 Okay, so we have a couple more things I want to show. The first one is, you know, how to delete columns and rows. So for this, we can use the drop function. And so depending if you want to delete columns, I think this we've already seen it before, right? I can use DF, I do use a drop method and pass the name of the column. And if I wanted to delete a row, then I would pass the argument index and give the index of the row to delete. Drop also takes these in-place arguments that can be true or false, depending on if you want to return a copy of the data frame or modify the actual data frame. Okay, so let's just quickly look at the example. So we have our original data frame here. Now let's say we want to delete the name column. So I will, here I will put it in a variable, but you can also pass it directly. But here I set column to delete equals name. And then I will call the drop method and pass it column to delete. And you see that because I did not specify in place equals true, what I got is a copy of the data frame. So in my original data frame, I still have the name column, but not in the copy. And if I now had, if I put in place equals true, then you see that the value that is returned is now a data frame. It's a object none, because when you put in place, then the function returns none. And what happens is that it modifies the original data frame. So now the column name is no longer present. If I test, if the column name is present in the original data frame, it's deleted. And the last thing we want to see is how we can then, once you finished doing your analysis, maybe you did some changes to your data frame, like you maybe updated some columns or you added some new columns that you want to keep. And so you want obviously to make your work permanent. You want to save this, you work to a file. Okay, so basically you want to export the data frame to a file on disk. And here it's again, just like for reading, there are a number of different functions that will export to different file forms. So you have, for instance, two CSV to write a file to a comma separated text file. But if you wanted to export to Excel, you'd also do this with two Excel or one HTML document with two underscore HTML and so on. You can click here to see other formats to which you can export. Okay, and then the way that you use this method is very simple. You simply take your, the data frame you want to export, you call the two CSV method on it and you pass as argument to give the name or the pass of the file where you want to write. Okay, so if I export my data frame to CSV, here I will create a file called my data. If I go into my notebook browser, I should see that I have now a file named my data. And if I open it, it will contain the data export. Yeah, again, you have a couple of options. I mean, you have many options that you can pass to these functions. So maybe most useful being set just like when reading, when writing, you can also specify which character should be used as separator in your output file by default. It's a comma, but I could change this to something else. And I can specify if the header should be, for instance, included or not in the output, in the export of my file.