Maps & Filled Maps

Quick reference

• 00:04 In this video we're going to look at two of Power BI's maps.
• 00:09 We're going to look at the regular map visual as well as the filled map visual.
• 00:15 Now there is another visual that is currently in Power BI called ArcGIS maps,
• 00:20 this is a very, very complicated mapping visual.
• 00:23 We could do an entire course on this, so
• 00:25 I'm not gonna dig into this particular one.
• 00:27 I'm gonna start, though, with the regular old map.
• 00:31 Now the regular map, one of the big,
• 00:33 big pieces that you really wanna focus on here if you can possibly get it,
• 00:37 is you really want to use latitude and longitude for your mapping points.
• 00:43 And if you ever find that this actually says sum of latitude or something like
• 00:46 that, click the box here and change to make sure that it doesn't summarize.
• 00:50 You can't use an average or a max of latitude or
• 00:53 longitude in order to make this work.
• 00:55 So I'm gonna put my lat and my long in here.
• 00:58 And you'll notice that immediately, I actually see
• 01:01 the three data points from my location's table that are actually being mapped here.
• 01:05 And one big key here,
• 01:06 you must be connected to the Internet before you actually start this process.
• 01:10 If you're not, your maps will never render.
• 01:13 Even if you connect to the internet later, and you try slicing and dicing stuff,
• 01:16 your maps just won't show a visual, which is really unfortunate.
• 01:19 So make sure you're connected to the internet before you open Power BI.
• 01:22 You can use a location field by going into the power query editor and edit queries.
• 01:31 You can aggregate things like the street and the province and the country and
• 01:35 whatnot in order to try and
• 01:36 get all of that stuff into a nice little text stream that can be mapped.
• 01:40 One thing I will tell you is that, especially if you are outside the US,
• 01:43 the results that you get are very hit or miss.
• 01:45 This uses the Bing mapping engine and I have seen
• 01:49 all kinds of weird stuff happen with this, that get people very frustrated.
• 01:53 So if you can get longitude and latitude for your data, do it.
• 01:57 If you can't, well, then you may be resorting to going back and
• 02:00 actually merging columns together to doing that.
• 02:03 Now this is cool and everything else.
• 02:05 We can see our three data points.
• 02:06 It wouldn't be nice if they were a little bit bigger?
• 02:08 Well, sure.
• 02:09 So what if we did this?
• 02:10 What if we actually went and said lets make them bigger, but
• 02:12 in proportion to the sales dollars.
• 02:15 So I am gonna drag the size right on there and
• 02:18 notice now this doesn't tell me that this is this much bigger than the small dot.
• 02:23 What it tells me is that this is 1.5 million is the smallest,
• 02:26 this one here is 1.8 million and this one here is 1.81 million.
• 02:31 So these two are pretty close to the same size.
• 02:33 So really, it's not a perfect gauge to say this is the exact size,
• 02:38 but it does give you something to say which are my bigger data points and
• 02:41 which ones are my smaller ones?
• 02:44 We can also go and do some other things with this as well.
• 02:47 Something else that becomes really useful with maps is
• 02:50 when we start looking at this, we see, okay that's sales,
• 02:52 I can see the longitude and latitude, but what location name is that?
• 02:55 But why not do that as we drag location name and we'll put it on tool tips.
• 03:01 And you know what, what were there, why don't we grab budgets?
• 03:04 And put this on the tool tips as well and why don't we grab something like I dunno,
• 03:09 how about the sales units and put that on tool tips, lots of things here.
• 03:13 And now when I mouse over one of these little boxes,
• 03:16 you can see that the location is ethical development.
• 03:19 We can see that it's got a budget of 1.8 million.
• 03:22 Maybe I don't want this called first location name, though.
• 03:24 That's kinda gross.
• 03:26 Can I go back and rename this to just say location?
• 03:33 Absolutely.
• 03:34 So that looks much better.
• 03:36 Now that's the regular map visual.
• 03:37 There's a couple of things we can play with, color saturations and whatnot, but
• 03:41 overall I think you get the idea of how these things work.
• 03:44 Now I wanna show you the field map.
• 03:46 So let's grab the field map.
• 03:48 Now the field map starts with a location field as well.
• 03:51 So you know what I'm gonna do is, I'm gonna go back to my location stable and
• 03:56 I'm gonna say, why don't you show me the field map?
• 03:58 Let's fill my province British Columbia.
• 04:00 So this is British Columbia, Canada.
• 04:02 And you can see that when I drag that on, it plainly maps British Columbia, Canada.
• 04:07 No, wait it minute, no, it doesn't, that's Baja California,
• 04:09 what the heck is going on with that?
• 04:11 So this is a challenge, right off the bat you can see that BC, which is
• 04:15 pretty much known as our province is mapping to somebody completely different.
• 04:20 That's a challenge.
• 04:21 So how do we fix that particular problem?
• 04:24 Well, let's go and drop City underneath Province.
• 04:27 It doesn't seem to make any difference, and
• 04:29 yet, if I drill down on Baja, guess what?
• 04:33 It comes back in Vancouver, British Columbia.
• 04:35 This is just weird, okay, but it is something that ends up happening.
• 04:38 So let's go and drill back up here and see if we can fix this little problem.
• 04:42 If I had a country field above this,
• 04:44 if I started with Canada and then went into BC it would work.
• 04:48 Okay, so that's something that would work.
• 04:50 The other option that I have here, is that I can also go and grab, say a latitude.
• 04:55 Look at this, it's giving me an Average of Latitude, that's not so good.
• 04:59 So let's go fix this too.
• 05:00 Let's classify this data actually.
• 05:01 I'll go back to my data table, I'm gonna find my locations table,
• 05:06 and you'll notice here that I have latitude and on my modelling tab,
• 05:11 it's classified with the data category of uncategorized.
• 05:15 I'm gonna change this to be Latitude.
• 05:19 I'm gonna go to long and I'm gonna change this to be Longitude.
• 05:24 And now we're gonna go back over to our visual.
• 05:27 Now it hasn't changed anything here, but I'm gonna remove this average of lat.
• 05:32 We're gonna bring the Latitude back in, it still gives me the same thing.
• 05:35 Okay, it doesn't seem like there's much difference although it's using globe
• 05:38 instead of a number.
• 05:39 Let's put the Longitude on and that changes things right off the bat.
• 05:44 Now it actually puts it back in the right place, so again, Latitude,
• 05:46 Longitude you know information is really usable.
• 05:48 Having said that, if you just had country province city in your hierarchy,
• 05:52 that would allow you to actually get the right thing as well.
• 05:55 So I can drill in now into this particular data point.
• 05:58 And you'll notice that if I were to zoom all the way into Vancouver,
• 06:02 it actually highlights the region for Vancouver.
• 06:04 Now I'm not gonna go too much deeper with this particular map only because this one
• 06:08 really shades regions.
• 06:09 And it doesn't get too much more granular than getting into the city level.
• 06:13 Some post codes work for some things.
• 06:15 It doesn't for the Canadian data, though.
• 06:16 I can tell you that for sure.
• 06:18 So that's a challenge.
• 06:20 This is a different way of working with maps.
• 06:21 If you've got lots of regions, it can actually work out quite nicely.

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