data_types.qmd

# Data Types {#sec-data-types}

## Questions

-   What are the primary data types in R?

-   Can one convert between different data types?

-   How does R handle different types of data?

-   How can I determine variable type in R?

-   What are some helpful functions for identifying and manipulating data types?

-   How do data types impact my analysis and coding in R?

## Learning Objectives

-   Identify and differentiate between common data types in R.

-   Learn how to convert between different data types.

-   Use functions like `class()`, `typeof()`, and `str()` to inspect types.

-   Convert between data types using the `as.___()` functions.

## Lesson Content

### Introduction

R and RStudio utilize multiple data types to store different kinds of data.

The most common data types in R are listed below.

| **Data Type** | **Description**                                                                                                                                                                           |
|----------------|--------------------------------------------------------|
| Numeric       | The most common data type. The values can be numbers or decimals (all real numbers).                                                                                                      |
| Integer       | Special case of numeric data without decimals.                                                                                                                                            |
| Logical       | Boolean data type with only 2 values (`TRUE` or `FALSE`).                                                                                                                                 |
| Complex       | Specifies imaginary values in R.                                                                                                                                                          |
| Character     | Assigns a character or string to a variable. The character variables are enclosed in single quotes ('character') while the string variables are enclosed in double quotes ("string").     |
| Factor        | Special type of character variable that represents a categorical such as gender.                                                                                                          |
| Raw           | Specifies values as raw bytes. It uses built-in functions to convert between raw and character (`charToRaw()` or `rawToChar()`).                                                          |
| Dates         | Specifies the date variable. Date stores a date and POSIXct stores a date and time. The output is indicated as the number of days (Date) or number of seconds (POSIXct) since 01/01/1970. |

### Examples of data types in R

1.  Numeric

```{r}
89.98
```

```{r}
55
```

2.  Integer

```{r}
5L
```

```{r}
5768L
```

3.  Logical

```{r}
TRUE
```

```{r}
FALSE
```

4.  Complex

```{r}
10 + 30i
```

```{r}
287 + 34i
```

5.  Character or String

```{r}
'abc'
```

```{r}
"def"
```

```{r}
"I like learning R"
```

**NOTE: A comprehensive overview of handling characters with the `stringr` package will be provided in a subsequent series on the Tidyverse.**

6.  Dates

```{r}
"2022-06-23 14:39:21 EAT"
```

```{r}
"2022-06-23"
```

7.  Raw

```{r}

```

8.  Factor

```{r}

```

### Inspecting various data types

Several functions exist to examine the features of the various data types. These include:

1\. `typeof()` – what is the data type of the object (low-level)?

2\. `class()` – what is the data type of the object (high-level)?

3\. `length()` – how long is the object?

4\. `attributes()` – any metadata available?

Let’s look at how these functions work with a few examples:

```{r}
a <- 45.84
b <- 858L
c <- TRUE
d <- 89 + 34i
e <- 'abc'
```

1.  Examine the data type at a low-level with `typeof()`

```{r}
typeof(a)
```

```{r}
typeof(b)
```

```{r}
typeof(c)
```

```{r}
typeof(d)
```

```{r}
typeof(e)
```

2.  Examine the data type at a high-level with `class()`

```{r}
class(a)
```

```{r}
class(b)
```

```{r}
class(c)
```

```{r}
class(d)
```

```{r}
class(e)
```

3.  Use the `is.____()` functions to determine the data type. To test whether the variable is of a specific type, we can use the `is.____()` functions.

First, we test the variable a which is numeric.

```{r}
is.numeric(a)
```

```{r}
is.integer(a)
```

```{r}
is.logical(a)
```

```{r}
is.character(a)
```

Second, we test the variable c which is logical.

```{r}
is.numeric(c)
```

```{r}
is.integer(c)
```

```{r}
is.logical(c)
```

```{r}
is.character(c)
```

### Converting between various data types

To convert between data types, we can use the `as.___()` functions. These include: `as.Date()`, `as.numeric()`, and `as.factor()`. Additionally, other helpful functions include `factor()` which adds levels to the data and `nchar()` which provides the length of the data.

#### Implicit vs. Explicit conversion

Examples

```{r}
as.integer(a)
```

```{r}
as.logical(0)
```

```{r}
as.logical(1)
```

```{r}
nchar(e)
```

Order of precedence when converting between data types is:

Character `>` Numeric `>` Integer `>` Logical

## Exercises

-   What are the basic data types in R? Give examples of each.

-   How can you check the data type of a variable in R?

-   Use the `class()`, `typeof()`, and `str()` functions to check the data type of objects.

-   Describe the process of coercion in R.

-   Provide an example of implicit and explicit coercion between data types.

-   How can you coerce or convert between different data types in R?

-   What does it mean for an object in R to have attributes? What attributes are commonly used?

## Summary

In this chapter, I have demonstrated the primary data types in R. Additionally, the learner has been trained on how to identify and convert between the different data types. Next, we will review vectors, which are key data structures in R/RStudio.