Viewing Data and Variables
In this lesson we will go over how the print function works and
how we can use it to print text or a dataframe.
In programming, a simple yet fundamental function is one that displays the content
of a variable. If we want to display the text "Hello World!" we pass this text
as an argument to the print function.
Let's consider another situation.
Imagine a loading screen during a game's installation process.
This screen might show a percentage to indicate progress.
It comprises static text and a dynamic number such as "Progress: 16%".
The print function we just learned can combine these two things
together with some difficulty. However, there is another function which
makes the task easier, the cat function. "cat" stands for concatenate,
which means to join together. The cat function joins
together the arguments provided to it and prints them out.
Let's see an example of this.
While the cat function is useful for combining
text and numbers to print out, it has one drawback in comparison
to print, and that is, it does not automatically start
a new line with each call. This means that if we want to print
out multiple lines of text, we need to embed within the text the
\n character, which is a special character sequence,
known as an escape sequence, that tells R to start a new line.
In the next code block, try running it first, then try running it again after deleting the escape sequence and see what happens!
Printing dataframes
The simplest way to print a dataframe is to include it inside a print
statement. For instance, after creating the iris dataset,
we can use print(iris). However, as this dataset has 150 rows,
this will display the entire dataset, which may be a tad overwhelming.
Instead, we can use other functions called head or
tail to view the first and last six rows,
respectively. The number of displayed rows can be adjusted
with an optional input.
There was something else we snuck in there and that is a comment.
A comment begins a line with the pound symbol #,
which tells R to ignore anything found after it.
What might happen if we have an R program that
contains only comments? Well, nothing will happen! So why are they
important? Comments are added to code to help fellow data scientists,
developers (or yourself a year from now) have a better understanding for
why a line of code is written the way it is. This is incredibly useful in
maintaining a code base as sometimes we need to understand the
history / reason / purpose of a code chunk to really understand it.
We can further access a single column of data from the dataframe by
writing the dataframe name and the column name separated by
a dollar sign $. For instance, to access the
Sepal.Length column, we write iris$Sepal.Length.
Practice exercise
Assign to a variable a the string Hello World.
This will be printed out with the provided cat function.