Common Data Creation Commands

Here is a video tutorial where I go through some of the most commonly used commands in creating and manipulating data. As soon as I want to do more than just running a single regression, I use these commands more than any other set of commands (in some of the other videos, you may have seen these).



Here is the code I use in the video if you would like to try out these commands for yourself.

	## ------------------------ ##
	## Data Creation in R ##
	## Tutorial by Tony Cookson ##
	## ------------------------ ##
	## Simplest way to create a vector is to use the colon.
	a = 1:4
	b = 4:1
	a
	b
	## But, they're just sequences
	## c() can be useful for creating more interesting
	## vectors
	y = c(1,2,3,6) ## basic usage
	y2 = c(a,b) ## binds vectors together into one vector
	## More interesting... can create a vector
	## recursively
	weight = NULL ## It can be useful to initialize a null vector to define the vector recursively
	for(i in 1:14){
	temp= rnorm(10, mean = i*5, sd = 2)
	weight = c(weight, mean(temp))
	}
	## seq() is a fancy way to create a vector
	seq(1, 4) ## Same as 1:4
	seq(0.5, 4) ## Default Step is 1
	seq(1, 4, by = 0.5) ## Can Go in different number of steps
	seq(1, 4, by = 0.4) ## Doesn't have to partition the interval (1,4)
	## It can be useful to repeat a short sequence many times
	## The rep() command is useful for this.
	x1 = c(1,2,3,1,2,3,1,2,3,1,2,3) ## 1:3 repeated 4 times
	rep(1:3, times = 4) ## More efficient
	x2 = c(1,1,1,1, 2,2,2,2, 3,3,3,3) ## 1:3 each element repated 4 times
	c(rep(1,4), rep(2,4), rep(3,4)) ## Can do it this way
	rep(1:3, each = 4) ## Or use the "each" option (Most Efficient)
	rep(1:3, each = 4, times = 2)
	## Can be useful to organize into a matrix
	y = rnorm(12, 8, 2) ## Creates a length 12 vector with a mean of 8 and sd = 2.
	## I could also use c() then give the matrix dimensions
	x.vec = c(y, x1, x2)
	Xalt = matrix(x.vec, ncol = 3) ## coerces vectors into matrices
	Xalt2 = matrix(x.vec, nrow= 12) ## Equivalent
	Xmess = matrix(x.vec, ncol= 3, byrow=TRUE) ## Can reverse the way the matrix is filled
	Xmess = matrix(x.vec, ncol= 12, byrow=TRUE) ## using byrow
	## If I want x1, x2, and y in a matrix,
	## I can use cbind() and rbind()
	X = cbind(y, x1, x2)
	Xrow = rbind(y, x1, x2)
	## Maybe I want to use the names, too.
	## Then the data.frame() command is useful
	Xdf = data.frame(y, x1, x2)
	Xdf ## The matrix
	Xdf$y ## the vector named y...
	## nice to have variable names

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