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Pictures From the Gallery 6: Select Advanced Graph Builder Views (2021-EU-45MP-734)

Level: Beginner


Scott Wise, Principal Analytical Training Consultant, Learning Data Science Team, SAS


A picture is said to be worth a thousand words, and the visuals that can be created in JMP Graph Builder can be considered fine works of art in their ability to convey compelling information to the viewer. This journal presentation features how to build popular and captivating advanced graph views using JMP Graph Builder. Based on the popular Pictures from the Gallery journals, the Gallery 6 presentation highlights new views available in the latest versions of JMP. We will feature several popular industry graph formats that you may not have known could be easily built within JMP. Views such as death spiral run charts, marker expressions, hexagonal heat maps, cartograms and more will be included that can help breathe life into your graphs and provide a compelling platform to help manage your results.  A JMP Journal with data, scripts and instructions is attached so you can recreate these views for yourself.



Auto-generated transcript...




Scott Wise More Advanced Graph Building Views. My name is Scott Wise and in this edition, we're going to see a collection of surprisingly beautiful and very useful visualizations
  that can be built in Graph Builder. So to kick us off, I'm joined by my new business associate, the Gillman, or better known to those in the movie business as the creature from the Black Lagoon.
  So Gillman, I found out that you're using a lot of our firm's money to buy beachfront property. Is that right?
  Okay, are you worried at all about global warming that might be causing this sea levels to flood? You a little worried about that? I am too, so let me show you.
  I'm gonna share my screen real quickly, and let me show you what I found out is going on in JMP. So I've got some data that the University of Colorado has been
  posting on the average rise in global sea levels. And if I just take a look at a quick graph,
  you can see that there's a big trend upward when it comes to, you know, proof, right, that the sea levels are increasing, year after year. All right, all right. Well,
  here's the problem I see. I'm going to apply pull...I looked at the projections, and I took one of your latest properties and it was in a pretty high risk coastal flooding area.
  And I just kind of looked at how many feet might the floods be, over, you know, projected it out if things do go bad. And
  I even came up with an example of our two level beach house, does that look right? Okay, and this is what the water level will look like over the years. So if we take a look at it from maybe about
  four years out,
  it's getting...we're starting to lose our beach, you know. We take a look at it almost, you know, nine years out, it's almost up to our steps.
  We get out about 19 years out, it's getting into the first floor. I mean if we're around there for 80 years, we don't even have a first floor anymore. So do you have any contingency plans if this happens?
  You do.
  Oh, thank you, you got you got a prospective as well?
  Oh, my goodness, thank you. So your Creature from the Black Lagoon Bed and Breakfast, huh? So I noticed that Gillmen are welcome. And there's...let me show this to the folks who are look...watching over zoom here, we have ocean access and free fish buffet.
  Well I'm glad you got that covered and I guess you're ready for it. I don't think most of us that are human are ready for it, as well, but thank you for helping me out and I'll see you for sushi later.
  All right. Thank you so much, thank you, Mr Gillman.
  All right, so I'm showing my....I'm going to go back and show my screen.
  And let me show you how I built this chart.
  So this chart here
  is showing me...this is...this is just simply a projection,
  got year over here, starting with, you know, this year and going up in the future, and then I've just put...
  I put the possible flooding sea rise level on this column. So to make this thing work, all we're going to do is I'm just going to go in the Graph Builder.
  I'm going to put the sea level rise on this y axis.
  And instead of points I'm going to ask for an area chart.
  In the area style I want to see is overlaid.
  In the summary statistic will be the range. Okay now, there's 10...there's a 10 foot possible range. I want to make this look like my average house. I'm going to go and make it about a 20 foot house, like 10 foot ceilings, maybe I'm so lucky, right? And then
  now, it's just real simple right now to go ahead and size down this chart the way I want it. And I'm going to go to,
  basically, find a picture that I think is representative, so here's a picture of this beach house. I just grab it and drag it. Now I grabbed it and dragged it, I now can go in and just kind of manipulate this view
  and stretch it
  so it fits my space.
  Yeah I'll say done here.
  under the hotspot, now I can bring in the year and make it interactive. So I'm going to go under this red triangle, I like to call them hotspots, go to local data filter, add in the year. You notice
  as I added the year, it's continuous. That's not going to be as good for a range selection, maybe, so I'm going to go under that red triangle. Go to the modeling type, change it to nominal/ordinal. I get kind of this list view and now I can just go click on 2021
  and holding my control key down, or my command key if you're using a Mac like I am, that would be after the first year of range.
  Here would be where we are again and then about nine years out, then here would be the maximum if we go out almost 80 years.
  So this actually...I saw this used for great effect on the website, where in the US, they're trying to convince people that we have some...definitely some areas that were at risk
  of coastal flooding and subject to this rising sea level. And
  so they took pictures of some of my favorite places on the North Carolina coast and the Georgia coast and the Texas coast, and it was
  very impactful, even in a 2-D world here, to see that high level floodmark go up in some of my favorite places. So I'm going to do a blog on this one, if you just go to the Community just look up a local sae rise and
  you can go and see me apply this again and get the data, as well, to play with. All right, that was a lot of fun and thank you, thank you for welcoming my guest.
  Let's talk about pictures from the gallery, so if you're a fan of this presentation I've been doing and it's on its sixth year,
  every year we come up with six really advanced views, and they're not advanced in terms of you have to be an advanced JMP user,
  they're advanced in terms of these are probably views you didn't know the Graph Builder could give you in JMP. And they're really easy to do. You just got to know how to set them up, and what are the little tricks
  that make it shine. And so we're going to show six new ones. We have hexagonal heat maps. This is a new one coming up in JMP 16 and I'm really excited about it. We have map cartograms.
  We have time series. This came out in JMP 15
  by adding a time series to your Graph Builder. We have row ordinal spirals.
  We have HDR box plots. This one came out in 15 and graphlets, which came out in 16. So I'm excited to show these to you. So if you...if you've seen my presentation before, you know I always give you a gift.
  This journal I'm showing you, that's going to be posted in the link, it's going to be posted in the Community.
  You will have it and anytime we talk about one of these graphs, you'll be able to see it, you'll be able to not only get some hints but you'll be able to follow the steps, and I even put in the data for you.
  So hopefully this will be a big help for you, alright. So everything's got kind of a pandemic theme because we're all being affected by the pandemic here, and we're doing this talk virtually, not face to face.
  our honey and the bees that make the honey. And
  there's been a lot of good data on what's going on with the bee population in the United States and it's very threatened here.
  I know SAS actually has their own beehives and we've taken a little bit of data on them and had great talks about what they look at, in terms of data.
  But one of the things they worry about are colony collapse. And a colony collapse is when all the male bees, all the worker bees take off and they...
  they go and take off and
  leave the hive. Leave, kind of, leave the queen bee and the little bees behind, you know, the young bees behind. And it basically is is pretty devastating and a lot of research is going on what is causing those. But what we have here
  a heat map, but it has a special shape, it has the hexagonal shape, and I'm going to see if this can help us see the effect of colony loss over some recent years, all right. So you're going to have your tips, you're going to have your steps. Let me open it up and show you how this works.
  So, right here I've got my US State Bee Colony
  information. I have time periods, so this is kind of a season, you know, and I look over the winter and see how many bees get lost.
  So that's this percentage right here. So here in 2008 in Alabama, of all hives that got reported, they lost about 39.7% of their bees.
  And we know how many beekeepers and how many colonies were done that year or active that year and being measured.
  So, to pick this up I'll just stick the Graph Builder. Here in the Graph Builder, I'll take the total winter/single state only loss. I'm going to put this on the Y. I am going to take,
  as well,
  the time period.
  Or before I take the time period, I think I'll put the colonies on the X and I'll put the beekeepers on the color.
  And I'm going to take off this smoother, I've just got points. Right now, I'm going to go and I'm going to select the heat map.
  Now I've got this heat map selected.
  I am going to go and change the view. Now, before I change the view, it's looking like I got a lot of things that
  are kind of between zero and...what's this, like 50,000 colonies? So to handle that one, I'm going to right click on the colonies on the axis setting and I'm going to ask for the log.
  And up here, this one's doing percentage. That's pretty good. I'm going to go here to the axis settings and I know they consider anything over 30% to be a problem, so I'm going to add a little
  reference line right there. So I got that line going across. Now I can go under the heat map area. I can go under this bin shape and now in 16, I can turn on this hexagonal shape.
  Now this looks pretty good. Got too much stuff that is in the blues here in this beekeeper gradient, so I'll right click. I'll go to gradient. I will go under the color theme. I've got this...
  it's called black body, but it really goes from kind of white and yellow all the way up...that kind of looks to a dark red to a black kind of color. I like that one. I'm going to say okay. I'm going to maybe put eight labels of them.
  And I'm going to make this one log as well, so the colors are a little more dispersed. That's looking better. Now can we do something about the time period?
  Yes, we can, so I'm going to put the time period up here on the X axis, that gives me different panel views. I'm going to right click right there under time period, levels in view. I'm going to put two at a time and I'm just going to scoot over 'til the most recent two years of the data.
  Okay, this looks good. Now some things that are lighter color are starting to fade and how you handle that, you will right click
  within the data, and I'm gonna have to do it twice since I've already got this thing paneled, but if I did it before, I wouldn't have to do it twice.
  And I'm just going to right click, go to customize, and where I see the heat map shapes, I'm going to add an outline. And you can see what it did. And I'm just going to do the same thing over here as well.
  And heat map cells, add it to the line width here. There we go and then you can work and get the right size bin. And now I can see something like here 2018, 2019 in Pennsylvania,
  they were between 43 and 50% of colony loss, so they might have been having some of this colony collapse, but now in 2019, 2020 things have gotten a lot better,
  33 to 40% and it looks much better, you know, the previous season. We'll see how this season turns out. Researchers think that colony collapse could have something to do with, like, pesticides that might be affecting
  the neural behavior of bees, even beekeeping methods and so it's something we can deal with. But in other parts of the world, the bee colonies are actually growing at a rapid pace like China, so I think this is definitely something
  we can get a handle on but measuring it is a good place to start. Alright, so that is a pretty good start to our data. Again, you have all this available to you. I will move on. I am going to go to
  the cartogram, alright. So this is looking at the number of McDonald's outlets because,
  you know, during the pandemic, picking up food is one of the of the few things we can do. I can't eat in restaurants very safely,
  so I appreciate a good quality fast food restaurant and they are...some things at McDonald's are very, very good. They've got good coffee too.
  So they're around the world, and I know they're consistent everywhere I've traveled. So if I'm telling my friends out in Europe, maybe where where the McDonalds are
  in recommending that for dinner, for lunch, here is a map. Now it's doing something a little different here, you see the outline of the states...
  of the countries, I should say, but you'll also see that in some of the countries, the shaded area still respecting the boundaries
  of the country, but it's smaller and that's giving you some sort of idea of the people per outlet. So the fuller it is, the more people per outlets are being served.
  The smaller it is, the more spread out the people are, some of the outlets the McDonald restaurants are serving less people.
  You can get kind of a color by number of outlets. And so this...the reason we like this is it kind of helps you with unbalanced
  sizes in your map shapes, you know, because some countries might have a lot of territory,
  be big and wide but they don't have too many people, and others might be small, but they're very densely packed. They might have a lot of McDonald outlets compared to a bigger place with less people, so this can help you.
  I'm going to use backgrounds and lines is a good tip to do. Again, you have the instructions, but here we go. Pretty easy to do. I'm going to pick up from the data
  what's going on. I'm going to put the country name on the shape.
  I'm going to put the people per outlet on the size, and I'm going to put the number of outlets on the color.
  Okay, now it doesn't look like anything is going on here, but um it will get better when we zoom in, because we've got every McDonald's outlet in the country.
  So it's not really showing up. So under my red triangle, let's go to my local data filter. I'm going to add the only EU countries and those that have only have 300 or more. So when I click on this, I'm going to select just the EU countries. Now you see something starting to happen.
  And just 300 plus outlets and that restricted myself down to just a couple of European countries, but now they pop out there, and now I can see what's going on in Spain
  in France
  and Germany and Poland and Italy. Okay and.
  other things you can do. As you saw before, I definitely can drag in
  the golden arches here.
  Just from a from a picture file and, of course, you can as well,
  you know, go and orient that picture. It's a nice little background. What if I wanted to add the country map? I would right click. I would go under graph. I would go under background map.
  And maybe let's do a detailed earth, and there we go. There's the detailed earth we have. And again, you can play with the gradients and do other things as well. This one I'm probably going to right click as well. To to customize in here under the
  shapes here, I'm probably going to make this more prominent.
  Give them more of a black color and now I can see the outline a little better. So again a really cool thing you can do with maps to actually help you interpret it.
  All right, number three is time series.
  So here in the pandemic, well, I'm sure we're all playing more games with our families and the people we live with, so I took some classic board games.
  And I went out to Google trends, which actually will let you have...which will actually, it's a data mining tool and it will go out and
  show you the frequency of words that are talked about out there in social media over time, which is pretty cool. So I took since October and every day I look to see if we were starting to increase us talking about
  games, right, these games. Are we talking about playing them? Are we talking about learning them? Are we looking stuff up online?
  And you can see some things are happening on this chart. So let me show you how to do this. And the neat thing on this one is in 15, they allow us not only to
  do a trend, you know, and put a line through it, if you fit a line, but they let us to do a time series forecast, which is really cool. And it's not going to replace
  all the options you have under our main time series and time series forecast platforms in the modeling sections of JMP, but it will give you a good one, a good basic one you can use just in Graph Builder.
  And let me show you how this one works.
  Alright, so let's go ahead and let's pick up that data I got from the Google trends. I can see
  how many times these games were mentioned over their analysis, however, they scaled them, scaled them over an index.
  So what's going on? Oh, by the way, I do have a column here that's an expression column,
  where I dragged in a couple of pictures I thought might help me when I hover over some of these labels. So I'm not going to show you what those pictures are to ruin it. I'll show you to you live, alright. So here I'm going to take the day
  and put it on the X axis. I'm going to take all the games, I'm going to put them on the Y axis. So I've got points. I've got a smoother. I don't want a smoother, I'll disconnect it.
  I'm not going to go to line, I'm going to go to fitted line, I hold my little shift key down, and you can see, you know, this chess has something going on
  better than the others. Those lines are straight, this one looks like it's trending, but down here under fit, now from polynomial and 15 you can go to time series.
  Now the forecast model is showing you the information up here. Unless you're really good at a time series, it's probably not going to mean much for you. I'm going to turn that off.
  But seasonal period, remember, I was doing this by day and I knew that they talk about games, and we play games more on the weekends so I'm going to assume like a seven day seasonal period, there'll be a trend.
  That's why you see, kind of, the up and down but it's look but it's going over seven days, so it basically looks it looks over seven days to actually figure out
  where things are going. And how many periods do you want to forecast? Let's forecast out 14 or...since we're doing this, I'm going to forecast out 21 days, how about that?
  OK, and now that we do this now, you can see what's going on. And I'll say done, and I can see that games like dominoes and backgammon are just not that interesting, right? Pretty flat. Mahjong and poker looked interesting. Now everybody
  went up slightly over Christmas, because we played more games over Christmas, but let's take a look what's going on with poker.
  Right before Christmas, oh I've got a little picture of the chips they...and the symbol they use for the world series of poker.
  What happened was, given the length of a pandemic, these big tournaments, these big poker tournaments that play Texas hold'em, in a lot of cases,
  they decided that people weren't going to come back to conference centers, so why don't we hold most of it online? So like 95, 98% of all the gameplay is online, and then only that final table goes and meets in a,
  you know, socially distancedj, controlled way, and does it live. So they've all gone to this format and it's increased in popularity, so I think that's going to continue.
  As virtual online poker is hot, but what about this? I mean Christmas, that jumped up for chess but it's been going gangbusters for chess. What's going on with chess?
  And if I look what's going on here, oh, The Queen's Gambit. So if you're like me and you've watched a lot of shows
  on Netflix or or other type of places, you can watch these these fictional historical dramas, this was a really nice one about chess, about a young girl that
  fought her own demons, got...was really good at chess and not only became a master but started to beat some of the best players in the world. And so the minute that happened, everybody wanted to learn chess. So if there was a stock on chess, we should all have invested it.
  All right.
  So we're down to the bottom three here, checking how we're doing on time. Run ordered spirals. Now Julian Paris is one of my good friends and he he hosted
  and did a great job with the JMP On Air series that you might have seen on the Community or watched live a little earlier in the year. And
  he used to bring up some challenge graphs that his friends would give them and one of his friends gave him a chart that spiraled around and looked like a tornado.
  And he was able to replicate it in Graph Builder, but he made the comment, I don't see where this will be helpful to anybody. And I got thinking, where do we care about
  figure skating (and there's something called the death spiral in figure skating,
  which is where one you're skating partners and your partner's in the middle
  of the of the radius there and he's and he's holding you and then you're skating on the outside and you make're doing a 360 and you make a wide circle and then
  he pulls you in and you go faster and you go even closer and closer and closer and it's really eye popping, right?) Well, pilots do this as well, and they call theirs a graveyard spiral
  or sometimes, it's suicide spiral. And what happens, you're flying your plane, you're in clouds, you're at night, you don't see the horizon, you can't see the ground.
  Maybe you don't have instruments that would be the worst, but what happens is you feel like you're dropping an altitude.
  And you feel like something's wrong because you feel like your level, but what it is, is you're actually got yourself into a spiral and you're actually banked.
  And if you stay with it you'll actually go faster and you'll actually tighten that spiral, and you will eventually
  land, you know, crash into the ground, unless you can pull out. So they teach you how to get out of a graveyard spiral, and I wrote these lessons down and people was like can you can you put notes...
  labels, you know, on on JMP charts? Oh sure, on Graph Builder, it's great. So I colored this first spiral, this phase one. Don't panic, the secret here is trust your instruments, not what you feel.
  And your instruments will tell you that you need to level your wings. So in phase two, you have time to level your wings, if you take it calm, if you reduce the power.
  You pull up a little on the nose, then you take control. In phase three, once your power's normal, you return to normal airspeed and you can see, this plane got out of it and it's going to a good area.
  Okay, so, as we say, here how we make this graph work. So we go into this graveyard spiral, okay. I've got X, Y, I've got the phase.
  So here under Graph Builder, I'm going to take my X, I'm going to put it on the X; I'm going to take the Y, I'm going to put it on the Y.
  I kind of see the shape, just with the points, but the minute I try to add
  a line, it gets all out of whack. Well there's a big row order box right here. I click that row order. I bring it back. I'm going to hold my shift key down and add back in the points. And now I'm just going to go phase by color in there I'm at. That easy.
  So pretty cool chart.
  Alright, so next, our fifth graph.
  Our fifth graph is HDR contour plot. It stands for high density region and it's a type of box plot that allows you to make some comparisons.
  And you're going to set it up the standard way, but you have to know where to get it and it's under the contour, which is kind of a different place to have it.
  So I'm going to open this up. Now you're probably in the pandemic, you're probably eating a bunch of stuff you probably shouldn't be eating.
  And candy is probably one of them, right. So Valentine's Day is coming up here pretty soon, and probably has passed by the time you see this recording,
  but definitely chocolate's good and in moderation, can be good for you, but I've got these major brands and I have their nutritional information. So let's see if charting can help me a little bit.
  So I'm going to go to Graph Builder.
  I'm going to put the brand on the bottom and under nutrition here, I've got several things. And let's just start with one and get the view right. Let's just start with my calories.
  So I put the calories on the Y axis. Now, instead of points I'm also going to add in under contour.
  I click on the contour element here. It says violin type. I don't want violin, I want the HDR. And now what you're seeing is, I am seeing the shaded area is around the modal, that's the density mode and this is the...this is the most dense area.
  And it's where the more points are, if the more points are on the end, it will be...
  let me give will be on the ends. Okay, and you can see where those points are
  in relation.
  So that's a pretty cool chart. Now can I make this a little better? Oh sure I can color by brand. We can add in other things. We can add in the carbs.
  You know, you might add in the total fats. Say done. Now at this point, you might want to worry about these marker colors and make the points blue so they don't get totally
  washed out by the bars. And now, you know, you can you can click on M&M and see where they all are. So this can help you make a better decision. And you can also make some comparisons here over,
  how the brands are doing or I should say the...yeah how the brands are doing with their products in relation to making healthier chocolate.
  Alright, so the last chart we are going to take a look at
  is the graphlet. And this graph is a little washed out, but I think you can see why it's good. So you know we could always...I knew how to make...use filters
  to change the...change up what I'm seeing in a graph. I even knew how to create a dashboard and instead of using a filter, make one...the settings of one graph cast...
  cast into other graphs, you know, control other graphs like it was a filter.
  So there's just a lot of ways to do that, but the graphlets are a wonderful way of of using the hover labels to actually bring up, usually, other graphs, and generally, drill down graphs.
  And I'll be able to drill down more and more. So the things in this red bar and this happens to be an Asia region and I'll show you this data live,
  when I click on the hover, it will give me the option to bring up this graph, which is a tree map, and when I click into this square, I can now bring up...I can bring up now
  tabulate. And this tab here, this table's giving me all the raw information underneath
  try to order your columns from a high level, drill down to a low,
  and start with the end in mind.
  Okay, so I'm going to bring up this international beer nutrition, because what goes better with the chocolate than a good international beer. So no U.S. beers, but I do have Canada and Jamaica in here, as well as several countries in Asia and Europe.
  Alright, so the first graph, and I'm going to start with the last one I care about, is tabulate and I hope you've seen tabulate before. It's under analyze, tabulate, it's where we kind of do our
  like, you know, pivot table created type of tables summaries, and you can just literally go in and dump in region and dump in country next to region.
  And maybe the brewer next to that one, and then you can can take a thing, like the out...
  output, like the alcohol percentage, and you can get whatever statistic you want. So I've got this type of graph already open. Save that
  as a script, so it's there. I'm going to keep that one open. Let's go to what the second graph was, the one in the middle, the middle level of detail. This one was a tree map, where I have country nested in region,
  and I have it sized by calories, by average calories, I should say, and colored by average carbs. So to create this kind of chart, it's going to be simple to go out to Graph Builder.
  It's going to be simple, just to go, let me take my region, first, and let me take my country, next to my region. Let me go ahead and ask for the tree map. So things are looking pretty good so far. I'm going to size it by...I think I sized it by carbs.
  And I think I colored it by calories.
  Now it jumps out at you and there's just a lot you can do here. You can even control the layout. I like the square five layout.
  But that's how you create this chart, right. Now we'll keep that one open there in the back. And the last thing we're going to pull up is this point and line fit chart and it's kind of a cool chart.
  I really just want to show the mean of, like, here's the mean alcohol level of Asia and the rest of the Americas and Europe. And to make this chart but with these kind of shading around my mean prediction there, to make that happen, I'm going to go on the Graph Builder.
  There I pulled it up. Alcohol percentage. Maybe I'll just put the region down here, instead of points, when the summary statistic is mean. Now when I do that and I hold my shift key down and I turn in a fit line, it gives me, kind of, this confidence interval around my my my mean.
  And I'm going to color by that region as well, or overlay, I should say, by the region. That's how I generated this view. Very simple. Okay, now I have
  all these charts open. How did I make the graphlet work? Because when I'm hovering over this one, it's not giving me anything but just information.
  How do we make that happen? We'll start with the most detailed chart, the one at the bottom, right, the one you're going to drill down and end with.
  This is the one I want. I right click. Save script to the data table, which is a good place to put it, or save it to a script window, which this is just puts those clicks.
  In the JMP scripting language that I made to make this chart. I'll tell you what you do. Just go save the script to the clipboard.
  You can close this now, go to your second chart, go under,
  like, where it says United Kingdom, any of these squares. Just right click. Go to hover label. There's a lot of features on hover label, you got this wide open editor, you can do some charts on the fly, but I've already got the JSL saved in my clipboard so just say paste graphlet.
  And did it work? Well there's United Kingdom, I click on this. It brings up the tabulate, in fact, it gives me a nice little filter so I can change things around,
  which is really cool. So I can say, my second home is in the Philippines, I can see what's going on, what brands are being represented by the Philippines. That's kind of cool. All right, same thing, right click, save script to clipboard, right. What this one has done
  if I show you in the script window, it has all this tree map Graph Builder stuff I built, but it still has what I did with the tabulate as the graphlet.
  OK, so now that it's in the clipboard, I should be able, if I did this right and cross your fingers here, I'm going to close this one, I'm going to go into just any of these shaded areas, right click, hover label on the first graph,
  the high level graph. And now I'm going to go to paste graphlet. If I did it right, I go to Europe, there's a tree map. I click on the tree map, okay. What's going on in Ireland? I click.
  Let's click on the graph and now it brings up all the
  good international and export beers there in Ireland and
  sometimes it's better just to have a Guinness, because the carbs aren't too bad. The calories aren't so bad, the alcohol levels, not too bad. All my friends
  in Ireland, good shout out to them, because we drank many a Beamish together. So there you go. So that's how this works, and when you save
  this one and I'll save this script to my data table and I'll call this my Finished Graphlet Graph.
  I close out of it and I pull back this data.
  There it is, Finished Graphlet Graph. Click on it, there I go, and it's every bit as interactive as before.
  And that's the wonderful world of graphlets, so please use this technology if you can.
  All right, so you've been a fantastic audience here. I'm at time, would love to show you more, but definitely let me know if you have questions.
  You will, again, get this journal in your link and also looking at the, you can find those. You can find the links to the older galleries, we did about six for each year.
  Six unique views so now we're up to about 36, you know, or or just big number out there, usually six is what you get. So here we have several blogs that feature graphs, so definitely check your Community blogs. Also there's some great
  presentations in the YouTube in the Community on how to actually get the most out of Graph Builder, build dashboards and there's some great tutorials as well. And this is all in your journal and you'll be able to go click the link and learn more.
  All right, so I thank you so much for joining us for the pictures from the gallery.
  And I look look forward to the next time we can meet, especially face to face, so take care.

Link to the full JMP Community Blog on the intro Global Sea Level Rise graph view with attached data and scripts:Visualizing the Effects of Global Sea Level Rise (Graph Exploration)