 Data, if I wanted to edit the data, there's our editing of the data, closing this back out, closing this back out, and then you've got your formatting options as well. So there's the formatting options for the chart. Now, the other way you can go into that stuff is sometimes you can right click on a particular item. So oftentimes when I wanna add the data labels, I'll go here and then add data labels, so that I can add the data labels like that, and I can then format the data labels if we so choose, possibly making them a little larger or bolding them or something, and then you have your options on the right, which once again you've got the axis, you've got the axis titles, you can see the titles kind of popped up there. If you needed those, you've got the chart title, which is often what you might put into a chart like this, because this is usually representing one kind of set of data labels, grid lines, if you want the grid lines on or off, you can remove the grid lines, and we've got the legend, we don't usually need a legend here, and this one gives you another place to find kind of more options. So there we have it. All right, so now let's make another one and let's just do some comparisons and we'll change some of those options. The biggest change I wanna think about is, well, if I was presenting this data, what would it look like? And remember, there's two ways you wanna think about this. One is I wanna make the histogram so it represents the data in such a way that I can get an understanding of it. And two, I wanna know how if I start to change the bucket sizes and possibly the heights of these, what would that do if someone was trying to manipulate me with or manipulate someone like advertising or something like that using the data to try to get to a certain narrative? In other words, if someone's trying to argue their point and they're presenting data to argue their point, they might manipulate their graphs to articulate whatever point that they're looking at. And if we're trying to be in an honors conversation within that environment, which is often the case, we're gonna have to be able to see that so that we can know what's going on. So if I select the data again, let's go and say we insert another histogram and I'm gonna pull this down to the bottom. And so now we can say, all right, let's take the title off of this one and let's change the bucket sizes now. So I'm gonna click on the bucket sizes and say, well, what would that do if I went into my categories here and if I say that I want a very large buckets like 500 or 5,000 space between them, that's gonna change the size of the buckets a lot, right? So now you got from 55 to 60. If I bring that even larger to like 7,000, now it looks quite centered now at this point in time. Now that might not be a, this may not be like a misrepresentation of the data, but it certainly kind of gives you a different feel than this chart, right? Because of the size of the buckets. So, you know, if you were arguing here that yeah, well, there's no really, if someone was arguing, well, there's no really outliers here, everything is basically kind of everybody, most of the people fall in the middle, you know, kind of thing, then if you increase the bucket size, you know, that might give you that kind of sense or feel, you know? So that, you know, that's one thing that they could look different. Let's make another one and go the other way. So I'm gonna make another one. I'm gonna insert my data set here again and say let's insert chart and another histogram. Let's pull this at the bottom. And let's say now we're gonna make a whole bunch of buckets. So now I'm gonna say, all right, let's increase the size of the buckets. So I'll make this a little wider. And so let's go to our data down below on this one. And I'll go to my symbol on the right and we'll say, well, what if I bring this down, this bend width down to like 500. So now I just have a $500 difference. Well, now the data is getting so spread out that it might not be giving you relevant information. It might, it's still giving you a kind of a feel of where everything is lying here. So that gives you a pretty good feel, but you can see how you can go too far here. Like if I made this $20, then that's not all that useful. This looks like a mess. If I bring it up to like $30, then again, it's not exactly a useful thing. If I bring it up to $100, still not very helpful, $200. Right now you're getting something that resembles a data set. And again, that might be useful to some degree, but notice you're getting a whole different kind of feel for the data when I look at it in this format, then this format, then this format. And so you have, so when you look, and this is what leads people to start thinking that the data's just manipulative. It's all relative, right? What's the point? But the point is that you need to look at it from different angles in order to get in order to get a sense of the data. So one angle at the data usually isn't the full thing. If you're only getting one picture of the data, then you might be being deceived, right? So if I go, there might be some manipulation going on. There should be multiple pictures to try to get a feel of what is going on for the data ideally, right? So if I select the data again, if I insert again, and let's insert another one, and let's pull this down. And let's say that we bring this down here. And let's get rid of the title on this one. And this time, let's possibly adjust this side of things. So I could say, well, let's go to double click it on this one, and I go to the axisies. And it's going from zero. If I brought this up to like 100, then now you get kind of a squat type of graph, which gives you a kind of a different look and feel for it. There you might say, well, and again, notice the difference between, if I looked at this one, you're saying, ah, well, there's a pretty tall difference between some of these, but if you were to add a larger column size, then everything looks a little bit more squat, right?