Here we go.
So here we are with the last bloating that is known as the metric.
They're a little different from the all we have learned before.
Because with that we can use distinctly the data sets and broke them.
And I have classified them according to point and distribution and figured but now we will move to this
one.
Here we have two data sets.
That is first the tips.
The one we are using in most of the cases you will get this one here we have seven columns in which
we have two numerical columns and four string type columns.
Then we had this on flights.
And if you print the head of that one you will get a simple data set in which we have only truculence
to denoting numerical values one denoting strings.
So this one is a little easier to use here.
You can also use an other dataset but I'm going to use this one.
So first of all if you go to the gallery you will find here we have to solve metric bloat that is first
to the heat map this one second one is the cluster map.
Any payload which is showing values like these here you will notice corresponding values to every particular
through and column.
These are denoting metric dots.
And one more thing they are not known as the plots they are known as the maps.
This thing here any thing that we are going to work with Dedmon require maps instead of plot they are
parameters like color etc are also different that we are going to discuss here.
Hey if you notice we have a bar here which is showing the amplitude with color like light to the color
higher value 606 is the maximum.
And later devalue darker the value lower the amplitude.
So let's just move to this one.
One more thing now we cannot just directly applaud that.
Like if I write Come on S.A. dot heat map and then I provide just like tips.
This will show me at a and if you focus on the Edit here you will find a better.
This is something a little different maybe you will not get a vibe bloating in bloating you will just
get syntax errors then you write something unnecessary like this thing here syntax ETA you will get
value add a but not the type that type something when we have used different kinds of data from that
one that is required there.
And here these datasets are required to be changed in metric dataset.
After that we can use these with the heat maps and based on the conversion we have two methods.
There is first one water.
Second one is known as the pivot method both of which we are going to discuss here.
First one is this year you are a simple one but not used.
This one is something like if I have tips and I make this one do so that it will be different from that
one you just need to write the original one that is tips don't seawater Francis.
Now this dip is converted into metric.
If you print that one you will find a metrics they some drawbacks in this metric like you do not have
all the values like here I have three of the new one so the numerical columns that only present here
but did not contain all the values like here we have only nine values that they are values like something
corresponding Total Total will one day one say sized one because the variation with them self is always
same then we have the tip the total bill and here we have with totally opposite one but the values are
same there.
So that's why it's not use because it lacked the values.
If you do the same with the flight like I have flight.
And this will be flights don't see order princes you will get flight to like this one only four values
but now you can use these values to plot like just use here send don't heat map now you re not required
to explode here because here the map is doing the same thing it's mapping the values now just provide
tips you will get an idea as soon as don't it map so that when I have again done with the tips do original
value converted values tip.
So for that one Navy go here we have the heat map showing all the nine values available in that one
if you do same thing with the flight to just NASA send us don't heat map then the princes and David
go with that one shift and then you will get this one so minting it lacks the values that why we don't
use this one.
But let me show you some of the modification you can do and these modification will be same with the
method to also Lego's DePalma does seem so teaching you that one on a little graph is more easier and
if you notice these two look pretty similar but he has more values he doesn't have and one more thing
if you notice there this one is with the flights the same day as a I'm using but it has only four values
and it has approximately 144 values that is twelve go straight so how do values out there.
So that will is something we can do the second matter but before that here like if you want to have
the values denoting to particular of these boxes like these values when I had to at 115 so you can just
do and not a barometer here and make this one true shift return you will get two values
same with this one you will have the values if you can notice diagonals are 1 1 and the corresponding
values are different.
These are two seeing these two same these two same after that if you need some separation between these
boxes like you did not equate attachment NAND you can just straight line winds make sure you are also
using SDM and make this one then you will get the arrows attributed to let me check out Dedmon soda.
I have made a spelling mistake here that is w I'd be SD.
This one is to.
So sorry for that man.
I got a little mistake while typing.
So there we have the separation in between them.
You can also reduce or make larger deception and if you notice that both sides are decreasing while
you're increasing these like if I have this one 3 under the hand we do not have the boxes.
And if this one is like hundredth again we do not have let me have some value like 50.
So if you notice the box are decreasing the disease that that's the thing here that this seismograph
is not increasing only the values are decreasing.
So make sure you are using a value that will not affect the value these values.
And instead of writing this long thing you can just write LW There denoting language.
You can also make these languages colorful just by line color and provide this one like any value read.
This one is right now.
If you write here blue this one is blue now.
If you write black this one is black no.
So you can modify this graph in any way.
After that if you want to change the color of these values.
So here you going just use color like this one.
And cool there.
If you press shift return you will get added.
Also if you use the palette method you will get the edit because these are not thoughts.
These are maps.
So here we use see map denoting color map shifted and you will get the change you can provide any change
you want to.
I could go on this one so this is about the modification you can do in any graph.
Now let me move to the second method.
So to move all these value so that we can have a look at the head there.
So we go.
Just this one more.
Now this method is known as the fluid method.
This is also simple.
You just need to have this flight to and we are going to a good flight to here now.
You can also do with the tips but I'm going to pay for this one because it has only two columns.
Do you have to specify the columns so go for the simple one and you can also try that one device here.
It will take more time.
So you just need to write
first deflate.
Then we have to the it underscored.
Here we have different options here.
We are going to use a table option there.
You can check out either by googling that one then we need to provide an index.
That's what I'm telling you here that you have to provide the columns.
But here we have only 2 so we are not required to focus on that which one to choose.
So here just provide index that is these rows which are mine.
Then we have the columns E M and the values will be passenger.
So here we have the month.
Then we have the columns.
That is CIOL You add minus.
And this one is going to be easier.
Then we have the values
these are like the passengers one thing and they and I need to tell you make sure you are writing these
in quotes so she is done.
Now here we have the data in the metallic form.
And if you bring that one like flight two you will get the data in metric form.
Here we have the e months.
These are years months and the values.
You can also do the same thing with the dips.
You just need to have data like if I have a store this one
then we have dips and then don't be it technical in this one.
Come on C and come on we did just jeans this one like you need to do.
The total bill
and this one like a day we had the sun and then this one day and the values must be a little different.
Let me have the raw data.
This one day and this one totally shifted on that one.
And if you run the dips to
Saudi note at the rate that we have displayed here this is the reason I have not used the tips because
in most of the values there you will get.
And the reason for that is it may be possible that with the values of so many total below in any size
you do not have any particular day value of something like that.
So definitely some tips.
And if you want to use these sorts of flights and if you want to use tips you can also go with that
one.
Now here we have flights to this data and you can just do no S.A. dot.
So the heat map heat map and then this data flights to and flight day we go here we have the same map
as the sun.
If you notice here you can have the same barometers there like elder blues equal to one.
And let me have the color is equal to go.
There we go.
Here we have this one so you can modify the heat map in the way you want to.
So this is about the heat maps how you can change the data.
So make sure you have converted the data.
Otherwise you will get added and make sure you are using proper kind of data so that you will not get
any empty values if you use this one with tips too.
Like here we have tips to use their tips too.
Yes.
That is and shifted on that one you will get something like that.
Because of missing values.
So make sure you are using the proper data and am again focusing on the tips because I need to show
you that what happens when you use improper kind of data.
Now here we have the heat map.
After that we are done with this one move to second one that is cluster map.
So these are the cluster maps and very easy to use.
You just need to first convert the data.
Like here we have the data converted and then used it.
David S.A. don't just cluster a map here instead of heat map and provide the data flight to.
And then we have shifted down we get this one.
This one is a little loud.
Let me change the color that is see map there.
And this one called
so here we have this one now a little view or that how it's working.
Like if you notice on the basic note these thing if you notice this line it's divided into two segments
net is these six and d six and there's a difference in both.
Like these are light and these are darker.
Then we have this line it's again divided into two parts.
This one and this one it can be divided in like something this one instead of this one we have this
light on so that the four lines will be lighter and one is darker.
But in that case the separation is like here we have two here we have four the submission will always
been paid of two and maybe the different one but all will be the same.
So that's why this light blues here this light blues here and separated by a dark one here we have this
one dark and this one a little darker than this one is a little light but they all are darker than this
one.
So I hope you got the idea that what I want to see here that these lines are dividing the values according
to their amplitude or any variation like here we are using the values.
So they are using the amplitude to divide the lines and if you notice here we have 1949 Navy Hymn nineteen
forty nine then followed by 50 51 52.
But here we have 50 men 53 54 51 52 59 60 57 something randomly.
That's because if you notice on the graph we have darker values here in the last that are 1960 here
but we have these darker at this point.
That's why that is because if this one is here then this ambition is not visible properly.
So that's why we have these roots.
They are just used to separate values in different forms.
And this one is also less used because it's a little less efficient because of this thing.
Columns are separated randomly.
Here we have also the bar showing the values amplitude according to the colors.
So this is all about the metric dots.
I hope you got the idea.
And they're very easy to use.
Just you need to convert the data into metric type and then just go with the flow right hate medal plus
to map and provided better images.
So thanks for watching.
We're done with this.
And it's in the next video.