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.

The data for this assignment can be downloaded from the course web site:

Dataset: 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

Loading and preprocessing the data

Read the dataset

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

Convert date column to Date type

data$date <- as.Date(data$date)

display the structure of the data

str(data)

## 'data.frame':    17568 obs. of  3 variables:
##  $ steps   : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ date    : Date, format: "2012-10-01" "2012-10-01" ...
##  $ interval: int  0 5 10 15 20 25 30 35 40 45 ...

What is mean total number of steps taken per day?

Calculate the total number of steps taken per day

library(dplyr)
# Remove NA values
clean_data <- data %>% filter(!is.na(steps))
# Calculate total number of steps per day
daily_steps <- clean_data %>%
  group_by(date) %>%
  summarise(total = sum(steps))

Histogram of the total number of steps taken each day

hist(daily_steps$total, main = "Total Steps Per Day", xlab = "Steps", col = "lightblue", breaks = 20)

Mean and median number of steps taken each day

mean_steps <- mean(daily_steps$total)
median_steps <- median(daily_steps$total)

mean_steps

## [1] 10766.19

median_steps

## [1] 10765

What is the average daily activity pattern?

Calculate average steps per 5-minute interval

interval_avg <- clean_data %>%
  group_by(interval) %>%
  summarise(avg_steps = mean(steps))

Time series plot of average steps across intervals

plot(interval_avg$interval, interval_avg$avg_steps, type = "l",
     xlab = "5-Minute Interval", ylab = "Average Number of Steps",
     main = "Average Daily Activity Pattern")

Find the 5-minute interval with maximum average steps

max_interval <- interval_avg[which.max(interval_avg$avg_steps), "interval"]
max_interval

## # A tibble: 1 × 1
##   interval
##      <int>
## 1      835

Imputing missing values

Calculate the total number of missing values

sum(is.na(data$steps))

## [1] 2304

Replace NAs with the mean for that 5-minute interval

imputed_data <- data %>%
  left_join(interval_avg, by = "interval") %>%
  mutate(steps = ifelse(is.na(steps), avg_steps, steps)) %>%
  select(steps, date, interval)

Recalculate total steps per day with imputed data

daily_imputed <- imputed_data %>%
  group_by(date) %>%
  summarise(total = sum(steps))

Plot histogram of total steps per day after imputation

hist(daily_imputed$total, main = "Imputed: Total Steps Per Day", xlab = "Steps", col = "lightgreen", breaks = 20)

The new mean and median total number of steps taken per day

mean_imputed <- mean(daily_imputed$total)
median_imputed <- median(daily_imputed$total)

mean_imputed

## [1] 10766.19

median_imputed

## [1] 10766.19

Are there differences in activity patterns between weekdays and weekends?

Add a factor variable indicating weekday or weekend

imputed_data <- imputed_data %>%
  mutate(weekday = weekdays(date),
         day_type = ifelse(weekday %in% c("Saturday", "Sunday"), "weekend", "weekday")) %>%
  group_by(interval, day_type)

Calculate average steps by interval and day type

interval_by_day <- imputed_data %>%
  group_by(interval, day_type) %>%
  summarise(avg_steps = mean(steps))

## `summarise()` has grouped output by 'interval'. You can override using the
## `.groups` argument.

Panel plot comparing weekday and weekend activity patterns

library(lattice)
xyplot(avg_steps ~ interval | day_type, data = interval_by_day,
       layout = c(1, 2), type = "l", xlab = "Interval", ylab = "Number of Steps")

Reproducible Research: Peer Assessment 1