Sees it is differences like: 'Cream cheese crust apple pie' vs 'No crust zucchini pie'. But because I could only label the cluster with common words in the recipe title it couldn't find common enough words

Looks like a map from some fantasy universe.

What's up with so many of the different-colored groupings having identical labels (e.g. the five adjacent clusters that are each labeled "crust pie"?)

I don't know how to even approach consideration of this curiosity. It is intriguing in its layout, and yet indescribably baffling. Did the author intend any structure? Is there meaning in the clusters and islands? The work intrigues, but leaves the viewer hopelessly lost in the depths of its mystery.

I'm just enjoying commenting at this point. I am actually interested in the full essay that would enlighten us about exactly how this chart can be interpreted.

Edit: Also, I disagree with the insinuation that a viewer has any obligation to help with the presentation of the data. We have awarded feedback, and with that, you may make a choice: Will you try again and improve the work, portraying the glory of excitement that you've felt upon pondering the mystery you've sought to dispel? Or will you leave the viewership to ponder the mystery of the graphic they see before them, and the origin of the authorship which led to its creation? It is up to you, and you have no real obligation to choose the former option. The only difference you will see is in your Reddit point count, which you may or may not see as consequential, but which absolutely is inconsequential in the grand scheme of life.

lmao data is indeed beautiful. It really started right after the Copa win and carried us to the World cup.

What was the methodology used to determine which circle a movie would fall into?

Ahh, you're not trying to help , you are just opinionated

Even with that, it would seem to have the level and quality of meaning I could attribute to any given audio track on Autechre's album, "Draft 7.30".

Interesting how most of the movies in the she category have female protagonists or showcase a female in a more prominent role. Similar sentiment on the He category with the exception of Halloween 1978.

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As a guy, apparently my movie tastes are significantly more she than he or xe.

Edit: typo

HHmm, I may need to add more backstory. Like "Euclidean distance represents ingredient similarities"

A network graph using something like graphviz might be a better method. The problem is, the result represents a snapshot in time. So you'd likely have to animate it or otherwise make it interactive with a timeline slider.

I'm interested in those 418 after the World Cup. Were people afraid of it being taken away? Or were these unrelated to the WC and just caught by the method being used?

This is incomprehensible in its current form. It doesn't seem to link anything to anything else in any way that makes sense. I am utterly baffled trying to decipher it.

Can we get homicide rates vs gun ownership rates?

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I dropped a pin in Colorado and learned there’s a place along the Green River named Molly’s Nipple.

Took me down a rabbit hole where I learned an early pioneer to Utah named seven peaks, one butte, a well, a lake, and a ranch Molly’s Nipple to commemorate his wife’s nipples.

That’s a lot of nipples! This is the kind of stuff they should be teaching in geography.

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This took way more NLP than I anticipated.

Recipes that have similar ingredients are closer together. The idea was the take 3700 different recipes for pie, but understand how much variation there is in terms of their ingredients. So the algorithm will cluster recipes that have very similar ingredients and give them one color, and place the cluster in such a manner that clusters with very different ingredients are far away from each other.

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Tools: NLTK, UMAP, HDBSCAN

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e.g. Sugar dimension represents-> ['brown sugar', 'light brown sugar', 'cinnamon sugar', 'white sugar', 'powdered sugar']

BPC fire in saint basile le grand, right next to montreal in 1988 was much much worse lol.

Every step is to add salt and pepper! And sometimes you had salt and pepper twice in a step. Step 1: add salt and pepper step 2: salt and pepper your salt and pepper.

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We got a lemon zester for a present and it sat in a drawer for 25 years until we started getting Hello Fresh / Good Food / Chef's Plate.

Now we joke about shaving lemons and cuddling the chicken (pat chicken dry with a paper towel then yadda yadda...)

Anything similar for driving trip from say google maps?