Welcome to video three of our factor module. We're going to talk for a minute about other things we can do with some of the factor verbs. So like anything when you pull up factor, FCT for this package, you can find all sorts of options that you might want to use to deal with factors, okay? So in this case, I want to just play with for a moment factor unique and see how that works for dcclimate month. So this tells me the unique entries that I have. Let's try the same thing for our sizes that we had. Let's see, let's try for S, let's see, factor unique, Sizes. Hang on. Which didn't work real well for something that didn't have a lot of entries in it, right? It's when I want to sort out what the unique levels are. But factor count is very helpful because I can see that I have no entries for the month of June, I have no entries for the month of August, but I have one for NA. So you can also look at the number of levels within levels and see how many levels you have of a particular factor variable. Now, one of the things that is helpful is to be able to plot, right? That was one of our original problems with this. Remember here's our plot, still hanging around here. But now that we have made it into a factor, right? Under month FC, then we can then plot them in order and this is now in the order of the factors. So when I plot a factor variable, it goes in order of the factors. So, if I want, but you can see now June is missing because it wasn't in the data set. So, I can fix that if I want, with using a drop equals false for my X axis and it shows that I have some missing stuff here, right? I don't have an entry for June or August, but I do have this entry for NA. So I need to fix that before I go much further. Okay, I want you to look very quickly at there is a GSS, general social survey data that is built in to this package so that we can play with different categorical variables, okay? So, I'm just going to go ahead and attach this data set. I don't have to keep referring to it and piping it in. Okay, so now I'm attaching the data set and I want you to look for a moment at, let's see, what our, let's look here. We've got you see a bunch of factor variables that are already in here. You see these things with FCT on them? This tells us these are the factor variables, okay? So we could look at what are the levels, for instance, of the variable race. We can see what possibilities there are. We could look at the levels of party ID, okay? So, we could in fact then do a count and see use the count and see how many respondents did we get in each of those categories, right? We can do the same sort of thing. With counting our party ID. [INAUDIBLE] Simple in there. Let's see, let's get rid of that. Okay, so we can see just an overall field by the factors this way and we can look at say a bar graph. Bar race or we can force the levels that don't appear to show up in our graph with our drop equals false. This shows that we had none under not applicable.
