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Here even so I hope you get that debate outside.

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And if you don't get that then follow the lecture.

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So we are now done with the joint plot.

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I have removed that one.

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You can also use any other NTSB file him like if we go for notes NTSB No.

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So consider dot here then this one don't and don't.

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So this one also need to be dot there.

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And David go with that one.

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Here we have one two three.

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Okay that's fine.

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Now the thing here is what the joint plots are joint plots or something like they will plot every possible

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plot available in the dataset.

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Like here if we have three known numeric Itanium Rick values that is 80.

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These all these LPT this firing it and this coherence then it will provide trained 2 3 9 possible combinations

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of deployed that is time with coherence time with fighting date coherence with fighting firing rate

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and there with them said like time with time time with coherence and fighting date with fighting date.

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And maybe you get that now.

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So it's simple like a sentence don't bear bloat and just pass the data set like dots here and then it

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will take a time and then you will get destroyed.

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So here if you notice we have nine possible combination like time with time then time with coherence

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then time with fighting date then we have coherence with time coherence with coherence coherence in

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food filing.

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Similarly all treated fighting date.

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So this one is a pretty one used to install.

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So we used to analyze all the data at once and there are fewer patients with that and that's why there's

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a separate video for debate upload like here.

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If you have any no numeric column like if I print that one here I have t1 t2 so here I have two things

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to an end to do and endorse.

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I have also to take things that is dose and sec so I will consider the choice here.

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So now here if you do not able to analyze the data and second thing if you analyse the data according

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to the choice.

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So here you can also include the parameters like the two benefits that already included the third one

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you can include here is the No no medical columns and that is included by using X you eat and then the

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pasta column like choice here.

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If you run that one you will get different graphs with choice and so if you do an entry two separately

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like even those denoting blue t two are those denoting orange and this one you will get like here we

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had choice and coherence or retirement coherence in which we have first all the oranges.

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And here we have also the oranges.

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There is no blue or maybe they are below them.

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So this is how you can separate according to a new numeric of mode you would understand.

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Let me consider the first one also that is just let me copy this one and one more thing.

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Never upload a load any two types of data in the same cell a device you will get there and your notebook

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will get crash.

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So here I will have tips and then this one tips and then as soon as.

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Don't be a float first.

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I also need the column so hey I have tips dot head they.

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Now as soon as Dot bear glowed

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and then here we have tips and I will separate them according to like here.

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This one sex there.

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So hey I will write at you.

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E And this will be equal to sex death.

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Now if you read that one you will get this one here.

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The blue eyed denoting male orange denoting female.

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If you do hear a smoker that is smoking also have two there.

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Then you will get something like

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let me say here.

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This one with the smoker and nonsmokers why I have included tips now because tips have this day which

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have more than two parameters so adding more than two options there.

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So if I include here day and run that one then you will get all this bill blowed separated with different

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days like Thursday Friday Saturday Sunday that we have in our dataset and all they are in different

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colors like blue or red orange and they are written here.

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So that's how you can get a perfect visualization of the data and that's why people pay for using their

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blocks so that you will easily get D1.

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Also there are few things you can do with that one.

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Like what if I need total bill and size bloat in some other like in this plot or in scattered abroad

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or in KDE bloat and I need these into any other different kinds like I need total bill and total bill

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in bar chart.

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What I mean is something like here you can also do a few more things that is first I need to provide

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a variable here.

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This one in a variable that is X and.

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Okay.

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Move it.

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So now hit return or enter and windows.

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And if you're also doing the same thing that I am doing here.

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Make sure you are doing again in the same cell.

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Don't use a different.

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Otherwise it will not work.

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Let me also show you that one.

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Like here.

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I use just X dot a map.

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Function here then map underscore and then provide value.

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Want to have like if I want to have all the charts here in the diagonal as the dist blobs like all the

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are in now key day or I need a person in that one.

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Like if I can't see the upper and then what are these three at a bus that are about the diagonal.

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These three are lower and this one is diagonal so you can choose anyone like you if I choose up here

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then defenses and then use a sentence.

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Note the type of plot you need like if I need based plot.

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So here I have this plot run that 1 and you will get data that is something unexpected.

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No not that error.

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You get the output missed most in prison will not leave in an eddy.

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So let me have here diagonals that is d i.e. a g denoting deep diagonal and then run that one

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so wait for that is present.

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So here we get that.

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So if you notice here we have the least plot on the diagonal and you do not get that same on the upper

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part and the reason for that one is I am using the best plot and this to is a point plot in which you

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must use only one parameter.

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So here in the upper and lower triangular parts I am getting two different parameter but on the diagonal

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I have seen that is total bill total bill to tip tip on this one and what is on.

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Size and size on this one.

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So that's why I get the ordering at a man I'm using the least plot on the upper.

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But you can use any other ball type of plot there.

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Like.

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Let me show you.

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But before that something else.

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Like if you do this thing here.

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Just run that in a variable it will still get the plot output.

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Here it is.

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And if you try to run the thing knowing the different cell and on that one you will get added.

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So that's what you need to focus here.

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Make sure you are using the same plot.

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Now let me convert all the upper ones indicating a plot that is X..

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Note map underscored the above.

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Then as an as Dot KDE E block simple like that.

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And then on that one.

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Now it's processing don't focus on this one.

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This is just that particular warning.

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Now here it is processing and giving me warnings

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00:09:12,910 --> 00:09:16,270
and there they are getting warnings and warnings again.

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Let me read that one and use a different set.

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So here I have Saudi.

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Forget that one also.

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So this is the one that we are getting here.

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The key to applauds uploaded here.

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Also the scatter plot.

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Because I have not remove this one and plotted appeared brought there.

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So I hope you got the idea.

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Now how did things work.

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You can also change the lower ones into KDE.

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That is just right.

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Lower here and run that one.

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Now we will get that one

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wait for that one to be processed completely.

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Again warnings mornings and you can also remove that one so that you would just get either the gate

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00:10:07,930 --> 00:10:12,180
plot or the list plots that I will tell you later.

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00:10:13,740 --> 00:10:16,300
So here we go the output line.

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Now we will guarantee results.

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So here's the deal result lower the KDE implodes and apparently again scattered about the middle ones

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are the list blocks.

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00:10:27,120 --> 00:10:31,820
So I hope you get this one now that debate plots are and how they work.

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So thanks for watching.

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This one is a little boring one because you get to L.A. but this one is important one so please stay

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00:10:39,660 --> 00:10:44,720
focus while you continue this video and if you do not get one then go to the video again.

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So thanks for watching.

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I would assume the next video.