A summary of your data collection, analysis and visualization methods, including the why you chose your methods, and what tools you utilized.
1.How many steps do I take every day? How has it changed?
2.How much time do I spend on my phone everyday?
3.How often do I pick up my phone everyday?
4.What is my sleep pattern like, i.e. sleep duration and quality
5.How are the relationships between my sleep duration, sleep quality, steps I took, phone usage?
Steps data are from iphone app “Health”. It was hard to get easily-formatted steps data directly, so I downloaded the data from “Gyroscope”“, connected to multiple self-tracking apps. The data was formated in csv with only three columns, date, steps, device (which is HealthKit, because it’s where Gyroscope got data from). Health has been tracking my steps since a long time ago, but I only used three months worth of data to visualize: May, June, July.
Phone usage data came from an app called “Moment”. It monitors how many times I pick up the phone. It also asks me to take a screenshot of the battery usage in iphone “Setting” every week to get more accurate data on what apps I spent on and how much time spent. I started using the app from July 05, 2018. The original data for download was in json, and I transformed it into csv file.
For sleep data, I used an app called “Sleep Cycle”. I hit start before going to sleep, and stop when getting up the next morning to tracks the time slept. And the app tracks the sleep quality through microphone. I collected data from July 12, 2018 to August 2, 2018. I downloaded the data directly in csv format.
1.To show the trend in steps taken overtime I used a line chart.
2.&3.Similarly I used line charts for phone usage overtime, minutes on the phone and number of pickups. To show the difference between different days of the week I used boxplot, which is a good aggregated picture.
4.I used scatter plots to show the overall picture of how long I slept, when I went to bed. And I used Ridge line chart to show the difference in sleep duration and sleep quality between different days of the week.