Tracking 2018 (February) - Food Types

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In February, I tracked my eating habits. The visualization below illustrates the food groups (plus caffeine) that I consumed. I annotated the foods I ate for the month in an Excel sheet, and cleaned the data accordingly to derive sets of analyses from it.



Using R, I clustered my dataset and determined 5 main eating patterns.



February was an interesting month to track because of the change in lifestyle. I went to Vancouver from February 16 - 21, which was when a spike in amount of types of food occurred. This was because as a student, I'm normally limited to the options I have around me regularly, plus how I prefer to cook at home most of the time. I started feeling a bit ill in Vancouver, and looking back at the food choices, I'm not surprised; a normal day for me at school would constitute of "egg, grilled zucchini, baked chicken, popcorn" but Vancouver yielded a lot more variety, from sushi nights to "beer-battered scallops and prawns, fries, takeout noodles".

I chose not to separate my types of protein (animal/plant-based) for my analysis because I don't tend to eat much meat, which is a mild point of concern to my parents. Thus, I wanted to see my normal protein distribution, regardless of the source.

The two most popular snacks in February were Lara bars and cookies. This graph illustrates how many times I would eat cookies/bars a day. Typically, I ate 1 Lara bar at a time, and sometimes 1-2 cookies at a time.

The cookies I ate were only of 4 varieties: chocolate chip, chocolate chip oatmeal, oatmeal, and raspberry oat. There were days where I ate an embarrassingly high amount of cookies, and I totaled 24 times of eating cookies in the entire month.

The Lara bar flavours (I ate a total of 15 during the month) I seemed to really like were: cashew, apple, and chocolate chip peanut butter.

My Lara bar consumption dropped while my cookie consumption continued (and even peaked at one point) mostly due to lack of accessiblity in Vancouver, as well as the cost.

I took the liberty to conduct some statistical analysis on my dataset. In February, I started really liking kimchi omelettes. Given the condition of me eating an egg, I made a regression model that showed that if I ate an egg that day, the likelihood of it being part of a kimchi omelette was 17.58%.

In total, I'd say that monitoring my food intake really made me more aware about how unhealthily I eat. I do try to fill my day with as much fruits/vegetables and protein as possible, but I actually eat a lot of filler carbs and snacks without realizing it. It pains me to admit, but I especially eat an unhealthy amount of cookies.

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