HW2

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Homework 2

1. Loading the data

setwd("C:/")
activity <-read.csv("./activity.csv")

totalSteps <- aggregate(steps ~ date, data = activity, sum, na.rm = TRUE)

2. what is mean total number of steps taken per day? histogram

hist(totalSteps$steps,col="blue")

mean(totalSteps$steps)

## [1] 10766

median(totalSteps$steps)

## [1] 10765

3. what is the average daily activity pattern?

stepsInterval <- aggregate(steps ~ interval, data = activity, mean, na.rm = TRUE)
plot(steps ~ interval, data = stepsInterval, type = "l", col="blue")

stepsInterval[which.max(stepsInterval$steps), ]$interval

## [1] 835

4. Imputing missing values

sum(is.na(activity$steps))

## [1] 2304

교수님 이건 안배운거 같아요.

interval2steps <- function(interval) {
    stepsInterval[stepsInterval$interval == interval, ]$steps
}

이건 진짜로 모르겠네요~~

activityFilled <- activity 
count = 0 
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")

## Total  2304 NA values were filled.
## 

요건 약간 익숙해졌네요.

totalSteps2 <- aggregate(steps ~ date, data = activityFilled, sum)
hist(totalSteps2$steps, col="pink")

mean(totalSteps$steps)

## [1] 10766

median(totalSteps$steps)

## [1] 10765

5. Are there differenced in activity patterns between weekdays and weekends?

멘붕

activityFilled$day = ifelse(as.POSIXlt(as.Date(activityFilled$date))$wday%%6 == 
    0, "weekend", "weekday")
activityFilled$day = factor(activityFilled$day, levels = c("weekday", "weekend"))

stepsInterval2 = aggregate(steps ~ interval + day, activityFilled, mean)
library(lattice)
xyplot(steps ~ interval | factor(day), data = stepsInterval2, aspect = 1/2, 
    type = "l", col="green")

교수님 다 컨닝했어요. 죄송해요 ㅠㅠ