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<h2>Loading and preprocessing the data</h2>

<p>One of the principles of reproducable research is start processing your data from its raw form.  So I start here by unzipping the original data archive.  I avoid this step if it has already been done.</p>

<h3>Loading</h3>

<pre><code class="r">if(!file.exists(&quot;activity.csv&quot;))
{
    unzip(&quot;activity.zip&quot;)
}

steps &lt;- read.csv(&quot;activity.csv&quot;)
str(steps)
</code></pre>

<pre><code>## &#39;data.frame&#39;:    17568 obs. of  3 variables:
##  $ steps   : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ date    : Factor w/ 61 levels &quot;2012-10-01&quot;,&quot;2012-10-02&quot;,..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ interval: int  0 5 10 15 20 25 30 35 40 45 ...
</code></pre>

<h3>Preprocessing</h3>

<p>I&#39;ll need to summarize this data by date and figure out what days are weekends and weekdays to answer the questions below.  So I&#39;m going to convert the dates from strings to date class objects.  We also need to convert the interval identifiers to minutes.  I&#39;ll attach these to the date to make it easier to plot time series data later.</p>

<pre><code class="r">library(lubridate)
steps$date &lt;- ymd(steps$date)
str(steps)
</code></pre>

<pre><code>## &#39;data.frame&#39;:    17568 obs. of  3 variables:
##  $ steps   : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ date    : POSIXct, format: &quot;2012-10-01&quot; &quot;2012-10-01&quot; ...
##  $ interval: int  0 5 10 15 20 25 30 35 40 45 ...
</code></pre>

<h2>What is mean total number of steps taken per day?</h2>

<p>We&#39;ll need to summarize the number of steps by day here.  Dplyr has a handy function for this:</p>

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

<pre><code>## 
## Attaching package: &#39;dplyr&#39;
## 
## The following objects are masked from &#39;package:lubridate&#39;:
## 
##     intersect, setdiff, union
## 
## The following object is masked from &#39;package:stats&#39;:
## 
##     filter
## 
## The following objects are masked from &#39;package:base&#39;:
## 
##     intersect, setdiff, setequal, union
</code></pre>

<pre><code class="r">steps_per_day &lt;- steps %&gt;% group_by(date) %&gt;% summarize(total_steps = sum(steps,na.rm=TRUE))
hist(steps_per_day$total_steps)
</code></pre>

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

<pre><code class="r">mean_steps_per_day &lt;- round(steps_per_day %&gt;% summarize(mean(total_steps)))
median_steps_per_day &lt;- steps_per_day %&gt;% summarize(median(total_steps))
</code></pre>

<p>So the mean total number of steps taken per day is: 9354<br/>
The median total number of steps taken per day is: 10395</p>

<h2>What is the average daily activity pattern?</h2>

<p>Here we will average the number of steps across the days during each 5 minute activity period.</p>

<pre><code class="r">avg_steps_per_int &lt;- steps %&gt;% group_by(interval) %&gt;% summarize(avg_steps = mean(steps,na.rm=TRUE))

library(stringr)
avg_steps_per_int$interval &lt;- str_pad(avg_steps_per_int$interval,4,pad=&quot;0&quot;) # pad the hours and min for the time interval so that they are consistent
avg_steps_per_int$hour &lt;- substr(avg_steps_per_int$interval,1,2)
avg_steps_per_int$min &lt;- substr(avg_steps_per_int$interval,3,4)
avg_steps_per_int$hms &lt;- ymd_hms(paste(&quot;681122&quot;,avg_steps_per_int$hour,avg_steps_per_int$min,&quot;00&quot;)) # just picking a random date here to make the plot look nice
 plot(avg_steps_per_int$hms, avg_steps_per_int$avg_steps,type=&quot;l&quot;)
</code></pre>

<p><img 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" alt="plot of chunk unnamed-chunk-4"/> </p>

<pre><code class="r">sorted_by_avg_steps &lt;- avg_steps_per_int %&gt;% arrange(desc(avg_steps))
max_avg_step &lt;- sorted_by_avg_steps[1,2]
hour &lt;- sorted_by_avg_steps[1,3]
min &lt;- sorted_by_avg_steps[1,4]
</code></pre>

<p>So the maximum number of average steps taken is: 206.1698113 at 08:35</p>

<h2>Imputing missing values</h2>

<h3>Amount of population with missing values</h3>

<p>Let&#39;s get a sense of how complete our data is by figuring out how many missing values we have:</p>

<pre><code class="r">nas &lt;- table(is.na(steps$steps))
missing &lt;- nas[2]
percent_missing &lt;- round(nas[2] / (nas[1]+nas[2]) * 100)
</code></pre>

<p>So we have 2304 missing values which is 13% of the total population.</p>

<h3>Strategy for imputing missing values</h3>

<p>Our strategy for imputing missing values will be to use the average number of steps taken for the interval in question to impute any given missing interval step data.  We&#39;ll do this by creating a new table that links our step data to the table we made above to get the average number of steps per interval across all the days:</p>

<pre><code class="r">avg_steps_per_int$interval &lt;- as.integer(avg_steps_per_int$interval)
imputed_na_steps &lt;- steps %&gt;% left_join(avg_steps_per_int)
</code></pre>

<pre><code>## Joining by: &quot;interval&quot;
</code></pre>

<pre><code class="r"># replace the NAs with the average for the interval
isNA &lt;- is.na(imputed_na_steps$steps)
imputed_na_steps[isNA,]$steps &lt;- as.integer(round(imputed_na_steps[isNA,]$avg_steps))

# get rid of extraneous columns so that our new data set is equal to the first but with NAs filled in
imputed_na_steps &lt;- imputed_na_steps[1:3]

# Here is the first steps dataset and the imputed NA dataset.  Notices that the first has NAs in the interval while the second has the NAs replaced with the interval average
str(steps)
</code></pre>

<pre><code>## &#39;data.frame&#39;:    17568 obs. of  3 variables:
##  $ steps   : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ date    : POSIXct, format: &quot;2012-10-01&quot; &quot;2012-10-01&quot; ...
##  $ interval: int  0 5 10 15 20 25 30 35 40 45 ...
</code></pre>

<pre><code class="r">str(imputed_na_steps)
</code></pre>

<pre><code>## &#39;data.frame&#39;:    17568 obs. of  3 variables:
##  $ steps   : int  2 0 0 0 0 2 1 1 0 1 ...
##  $ date    : POSIXct, format: &quot;2012-10-01&quot; &quot;2012-10-01&quot; ...
##  $ interval: int  0 5 10 15 20 25 30 35 40 45 ...
</code></pre>

<pre><code class="r">imputedNA_steps_per_day &lt;- imputed_na_steps %&gt;% group_by(date) %&gt;% summarize(total_steps = sum(steps))
hist(imputedNA_steps_per_day$total_steps)
</code></pre>

<p><img 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alt="plot of chunk unnamed-chunk-6"/> </p>

<pre><code class="r">imputedNA_mean_steps_per_day &lt;- round(imputedNA_steps_per_day %&gt;% summarize(mean(total_steps)))
imputedNA_median_steps_per_day &lt;- round(imputedNA_steps_per_day %&gt;% summarize(median(total_steps)))
</code></pre>

<p>So now that we have imputed values for NA we can make the following comparison to get a sense of how imputing the missing values affects our anaysis:<br/>
imputed NAs mean: 1.0766 &times; 10<sup>4</sup><br/>
imputed NAs median: 1.0762 &times; 10<sup>4</sup>  </p>

<p>ignoring NAs mean: 9354<br/>
ignoring NAs median: 10395</p>

<p>The two strategies of ignoring NA values versus imputing them does have an affect on our analysis.  When we impute the values the mean and the median shift to larger values.  Looking at the two histograms of the total steps we can see that ignoring the NAs has the effect of showing an increased number of days with 0 - 5000 steps.  Imputing the NAs creates a <em>normal</em> distribution.</p>

<h2>Are there differences in activity patterns between weekdays and weekends?</h2>

<pre><code class="r"># add a factor variable with the weekend or weekday
imputed_na_steps$type &lt;- factor((weekdays(imputed_na_steps$date) %in% c(&quot;Saturday&quot;,&quot;Sunday&quot;))+1L,levels=1:2,labels=c(&#39;weekday&#39;,&#39;weekend&#39;))

# get the average steps on weekends
avg_steps_per_int_we &lt;- imputed_na_steps %&gt;% filter(type==&quot;weekend&quot;) %&gt;% group_by(interval) %&gt;% summarize(avg_steps = mean(steps,na.rm=TRUE))
avg_steps_per_int_we$type &lt;- factor(&quot;weekend&quot;)

# get the average steps for the intervals on weekdays
avg_steps_per_int_wd &lt;- imputed_na_steps %&gt;% filter(type==&quot;weekday&quot;) %&gt;% group_by(interval) %&gt;% summarize(avg_steps = mean(steps,na.rm=TRUE))
avg_steps_per_int_wd$type &lt;- factor(&quot;weekday&quot;)

# join the avg_step tables
wsteps &lt;- merge(avg_steps_per_int_we,avg_steps_per_int_wd, all=TRUE)

library(lattice)
xyplot(avg_steps ~ interval | type, data=wsteps, type=&quot;l&quot;)
</code></pre>

<p><img 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" alt="plot of chunk unnamed-chunk-7"/> </p>

<p>So we can see from the plot that the subject walks further on morning weekdays.</p>

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