[MUSIC] All right, we're in step three of three of this project to visualize average life expectancy around the world, and in this video we're going to build on what we've done in the previous two. So we've already set up the map, and we've already read in the data from the CSV file, which tells us the average life expectancy for each country, and now we want to translate that data into the colors of this map. And so hopefully you've implemented everything that we've done so far in Eclipse, and you're ready to get going and do this last piece with us. So the data we need in order to annotate the map with this information is not only the life expectancy for each country, but also how the countries look on the global map itself, what their coordinates are and how they occupy space in the map. So that information is located in a file in the data directory of the unfolding maps library, and it's called countries.geo.json. Json is an extension that indicates we've got formatted text. Now in order to pull all of this information together, the geographical information about the countries as well as their life expectancy's, we want to design some objects, or use some predefined objects, that help us organize both geographical locations and features, or properties, of these locations. So what we're going to think about are the underlying groupings of the properties and locations as distinct from their visual representations on the map. And in fact unfolding as a library, has some classes that are able to manage that distinction for us. So when we're just thinking about a particular location in the world and it's associated properties, we wanted to find or use the type feature. So use objective type feature for talking about locations with properties. But then when we want to translate those into some sort of visual representation on the map, then we could use the marker class in the unfolding library, which then lets us style how these properties might impact what we display on the map. So let's think about how we are going to store all of this information, because we have a lot of countries, and so we want to have a list of features, and also a list of markers. So this is another example of an abstract data type. In the previous video, we saw the abstract data type math, which let us store pairs of pieces of information, pairs of objects, and now we've got lists. And lists are relevant whenever we want a collection of objects that are ordered in some way. Okay, so we've already seen other examples of lists. For example, when you think about ArrayLists, then that's a particular implementation of a list. And we'll talk more about this data type and its implementations later, but for now, we want to think about a list of features, each one associated with a country. So, in our output we're going to think about all of the countries, each of the countries has associated its life expectancy in some other pieces of information, and so each of that is going to be a feature. We're going to have a feature object for each country, and we'll store them all, all of those feature objects in a list. Similarly, we'll have an marker object, a different marker object for each one of our markers, for each one of our countries, and so, in our class we need to declare a list of features and a list of markers, and this is how we do it. Now, instead of just declaring that's not good enough, if we want to work with these objects, we've declared them but now we need to build them, and so we need to create one feature and one marker per country. So here's the code that we might include in our setup method to do so. We're not gonna go into the details of how this goes about. We're using helper methods that are provided by the UnfoldingMaps library, and these are standard methods that you will use in your project and thread when you want to create features and markers for a list of countries that you already have. Once we have these features and markers, we want to add them to the map, which means that we display the markers, but not only do we want to add them to the map, we want to manipulate them, and what we'd like to do is shade them based on the colors, based on the life expectancy. Okay, so let's dig deeper into what this shading will look like, and we've defined a new helper method that will let us do that in some detail. Okay so this is our helper method, remember that our rule of thumb is that they are private unless there's a reason to open it up to the world, we're going to keep it private. And what we're going to do is go through all of the markers that we created, remember there's one marker for each country. And what we'd like to do is for each of the markers, for each of the countries and their associated markers, we're going to decide how to color the marker, and the coloring is going to depend on the life expectancy. Now, that life expectancy is a number. The number's typically between 45 and 90, and that number is stored in the map data structure, right? We can access it by saying, hey map, I would like the value associated with a key country. And so if we pass as an argument to the get method of the map the countryID, or the string that has that countryID, and then the map object gives us back the value associated with that key and that's a float. Once we have that number, well we'd like to translate that number to a color, and this is where I apologize, because not only do we have two ways of using the word map in this sequence of videos, we now are including a third. So let's think back to all of the maps that we've used. We've got the global map, the picture, the map of the world. We've got maps of data structure, which associates keys with values. And now we've got map the method, and this is a built in method in the library and it's a really useful one. So this method map lets us take a number in a predefined range, and map it into its comparable location in a different range of values. So in this particular instance, we're taking the number which is life expectancy of the country that we're currently focusing on. And we know that the life expectancy ranges from between 40 in countries with the lowest average life expectancy to 90 at the top end, and we'd like to translate that to something to do with color. And if you think back to a couple of videos ago, when we first introduced colors and the RGB codes for colors, remember that those RGB channels had minimum value zero and maximum value 255. So we'd like to translate the range 40 to 90 over to the range of zero to 255, so we're in a range of numbers that's more compatible with color codes, and this map method lets us do just that. Okay, so we invoke it. What we get back from it is a float, and we're going to cast it to an integer, because for the RGB colors, we just deal with integers. So in the RGB coding of colors we want an integer between zero and 255 for each of the three color channels, red green and blue. All right so, we've translated the life expectancy of the country that we're focusing on to some integer value between zero and 255, and what we'd like to do is, countries that have really low life expectancy relatively speaking are going to be colored bright red. So bright red means that the red channel should be at highest possible, somewhere around 255. And if we want the countries that have very high life expectancy to be colored bright blue, then for those the blue should be high, 255, and all the other channels should be pretty low, and so we can define the color of the marker appropriately. So the red channel is going to be the first argument of the color method, and it's going to be 255 minus the number that we just calculated. So if the color level that we calculated is zero, then the color that we're setting our marker to is going to be very close to 255, it's gonna be 255. So it's gonna be a very, very red marker, and the other two arguments are going to be very low, and so we'll see that bright red color. And on the other side, if the color level that we calculated corresponds to a really high life expectancy, then we're gonna get a large number, which means that the red channel, that first argument to the color method, will be very low, and so our marker will be a bright blue. Now, think back about this logic that you see in this code, and we have an if else in there, and if that if else is dependent on the conditional statement if lifeExpMap.containsKey(countryId), well what on Earth does that mean? It could be that the marker that we're looking at currently has a country ID that doesn't show up in the file of life expectancy's. It could be that when the World Bank put together all of their data on life expectancy's, they weren't able to reach the statistics of one particular country and we don't want our code to crash just because we don't have information about a particular country. So what we're going to do is check, we're gonna ask our map, the map that associates countries with life expectancy if they actually have a value of life expectancy for the country that we care about. And if there is such a life expectancy for the country we care about, then we go ahead and do our calculation that we just did, and we color the marker appropriately. But if we don't, then we want to have some sort of default setting for what that color's going to be, and remember when Christine was talking in her supplementary video about color codes, she mentioned that if we set all three colors, R, G, and B to the same value, then what we get is a shade of grey. So our default color for the marker is just going to be a shade of grey if we don't happen to have information about the life expectancy of a particular country. All right, we've done it. What we've done now is we've colored the whole world based on the data in the life expectancy file. And what's really powerful about the techniques that we've gone through in these three videos, is that really most of what we're talking about doesn't depend on the fact that we're talking about life expectancies. Any time we have a data file that tells us some values associated with country IDs. We could do exactly the same process and color the world based on all sorts of other information and data. So I hope now you're excited about doing these kinds of projects. What you might wanna do is look for additional data sets about things that you care about. Or, you could also punch right back into your project and think about how to use these techniques when you're customizing your markers and displaying the data that you're working with in the project.
