PA1_template.Rmd

---
title: "rpweek2"
author: "dawky"
date: "Sunday, November 19, 2017"
output: html_document
---

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```{r}
library(ggplot2) 
library(lattice) 
library(gridExtra) 

setwd("D:/r/coursera")

## Load and Observe Data 
myfile <- "D:/r/coursera/activity.csv" 
dat <- read.csv(myfile, stringsAsFactors=FALSE) 


dat2 <- dat[complete.cases(dat),] 


## What is mean total number of steps taken per day? 
png("p1.png",width=480,height=480)

 

data<-aggregate(steps ~ date, dat, FUN = sum) 

stepsmean <- mean(data$steps) 
stepsmedian <- median(data$steps)
hist(data$steps,breaks=20,xlab="steps",main="steps taken per day",col="grey")
legend("topright",col="blue",legend=c(paste("stepsmean",stepsmean),paste("stepsmedian",stepsmedian)))

dev.off()

## What is the average daily activity pattern? 

png("p2.png",width=480,height=480)

dat4 <- aggregate(steps ~ interval, dat2, FUN = mean) 
maxsteps <- max(dat4$steps) 
maxinterval <- dat4[dat4$steps == maxsteps, ]$interval
plot(dat4$interval, dat4$steps, type = "l", main = "average daily activity pattern", 
     xlab = "interval", ylab = "steps") 

legend("topright",c(paste("maxinterval",maxinterval),paste("maxsteps",maxsteps))) 


dev.off()

## Imputing missing values 
png("p3.png",width=480,height=480)

dat5 <- dat
for (i in 1:nrow(dat5)) { 
  if (is.na(dat5[i, ]$steps)) { 
    dat5[i, ]$steps <- 
      dat4[dat4$interval ==dat5[i, ]$interval, ]$steps 
  } 
} 
dat5a<-aggregate(steps ~ date, dat5, FUN = sum) 

hist(dat5a$steps,breaks=20,xlab="steps",main="steps taken per day after inputing",col="grey")
stepsmean5 <- mean(dat5a$steps) 
stepsmedian5 <- median(dat5a$steps) 
legend("topright",c(paste("stepsmean",stepsmean5),paste("stepsmedian",stepsmedian5)))



dev.off()

```

## Do these values differ from the estimates from the first part of the assignment

```{r}
paste(stepsmean,stepsmedian)  
paste(stepsmean5,stepsmedian5)
```

## impact of imputing missing data on the estimates of the total daily number of step
```{r}
sum(dat2$steps)  

sum(dat5$steps)
```

```{r}

## Are there differences in activity patterns between weekdays and weekends? 

png("p4.png",width=480,height=480)

dat5$day <- NA 
for (i in 1:nrow(dat5)) { 
  if (weekdays(as.Date(dat5[i, ]$date)) == "Saturday" | weekdays(as.Date(dat5[i, ]$date)) == "Sunday") { 
    dat5[i, ]$day <- "weekend" }
  else { 
    dat5[i, ]$day <- "weekday" 
  } 
} 
dat5$day <- factor(dat5$day) 
dat6 <- aggregate(steps ~ interval + day, dat5, FUN = mean) 
xyplot(steps ~ interval | factor(day), 
       data = dat6, 
       type = "l", 
       layout = c(1,2), 
       xlab = "Interval", 
       ylab = "Number of Steps")

dev.off()

```

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