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<body>
<h1>The fatal impact of tornadoes and economic effects of floods</h1>

<h2>Synopsis</h2>

<p>This report downloads data from NOAA Storm Database and performs a
statistical analysis on the impact of physical events to population
health and economy.</p>

<p>Examining the event types, we observe that most of the physical
phenomena cause injuries to people, which sometimes are fatal. By far,
Tornadoes are the most dangerous events, caused ~100.000 injuries on
the last 60 years.</p>

<p>When analysing the event types by the impact on the economy, we
observe that floods caused $15 billions damages on the last 60 years,
mostly on properties.</p>

<h2>Data Processing</h2>

<h3>Load</h3>

<p>How the data were loaded into R.</p>

<p>Data are downloaded and imported in stormdata data frame.</p>

<pre><code class="r">fileUrl &lt;-
&quot;https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.c
sv.bz2&quot;
download.file(fileUrl, destfile = &quot;tempdata.csv.bz2&quot;, method
= &quot;curl&quot;)
stormdata &lt;- read.csv(&quot;./tempdata.csv.bz2&quot;)
</code></pre>

<h3>Process</h3>

<p>How the data are processed for analysis.</p>

<p>To calculate the injuries to humans, <code>damages</code> dataframe
is being used, to aggregate both fatal and non-fatal injuries.</p>

<p>The economic impact is assessed by calculating the exponential value
of the property and corp damage in data frame <code>economic</code>.</p>

<p>Two small data frames <code>dam</code> and <code>eco</code> are used
to calculate only the top 10 events in human and economic impact
respectively.</p>

<pre><code class="r">library(Hmisc)
</code></pre>

<pre><code>## Loading required package: grid
## Loading required package: lattice
## Loading required package: survival
## Loading required package: splines
## Loading required package: Formula
##
## Attaching package: &#39;Hmisc&#39;
##
## The following objects are masked from &#39;package:base&#39;:
##
##     format.pval, round.POSIXt, trunc.POSIXt, units
</code></pre>

<pre><code class="r">library(reshape)
library(ggplot2)
library(car)

stormdata$EVTYPE &lt;- capitalize(tolower(stormdata$EVTYPE))

damages &lt;- aggregate(cbind(FATALITIES, INJURIES) ~ EVTYPE,
stormdata, sum)
dam &lt;- melt(head(damages[order(-damages$FATALITIES,
-damages$INJURIES), ], 10))
</code></pre>

<pre><code>## Using EVTYPE as id variables
</code></pre>

<pre><code class="r">
stormdata$PROPDMG &lt;- stormdata$PROPDMG *
as.numeric(Recode(stormdata$PROPDMGEXP,

&quot;&#39;0&#39;=1;&#39;1&#39;=10;&#39;2&#39;=100;&#39;3&#39;=1000;&#39
;4&#39;=10000;&#39;5&#39;=100000;&#39;6&#39;=1000000;&#39;7&#39;=1000000
0;&#39;8&#39;=100000000;&#39;B&#39;=1000000000;&#39;h&#39;=100;&#39;H&#3
9;=100;&#39;K&#39;=1000;&#39;m&#39;=1000000;&#39;M&#39;=1000000;&#39;-&#
39;=0;&#39;?&#39;=0;&#39;+&#39;=0&quot;,
    as.factor.result = FALSE))
stormdata$CROPDMG &lt;- stormdata$CROPDMG *
as.numeric(Recode(stormdata$CROPDMGEXP,

&quot;&#39;0&#39;=1;&#39;2&#39;=100;&#39;B&#39;=1000000000;&#39;k&#39;=1
000;&#39;K&#39;=1000;&#39;m&#39;=1000000;&#39;M&#39;=1000000;&#39;&#39;=
0;&#39;?&#39;=0&quot;,
    as.factor.result = FALSE))

economic &lt;- aggregate(cbind(PROPDMG, CROPDMG) ~ EVTYPE, stormdata,
sum)
eco &lt;- melt(head(economic[order(-economic$PROPDMG,
-economic$CROPDMG), ], 10))
</code></pre>

<pre><code>## Using EVTYPE as id variables
</code></pre>

<h2>Results</h2>

<h3>Human casualties</h3>

<ul>
<li>Question: Across the United States, which types of events (as
indicated in the EVTYPE variable) are most harmful with respect to
population health?</li>
</ul>

<p>By using the ggplot2 library we present a combined flipped barplot
graph of the fatal (Deaths) and non-fatal Injuries, by event type.</p>

<pre><code class="r">ggplot(dam, aes(x = EVTYPE, y = value, fill =
variable)) + geom_bar(stat = &quot;identity&quot;) +
    coord_flip() + ggtitle(&quot;Harmful events&quot;) + labs(x =
&quot;&quot;, y = &quot;number of people impacted&quot;) +
    scale_fill_manual(values = c(&quot;orange&quot;,
&quot;black&quot;), labels = c(&quot;Deaths&quot;,
&quot;Injuries&quot;))
</code></pre>

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kSuQmCC" alt="plot of chunk unnamed-chunk-3"/> </p>

<h3>Economic impact</h3>

<ul>
<li>Question: Across the United States, which types of events have the
greatest economic consequences?</li>
</ul>

<p>By using the ggplot2 library we present a combined flipped barplot
graph of the property and corp damages, by event type.</p>

<pre><code class="r">ggplot(eco, aes(x = EVTYPE, y = value, fill =
variable)) + geom_bar(stat = &quot;identity&quot;) +
    coord_flip() + ggtitle(&quot;Economic consequences&quot;) + labs(x
= &quot;&quot;, y = &quot;cost of damages in dollars&quot;) +
    scale_fill_manual(values = c(&quot;orange&quot;,
&quot;black&quot;), labels = c(&quot;Property Damage&quot;,
        &quot;Crop Damage&quot;))
</code></pre>

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