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Project 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.

Project Motivation

I have a background in Finance, by degree and profession. For my course project, I am motivated to analyze the Data I collected on my income and expenses. Being able to balance my expenses and my income is critical to me as a Finance person. In additional to this, I would also like to evaluate data on my physical activities and lifestyle, as I have always liked any form of physical activities and I am aiming to participate in upcoming Marathons. The data on my physical activities will help to check how prepared I am for my Marathons.

Project Questions

  1. What are my expenses by categories?

  2. What are my expenses across months?

  3. What are my monthly and weekly active miles trend?

  4. What are my active energy burned?

  5. What are my heart rate during physical and idle state?

Data Collection

For my spending and expenses, I am leveraging on my credit card statement and banking app. I will be reviewing my monthly spending over the last three years.

For my physical activities; steps, heart rate and walking, I will leverage data from my Apple Watch.

Data Processing & Visualization

All data are downloaded and saved in excel sheets and imported using read_excel function. The dashboard visualization utilize bar charts, line charts and categorized charts like function facet_grid.

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Heart rate during physical and idle state

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Average Walking Steps

Expenses by Categories