In this session, we will discuss about data visualization, data visualization is a tool which helps
us in locating the data visually.
So we will be reading several blogs and learning how we can create blogs using the most frequency use
libraries, which is my third clip, and see what my blog has extensive number of functions which allow
us to change, even though my new details of the plot, which we are creating.
And it takes a number of line of votes to bring those plot lines when we are working with C one, it
helps in creating a lot more beautiful plot in a more concise number of line of.
So we will learn both of these and see how things work out for this.
So the first thing which we will be doing is we will import the required module, which is my dog fight
block, and we will name it as blocked, this would be our Eleusinian.
So let me in for this now, what we will be doing is here we have x axis values, so I have deleted
certain X values, which is one, two and three and four responding by values as two, four and one.
Now we will be plotting these ways, using like dot plot and we are living in the values X invite to
it.
So, ladies, just like this, much of the.
Lines of code for now.
So when I ran this, I get just a single line here.
This single line does not have any name or any labels, what you can see here is just the values one
for to.
Then do up for.
I'm sorry, Obama one.
Now, next, what we will be doing is there are a few more functions like Lord X label, X label allows
us to provide a label for the X axis, and while it will allow us to provide a label for the Y axis.
So this is just the name which would be printed in front of the X and Y axis.
Next is the title which allows us to give a title to the plot.
Along with it, we have the option to sell the blood group if we want to say this, true or false.
So let us put this as false for now and we'll just run this.
So when we run this envelope, so forth, it brings the Y axis, the x axis, the graph name.
Let me.
Change this, so now it is giving a grade on top of what you can see, these blocks have been highlighted.
So this is the grade, which it has noted for us.
Now, next, what we will be doing is we will be plotting two lines instead of one line in a song we've
got now, the process remains the same.
We will give the X and Y points in the plot dot plot and we will give them leave before the line.
Similarly, we will give the X and Y values for the second line and we will give the label for the second
line.
After this, we are giving a lot of thought, maybe this will give the next level to the Lord itself
is inviolable for the y axis.
And the other thing that I did, do it again.
Now we will learn the religion, this plot basically plots this small block on the right side, which
will give us what life actually represent.
Which particular line?
No.
So this is what has been Peter and I, just coming this way, so now you can see that no legend has
been printed.
So this that legend basically allows us to create the legend.
Now, the next option here is.
To select the axis value, so again, we are giving X and Y values and along with the X and Y values,
when we are giving the plot details, we are giving one more Nevius to it.
Now, initially, what we used to give was we just used to give the X and Y values.
And along with it now we are giving more details like what color do we want to have?
What color lines do we want to have then?
What type of line do we want to have?
We do we want to have a continuous line or we want to have a dash line, then the width of the line,
then the marker, which we want to use the face of the marker, the color of the market, which we want
to use and the size of the market.
So this is the floor which has been created to allow.
Let me reduce the size of the.
So this is the plot which has been delayed until now.
Now, what we can do is let me remove this as of now.
So now you can see if I will change the board of the line nine and so it will just change the way it
is.
It is more doctor.
And now I just change it back to three.
Now, my is basically the size of the door, which we are able to see so we can change it to a smaller
value also.
So you can see the SOCOs, how small a smaller size now and I just change the size 12 and the market
would change to any other.
So I'm changing it to a star.
So it is changing into a star now.
So same as the color of the market is still here.
I can change 220 so that you will be able to see the color model so you can see the color again.
Now, for the same things I've been through, I provided with is the violin with an X, this violin
with the next movement will basically increase the range of the access which we have currently.
We have one to six and one to six.
I would the access.
Now, what we are asking it to be is one, two, eight.
Next is viable label in the title, so let me run this again.
So now you can see the limits have been changed and the exercise has changed from one to six to one
to eight to.
Now, the next things which we have is, again, we are giving just the name is different.
So initially we were giving X and Y values.
Instead of that, we have just given right and left.
Now, this is the same thing which we have provided now.
Now, the plot is different now when we use a plot line for us.
Now we're using Clodagh, but.
This means that people want to plot Barcia.
Now, what does a bar chart bar tried to something which has the bars for the frequency of the values
which we have here, so that the values which we have is one, two, three, four, five.
So for these values, the frequency of Ballston, the frequency of two is twenty five.
The frequency of three is thirty five.
So we have these frequency values.
So the same thing that we have provided here.
So we have provided one, two, three, four, five, and we have provided the height of the bar which
we want to have.
Identical labels is just the labels.
Would you want to give for these values.
So if we would not have given this, it would have simply shown one, two, three, four, five.
But we wanted to give the actual tape.
So we gave these values to.
Now, what we are doing is we are simply saying goodbye, which means, please, a lot of our flight
and for Varjak, give this X value, give high does value, then these are the big labels which you
want to flog.
The victim of the plot is Point East.
And these are the values which you want to have.
We can have given any colors.
You.
Now, here we have the verdict so we can change the world today.
Also, let me put it as one point nine.
So if you're on this so you can see the weight of the plot of the bars has fezzes, I can reduce it
also now, so I have just reduce the rate of the blood on the jacket.
So and these values may actually be available data.
These are just the same things.
And not to simply lotting the.
A lot on this trip, Daniel.
Now, the next thing.
Now we are plotting the histogram.
Now.
This bar chart simply thinks the values from the heights here and similarly histogram will also do the
same thing.
It's the only difference which we have here in case of his program is that we will provide certain values.
And from these values, it will break out on the basis of a certain range, I think, of frequency for
the ranges.
So we are giving the agents and we have given a list of agents here, and based on these ideas, we
have given a range that we want to have.
It is from zero to hundred.
That is why it is creating a plot from zero to hundred.
They are giving the vinces Benzi is basically the present how large we want these bars to be.
Now, how we do that, I just show you in the white.
Then we give the artist, which means that has to come now for this Instagram.
We want it just to be in the X-axis.
We want Vince to be in the Y-axis.
Always remember, first we will give X, then we will give Y value.
Then we provide the range.
Then you provide the color, then we provide what type of Instagram do we want, we want the bar chart
type always to come, and this is the word that you want to have.
So let me change the post.
So let me have it one point so you can see the word has changed.
Let me make it back to zero point now.
And the world has changed, but now the Belsize is five, which means that I want to have five bars
here one, two, three, four, five.
Now, what I could have done is I could have reduced the number of bins.
So let us say I just want to have two bins.
So when I have two bins, the frequency increases.
The number of people in the first one is now 16 and the number of people in the second one is almost
six.
Then I have the vinces, the 20.
What happens is now the highest number of frequency which we have is five and others are subdivided.
So how precisely we want to see is dependent on the number of bits.
If we want to see for a smaller range, then we will use the larger bean size if we want to have a view
of a larger means.
We want to view data for a broader sense.
Then we will use the smaller bins.
So let us get back to the five minutes now.
So this is showing for a larger space.
So it is showing the range from zero to 20.
This particular 20 to 40, this particular it was showing for the smaller, smaller amount that the
five within that.
Now, other things remain the same makes me believe I live in L.A. or.
Now, again, let us get back now.
This is the X and Y value, and the block which we are trying to block now is Scatterplot.
Now, Scatterplot is again taking the similar kind of input values would just X and Y values then the
label, what kind of label we want to have.
So the label is then the color is green, the marker which we have.
Is stars here, and this is the size of it, so I would have like thirty three hundred also, so now
the size has increased.
Now, the legal simply means, what is the name of the Markovitch we want to have so we want to give
this stock so that is why we have these funds.
Now, these actually bilabial didley is just the same thing.
And Florilegium is, again, the same thing.
Scatterplot is simply what gives us a market at every point, at every data point.
So actively explain why it gives the market.
This is what the scatterplot.
Now, the next kind of plot which we will be talking about is the five plot, so by plot will basically
give us a fight.
So in this fight, we have, first of all, defining the labels, which we have.
So the labels are these activities, which is easy, Wolf.
And then the portion of time or portion of each label which has been covered is also given.
So it is three seven, eight six.
So it will Kanwar this are these values and find out the percentage of area of the pie and what should
be given to this much sleights.
Then these are the pilots for each Eataly.
Now, what we do in case of blood is we give the slices values, we give the labels that water labels
should be given, we provide the colors, then we provide the angle that we want the starting gun going
to be 90 degrees.
Then we give the Shadowfax false.
So let's say instead of 90, we wanted to have seen it see 180.
So it changes initially it signaled something which actually had nine people think of the need of it,
but now it has been something which is nearer to 180 degree angles.
So let's say we wanted to have a smaller angle, say one hundred, so it will decide accordingly.
So it has one hundred degree angle and beginning with a 100 degree angle.
So for more like looking, we will just select 90 degree because 90 degree looks better with you.
Now, the next thing which we have this.
We will have the shadow, so we are putting shadows false so you can see there is no shadow behind if
I make this as true.
It adds a shadow to the speech and it gives a 3D look.
Next is the explored option.
Explored option basically allows us to have this thesis pulled out of the plot itself.
So if I just change this to zero point three, this one until then, it will be a lot more.
And if I give this as itself, then it will be just a part of the.
And one point is the radius of this block, and this is changing to automatically percentage for.
Then legend will allows it to create a legend.
So if I had just done this.
It was the legend again, now how we provide the size of the blocks, how we decide where the site should
be, is is done by the Lord God religion.
So we are doing it if using this legend and this is the location which we want.
So we are seeing that we wanted to be at the center live.
So let we not give this as of now.
And on this, so now it is President Sando and it is president of the left.
Now let me change it to center right.
So it goes to the center right now.
I want to change the location of it, so I want to change the box location to one and.
Let's say zero point five to zero point five.
So it goes by.
I wanted to be one.
And zero point five, so its location is slightly more changed.
I wanted to have one point five and one point five, so it goes outside.
So it is from the center of the block.
This exercise has been decided so you can modify it and decide where you want this legend to be.
Now, the next block years are simply using a sign.
So in this we are simply creating a function.
So I am randomly selecting the values of X and we are randomly creating the Y values based on these
X values and we are simply plotting.
So it gives us this function.
The next is we are generating plants based on the coordinates, so I'm just giving a function here and
this function is generating four types of plants, which is already flawed cubic lorden.
But they fly, and this is one thing where you can find out different types of stylesheet stylesheets
is just how we want this block to look.
There are different color schemes which are present so you can select from different color schemes from
this particular website.
And this is the plot, not style, which we are currently using.
And now the most important thing.
Now, what we have been doing is we have been plotting just one single thought in the area.
Now we have to decide how we can have multiple plots.
Created in a single figure, so that is what we are doing now.
So what we have to do is the first thing that we do is we declare off the good.
We let my relatives know that we have to create a figure, so we say feel good and we believe that my
figure needs to have a subplot.
And for that, what I do is I feel that my subplot has to be us to cross, to make Rick's my subplot
has to be a fog of cross to matrix and legacy.
This is Michael rostral matrix.
Now, here's what I wanted to have, is I want to see a trustful matrix, so it creates a matrix like
this.
First of all, we declare a figure so it knows that we want to create a figure.
And also that figure we declare that I want to have a two plus two matrix.
So it should have.
One.
To.
Three.
And full portions, so this is one, two, one, two, so this is like two cross two and it has four
subdivisions.
So out of this Blue Cross do anyhow, it will have four subdivisions.
So what I learned is that in this figure I had a subplot and one that subplot has to be it has to be
two women who do find one, which means that it has to be this two plus two one section, this one section.
It has to meet after that.
When I say good, I don't add subplot to Bill to this means that in this to graspable matrix, pick
out the second one for me.
Then when I say I got I've subplot two to three, it means that out of this to Matrix pick out the code
works for me now.
And similarly to do for me from the book was to pick out the fourth one for me.
So based on this, we provided that I wouldn't float one or two or three or four to be like this, and
after that, once we have provided, then this should be my blog, then I would love not be destroyed.
So what I do is I simply get the X and Y credentials and these X and Y values.
I put it in Duflot one dot plot and I put the X and Y values and provide.
Similarly I get the X, X and Y values and get the block to and in plot to I be X and Y values.
And so.
Now.
While I do this, I also give the title and by giving the title.
We have this mathematical function available, which basically allows us to provide subscriptions to
Facebook, so whenever I'm writing something between these dollar signs and I am using the underscore
inside this, so whenever I'm using an underscore, it understands that this number was just following
on whatever characteris has to be made a subscript and whatever is followed by this bovver site is a
superscripts.
So similarly, this one becomes a subscript deal and this too becomes a superscript you.
Everything is is just the same.
We simply have this sick title.
All these values and apart from that, we have this figured out subplot.
And just so we are giving the height and weight spaces so I can give.
Point two also here, so you can see one side you point to this will change gradually.
See, the space between these has been decreased a lot, so I'll just simply give one on one here so
that it has sufficient space.
Now, the next thing which we will be doing here is we are creating a group saying now this is one method
of creating a grade one method of plotting different.
Figures together adding different floods to a single figure.
Now, another way of doing this is define us in red size.
So this is my size.
When I say to me, Grosseto, this means that I want to have to be rows of data and two columns.
Now, what I'm seeing here is my finger size has to be 12 for my eight.
So it has to be 12 portions.
Call eight portions.
I'm out of this.
What I want to have is that they're zettl pharmaceutically stopping.
Give me a call, Spanel, and we'll spanel who and make it up.
It's a good one.
This is one.
I'm aware, glad I have this great size starting from zero.
Give me a portion.
As to and wherever you go, no one is stopping, give me a portion extra.
So let us see how this works out.
So here's what we have is we have up to the four million, which means there's this complete image is
created out of three rolls and two volumes.
So although this we are selecting we are starting from zero point zero, which is the origin point,
this particular point I'm from this I want to have two volumes.
I thought this is two column I thought out was a little three.
So let me change it to.
One volume and one.
So now you can see that one problem is this much so this is Tuvalu's and Thoros area, which we had
earlier given to the this X one.
Now, let me do one thing, let me change it from.
Two one zero one one one zero.
So now the figure which was present below has moved up.
And now what I can do is I can also change the size of it.
Eigen.
Change the size to.
I want to have calls been asked to.
So now the columns fan of this one has been pleased to do so, similarly, you can fix the size of the
grade and point at which location do you want the finger to start back and where you want to have this
particular plot to start the subplots to start.
So similarly, we have created another plot here.
And in this plot, I have given the size of 11 Gunma one.
And this is the position which I have I have selected from a zero and from zero point zero.
I have given a rule span of three and a span of one.
And and based on that, I have given this kind of distribution.
So this is the distribution which I have received finally.
So you can try different combinations of rule span and call span and find out what or how this actually
works.
Now, the next type of figure which we have is a plot stack plot basically allows us to create plot
with just that one over the other.
So I have this particular plot for East Asia and that is the plot for Eurasia and another plot for East
Asia, Oceania, Asia, which is plot one over the other.
So what I have done is I have simply created certain values of years.
Orangy and are the.
So this is the X value, which is the year and the Y value is basically this Orenda plus orangy.
And the Lebas is East Asia, Eurasia and Oceania, and this is the 29th.
This is the legendary location.
This is the Lislevand and this is the Slimer, what I want the cinema to be.
And based on this, I have just started this entire thing.
I be brought into sackcloth.
Now, the next thing what we can do is we are plotting a combination of lots.
So what we have simply done is we have simply said we want to have a figure and in that figure we want
to have subplots and these subplots should have in rules one and volume two, the number of rules is
one, the number of columns is two and the total figure sizes also provided.
So based on there, it will automatically subdivide this.
This particular area, based on these plot and we are simply giving that X one should be a scatterplot
and these other things for the scatterplot, then X2 should be a histogram.
And these are the details for the Instagram and hence this has been created.
Now, the only thing to notice here is that we have simply provided the number of rules and number of
columns which we want to allocate to these two figures.
And it has authorized, bitterly divided the area equally for the full subplots, which we have in the.
Next is the Seabourne Library.
So in case of civil liability, we will be learning about the fate of flight.
Now, one thing to notice here is that we will be walking on different floors now, these plants will
also help us analyze what type of data we have, what type of distributions do we have.
So we are picking out one detail said.
So the data set is basically of this FIPS dataset.
So this is what we will be using here.
So let me show you what all plots do we have here.
So first of all, we are improving the libraries, which is no fun, does the one make our site bisects?
So we are simply creating a distribution block distribution plot is simply a plot which has the density
of data, how data is distributed or where different values and blood clot did before that.
So here you can see when we think the normal distribution floor without any bottom windows, this is
what it lot.
So I have generated this with random values.
So here you can see the values are ranging from minus two to three.
And these are the frequencies for these values.
And this is the density of the value, which is similar to somewhat similar to what the histogram also
depicts.
So although the density plus is a lot more smoother in nature, so we get a better picture.
So when we use the distribution block and we see the full defaults, you can see the line for the van
to be full, which was created, has been removed.
And there is another option to include a drug.
This really is these small lines which are depicting the density of the dog, any particular point of
time.
So you can see these have a higher density, so this has a more density of smaller draglines here.
We have another option to keep or remove the histogram, so when I make this histogram as follows,
the Instagram behind has been removed.
Now, all we have been creating, only singleplayer to now what we are doing is we are creating multiple
plot and these plots are actually the forward into the plot Stinson's.
So the plot is what gives us the then to develop.
And I'm just plotting to be called into these plots in a single plot here.
So each line represents a different continents like.
And that is an option to include the shading, this shading basically eyes this color below the area
of just covered as a part of the skull.
And we have an option to either block, which is, I think, the drugs to it, so we could have achieved
this using density lost plot also.
So the distribution plot also.
So it is completely up to you how you want to plot this then.
And the plot is the distribution plot against.
In this distribution block, I am have I begged the government entity I have given the drug lord also
and I have also given defragment, these beans walk the same way, how other beans and other things
to them as well.
So as the increase, the number of beans, a smaller bar, a smaller size bar will be added so more
number of bars will need.
And when we decrease the number of Beenz.
Smaller number of bars would be needed, which would be broader in size.
Now, here we have.
Again, the.
Seabourn style, which is why the great.
And this is the data set which we are loading.
And here we have the distribution block, which we are creating for the global village values, so this
is a total value.
So you can see the usually the bail amount is ranging from as low as five or two and it is going up
to 50.
But most of the people who are visiting the restaurant are being something around 15 to five.
Next is the distribution floor for the VIPs.
Here you can see that the tapes are usually ranging for one to eight and then also by the major tapes
are between two to four dollars.
Now, this is the box, we have also discussed this earlier, but let me repeat this again.
So a box flight is a representation of the coordinates.
So the lower part of the box is queue one line.
So below this line.
Twenty five percent of the data is in.
The middle of the box is represented by the median, which means that.
Fifty percent of the vice president below the same, then the upper line.
Is the quality of the data, which means that seventy five percent data is present in this particular.
Then we have the law with the.
Then no outlier value has risen, the whiskered would be lying Geike, Q1 minus.
The story then, no detail will be present, no outline that will be present, this law school will
be present at the minimum value in case of our client would be present, then this is the way we move
to Q1 minus one point five IQ and the outliers will be below this.
And when the upper riska will be present, the maximum value, when there will be no outlier.
Above and it will be present at.
Guilty plus one point five Fames Aikawa.
In case any outliers are present and the outliers will be present here, just like they are present
at this particular moment.
So this is what a box blood is, so this also shows that the values are majorly present between of 12
to 24 something.
And a more a better version of this.
In case we want to view the Golden City also.
Is the William.
The wilin plot is similar to this plot, but it does not show the exact points of median.
You can see the point of median as this white dot, the darker point here and this darker line here
as you one and three.
And these the smaller lines, this thinner line represents the line for the minimum the law was and
the line for the upper Mr..
Apart from that.
This majorly shows the only to be so you can see how the values are changing actually in this particular
dataset.
Now, another plot that we have is about plot.
This is a bad lot for the Devastator.
Here we have a count.
Lord count gives the count of the values, so we have created the ground floor for the sex column and
it has the values, male and female.
So the male values is around 160 and the female value is around 80.
And you can see the majority value is for males and females is not in the majority.
Then here is a count for these.
So you can see the maximum number of customers come during the weekends, that is on Saturdays and Sundays.
I'm here is a lot of VIPs, the.
And here they have provided a view which is a change in color and this change in color is shown with
respect to time.
So there are two times when people are coming in, one is lunch and another one is enough.
So if they come back, you can see that people are coming usually during lunchtime in the days and during
dinner time during the weekends.
And there are more number of people coming during the weekend.
And you can see that all the people who are coming are.
Coming during the dinnertime.
Now, these are all analysis, which we have done on a single column on a single variable.
We can also do analysis on multiple variables.
So these are a few analysis which we have done here.
So here we have created a box plot and we have created the box plot between the X value being the which
is closed Friday, Saturday, Sunday.
And that would be.
Now, when we compare these of the plot, which has been created, you can see that the total bill is
higher during Saturdays and Sundays and even the median value.
For these bills is higher during the meakins.
While the total bill is lower during the weekdays.
When we compare the time with the amount of depth, you can see that immediately, the tapes do not
very much.
Although the median of the depths is higher during the dinner time and the median for lunch is lower.
And there are also certain outliers present during the dinner time which supports the fact that the
person would be getting more tips if they're walking in the dinner shift.
Then here is a comparison between the total bill for smokers, so this has been segregated with smoker
and non smoker.
So you can see here when we compare with the Thursday and Friday with respect to smokers, the total
value that the blue is for smokers.
So you can see the value is not really changing much, although there are a few outliers in case of
smokers.
But the value is almost similar, like in the case of the Vikings, the value is comparatively the free
in case of smokers and nonsmokers.
As you can see, the median for smokers and non smokers is very different.
For weekends.
And then is a larger amount of.
Outliers present in these cases.
Here we are again, comparing the two Thebans and the De.
With respect to Smokers'.
So here you can see that the values are not changing much, but in case of smokers.
The total bill is higher and.
For nonsmokers, the total bill is almost similar.
Here is another kind of plot, which is a joint plot, joint plot is a collection of two plots, so
it has a histogram on the top.
And it has it has another kind of plot in between this kind of plot could be a scatterplot, it could
be a regression, it could be a residual, it could be a corporate entity plot.
Any kind of fraud could be present in between.
So here it is.
We have not provided the kind, so it has taken the lead for skying, which is the site.
So we have plotted the total bill with respect to the tips.
So you can see there is somewhat a linear relationship between the billion tips.
As the total billing freezes, the tips also increase.
And.
You can see this is, again, the plot for the value with respect to the depth.
So you can see these plots also created by the site.
Now we can change the mind also here, so we have the defined progression, which is the reason why
it has added to this regression line here.
Here you can see we have converted the type two hexagon, so instead of having these dots, it has actually
created hexagons here and you can see the color variance in the types of hexagons.
So wherever the density of the points is higher, the color of the hexagon is doubtful, while wherever
the density of the point is lower.
The hexagons are lesser in number and the color is lighter.
Now, here we are creating another blog.
And this one is a joint plot where we have given the kind as hexogen and we have provided a stai to
the axis, so this is the axis styling, which we have provided under the existing name is dark.
So we can provide Stine's to these also.
So there are a lot of methods which are present.
There are a lot of variants present for each and every plot which we are generating.
The foreign leaders, which we are including for any plot, are a lot lesser in number in comparison
to those actually exist.
So whenever you are creating a plot and you think that there should be some way in which you need to
have, then you can go to the documentation of that particular plot.
And see what will be the inside of prison, what changes you can do the Fulda in good barometers to
get a different kind of Lord or any changes in your.
So here we have created another joint plot and you can see I have just changed the size by changing
the height and racial.
So you can play around with the height, value the racial value and change these things.
Here I have needed a relation, Lord.
Relation plot is just creating a line here.
I have given the X values, the Y values, apart from that, I have given no hue.
Hue is basically a color line, which I have provided, and the hue is for smoker.
So for the values of small, good, different values of small good, that is a different color vision.
So because Morgan has two values, yes and no.
So, yes, he has a different color of line.
I know has a different color of mine.
Apart from the color of lime, we can also have a stai, like we have here, style as dyeing.
So because the time has dinner and lunch, two different values.
So the style of the line has also been changed.
So for all the detail which is related to dinner, the style is a straight line, while for lunch the
style is a dotted line.
Similarly, we have this size and sizes for size group of the size of the people coming, so we have
four types of size, zero to four and six.
So based on the size of group of people, again, the width of the line has been changed.
I'm kind is basically the lying vibe that we have provided here.
Now for this relation block.
We have, again, given the similar data and we have given although if a state.
So it has created this line here.
Another thing is here we have the same thing, we are given a different dataset here.
So when we create this relation floor, it also gives.
Oh.
Confidence in double value, so you can see this light shade area, which has been cheated here, apart
from the line, this is basically the confidence interval which has been shown now.
Similarly, when we are giving the CIA the confidence interval value to be standard deviation.
In that case, it has created the value as standard deviation now of the confidence interval is actually
pointing towards the standard deviation of the.
So similarly, we can plot different kind of clouds beginning different hues to the Lord and divide
the plot into different plots.
So there are different kind of things which we can do here.
Another thing which we can do is we can either rose in volumes.
So here we have created a simple relation plot with X and Y, and we have given the difference in color
using human being for smokers.
And apart from that, we have given column.
So we have created two columns based on the time at which the customer is coming in.
So if the customer is coming in lunch, so there is the left column for that.
And if the customer is coming in, then also there is this right column for that so that we can compare
these right in front of each other.
Similarly, we can have multiple roles and multiple columns based on the types, the categories, the
categories.
So if time has two more categories, then it will create four columns here.
And here we have event value and we have a region value, so here Virgin has two types of values and
strengthens.
So two columns have been created here because we have given column time as region and we have given
life as giving.
So based on what event it has created, two different rules for us.
And again, we have given the kind of line, the x value, the value that he knew to be the subject
and raised on the subject and has created different lines, now, we could have taken a subset of the
subjects and created different lines for those also to view it more clearly.
So there are different variants which we can try here.
And here we have a beer plant.
A beer plant is basically gives a complete.
Analysis of different variables come back together in pairs, so if we compare different values with
different numerical problems, so we have size, we have tips we have to table and these have been compared
with each other and created plots for.
So here we can analyze and see what is related to what help.
And the last one is the correlation plot, which shows how one column is correlated with another.
So here you can see the lighter value refers to one, which means that the diagonal will always be one
because it would be always highly correlated with total because it is the same column by here you see
the values dips has zero point six to eight as the correlation coefficient with the size has zero point
six.
Correlation with total size has zero point four nine as correlation coefficient with dips.
So similarly, the more the number of columns, the more colors will be present here and then we can
find out.
The columns, which are highly correlated and then again removed them, we will see how we remove the
columns.
We will be using this correlation matrix to remove certain columns.
In upcoming video in the next session, probably.
And then you can see how this works.