# Set Operations in R and Python. Useful!

Set operations are super useful when data cleaning or testing scripts. They are a must have in any analyst’s (data scientist’s/statistician’s/data wizard’s) toolbox. Here is a quick rundown in both R and python.

Say we have two vectors x and y…

# vector x x = c(1,2,3,4,5,6) # vector y y = c(4,5,6,7,8,9)

What if we ‘combined’ x and y ignoring any duplicate elements? ()

# x UNION y union(x, y) [1] 1 2 3 4 5 6 7 8 9

What are the common elements in x and y? ()

# x INTERSECTION y intersect(x, y) [1] 4 5 6

What elements feature in x but not in y?

# x members not in y setdiff(x,y) [1] 1 2 3

What elements feature in y but not in x?

# y members not in x setdiff(y,x) [1] 7 8 9

How might we visualise all this?

What about python? In standard python there exists a module called ‘sets’ that allows for the creation of a ‘Set’ object from a python list. The Set object has methods that provide the same functionality as the R functions above.

References:

http://rstudio-pubs-static.s3.amazonaws.com/13301_6641d73cfac741a59c0a851feb99e98b.html

https://docs.python.org/2/library/sets.html