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<title>Reproducible Research: Peer Assessment 1</title>
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<h1>Reproducible Research: Peer Assessment 1</h1>
<h2>Loading and preprocessing the data</h2>
<ol>
<li>Load the data (i.e. read.csv())</li>
</ol>
<pre><code class="r">unzip("activity.zip")
df <- read.csv("activity.csv")
</code></pre>
<ol>
<li>Process/transform the data (if necessary) into a format suitable for your
analysis. I made also the aggregation needed <strong>later</strong> here.</li>
</ol>
<pre><code class="r">missingvalues <- which(rowSums(is.na(df))>0)
dfNA <-df[missingvalues,]
dfNoNA <- df[-(missingvalues),]
dfNA$steps <- NULL
steps_mean_5minutes <- aggregate(dfNoNA$steps, list(dfNoNA$interval), FUN=mean)
names(steps_mean_5minutes) <- c("interval", "steps")
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<ol>
<li>Make a histogram of the total number of steps taken each day</li>
</ol>
<pre><code class="r">steps_daily <- aggregate(df$steps, list(df$date), FUN=sum)
names(steps_daily) <- c("Date","Steps")
hist(steps_daily$Steps, breaks=30, xlab="Daily steps",
main="Total number of steps taken each day")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-3"/> </p>
<ol>
<li>Calculate and report the mean and median total number of steps taken per day</li>
</ol>
<p>Mean steps each day</p>
<pre><code class="r">mean(steps_daily$Steps, na.rm=T)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<p>Median steps each day</p>
<pre><code class="r">median(steps_daily$Steps, na.rm=T)
</code></pre>
<pre><code>## [1] 10765
</code></pre>
<h2>What is the average daily activity pattern?</h2>
<ol>
<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>
</ol>
<pre><code class="r">library(ggplot2)
ggplot(steps_mean_5minutes, aes(x=interval, y=steps)) + geom_line()
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-6"/> </p>
<p>Which 5-minute interval, on average across all the days in the dataset,
contains the maximum number of steps?</p>
<pre><code class="r">maxSteps <- max(steps_mean_5minutes$steps)
subset(steps_mean_5minutes, steps==maxSteps)
</code></pre>
<pre><code>## interval steps
## 104 835 206.2
</code></pre>
<h2>Imputing missing values</h2>
<ol>
<li>Calculate and report the total number of missing values in the dataset
(i.e. the total number of rows with NAs)</li>
</ol>
<pre><code class="r">length(missingvalues)
</code></pre>
<pre><code>## [1] 2304
</code></pre>
<ol>
<li>Devise a strategy for filling in all of the missing values in the dataset.
The strategy does not need to be sophisticated. For example, you could use
the mean/median for that day, or the mean for that 5-minute interval, etc.
<strong>Comment: Here NA values are given mean value of that particular interval.</strong></li>
</ol>
<pre><code class="r">dfNA <- merge(x = dfNA, y = steps_mean_5minutes, by = "interval", all.x=TRUE)
</code></pre>
<ol>
<li>Create a new dataset that is equal to the original dataset but with the
missing data filled in.</li>
</ol>
<pre><code class="r">df_new <- rbind(dfNA,dfNoNA)
</code></pre>
<ol>
<li>Make a histogram of the total number of steps taken each day and Calculate and
report the mean and median total number of steps taken per day. Do these values
differ from the estimates from the first part of the assignment? What is the
impact of imputing missing data on the estimates of the total daily number of
steps?</li>
</ol>
<pre><code class="r">steps_sum_day <- aggregate(df_new$steps, list(df_new$date), FUN=sum)
hist(steps_sum_day$x, breaks=30, xlab="Daily steps",
main="Total number of steps taken each day with filled data")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-11"/> </p>
<pre><code class="r">mean(steps_sum_day$x, na.rm=T)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<pre><code class="r">median(steps_sum_day$x, na.rm=T)
</code></pre>
<pre><code>## [1] 10766
</code></pre>
<p>Median changes slightly, since values are skeved little bit to left. </p>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<ol>
<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>
</ol>
<pre><code class="r">weekend <- c("Saturday", "Sunday")
weekday <- ifelse(weekdays(as.Date(df_new$date)) %in% weekend,
"weekend", "weekday")
df_new$weekday <- as.factor(weekday)
</code></pre>
<ol>
<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).</li>
</ol>
<pre><code class="r">weekdays <- subset(df_new, weekday=="weekday")
weekend <- subset(df_new, weekday=="weekend")
weekdays <- aggregate(weekdays$steps, list(weekdays$interval), FUN=mean)
weekend <- aggregate(weekend$steps, list(weekend$interval), FUN=mean)
names(weekdays) <- c("interval","steps")
names(weekend) <- c("interval","steps")
weekdays$name <- "weekday"
weekend$name <- "weekend"
x <- rbind(weekend, weekdays)
ggplot() + facet_wrap(~name) + geom_line(data=x, aes(x=interval, y=steps))
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk unnamed-chunk-13"/> </p>
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