So far, we have seen creating different visualizations through ggplot2 package, and we realize that it's not easy to remember those commands. And that's why as promised we are going to share a tool which is going to allow you to create those graphics without writing codes. But remember, when you move to something which does not require you to write codes the flexibility is going to be less. But for your initial plotting tasks, I think it would just be fine. The package that you need for building ggplots without code is known as esquisse. It's a French word, so you need to install the package. I have already installed it here. So I am directly going to take you to where you start working with this. So you go to Add in and Add in is a very nice feature in R Studio now and it allows us to add lot more functionalities to R without coding. And I use many of those add-ins and one of them is this ggplot2 builder, that actually comes when you install the package esquisse. A few things before we get there. You need to have your data loaded in your environment variable. So I have already loaded a subset of the, data in the data frame called DF. Once I have it there, I go to Add in, then GGplot Builder. So once we are here, first thing that we need to do is choose of a data frame. This is the first object of ggplot2. Now you can make some selection if you want to make some changes in your variable types. The best way is change them before you bring here because every time you make a change here, it's not recorded in the data. So once you are out of this builder, the changes go away. Right now I'm just going to go as we have the data. So we only have to worry about like top three layers. The first one is the data, second one is the aesthetic mapping, and the third one is the geometric object we want to create. And this is where ggplot builder helps us a lot, because it just forced us to read the data. That means the data part is already taken care of. Now we have all these variables sitting at the top and all these options x-axis, y-axis, fill, color, size group, and facet. They are going to allow us to do the aesthetic mapping part. And the options here are the geometric objects. So it's so easy, if I have to let's say make a histogram of price. What I can simply do is data is already there, I need to specify the aesthetic mapping and I just drag price here. When I do this, let's just look at the code. What we have got in the code is ggplot has got the data. In the aesthetic mapping I have got the price and it has automatically selected histogram and certain options in that. You can always copy this code which I would suggest you do, copy this code and take it to your R and run it from there, so that you can recreate these plots again without coming here. It has automatically selected histogram, if you want to change. So things that are not allowed for this type of variables will be shown like this. We see that we can also create box plot and I create a box plot here and it will looks exactly similar to what we had earlier. And if you see the code has changed from geom_hist, now he geometric object has changed to geometric underscore box plot. If I bring a categorical variable, let's say department. What I see is a bar chart which is the standard graphic for a categorical variable. If you go and see the code, you will see the difference. You know now the geometric object is geom_bar and aes, aesthetic mapping is x equals to department. If you try to do a histogram it will not allow you, make sense. Now, there were other layers also that we really didn't go into much detail such as labeling, such as themes. You can take care of these things here, I would recommend that you try these options like typing something and see where exactly does it come. So the title comes here. There are these plot options which allow you to either flip your coordinate or do something like choosing themes, try to learn better. And then the last thing here to see is the data. So you can always subset your data right on the fly here. So if you only want to focus on let's say like there are these nine departments. If you want to focus only on just couple of them just remove the other and it allows you to do that. And when you go to the code, you will see that this filtering is going to happen here. I can always bring this facet to create charts for separate subsets of data. If I am showing the histogram for price, I can always bring a categorical variable in the facet to create different histograms for each department. Lastly, don't forget to look at the code every time you run the command and copy the command to your clipboard and take it to R, take it to r to run this code there and you should be able to reproduce the same graphics. Here you see, so hopefully you appreciate that this ggplot builder allows you to create nice ggplot graphics without writing the code. But my suggestion would be to play with ggplot builder to get better at writing ggplot2 codes. Gradually, you should move to writing your codes to really enjoy the flexibility that ggplot2 package offers.
