All language subtitles for 007 Analytical Features_en

af Afrikaans
ak Akan
sq Albanian
am Amharic
ar Arabic
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bem Bemba
bn Bengali
bh Bihari
bs Bosnian
br Breton
bg Bulgarian
km Cambodian
ca Catalan
ceb Cebuano
chr Cherokee
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
ee Ewe
fo Faroese
tl Filipino
fi Finnish
fy Frisian
gaa Ga
gl Galician
ka Georgian
de German
el Greek
gn Guarani
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hmn Hmong
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ia Interlingua
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
rw Kinyarwanda
rn Kirundi
kg Kongo
ko Korean
kri Krio (Sierra Leone)
ku Kurdish
ckb Kurdish (Soranรฎ)
ky Kyrgyz
lo Laothian
la Latin
lv Latvian
ln Lingala
lt Lithuanian
loz Lozi
lg Luganda
ach Luo
lb Luxembourgish
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mfe Mauritian Creole
mo Moldavian
mn Mongolian
my Myanmar (Burmese)
sr-ME Montenegrin
ne Nepali
pcm Nigerian Pidgin
nso Northern Sotho
no Norwegian
nn Norwegian (Nynorsk)
oc Occitan
or Oriya
om Oromo
ps Pashto
fa Persian
pl Polish
pt-BR Portuguese (Brazil)
pt Portuguese (Portugal)
pa Punjabi
qu Quechua
ro Romanian
rm Romansh
nyn Runyakitara
ru Russian
sm Samoan
gd Scots Gaelic
sr Serbian
sh Serbo-Croatian
st Sesotho
tn Setswana
crs Seychellois Creole
sn Shona
sd Sindhi
si Sinhalese
sk Slovak
sl Slovenian
so Somali
es Spanish
es-419 Spanish (Latin American)
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
tt Tatar
te Telugu
th Thai
ti Tigrinya
to Tonga
lua Tshiluba
tum Tumbuka
tr Turkish
tk Turkmen
tw Twi
ug Uighur
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
wo Wolof
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu

Original subtitles

In this lesson, I'd like to have a look at the analytical features that we can use with our graphs.

Now, previously in the course I mentioned that we had the analytical features, which is this icon

across here.

Now, I also mentioned that you cannot use this with our tables, with our matrices, and with our cards.

It doesn't give us any options.

However, when it comes to our graphs, we often do get options that we can use for this.

So we're going to explore this in a little bit more detail.

So I'm just going to change these graphs a little bit, just to give an example that we can use.

So I'm going to delete that bar graph and let's just make this one a little bit bigger and we're going

to remove the region from here and let's just make it a clustered column.

So we're back to showing our sales by manufacturer.

Now, there's some certain things that I might want to do with this.

For example, if I had a reference line at my average point, it would make it easy for me to see which

manufacturers are above average and which manufacturers are below average.

So you see that if I go across my features, I can then see that there's different types of lines that

I can add into this, and one of them is actually my average line.

So when I select my average line, I would say apply settings to I'm going to add a new line so you

can actually have more than one line with these as well.

We just need one line at the moment.

You can change the name of this.

I can just click on the edgy on the edit button and we could just say this is going to be my average

line and you'll see that I'll put a hyphen in there, I'll put a dash and you'll see it a little bit

later as to why I've done that.

Also, then we're going to say what series is it going to apply to?

In this case, I've only got the one series, which is my sales.

However, you may have more than one series in your graph.

You may have sales and profit, for example.

You'd say which one?

And the next question is what type of line do you want to use?

So I can change the color of this.

I'm actually going to go for a darker color just so that it sits, sets out quite clearly.

We're going to use a darker gray can change the transparency your style.

You can also change.

I'm kind of fan of the dotted line.

Just show a dotted line across there.

To be honest, actually, maybe go for it slightly.

Not so great.

There we go.

There probably sits not too badly.

It doesn't take away from looking at the graph, but it does now show the user quite clearly with the

average pointers.

You can also say, where do you want the positioning?

In this case, it makes sense to be in front just so that it goes across those lines.

Right.

A dead label we're going to set on for this and where do we want it to be positioned?

We're going to put it on the left.

And you may see that we've got a value that's been put on here.

Not particularly easy to read because the color is the same as the other color.

So we're going to make that black just so it sticks out a little bit better.

That's where we go.

So the vertical position is we're going to have it above the line, could have it under also the star.

Now I'm going to actually say I want the name because you can do the name.

And the name is what I call this right at the beginning.

And you may remember I called it Avg Dash.

There was a reason for that.

When I say both, now you'll see that it's now showing on here a v g dash and then the value that is

actually the average.

So you can see also that you could change your display units.

In this case, if I wanted it to have be millions, then it would be a bit shorter.

But if you're using this with different filters, it may be better.

The fact that you just keep it as auto and when the filters apply, then you may not have the wrong

format in there.

So there we go.

We got now an example of a data line.

I'm going to just collapse that.

And what I want to show an example of, you'll see that I've got my avg dash here.

But earlier on in the course we looked at our slicer, so let's just add a slicer in here, just as

an example to see what happens to this when we filter our data.

So I'm going to go up and let's say we want to put our region into our slicer, get our different regions.

So you see that when we filter our data that the average now is recalculated obviously to show the average

for the data that is being shown, this is quite useful.

When you recalculating those values.

So there we go.

There's one example of using a analytical feature.

Let's look back at some of the other options.

So the first one over here is the ability to create a constant line.

Let's just remove this filter just so we got the full values.

Now, say, for example, you wanted to show a reference line at 6 million.

You could just add a line in here, and that line would then always stay at 6 million.

So that's basically what the constant line would do.

The min line will show you a line at your minimum value.

Now, in this case it would be northwind traders.

It wouldn't really make sense to put it into this graph.

But sometimes when you go quite a lot of items on a graph, you may want to just show what the minimum

value is and the max works the opposite.

The max would go to the fabric cam, which is the highest value and would put a line there.

You also have a median line.

Sometimes you're comparing your average against your median.

Your median is your middle value within the range of values.

So it would actually put a line against the middle value out of this.

Right.

In this case, our average looks pretty close to a median, but in sometimes it's not the case and you

may want to have the median line.

For example, one of the options that I do like is your percentile line.

So what are your percentile line allows you to do is to say, I want to show where 25% of the values

are below the line.

Or I might want to show where 75% of the values are below the line.

So let's start off.

Let's create a line for 75% value.

So we're going to add a line and we're going to call this 75%.

Let's just edit that.

Try that again.

75%.

There we go.

And again, our series is going to be the summer sale.

In this case, we're going to use a line.

I'm going to use a darker line just so that it sticks out.

So you can see at the moment that the color has gone, but the percentile has been set to 90%.

So I'm actually going to change this and say we want this set to 75.

Just be aware.

One of the things that's it's not great with is often you've got to delete the values here.

So just make sure when you're entering the values, sometimes you find that you've actually got to use

this thing.

There we go.

We'll get to 75.

So we go to 75.

Now, what is showing me is that 75% of values are now below this line and 25% of the values are above

the line.

Again, from a bit of data analysis, this can be quite useful.

And what we could add is another line.

And we want to see where 25% of the values are below the line.

So we could add a second line here.

And again, I could edit this and I could say 25%.

Of the line.

And again, now with this one, we go back and we say the percentile, We're going to go choose 25%.

Hopefully we'll get to that value.

There we go.

And again, I can change the color and let's make it a dark color.

So now what is showing me is it's saying that this line, 25% of the values are below the line and 75%

of the values are above.

So it just helps you a little bit with your data analysis.

So as you can see, there's a couple of analytical lines that can help you with your graph.

And what you'll see is obviously as you filter this, is that the dynamic?

And that will change according to the filtered data.

It just gives the user some nice reference to be able to use and really at any point, if you want to

remove these can just go into them, become the delete percentiles, delete these if you wanted to and

you can easily remove them as well.

Okay.

There we go.

We're going to conclude the lesson there.

I will see you in the next one.

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.