Welcome back. As we discussed earlier, packages are a big part of what makes R so great. Packages offer a helpful combination of code, reusable R functions, descriptive documentation, tests for checking operability, and sample data sets. And for lots of data analysts, at the top of the list of useful packages is tidyverse. Tidyverse is actually a collection of packages in R with a common design philosophy for data manipulation, exploration, and visualization. Using tidyverse can help you work your way through pretty much the entire data analysis process. The packages in tidyverse work together naturally. I started learning about tidyverse when I was working on a survey project. It felt like I was stepping into a more advanced zone of R. I understood the basics, but now I was finding out how the tidyverse improves on the basics. That's when I got even more excited about working in R. I realized that the more I put into learning about the tidyverse, the more I get out of it. On top of that, the community support for tidyverse is strong too. It's one of the reasons why tidyverse is considered a key part of programming for most R users. The principles associated with tidyverse, which you'll learn both here and at your job, have been widely adopted by the R community. You'll find lots of tutorials and examples related to the tidyverse online that show you these principles and how they're applied to data analytics. Okay, let's install the tidyverse. You can follow along on your own, using your RStudio cloud account. Check out the reading for more details. Earlier, you learned how to find Base R packages using the function install packages. To install packages like the tidyverse that aren't in Base R, we'll use the install packages function. As we discussed earlier, this function calls the tidyverse and other packages from CRAN. Let's talk about why CRAN was created. Since packages not in Base R are mostly made by R users, people need a reliable way to check and validate submitted code. CRAN makes sure any R content open to the public meets the required quality standards. So, if it's sourced through CRAN, you can feel good that the package is authentic and valid. Another major source of packages and other R content is GitHub. Now, we'll get back to installing the tidyverse. We'll first type install.packages. Then, between the parentheses, we'll type tidyverse in quotes. The quotes aren't always necessary, but best practice is to use quotes to make sure that we are accurate. We'll press Enter and wait for RStudio to install tidyverse. When we click on our packages tab, we come across a lot of new packages on the list. That's tidyverse. You might have noticed that none of the packages are checked off. We need to load them first before we can use them. But that's a mighty long list. So, let's just load the package named tidyverse for now, using the library function. The return shows that not only was tidyverse loaded, but eight other packages were too. It also shows a list of conflicts. Conflicts happen when packages have functions with the same names as other functions. Basically, the last package loaded is the one whose functions will be used, so we'll stick with the tidyverse functions. But it's important to note that these messages only appear once. So, as you get more used to R, you'll be able to figure out if you want to use certain functions over others. The loaded packages are ggplot2, tibble, tidyr, readr, purrr, dplyr, stringr, and forcats. These packages are the core of the tidyverse because you'll use them in almost every analysis. All of them work together to make your data analysis smooth and efficient. With these packages, tidyverse helps you do everything from importing and transforming data to exploring and visualizing it. We'll check out this core of packages soon, and we'll use them even more as we continue working in RStudio. If you're working on your own in R, you can check out some of the other packages too. The packages available in tidyverse change a lot, but you can always check for updates by running tidyverse_update() in your console. You can then update the packages in a couple of ways. If you use the update packages function, it'll update all of your packages. That might take a while. So, if you just want to update one package, you can use the install packages function again with the package name as your argument in parentheses. You should update packages regularly to make sure you've got the latest version in your code. Conflict notifications are just one type of message that can show up in the console. You might find warnings and error messages as well. A quick search using the help tab will usually tell you what the message means and what, if anything, you'll need to do to address it. Coming up, we'll keep moving through the tidyverse. You'll find out more about why tidyverse is such an integral part of R. See you.