Hello, everyone.
So let's just load this data into Python.
For that, we first have to learn to bite the notebook.
You can go to an iPhone to navigate that from your to start menu.
Sequel in that OpenAir.
Licona get known shogan.
Now in the lighter notebook by logbooks, click on launch.
So the home page you are seeing is your default, what kinetic three?
You can open any existing notebook which are stored in this work industry.
For example, if I want to open lecture one dot, I bite a notebook.
I can just click on it and it will open that notebook.
But since we want to turn your notebook will go to home and click.
On this new look.
And then the drop down menu, I would click one by country.
And this video will lend out the import of what house price data?
And we will also look at the duty.
So before starting, we will first look at of the new year, what kinetically?
So, you know, you're working directory.
You have to write BWB.
Just different bet.
So this is you got to work indirectly.
We will use this working directory later on in our courts to copy BETYE and do this sort of kinetically
or to save files.
And this what, kinetic three.
And this is the directory which you are seeing in your home bits.
If you click on home.
Does the content of that working directory.
So all this for years and all this files are present at the folder.
Mention the import of the CSP file off our whole space data.
Download the yes we find from the resource section of this lecture and copy that file anywhere in this
working directory before importing.
Let's just import all the libraries.
So we will first import.
No, I will write.
Import them by as Empy.
Will import ban does.
Right.
Import Ban does SPDM then for Groff's.
We will import Seabourne like Seabourne as S.A.S..
And run.
You can see here and sort of when I'm getting a stick sign that I mean, this statement is running in
our garden.
So whenever you see this a strict sign, that means that cell is executing in the background.
Now, the important thing is, if I will first define a variable for our data frame that is D.F., then
equal to.
We will use the reach CSP function of pandas.
All right.
Beadie Daughtry's, ESV reads, E.S.P is a function defined in Pandas library and we are important pandas
as speedy.
That's why I will write Beauty Dot Route CSP.
The first argument of read CSP is the location of your CSC fine.
So I have just copy paste the location.
If you are using windows, you may get backslash in sort of this forward slash.
So if you are just copping the address from the address, but off windows, you will be getting address
in the form of Beck's leches instead of forward slathers.
So convert those back slashes and do forward slashes before running this, come on.
And the second argument, I will write.
Does equate to zero.
Since my CSU file contains high debt and the location of higher debts is at the first draw.
That is the zero, all of the file.
That's why I let that make those zero.
I run this command by using a director.
If you remember, either under executes the come on.
And also ended up blank sell below.
Now we'll look at our data frame, which be B.F. Dopehead.
If you remember, Head will give me.
The first five rows of my data.
Then there.
As you can see, we have all the data in our variable EDF.
We have already discussed the meanings and definitions of all this variable in the word theory lecture.
So let's just look at the number of rules and number of columns of this dataset.
Will that be a dot ship?
You can see the first argument is the number of rows.
So we have total 506 observations.
And total number of variables are 19.
So.
We have 19 columns and five zero six rows in our data set.