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Rmarkdown_ex2.html
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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<meta name="generator" content="pandoc" />
<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
<title>Code chunks in R markdown</title>
<script src="site_libs/header-attrs-2.29/header-attrs.js"></script>
<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
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margin-bottom: 20px;
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<h1 class="title toc-ignore">Code chunks in R markdown</h1>
</div>
<p> </p>
<p>During this exercise you will practice adding code chunks and inline
R code to the R markdown document you created during the <a
href="Rmarkdown_ex1.html">previous exercise</a>. The solutions to each
section of the exercise can be revealed by clicking on the
<code>Solution</code> button (don’t be too quick to do this though!).
Once you have finished you can find my version of the <code>.Rmd</code>
file <a href="squid_analysis.Rmd">here</a> and the rendered html
document <a href="squid_analysis.html">here</a>. A pdf version of the
document is <a href="squid_analysis.pdf">here</a> </p>
<p>So, the first thing you will need to do is open your
<code>squid_analysis.Rmd</code> file in RStudio. You will already have a
nicely marked up description of the data and the morphological variables
measured during the study so we will continue with data import,
exploration and some simple visualisations. You will need to download
the <code>squid1.xlsx</code> file from <strong><a
href="data.html"><i class="fa fa-download"></i> Data</a></strong> link,
open it in excel and save it as a tab delimited file called
<code>squid1.txt</code> (as we did during the R course). </p>
<p>Create a code chunk named <code>data-import</code> and include some R
code to import the <code>squid1.txt</code> file into R using the
<code>read.table()</code> function and assign it to a variable called
<code>squid</code>. Within the code chunk get R to print out the
structure of the <code>squid</code> variable. Add some text below the
code chunk to explain (to your future self) what you are doing. Also
write some text with inline R code to state how many observations are
present (hint: use the <code>nrow()</code> function) in the dataset and
how many variables were measured (hint: use the <code>ncol()</code>
function).</p>
<p> </p>
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<div class="sourceCode" id="cb1"><pre
class="sourceCode markdown"><code class="sourceCode markdown"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="in">```{r, data-import}</span></span>
<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a><span class="in">squid <- read.table('./data/squid1.txt', header = TRUE)</span></span>
<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a><span class="in">str(squid)</span></span>
<span id="cb1-4"><a href="#cb1-4" tabindex="-1"></a><span class="in">```</span></span>
<span id="cb1-5"><a href="#cb1-5" tabindex="-1"></a> </span>
<span id="cb1-6"><a href="#cb1-6" tabindex="-1"></a>In this dataset <span class="in">`r nrow(squid)`</span> squid were caught and <span class="in">`r ncol(squid)`</span> variables were measured </span>
<span id="cb1-7"><a href="#cb1-7" tabindex="-1"></a>for each squid. Details are shown above.</span></code></pre></div>
</div>
<p> </p>
<p>Perhaps you might remember from <a
href="exercise_4_solution.html">Exercise 4</a> that the
<code>year</code>, <code>month</code> and <code>maturity.stage</code>
variables were coded as integers in the original dataset (see the output
from <code>str(squid)</code> above to confirm) but we want to recode
them as factors. Create a new code chunk called <code>data-recode</code>
and include R code to create a new variable for each of these variables
in the <code>squid</code> dataframe and recode them as factors. Change
the chunk option to hide this code in the rendered document. Write some
text to describe that you have recoded the variables to let the reader
know you’ve done this (even though you don’t show the code in the final
document).</p>
<p> </p>
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<div class="sourceCode" id="cb2"><pre
class="sourceCode markdown"><code class="sourceCode markdown"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a><span class="in">```{r, data-recode, echo=FALSE}</span></span>
<span id="cb2-2"><a href="#cb2-2" tabindex="-1"></a><span class="in"># convert variables to factors</span></span>
<span id="cb2-3"><a href="#cb2-3" tabindex="-1"></a><span class="in">squid$Fmaturity <- factor(squid$maturity.stage)</span></span>
<span id="cb2-4"><a href="#cb2-4" tabindex="-1"></a><span class="in">squid$Fmonth <- factor(squid$month) </span></span>
<span id="cb2-5"><a href="#cb2-5" tabindex="-1"></a><span class="in">squid$Fyear <- factor(squid$year)</span></span>
<span id="cb2-6"><a href="#cb2-6" tabindex="-1"></a><span class="in">```</span></span>
<span id="cb2-7"><a href="#cb2-7" tabindex="-1"></a></span>
<span id="cb2-8"><a href="#cb2-8" tabindex="-1"></a>The variables <span class="in">`maturity.stage`</span>, <span class="in">`month`</span> and <span class="in">`year`</span> were converted from integers to factors in the dataframe </span>
<span id="cb2-9"><a href="#cb2-9" tabindex="-1"></a><span class="in">`squid`</span>. These recoded variables were named <span class="in">`Fmaturity`</span>, <span class="in">`Fmonth`</span> and <span class="in">`Fyear`</span>.</span></code></pre></div>
</div>
<p> </p>
<p>Next create a code chunk (give it a suitable name) and write some
code to create a table of the number of observations for each year and
month combination (hint: remember the <code>table()</code> function?)
Don’t forget to use the factor recoded versions of these variables. Use
the <code>kable()</code> function from the <code>knitr</code> package to
nicely render the table (remember you will need to use
<code>library(knitr)</code> to load the package first). You might want
to also include the argument <code>row.names = TRUE</code> when you use
the <code>kable()</code> function so the table contains the month
numbers. Another argument that is often useful to include is
<code>format = 'markdown</code> which will ensure the table renders
nicely in HTML and pdf formats. Write some text to highlight which year
has the fewest number of observations and which year and month
combinations have no observations.</p>
<p> </p>
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<div class="sourceCode" id="cb3"><pre
class="sourceCode markdown"><code class="sourceCode markdown"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a>Next, let's take a look at the number of observations across years and months.</span>
<span id="cb3-2"><a href="#cb3-2" tabindex="-1"></a></span>
<span id="cb3-3"><a href="#cb3-3" tabindex="-1"></a><span class="in">```{r, data-obs}</span></span>
<span id="cb3-4"><a href="#cb3-4" tabindex="-1"></a><span class="in">library(knitr)</span></span>
<span id="cb3-5"><a href="#cb3-5" tabindex="-1"></a><span class="in">kable(table(squid$Fmonth, squid$Fyear), row.names = TRUE, format = 'markdown')</span></span>
<span id="cb3-6"><a href="#cb3-6" tabindex="-1"></a><span class="in">```</span></span>
<span id="cb3-7"><a href="#cb3-7" tabindex="-1"></a></span>
<span id="cb3-8"><a href="#cb3-8" tabindex="-1"></a>Or,If you want a fancy table with the variable names (month and year) then use the pander function from the </span>
<span id="cb3-9"><a href="#cb3-9" tabindex="-1"></a>pander package. You will also have to provide the dimnames to the table and use the ftable function to </span>
<span id="cb3-10"><a href="#cb3-10" tabindex="-1"></a>'flatten' the table. </span>
<span id="cb3-11"><a href="#cb3-11" tabindex="-1"></a></span>
<span id="cb3-12"><a href="#cb3-12" tabindex="-1"></a><span class="in">```{r, data-obs2}</span></span>
<span id="cb3-13"><a href="#cb3-13" tabindex="-1"></a><span class="in">library(pander)</span></span>
<span id="cb3-14"><a href="#cb3-14" tabindex="-1"></a><span class="in">mytab <- table(squid$Fmonth, squid$Fyear)</span></span>
<span id="cb3-15"><a href="#cb3-15" tabindex="-1"></a><span class="in">names(dimnames(mytab)) <- c("Month", "Year")</span></span>
<span id="cb3-16"><a href="#cb3-16" tabindex="-1"></a><span class="in">pander(ftable(mytab))</span></span>
<span id="cb3-17"><a href="#cb3-17" tabindex="-1"></a><span class="in">```</span></span>
<span id="cb3-18"><a href="#cb3-18" tabindex="-1"></a></span>
<span id="cb3-19"><a href="#cb3-19" tabindex="-1"></a>In 1989 data were only collected during December and in 1991 data collection stopped in August. </span>
<span id="cb3-20"><a href="#cb3-20" tabindex="-1"></a>During 1990, no data were collected in either February or June. There are also some months that </span>
<span id="cb3-21"><a href="#cb3-21" tabindex="-1"></a>have very few observations (May 1990 and July 1991 for example) so care must be taken when </span>
<span id="cb3-22"><a href="#cb3-22" tabindex="-1"></a>modelling these data. </span></code></pre></div>
</div>
<p> </p>
<p>We should also create a summary table of the number of observations
for each level of maturity stage for each month. Create a code chunk and
include code to do this but hide the code in the rendered document using
the appropriate chunk option. If you feel like it, experiment with the
<code>kableExtra</code> package to alter some of the formatting (text
size etc). You may need to install the package before you can use it.
Again, write some text to summarise your findings.</p>
<p> </p>
<div class="toggle">
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<div class="sourceCode" id="cb4"><pre
class="sourceCode markdown"><code class="sourceCode markdown"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a></span>
<span id="cb4-2"><a href="#cb4-2" tabindex="-1"></a>Number of observations each month for each of the squid maturity stages are given in the table below.</span>
<span id="cb4-3"><a href="#cb4-3" tabindex="-1"></a></span>
<span id="cb4-4"><a href="#cb4-4" tabindex="-1"></a><span class="in">```{r, maturity-obs, echo=FALSE}</span></span>
<span id="cb4-5"><a href="#cb4-5" tabindex="-1"></a></span>
<span id="cb4-6"><a href="#cb4-6" tabindex="-1"></a><span class="in"># using just kable</span></span>
<span id="cb4-7"><a href="#cb4-7" tabindex="-1"></a></span>
<span id="cb4-8"><a href="#cb4-8" tabindex="-1"></a><span class="in">kable(table(squid$Fmaturity, squid$Fmonth), row.names = TRUE)</span></span>
<span id="cb4-9"><a href="#cb4-9" tabindex="-1"></a></span>
<span id="cb4-10"><a href="#cb4-10" tabindex="-1"></a><span class="in"># using kableExtra (good for html output)</span></span>
<span id="cb4-11"><a href="#cb4-11" tabindex="-1"></a></span>
<span id="cb4-12"><a href="#cb4-12" tabindex="-1"></a><span class="in">library(kableExtra)</span></span>
<span id="cb4-13"><a href="#cb4-13" tabindex="-1"></a><span class="in">kable(table(squid$Fmaturity, squid$Fmonth), row.names = TRUE) %>%</span></span>
<span id="cb4-14"><a href="#cb4-14" tabindex="-1"></a><span class="in"> kable_styling(bootstrap_options = "striped", font_size = 14)</span></span>
<span id="cb4-15"><a href="#cb4-15" tabindex="-1"></a><span class="in">```</span></span>
<span id="cb4-16"><a href="#cb4-16" tabindex="-1"></a></span>
<span id="cb4-17"><a href="#cb4-17" tabindex="-1"></a>Not all maturity stages were observed in all months. Very few squid of maturity stage 1, 2 or 3</span>
<span id="cb4-18"><a href="#cb4-18" tabindex="-1"></a>were caught in the months February to May whereas maturity stages 4 and 5 were </span>
<span id="cb4-19"><a href="#cb4-19" tabindex="-1"></a>predominantly caught during these months.</span></code></pre></div>
</div>
<p> </p>
<p>Ok, lets produce some exploratory plots in our document. The first
thing we would like to know is whether there are any unusual
observations in the variables; <code>DML</code>, <code>weight</code>,
<code>nid.length</code> and <code>ovary.weight</code>. Create a code
chunk containing code to plot cleveland dotplots of these variables. You
can either plot one after the other or split the plotting device into 2
rows and 2 columns to plot them all together. This time we would like to
show the code used to create these plots. Describe what you see and come
up with a plausable explanation (refer back to Exercise 4 Question 7 for
a hint.)</p>
<p> </p>
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Solution
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<div class="sourceCode" id="cb5"><pre
class="sourceCode markdown"><code class="sourceCode markdown"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a></span>
<span id="cb5-2"><a href="#cb5-2" tabindex="-1"></a>Now let's check for any unusual observations in the variables; <span class="in">`DML`</span>, <span class="in">`weight`</span>, </span>
<span id="cb5-3"><a href="#cb5-3" tabindex="-1"></a><span class="in">`nid.length`</span> and <span class="in">`ovary.weight`</span>. </span>
<span id="cb5-4"><a href="#cb5-4" tabindex="-1"></a></span>
<span id="cb5-5"><a href="#cb5-5" tabindex="-1"></a></span>
<span id="cb5-6"><a href="#cb5-6" tabindex="-1"></a><span class="in">```{r, dotplot}</span></span>
<span id="cb5-7"><a href="#cb5-7" tabindex="-1"></a><span class="in">par(mfrow = c(2, 2))</span></span>
<span id="cb5-8"><a href="#cb5-8" tabindex="-1"></a><span class="in"> dotchart(squid$DML, main = "DML")</span></span>
<span id="cb5-9"><a href="#cb5-9" tabindex="-1"></a><span class="in"> dotchart(squid$weight, main = "weight")</span></span>
<span id="cb5-10"><a href="#cb5-10" tabindex="-1"></a><span class="in"> dotchart(squid$nid.length, main = "nid length")</span></span>
<span id="cb5-11"><a href="#cb5-11" tabindex="-1"></a><span class="in"> dotchart(squid$ovary.weight, main = "ovary weight")</span></span>
<span id="cb5-12"><a href="#cb5-12" tabindex="-1"></a><span class="in">```</span></span>
<span id="cb5-13"><a href="#cb5-13" tabindex="-1"></a></span>
<span id="cb5-14"><a href="#cb5-14" tabindex="-1"></a>It looks like the variable <span class="in">`nid.length`</span> contains an **unusually large** value. Actually, this value </span>
<span id="cb5-15"><a href="#cb5-15" tabindex="-1"></a>is biologically implausible and clearly an error. I went back and checked my field notebook and </span>
<span id="cb5-16"><a href="#cb5-16" tabindex="-1"></a>sure enough it's a typo. I was knackered at the time and accidentally inserted a zero by mistake </span>
<span id="cb5-17"><a href="#cb5-17" tabindex="-1"></a>when transcribing these data. **Doh!** This squid was identified as observation number </span>
<span id="cb5-18"><a href="#cb5-18" tabindex="-1"></a><span class="in">`r which(squid$nid.length > 400)`</span> with a sample number </span>
<span id="cb5-19"><a href="#cb5-19" tabindex="-1"></a><span class="in">`r squid$sample.no[which(squid$nid.length > 400)]`</span>. This observation was </span>
<span id="cb5-20"><a href="#cb5-20" tabindex="-1"></a>subsequently removed from the data set. </span></code></pre></div>
</div>
<p> </p>
<p>Next, produce a boxplot of the <code>DML</code> variable against
<code>Fmaturity</code> to examine whether the size of the squid changes
with maturity stage. Change the chunk option to supress the R code in
the final document and only display the plot. Write some text to
summarise the main conclusions from the plot. Also include some inline R
code to report the mean value of DML for each of the maturity
stages.</p>
<p> </p>
<div class="toggle">
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<div class="sourceCode" id="cb6"><pre
class="sourceCode markdown"><code class="sourceCode markdown"><span id="cb6-1"><a href="#cb6-1" tabindex="-1"></a></span>
<span id="cb6-2"><a href="#cb6-2" tabindex="-1"></a>Let's take a look at whether DML changes with maturity stage. </span>
<span id="cb6-3"><a href="#cb6-3" tabindex="-1"></a></span>
<span id="cb6-4"><a href="#cb6-4" tabindex="-1"></a><span class="in">```{r, maturity-dml, echo=FALSE}</span></span>
<span id="cb6-5"><a href="#cb6-5" tabindex="-1"></a></span>
<span id="cb6-6"><a href="#cb6-6" tabindex="-1"></a><span class="in">boxplot(DML ~ Fmaturity, data = squid, xlab = "maturity stage", ylab = "DML")</span></span>
<span id="cb6-7"><a href="#cb6-7" tabindex="-1"></a></span>
<span id="cb6-8"><a href="#cb6-8" tabindex="-1"></a><span class="in">```</span></span>
<span id="cb6-9"><a href="#cb6-9" tabindex="-1"></a>DML was lowest for maturity stage 1 with a mean length of </span>
<span id="cb6-10"><a href="#cb6-10" tabindex="-1"></a><span class="in">`r round(mean(squid$DM[squid$Fmaturity == 1]), digits = 2)`</span> mm. DML </span>
<span id="cb6-11"><a href="#cb6-11" tabindex="-1"></a>increased until maturity stage 3 </span>
<span id="cb6-12"><a href="#cb6-12" tabindex="-1"></a>(mean <span class="in">`r round(mean(squid$DM[squid$Fmaturity == 3]), digits = 2)`</span> mm) </span>
<span id="cb6-13"><a href="#cb6-13" tabindex="-1"></a>after which it remained reasonably consistent for maturity stages 4 </span>
<span id="cb6-14"><a href="#cb6-14" tabindex="-1"></a>(mean <span class="in">`r round(mean(squid$DM[squid$Fmaturity == 4]), digits = 2)`</span> mm) </span>
<span id="cb6-15"><a href="#cb6-15" tabindex="-1"></a>and 5 (mean <span class="in">`r round(mean(squid$DM[squid$Fmaturity == 5]), digits = 2)`</span> mm). </span></code></pre></div>
</div>
<p> </p>
<p>It’s always good practice to include a summary of the version of R
you have been using as well as a list of packages loaded. An easy way to
do this is include <code>sessionInfo()</code> in a code chunk at the end
of your document.</p>
<p> </p>
<div class="toggle">
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<div class="sourceCode" id="cb7"><pre
class="sourceCode markdown"><code class="sourceCode markdown"><span id="cb7-1"><a href="#cb7-1" tabindex="-1"></a><span class="in">```{r, session-info, echo=FALSE}</span></span>
<span id="cb7-2"><a href="#cb7-2" tabindex="-1"></a><span class="in">sessionInfo()</span></span>
<span id="cb7-3"><a href="#cb7-3" tabindex="-1"></a><span class="in">```</span></span></code></pre></div>
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