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Building scatter plots

From: Interactive Data Visualization with Processing

Video: Building scatter plots

In our last movie, we looked at how we could create dot plots to represent one-dimensional distributions, and what that is is one variable at a time just running from lowest to highest. In the example that I had, I actually showed several variables, but they were all just separate, one-dimensional distributions. In this movie, I want to show you how to do a scatter plot, a very common two-dimensional distribution for two quantitative variables. And in this case I'm going to be using a lot of the same information. We are using the same data set, which is based on Google's search trends, on a state-by-state basis.

Building scatter plots

In our last movie, we looked at how we could create dot plots to represent one-dimensional distributions, and what that is is one variable at a time just running from lowest to highest. In the example that I had, I actually showed several variables, but they were all just separate, one-dimensional distributions. In this movie, I want to show you how to do a scatter plot, a very common two-dimensional distribution for two quantitative variables. And in this case I'm going to be using a lot of the same information. We are using the same data set, which is based on Google's search trends, on a state-by-state basis.

Because this is a rather lengthy code, I am just going to walk through this one instead of typing in in front of you. Let me just show you, starting at the top, first, I've got to put that as a comment or I am going to get an error message. So I'll save that. I have my color palette that I brought in, and then I've saved some fonts. I created the fonts with the tool in Processing. If I go up to Tools here in the menu bar and click on that, down to Create Font, this is where I created the font. Now on your computer the fonts available, may be different.

We've got Adobe CS6 installed on this one, so we probably have some fonts that most computers won't have. If you have any problem with the fonts, also just feel free to comment out the fonts that I have got in this example, or just replace them with other ones that you do have on your computer system. But in the third line, I am declaring the font variable. Actually, it's an object. Beneath that, I am declaring the data. That's a data object. Below that, I have a variable for the rowCount in the data set.

Then I have a little global variable for the diameter of the circles that I'll be using. In the setup block--I'll scoot up a little bit-- I have a window that's 600 x 500, because normally, I only do 200 tall in this course, but a scatter plot needs to have enough vertical room to work well. So I've made it nearly square. Then I am calling the data. I'm loading it into the stateData object, by referring to the stateData.tsv, tab-separated value file.

Then I'm also getting the rowCount by referring to one of the object methods, the getRowCount. Then I'm going to print out the rowCount just to double-check down in the Console. Then I load the font into labelFont. And then I have the anti-aliasing turned on. Then we go down to draw. I have got a background which is based on the first index color in my palette, the array of colors. Then I call on the font, and I load the stroke and the fill for the shapes in a medium gray.

And then I start placing some axes. Now, remember, when you're drawing in Processing, you want to do things sort of in a reverse order, because the things that come later will get drawn on top of the things that come earlier. So, a lot of times you want to put the foundational stuff very first and then other things later. So right now, I'm just doing the lines and the labels for the X axis. So I'm going to do textAlign (CENTER). I'm drawing a line across the bottom. And then this little for loop is going to insert the labels across the X axis.

You'll see this when we bring them up. And then I'm also calling on the text, just to put the word Videogames underneath that, because what I'm looking at in this one is the relative interest in Google searches for the term videogames. Below that, I do a similar thing for the Y axis. Let me roll this up a little bit. I've changed the alignment because I want them to be a little snug on the right to the axis. I draw the vertical line for the axis, and then I use another for loop that places the markers and the numbers along the side.

And then I have the word dance that appears to the side of the whole thing, because on the Y axis we're depicting the state's relative interest in the search term "dance" in Google. Beneath that, we have a for loop within the draw loop that loads the data. So it goes through the data set, one row at a time, and first it loads the state names into a string variable called state. Then it loads the video game data. It says float, because it's a floating point variable.

It has decimal places. Then we have the name of the variable, videoGames, and then it gets it from the stateData object using the .getFloat method for the object. And then it just says go one row at a time, because we're using the row variable from above, and then it is in the fifth row. It's actually in the fifth index, so it starts at zero. And then I tell it to map it. Now, you may recall that in the last example when I did the dot plots, I did some rather Byzantine calculations on how to get things spaced out correctly.

That was one way to do it. Another way to do it that actually can make things a lot simpler is to use Processing's Map function, and what this does is it changes the scale between two things. So on this one, I said I created a new variable called x because I am using x coordinates. And I said I want you to map the videoGames variable, which has a naturally occurring range of about -3 to +3 in this data set, and I want you to change that so it goes from 100 to 555, because that's a multiple of the labels on the bottom.

So I don't have to figure out that a score of 1.477=417 or something. This will just do that automatically for me. It's even better on the next one, dance, because I'm dealing with axes that go in different directions. Because when you do a scatter plot, you want to start with zero at the bottom. Now we want the numbers to get bigger as you go up. The problem is, however, in a computer, zero is at the top and the numbers get bigger as it goes down, and by using the Map function, I'm able to flip that around without any math on my part.

So I say I have a new variable, a floating variable called y, and then I'm using Map to take the dance variable and to take its naturally occurring values of -3 to +4 and map those. It starts at 400 and then goes to 50. I am actually trying to even flip the order in which things go, but this one makes life much easier than having to figure out by hand what the adjustment should be for the calculations. After that, I turn off the stroke and then I put in a fill color for the ellipses.

I also make them somewhat transparent. That's the 180. There is the alpha. Because I have an x variable, a y variable, and a d variable for the diameter up above, I just put x, y, d, d for the eclipses. Then what I have is a small amount of text that enables rollovers, to see what the states are for the data points. Now, it gets a little crowded in the middle, but this does work well for extreme cases. And then on this one, what I have used is Processing's Distance function. And what I have said is if the distance between the midpoint of a dot--because this is going through one dot at a time--if the difference between a dot and the mouseX and mouseY is less than the half of the diameter of the dot, the diameter is 10/2 gets 5, I added one on so we have just a little bit extra room for that one, because sometimes five pixels can be hard to hit.

And then I say but if the mouse is that close to the center of a dot, then bring up the state name and put it just off to the side. Also, you see I have a second tab. We have used this one before. That has Ben Fry's Table class. Rather lengthy here. Again, I'll just point out that you can copy it from here, but you can also find the Table class in the Processing's built-in examples. So I show you really quickly. We go File, to Examples, click that Open and then go to Books.

That's the fourth one down. Go to Visualizing Data, the third one down, and then just go to usmap, the first one. It says chapter 03 usmap (ch03-usmap). And then the second one, starting here, when you click that open, you will find the same Table class information. So you can also get it from there. So it's built into the Processing program as well. And we fully anticipate that with version 2.0 of Processing this will be a native part of Processing that you won't require any special installation.

So anyhow, back to where we were, We hit Run and there is our scatter plot. You see we have Videogames scores across the bottom. 0 indicates that that state's relative interest in that search term is at the national average. If they have a positive number, it means they're above the national average. If they have a negative number, they are below. Similarly, Dance going up and down the side, zero is at the national average, positive numbers are higher, And we have a few interesting cases right here. We got a bunch of cases just right here in the middle.

There's Montana, there is Missouri, there's Texas. Nothing particularly special. They are close to the national average on both of them. We do have one right here. Iowa is the highest of all in searching for Videogames, and they are at the national average for Dance. Down at the very bottom-left is Virginia, which is three standard deviations below the mean on both of them. And I don't have any explanation; if anybody here is from Virginia, I'd love to hear what your theories on that one are. And then way up at the tippy top is Utah, my home state.

You see there's a huge difference between them and everybody else on search for Dance terms; in fact there is over two standard deviations in between them and anybody else. I have some theories about that. Performing arts are very popular in Utah. But anyhow, it's an interesting thing, and this is a very easy form of interaction. All it is is a rollover. Don't even have to do anything. And that is how you can create an interactive scatter plot in Processing.

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This video is part of

Image for Interactive Data Visualization with Processing
Interactive Data Visualization with Processing

72 video lessons · 12134 viewers

Barton Poulson
Author

 
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  1. 3m 16s
    1. Welcome
      58s
    2. What you should know
      1m 22s
    3. Using the exercise files
      56s
  2. 11m 51s
    1. Overview of data visualization
      11m 51s
  3. 11m 53s
    1. Installing Processing
      3m 38s
    2. Overview of Processing
      4m 5s
    3. Exploring libraries
      4m 10s
  4. 1h 1m
    1. Basic setup
      7m 31s
    2. Drawing points
      4m 37s
    3. Drawing lines
      5m 6s
    4. Drawing ellipses and circles
      5m 24s
    5. Drawing arcs
      6m 54s
    6. Drawing rectangles and squares
      4m 58s
    7. Drawing quadrangles
      3m 25s
    8. Drawing triangles
      2m 55s
    9. Drawing polygons
      3m 37s
    10. Drawing simple curves
      4m 54s
    11. Drawing complex curves
      6m 46s
    12. Drawing Bézier curves
      5m 38s
  5. 54m 3s
    1. Introduction to variables
      10m 44s
    2. Understanding variable scope
      6m 53s
    3. Modifying variables
      9m 8s
    4. Creating arrays
      9m 53s
    5. Modifying arrays
      6m 37s
    6. Creating strings
      7m 3s
    7. Modifying strings
      3m 45s
  6. 1h 2m
    1. Incorporating randomness
      7m 59s
    2. Using Perlin noise
      4m 24s
    3. Shuffling with Java
      3m 30s
    4. Specifying line attributes
      8m 2s
    5. Changing placement modes
      5m 45s
    6. Understanding color attributes and functions
      4m 16s
    7. Exploring color spaces
      7m 44s
    8. Using color palettes
      7m 5s
    9. Transforming the grid
      8m 38s
    10. Exploring the attribute matrix
      5m 33s
  7. 52m 7s
    1. Building code blocks
      5m 57s
    2. Writing a while loop
      3m 52s
    3. Using for loops
      5m 35s
    4. Creating conditionals
      14m 50s
    5. Working with easing
      10m 51s
    6. Creating spirals
      11m 2s
  8. 18m 55s
    1. Mouse tracking
      3m 54s
    2. Hovering and clicking
      11m 16s
    3. Understanding keyboard interaction
      3m 45s
  9. 27m 32s
    1. Specifying fonts
      6m 43s
    2. Using images
      5m 51s
    3. Playing a video loop
      6m 20s
    4. Exporting video
      3m 47s
    5. Adding sound
      4m 51s
  10. 20m 49s
    1. Creating functions
      11m 48s
    2. Creating classes and objects
      9m 1s
  11. 31m 10s
    1. Using embedded data
      5m 26s
    2. Working with appended text data
      6m 4s
    3. Working with appended tabular data
      10m 26s
    4. Reading XML data
      9m 14s
  12. 48m 17s
    1. Generating dot plots
      11m 11s
    2. Building scatter plots
      10m 0s
    3. Making line plots
      9m 55s
    4. Creating bar charts
      9m 12s
    5. Checking out examples of maps, hierarchies, and networks
      7m 59s
  13. 20m 57s
    1. Introducing some principles of 2D design
      13m 44s
    2. Understanding color theory
      7m 13s
  14. 24m 46s
    1. Interacting with zooming, rotating, and sliding
      6m 26s
    2. Implementing slicing
      6m 47s
    3. Using rollovers
      5m 58s
    4. Introducing the GUI libraries
      5m 35s
  15. 10m 35s
    1. Sharing via OpenProcessing and other sites
      3m 19s
    2. Saving as a desktop application
      2m 42s
    3. Saving as JavaScript
      1m 47s
    4. Saving as an Android application
      2m 47s
  16. 2m 38s
    1. Where to go from here
      2m 38s

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