Original subtitles

Welcome to this lesson.

So we're going to continue our case study just looking at the coronavirus.

So in the previous lesson I showed you where I download the data from and also showed you that the World

Health Organization also has some of their own data analysis.

Now, this is a report that I put together kind of just on a global view to get an overview of what

was happening at the time with the data.

So if we start in the top left hand corner and just remember when you're putting your reports together,

it is most often that people will start in the top left hand corner when they're looking at the data.

So it's normally a good idea to have your key metrics, your key information in that top left hand corner.

So what I did was just make it simple.

We just wanted to show what was the new cases and new deaths for the day.

And then at that point in time as well, what was the total number of cases and the total number of

deaths that had been recorded through the World Health Organization?

So this was as at that point in time, if we go down a little bit, you can see then we break out those

numbers just by the different regions.

So these are the regions that the World Health Organization use.

I just kept the same codes.

They're normally quite easy to actually figure out, like you've got Europe and you've got Africa,

for example.

So you do have those regions just showing you what the breakdown is then for each of the regions.

And I wanted to show some sort of key trends so you can sort of see what was the new cases by the dates

and also how is the cumulative cases.

So as you can see at this point in time, the number is close to three fourths of a billion people who

have been infected, over 750,000 million people who have been infected.

Although to be honest, if a lot of you have seen the different steps, then you may see as well a number

of countries maybe not reporting as many cases as they did previously.

Okay.

Then we've got another trend graph down here.

And this is basically to show the number of deaths by the data and the cumulative deaths as well.

So I just wanted a couple of easy to see trend graphs that you could see.

Now, you may not down here that I've empty using a ribbon graph and the idea of this was especially

in the early days, was to see which regions were actually getting the most cases and using your ribbon

graph for this, I'm actually going to move this into full focus mode so you can just have a look at

that and you can sort of see as we go back in time, you can see that the numbers were pretty low and

then around the beginning, interesting in January 2020 had quite a spike.

Europe had quite a big spike at that time.

And at this time, January 2023, I think China did a lot of reporting of numbers as well.

That showed a huge spike in terms of things.

But the idea of this graph was really just to see with the regions, you can see how the colors change

using our ribbon graph.

If I go back to our view, you'll also see that I have put a slicer at the top just for your region.

So if you did want to focus on a specific region, if you wanted to look at Europe, for example, then

you could just see that.

And then obviously that would just filter all of your different different information.

Well, for example, you just shown the countries now you've shown the trend graphs just for that region.

So it gives you the totals just for that region alone.

Okay.

So you could have a specific region and for example, could again look at Asia over here, parts of

Asia, Japan, China.

Recording of those numbers.

I'm going to turn off the region.

Just go back to show all of the information.

The other view that I did want to show was the ability to have the countries.

And the idea here was to have total cases of new cases, total deaths and new deaths.

So if you wanted to, you could easily sort in this to see which was highest, which was lowest at that

point in time.

So at this point in time, if we looked at the total cases, we can see that the United States is over

100 million at this point.

China closely followed 98 million.

But because we can use that cross filtering that we covered in the course, you could click on China,

for example, and it would now filter the other views to be able to see that.

And as we can see, pretty much most of the cases all were towards the end of 2022, towards 23.

Again, if we look at India, India did have some high spikes towards the beginning of around 21 and

so on.

So you could go by country by country if you wanted to look at the details of this.

So that's really what I was looking to do with this report was just give an overview and just give a

way of being able to get an understanding of what the trends are.

What were the new cases, what were the new deaths, for example.

And people could then do their data analysis from here.

What we did was we then uploaded this into the PA by service and we then embedded it into a public website

so that people could have access to this.

And again, the link to the public website is in the Udemy course notes for you to go to.

So in the next lesson, I'm going to be looking at the embedded report.

We're going to just have a look at creating an embed code and then seeing how we created that.

So we're going to conclude this lesson and we'll see you in the next one.