View the online visualization here.
Design Statement
The topic that I chose to use for this semesters personal data project was to compare my mood rank to the outside temperature at the time that I left my house in the morning. I Thought that this information would be interesting to look at and compare because something that I figured was that, as the temperatures decreased over time, my overall mood would be consistent with this decrease. I figured this data would have a correlation because personally I do not like when the weather drops because of things that tend to happen in the cold. People start to get sick, icy conditions cause traffic problems as well as much a lot of snow. A significant event that happened it when on the first school snow day, I fell and messed up my wrist and cracked my phone screen. So, from this I automatically knew that when the weather dropped, my mood would most likely drop right along with it. I collected my data by making a table, and each day I would wake up, I would record the temperature and my mood along with the week (1-10) and the day (Mon-Fri). On certain days I would also add a little note explaining the reasoning for some of the days that seen a significant drop in mood.
For this project, I chose a couple different types of chart forms to get my point across to the audience. The first chart form I used was a lien chart and I did this for both the chart comparing my mood rank and the day, as well as the day and the temperature. I made the decision to use this type of chart because this project covered the span of a 10-week period of time. Line charts are commonly known for being being the best choice when attempting to show changes in continuous data over time which I believe it did a great job of in this case. Also, line charts emphasize increases and decreases which really helped to point out trends in data especially around the period in week 5 where I got sick. The line plots accurately showed the dip in the temperatures compared to the accurate measurement in my mood which was because of that temperature drop. I chose the color of blue to represent a lot of the charts because the color blue represents cold which was how things felt when the temperature began to really drop. I used the color Orange to show how Saturdays had the highest average because that was a color that really stood out. The data that was most interesting was the graph that showed the day of the week and the averages for that day through 10-weeks. This was interesting because the averages really made sense with the says they aligned up with.
What I learned from doing this project was that, next time if I am going to do a project like this, maybe I need to be a little more specific with the way I record the data. Maybe just saying my mood compared to the temperature outside wasn’t enough. I believe this because over time, I started to notice that maybe the weather actually isn’t the major determining factor when it comes to what my mood for that day actually is. Other factors to take into account were things like me getting sick; having a visitor for the weekend; if I woke up late or not for that day; or things like if I completed all the required homework that was due for that specific day. I really didn’t start to notice something so obvious as this until I was about a few weeks in to recording the personal data. What I learned from the data was that a lot of times, the cold weather really did not have much to do with my overall mood. For example, on November 11th, the temperature when I left my apartment was 27 degrees Fahrenheit, but my actual mood for that day was a high 8 out of 10. I did encounter a surprise when a couple days during week 9 where I noticed an increase from the 30s to the 50s in the early morning temperature. These days were consistent with the overall mood trend because during week 9, these two days is where I recorded a better mood ranking for that week. If I were continuing this project, I would probably change the time I record my mood and temperature. What I would do is actually record the highest temperature for that day and then record the mood at the end of the day to get a more accurate rating of how I felt the entire day rather than the morning I woke up. I believe I answered all the intended questions that I set out to answer.