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Ok but on that site you can't search by lyrics. Only by title.

Interesting. How would you rewrite the first sentence to sound positive?

Well my problem isn't with the writing in its original form, it's with the downvoting in response to it. I am fine with someone bringing bad news if it's helpful info.

Me too. I meant "How could the first sentence be rewritten to sound positive/ not attract downvotes?"

Yes it's a very broad global average. Advertisers pay much more for North American users, then European users.

And the ones they want to reach the most are the same ones willing to pay for a subscription to remove ads.

Source cited by @chriso-wiki.bsky.social is this article on DR.dk, the Danish public broadcaster:

https://www.dr.dk/nyheder/indland/groenland/danmark-forbered...


Because “ID columns” and “value columns” (or "pivot") are dry statistician jargon, as opposed to terms like "wide-to-long" , and most of your users won't be MS in statistics or economics. So like you do, just visually separate the columns into "columns used to identify the data" , e.g. Year-WkOfYear-Store-Department, and "value columns". (Posting a few screenshots for illustration would be really good).

> The harder part has been defaults. If the dataset has clear patterns, like columns named month_1 to month_26, it’s easy to guess what should be treated as values. But when naming is inconsistent, the guesses are often off.

Well, you'll probably need to iterate with user assistance via your UI, but you can often eliminate a lot by filtering on the inferred data type (float/integer/date/categorical/string/etc.), permitted range of values (e.g. 'Sales' is probably a positive float or integer), units, formatting, assume related columns tend to be (fairly) contiguous, etc.

Post us a corner case or two. It helps if you tell us what domains your data typically comes from.


If you rewrote it to be less trollish, it would be reasonable comment. Also, less blatant sales pitch on the URLs.


Sampling 50/50 choices would be a binary distribution that (very crudely) approximates a normal distribution.

But the counterintuitive thing about the CLT is that it applies to distributions that are not normal.


This reminds me of having the reverse experience with the 2017 New Yorker viral "Cat Person" story [0] which a (usually trustworthy) friend forwarded and enthusiastically told me to read: waste of time shaggy-dog story, intentional engagement-trolling aimed at the intersection of the hot-button topics of its target readership *. But why are we culturally expected to allow more slack to a human author, even a meretricious one? Both are comparably bad. The LLM-authored one needs a disclaimer at the top to set its readers' expectations right, then readers can make an informed choice.

(* "Cat Person" honestly felt like the literary equivalent of Rickrolling; I would have stopped reading it after the first page if not for my friend's glowing endorsement.)

https://news.ycombinator.com/item?id=27778689


(Sorry, the correct link for Roupenian's 2017 story "Cat Person" is at https://news.ycombinator.com/item?id=15892630 )

Oh god, that was insipid.

It had a very similar quality to the AI'd article from this thread. A sort of attempt at Being Literary but never really ever getting to the point of saying anything. It has the same feeling of wallowing, of over indulging in its shtick.


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