So now let's have a look at RStudio.
RStudio is IDE, Integrated Development Environment,
and it's made for the programming language R. R is
a statistical programming language which has been
derived from the closed source S language.
So R is open source,
RStudio is open source,
and it's completely for free.
The central data structure in R is a DataFrame.
So we have here a window which contains
an editor and below we
have here a window which contains the console.
The R interpreter is the interactive interpreter.
So you have access to the interpreter here at anytime,
but it's handy if you have a text editor here.
You can always execute
the code you're writing here in this text editor.
On the top right,
you have a narrow window
where your environment is displayed,
so every variable on
the heap is accessible and you can also inspect it.
If you plot graphs,
they are ending up here.
So let's start with a DataFrame.
So in order to find out where we are,
we say, "Getwd," so get working directory.
So we are in the "Home" folder. That's pretty cool.
So now we say, DataFrame equals.
You might have seen this symbol here, so that's legacy.
There's only a slight difference in function codes,
so don't worry about it
unless you're using it in function codes.
So you can use the normal ordinary assignment operator,
which makes our looking a bit less ugly.
So we say now read.csv and now we can say,
"Go to my Downloads folder".
In here we see all the possible files.
So I know it started with CU,
so it's customer messages.
We hit Enter, we can execute this line.
Then this line gets copied
to the console and gets executed.
At the same time, you see here DataFrame is
basically containing the data from that CSV,
and we can now have a look at
the contents of this DataFrame.
If we say, "View(df)", you see
here it's already shown inside the editor window.
What we notice is that
the first line has been interpreted as header.
That's something we don't want.
So we can say, "Header FALSE".
It's very handy that you have autocompletion here as
you always know what parameters a function has.
If you now have a look at DataFrame again,
you see here the first line is
now part of the data and not the header.
So that's how you can load data.
You can, of course,
also load data from remote database systems.
You can use ODBC for that,
but that's beyond the scope of this tutorial.
What I want to show you is another way of importing data,
you can say here, "Import from CSV"
and then the code is actually created for you.
So let's open the file again.
It's basically doing the same,
just that you have an idea.
You have a data preview with the same problem
that you have the first line interpreted as header.
So you can actually uncheck
this one here and then it's as it should be,
and you say, "Import".
You notice here you have a second object
here on the heap which is called customer messages.
It's also DataFrame and it's also shown here.
That concludes the first video.
In the next video,
I will show you how to work with libraries,
and then after that I will show you how to create plots.