Building Custom Data Visualizations

Dataset Solution, Part 2

Shirley Wu

Shirley Wu

Data Sketches
Building Custom Data Visualizations

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The "Dataset Solution, Part 2" Lesson is part of the full, Building Custom Data Visualizations course featured in this preview video. Here's what you'd learn in this lesson:

Shirley records the potential questions from the previous section, and gathers more questions and hypotheses around that dataset that seem interesting.


Transcript from the "Dataset Solution, Part 2" Lesson

>> Shirley Wu: Let's talk about based on some of these things. I think we already have some things we're interested in, so let's kind of together list out the questions. And let's just throw out some questions and then maybe after we throw them out we can like prioritize them in terms of which one to explore first.

And so let's write down some of the ones that have already been talked about. And so I think one of them was comparing between like Metacritic versus Rotton Tomatoes versus IMDB ratings. I think what another one was the combination of directors, writers, and actors versus the box office figures.

And then I think we talked a little bit about the difference between like,
>> Shirley Wu: DVD, so the release date, some movie release date,
>> Shirley Wu: Versus DVD release date. What were some of the other ones that you were talking about or that have stuck out, ones we were talking about, the attributes?

Sorry, I just realized that we were doing a lot of versus. So I also want to encourage just question formats. So instead of just versus, kind of if that was the case, how can we turn that into a data question? So, instead of saying versus, is that like-

>> Speaker 2: Does it correlate, do you have, if you see certain number type of words, does that correlate with a higher metascore?
>> Shirley Wu: So-
>> Speaker 2: Even just look at wins alone, right?
>> Shirley Wu: Yeah, or-
>> Speaker 2: Do the number of wins correlate with even just Rotten Tomatoes or something, right?

>> Shirley Wu: Yeah, absolutely. Okay.
>> Speaker 2: I like that as a simple, that's a really good one.
>> Shirley Wu: So basically, is there any relationship between the number of wins and how popular or well rated it is by the general public? Something along those lines. I kind of think for those first few I was doing them to be more shorthand.

But in general, I would kind of encourage putting your questions as a, if this exploration turned out well, is this a hypothesis? Can this be like the title of your visualization kind of the the theme to build the visualization around? So I think yeah then if that turns out well then there's a relationship between Academy Awards and the popularity of a movie or something like that.

>> Speaker 2: How about the relationship between popularity to genre over time?
>> Shirley Wu: Okay.
>> Speaker 2: So you could see people are preferring comedies these days versus horror movies.
>> Shirley Wu: Do people prefer-
>> Speaker 2: Times of the year and.
>> Shirley Wu: Yeah, let's go in that direction.
>> Speaker 2: Or it could be by month, or it could be just by year.

>> Shirley Wu: Yeah, wait, let's-
>> Speaker 2: You could say like over time people are preferring these. Or there's a slew of really great horror movies that were really just between these dates.
>> Shirley Wu: Yeah.
>> Speaker 2: Really great comedy movies released between these dates.
>> Shirley Wu: Yes, I love this thought process. So basically kind of you have these hypotheses, and that, I call them questions or hypothesis, but you have these hypotheses that you want to test with the data.

And so I think there was really a few different great ones in there. I think there was, are there genres we prefer more now than we did a decade ago? So let's try that. Are there genres we prefer more now than a decade earlier? There was also, I think the two of you were mentioning, do certain months have particular genres that are more popular?

So do certain months have genres that are more popular? So the reason why I wanted to get away a little bit from versus, the versus is very correlations, which is a really great thing to look at. But there's definietly other kind of analysis we can do, so this temporal direction is really great.

Yeah, so how do you feel about this? Is there other ones you want to brainstorm and put out there?
>> Speaker 2: Online there's a few. Which production company makes more in the box office?
>> Shirley Wu: Ooh, that's a good one! Which production companies make more in the box office? How about which ones get the best ratings?

That might be interesting, too.

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