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<h1>RepData peer Assesssment 1</h1>
<h2>Loading the data</h2>
<ul>
<li>Load the data</li>
</ul>
<pre><code class="r">activity = read.csv("activity.csv")
</code></pre>
<ul>
<li>Process/transform the data (if necessary) into a format suitable for your analysis</li>
</ul>
<pre><code class="r">totalSteps <- aggregate(steps ~ date, data = activity, sum, na.rm = TRUE)
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<ul>
<li>Make a histogram of the total number of steps taken each day</li>
</ul>
<pre><code class="r">hist(totalSteps$steps)
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-3"/> </p>
<ul>
<li>Calculate and report the <strong>mean</strong> and <strong>median</strong> total number of steps taken
per day </li>
</ul>
<pre><code class="r">mean(totalSteps$steps)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<pre><code class="r">median(totalSteps$steps)
</code></pre>
<pre><code>## [1] 10765
</code></pre>
<ul>
<li>The <strong>mean</strong> total number of steps taken per day is
1.0766 × 10<sup>4</sup> steps.</li>
<li>The <strong>median</strong> total number of steps taken per day is
10765 steps.</li>
</ul>
<h2>What is the average daily activity pattern?</h2>
<ul>
<li>Make a time series plot (i.e. type = “l”) of the 5-minute interval (x-axis) and the average number of steps taken, averaged across all days (y-axis)</li>
</ul>
<pre><code class="r">stepsInterval <- aggregate(steps ~ interval, data = activity, mean, na.rm = TRUE)
plot(steps ~ interval, data = stepsInterval, type = "l")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-5"/> </p>
<ul>
<li>Which 5-minute interval, on average across all the days in the dataset, contains the maximum number of steps? </li>
</ul>
<pre><code class="r">stepsInterval[which.max(stepsInterval$steps), ]$interval
</code></pre>
<pre><code>## [1] 835
</code></pre>
<p>It is the <strong>835th</strong> interval.</p>
<h2>Imputing missing values</h2>
<ul>
<li>Calculate and report the total number of missing values in the dataset (i.e. the total number of rows with NAs)</li>
</ul>
<pre><code class="r">sum(is.na(activity$steps))
</code></pre>
<pre><code>## [1] 2304
</code></pre>
<p>Total 2304 rows are missing.</p>
<ul>
<li>Devise a strategy for filling in all of the missing values in the dataset. The strategy does not need to be sophisticated. For example, you could use the mean/median for that day, or the mean for that 5-minute interval, etc.</li>
</ul>
<p>: I used a strategy for filing in all of the missing values with the mean for that 5-minute interval. First of all, I made a function <strong>“interval2steps”</strong> to get the mean steps for particular 5-minute interval. </p>
<pre><code class="r">interval2steps <- function(interval) {
stepsInterval[stepsInterval$interval == interval, ]$steps
}
</code></pre>
<ul>
<li>Create a new dataset that is equal to the original dataset but with the missing data filled in.</li>
</ul>
<pre><code class="r">activityFilled <- activity # Make a new dataset with the original data
count = 0 # Count the number of data filled in
for (i in 1:nrow(activityFilled)) {
if (is.na(activityFilled[i, ]$steps)) {
activityFilled[i, ]$steps <- interval2steps(activityFilled[i, ]$interval)
count = count + 1
}
}
cat("Total ", count, "NA values were filled.\n\r")
</code></pre>
<pre><code>## Total 2304 NA values were filled.
##
</code></pre>
<ul>
<li>Make a histogram of the total number of steps taken each day and Calculate and report the mean and median total number of steps taken per day. </li>
</ul>
<pre><code class="r">totalSteps2 <- aggregate(steps ~ date, data = activityFilled, sum)
hist(totalSteps2$steps)
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-10"/> </p>
<pre><code class="r">mean(totalSteps2$steps)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<pre><code class="r">median(totalSteps2$steps)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<ul>
<li>The <strong>mean</strong> total number of steps taken per day is
1.0766 × 10<sup>4</sup> steps.</li>
<li><p>The <strong>median</strong> total number of steps taken per day is
1.0766 × 10<sup>4</sup> steps.</p></li>
<li><p>Do these values differ from the estimates from the first part of the assignment? What is the impact of imputing missing data on the estimates of the total daily number of steps?</p></li>
</ul>
<p>: The <strong>mean</strong> value is the <strong>same</strong> as the value before imputing missing data because we put the mean value for that particular 5-min interval. The median value shows <strong>a little</strong> difference : but it depends on <strong>where the missing values are</strong>.</p>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<ul>
<li>Create a new factor variable in the dataset with two levels – “weekday” and “weekend” indicating whether a given date is a weekday or weekend day.</li>
</ul>
<pre><code class="r">activityFilled$day = ifelse(as.POSIXlt(as.Date(activityFilled$date))$wday%%6 ==
0, "weekend", "weekday")
# For Sunday and Saturday : weekend, Other days : weekday
activityFilled$day = factor(activityFilled$day, levels = c("weekday", "weekend"))
</code></pre>
<ul>
<li>Make a panel plot containing a time series plot (i.e. type = “l”) of the 5-minute interval (x-axis) and the average number of steps taken, averaged across all weekday days or weekend days (y-axis). The plot should look something like the following, which was creating using simulated data:</li>
</ul>
<pre><code class="r">stepsInterval2 = aggregate(steps ~ interval + day, activityFilled, mean)
library(lattice)
xyplot(steps ~ interval | factor(day), data = stepsInterval2, aspect = 1/2,
type = "l")
</code></pre>
<p><img src="data:image/png;base64,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" 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