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So now let's have
a look at RStudio.

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RStudio is IDE, Integrated
Development Environment,

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and it's made for the
programming language R. R is

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a statistical programming
language which has been

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derived from the closed
source S language.

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So R is open source,

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RStudio is open source,

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and it's completely for free.

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The central data structure
in R is a DataFrame.

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So we have here a
window which contains

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an editor and below we

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have here a window which
contains the console.

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The R interpreter is the
interactive interpreter.

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So you have access to the
interpreter here at anytime,

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but it's handy if you
have a text editor here.

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You can always execute

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the code you're writing
here in this text editor.

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On the top right,

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you have a narrow window

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where your environment
is displayed,

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so every variable on

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the heap is accessible and
you can also inspect it.

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If you plot graphs,

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they are ending up here.

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So let's start with a DataFrame.

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So in order to find
out where we are,

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we say, "Getwd," so
get working directory.

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So we are in the "Home"
folder. That's pretty cool.

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So now we say, DataFrame equals.

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You might have seen this
symbol here, so that's legacy.

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There's only a slight
difference in function codes,

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so don't worry about it

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unless you're using
it in function codes.

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So you can use the normal
ordinary assignment operator,

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which makes our looking
a bit less ugly.

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So we say now read.csv
and now we can say,

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"Go to my Downloads folder".

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In here we see all
the possible files.

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So I know it started with CU,

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so it's customer messages.

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We hit Enter, we can
execute this line.

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Then this line gets copied

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to the console and gets executed.

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At the same time, you
see here DataFrame is

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basically containing
the data from that CSV,

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and we can now have a look at

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the contents of this DataFrame.

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If we say, "View(df)", you see

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here it's already shown
inside the editor window.

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What we notice is that

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the first line has been
interpreted as header.

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That's something we don't want.

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So we can say, "Header FALSE".

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It's very handy that you
have autocompletion here as

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you always know what
parameters a function has.

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If you now have a look
at DataFrame again,

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you see here the first line is

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now part of the data
and not the header.

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So that's how you can load data.

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You can, of course,

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also load data from
remote database systems.

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You can use ODBC for that,

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but that's beyond the
scope of this tutorial.

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What I want to show you is
another way of importing data,

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you can say here,
"Import from CSV"

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and then the code is
actually created for you.

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So let's open the file again.

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It's basically doing the same,

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just that you have an idea.

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You have a data preview
with the same problem

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that you have the first
line interpreted as header.

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So you can actually uncheck

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this one here and then
it's as it should be,

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and you say, "Import".

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You notice here you
have a second object

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here on the heap which is
called customer messages.

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It's also DataFrame and
it's also shown here.

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That concludes the first video.

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In the next video,

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I will show you how to
work with libraries,

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and then after that I will
show you how to create plots.