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<h1>Reproducible Research: Peer Assessment 1</h1>
<h2>Loading and preprocessing the data</h2>
<p>1) and 2)</p>
<pre><code class="r">df <- read.table("~/activity.csv", sep = ",", header = TRUE, stringsAsFactors = FALSE)
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<p>1) Make a histogram of the total number of steps taken each day.</p>
<pre><code class="r">df1 <- aggregate(steps ~ date, data = df, na.rm = TRUE, sum)
with(df1, barplot(steps, main = "Total Number of Steps by day", ylab = "", xlab = "",
names = date, las = 2, cex.names = 0.5))
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-2"/> </p>
<p>2) Calculate and report the mean and median total number of steps taken per day</p>
<pre><code class="r">df2 <- aggregate(steps ~ date, data = df, na.rm = TRUE, mean)
df3 <- aggregate(steps ~ date, data = df, na.rm = TRUE, median)
M <- merge(df2, df3, by = "date")
colnames(M) <- c("date", "mean", "median")
head(M)
</code></pre>
<pre><code>## date mean median
## 1 2012-10-02 0.4375 0
## 2 2012-10-03 39.4167 0
## 3 2012-10-04 42.0694 0
## 4 2012-10-05 46.1597 0
## 5 2012-10-06 53.5417 0
## 6 2012-10-07 38.2465 0
</code></pre>
<h2>What is the average daily activity pattern?</h2>
<p>1) 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).</p>
<pre><code class="r">df4 <- aggregate(steps ~ interval, data = df, na.rm = TRUE, mean)
with(df4, plot(interval, steps, main = "Average Number of Steps by Interval",
ylab = "Average Number of Steps", xlab = "Interval", type = "l"))
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-4"/> </p>
<p>2) Which 5-minute interval, on average across all the days in the dataset, contains the maximum number of steps?</p>
<pre><code class="r">df4[df4$steps == max(df4$steps), ]
</code></pre>
<pre><code>## interval steps
## 104 835 206.2
</code></pre>
<h2>Imputing missing values</h2>
<p>1) Calculate and report the total number of missing values in the dataset (i.e. the total number of rows with NAs).</p>
<pre><code class="r">nrow(df[df$steps == "NA", ])
</code></pre>
<pre><code>## [1] 2304
</code></pre>
<p>2) Devise a strategy for filling in all of the missing values in the dataset. The strategy does not need to be sophisticated. For example, you could use the mean/median for that day, or the mean for that 5-minute interval, etc.</p>
<p>Strategy: Mean for that 5-minute interval. </p>
<pre><code class="r">df <- read.table("~/activity.csv", sep = ",", header = TRUE, stringsAsFactors = FALSE)
df1 <- aggregate(steps ~ interval, data = df, na.rm = TRUE, mean)
t = nrow(df)/nrow(df1)
dfx = NULL
for (i in 1:t) {
dfx <- rbind(dfx, df1)
}
for (i in 1:length(df)) {
it = which(is.na(df$steps))
for (j in 1:length(it)) {
df$steps[it[j]] <- dfx$steps[it[j]]
}
}
head(df)
</code></pre>
<pre><code>## steps date interval
## 1 1.71698 2012-10-01 0
## 2 0.33962 2012-10-01 5
## 3 0.13208 2012-10-01 10
## 4 0.15094 2012-10-01 15
## 5 0.07547 2012-10-01 20
## 6 2.09434 2012-10-01 25
</code></pre>
<p>3) Create a new dataset that is equal to the original dataset but with the missing data filled in.</p>
<pre><code class="r">write.table(df, "activity1.csv", sep = ",", row.names = FALSE)
</code></pre>
<p>4) 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?</p>
<p>The impact is small, in general. Also it's possible to see that two days were added: 2012-10-01 and 2012-11-30. Moreover, the number of rows without NA is 17568 and the number of rows with NA is 2304. The total number of steps without NA is 570608 steps and the total number of steps with NA (filled in) is 656737.5 steps, ie. a difference of 89129.5 steps or +15%.</p>
<pre><code class="r">df1 <- aggregate(steps ~ date, data = df, na.rm = TRUE, sum)
with(df1, barplot(steps, main = "Total Number of Steps by day", ylab = "", xlab = "",
names = date, las = 2, cex.names = 0.5))
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-9"/> </p>
<pre><code class="r">df2 <- aggregate(steps ~ date, data = df, na.rm = TRUE, mean)
df3 <- aggregate(steps ~ date, data = df, na.rm = TRUE, median)
M <- merge(df2, df3, by = "date")
colnames(M) <- c("date", "mean", "median")
head(M)
</code></pre>
<pre><code>## date mean median
## 1 2012-10-01 37.3826 34.11
## 2 2012-10-02 0.4375 0.00
## 3 2012-10-03 39.4167 0.00
## 4 2012-10-04 42.0694 0.00
## 5 2012-10-05 46.1597 0.00
## 6 2012-10-06 53.5417 0.00
</code></pre>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<p>1) 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.</p>
<p>New factors: weekday and weekend</p>
<pre><code class="r">df$date <- as.Date(df$date)
df$day <- weekdays(df$date)
df$day[df$day == "Saturday" | df$day == "Sunday"] <- "weekend"
df$day[df$day != "weekend"] <- "weekday"
</code></pre>
<p>New table dft with new factors</p>
<pre><code class="r">dfwy <- subset(df, df$day == "weekday")
df4 <- aggregate(steps ~ interval, data = dfwy, na.rm = TRUE, mean)
df4$day <- "weekday"
dfwd <- subset(df, df$day == "weekend")
df5 <- aggregate(steps ~ interval, data = dfwd, na.rm = TRUE, mean)
df5$day <- "weekend"
dft <- rbind(df4, df5)
head(dft)
</code></pre>
<pre><code>## interval steps day
## 1 0 2.25115 weekday
## 2 5 0.44528 weekday
## 3 10 0.17317 weekday
## 4 15 0.19790 weekday
## 5 20 0.09895 weekday
## 6 25 1.59036 weekday
</code></pre>
<p>2) Make a panel plot containing a time series plot (i.e. type = “l”) of the 5-minute interval (x-axis) and the average number of steps taken, averaged across all weekday days or weekend days (y-axis).</p>
<pre><code class="r">library(lattice)
xyplot(dft$steps ~ dft$interval | dft$day, layout = c(1, 2), ylab = "Number of Steps",
xlab = "Interval", type = "l")
</code></pre>
<p><img 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alt="plot of chunk unnamed-chunk-13"/> </p>
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