2. Functions

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    A((Objects)) --> B((Functions)) --> C((Operators))
    style B fill:#1a1a1a,stroke:#1a1a1a,color:#fff
    linkStyle default stroke:#adb5bd,stroke-width:2px

Now that you understand the nature of objects, it is important to understand functions — the other building block of programming in R.

The function performs some operation on an object. For example, class() is a function that returns an object’s class.

Functions can be broken down into this structure:

new_object_name <- function(argument)

Arguments can be: 1. commands to feed the function, 2. objects, 3. other functions, 4. operators.

Using functions on objects

In the case of class(first_df), the argument is a dataframe object. In the case of the function mean(), which calculates the average of a vector/column/variable, you need to specify the column you want it to run the function on.

mean(first_df) returns an error. mean(first_df$pie_num) returns the mean of the column pie_num.

Run this example — using mean() on a dataframe column

Storing function output

Now you can store the output of a function as an object, for example: avg_pie_num <- mean(first_df$pie_num)

Run this example — storing function output as an object

Your turn

Your turn — use median() to find the median of pie_num, then store it in an object called med_pie
Show Solution 
med_pie <- median(first_df$pie_num)
med_pie

What does mean(first_df) return?

In the code avg <- mean(first_df$pie_num), what is avg?

Key takeaway

Creating objects through functions is essentially what you do in R. Everything else is really just various levels of increasingly sophisticated functions to accomplish similar objectives.

Click Next to continue to Operators.