Tableau 2020.2 Set controls full built out example
I'll rebuild this interactive London house price map from scratch so you can see exactly how 2020.2 set controls work end to end.
- Tableau 2020.2 lets you expose a set as a filter-like control by adding it to the filter shelf and choosing 'show in and out of set', so users can change set membership from a drop-down rather than clicking the chart.
- To compare a selection against everything else, build an EXCLUDE LOD that excludes the set dimension, then subtract it from the plain average to get a difference-from-average measure.
- Spatial data won't always be recognised automatically, so assign a geographic role (postcode) to the out code field and switch the marks card to a map to render polygons.
- A 'highlight to self' action is a handy hack to stop set actions fading out the rest of the visualisation, keeping context visible while you select.
- Set actions and set controls are applied at the dashboard level, not on individual worksheets, so build the worksheet first then add the change-set-values action.
- Finished product demo0:00
- Connecting the data and base chart2:27
- Assigning geographic roles for mapping4:48
- Formatting the map layers6:10
- Defining the analysis challenge7:27
- Creating the set and calculations9:22
- Adding context to the chart15:45
- Adding a date period filter17:47
- Building the dashboard and set actions19:26
- Highlight action hack22:42
- Using the new set control24:39
- Final formatting flourishes26:16
0:00In Tableau 2020.2 Tableau have added the
0:02ability for sets to be controlled with
0:05filter-like
0:06controls. I'm going to start this video
0:08backwards by actually showing you the
0:09finished product of
0:10what we're going to build right from the
0:12beginning. So here we have a map of London
0:14and we're basically comparing the
0:16differences in averages across prices in
0:19different sort of post
0:20codes. Okay so the cool thing about this is
0:22it's got set actions already applied in the
0:25background
0:26so I'm actually going to show you two ways
0:28of doing the same thing. When I select this
0:30particular region you'll notice that the
0:32chart changes and that's because it's
0:34comparing the
0:35average price against the selection that I
0:38've made. So when I make a selection it
0:40changes the
0:41comparison point and when I click on it
0:43again it actually clears that selection
0:45then just compares
0:46it across the average of everything. Okay
0:49so this makes it really really interactive.
0:51I can actually
0:52sort of click on a particular part of
0:54London and see well how do house prices
0:56compare against this
0:58particular selection that I've made or this
1:01other one here in E6. And notice as I do
1:03that
1:04the selection I make gets a label. We've
1:06also got this information here in the
1:09tooltip. You'll
1:10notice the difference from the average is
1:12zero because this is actually comparing
1:14itself against
1:14itself so there is no difference. Yet if I
1:16go to the one above it you'll see there's a
1:18difference
1:19of 53 000 pounds. Okay now the other thing
1:22you'll notice is that I've actually got
1:24that difference
1:25in average up here so you can actually see
1:28that comparison straight up. Okay so you
1:31can actually
1:31see the average price for the selection in
1:34this tooltip so you actually know what you
1:37're working
1:37with. There's a lot of context here. Now
1:39the new feature in 2020.2 is the ability to
1:43control this
1:44using a filter like interface. You can see
1:46right here that E11 there and E11 are the
1:49same and I
1:49can actually go down in here and tick
1:51another selection and notice that the chart
1:54changes. Now
1:55this doesn't quite work as well because I
1:59've got a set action applied over here but
2:02the selection
2:02only shows the mouse selection so what I'd
2:05have to do for this to work is select
2:07several and then
2:08you'd see the regions apply but then those
2:10are also available here and you can sort of
2:12play
2:12around with them and see how they work.
2:15Okay so this is quite a complex bit of
2:17analysis we're
2:18doing and in order to build it we have to
2:20kind of start right from the basics by
2:22building the
2:23very basic chart. That's what I'm going to
2:25show you how to do next. So the first thing
2:27we need
2:28to do is obviously connect to the data
2:30source and basically start looking at our
2:32data. So I've
2:33actually got a CSV file that I'm going to
2:35be connecting to here it's just on my
2:37desktop.
2:39If I go to my desktop here go to 2020.2 you
2:42'll see that I've got this London house data
2:45available to
2:45me. Now this example is actually modified
2:49ever so slightly from the beta test
2:51scenario that we were
2:52asked to test to test this feature if that
2:54makes sense. So I've made it slightly
2:56simpler for the
2:58purpose of this tutorial but it's
2:59essentially the same data if you've been
3:01using the Tableau beta.
3:02Okay so let's go into the sheet and you'll
3:05see that we have our data sources here on
3:08the left
3:08hand side. For those of you wondering why I
3:10can't see dimensions and measures that's
3:13because in this
3:13version the data model has been rolled out
3:16so that slight distinction between
3:18dimensions and measures
3:19is now only really seen when you try and
3:22drag items between the two sections. You
3:26can see this
3:26very subtle line that does that sort of
3:28distinction. Okay so let's start building
3:31our chart and I'll
3:32sort of talk through the problem as I build
3:33this and I really sort of ask that you bear
3:35with me
3:35as I walk you through this because this can
3:37be a bit of a mind maze but we're going to
3:39get there
3:40and we'll build this chart. So I'm going to
3:42right click my data source and then I'm
3:44going to take
3:44an extract. The reason I'm doing this is
3:47because it makes the data source faster
3:49okay so it just
3:50makes working with this especially in a
3:52demo that I'm doing right now much much
3:54faster and I know
3:55it's an extract because if you see here you
3:57'll see these two cylinders and an arrow
3:59going between
4:00them that lets me know that it's a Tableau
4:02data extract it's actually using the hyper
4:05file format
4:06okay. Now the next thing we'd like to do is
4:08to just visualize the information that we
4:12have okay.
4:12This can be slightly sort of cumbersome
4:15because I'm dealing with spatial data and
4:17yet I have no
4:18real information here that's that sort of
4:20signals spatial information other than a
4:23postcode and a
4:24postcode area. So let me just double click
4:26these and just see what happens. You'll
4:28notice that
4:29there's obviously an issue there so that
4:31doesn't work it's not recognizing the post
4:33codes properly.
4:34So what I normally do is I try the other
4:36one that I have in my data set just to see
4:37if that
4:38sort of yields different results and if I
4:40double click that as well you'll see I also
4:42have the same
4:43issue okay. So I'm having a slight problem
4:45here just basically figuring out what's
4:48actually going
4:48on okay. Now what I need to do is I need to
4:51actually define that this out code if I
4:54just
4:55describe this field here you see this out
4:57code this is actually the spatial
4:59information that I
5:00want to work with. So I'm going to click
5:03close and I'm going to go right click on
5:05out code and I'm
5:05going to go to geographic role and I'm
5:07actually going to assign this a postcode
5:10okay and when I
5:11do that then double click that you'll see I
5:14now get the spatial information that I want
5:16. So just
5:17always bear with the data source sometimes
5:19it's not where you expect it to be and you
5:21might just
5:22need to do some work to make things work
5:24out. Now you can see dots here and that's
5:27great because it
5:28tells me exactly where the centroid of that
5:31particular postcode is but what I'd
5:33actually
5:33need to do is actually make a field map. So
5:36in order to do this there's one place to do
5:38this
5:38every single time and it's the marks card
5:40over here. So in the marks card if you
5:42select the drop
5:43down you'll see you get different chart
5:45types and actually we want Tableau to not
5:47use the automatic
5:48suggestion here which is a circle and
5:51instead use a map and when I change that
5:53you now see that we've
5:55got the out codes nicely sort of shaped out
5:57. This information is actually held inside
6:00of Tableau
6:01has something called a Firebird database
6:03that has all this information and that's
6:05where it's
6:06getting the spatial information to draw
6:08this detail onto the map. Now the next
6:11thing we
6:11probably need to do is just to style this a
6:13little bit before we move on it's easy to
6:15do it now rather
6:16than later so I'm going to go to the map
6:18layers at the very top by clicking on map
6:20and then going
6:20down to this second to last option. Now
6:23once we're there we can add some detail
6:25onto the map.
6:26I'm going to add streets because that
6:28always helps to give some point of context
6:30on a map and you can
6:32obviously you know be more fancy with these
6:34other map styles but I actually want to
6:36keep this fairly
6:37simple and what I'd like to do is add some
6:39context that's relevant to what we're
6:41looking at. So
6:42I'm going to add the postcode boundaries
6:45and the postcode labels so we can sort of
6:47get a sense of
6:48which postcodes are covered and which aren
6:51't covered in our analysis. The last change
6:54I'm
6:54going to make is by making the border of
6:56all each of these shapes white so I'm going
6:59to go down here
7:00to the border options and I'm just going to
7:02select the white option and you'll see that
7:05that now sits
7:05a lot better and I might just change this
7:08transparency ever so slightly more just so
7:11that it's a little bit lighter on the eyes.
7:14Okay so we've done some basic formatting
7:16here now
7:17and we're pretty much ready to start doing
7:19our analysis and what is key here is sort
7:22of
7:22highlighting the challenge that we have so
7:24let's let's take another look at that in
7:26more detail.
7:26Now typically when you get to this view the
7:29first thing you do is you'd probably just
7:31take the price
7:32and place that on color so let's just do
7:35that very quickly and see what what issues
7:37we have. Well if
7:38I just put the price then obviously the
7:41area with the most properties is going to
7:43have the sort of
7:44largest price so we need to look at the
7:47average price okay so we need to go in here
7:49to this
7:50aggregation which is green here which says
7:52sum and we need to change that to an
7:55average and now
7:56that we've done that we're now looking at
7:59the averages and you can start to see where
8:01we have
8:02a little bit of an issue here because
8:04obviously in a place like London or even
8:06New York any city
8:07in the world there are going to be areas
8:09which have an average price higher than the
8:12rest of the
8:13areas and the point with this sort of
8:15analysis is that actually you know when we
8:18when we just think
8:19about this a second it's no use just
8:21basically always having the context driven
8:25by some of these
8:25more expensive areas you can see here that
8:28my legend here is sort of got a very very
8:31big range
8:32here and it's it's very difficult actually
8:34to make any sort of sense of this what
8:35would be more
8:36powerful would be if I was maybe able to
8:39select a region and then see how that price
8:42or the average
8:42price in that region compares to the
8:45average price in other regions okay so that
8:48would be a much
8:49better form of analysis but in order to do
8:51that we're going to have to build up a set
8:54of calculations
8:54that do a couple of things the first thing
8:57it needs to be able to do is to understand
8:59the
9:00selection we've made the second thing we
9:02need to do is to be able to calculate the
9:04average price
9:05not just for that selection but for
9:07everything else that we haven't selected
9:10and the last thing
9:10we need to do is obviously calculate the
9:13difference between those two things so in
9:15order to do that of
9:16course we do that in tableau using a
9:18calculation so let's go ahead and create
9:20these calculations now
9:21I'm first going to remove the price of the
9:24color so that we can just have sort of a
9:27neutral
9:28set of context and when I'm working with
9:30calculations for a long while I tend to
9:32move my
9:33calculation window all the way out just by
9:35dragging this line and moving it out as you
9:37can see that I'm doing here I then right
9:39click on any white space and I just simply
9:42create
9:42calculated field if you're wondering how to
9:45get this information tab open there's this
9:47little
9:48carrot here that you can just click open
9:50and that opens up this view here and you
9:52can just see some
9:53little hints I tend to leave that open it's
9:55a shame that you can't leave it open whilst
9:57you're
9:58resizing that so that's what I'm just doing
10:00there and now we're pretty much ready to go
10:02and start
10:02creating our calculations right the first
10:06thing we need to do is simply to create a
10:08set and actually
10:09in order to do that we don't need this
10:11calculation window so let's just go and
10:13right click create and
10:15set and that's pretty much it that we've
10:17created a set very quickly and the thing
10:20about this set is
10:21we don't actually care what's in it we're
10:24going to be dynamically selecting items so
10:26initially I'm
10:27just going to use all the options available
10:29to me I'm just sort of tick this option
10:32here use all
10:32and that saves me having to make some
10:35selections then click ok and now we have
10:37our out code set
10:38the next step is to create a calculation
10:42that basically checks that set to make sure
10:46if we've
10:46made a selection or not okay so this is a
10:49very simple calculation we basically just
10:51say if
10:53the item we've selected is in the out code
10:55set that's how you sort of define that in
10:58tableau
10:58then I'd like to look at the price
11:01essentially so we're just basically isol
11:04ating the selection
11:05and the price for that selection and that's
11:08pretty much it okay we can call this
11:11selected
11:13price or we can call it whatever we want
11:14okay so I'll just call this selected price
11:21then I'm going to hit ok so we've got our
11:23first calculation okay now the next
11:27calculation we need
11:28to do is slightly more complicated and I'm
11:30going to try and explain this as I type it
11:33what we need
11:34to do is basically calculate the average
11:37price for the selection I've made okay and
11:39we need to
11:40make sure that it's taking into context the
11:43selection it sounds like a bit of a tongue
11:45twist I'm using the same word to describe
11:47the same thing but really bear with me here
11:50I'm going to use
11:50something called the level of detail
11:52calculation okay and in this particular
11:54case I'm using the
11:55exclude function in that calculation okay
11:59and the thing I need to exclude from my
12:03aggregation in
12:03this particular case is the selection you
12:06can see here an exclude computes an
12:08aggregate excluding the
12:09specified dimensions if present in the view
12:12so you see here I've got my out code
12:14present in the view
12:15and I'd like to exclude that from my
12:18aggregation and the aggregation I'm going
12:21to do is going to
12:21be the average price for the selected the
12:24average for the selected price essentially
12:27so let's go ahead and type this out bring
12:32the out code I do a colon there then I do
12:35average
12:35and we're going for the selected price here
12:38okay and that's pretty much the calculation
12:41in a nutshell
12:42so just to go over that one more time I'm
12:45asking Tableau to do a calculation here
12:47where it calculates
12:48the average of the selected price the
12:51previous calculation we created excluding
12:54this out code
12:55in the analysis so what that will do is it
12:57will give me an average for everything in
12:59the
13:00visualization so we can basically pretty
13:02much compare that okay so let's just give
13:04this a name
13:09okay so we've got a calculation available
13:12to us here and then I'm going to click
13:13apply
13:14and now we can see that available to us
13:16just here now the last calculation is a
13:20little bit simpler
13:21we just basically need to do some math to
13:24get the average price this is just type avg
13:27type in price
13:28minus and this is a key one minus the
13:33average
13:37of the average price for selection if that
13:42makes sense okay and you're probably
13:45wondering why why
13:46on earth am I doing an average of an
13:48average well it's just because of basically
13:51the way this
13:52calculation works if we just remind
13:54ourselves what's inside of this calculation
13:56if I click
13:57inside of it you'll see here what it's
13:59doing is it's basically taking it's
14:01basically excluding
14:03this out code from the analysis okay and
14:05this average price isn't doing that so by
14:09doing that
14:09we create these two contrasting values one
14:11which only takes into account the selection
14:14that I've
14:14made mind you there's multiple sort of
14:16properties and cells in that particular
14:18sort of region that
14:20I select and then on this one on the one on
14:23the left it's not excluding the out code
14:25from the
14:26analysis so it's actually calculating the
14:28average price for each out code so you can
14:31add a comment
14:31here just to sort of make it easy to see so
14:37average price computes the average for each
14:44out code and the second one the average of
14:49the average price for selection
14:58computes just the average for the selection
15:03I've made okay so that's how you do
15:06comments in table
15:06it's very useful to add that in and I'll
15:08leave that into the calculation apologies
15:10for any typos
15:12while I record this I'm notoriously bad at
15:14spelling and so we just need to give this a
15:16name
15:17and this is essentially the difference from
15:20the average okay so I'm just going to call
15:22this
15:23difference from the average okay and then
15:27now that calculation is valid I can hit
15:31apply
15:31and now we have our calculation here on the
15:35left hand side we finish the bulk of
15:38calculations
15:39and now we can start adding this context
15:41onto the chart okay the next step is to
15:45bring a few
15:45more items into the visualization so the
15:47first thing we're going to do is to bring
15:50the difference
15:50from the average onto color and you'll see
15:53that that immediately colors some of the
15:55items okay
15:56you can see that it's an aggregate
15:58calculation and then the next thing to do
16:01is to bring the average
16:02price for the selection just onto the
16:04detail what this does is it brings it into
16:07context should we
16:08need to use it a little bit later on
16:10because we need to be sort of aware of what
16:12's going on when
16:14these these calculations are being done and
16:17so we want to be able to add a nice label
16:19at the top to
16:20share the values that are being used in the
16:23calculation now if I just hover over some
16:25of
16:26these you can actually see the calculation
16:28starting to work the average price for the
16:31selection is currently 723 292 and this is
16:35actually the total for the entire data set
16:38whereas for this property e11 the
16:41difference from the average is through 232
16:45701 so the thing that
16:47might make sense here to add might be just
16:50the average price so let's add that in so
16:53we know that
16:54value in each of these data sets so let's
16:57just make that an average we'll put that on
17:01the
17:01tooltip rather than on detail I'll just
17:03click on that small icon select tooltip and
17:05now you'll see
17:06here that I can actually see those values
17:10playing out the average price is 490 591
17:14and you can see
17:15it's a difference of 232 000 from the 723
17:19average across the entire data set so this
17:23is actually
17:23starting to do the job that we wanted it to
17:26do and now what it's not doing at the
17:28moment is when I
17:29select something you can see the values
17:31aren't just changing yet and that's because
17:32that's the
17:33kind of change that we apply on the data
17:36set when it's in a dashboard these are
17:39essentially actions
17:40that are applied hence the term set actions
17:42and set controls those are typically
17:44applied at the
17:45dashboard level now the last thing I want
17:47to do is probably give some date parameters
17:49to this so I'm
17:50going to drag date onto the filters okay
17:52and I'm going to use a range of dates and
17:55just click next
17:56I can sort of choose a bunch of different
17:59ways of doing this I'll click I'll click
18:01okay because what
18:03I'll do is I'll I tend to I tend to prefer
18:05to show these in a slightly different
18:07format so if I click
18:09on this drop down then I get this sort of
18:11nice period analysis right so I can
18:13actually say browse
18:14periods and that will change this sort of
18:18filter and if you choose over the last day
18:21well there's
18:22no sale in this data set that's happened in
18:25the last day or probably week or month but
18:27if I go
18:27back a year or maybe even five years then
18:30that really does bring into context
18:32everything that
18:33we need okay you can obviously change that
18:35again and maybe choose like a starting
18:38point and an end
18:39point or even just you know looking at
18:41these items I think the issue with the
18:44browse periods is I can
18:46actually probably edit it ever so slightly
18:49to anchor relative to the largest date
18:52rather than
18:53today I can actually anchor this relative
18:57to a specific period of time so I don't
19:00know when the
19:01last house sale was in this data set if I
19:05just look at this 2015 if we just go back
19:09maybe to
19:10let's just go back to 2018 I think that
19:13should cover us off pretty well then it can
19:16we can just
19:16restrict the data set that way so just go
19:19back to you know use that and then that
19:22should be just
19:22about fine yeah that's about right okay
19:25cool so now that we've got this the next
19:28bit of analysis
19:29we need to do is to make this a dashboard
19:32and essentially make it easy to be able to
19:35change this
19:37around so I'm going to create a new
19:38dashboard just by doing that then I'm just
19:41going to bring
19:41this sheet in and immediately it brings in
19:44all the controls that we're used to I'm
19:46also just going to
19:47zoom in if I remove this little pin here
19:50what it does is it makes the map fit the
19:53space that it's
19:54actually available to fit in okay the next
19:56thing I'm going to do is I'm just going to
19:58change this
19:59title a little bit I'll just call this
20:01difference okay you could use the
20:05percentage difference but
20:07I'm just going to use the term difference
20:09in this particular case and I'm also going
20:12to add a couple
20:13of things so I'm going to add the average
20:18price in the selected region okay and this
20:23value is going
20:25to come from this particular sheet okay so
20:28if you click insert and then go down to the
20:32average price
20:32selection it actually gets the value and
20:34inserts that into the very top and I'll
20:36just drop it down
20:37two sizes so it's clear that this is a
20:41meaningful sort of different subtitle so
20:43you can see there
20:44now that this is working and this is
20:46working really really nicely
20:52now the other thing I need to do is to
20:54actually put my set into the filters and
20:58the reason that is
20:59is because I'm going to be using some
21:01interactivity in this particular
21:04visualization and notice when I
21:06drag this in it doesn't actually it doesn't
21:09actually sort of present in the same way
21:12that
21:12I want it to present I wanted to show what
21:14's in and out of the set so what I'm
21:16actually going to
21:17do I'm going to leave this out and then we
21:18're going to come back to this when it's
21:20been built
21:20so we can you can see sort of the finished
21:23result and why the filters behave the way
21:26they do
21:26now the last thing to do is to add some
21:30actions if I go over here to actions then
21:34add an action
21:35and here you'll see a bunch of options the
21:38thing we're most interested in is to change
21:40the set of
21:41values okay and so what we're trying to do
21:44is to change set values that's what I'll
21:48name that
21:50and we want to do it on a selection so that
21:51's absolutely correct and the set we're
21:54trying to
21:55influence is this out code set okay and so
21:58when I make a selection it's going to
22:00change the values
22:01of this set it's currently got everything
22:04selected so the moment everything's in the
22:06set but when I
22:07make a selection one thing will be in the
22:09set or two things will be in the set and
22:10that will become
22:12it's our comparison okay so I'm just going
22:15to click okay and I click okay again and
22:18now
22:19as I make a selection you can actually sort
22:21of see that this axis up here is changing
22:26and you notice that the color range is
22:28changing you can just see it very subtly in
22:31the background
22:32but we we kind of have a problem here
22:33because because it's fading out the items
22:36we can't
22:37actually see the visualization so we need
22:39to do one more thing and this is a bit of a
22:41hack okay
22:42we go into the sheet and we just create a
22:45new calculated field and we're just going
22:48to call
22:48this highlight okay in fact this is already
22:51in the data set because I was creating this
22:56earlier on
22:56and it's baked into the data set into the c
22:58sv so I don't actually need to do anything
23:01here I can
23:01just bring this in but let's just assume
23:03that you didn't have that available to you
23:06you just
23:07basically need to type a calculation in it
23:09can be absolutely anything it can be you
23:11know elephant
23:12whatever you just need to create a
23:14calculation and just put some text inside
23:17of it sometimes I
23:19use the term all and that will do exactly
23:21the same thing so I'll do that I'll use
23:24this new one that
23:24I've created so you can just see the
23:26process okay and I'm going to put that in
23:28front of my item and
23:30then the last thing I want to do is
23:31obviously hide these headers so that you
23:33can't see that
23:34then when I go back to my dashboard and I
23:37go to dashboard actions I want to add
23:41something called
23:42a highlight action and if you just see here
23:44the second option here is a highlight
23:46action
23:46so when I click on that you'll see that I
23:49get this interface and basically what it's
23:51going to do is
23:52it's going to apply this highlight to
23:55itself so it has this effect of basically
23:58selecting itself
23:59whenever I make a selection okay and that
24:02was actually going to come first you can
24:04see there
24:04that it goes to the top I'm going to click
24:06okay and go back out and now watch what
24:09happens when
24:09I make a selection I actually maintain the
24:12context of the visualization it doesn't
24:15fade it out into
24:16the background so that's a nice little hack
24:18that you can use to sort of maintain
24:20selections if
24:21you're trying to sort of analyze some
24:23information and now you can see that as I'm
24:25clicking around
24:26it's calculating the difference from the
24:28average and you can see that as I hover
24:30around you can
24:31even see the average price for the selected
24:34region that I'm in okay okay so now that we
24:39've built
24:39this out you can see that we now need to
24:41get onto the new feature which is the set
24:43control this
24:44selection is working but the whole point of
24:46this feature is that I can actually choose
24:48these just
24:49by using a drop down filter which is
24:51similar to sort of this sort of interface
24:54up here so let's
24:55go ahead and just figure out how to do that
24:57if we go into the sheet what I need to do
24:59is bring this
25:00out code set into the filter pane okay then
25:03I need to change that into a show in and
25:06out of set
25:07sort of option okay and I'm just going to
25:09again use all and click okay and then go
25:12back to the
25:12dashboard and then when I go back to the
25:14dashboard you'll see now that I have this
25:16option to show the
25:17set control and when I click on that I now
25:21get the full list of items that are
25:23actually available in
25:25the set and you can actually see that
25:27everything is ticked so right now it's
25:29comparing everything
25:31against the average of everything and when
25:33I make a selection here in this case e17
25:36you can see that
25:37that selection changes to e17 if I do the
25:39same again for e11 you can see it changes
25:42there and so
25:43on and so forth so you get the idea this
25:45control is doing exactly the same as my
25:47selection so let's
25:48have a go at doing that let's deselect
25:51select e2 there you go select e3 there you
25:54go and the great
25:55thing is is this has uh sort of the
25:57capabilities of a normal filter I can
25:59actually even do a single
26:01value drop down which would make the most
26:03sense here because you never want to really
26:04look at
26:05multiple items at the same time in this
26:07analysis you can just go down here and
26:09choose different
26:10items and you can see the chart is updating
26:12a little bit more okay and so that's pretty
26:15much
26:15the feature in a nutshell okay we've pretty
26:17much built everything we need to build out
26:19the only
26:20thing we've got left are some flourishes to
26:22make this a lot clearer to see you can see
26:24here that
26:24the color range is a little bit sort of
26:26extraordinary because it's sort of all
26:28skewed
26:29towards one end so I'd like to make this so
26:31that the legend is a little bit more
26:33balanced so we can
26:34just go ahead here and edit the colors and
26:37we can actually change this a little bit so
26:39we can set it
26:40to be you know go from minus 500,000 and
26:44end at plus 500,000 so anything over 500,
26:49000 which is
26:50pretty much I you know more than I could
26:53ever afford that will automatically sort of
26:57go to
26:57that end so now you have a much much more
26:59balanced scale and you can see that that
27:01immediately
27:01improves the way this chart works and now
27:04as we start to use some of these items here
27:07it's much
27:07much much easier to see okay now the other
27:10thing to make sure is to make sure that you
27:13know the
27:14legend is the right way around like when I
27:16select this option here you can see here
27:18that the
27:18difference does correctly reflect the
27:21direction sometimes you can end up with a
27:23legend that
27:24incorrectly sort of reflects what's what's
27:26going on in terms of the range just make
27:29sure your colors
27:30line up where red is not so good and blue
27:32is a little bit better we're not using a
27:35red and green
27:36because of being sort of colorblind aware
27:39for those who have visual impairments now
27:42the other
27:43thing we did in the initial example I
27:45showed you is we added a label for the
27:46selection so
27:47that's actually done inside of the chart so
27:50if I go over here you can see that I have
27:52this label
27:53option but what I need to do is essentially
27:56bring the out code itself onto the label
27:59okay and when
28:00I do that you'll see it labels every single
28:02one and that's not what I want to achieve
28:04so what I
28:05do instead is I go back into label and then
28:08I have some options here of how to apply
28:11those labels so
28:12I'm only going to choose those that are
28:14selected okay and then now what that does
28:16is when I make
28:17a selection that label shows up and then
28:20when I deselect it disappears if I select
28:22multiple items
28:23they all show up too so it's much much
28:26easier to see what's going on so now let's
28:28go back to the
28:29dashboard and when we click on an item we
28:31can see that that's the case and now that's
28:34working
28:34exactly as we expected and it's much much
28:37much nicer way to sort of play around with
28:39this data
28:40and work and so that's pretty much it we've
28:42rebuilt the chart that we started out with
28:44and it's much much easier to see sort of
28:47what's going on if you've enjoyed this
28:50video thanks for
28:50watching hit the like button hit subscribe
28:54and I'll catch you in the next video.
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