How long before we do go into this session, let's have a quick recap of what we have done in our project
in so doing, lots of preparation and after we have got this amazing tree map and from this, we can
definitely conclude some inferences as well so that we have find this.
What exactly is a trend with respect to gun phone number of that number of recovered and number of active
cases as well?
So in the session, we had the very first part of a statement in which we have to visualize what exactly
the population to test the ratio.
So we have to visualize this estates.
But you will notice over here in this world underscore DataDot had and if I'm going to show you this
data frame, you don't have any column where you have this state, where you have this population test
done feature over here, you will see you don't have any future.
It means you have to create this feature.
So far, this what I am going to do now over here, let's say I'm just going to define that feature
that features nothing.
But my population will get divided by what exactly the total number of test ongoing, which is exactly
this.
So here I'm just going to say, let's see, very first I have to exit the data frame.
And on this I have to access this population, which is exactly this one.
The data we have to use this operator.
And after it, I have to use this one.
And on this, I'm going to use this total test.
And if I'm going to execute all these things, you can visualize with respect to each and every country,
or you can see with respect to each and every index, you have some values assigned to it.
So for this, we can do let's see, I just need this top 20 index values for this for you guys can call
this index location.
And here I'm going to say zero to 20, because in your top 20, your Mazher countries like India, Brazil,
US, the UK are going to like it here.
So let's see what our stats it will return me.
I'm going to store it somewhere else.
Let's see.
This is exactly my population on the score test, on this score ratio, whatever variable name we want
to assign, it's all up to you.
After what we have to do, we have to simply visualize this data for this.
I'm just going to use my back over here, which is exactly this bar over here.
And these are all the custom parameters of this function.
Your data frame, what you want on your access is what exactly you need on your y axis and all these
kinds of things.
So now, very first, I have to mention what exactly my data, which is exactly what data after it.
Now I have to mention in this data frame, I just need the top 20 index for this.
I have to use this.
I like over here zero to 20.
So this is exactly my entire data frame over here.
Let's say on X axis, I have to set some value, which is exactly my country.
So you can just pass over there.
That's it.
Operate on y axis.
You have to set some values.
So here on y axis, I'm going to say whatever value I have over here, that's it.
And if I'm going to pass shift staff to check my all the custom parameters here, you have a very cool
parameter, which is exactly this.
So it means according to your color or you can see on the basis of what feature you have to assign color
to your boss.
So let's say I'm going to say color equals to, let's say country, class, region, and let's see if
I have to assign some title as well.
So let's my title is nothing, but actually my title is Population to Test.
Don't they should say this is exact population to test done that.
This is exactly my title, so I'm just going to store it somewhere else.
Let's say in figure and figure is exactly an object, Utterback thought.
And after it, I'm just going to call this show over here.
And before executing this, you have to pass over here on Axis because over here in this data frame,
you will figure out you had just stopped on the index.
It means on y axis, you have to say, yeah, I have to pass that top 20 values for this.
I have to say zero to to twenty.
That's it.
And just execute the set and it will return you.
This beautiful, this amazing is overhead.
Now you will.
With respect to this Bangladesh, you have that much.
You can say population to test and issue.
Similarly, with respect to this Mexico, similarly with respect to India, you don't have that much
good test and issue of arrest with respect to Russia.
Definitely you have good test and issue.
Similarly, with respect to U.K., with Saudi Arabia, it is in all the Western countries, you have
definitely a good population to test on the issue.
So that's the type of inference you can fetch from this Vizsla.
So let's go ahead with our next analysis in which we have to find what are the 20 countries that are
badly affected by this coronavirus so far?
This what we can do.
Let's say I'm just going to call our columns over here to showcase what are those columns that will
play a very major role over here in this problem statement.
So let's say on a basis of this serious on the basis of this critical and definitely on the basis of
total less total record.
So these are those features that will impact highly in this analysis.
So let's say I'm just going to use a bar plot over here.
And if I'm going to shift crosstab, these are all the custom parameters that you all are already aware
about it.
So let's say I have to need I just need the 20 countries for this.
I have to say, I look and here I have to say zero to 10, 20.
That's it.
And definitely I have to pass something on x axis and some values on X Y axis as well.
So on X axis, I have to mention this country reason because on this X axis, you will figure out here
you have some countries.
So here I would say on Axis I have all this stuff and definitely on Y axis, I'm just going to say I
have to pass my data.
And the list to the very first is, you see this.
The second one is you're critical.
So I'm just going to copy all these stats over here, all these stuffs, and make sure you have to separate
it using comma after doing all these things that hard feature that will definitely impact over here,
which is exactly what total let's say.
I'm just going to copy from here, just going to paste to it here.
The fourth feature that will play a major role over here.
My recovered case is my active cases and my total cases.
So these are my total recovered cases.
So these are exactly my total record.
These are my total active cases.
So these are exactly my total active cases.
I'm going to say these are my active cases and these are my all the total cases.
So I'm going to say these are exactly my all the total cases over here ones I have all these estates
over here.
What do we have to do?
We have to just execute this solution here.
So this is your amazing statistics over here.
And if you want to assign some titles and if you want to update your layout, you can definitely do
that.
That's that's not a very clean task there.
That's just like a piece of a cake.
So here you will observe this.
This is exactly estaba chart.
So you will figure out this this arrangement with the respective total cases.
Where is this purple with respect to see this critical?
This green one is exactly it is totally covered.
There is all these things with respect to that and all other things you will visualize already here.
This is with respect to USC.
This is your Brasi, this is your India, this is Russia.
And you can easily figure out over here this USC has a highest number of total number of cases.
After that, we have this Brazil, then we have India, then we have Russia.
And this is exactly that in that.
HATALSKY So this is amazing inference from this visa.
So that's all about the session of the session very much.
Thank you.
Nice day.
Keep learning.
Keep growing.
Keep.