria-hidden="true" tabindex="-1"></a><span class="fu">colnames</span>(attribute_inc_df) <span class="ot"><-</span> <span class="fu">paste0</span>(<span class="st">'incidence_'</span>, <span class="fu">colnames</span>(attribute_inc_df))</span>
<span id="cb4-53"><a href="#cb4-53" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-54"><a href="#cb4-54" aria-hidden="true" tabindex="-1"></a><span class="co"># Retrieve ID code from row names</span></span>
<span id="cb4-55"><a href="#cb4-55" aria-hidden="true" tabindex="-1"></a>attribute_inc_df<span class="sc">$</span>ADM1_PCODE <span class="ot"><-</span> <span class="fu">row.names</span>(attribute_inc_df)</span>
<span id="cb4-56"><a href="#cb4-56" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-57"><a href="#cb4-57" aria-hidden="true" tabindex="-1"></a><span class="co"># Have look at the final object</span></span>
<span id="cb4-58"><a href="#cb4-58" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(attribute_inc_df)</span>
<span id="cb4-59"><a href="#cb4-59" aria-hidden="true" tabindex="-1"></a><span class="fu">summary</span>(attribute_inc_df)</span>
<span id="cb4-60"><a href="#cb4-60" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(attribute_inc_df)</span>
<span id="cb4-61"><a href="#cb4-61" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-62"><a href="#cb4-62" aria-hidden="true" tabindex="-1"></a><span class="co"># Might look longer to use this option but reminds that when you have larger dataframe </span></span>
<span id="cb4-63"><a href="#cb4-63" aria-hidden="true" tabindex="-1"></a><span class="co"># in hand this option is way more convenient than dealing with each line with the </span></span>
<span id="cb4-64"><a href="#cb4-64" aria-hidden="true" tabindex="-1"></a><span class="co"># risque of producing mistakes</span></span>
<span id="cb4-65"><a href="#cb4-65" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-66"><a href="#cb4-66" aria-hidden="true" tabindex="-1"></a><span class="do">### 5.2 Merge with the spatial object</span></span>
<span id="cb4-67"><a href="#cb4-67" aria-hidden="true" tabindex="-1"></a><span class="co">#---------------------------------------------------------</span></span>
<span id="cb4-68"><a href="#cb4-68" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-69"><a href="#cb4-69" aria-hidden="true" tabindex="-1"></a>province_pop_inc_sf <span class="ot"><-</span> <span class="fu">merge</span>(<span class="at">x =</span> province_pop_sf, <span class="at">y =</span> attribute_inc_df, <span class="at">by =</span> <span class="st">"ADM1_PCODE"</span>)</span>
<span id="cb4-70"><a href="#cb4-70" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-71"><a href="#cb4-71" aria-hidden="true" tabindex="-1"></a><span class="fu">class</span>(province_pop_inc_sf)</span>
<span id="cb4-72"><a href="#cb4-72" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(province_pop_inc_sf)</span>
<span id="cb4-73"><a href="#cb4-73" aria-hidden="true" tabindex="-1"></a><span class="fu">summary</span>(province_pop_inc_sf)</span>
<span id="cb4-74"><a href="#cb4-74" aria-hidden="true" tabindex="-1"></a><span class="fu">dim</span>(province_pop_inc_sf)</span>
<span id="cb4-75"><a href="#cb4-75" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-76"><a href="#cb4-76" aria-hidden="true" tabindex="-1"></a><span class="do">### 5.3 Map incidence</span></span>
<span id="cb4-77"><a href="#cb4-77" aria-hidden="true" tabindex="-1"></a><span class="co">#---------------------------------------------------------</span></span>
<span id="cb4-78"><a href="#cb4-78" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-79"><a href="#cb4-79" aria-hidden="true" tabindex="-1"></a><span class="co"># OPTION 1: Just like we did earlier with the number of cases, plot by plot</span></span>
<span id="cb4-80"><a href="#cb4-80" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-81"><a href="#cb4-81" aria-hidden="true" tabindex="-1"></a><span class="co"># OPTION 2: Use a loop !</span></span>
<span id="cb4-82"><a href="#cb4-82" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-83"><a href="#cb4-83" aria-hidden="true" tabindex="-1"></a><span class="co"># A loop repeat a part of your code for many values</span></span>
<span id="cb4-84"><a href="#cb4-84" aria-hidden="true" tabindex="-1"></a><span class="co">#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++</span></span>
<span id="cb4-85"><a href="#cb4-85" aria-hidden="true" tabindex="-1"></a><span class="co"># Simple examples:</span></span>
<span id="cb4-86"><a href="#cb4-86" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span>(i <span class="cf">in</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">10</span>){</span>
<span id="cb4-87"><a href="#cb4-87" aria-hidden="true" tabindex="-1"></a> <span class="co"># i is a variable that will successively takes the values contains in the vector given after 'in' </span></span>
<span id="cb4-88"><a href="#cb4-88" aria-hidden="true" tabindex="-1"></a> <span class="fu">print</span>(i)</span>
<span id="cb4-89"><a href="#cb4-89" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb4-90"><a href="#cb4-90" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-91"><a href="#cb4-91" aria-hidden="true" tabindex="-1"></a>j <span class="ot"><-</span> <span class="st">"Fixed value ouside the loop"</span></span>
<span id="cb4-92"><a href="#cb4-92" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span>(i <span class="cf">in</span> <span class="fu">c</span>(<span class="st">"a"</span>, <span class="st">"b"</span>, <span class="st">"d"</span>, <span class="st">"end"</span>)){</span>
<span id="cb4-93"><a href="#cb4-93" aria-hidden="true" tabindex="-1"></a> <span class="fu">print</span>(i)</span>
<span id="cb4-94"><a href="#cb4-94" aria-hidden="true" tabindex="-1"></a> <span class="fu">print</span>(j)</span>
<span id="cb4-95"><a href="#cb4-95" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb4-96"><a href="#cb4-96" aria-hidden="true" tabindex="-1"></a><span class="co">#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++</span></span>
<span id="cb4-97"><a href="#cb4-97" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-98"><a href="#cb4-98" aria-hidden="true" tabindex="-1"></a><span class="fu">png</span>(<span class="at">filename =</span> <span class="st">"img/Incidence_R_infections.png"</span>, </span>
<span id="cb4-99"><a href="#cb4-99" aria-hidden="true" tabindex="-1"></a> <span class="at">width =</span> <span class="dv">700</span>, <span class="at">res =</span> <span class="dv">100</span>) <span class="co"># Run the code until "dev.off()" function</span></span>
<span id="cb4-100"><a href="#cb4-100" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-101"><a href="#cb4-101" aria-hidden="true" tabindex="-1"></a><span class="fu">par</span>(<span class="at">mfrow =</span> <span class="fu">c</span>(<span class="dv">2</span>,<span class="dv">2</span>)) <span class="co"># create subplots</span></span>
<span id="cb4-102"><a href="#cb4-102" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span>(year <span class="cf">in</span> <span class="fu">c</span>(<span class="st">"2018"</span>, <span class="st">"2019"</span>, <span class="st">"2020"</span>, <span class="st">"2021"</span>)) {</span>
<span id="cb4-103"><a href="#cb4-103" aria-hidden="true" tabindex="-1"></a> <span class="fu">print</span>(<span class="fu">paste0</span>(<span class="st">"Plot incidence for the year "</span>, year))</span>
<span id="cb4-104"><a href="#cb4-104" aria-hidden="true" tabindex="-1"></a> </span>
<span id="cb4-105"><a href="#cb4-105" aria-hidden="true" tabindex="-1"></a> name_col <span class="ot"><-</span> <span class="fu">paste0</span>(<span class="st">"incidence_X"</span>, year) <span class="co"># Define names of the plotted column</span></span>
<span id="cb4-106"><a href="#cb4-106" aria-hidden="true" tabindex="-1"></a> <span class="fu">mf_map</span>(province_pop_inc_sf)</span>
<span id="cb4-107"><a href="#cb4-107" aria-hidden="true" tabindex="-1"></a> <span class="fu">mf_map</span>(province_pop_inc_sf,</span>
<span id="cb4-108"><a href="#cb4-108" aria-hidden="true" tabindex="-1"></a> <span class="at">var =</span> <span class="fu">c</span>( <span class="st">"pop"</span>, name_col) , </span>
<span id="cb4-109"><a href="#cb4-109" aria-hidden="true" tabindex="-1"></a> <span class="at">inches =</span> .<span class="dv">2</span>,</span>
<span id="cb4-110"><a href="#cb4-110" aria-hidden="true" tabindex="-1"></a> <span class="at">type =</span> <span class="st">"prop_choro"</span>,</span>
<span id="cb4-111"><a href="#cb4-111" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> <span class="st">"#000066"</span>,</span>
<span id="cb4-112"><a href="#cb4-112" aria-hidden="true" tabindex="-1"></a> <span class="at">leg_title =</span> <span class="st">"Incidence"</span>)</span>
<span id="cb4-113"><a href="#cb4-113" aria-hidden="true" tabindex="-1"></a> <span class="fu">mf_layout</span>(<span class="at">title =</span> <span class="fu">paste0</span>(<span class="st">" Incidence of R infections per province ("</span>, year, <span class="st">")"</span>))</span>
<span id="cb4-114"><a href="#cb4-114" aria-hidden="true" tabindex="-1"></a> </span>
<span id="cb4-115"><a href="#cb4-115" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb4-116"><a href="#cb4-116" aria-hidden="true" tabindex="-1"></a><span class="fu">dev.off</span>() <span class="co"># Don't forget to close the plotting window</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
</section>
<section id="go-further-in-analysis-advanced-r" class="level2">
<h2 class="anchored" data-anchor-id="go-further-in-analysis-advanced-r">Go further in analysis (Advanced R) …</h2>
<p>The section gives suggestions to go further into the data description.</p>
<section id="work-with-averaged-incidence" class="level3">
<h3 class="anchored" data-anchor-id="work-with-averaged-incidence">Work with averaged incidence</h3>
<p>We are now interested in the averaged incidence between 2017 and 2022. In other terms, we want to compute the mean values of incidence for each row.</p>
</section>
<section id="let-look-at-hospital-distribution" class="level3">
<h3 class="anchored" data-anchor-id="let-look-at-hospital-distribution">Let look at hospital distribution</h3>
<p>Do I have higher incidence if there is more hospital in the province ? In other term, is there a bias in case detected cause by the access to health care ?</p>
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