Activity Monitoring Using Smartphones, Wearables or Any Activity Monitoring Devices

With the rising trends of smartphones and wearables, it is easy for any individuals to collect a large amount of data about their personal activities. In this post, I’m going to explore the data, from the Data Science Specialization from Coursera. This data were collected at 5 minute intervals, througout the day, during month of October and November in 2012.

Quick Peek into the dataset

The dataset contains a lot of missing data in the steps, and the date starts from 2012-10-01 to 2012-11-30. And, the maximum amount of steps within 5 mins is 2355. And, the missing data are in those days where there are nothing recorded in the graph below.

##      steps           date               interval   
##  Min.   :  0    Min.   :2012-10-01   Min.   :   0  
##  1st Qu.:  0    1st Qu.:2012-10-16   1st Qu.: 589  
##  Median :  0    Median :2012-10-31   Median :1178  
##  Mean   : 37    Mean   :2012-10-31   Mean   :1178  
##  3rd Qu.: 12    3rd Qu.:2012-11-15   3rd Qu.:1766  
##  Max.   :806    Max.   :2012-11-30   Max.   :2355  
##  NA's   :2304

Daily Pattern and Activity

Although the individual is not walking consistently the same number of steps everyday, there are about 8 days where he walked around 10,000 steps. The average number of steps he/she is taking per day is around 10766.19.

On average, he/she is taking more steps between 0730h and 1000h, than any other time of the day. And, the number of steps peaks at around 835h.

On average, there are more steps taken in the morning during the weekdays, while there are more steps taken in the afternoon and evening during the weekend.