So now we are just going to look at another way of dealing with.
The detail that we don't meet and in the previous.
Lecture we had cleaned the data for Mumbai.
Now, if you recall in the previous lecture, in some of the roles we were left with none.
So basically we either didn't have information about the zone or the neighbourhood and in this case
have removed those.
Now, obviously, keeping those nuns, that wasn't affecting us.
But if you just want your data frame neater, then this is just a quick way of going about it.
And I'll just talk you through this.
So import requests from for import beautiful Superboy's from PANDAS import data frame, you are all
again the same.
You are all source requests that get you all that text.
So I have imported my beautiful Superboy's to be a source XML in the soup.
Then we import Pantazis Speedy SDI Group table so we get the structure of the table.
We read it into a panel of data frame using Reed underscore HDMI.
And D.F. zero.
That will give us the table that we want.
I just see.
Right now, what we want is, well, now we'll simply split it up as usual, and the western suburbs
and the western suburbs, the western suburbs, so I do the same thing.
The F location dot string contains comma reset index, drop trou again location.
And we are splitting on the basis of location.
Strings played and won.
So we have Zohn.
The first new Collum zone and the neighborhood, and you can see these here zone and neighborhood,
and we no longer have those Nunc.