The graphic above depicts a general overview of the colour combinations I wore during the month. The first row is for days 1-8, the second row for days 9-16, then days 17-24, and lastly, days 25-31.
Not surprisingly, I wear a lot of black. I expected to wear something black every single day (my go-to is a pair of black jeans); however, I didn't wear black at all on March 24. I wear a limited selection of colour, but I do cycle through blues, reds, and pinks quite regularly (a bit more than expected).
I clustered my dataset using R, and plotted them on a graph. The components/dimensions on which my cluster plot was graphed on were based on system-determined similarities. From this plot, 5 trends were observed: blue jeans, a cardigan + tee combo, monochromatic + belted combo, plaid button-down days, and other combinations.
I calculated a few regression models to observe the predicability of certain outfits or trends:
I plotted a scatter plot to visualize the types of belts I wore with the types of outfits (I used all-black as a baseline to compare to). As it turned out, black stuck to black (or no belt), and everything else was relatively fair game.