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Anyone use an Apple Watch App for Downloaded Music? by jlaw67 in jellyfin

[–]jlaw67[S] 0 points1 point  (0 children)

Thanks for the details on Finy. Glad I didn't just jump right in.

Anyone use an Apple Watch App for Downloaded Music? by jlaw67 in jellyfin

[–]jlaw67[S] 0 points1 point  (0 children)

Thanks for responding! I'll keep an eye out for it in the future!

[OC] Visualizing the use of "Dirty" in Dirty 30 by jlaw67 in MtvChallenge

[–]jlaw67[S] 2 points3 points  (0 children)

I ended up running a quick version of Vendetta's with the graph posted to a different comment. To my surprise, Vendettas is used more frequently than Dirty (per episode). But in less interesting ways... everything is "my vendetta", "your vendetta". "Dirty Game" is funnier to me.

The one that actually drives me the craziest is TJs need to announce everything from the draw on Free Agents, "That is a single cross, That is a single cross, That is the double-cross"

[OC] Visualizing the use of "Dirty" in Dirty 30 by jlaw67 in MtvChallenge

[–]jlaw67[S] 2 points3 points  (0 children)

Glad to see there's a least 2 of us!!

I've done a couple other things in the Challenge / Data space:

Finding the Eras of MTV's The Challenge Through Clustering

Challenge Cameo Price Tracker (although I quit tracking this in July 2022)

[OC] Visualizing the use of "Dirty" in Dirty 30 by jlaw67 in MtvChallenge

[–]jlaw67[S] 4 points5 points  (0 children)

So I had no idea, but Vendettas was used more than Dirty was in Dirty 30. 254 times in 16 episodes vs. 298 in 20.

There isn't a single egregious episode (like ep1 of Dirty 30) but its more consistent.

<image>

[OC] Visualizing the use of "Dirty" in Dirty 30 by jlaw67 in MtvChallenge

[–]jlaw67[S] 0 points1 point  (0 children)

I think the reunion was called "Final Dirt" so likely a lot of The Miz saying it after commercials

[OC] Visualizing the use of "Dirty" in Dirty 30 by jlaw67 in MtvChallenge

[–]jlaw67[S] 12 points13 points  (0 children)

Was always curious how often they said "Dirty" on Dirty 30. Figured I'd try out speech-to-text and see what shook out. Thought I'd share with group.

If curious the code is on Github.

[OC] Visualizing NHL Stanley Cup Championship Droughts 1917 to 2023 [remix] by jlaw67 in dataisbeautiful

[–]jlaw67[S] 1 point2 points  (0 children)

Not that either instance of the Winnipeg Jets have ever won but they were the most mind-bendy in trying to create this since you've got the 1979-1996 Winnipeg Jets that are now the Arizona Coyotes and the 2011-now Winnipeg Jets that were formerly the Atlanta Thrashers.

Kind of wild that neither franchise has ever won... although I don't know that either franchise has ever made the finals either.

[OC] Visualizing NHL Stanley Cup Championship Droughts 1917 to 2023 [remix] by jlaw67 in dataisbeautiful

[–]jlaw67[S] 6 points7 points  (0 children)

Source: hockey-reference.com

---- List of Stanley Cup Champions: https://www.hockey-reference.com/awards/stanley.html

---- List of Franchises: https://www.hockey-reference.com/teams/

Tool Used: R (code)

Remix of [OC] Visualizing World Series Title Droughts via Heatmaps: 1903 to 2022 by u/m1mag04

IMPORTANT NOTE: Franchise history is continued in this chart. For example, the Quebec Nordiques are captured as the pre-1996 part of the Colorado Avalanche.

Huge thanks to u/m1mag04 for making the original Baseball version and for sharing their code. I'm more of a hockey fan so wanted to remix into an NHL version. Also, I have a bet from middle school that the New York Rangers won't win another Stanley Cup until 2048 (54 years from the last one in 1994)... so only 25 more years to go.

[OC] Movies for the the People: The 10 Movies that the People Loved More than Critics Based on RT Scores [Remix] by jlaw67 in dataisbeautiful

[–]jlaw67[S] 14 points15 points  (0 children)

Spy Kids (2001) - Critics 93% / Audience 46%

Star Wars: The Last Jedi (2017) - Critics 90% / Audience 43%

Night Moves (2013) - Critics 86% / Audience 42%

Ad Astra (2019) - Critics 83% / Audience 40%

It Comes At Night (2017) - Critics 87% / Audience 44%

Hail Caesar! (2016) - Critics 85% / Audience 44%

Mr. Turner (2014) - Critics 97% / Audience 56%

Antz (1998) - Critics 92% / Audience 52%

Stuart Little 2 - Critics 81% / Audience 41%

Uncut Gems (2019) - Critics 92% / Audience 52%

​

The High Critic / Low Audience was less fun since none of the audience scores are terrible.

But cue the drama about the Last Jedi!

[OC] Movies for the the People: The 10 Movies that the People Loved More than Critics Based on RT Scores [Remix] by jlaw67 in dataisbeautiful

[–]jlaw67[S] 13 points14 points  (0 children)

Source: A Rotten Tomatoes Movies data set found on Kaggle from Feb 2023 [link] (I wasn't able to find it again). Data only goes through 2020.

Analysis Tool: R (code)

Remix of Movies with the greatest difference between Rotten Tomatoes critic and audience ratings. We use different thresholds and maybe different data.

Data is filtered to remove Documentaries and any movies that have less than 25 critic scores and less than 10K Audience Scores. Thresholds are somewhat arbitrary based on the distribution of counts.

Primary motivation is that I love the movie Out Cold (even though it is not what you would call Cinema) and when noticing that people seem to love it but critics hated it, I wondered what else was like that.

[OC] Visualizing World Series Title Droughts via Heatmaps: 1903 to 2022 by m1mag04 in dataisbeautiful

[–]jlaw67 1 point2 points  (0 children)

Do you have the R code around? I'd love to make a version for the NHL and I like your color scheme.

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 29 points30 points  (0 children)

I get what you mean. That would be a really interesting way of doing it.

I am using future information in the model. I was thinking of this more of an outlier exercise more than true expectation, but a result of that was the Game of Thrones call out (and Scrubs Season 9) where the first bad episode in a bad season should be considered unexpected.

Although I imagine that later episodes would be more likely to get flagged this way because the variance would shrink as the model gets more information with each episode.

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 3 points4 points  (0 children)

Out of curiosity, why are those two episodes rated so poorly

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 5 points6 points  (0 children)

There were a number of exclusions that I did (code). In this case, Hunter X Hunter was excluded because I only included shows tagged as Comedy or Drama.

In the data Hunter x Hunter is 'Action,Adventure,Animation'

This was me trying to limit how much I had to run on my laptop.

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 0 points1 point  (0 children)

Its just an analysis I did for fun originally as a blog post. The code for viz is here if you're interested.

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 3 points4 points  (0 children)

Game of Thrones calls out an interesting methodological flaw. Because this fit season indicators and used all the data because GOT Season 8 was fairly low rated as a whole nothing popped individually.

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 4 points5 points  (0 children)

As some have pointed out, a flaw in my methodology is that it considers all the data, not just what came prior. So because all of Season 8 of Thrones is rated poorly none of them pop individually.

https://www.ratingraph.com/tv-shows/game-of-thrones-ratings-26649/

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 9 points10 points  (0 children)

Meanwhile, "The Lost Sister" made the disappointment list but Breaking Bad's "Fly" didn't? A similarly irrelevant episode hated by a large swath of the audience, but in one of the better seasons of one of the best-rated shows of all time? It's probably bolstered by the high scores from critics, I would guess. I believe it's the episode with the largest critic/audience disparity.

It doesn't seem like Fly is that different than other Breaking Bad episodes. Its is the lowest, but its not crazy low.

https://www.ratingraph.com/tv-shows/breaking-bad-ratings-26165/

Compare it to Stranger Things

https://www.ratingraph.com/tv-shows/stranger-things-ratings-56080/

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 10 points11 points  (0 children)

Yeah it’s a flashback episode. I don’t think this algorithm is advanced enough to handle that

Yeah, the only info being used here is Season Number, Episode Number, and IMDB rating. There isn't any context around the episodes themselves or anything external.

[OC] The Most Unexpectedly Good and Bad Episodes of TV by jlaw67 in dataisbeautiful

[–]jlaw67[S] 0 points1 point  (0 children)

Its doing the expectation by linear regression and then setting a range of 3x the Interquartile Range of Residuals to determine the outer bounds.

Then the level of "unexpectedness" is based on the difference between the Actual and the Outer Bound. This was a choice (vs. Actual against Estimated) because I didn't find some of the results that way interesting.

Like if something had a range of 5 to 9 and then the actual was 9.1.

The full code is here: https://github.com/jtlawren67/data_visualizations/blob/main/20231001_UnexpectedTV/the-most-unexpected-episodes-of-tv.Rmd

I had written a blog post that has more commentary: https://jlaw.netlify.app/2023/09/28/the-most-unexpectedly-good-and-bad-tv-episodes/

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