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scope - What are the double colons (::) in R?

I am following a tutorial in Rbloggers and found the use of double colons, I looked online, but I couldn't find an explanation for their use. Here is an example of their use.

df <- dplyr::data_frame(
  year = c(2015, NA, NA, NA), 
  trt = c("A", NA, "B", NA)
)

I understand it creates a data frame but I don't understand their purpose.

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As you probably have looked up the help page by now usage of :: helps to access the exact function from that specific package. When you load dplyr you probably got a message as follows..

The following objects are masked from ‘package:base’:
       intersect, setdiff, setequal, union

So, for instance, if you would like to use intersect function from dplyr or base package, you need to specify using the :: double colons. Usage will be as follows

mtcars$model <- rownames(mtcars)
first <- mtcars[1:20, ]
second <- mtcars[10:20, ]
dplyr::intersect(first, second)
base::intersect(first, second)

Update: Added additional explanation

Note: The sequence you load libraries determine the preferential access of the specific functions. Developers of different package tend to use same function names. However, when R encounters a function, it runs through the different libraries that particular session has loaded in a sequential manner. You can check the packages in a session by running (.packages())

 [1] "tidyr"      "data.table" "dplyr"      "stats"     
 [5] "graphics"   "grDevices"  "utils"      "datasets"  
 [9] "methods"    "base"    

As you can see in my example session above, tidyr is the last library I loaded, which is r session 1st entry. So, when you use any function in your code , first it is searched in tidyr -> then data.table -> then dplyr and so on, finally the base package is looked up. So, in this process when there is function name overlaps between packages the one which loaded the last masks the previous ones. To avoid this masking, you specify in R code where to look for the function. Hence, here base::intersect, will use the function from base library instead of the dplyr. Alternatively, you can use to avoid loading of complete library. There are positives and negatives with this. Read the links and learn more.

run and check the differences. Here are some resources for you to get an understanding.

Compare library(), require(), ::

Namespace


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