Everyone soon the last video we have plotted this graph using of our own defined values and some standard
values.
Now in this video we plot the original values from the CSU file on this plot so that we will be more
familiar with that one.
So for that of a plot this same of an axis same.
We just need to change these two values.
So let me begin with that one.
That is the data.
So your answer I agree with deadpan plot is same.
An X is outsourcing.
We just need to change the layout and data according to all the values available here.
Now we will begin with dictionary vitamin romancing because we are putting corporate locations we have
defined five location but we now need all the locations present here.
So how can you use all the locations that entail just simply agree the name of define then by indexing
using this code.
So codes and code.
Make sure they use it quotes them then locations more distilled them in some other states.
Then the Z here it's using of a defined values that is 1 to 30 40 50.
Now here we will use the origin values and if you notice on this figure that is representing the values
on the particular location that is total exports because we are analyzing the total values we are not
going to realize every single thing we will analyze all the values so here we will use agreed.
And in that one total space exports.
So make sure there's nothing in between them just a space.
So total exports.
And also here we have only 5 text but we can only find the text for every value deal but we will use
a smart B again by using this text.
So at Green Square brackets courts and in that one just text shifted an individual v Dettmer.
So we are done with that one.
Now it would change the layout.
So if you'd run that one right now you will have this take all the values here.
Our plot is already done.
We just need to make few changes.
So here if you notice Washington with value 3 8 9 4 8 1 and the tax is be 5 nine point two data all
that things here of California that we have also defined before Arizona.
This one Alaska up this one buggered with that particular name are penises.
So now I hope you got the idea that how this thing is working now you can also change this color just
by using color skin there that is color and skin you have different options there like
Portland if he'd done this one here we have this one these colors this is widely used you can also use
greens as we are using something like the agriculture things so you can just use greens there we have
this one all the values in green and then went later will have the maximum value darker had the lower
value.
This is a positron after that here we had this thing and then you can also change the name of discipline.
This color scale just by defining color bar and we had this one color back and make this one dictionary
there or you can just simply pass them in this curly braces because you need to define this name so
you can a title like gala but and also this morning coats shifted on Navy had this one color.
So this is about changing these things.
That's how you can change these values.
After that if we talk about layout let me reset it.
If we talk about layout so here we have a layout.
You can add a few things here.
So like first if I change this one into a dictionary because I'm not just only defining a scope here
right now.
So remove the quotes that equal design and display.
Here I can define a few more characters like show legs to show all the legs present death and make this
one true shift return shifted tone shifted.
Here we have the lakes and they level there.
So this is also a most basic thing.
Many people prefer.
You can also add a title to this one.
So you just simply write the title.
And this one is like every plot representing the agriculture plot shift returns should be done.
There we have crippled.
So that's how you can represent all the values from a CSA file upload without using much coding how
much you have coded here.
Just one two three four sets in four says you have analyzed all the data available here.
So this is the power of Python and data science.
You can even calculate the mean and the average all the values there are much more in datasets.
So in a footnote we will continue in the next video on the global scale with GDP 5.
So thanks for watching.
Continuing the next video.