Original subtitles

Hi, everyone, and welcome in this new video and this video, we will begin to import and reprocess

some data.

First, we will pre-processed the data, which come from medicine to the front because it's the most

important.

So here we just have installed why plans to import that data from Yahoo Finance in the next video,

then I have all on this site libraries and this code is not necessary in your case.

So first, we need to import the data.

In all, case, I have just input manually the data from makers all five.

But.

In the next chapter, I will show you how to import some data using Python and data which come from

metaphor or frame.

But.

I think it's very important to begin by the easiest parts.

So, for example, you can take the CSB, file it, so one of the things we find.

Of the zip file attached to this video, this find contain nearly 10 currency data.

OK.

And you can take.

The data that you'll then you just have to drag and drop here.

In Google.

OK.

If you walk in Jupiter on a book, you need to have your notebooks and you see the file in the same

folder.

It's very important because a lot of you doesn't walk with Google Club and.

So if you work with Jupyter Notebook, but you don't really muster it, you will have a problem then

problem.

OK, so if you or move very comfortable with Python and Jupiter on a book, I only advise you to work

with Google.

So first, we need to import the data to improve the data.

I will create a new variable def for data.

And I use the really as function from ponds to import the CSP file.

So we need to put the name of the CSB find.

And then we can enforce it and show what this fight is.

OK, I have just four kids to run this, so.

And now, as we can see, we have a little problem, OK?

This problem is that.

The three metre between each value is backslash T.

OK, as we can see between each value we have.

But that's OK because.

The delimiter isn't a stone cold.

And then and this is not able to.

Find it automatically.

Needed to specify the daily meter in the function as input.

So backslash key.

OK.

I'll just put it here.

And now, as we can see, we have a much better results.

But we.

Still wants to make some modification.

First, we don't want the volume and spread color, so we needed to remove it.

We need to remove sensory.

And to do it.

We will just create a little function to do all all necessary modification.

So the input of the pension is the name of the CSB fight then.

We want to remove this two columns, so to do it.

We just.

You, ADF, when you look, we take all the role and we take all of the rule from zero to minus two.

So if you're not comfortable with this, I would advise you to read again.

The BBB is talking about pandas in the chapter Python for that science.

And then if.

I use this function.

I can see that.

The last column as being removed.

But we still want to make some modification.

First, we want that dates.

Is the index OK, because financial data?

Or.

Time series and soon we want the dates as index and to do it.

We just need to put heat index quote equal.

Date.

So if we use like this, we will have dates as indexed, but pundits.

Doesn't understand that this dates or date.

OK.

It will.

Take this column as a story.

OK, so you need to specify porous.

Date Eagle.

So now the last thing that we need to do and is one of the most important is to rename the column and

it's very, very important one because.

And you have only two we can use data which come from several sources.

And if I take data which come from Methods four or five manually, you will have opened with capital

letter.

OK.

If I inputs the same data using pattern.

OK, so the data which comes from is a little fun.

OK.

You will have.

Open a local and te volume in knots in capital later.

OK, so.

The name of the killer.

Can change very often.

OK.

And so if you create a trading system that demand the close price, for example, and you call growth

in capitalism, OK, the next dataframe will have.

One time close in.

Capitalism.

One thing close, for example, like this one time like this, one time like this,

this execution.

OK, so.

If each time you had another notation, each time you will need to do some much of the modification

in your trading strategy.

And it's a really big problem because the goal of the ultimate ization is that we don't need it to.

Modifying something every time.

OK.

So to avoid you have this problem.

We will use.

We will rename the column.

So first, we need to rename the name of the column, so personally, I use this syntax.

OK.

But in your own protest, you can use the syntax that you want.

OK.

The only main point is to keep it all right.

So open a close and the thick volume.

OK will be named volume, but we know that is not really the volume, but you can take it to create

some indicators that demand the volume.

OK, but it's not.

Really a good method to do it.

OK, but sometimes if you don't have the volume and you want to try something using the volume, you

can take this color OK.

But I don't really advise you to do it if you don't really muster what you do.

So and then I just rename the name of the index.

This is not really mandatory, but.

I think it's a good practice.

And then we have the same.

Data from OK, so we are speaking with.

This data, OK?

And we have this data, so we I think we have very much.

Preprocessing, well, the data now I will show you how to process the data, which comes from why finance?

OK?

To show you the importance to process the data using the same syntax for data which come from several

sources.

Now I will show you how to import some data, which come from make a total of five manually.

OK, so.

I don't have show you how to do it automatically.

OK at this step, because for both of you which have a map, it's a little bit more complicated for

all you colleagues which work with Windows because you need to have a Windows device to use the Method

four or five library in Python.

OK.

But I will show you how to install Windows on your Mac using camp or an application like Perl Desktop

or.

It's a VP's Exeter.

OK, so I will give you some.

Possibility, OK.

To fix this issue.

So don't worry.

But I think is not the time to fix this issue because.

Were puts your algorithm in life, shooting is the last thing to do.

OK.

After before that, you needed to have a profitable strategy, and all the work is to find the profitable

strategy.

Once you have most profitable strategy, put it in life, writing is really the last of your.

Issues, OK.

So to import some data, it's very simple.

OK, you need to install the metal frame.

Application, OK.

It's available for Mac and Windows.

Then you give him her you.

Go him on bomb or ticks and you imports the assets that you want.

OK.

You can go check for some crypto exit to exit two.

If you choose one.

You choose the time frame.

OK, you choose the date and then you do you make your request?

I just want to.

I like that point is that in my case, I have to put just one time on request.

Sometimes you need to put several time.

Okay, so for example.

If I put daily, OK, it's possible that I need to.

Puts multiple time on request, so not this time, but if you have to put multiple time on request,

don't worry, it's normal, OK?

And then you export the raw, all the chips and you will have your data, so it's very easy to do it.