Original subtitles

Welcome to this lesson.

In this lesson, I'd just like to take a little bit of time to look at some other visualizations that

you might use in your reports.

So as you've seen, there is quite a wide range of visualization options that you've got.

So the first one that I want to look at is our pie chart.

So the pie chart is quite commonly used to be able to show a contribution.

So it's showing us how much something contributes towards the total.

So if we ever look at our wells, we can see we've got a legend, we've got values, we've even got

something called details as well.

Let's start with the legend.

Let's say we wanted to see our product category and our sales.

So we want to see how much does each product category actually contribute to the total of the sales.

So you can see straight away now it's created our pie graph and it's got quite a lot of useful information.

It shows us our product category, the color that it is.

And then also we've got the metric and the percentage that is being displayed.

So let's just have a quick look at our formatting and see how we can change some of these options.

So in the general you would see it's the normal options that we've got, the properties, the title,

the effects.

So I'm not going to worry about that.

We're going to move across to our visual.

So the first part is do we want to show a legend or not?

So I'm actually going to miss that for now.

What we're going to do is we're going to jump down to the detail labels that we're using.

So these are kind of like our data labels that just called detailed labels here so we can keep them

on.

And you can see that currently they're on the outside, which is right.

We've got them situated over here.

But the big one here is what is the label contents that we want to display.

Now, one of the things that I would suggest is that you actually have your category and your percentage

of the total being displayed.

So a paragraph should always be used to show percentages.

You're showing how much something contributes to the total, how much it contributes to the whole.

So this is called contribution analysis.

So when we turn on the category in the percentage of total, you can now see from the label which item

it is cameras and camcorders and what the percentage is.

Now this is much better than trying to match what the color is and then figuring out from your legend

what the item is.

So by setting this label to this makes it just much easier to understand our paragraph.

Now, the second part is we can now go to the legend and we can actually turn this off.

And now you'll see that you have a lot more space in your paragraph.

So as I said, we've now got this labeled.

We can now see how much each of these items are actually contributing to the total.

Now you will see that there's also formatting that you can never look at for your slices.

So basically, again, if we wanted to change the colors of these, I could go through and change it.

Also, if you wanted to change the rotation and the way that this actually is displayed, then you could

change that as well.

This is useful sometimes if your labels were not showing in a way that is easy for people to read.

For example, this tends to actually work quite well because now I can see these two values, which

were not that easy to see on their original rotation.

So sometimes it's worth playing with this if you're not able to read your labels very easily.

But that's the key part about the pie graph is basically that you just want to set it so that you're

showing your labels and your percentages.

Let's have a look at another type of visualization, and this one is called the tree map.

So if you look at the tree map, you'll see that the tree map allows us to create different rectangles.

And the rectangles now represent the size of how big or small something is.

So again, let's say, for example, we've got our country and our category, and we also now want to

share how much profit that it shows.

So you can see now we've got the country, we've got the profit mentioned.

The United States by far has the most profit.

You can see some of the profit there go China, Germany, France.

And you can see now that as the rectangles get smaller than basically the values that it's representing

are also smaller.

Again, there are some formatting options that could ever look at here.

So again, if you wanted to, you could have a legend for this.

I don't think it's particularly useful because we've already got the label on there, so you could use

that again if you wanted to.

You could change all the colors that have been used.

Or we've also got our data labels I'm going to turn the data labels on and you can see that this is

actually quite useful because it now shows me my values.

So you've got your values and I'm actually going to make this a bit bigger.

And then you can see that that actually shows quite a bit more.

Also, maybe give it a couple of decimal places, you get a bit more detail and precision to the total,

so that can be useful.

I would keep the category labels on.

If you turn them off, then you're not sure what you're looking at.

So just much better to have them on.

So there's another type of visual representation that you can use, which is the tree map.

So another type of visualization that we can use is a geographical one.

So you'll see that you've got a map option.

Please note that there might be some security to this, so you may get a warning just telling you that

you need to enable an option in your global security.

But I'm going to select that.

We're just going to get our map and we're going to pop that in there, make a nice and big.

And in this case, it's asking me where the location is.

So we're actually going to use our country as the location.

And you can see if you've got latitude and longitude data that you could use that as well.

So in this case, what's actually happening is that it's taken the country and it's used the Bing mapping

engine to try and find where their country is.

So most of the time I'll get it right, but sometimes it doesn't always get the data 100%.

Whereas if you're using longitude and latitude data, then you can definitely see that again, we could

pop something into our bubble size.

So we say that the sum of sales now and you can see that the bigger the bubble just means, the bigger

the amount of sales that we've got.

And when something like this, you can actually drill into it.

We want to drill into Europe and you'll see that obviously the map will then change as you drill further

and further input, you do get some formatting options that you can play around with with this.

So with the map settings, you can set the top styles.

So if you wanted to see an aerial one, if you wanted to see the dark version, see.

Greyscale and the road was, I think, the default we were using.

Also, do you want your controls so you can have the auto zoom on?

You can use Zoom buttons.

Also lets you, if you wanted to be able to use the rest, to pick specific data points to drag into

and turn that off.

And now they just have the zooms and also with the bubbles can change the toughest size that you're

using.

So if you wanted to make those bigger and smaller.

And we wanted to make them a bit smaller with the with that see, which is your colors that you're using.

Also, do you want any category labels if you turn those on?

And you can see that as we drill into this, you'll get your different information of your countries.

So a few options that you can play around with.

Also, do you want to use this as a heat map now?

Because the United States is so big, you can see that it's got its bubble.

It's difficult to see probably see in China that it's also got it's there.

So, yeah, because the values are so big, the heat map here wouldn't be particularly useful.

Bubbles would be a better option of using.

So there we go.

We'll stick to our bubbles.

So something to play around with.

If you wanted to, you could take country out of here.

If we wanted more details, we could pop it in our city and you could see your different cities.

And again, we wanted to.

To drill down into this and see a bit of detail as to how much is on the.

Just remember here you can use your tooltips and all those other functions that we use just to be able

to see the data.

So that is your geographic option that you could use.

So we're just going to delete that.

So really, that's just showing you a couple of other visuals that you can use.

I am going to do a couple of more lessons just on a couple of other visualizations that you might find

of use.

But really the big thing is now that you've got a chance to understand the visualizations, see how

they work, it's really a bit of experimentation and seeing which visuals are going to work best for

the type of data that you're going to be showing.

We're going to conclude the lesson there.

I will see you in the next one.