Here.
Before moving to the plot alibi and cufflinks we first need to set a plot away in cufflinks.
They what we are going to do in this video.
So we will begin with importing them.
Be as and B and import upon does as BD.
We go to Denver.
Also Ed met blowed lip space in line there.
There you go with Dedmon.
Now we will first import the plot all right that is import bloat and light as being to pretend.
Did you go with that one.
After that you need to import cufflinks as S.F. David Goldman.
Now you need to do two things here.
First you need to set up the connection to all flight because bloated by cufflinks are something that
works online.
In that case you need some I.D. and stuff like that one.
So we make this old stuff all flight.
So for that we require three commands here.
First one is import load elevate or flight.
As Bill shifted them now right the same tax bill.
That is this plot of land library.
Note in it underscore the notebook underscored more.
This is something that make the libraries connected in offline mode and make this one true.
After that make cufflinks or flight that is just simply this library S.F. dot go underscore or fly.
If you do not write this index you need simpler alibi and companies log Logan idea and password.
So to prevent death things just tried this long difficult despondency.
So this is what all you need to do to set up global grain companies in your projects.
You can also just make this one.
Now we are done with this so I am moving all these in just this life.
So this one here this one here.
This one here and these two indifferently because someday we will get some added while doing these in
the same line.
So there we go with that but now we will define some datasets that we are going to need.
Here first is just generally a random data offering BD or data frame.
I believe you are no expert in this thing.
So here we would generate a random data frame and we do random no grand don't use it and N for native
values and hundred rows and five columns you can take any and then we have columns.
These will be something like a b c d and e labial.
If you print that one you will find this bunch of options.
Sorry you did your defense.
After that we will define it under the definition that is a data frame that containing also these algebraic
kinds of values so that we can plot some different types of plots there.
So data from here we will define a simple dictionary first X and the values for x are like a.
Then we have B then we have C then we have d and we have e then we go after that we have white and white
will contain all the numeric values 1 2 2 4 and 5.
Then we have said that will also continue to values for distribution type of plots and the Eagles and
random values them should pretend.
And now we have f this one x y z columns and 5 those first one these values that has connected values
and then we have numeric values.