Here even so I hope you get that debate outside.
And if you don't get that then follow the lecture.
So we are now done with the joint plot.
I have removed that one.
You can also use any other NTSB file him like if we go for notes NTSB No.
So consider dot here then this one don't and don't.
So this one also need to be dot there.
And David go with that one.
Here we have one two three.
Okay that's fine.
Now the thing here is what the joint plots are joint plots or something like they will plot every possible
plot available in the dataset.
Like here if we have three known numeric Itanium Rick values that is 80.
These all these LPT this firing it and this coherence then it will provide trained 2 3 9 possible combinations
of deployed that is time with coherence time with fighting date coherence with fighting firing rate
and there with them said like time with time time with coherence and fighting date with fighting date.
And maybe you get that now.
So it's simple like a sentence don't bear bloat and just pass the data set like dots here and then it
will take a time and then you will get destroyed.
So here if you notice we have nine possible combination like time with time then time with coherence
then time with fighting date then we have coherence with time coherence with coherence coherence in
food filing.
Similarly all treated fighting date.
So this one is a pretty one used to install.
So we used to analyze all the data at once and there are fewer patients with that and that's why there's
a separate video for debate upload like here.
If you have any no numeric column like if I print that one here I have t1 t2 so here I have two things
to an end to do and endorse.
I have also to take things that is dose and sec so I will consider the choice here.
So now here if you do not able to analyze the data and second thing if you analyse the data according
to the choice.
So here you can also include the parameters like the two benefits that already included the third one
you can include here is the No no medical columns and that is included by using X you eat and then the
pasta column like choice here.
If you run that one you will get different graphs with choice and so if you do an entry two separately
like even those denoting blue t two are those denoting orange and this one you will get like here we
had choice and coherence or retirement coherence in which we have first all the oranges.
And here we have also the oranges.
There is no blue or maybe they are below them.
So this is how you can separate according to a new numeric of mode you would understand.
Let me consider the first one also that is just let me copy this one and one more thing.
Never upload a load any two types of data in the same cell a device you will get there and your notebook
will get crash.
So here I will have tips and then this one tips and then as soon as.
Don't be a float first.
I also need the column so hey I have tips dot head they.
Now as soon as Dot bear glowed
and then here we have tips and I will separate them according to like here.
This one sex there.
So hey I will write at you.
E And this will be equal to sex death.
Now if you read that one you will get this one here.
The blue eyed denoting male orange denoting female.
If you do hear a smoker that is smoking also have two there.
Then you will get something like
let me say here.
This one with the smoker and nonsmokers why I have included tips now because tips have this day which
have more than two parameters so adding more than two options there.
So if I include here day and run that one then you will get all this bill blowed separated with different
days like Thursday Friday Saturday Sunday that we have in our dataset and all they are in different
colors like blue or red orange and they are written here.
So that's how you can get a perfect visualization of the data and that's why people pay for using their
blocks so that you will easily get D1.
Also there are few things you can do with that one.
Like what if I need total bill and size bloat in some other like in this plot or in scattered abroad
or in KDE bloat and I need these into any other different kinds like I need total bill and total bill
in bar chart.
What I mean is something like here you can also do a few more things that is first I need to provide
a variable here.
This one in a variable that is X and.
Okay.
Move it.
So now hit return or enter and windows.
And if you're also doing the same thing that I am doing here.
Make sure you are doing again in the same cell.
Don't use a different.
Otherwise it will not work.
Let me also show you that one.
Like here.
I use just X dot a map.
Function here then map underscore and then provide value.
Want to have like if I want to have all the charts here in the diagonal as the dist blobs like all the
are in now key day or I need a person in that one.
Like if I can't see the upper and then what are these three at a bus that are about the diagonal.
These three are lower and this one is diagonal so you can choose anyone like you if I choose up here
then defenses and then use a sentence.
Note the type of plot you need like if I need based plot.
So here I have this plot run that 1 and you will get data that is something unexpected.
No not that error.
You get the output missed most in prison will not leave in an eddy.
So let me have here diagonals that is d i.e. a g denoting deep diagonal and then run that one
so wait for that is present.
So here we get that.
So if you notice here we have the least plot on the diagonal and you do not get that same on the upper
part and the reason for that one is I am using the best plot and this to is a point plot in which you
must use only one parameter.
So here in the upper and lower triangular parts I am getting two different parameter but on the diagonal
I have seen that is total bill total bill to tip tip on this one and what is on.
Size and size on this one.
So that's why I get the ordering at a man I'm using the least plot on the upper.
But you can use any other ball type of plot there.
Like.
Let me show you.
But before that something else.
Like if you do this thing here.
Just run that in a variable it will still get the plot output.
Here it is.
And if you try to run the thing knowing the different cell and on that one you will get added.
So that's what you need to focus here.
Make sure you are using the same plot.
Now let me convert all the upper ones indicating a plot that is X..
Note map underscored the above.
Then as an as Dot KDE E block simple like that.
And then on that one.
Now it's processing don't focus on this one.
This is just that particular warning.
Now here it is processing and giving me warnings
and there they are getting warnings and warnings again.
Let me read that one and use a different set.
So here I have Saudi.
Forget that one also.
So this is the one that we are getting here.
The key to applauds uploaded here.
Also the scatter plot.
Because I have not remove this one and plotted appeared brought there.
So I hope you got the idea.
Now how did things work.
You can also change the lower ones into KDE.
That is just right.
Lower here and run that one.
Now we will get that one
wait for that one to be processed completely.
Again warnings mornings and you can also remove that one so that you would just get either the gate
plot or the list plots that I will tell you later.
So here we go the output line.
Now we will guarantee results.
So here's the deal result lower the KDE implodes and apparently again scattered about the middle ones
are the list blocks.
So I hope you get this one now that debate plots are and how they work.
So thanks for watching.
This one is a little boring one because you get to L.A. but this one is important one so please stay
focus while you continue this video and if you do not get one then go to the video again.
So thanks for watching.
I would assume the next video.