 Hi folks, this is Dr. Don. I want to spend a few minutes doing a walkthrough of the lab one quick start and also your remix on that. Now, I'm just going to use the lab01studentname.rmd file, which you get over here in your files window. And what you got to do is just click on it to open it up and this opens up. This is called a source window or the editor window and we'll talk about that a little bit more. First thing you want to do though is to change the name. This is called a YAML up here at the top, the Y-A-M-L. Don't worry about it, it stands for you. You want to be very careful up here and make changes. We want to change the student name to the ger name and put the current date in there and then you can save it to get your name in there. The other thing you want to do is to change the name of the file. That will help a little bit and go down here in the files menu, click on the student name and then find the rename and what you would do is to put your cursor there, backspace and I'm just going to put my initials DEW. So I wouldn't know that but you would put your first name and last name there and so now you can see we've renamed that file and that's the remix file that you'll be submitting. Scroll on down here. It's got some code chunks you need to worry about. This is for the actual knitting. That's the code that controls that and as we scroll down you see the first thing is loading the library. I want to speak just a minute. The newer versions of RStudio IDE and remember that PositCloud is just RStudio IDE in the cloud so that you don't have to load it on your local computer. But it's the same. It's called the RStudio IDE IDE stands for integrated development environment and it's really just a way of making it a little bit easier to navigate the R code. Down here in this window this is the console and this is where the R code really runs and you can see we can do a lot of things in RStudio IDE to make it a little bit easier to understand what's going on down here and that's the reason we want you to use the RStudio now also called PositCloud. First thing we want to do is to load the packages and quite often when you're loading packages into the library you'll get a lot of warnings and messages that will maybe distract you a bit. What we really care about is known as errors and so I've added this little message there code there to suppress the warnings, suppress the messages so it would make it a little bit cleaner when you run it. Errors would still show up and you want to pay attention to those. Okay and we've got these five packages. I'm not going to spend a lot of time on those. Tidyverse is the main one. That controls makes it easier for us to manipulate data and do things in a logical way and then we've got the UNVotes which is the library that has the data that we're going to use. So I'm going to go ahead and run that code. Use a little green triangle there to run that code block and the next thing we're doing here is to join these three data frames together. In order to make it a little bit easier to see I've added in a code chunk here and this is a comment after the pound sign. I want to inspect the three tables. The UNVotes table UN roll calls table and the UN roll call issues table and to do that I'm going to create some temporary data objects or data files or data frames recall just by using their names and this is the assignment operator there. I need less than with a dash so it says assign UNVotes to a data object known as UNVotes and they will show up over here in the environment. So I'm going to click that green arrow, run the current chunk, run those chunks and you can see now we've got these three data frames data objects created over here in the environment and you can see it gives you a summary there. The UNVotes has roughly 870,000 observations. Observations are the rows, four variables those are the columns. UN roll calls has 6200 observations of nine variables and UN roll call issues has 5,725 rows or observations of just three variables and we want to pull these together into one table. Let's look at a little bit. The UNVotes by clicking on the little blue triangle there in the blue circle you can expand it. You can see it lists the four variables we have there and what type of variable they are and starts printing those out you could actually scroll to the end and you can see all those. Another way of seeing what this looks like I'm going to double click on the name UNVotes and it opens up over here and now you can see a little bit more clearly we've got the RCID number which stands for roll call ID number the country country code and what their vote was. So I'm going to look at UN roll call votes you can see now we've got nine we've got the RCID again that's a common variable which session it was a supporting vote now we've got the date and we've got some descriptions of it and again if we look at the issues it's only got three variables RCID again short name for the issue and the long name for the issue we want to put all those together so I'm going to go back here to my markdown sheet and we're going to run this and we're going to join together and create another data object called UNVotes with no dash so I'm going to do this one at a time so you'll see what's happening I'm going to go over here and highlight that short of the pipe operator the pipe operator is that percentage greater than sense than which again tells us just and then do the next step takes whatever we do here and pipes it into the next step so I'm going to run that with control enter and now you'll see that we've added a data object here 870 000 of just the four variables because all we've got in there is that original table so now I'm going to do an inner zone join don't worry about inner join outer join those are things for data wranglers we don't do that in this course so I'm just going to highlight the first two stopping short of the pipe operator this time so I want to merge the UNVotes and then inner join UN roll call so control enter and we can see over here that UNVotes has changed again now we've got our same 870 000 rows but now we've got 12 variables and then we'll do the same thing again running all three of these and we'll end up with UNVotes without the underscore having 14 variables that's all our information merged together and if we look at UNVotes when we're closely and you can scroll over here and see all 14 variables have been put in there and the common column that joined by the RCID so I hope that helps a little bit on this first part and then I'm going to stop here and we will move on to the plotting part in the part two of this debrief walkthrough