 Alright, welcome to the third option for importing files into Google Colab. This is the upload files option that uses a special bit of code to first create a clickable button and then load the file in. So a reminder, libraries and some key words, but then we can get in. So the main flow of this is that we're going to first import the files library again from Google Colab, and then we're going to navigate through to eventually read it in using pandas. So we start off and we say from Google Colab. Import files so similar to our previous mounting Google Drive option but this time we're using the files library. And then step two, we create a variable called uploaded. And say files dot upload open and close parentheses. And what this says here is that this should actually bring up a clickable button. And you can use it to navigate to the file on your local computer. So if we first make sure we're connected to Google Colab and then hit run. We can see that this button has shown up and the code will keep spinning. So won't stop running until you click this button or cancel the upload. I will choose files. It opens up my file explorer and I can click here into lecture zero three retail sales. And then it tells me that it's done. So we come out over here under variables. We can see that uploaded has actually dictionary type. So it's a little bit different than our previous upload possibilities. In this case, the files dot upload creates a dictionary that is pointing to the location of this file in Google's memory space. So in order to actually get this file from the Google Cloud into our local Google Colab session, we need to use an additional library called the IO library. So I'm just going to import IO. I'm going to use the nickname because it's already fairly short. So there's not really any need to shorten it. And then we actually read the file in. And so we're going to use two commands here. We're going to use the pan PD dot read CSV from pandas. We're going to use IO dot bytes IO. So I'm going to make sure I get pandas as PD in there, and then start off with pan PD dot read CSV. And normally this is where I would put my file path, but we don't really have a file path yet because the file is still somewhere in Google's memory space. So we're going to do IO dot bytes IO. And what this does is it provides an opportunity to converse, so to speak, with Google's memory space and pull our file in. So then we say uploaded, which is what we called the file up here. And we can see after we start the quotes that it is predicting the name of the variable because that's the essentially what it's been stored at within uploaded. And a key aspect here, after we come outside of the bytes IO library, but inside the read CSV parentheses, we say comma skip rose equals four, because we're still trying to make sure we get those headers correct. So if we run this, and I will come over here and enter down to make that look a little easier. And so you can enter within Python and it'll still work. But now if we come over here to our variables tab, we can see we've got our data frame type data frame as we have in the previous two videos. So this is the final way that we can do it. We can upload into Google Colab. It's a little bit more intensive, a little bit, a couple more steps. But again, it's always an option if you would like to go about uploading in this way. Thank you.