 Hello. Today we're going to be talking about how you import data into Google Colab. We're going to talk about three different methods over the course of three videos, each of which is slightly different, but it will give you good practice on how you can import data. And then going forward, you can always choose whichever one you feel the most comfortable with. So without further ado, let's go ahead and get started. So over here in Google Colab, we have our just some tech cells that describe these different methods. So the first one I'm going to go over is mounting your Google Drive. The second is what I call the drag and drop. And the third is using a special upload files button. Before we get started, just a reminder of some key terminology. We'll be working with libraries and we'll be working with functions within those libraries and we're going to give libraries nicknames. And we do all of this through using the from import and as commands. All right. So in order to mount your Google Drive first, in order for this to work, you will need to have all of your data stored on your personal Google Drive. But once it's there, you can always access it through this process. So to start, we're going to import the Drive library from the Google Colab meta library. So we say from Google Colab. So this is our meta or larger library. We're going to import a sub library called Drive. And then in order to connect to our Google Drive, we use that library Drive with the mount command. And we say slash content slash drive in quotes. And so we click this and it's going to go through a process. So you need to say yes, connect, use your Penn State email address. Say allow, and it'll sort of go through its process. And occasionally it takes longer or shorter depending on, you know, the current resources available. But once it's done, you'll see this check mark. It'll tell you that we mounted it. And if you click this file folder over here, we now see that there is a drive folder. And so this is where we start step three, we click the file folder icon, we click into the drive folder, and you navigate to wherever you stored your data. So I'm going to use this lecture three retail sales. I'm going to click these three dots over here and copy the path. And then I'm going to close that. And that path is where we're going to actually access the data. Before we can do that though we need to import another library. So we say import pandas as PD. So here the library is called pandas. And we're giving it a nickname PD, so that when we use these command, we don't need to repeatedly type pandas over and over again we can just type PD makes things a little faster. And so then to actually read the file in, we give it a name. So I'll just say the F for data frame, and the command is PD dot read underscore CSV. And then you open some quotes. And here is where you actually paste that file path that you copied earlier using step three. And sometimes this will be where you end in this particular file we need to add an additional argument we say skip rows equals four. And we're doing this because this particular data set has four rows of metadata where it's telling us the units and the source of the data, and their own internal processes they went through. So we don't need that we want to start with row five, which is where the headers are. And this is something that you generally only learn by opening the actual file up in Excel to figure out how many rows you need to skip. But we can run that. We can see that it's been it's run here. If we open up the variable tab over here this x and curly bracket, our data frame now shows up as D F tells us the type of data, and the shape. We can also come over here, print the data frame by just typing the name and hitting run. And then we can see that we've got different variables column headers and different pieces of data within that data frame. And that is the first option that we have in order to upload data into Google Colab.