Good! Now you can convert numbers into integers while creating. But what if you want to convert specific results? Putting `L` will not help and raise an error, like in the example below.

# Some number
num <- 20
numL # Trying using L for converting

The output of the script above is:
```
Error: object 'numL' not found
```
Surely, not what we were wanted to do.

R provides us with very simple and convenient functions to convert variables/values into different formats. These are `as.double()`, `as.integer()`, `as.complex()`. See, the functions' names are intuitive!

There is a 'hierarchy' within numerical types, i.e., each `integer` number can be converted into `double` and `complex`, and each `double` can be converted into `complex`. `complex` numbers can not be converted into either `double`, either `integer` type (unless the imaginary part is 0). `double` numbers can be converted into `integer`, but this will not round, but *truncate* to integer part.

R is one of the most popular programming languages among data analysts and data scientists. R has a wide community that will always help you with any problem. Also, R has tons of different packages designed to solve various problems. The language can be easily applied to statistics and data analytics problems. In the first part, you will be introduced to the very basics of R and will deal with single 1-D values of different types.

In the first section, you will consider the very basics of R - outputting and performing basic operations. You will finish the section with the variables theory.

In the second section, you will learn the vector class in R, which represents single values too. You will consider the main data types for single values and how to work with multiple values of a kind at once.

Converting

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