I'm brand new to R. In my quest to become fluent in the statistics and linear algebra aspect of Machine Learning this year, I've ventured toward learning R in all its glory (I might also go with Python/Matlab for the linear algebra aspect). As a part of that venture, I bumped into how one could actually give names to rows and columns in R's matrix.
Here's how to do so:
First, you get your column and row names defined:
localities <- c('Koteshwore', 'Battisputali', 'Chakrapath', 'Kalanki')
localities above stores some localities in the Kathmandu Valley. We will have this vector as our row of the matrix we will define shortly. Before that, let's get t defining our column as another vector:
ponds <- c('Ranipokhari', 'Khhichapokhari', 'Panipokhari', 'Gahanapokhari')
ponds vector stores some pokharis (पोखरी, in Nepali) around the Kathmandu Valley. A pokhari in Nepali, as you might have guessed by now, means a pond, in English.
Moving on ... so how far are the ponds from the localities we defined above? Let's create more vectors, shall we?
distance_from_koteshore <- c("8.5", "7.5", "4", "9")
distance_from_battisputali <- c("4", "5", "5.5", "3.5")
distance_from_chakrapath <- c("5", "6", "2", "5")
distance_from_kalanki <- c("9", "8", "12", "11")
Those distance are in kilometers (My approximations).
Can we create the matrix already?
distance_matrix <- matrix(c(distance_from_koteshwore, distance_from_battisputali, distance_from_chakrapath, distance_from_kalanki), nrow=4, byrow = TRUE)
Finally, right? Alright, printing out our
distance_matrix in RStudio gives us the following:
Cool! Well, almost ... would be way cooler if we could just name the rows and columns too. And we can. Remember our
ponds vectors above? Let's put them to good use:
colnames(distance_matrix) <- ponds
rownames(distance_matrix) <- rows
Look what we've got! A readable, understandable matrix:
Wooohooo!! Why didn't I learn this amazing language before? I mean look at that matrix and the promise it shows. I've got my localities, my ponds, and my approx. distances all captured in a clear, readable matrix. I mean: what more do I need?
A lot more, for sure.
In my next post, I intend to dig a bit more into R and capture my findings here.