first commit for PA1.

PA1_template.Rmd

@@ -8,15 +8,64 @@ output:
 
 ## Loading and preprocessing the data
 
+### Load the activity data
+Extract the zip file on your OS and load the data file 'activity.csv' in R.
+
+```{r loaddata, echo=TRUE}
+dat <- read.csv("activity.csv", sep = ",", header = TRUE)
+```
+
+### Process the data
+Factor the 'date' field for further analysis.
+
+```{r preprocess, echo= TRUE}
+dat <- transform(dat, date = factor(date))
+```
 
 
 ## What is mean total number of steps taken per day?
 
+### Histogram of the total number of steps taken each day
+```{r histogram.steps.each.day, echo = TRUE}
+library(ggplot2)
+steps.per.day <- tapply(dat$steps, dat$date, sum, na.rm = TRUE)
+steps <- data.frame(steps.per.day, names(steps.per.day))
+hist(steps$steps.per.day, breaks = length(steps.per.day), xlab = " Number of Steps Each Day", main = "Histogram of Steps Taken Each Day")
+```
+
+---
+![Histogram of steps taken each day](instructions_fig/histStepsEachDay.png)
+---
+
+###  Mean and median total number of steps taken per day
+```{r meanAndMedian, echo = TRUE}
+mu <- mean(steps.per.day, na.rm = TRUE)
+median <- median(steps.per.day, na.rm = TRUE)
+```
+Mean of total number of steps taken per day is **`r mu`**.
+
+Median of total numnber of steps taken per day is **`r median`**.
 
 
 ## What is the average daily activity pattern?
 
+### Average Steps taken for each interval across all days
+```{r avgStepsPerInterval, echo = TRUE}
+dat <- transform(dat, interval = ordered(as.numeric(interval)))
+avg.steps.per.interval <- tapply(dat$steps, dat$interval, mean, na.rm = TRUE)
+avg.steps <- data.frame(steps = avg.steps.per.interval, interval = as.numeric(names(avg.steps.per.interval)))
+plot(x = avg.steps$interval, y = avg.steps$steps, type = "l", xlab = "Interval", ylab = "Steps", main = "Average Steps per Interval")
+```
+
+---
+![Average Steps Per Interval](instructions_fig/avgStepsPerInterval.png)
+---
 
+### Overall Maximum Steps Interval Identifier
+```{r maxStepsInterval, echo = TRUE}
+interval.id <- avg.steps[which.max(avg.steps$steps), 2]
+```
+Id **`r interval.id`** is the 5-minute interval id, on average across all the days in the dataset, which contains the maximum number of steps.
 
 ## Imputing missing values
 

PA1_template.md

@@ -0,0 +1,79 @@
+# Reproducible Research: Peer Assessment 1
+
+
+## Loading and preprocessing the data
+
+### Load the activity data
+Extract the zip file on your OS and load the data file 'activity.csv' in R.
+
+
+```r
+dat <- read.csv("activity.csv", sep = ",", header = TRUE)
+```
+
+### Process the data
+Factor the 'date' field for further analysis.
+
+
+```r
+dat <- transform(dat, date = factor(date))
+```
+
+
+## What is mean total number of steps taken per day?
+
+### Histogram of the total number of steps taken each day
+
+```r
+library(ggplot2)
+steps.per.day <- tapply(dat$steps, dat$date, sum, na.rm = TRUE)
+steps <- data.frame(steps.per.day, names(steps.per.day))
+hist(steps$steps.per.day, breaks = length(steps.per.day), xlab = " Number of Steps Each Day", main = "Histogram of Steps Taken Each Day")
+```
+
+![plot of chunk histogram.steps.each.day](./PA1_template_files/figure-html/histogram.steps.each.day.png) 
+
+---
+![Histogram of steps taken each day](instructions_fig/histStepsEachDay.png)
+---
+
+###  Mean and median total number of steps taken per day
+
+```r
+mu <- mean(steps.per.day, na.rm = TRUE)
+median <- median(steps.per.day, na.rm = TRUE)
+```
+Mean of total number of steps taken per day is **9354.2295**.
+
+Median of total numnber of steps taken per day is **10395**.
+
+
+## What is the average daily activity pattern?
+
+### Average Steps taken for each interval across all days
+
+```r
+dat <- transform(dat, interval = ordered(as.numeric(interval)))
+avg.steps.per.interval <- tapply(dat$steps, dat$interval, mean, na.rm = TRUE)
+avg.steps <- data.frame(steps = avg.steps.per.interval, interval = as.numeric(names(avg.steps.per.interval)))
+plot(x = avg.steps$interval, y = avg.steps$steps, type = "l", xlab = "Interval", ylab = "Steps", main = "Average Steps per Interval")
+```
+
+![plot of chunk avgStepsPerInterval](./PA1_template_files/figure-html/avgStepsPerInterval.png) 
+
+---
+![Average Steps Per Interval](instructions_fig/avgStepsPerInterval.png)
+---
+
+### Overall Maximum Steps Interval Identifier
+
+```r
+interval.id <- avg.steps[which.max(avg.steps$steps), 2]
+```
+Id **835** is the 5-minute interval id, on average across all the days in the dataset, which contains the maximum number of steps.
+
+## Imputing missing values
+
+
+
+## Are there differences in activity patterns between weekdays and weekends?

PA1_template_files/source/temp.R

@@ -0,0 +1,33 @@
+x <- rnorm(100, sd =0.5)
+mean(x, na.rm = TRUE)
+setwd("/data/courses/reproduce-research/work/reproduce-research/RepData_PeerAssessment1")
+dat <- read.csv("activity.csv", header=TRUE)
+dat <- transform(dat, date <- factor(date))
+str(dat)
+
+steps.per.day <- tapply(dat$steps, dat$date, sum, na.rm = TRUE)
+str(steps.per.day)
+names(steps.per.day)
+steps.per.day["2012-10-02"]
+steps <- data.frame(steps.per.day, names(steps.per.day))
+hist(steps$steps.per.day, breaks = length(steps.per.day), xlab = " Number of Steps Each Day", main = "Histogram of Steps Taken Each Day")
+mu <- mean(steps.per.day, na.rm = TRUE)
+median <- median(steps.per.day, na.rm = TRUE)
+mu
+median
+
+dat <- transform(dat, interval = ordered(as.numeric(interval)))
+str(dat)
+avg.steps.per.interval <- tapply(dat$steps, dat$interval, mean, na.rm = TRUE)
+head(avg.steps.per.interval)
+names(avg.steps.per.interval)
+avg.steps <- data.frame(steps = avg.steps.per.interval, interval = as.numeric(names(avg.steps.per.interval)))
+plot(x = avg.steps$interval, y = avg.steps$steps, type = "l", xlab = "Interval", ylab = "Steps", main = "Average Steps per Interval")
+
+avg.steps[which.max(avg.steps$steps), 2]
+
+foo <- function(x = 1, y = 2) c(x, y)
+bar <- function(n, x) replicate(n, foo(x = x))
+bar(5, x = 3)
+x <- list(a = 1:10, beta = exp(-3:3), logic = c(TRUE,FALSE,FALSE,TRUE))
+x