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Film music stats!: Sexism in the film industry?


indy4

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Hi all,

I'm learning a new statistical programming software, and one of the ways I'm learning it is just by finding data that interests me and making pretty pictures with it, just for fun. I figure whenever they concern film/film music type stuff, I'll post them here!

The first one is a graph of the gross of the films that win Best Score at the Oscars, over time. Interestingly, the number of films that win both Best Score and Best Picture are not as high as I suspected (less than 15% since 1970). Outliers (those that earned more than 500 million domestically) are labeled.

The second one graphs the award amount and composition of EGOTers (winners of an Emmy, Grammy, Oscar and Tony), and puts JW up against them to see how he stacks up.

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Oh no, indy4 has joined the bean counters! The horror, the horror.

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Interesting information, but the second graph speaks overwhelmingly to a point I've been making for years: that no matter how great a composer JW seems to be, he continues to underperform at the Tonys.

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I really dont see the point of your second graph though.

It's John Williams pitted against a bunch of other people who are also in the entertainment industry. Hamlish, sure. But Gielgud?

The point is to teach myself the statistical programming software...not all of the graphs are going to be important (especially not the ones I post on jwfAn) but to me they are somewhat interesting :)

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Why is ROTK so low on the gross graph? It's bullshit!

It looks like Indy took US grosses adjusted for inflation. Worldwide without adjustments, it would be a lot higher.

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Yup. I wanted to do worldwide, but I figured that would be a bit misleading since a) the Oscars are generally US-focused, b) can't adjust for inflation worldwide, which makes it impossible to look for trends over time and c) worldwide grosses are subject to the censorship from changing political regimes, while the US has been pretty consistent (at least since the 70s) in regards to censorship, etc.

But even with inflation adjustment, is it really that low? I find that doubtful.

Mind you, it was only labeled because it was an outlier....meaning it grossed significantly more than most films. It grossed 377 million in 2003 dollars, and 510 million in 2015 dollars

http://boxofficemojo.com/movies/?id=returnoftheking.htm&adjust_yr=2015&p=.htm

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I'm learning a new statistical programming software, and one of the ways I'm learning it is just by finding data that interests me and making pretty pictures with it, just for fun. .

I recently saw this and was impressed. You might be interested. Worth a look...

Out of curiosity, what is the statistical programming software you are using?

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That is awesome. I saw it somewhere a few years ago but actually forgot about it. Thanks for sharing! I'm using R...do you code?

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I'm learning a new statistical programming software, and one of the ways I'm learning it is just by finding data that interests me and making pretty pictures with it, just for fun. .

I recently saw this and was impressed. You might be interested. Worth a look...

Out of curiosity, what is the statistical programming software you are using?

That chart color scheme shouts R.

I'm using R...do you code?

Derp. I need to read posts more carefully.

Cool analysis! How'd you end up in the world of statistical programming?

Also, if you're just getting into the world of statistics I *strongly* *strongly* *strongly* recommend this book:

http://www.amazon.com/Statistical-Models-Practice-David-Freedman/dp/0521743850

It's highly readable but full of great insights into the modeling process and how not to go about it. It's not prescriptive, it doesn't tell you what to do (because there's no one right answer), but it helps you learn what to avoid.

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That is awesome. I saw it somewhere a few years ago but actually forgot about it. Thanks for sharing! I'm using R...do you code?

Yeah, .NET and Java mostly. But I've recently started a data science Udacity course through work which includes Hadoop, MapReduce and R. I'm looking forward to it.

Data Visualisation is very interesting to me. There is some very satisfying about taking raw data and displaying it in a nice user friendly graphic.

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I'm learning a new statistical programming software, and one of the ways I'm learning it is just by finding data that interests me and making pretty pictures with it, just for fun. .

I recently saw this and was impressed. You might be interested. Worth a look...

Out of curiosity, what is the statistical programming software you are using?

That chart color scheme shouts R.

I'm using R...do you code?

Derp. I need to read posts more carefully.

Cool analysis! How'd you end up in the world of statistical programming?

Also, if you're just getting into the world of statistics I *strongly* *strongly* *strongly* recommend this book:

http://www.amazon.com/Statistical-Models-Practice-David-Freedman/dp/0521743850

It's highly readable but full of great insights into the modeling process and how not to go about it. It's not prescriptive, it doesn't tell you what to do (because there's no one right answer), but it helps you learn what to avoid.

Thanks for the recommendation! I'll check it out. I got into this world by taking a few classes on R, but want to hone my skills beyond what we learn there

That is awesome. I saw it somewhere a few years ago but actually forgot about it. Thanks for sharing! I'm using R...do you code?

Yeah, .NET and Java mostly. But I've recently started a data science Udacity course through work which includes Hadoop, MapReduce and R. I'm looking forward to it.

Data Visualisation is very interesting to me. There is some very satisfying about taking raw data and displaying it in a nice user friendly graphic.

Totally agree. Making pretty pictures out of a mess of numbers is extremely satisfying

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But even with inflation adjustment, is it really that low? I find that doubtful.

It made a killing worldwide, but it actually wasn't a record-breaker in the US...still a blockbuster, obviously, but it's not even in the top 5 of the 2000s. Those would be Avatar, The Dark Knight, Shrek 2, Spider-Man, and Pirates of the Caribbean: Dead Man's Chest. The Avengers is also higher even after the inflation adjustments: http://boxofficemojo.com/alltime/adjusted.htm

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  • 2 weeks later...

Hi all,

I was curious about the oft-made claim that superficial qualities like looks are weighted more heavily for female actresses than male actors. As Amy Poehler said at the Oscars this year, "Boyhood proves that there are still great roles for women over 40, as long as you get hired when you're under 40."

To examine the extent to which these accusations are true, I examined the age of the winners for Best Actor, Best Supporting Actor, Best Actress, and Best Supporting Actress and graphed the results.

The first graph suggests that there is indeed a disparity. The average age of a Best Actress/BSA winner is 37.9, while the average age of the Best Actor/BSA is 46.6.

The second graph separates out the 4 different awards being examined. You can see that supporting actors are typically older than the leads, suggesting again that Hollywood may place considerable value in having a lead that is youthful. The average age of the winning supporter was 44.8, vs 40 for the lead.

Interestingly, this disparity is greater for males than females. Male supporters were on average 6.1 years older than the leads, while female supporters were on average 3.8 years older.

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Would be a fascinating set of data to play around with. Right now my biggest limitation is data--as far as I know, nobody has ever compiled this stuff together in one neat dataset before, which means I have to input these data manually to an excel spreadsheet before reading it into R. With something like age and gender it's relatively quick--I can just paste the year somebody was born into the spreadsheet, and the gender segregated categories makes it easy to assign genders to the winners (even if it presents an oversimplified view of gender). But for something like race, it would be quite tedious given the less clear cut definitions of racial groups and myriad of ways to categorize people racially. I can't necessarily just go to somebody's wiki page to get a good idea of their race, while I can absolutely do that to determine their age.

But if you already have these data, I would love to play around with them! :)

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We all know what's going on anyway, but gender and race statistics are interesting nonetheless.

I'm quite happy about the presence of John Boyega and Gwendoline Christie in Star Wars.

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Would be a fascinating set of data to play around with. Right now my biggest limitation is data--as far as I know, nobody has ever compiled this stuff together in one neat dataset before, which means I have to input these data manually to an excel spreadsheet before reading it into R. With something like age and gender it's relatively quick--I can just paste the year somebody was born into the spreadsheet, and the gender segregated categories makes it easy to assign genders to the winners (even if it presents an oversimplified view of gender). But for something like race, it would be quite tedious given the less clear cut definitions of racial groups and myriad of ways to categorize people racially. I can't necessarily just go to somebody's wiki page to get a good idea of their race, while I can absolutely do that to determine their age.

But if you already have these data, I would love to play around with them! :)

Manually?!

Time to learn some Python and scrape the web it sounds like! It's easier than you think!

Or actually Google Sheets also has some fairly useful web scraping capabilities that can populate cells automatically saving a lot of time!

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