All language subtitles for 7. Pandas Conditional selection

Everyone and welcome in this new video in this video, we're going to see how to do slicing empanadas,

so slicing with Panda's object is very similar, like slicing in a list or in the red.

But the only difference is that we need to have a large property first, all the lock property first,

depending of the slicing that you want to do here.

We want to do a normal slicing.

So we are going to use the L-look property.

Then we put alternate brackets and we put, for example, that we want to extract the roll from zero

to 1500 and the colons from zero to 10, for example.

So here we have only five columns, because I have said it to Peyton that he needed to take 10 seconds,

but all dataframe contained only four columns or five if we count the index.

So Peyton takes all the columns so we can also.

Do a slicing with a condition, for example.

Hugh, I want to do a condition on the index and the condition is that I only want to do the date.

Containing 2010 in the year.

I can also, for example, tell that I want the date from 2010 to 2000 12, for example.

So it is very powerful to use the look property when you want, for example, to extract some specific

data.

We can also, for example, do.

Conditional slicing by volume, for example, if I teach the theory of the doojoon

and I want only the venue.

Which have Dogen value greater than 15000?

I can do it just using this syntax.

Now I will show you also how to conclude a desert free.

To get some better friends.

It is very easy because it is also like for the Nampai.

All right.

Instead of, we use the conquered function from pundits and not to concatenate function.

And here we just need to specify an axis.

So here we have split or first that are set by the colon.

So we are going to be conquered by the colon here.

We have

split by the row, so we are going to conquered by the.