There is one package in particular that is not only tremendously useful but has also has had an enormous impact on the greater data science community. This is the Tidyverse package. The Tidyverse is actually a collection of packages, containing other packages such as ggplot2, dplyr, and tidyr. So when we install and load the Tidyverse package we are actually installing and loading all of the packages within its scope.

We have already pre-installed the Tidyverse package in our coding environment, so only the output from the library(tidyverse) is going to print out, let's see what we get here:

Let's examine what is printed out above. At the start of the first line it says Attaching packages, and at the end of this line it says tidyverse 1.3.2. The numbers here indicate the package version number that we learned about in the Packages lesson.

In the Attaching packages section it lists the packages and their versions that are being brought in, such as ggplot2 at version 3.4.0 and dplyr at version 1.0.10.

In the next section it says that there are some conflicts. The first conflict is

dplyr::filter() masks stats::filter()

What this is saying is that there is already a function called filter that was brought in from the stats package. The stats package is one of the packages that comes pre-installed and loaded in every R session. Since there are now two functions with the same function, if we use filter, then it will use the one from the dplyr package, that's what the masking means. We can still use the one in the stats package, we would just need to refer to it's namespace when calling it, so we woul need to call it as stats::filter.

dplyr::lag() masks stats::lag()

The second conflict is is the same issue as the first one, the lag function in the dplyr package will be the one called if we use lag, but we can still use the one in the stats package if we call it as stats::lag.