[light upbeat music plays] Hello and welcome to another DAVis workshop! This workshop is going to be about using shapefiles in Tableau. If you want to access the files that
are used in this workshop, visit this URL: libguides.uta.edu/DAVis Scroll down to the "Tableau Workshop Files" box.
Choose the "Tableau: Shapefiles" tab, and you will download this Excel file, and visit
this link, and click "Download" and "Shapefile." It will download a zipped file to
your computer, and you will leave it that way. So, let's get started. We are going to
use COVID-19 data for this exercise. To connect to the data, you're going to
click Connect "To a File," and you're going to select the DFW cities file. What this
file shows are coronavirus 2019 cases in the various cities in North Texas. We
have them arranged by county, by city - I'm going to change this to make sure
that it recognizes that that is the city - the number of cases, number of deaths, and
number of recovered in each city. So, this is my data, and Tableau allows for states,
zip codes, countries, and other polygons already existing within Tableau; however,
it does not include cities in its database. Since Tableau does not include
cities, I went ahead and used a public city shapefile, which comes from the
Texas Department of Transportation. I came here to download the shapefile and, um, you can also get familiar with the variables
that exist in the file by clicking on any of these boxes. OK, so, once you have that shapefile downloaded, you're going to go into Tableau, and you're going to add a new data
source. In this case, Tableau considers it a spatial file; so, we are going to call it...
Click to connect to a spatial file. In this case, I'm going to choose the Texas
Department of Transportation city boundaries. Notice that it's still in the
zipped file format. We're going to choose that, and we're going to open it.
Now, if your files are [not] overlapping - data that don't have a particular area where they join -
let's say one is in zip codes and the other is in counties, then you can do a
"Create a Join Calculation," where the first equals 0 and the second equals
1, and that will allow you to do a full outer join where those data do not align
with one another, and that will allow you to map them on top of each other. However,
in this case, we are going to use data that do align, and, in this case, they
align based on city name. So, in the first dataset it's called "Location," and in the
second, it's called "City Nm." And now it's going to join based on matching those
city names. So, you can see here where the Location is DeSoto, City Nm is also
DeSoto, and it appends that information. I'm gonna go ahead and do a full outer
join. The reason I'm doing that is because I want to keep the other cities
in Texas as a just-in-case. If you are 100% percent sure you're only going to want
those North Texas cities, you can do a left join that would only include the
data from basically that left dataset. Once your data are connected, you can go
to your first sheet, and you can start using those data points! From your shapefile, you can double click geometry or drag it on to the sheet, and it will show
you all of the shapes that you have in that file. Now, one thing about using a
shapefile in Tableau is that it automatically aggregates measures. So, it considers all of these shapes one singular thing. So, you can see when I
highlight my mouse, it highlights everything. We want to break it up by
each city, of course. So, then, if we go up here to City Nm and move that to "Detail."
Now I can look at each city as its own separate thing. This will come in handy
when I want to start looking at coronavirus cases by city. So now I can start using my other dataset which were the actual cases, deaths, and recovered.
So, for example, I could drag Cases to "Color." And, now I'm starting to color my dataset by how many cases there are. Please note, it assigns a color to everything.
So, even if there are null or zero cases, it is still prescribing it a color. In order to filter for that, I can move Cases to "Filters." I'm going to do SUM
because some cities exist in multiple counties, and I have that data in my dataset.
So, I want to add up all of the cases for the entire city, regardless of which
county it falls in. So, I'm choosing SUM, and then I am going to say it needs to be at
least 1. So, it needs to have at least one case. and then hit OK. So, basically what happened is
it's limiting back to North Texas So that you can see that all
my data are in North Texas and so you can see which cities
have how many cases. I can add things like the City name to the labels so that they're labeled. Typically, when I do this, I'll kind of remove extra ones that... All of this information is available if you highlight over it, and sometimes, since
some of these shapes are kind of oddly shaped you might want to get the wording
in the middle so that it's clearly shown. An example of that is Dallas.
Dallas is this dark shape which kind of crosses Garland. So we'll want to move Dallas onto, kind of,
its main area. Now, you can more clearly tell that
that's Dallas. You can keep doing this to clean up your dataset. Once you get it to, kind of, how you'd
like it to look, you can increase the size, the text. You can change the font,
make it a little bit more easy to read. I also sometimes like to make the
font match what I'm showing. So, I can do Cases to "Size," and have a little bit of a difference
between the size of the font to emphasize those with more cases. And just like that, I have
a map of cases in DFW. Now I can edit the map.
I can make it dark. You can edit the map and change the colors
how you like them to be. Edit the tooltip. So, let's create another chart! This time, we're gonna do deaths. So, I'm going to drag Geometry onto the screen, I'm going to drag City Nm onto "Detail," then I'm going to drag Deaths onto "Size." And this time, I'm going
to do Circles to show the number of deaths. Once again, just to be accurate, since we don't have data for the rest of the
state, I'm going to only include those with more than 0 or at least 1. You can add the name of the city,
increase the size of those bubbles. I can make the color. Since I want this color to
match my other map because I'm gonna put them together, I'm going to go in and copy the color
from the first map. I'm going to go here.
I'm going to find out what this hex value is,
I'm going to copy it, and then I'm going to put it into my new map. OK. I'm going to add the number
of deaths to the label. To put the number
in the center of the circle, I'm going to click "Label" and then
under Alignment, I will change it to centered and middle. I will also make the font bigger. I'll make it bold and white. ...maybe a little smaller. I'm going to also duplicate this. You can't tell, but there's
actually a line here. And, I'm going to "Map Layers"
and make this one dark as well. So, we can see. Can't really see the numbers here.
So, I'm going to make them black. On my second chart,
I'm going to remove the numbers. I'm going to change it to a shape. OK, I'm gonna change the color. Move this from "Color,"
and make it white. Make it a little bit bigger. And for this one, and I'm going to add a
label of city name. I want the label to be
back where it normally is and then I'm going to overlay these. I'm going to go up here and
click "Dual Axis," and now you can see they have
like a little white glow and the number is in
the center, and the name of the city is underneath. Let's see what happens if we
allow Mark Labels to overlap. I think that's okay,
a little bit of overlap. It's not bad. I'm going to rename these maps by right-clicking the tab and calling it... Cases and Deaths in DFW. Now, I put my charts together on a
dashboard. This can be shared via Tableau Public. It can be shared via Tableau Server
or however you'd like to share it with your intended audience. Thank you so
much for watching!
