Quantified Self Overview

Introduction

The Quantified Self (QS) is a movement motivated to leverage the synergy of wearables, analytics, and “Big Data”. This movement exploits the ease and convenience of data acquisition through the internet of things (IoT) to feed the growing obsession of personal informatics and quotidian data. The website http://quantifiedself.com/ is a great place to start to understand more about the QS movement.

The value of the QS for our class is that its core mandate is to visualize and generate questions and insights about a topic that is of immense importance to most people - themselves. It also produces a wealth of data in a variety of forms. Therefore, designing this project around the QS movement makes perfect sense because it offers you the opportunity to be both the data and question provider, the data analyst, the vis designer, and the end user. This means you will be in the unique position of being capable of providing feedback and direction at all points along the data visualization/analysis life cycle.

In this project, I analyzed the accumulated FitBit Data from October to November Looking at steps everday

The motivation behind collecting this specific data was that I had recently purchased a FitBit Charge 2 and had tried to have a record of my daily life such as how many steps I had, do I have enough activities. While it was nice knowing I was getting exercise I wanted to dig into the data and view the trends, correlations and accuracy of the FitBit data.

The data was downloaded from FitBit.com and accumulated in a csv which was downloaded into R.

Through analysis, I hope to evaluate the next 5 questions:

How many steps I have everyday ?

Average Number Steps per Day by Interval, the automatic record frequcy?

After impute some of the abnormal records what can I get?

Are there differences in activity patterns between weekdays and weekends?

Total Steps I had for 2 months?

Data Approaching:

Graph 1 : Total Steps Each Day

I sum the steps to see how many steps I have everday and create a histogram to genenerat the freqency for the total steps I have each day.

Graph 2 : Average Number of Steps per Day by Interval

Generate a graph to show the steps by interval

Graph 3 : Total Steps Each Day

Due to some data are missing so I do the imputation on my daily data. The missing values were imputed by inserting the average for each interval.

Graph 4 : Average Number of Steps per Day by Interval

Created a plot to compare and contrast number of steps between the week and weekend. There is a higher peak earlier on weekdays, and more overall activity on weekends.

Total Steps Each Day

Average Number of Steps per Day by Interval

Total Steps Each Day

Average Number of Steps per Day by Interval