PA1 Coursera Data Science, Reproducible Research, June 2015

roberto aviles

Peer Assesment Project 1

Coursera Data Science: Reproducible Research --- June 2015

Introduction

This assignment makes use of data from a personal activity monitoring device. This device collects data at 5 minute intervals through out the day. The data consists of two months of data from an anonymous individual collected during the months of October and November, 2012 and include the number of steps taken in 5 minute intervals each day.

Data

The data for this assignment can be downloaded from the course web site: Activity monitoring data [52K]

The variables included in this dataset are:

steps: Number of steps taking in a 5-minute interval (missing values are coded as NA)
date: The date on which the measurement was taken in YYYY-MM-DD format
interval: Identifier for the 5-minute interval in which measurement was taken

Slide 2

The dataset is stored in a comma-separated-value (CSV) file and contains a total of 17,568 observations.

  1. Firstly, we load and preprocess the data. My activity.zip file is right at the working directory along with the PA1_template.Rmd and other stuff
library(ggplot2)
act <- read.csv(unzip("repdata-data-activity.zip"))

## Warning in unzip("repdata-data-activity.zip"): error 1 in extracting from
## zip file

## Error in file(file, "rt"): invalid 'description' argument
  1. Format dates to the appropiate type
act$date <- as.Date(act$date , format = "%Y-%m-%d")

## Error in as.Date(act$date, format = "%Y-%m-%d"): object 'act' not found

--- .class #3

Slide 3

  1. From the original data, create and name the columns steps, day and interval
act.day <- aggregate(act$steps, by=list(act$date), sum)

## Error in aggregate(act$steps, by = list(act$date), sum): object 'act' not found

act.interval <- aggregate(act$steps, by=list(act$interval), sum)

## Error in aggregate(act$steps, by = list(act$interval), sum): object 'act' not found

names(act.day)[2] <- "steps"

## Error in names(act.day)[2] <- "steps": object 'act.day' not found

names(act.day)[1] <- "date"

## Error in names(act.day)[1] <- "date": object 'act.day' not found

names(act.interval)[2] <- "steps"

## Error in names(act.interval)[2] <- "steps": object 'act.interval' not found

names(act.interval)[1] <- "interval"

## Error in names(act.interval)[1] <- "interval": object 'act.interval' not found
  1. Now, to the orginal data, we'll aggregate and name a column with the mean number of steps per interval
act.m.interval <- aggregate(act$steps, by=list(act$interval), mean, na.rm=TRUE, na.action=NULL)

## Error in aggregate(act$steps, by = list(act$interval), mean, na.rm = TRUE, : object 'act' not found

names(act.m.interval)[1] <- "interval"

## Error in names(act.m.interval)[1] <- "interval": object 'act.m.interval' not found

names(act.m.interval)[2] <- "mean.steps"

## Error in names(act.m.interval)[2] <- "mean.steps": object 'act.m.interval' not found

--- .class #id

Slide 4

First Question: ¿What is mean total number of steps taken per day?

We'll calculate both MEAN and MEDIAN:

mean(act.day$steps, na.rm = TRUE)

## Error in mean(act.day$steps, na.rm = TRUE): object 'act.day' not found

median(act.day$steps, na.rm = TRUE )

## Error in median(act.day$steps, na.rm = TRUE): object 'act.day' not found

Note that the summary command shows, also, the number of NA in the set

summary(act.day$steps)

## Error in summary(act.day$steps): object 'act.day' not found
  • And, the requested histogram:*
hist(act.day$steps, col = "lavender", main = "Histogram of Total Number of Steps per Day",
     xlab = "Total Number of Steps per Day")

## Error in hist(act.day$steps, col = "lavender", main = "Histogram of Total Number of Steps per Day", : object 'act.day' not found

Slide 5

Second Question: ¿What is the average daily activity pattern? Specifically:

  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)
  2. Which 5-minute interval, on average across all the days in the dataset, contains the maximum number of steps?

Something slightly different (I do like more circles around dots of data than simple lines)

data <- read.csv("activity.csv")

## Warning in file(file, "rt"): cannot open file 'activity.csv': No such file
## or directory

## Error in file(file, "rt"): cannot open the connection

stepsInInterval<-aggregate(steps~interval, data, mean)

## Error in terms.formula(formula, data = data): 'data' argument is of the wrong type

plot(stepsInInterval$interval, stepsInInterval$steps, type='o', col='blue',main="Average of steps per day", xlab="Interval", ylab="Average of Steps in the Interval")

## Error in plot(stepsInInterval$interval, stepsInInterval$steps, type = "o", : object 'stepsInInterval' not found

--- .class #id

Slide 6

Now we want to find which 5-minute interval,in the dataset, contains the maximum number of steps?
(note the answer points exactly to the sudden peak in previous plot: the 5-minutes interval number 835)

act.m.interval[which.max(act.m.interval$mean.steps), 1]

## Error in eval(expr, envir, enclos): object 'act.m.interval' not found
Now: "The presence of missing days may introduce bias into some calculations or summaries of the data"

Third Question: ¿Are there differences in activity patterns between weekdays and weekends?

Slide 7

¿How many NA values are in the set?

table(is.na(data$steps))

## Error in data$steps: object of type 'closure' is not subsettable

In order to correct this situation, let's merge and replace lost/missed/NA values with the MEAN value for the interval, as given by the 'function' act.m.interval. and then create a 'new' set with NO NA values

act.lost <- merge(act, act.m.interval, by = "interval", sort= FALSE)

## Error in merge(act, act.m.interval, by = "interval", sort = FALSE): object 'act' not found

act.lost$steps[is.na(act.lost$steps)] <- act.lost$mean.steps[is.na(act.lost$steps)]

## Error in eval(expr, envir, enclos): object 'act.lost' not found

act.nona <- act.lost[, c(2,3,1)]

## Error in eval(expr, envir, enclos): object 'act.lost' not found

Before going any further, compare the new and old set of data Create a new dataset with the total steps per day

Slide 8

act.day.new <- aggregate(act.nona$steps, by=list(act.nona$date), sum)

## Error in aggregate(act.nona$steps, by = list(act.nona$date), sum): object 'act.nona' not found

names(act.day.new)[1] <-"day"

## Error in names(act.day.new)[1] <- "day": object 'act.day.new' not found

names(act.day.new)[2] <-"steps"

## Error in names(act.day.new)[2] <- "steps": object 'act.day.new' not found

And now plot the new 'corrected' histogram

hist(act.day.new$steps, col = "blue", main = "Total Number of Steps per Day (*without* NA values)", xlab = "Total Steps")

## Error in hist(act.day.new$steps, col = "blue", main = "Total Number of Steps per Day (*without* NA values)", : object 'act.day.new' not found

Slide 9

By looking histograms is hard to tell a difference; let's compare using the MEAN & MEDIAN:

mean(act.day.new$steps)

## Error in mean(act.day.new$steps): object 'act.day.new' not found

median(act.day.new$steps)

## Error in median(act.day.new$steps): object 'act.day.new' not found

MEAN values with AND without NA data are the same but, the original MEDIAN was slightly smaller than the 'corrected' value

Fourth Question: ¿Are there differences in activity patterns between weekdays and weekends?

Slide 10

First we need to separate our set in 'weekdays' and 'weekend' days.
And then we add a new column with this new datum: wDay (week or weekend day.)

act.nona$wDay <- ifelse(as.POSIXlt(act.nona$date)$wday %in% c(0,6), 'weekend', 'weekday')

## Error in as.POSIXlt(act.nona$date): object 'act.nona' not found

adi <- aggregate(steps ~ interval + wDay, data=act.nona, mean)

## Error in eval(expr, envir, enclos): object 'act.nona' not found

Now it is possible to use, again, a time series plot with 'interval' in the X-axis and
the average number of steps per days@interval in the Y-axis and compare the activity
of weekdays versus weekend days.

ggplot(adi, aes(interval, steps)) + 
    geom_line() + 
    facet_grid(wDay ~ .) +
    xlab("5-minute Interval") + 
    ylab("Average Number of Steps")

## Error in ggplot(adi, aes(interval, steps)): object 'adi' not found