 Hi, I'm Richard Darst. Hi, I'm Simo Tuamstam. And we're here to demonstrate installing Anaconda and an Anaconda environment on Linux for our data analysis course. This may be useful to other courses as well. So here I am on in my Linux terminal. So I've already downloaded the Anaconda Linux installer. So I'm going to run that with bash. So bash Anaconda. So I run this, I type. We read the license or more precisely we don't, we type yes. The default place to install it is usually good. So this will take a minute or two. Okay, so that didn't take too long. So I have this warning here, which I'm not going to worry about. Do I want to run Conda in it? And on my computer, I always do no, because I want complete control over when Anaconda is used and when it's not. So there, that is done. So to activate the Anaconda environment. I do source Anaconda 3 in activate. And there we go. And we see my prompt change to show that I'm in the base of the Anaconda environments. And now we need to install the data analysis packages. So here on the data analysis workflows page, if we go to the software installation, and then we scroll down some. We see this environment file defines all of the different packages that will be installed. So we can get this directory with git here. So we can run git clone. I'm going to copy it. And then paste it here. I had to remove my previous copy first. So I clone it. It doesn't take too long. And now I change to go inside of the directory. And here I am. And if I look using this program called less, there's environment.yaml. And the same thing we saw on the website. And we see here, this is called the data analysis environment. So I'm going to run conda in conda environment.yaml. So I will push enter. And now this is going to take a little while. The conda environment is basically like a huge collection of different software that's been distributed through this conda environment. So this environment contains various Python packages and various other packages. And distributing them otherwise would be quite hard. So this is the way we are currently doing it. Yes. So since this will take some time, I'm going to pause the video and we'll come back when it's done. So see you shortly. So we're back. It took maybe five or 10 minutes and now we've gotten here. So we see it says it successfully installed a bunch of stuff. Well, a bunch of stuff we're not reading. And it tells us how to activate the environment. So conda. Activate data analysis. And this is fast. And we see my prompt now says data analysis at the beginning. So now let's test if we can start Jupiter lab. So Jupiter lab. So if you leave off this web browser, it will find a web browser and then start it for you automatically. But since I have a lot of different web browsers running here, I wanted to start in this window. So I do that. And I copy this link into my web browser. And we see it start it suggests to do a build. Well, why not. Let's do that. So now we've got somehow it's open this file already for me. So we see I'm in a directory and this is the data analysis workflows course which I already downloaded with it. So first we need to download the data sets. So you would come to here and double click download data sets and then this window will open. Yeah, that's kind of happened sometimes. She didn't shouldn't be. Yeah, we don't worry about that. Yeah. Okay. So this defines a bunch of different data sets and some Python code which will automatically download them. So I can click anywhere in this box and then click here, run the selected cells and it will do it. And then we see here it's downloading different things here a folder called data has appeared. It looks like it's done data and we see the data is here. So let's test it. So I go back up clicking here to the root folder. And I go to Python exercises. And we do chapter one Python exercises one. And we go here and we can do run. Or is it colonel the current run all run and run all cells. And we see there's a little asterisk here, which means that the cells running and once it runs it becomes a number. So we scroll all the way down. And we see three plots. So this work. Now we can test the our exercises, if that's what you would do. So we go back up to the root folder here. And then we go to our exercises, double click. Chapter chapter one are exercises one. I double click to open it. And I can do the same thing run and run all cells. And that's just the way you output stuff. And on down. And the plots are made. And that is it if you can get this fire then you have everything you need to do both the first day and probably every day in the course. Yeah. So, thanks for watching. See you Monday.