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<h2>Loading and preprocessing the data</h2>
<pre><code class="r">library(ggplot2)
activity = read.csv("activity.csv", stringsAsFactors=FALSE)
activity[, "date"] = as.Date(activity[, "date"], "%Y-%m-%d") # convert to date format
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<pre><code class="r"># ignore NA values
# note that this will cause some dates to be missing
activity_by_day = aggregate(steps ~ date, activity[!is.na(activity["steps"]), ], sum)
hist(activity_by_day$steps, main = "Total Steps Per Day", xlab = "Total Steps Per Day", freq = TRUE, breaks = 10)
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-2"/> </p>
<p>The mean total number of steps taken per day is calculated below:</p>
<pre><code class="r">mean(activity_by_day$steps)
</code></pre>
<pre><code>## [1] 10766.19
</code></pre>
<p>The median total number of steps taken per day is calculated below:</p>
<pre><code class="r">median(activity_by_day$steps)
</code></pre>
<pre><code>## [1] 10765
</code></pre>
<h2>What is the average daily activity pattern?</h2>
<pre><code class="r"># ignore NA values
activity_by_interval = aggregate(steps ~ interval, activity[!is.na(activity["steps"]), ], mean)
plot(activity_by_interval$interval, activity_by_interval$steps, xlab = "Interval", ylab = "Average Steps",
main = "Average Steps Per Interval", type = 'l')
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-5"/> </p>
<p>The interval with the maximum number of average steps is calculated below:</p>
<pre><code class="r">activity_by_interval[activity_by_interval$steps == max(activity_by_interval$steps), ]$interval
</code></pre>
<pre><code>## [1] 835
</code></pre>
<h2>Imputing missing values</h2>
<p>The total number of missing values is shown below:</p>
<pre><code class="r">sum(is.na(activity$steps))
</code></pre>
<pre><code>## [1] 2304
</code></pre>
<p>To impute missing values, the average value for the missing interval will be used. It seems like this would result in more likely data. For example, in the
middle of the night, when there's little activity, it's better to use a tiny value than the average for that day, which would be higher and not typical for
the middle of the night.</p>
<pre><code class="r"># put the NA rows into a new data frame
activity_na = activity[is.na(activity$steps), c("date", "interval")]
# merge NA rows with interval averages
# sort columns to be in the same order as original data frame
activity_na_imputed = merge(activity_by_interval, activity_na)[, c('steps','date','interval')]
# combine merged data with non-NA rows
activity_imputed = rbind(activity_na_imputed, activity[!is.na(activity$steps), ])
# plot histogram
activity_imputed_by_day = aggregate(steps ~ date, activity_imputed, sum)
hist(activity_imputed_by_day$steps, main = "Total Steps Per Day After Imputing", xlab = "Total Steps Per Day", freq = TRUE, breaks = 10)
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-8"/> </p>
<p>The mean total number of steps taken per day after imputing is calculated below. </p>
<pre><code class="r">mean(activity_imputed_by_day$steps)
</code></pre>
<pre><code>## [1] 10766.19
</code></pre>
<p>The median total number of steps taken per day after imputing is calculated below:</p>
<pre><code class="r">median(activity_imputed_by_day$steps)
</code></pre>
<pre><code>## [1] 10766.19
</code></pre>
<p>After imputing, the mean is the same as before. The reason for this is all missing values came from days where every interval had a missing value. The result would be different if there were days where some, but not all, values are missing. Similarly, the median is almost the same and is slightly higher. The impact of imputing
missing data was to add more days which all had the average number of steps. This causes the data after imputing to have more concentration around the mean.</p>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<pre><code class="r">activity_imputed$day_type = is.element(weekdays(activity_imputed$date), c('Saturday', 'Sunday'))
activity_imputed$day_type[activity_imputed$day_type == "TRUE"] = "weekend"
activity_imputed$day_type[activity_imputed$day_type == "FALSE"] = "weekday"
activity_imputed$day_type = factor(activity_imputed$day_type)
activity_imputed_by_interval_day = aggregate(steps ~ interval + day_type, activity_imputed, mean)
ggplot(activity_imputed_by_interval_day, aes(interval, steps)) + geom_line() + facet_wrap(~day_type, ncol=1)
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-11"/> </p>
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