Hello, before going ahead in this session, let's have a quick overview of what type of analysis,
what type of data preparation we still have done on a what and type of data set.
So using this logic, we have collected data.
Then we have access derived features using all these logics.
What we have done then we have analyzed this problem statement in which we have basically analyzed what
exactly that rests with this back to each and every day.
Once after doing all these things.
And we have this problem statement after in the previous session, we have this problem statement in
which our problem statement was in what month your rights was maximum, that we have come up with a
conclusion in this month.
We have backed them.
Right.
So these all over through then we have in this beautiful piece.
So in this session, we have this assignment.
The very first problem, the statement is exactly your you have to perform your analysis of total.
Right.
Montalva is itemise.
It means you have to fetch each and every month using some loops.
Once you have that one, then you can include data that once you have that data frame, you can simply
access the of that data and you can simply plot your histogram.
That's it.
So what I'm going to do for this, let's say I'm going to say let's I'm going to use my enumerate over
here, is here I'm going to say enumerate of deals all month.
I have to just pass this.
And here I have to say on what I have to enumerate, it means I have to number it on a month dot unique.
It means I just need a unique values of this month.
That's it.
Once I have all these things.
So it will exactly return me to the very first one, it to return me my index and the second one, it
will exactly return me my money.
So I'm just going to it as this one.
And here I have to see my index will get a start from one that simple meaning of this one.
Once I have all this stuff, then I'm going to create a subplot using BLT Dot subplot.
I have six months here.
I'm going to say I have a method of three comma, two comma I it means on each and every subplot I have
to display some piece to it.
Then I'm going to say D.F. of month it Callicles to one whatever month I have passed from this to the
four I come a month in this number.
That's it.
And here I'm going to say this is equals two months.
This is exactly my futer.
I have to pass this in my data frame.
Let's say this one.
Let's say this is exactly my data framework to dissolve comma Paoletta.
This is my affair.
So let's say from this data frame, you have to access your day.
So I'm going to say d of of out of date and on this, what I'm going to do, I'm just going to call
my histogram to be ality dot of this.
Once you have all this stuff, let's say you have to assign some X labels.
And while it has to for this I'm going to say p l dot x label.
Let's see, my X level is nothing but let's say days in month, days in month.
And after this you have to say you have to assign some value.
But I'm going to say BLT dot y label, let's say Mylie y label is nothing but let's say total notes.
I'm just going to say my Y label is nothing but total rights.
Once after doing all these things, I have to just execute it.
But before executing, let's say I have to bring this act level as like two days in month and whatever
will be my month.
So here I'm going to add my placeholder and for this I'm going to say that format of month.
So this placeholder will receive value from this format function.
Let's say I have to sign my own window side.
So far this is what I'm going to do.
I'm just going to say VLT, Dot, Fagre, and here you have to sign your fixie, which is exactly this
one.
And efficacies, let's say 20 comma eight just executed.
It will take some couple of seconds and it will exactly give you your validation with respect to each
and every month.
Now you will see over here, this is exactly your visualization with respect to each and every month.
And from this realisation, it seems to have almost in the couple of last days, in each and every month,
you have maximum.
Right.
You can easily visualize from this histogram.
So that's a conclusion you can fetch from this all these six visas of all the six month.
So let's go ahead in our last statement of this assignment where we have to perform analysis rush in
our search for this, I'm basically going to use a very handy function of Seabourne, which is exactly
my point plot for this, I'm going to say, and this dot point plot.
And if here you will stab you will get all the documentation on this function, what those parameters
are, what are custom parameters, what this function will do.
So tell it, show point estimates and confidence interval using this is scatterplot Graff's.
So it is almost similar to a line.
But the basic difference is in this point plot, it notifies some particular point.
So here I'm going to say on X axis, I just need my outlet.
And on Y axis, I just need to say what exactly is my latitude?
Once I have all this stuff, I'm going to say, let's say, what exactly is material here?
My data frame is nothing, but let's say very fast.
I just need some data frame.
So this is exactly your beautiful point plot and it will definitely take some couple of minutes in its
execution because you will observe the data is definitely very huge.
So this is exactly your rush with respect to each an hour on different, different latitudes.
Let's say I have to modify this this point as well.
So for this here you have some of the parameters that you can play with as well.
So here you have a barometer, which is exactly your parameter.
It is on what column basis are on what parameter this is.
You have to split your graph.
So I'm going to say in this whole parameter, I have to pass my wigdor.
And after what I have to do, let's say I have to assign some title as well.
As for this, it is exactly my let's say X or you can say Azziz.
And here I have a function which is exactly my set on this gorditas for this.
I would say set in this code.
And here you have to find some title as well.
So my title is nothing more, let's say hours of the word says Lattitude of Passenger.
So this is exactly my title just executed.
It will definitely take some couple of minutes around two or three hours, depending upon what the specifications
you have.
So this is exactly a beautiful point.
With respect to each and every weekday, you will see this this red this red wine plot with respect
to toastie, which often refers to yeah, it is somehow on your peak, whereas this this pinkish will
definitely this back to your Riccardi, which is exactly my sun.
So that's the type of conclusion how you can conclude your result.
And if you try to maximize this result, just try to assign your own window.
That's what we all have done in all of our previous results.
That's all about this test.
And hope you would love the session very much.
Thank you.
Have a nice day.
Keep learning.
Keep growing.
Keep practicing.