Barton Paulson is the author of an introduction to R. He says R is arguably the language of data
science. R is free, open source and optimized for vector operations. He’ll show you how you can use
R to do your own work with data in a more productive and interesting way. You need to go to the
home page for the our project for statistical computing. And that ‘s at our dash project. Org. When
you get there , you can click on this link in the first paragraph that says download our and then I ‘ll
bring you to this page that lists all the places that you can download it. And if you’re on a Windows
PC , then you ‘re probably going to want this one base again , click on it , download it and go through
the standard installation procedure. On the left is the source window or the script window where
you actually do your programming. Any line that begins with a pound sign or hashtag or aka Thorpe
is a commented line. That ‘s not right. On these other lines or code that can be run, by the way , you
may notice a red warning just popped up on the right side. That’s just telling us about something
that has to do with changes in our and it does n’t affect us.
The next step and are an introduction and setting up is about something called our studio. And what
it is is a piece of software that you can download in addition to our what you ‘ve already installed. It
makes interacting with our a lot easier and a lot more organized and really more fun to work with.
The console is down here at the bottom. And that ‘s where you get the text output. Over here is the
environment that saves the variables if you ‘re using any and then plots and other information show
up here in the bottom right. Now you have the option of rearranging things and changing what ‘s
there as much as you want. Package packages are bundles of code that add new function to our
makes it so we can do new things. There are two kinds of package two general categories. Base
packages, these are packages that are installed with our so they’re already there. But more
significant than that are the contributed or third party packages. These packages need to be
downloaded and installed, and then loaded separately.
The most common are most frequently downloaded packages on GitHub for use and are now
regardless of how you get it. I find these packages that I use most often are really a lot more
effective and what easier. And I ‘m going to demonstrate all of these in another course that we have
here. But let me show you very quickly how quickly how to get them working. If you have Pac Man
installed, even if it ‘s not loaded, then you can actually use Pac Man to install other packages. This is
a much easier way to do it than the standard r routine. For base packages like data sets, that means
the ones that come with are natively like the data sets package. You can do library which simply
loads it without saying anything. RS plot command is also known as basic x , y plotting for the x and y
axes on a graph. It adapts to data types and to the number of variables that you’re dealing with. And
it ‘s a great way of getting a quick feel for what we ‘re able to do and are , I ‘ll come back to the full
window here
science. R is free, open source and optimized for vector operations. He’ll show you how you can use
R to do your own work with data in a more productive and interesting way. You need to go to the
home page for the our project for statistical computing. And that ‘s at our dash project. Org. When
you get there , you can click on this link in the first paragraph that says download our and then I ‘ll
bring you to this page that lists all the places that you can download it. And if you’re on a Windows
PC , then you ‘re probably going to want this one base again , click on it , download it and go through
the standard installation procedure. On the left is the source window or the script window where
you actually do your programming. Any line that begins with a pound sign or hashtag or aka Thorpe
is a commented line. That ‘s not right. On these other lines or code that can be run, by the way , you
may notice a red warning just popped up on the right side. That’s just telling us about something
that has to do with changes in our and it does n’t affect us.
The next step and are an introduction and setting up is about something called our studio. And what
it is is a piece of software that you can download in addition to our what you ‘ve already installed. It
makes interacting with our a lot easier and a lot more organized and really more fun to work with.
The console is down here at the bottom. And that ‘s where you get the text output. Over here is the
environment that saves the variables if you ‘re using any and then plots and other information show
up here in the bottom right. Now you have the option of rearranging things and changing what ‘s
there as much as you want. Package packages are bundles of code that add new function to our
makes it so we can do new things. There are two kinds of package two general categories. Base
packages, these are packages that are installed with our so they’re already there. But more
significant than that are the contributed or third party packages. These packages need to be
downloaded and installed, and then loaded separately.
The most common are most frequently downloaded packages on GitHub for use and are now
regardless of how you get it. I find these packages that I use most often are really a lot more
effective and what easier. And I ‘m going to demonstrate all of these in another course that we have
here. But let me show you very quickly how quickly how to get them working. If you have Pac Man
installed, even if it ‘s not loaded, then you can actually use Pac Man to install other packages. This is
a much easier way to do it than the standard r routine. For base packages like data sets, that means
the ones that come with are natively like the data sets package. You can do library which simply
loads it without saying anything. RS plot command is also known as basic x , y plotting for the x and y
axes on a graph. It adapts to data types and to the number of variables that you’re dealing with. And
it ‘s a great way of getting a quick feel for what we ‘re able to do and are , I ‘ll come back to the full
window here
