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<h1>Reproducible Research: Peer Assessment 1</h1>
<h2>Load required packages</h2>
<pre><code class="r">library(stats)
library(lattice)
</code></pre>
<h2>Loading and preprocessing the data</h2>
<pre><code class="r">unzip("activity.zip")
actv <- read.csv("activity.csv", na.strings = c("NA"))
summary(actv)
</code></pre>
<pre><code>## steps date interval
## Min. : 0.0 2012-10-01: 288 Min. : 0
## 1st Qu.: 0.0 2012-10-02: 288 1st Qu.: 589
## Median : 0.0 2012-10-03: 288 Median :1178
## Mean : 37.4 2012-10-04: 288 Mean :1178
## 3rd Qu.: 12.0 2012-10-05: 288 3rd Qu.:1766
## Max. :806.0 2012-10-06: 288 Max. :2355
## NA's :2304 (Other) :15840
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<pre><code class="r">actv_bydt <- aggregate(actv$steps, list(actv$date), sum, na.rm = TRUE, simplify = TRUE)
hist(actv_bydt$x, breaks = 15, xlab = "Total steps", main = "Histogram of Activity per Day - Raw Data")
</code></pre>
<p><img 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" alt="plot of chunk mean_steps_per_day"/> </p>
<pre><code class="r">actv_bydt_mean <- mean(actv_bydt$x, na.rm = TRUE)
actv_bydt_medn <- median(actv_bydt$x, na.rm = TRUE)
</code></pre>
<ul>
<li><p>The mean number of steps per day is 9354.2.</p></li>
<li><p>The median number of steps per day is 10395.0.</p></li>
</ul>
<h2>What is the average daily activity pattern?</h2>
<pre><code class="r">actv_byin <- aggregate(actv$steps, list(actv$interval), mean, na.rm = TRUE,
simplify = TRUE)
plot(actv_byin$Group.1, actv_byin$x, type = "l", main = "Mean steps by interval",
xlab = "interval", ylab = "mean steps")
</code></pre>
<p><img 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" alt="plot of chunk avg_daily_activity"/> </p>
<pre><code class="r">max_intv <- actv_byin[actv_byin$x == max(actv_byin$x), ]$Group.1
</code></pre>
<ul>
<li>The interval with the largest mean steps taken across all days is number 835.</li>
</ul>
<h2>Imputing missing values</h2>
<pre><code class="r"># Fill any NA steps values with the mean number of steps for that specific
# interval across all days or, if there are no non-NA values for that
# specific interval, the overall mean number of steps per interval
strt_na <- sum(is.na(actv$steps))
overall_intv_mean <- mean(actv$steps, na.rm = TRUE)
actv_impu <- actv
for (rownum in 1:nrow(actv_impu)) {
curr_step <- actv_impu[rownum, ]$steps
curr_intv <- actv_impu[rownum, ]$interval
if (is.na(curr_step)) {
intv_mean <- actv_byin[actv_byin$Group.1 == curr_intv, ]$x
if (!is.na(intv_mean)) {
actv_impu[rownum, ]$steps <- intv_mean
} else {
actv_impu[rownum, ]$steps <- overall_intv_mean
}
}
}
end_na <- sum(is.na(actv_impu$steps))
actv_bydt_impu <- aggregate(actv_impu$steps, list(actv_impu$date), sum, simplify = TRUE)
hist(actv_bydt_impu$x, breaks = 15, xlab = "Total steps", main = "Histogram of Activity per Day - Imputed Data")
</code></pre>
<p><img 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" alt="plot of chunk impute_missing"/> </p>
<pre><code class="r">actv_bydt_mean_impu <- mean(actv_bydt_impu$x, na.rm = TRUE)
actv_bydt_medn_impu <- median(actv_bydt_impu$x, na.rm = TRUE)
actv_bydt_mean_chng <- (actv_bydt_mean_impu - actv_bydt_mean)/actv_bydt_mean
</code></pre>
<ul>
<li><p>Total number of records with missing steps before imputing values: 2304. Number after imputation: 0.</p></li>
<li><p>Mean steps per day before imputing values: 9354.2. After: 10766.2.</p></li>
<li><p>Median steps per day before imputing values: 10395.0. After: 10766.2.</p></li>
<li><p>Imputing values for missing step counts raised the mean steps per day by 15.1%.</p></li>
</ul>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<pre><code class="r"># 5. weekdays vs. weekends -----------------------------
actv_impu$dayname <- weekdays(as.POSIXct(actv_impu$date, "%Y-%m-%d"))
</code></pre>
<pre><code>## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
## Warning: unknown timezone '%Y-%m-%d'
</code></pre>
<pre><code class="r">actv_impu$weekend <- factor(actv_impu$dayname %in% c("Saturday", "Sunday"),
labels = c("weekday", "weekend"))
actv_byin_impu <- aggregate(actv_impu$steps, list(interval = actv_impu$interval,
weekend = actv_impu$weekend), mean, na.rm = TRUE, simplify = TRUE)
xyplot(actv_byin_impu$x ~ actv_byin_impu$interval | actv_byin_impu$weekend,
type = "l", layout = c(1, 2), ylab = "Number of steps", xlab = "Interval")
</code></pre>
<p><img 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" alt="plot of chunk weekday_v_weekend"/> </p>
<ul>
<li>The weekend step pattern shows a relatively steady and relatively high step count throughout the day while the weekday pattern shows high step count in the morning followed by reduced activity during the remainder of the day. </li>
</ul>
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