 In this example, let's work with a pie chart. First, let's select our pie chart from our type at the top. We'll work with a data element. We'll work with the HIV group that we worked with previously, looking at the HIV test performed. Let us separate this into the different HIV service types that are available. We'll only select one period. And similarly, only one organization unit. With a pie chart, we cannot really select multiple periods or multiple organization units to appear on the same chart. Let's add in the HIV service types. We'll go down to the category and add the three HIV service types in. Now let's discuss the layout a little bit. In the layout, we see that there is still the category, the series, and the filter. This is a bit different when compared to the horizontal chart we were working with earlier. That had a very well-defined x and y axis. So what happens in the case of pie charts? This is why we use generic terms such as category and series, as we are not able to define specific terminology for each chart type. Let's have a look and see how these terms apply to a pie chart. The categories are essentially the individual slices of our pie. The series and the data are really not so relevant. The series and the filter are quite interchangeable in this case. Typically, we just want to leave the data as our series. But in fact, it doesn't really matter. And we'll show you the application of this back in the visualizer tool. Now we are back in the data visualizer. We want to separate our pie chart based on the HIV services. So we want the HIV service to be the slices of our pie. Let's move the HIV service down to the category. Remember, I typically said that the data can be put in the series dimension. Let's go ahead and update the chart and see what happens. We can see that the data is present regarding the number of HIV tests performed by these individual services. We see here the organization unit name and the period. Let's go back to the layout. The output indicates that our organization units are filtered first, followed by the period. Let's swap the periods with the data in the series. If I click on update, we see actually the same values appear. In this case, it's not really too important what appears in the series. As long as our category is correct. Now that we've gone to the trouble of making this pie chart, we might want to download it so we can use it later on. Just like pivot tables, charts can also be downloaded to our computer for use. If we go to download, we will see that there are a number of different file formats available. We will focus on the image and PDF formats that are underneath the graphics header. There are a couple differences between the image and PDF formats. For starters, an image might be the right format if you just want to quickly place this in a presentation. You can of course take the PDF format and place it inside something like a presentation, but a couple extra steps might be involved. Let's open up these two formats and discuss their differences a little bit more. First, we can click on image. This will download to our computer and we can open that up. The image format is a carbon copy of what's available in the data visualizer. Once we start to zoom in, however, we start to see that some parts of the image get a little bit blurry. This is because the image is static and is only at a specified resolution, so once we start to zoom in, it loses a bit of detail. Let's go back to the data visualizer. Let's now download the PDF format. So clicking on download again, and then we see the PDF format. If we open this up, we can see that it's a little bit clearer, especially when I start to zoom in. I notice that there is no loss in quality. This is one of the key differences between the two file formats, as the PDF allows you to scale up the image without any loss in resolution or quality. We're back in the DHIS2 data visualizer. Let's continue with another example to show you some more features of the data visualizer.