The first time you open RStudio there will be three panes:
The console is where you interact directly with R
The greater-than symbol, >, indicates that are is ready for your input.
The symbol will not be present where you have your output. Instead, you will see a one in square brackets, [1], which indicates the first element of our output.
See what happens when we have an output with multiple elements; for example, we can print the whole numbers from 42 to 100:
42:100 [1] 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
[20] 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79
[39] 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98
[58] 99 10042 is next to the [1] and the next row will show the nth element of the output.
If you see a plus sign, +, it means the console is waiting for more input.
If you don’t want to enter more code, press Esc.
R can be used as a calculator to do basic maths.
3 + 4[1] 7or more complicated arithmetic (at least for many on social media…)
8 / 2 * (2 + 2)[1] 16Here are some of the mathematical operators you can use:
| operator | function |
|---|---|
+ |
addition |
- |
subtraction |
* |
multiplication |
/ |
division |
^ or ** |
exponentiation/order |
() |
brackets |
%% |
modulus |
Performing operations and getting the output immediately is handy, but as we start performing more complicated calculations with multiple steps, it is useful to store outputs in memory.
To store an object in R, we use the ‘assignment operator’, <-. On the left side of the arrow is the name we want to give the object, and on the right side is the object we want to store.
my_sum <- 4 + 2As you may notice, there is no output in the console. That’s a good thing. Take a look in your Environment pane. There is now an object there called my_sum with the value 6.
To print the value of the object, we can use the print() function
print(my_sum)[1] 6or type the name of the object in the console.
my_sum[1] 6We can now perform further calculations on the object.
my_sum * 2[1] 12We can also overwrite the object by assigning a new value to it.
my_sum <- 3 * 9
my_sum[1] 27We can assign multiple values to an object by combining them.
fib <- c(0, 1, 1, 2, 3, 5, 8, 13, 21)and then the arithmetic operations are applied to each element in the vector.
fib + 2[1] 2 3 3 4 5 7 10 15 23fib * 2[1] 0 2 2 4 6 10 16 26 42One of the most common errors you will encounter is
my_sums
#> Error: object 'my_sums' not found
My_Sum
#> Error: object 'My_Sums' not foundR is really good at doing complex calculations. It’s not very good at reading the minds of humans, or inferring what we mean. Make sure you check for typos!
So far we have just worked with ‘numeric’ types. my_sum is numeric, but there are two types of numeric: double and integer.
To figure out what type my_sum is, we can use another R object called a ‘function’. R has a lot of built-in functions that can perform specific operations. You have already seen print(), which prints objects. We can use class() and typeof() to figure out what is my_sum.
class(my_sum)[1] "numeric"typeof(my_sum)[1] "double"Other types include
TRUE # logical
FALSE # logical
NA # logical
"string" # character
"also a string" # character
NULL # NULLThe true power of R is in the packages. The functions and other built-in objects we have been working with so far are part of ‘base R’. Stuff that is made available to you when you download R. You can get a lot done with base R. Using packages allows you to extend the functionality of R to pretty much anything you can (and can’t) imagine.
Packages are developed and maintained by R users who found something that R couldn’t do, or was awkward to do, and made a package to fix this. Packages are reviewed by the Comprehensive R Archive Network, or CRAN (Sounds familiar? this is likely where you went to download R).
At the time of writing, there are currently 21,205 packages on CRAN. And those are just the official packages that have gone through the submission procedure. There are many more also available on GitHub and other git-hosting platforms. But mostly GitHub (for better or worse).
There are a few different ways to install packages.
The quickest way is to do it from the console using the install.packages() function. For example, to install the tidyverse package:
install.packages("tidyverse")Just make sure to check your spelling (it’s also CASE-SENSITIVE).
The other option is in RStudio: Tools > Install Packages…
Installing a package makes it available on your device, but does not load it in R. To do that we use library().
library(tidyverse) # note no quotation marks
When you close RStudio, the packages will be unloaded, and you will have to load them again the next time you open RStudio. This allows R(Studio) to be very lightweight and not accumulate loaded packages resulting in a longer time to open RStudio.