fav_nums <- c(1,5,12,8,58) #Making a vector of values
mean_fav <- mean(x = fav_nums, na.rm = TRUE)
mean_fav[1] 16.8Functions
R and Functional Programming
At the core of using R is utilizing functions, which are statements that takes in data and a set of parameters and returns an object with something being done to the data provided. Functions are how you read in your data sets, clean them up, do statistical analyses, and visualize your data. You can even make your own!
Function Syntax
Before we get into some basic and common functions, one must first understand the components of a function. Below is the mean function, which as the name implies, finds the mean of a given set of values.
The structure of a function is the function’s name followed by a set of parentheses. For some functions that require no additional information, that is all you need. However, most functions require providing data objects and parameters so that the function is applied to a specific object in a specific way. For example, in the mean()function above, there are two parameters:xandna.rm
In this case, the x parameter is where we provide the data object that mean() uses. We assign the data object fav_nums to the x parameter using the parameter assignment operator, =. Generally, the very first parameter of a function will be where you provide the data object.
Similarly to assigning the fav_nums object to x, the logical value TRUE is assigned to the na.rm parameter, which tells the mean() function to remove any NA values in the provided set of numbers if there was any.
Something that makes writing functions easier is that there is a given order of parameters in a specific function. For the mean() function, there are three named parameters: x, trim, and na.rm. Rather than having to provide the parameter name, you can just provide the value for the parameter instead of the full parameter = value statement.
mean_fav <- mean(fav_nums)
mean_fav[1] 16.8Additionally, functions can have some parameters have default values. These default values are what a function uses if you do not provide an alternative value. An example of this is for the first usage of the mean() function. I did not provide a value for the trim parameter, yet the function still worked. This is because the mean() function provides a default value for that parameter. You can override that default value by setting the parameter to what you wish. An example is that the default parameter value for na.rm for the mean() function is FALSE, but I set na.rm to TRUE.
The most readily available source of information for understanding what a function does and what the specific parameters it uses is the help tab in RStudio. You can search by the function name and it will provide a reference guide to the function.