Seit 10 Jahren wiege ich meinen Frühstücks-Burrito am Samstagmorgen. Ich hole mir einen Wurst-Frühstücks-Burrito vom örtlichen Los Favs, nehme ihn mit nach Hause und wiege ihn. Ich habe die Gewichte in Excel aufgezeichnet und damit die Diagramme erstellt. Ich habe die ganze Zeit die gleiche Küchenwaage verwendet.
Von chiefd59
25 Kommentare
For ten years you’ve been eating cold burritos for breakfast on Saturdays? Impressive.
I respect the dedication, that’s a very specific thing to track. I guess the gradual trend downward is your scale losing calibration?
Rather than Los Favs, I highly recommend the burritos from Los Pollos Hermanos. Might get something extra!
To me, the amazing thing is to be in the same place for 10 years of Saturdays. I don’t think I’ve had a full year in my life.
An interesting and novel flavor of autism which I had not yet seen until today. Thanks for sharing, OP
This…this is the ‚tism I enjoy.
I think your data would be more informative with labels on the y-axis for your average weight as well as just plotting your standard deviation there instead of a separate graph
Now this is why I use Reddit.
Same scale for ten years – Have you calibrated it recently? Otherwise the measurements could be off.
Would like to see the cost of the burrito tracked here as well
Do you have something for the price as well ?
Plotting annual average without labeling the [14-16.5oz] y axis makes the change look far larger than it actually is. I’m not generally in favor of non-0-minimum y axes, but *especially* not here where the axis isn’t labeled.
You could combine the top two charts using a bar for each year’s average and error bars for +/- 1 SD. Alternatively, a boxplot per year could be interesting to see potential outliers or skew.
I’ve always said that 2022 was a bad year for burritos, I’m just glad I finally have evidence to back it up.
Now run it through an FFT and find the power spectral density.
This is the kind of beautiful data I am here for.
(Show us the burritos.)
ex-scientist here. While the concerns of the scale calibration are perfectly valid, have you all considered that the real culprit is an external force driving the density of the ingredients to gradually decrease over time?
Perhaps, avocado, rice, beans or meat are steadily becoming less dense over time. This would lead to the burrito place creating a burrito of similar volume, while the actual weight has decreased over time.
Is this the Los Favs in Arizona?
Whats amazing is how the pandemic and post pandemic rebound affected the weight in nearly the opposite way I would have expected
Immediately thought “whoa 10 years, I wonder if there’s a correlation between the weight and the recession in 2008.”
Not even close to 10 years ago.
You’re not pre/post weighing yourself after your post-burrito-shit?!? You’re leaving so much data untracked!!!
Now test for stationarity and fit an ARIMA model.
Also why don’t you combine the mean and stddev graphs into a bunch of boxplots?
How many Saturday mornings did you miss in 10 years?
This is the shit I live for. Entirely useless information being tracked, but it’s so goddamn interesting. Like over 10 years your burrito weighs approximately 10% less, pennies. You did this for the love of the data game
Gotta keep going back for that elusive 20 ouncer
This is the kind of long-term data commitment I respect, equal parts dedication, discipline, and love for burritos.