# Grouping functions (tapply, by, aggregate) and the *apply family

*updated a few hours ago*

The Ultimate Guide to Grouping Functions in R 🧩🔀

Are you a fan of making your code "map"py in R? 🤔 We all love using the `apply`

family of functions for their versatility and power. But have you ever been stuck trying to figure out which one to use and when? 🧐 In today's blog post, we'll demystify the differences between `sapply`

, `lapply`

, `apply`

, `tapply`

, `by`

, and `aggregate`

. Let's dive in! 💡

`sapply`

- The Vector "Transformer" 🦸♀️

When your input is a vector and you're expecting a vector or matrix as output, look no further than `sapply`

! 🌟 It applies a function to each element in your vector and returns a matrix if your function has a multi-element output.

Here's an example:

```
vec <- c(1, 2, 3, 4, 5)
f <- function(x) x^2
sapply(vec, f)
```

Output:

`[1] 1 4 9 16 25`

`lapply`

- Unleash the Power of Lists 📚

Similar to `sapply`

, `lapply`

is perfect for vector inputs. The key difference is that `lapply`

always returns a list. 📋 So if you prefer your outputs neatly organized in a list structure, use `lapply`

.

```
vec <- list(a = 1:3, b = 4:6, c = 7:9)
f <- function(x) sum(x)
lapply(vec, f)
```

Output:

```
$a
[1] 6
$b
[1] 15
$c
[1] 24
```

`apply`

- Master of Matrices or Arrays 🧮📈

Let's step it up a notch! If you need to operate on matrices or arrays, `apply`

is your go-to function! 💪 Specify the dimension (`1`

for rows, `2`

for columns) you want `apply`

to work on, and it will apply your function accordingly.

Here's an example:

```
matrix <- matrix(1:6, ncol = 2)
f <- function(x) sum(x^2)
apply(matrix, 1, f)
```

Output:

`[1] 5 61`

`tapply`

- The Grouping Maestro 🎭🎩

Say you have a vector and you want to apply a function to different groups within that vector. Fear not, because `tapply`

has got your back! 🙌 It returns a matrix or array where each element represents the value of the function at a grouping. The grouping labels are conveniently pushed to the row or column names.

Let's illustrate this with an example:

```
vector <- c(1, 2, 3, 4, 5)
grouping <- c("A", "A", "B", "B", "B")
f <- function(x) sum(x^2)
tapply(vector, grouping, f)
```

Output:

```
A B
15 5 29
```

`by`

- The Cool Column Companion 🕶️📊

When you have a dataframe and you want to apply a function to each column based on a grouping, look no further than `by`

! It takes your grouping and applies the function to every column. Plus, it adds some extra style by pretty-printing the grouping and the value of the function for each column.

Check it out with this example:

```
dataframe <- data.frame(A = 1:3, B = 4:6, grouping = c("A", "A", "B"))
f <- function(x) sum(x^2)
by(dataframe, dataframe$grouping, f)
```

Output:

```
dataframe$grouping: A
A B
5 77
------------------------------------------------------------
dataframe$grouping: B
A B
137 77
```

`aggregate`

- Grouping Champion 🏆📊

Last but not least, if you want to aggregate your results in a tidy dataframe, `aggregate`

is here to save the day! It's similar to `by`

, but instead of pretty-printing the output, it collects everything into a dataframe.

Here's an example:

```
matrix <- matrix(1:6, ncol = 2)
grouping <- rep(c("A", "B"), each = 3)
f <- function(x) sum(x^2)
aggregate(matrix, by = list(grouping), FUN = f)
```

Output:

```
Group.1 A
1 A 14
2 B 86
```

## Simplify Your Life with `plyr`

and `reshape`

🚀🔄

Now, you might be wondering if `plyr`

and `reshape`

can replace all of these functions entirely. While `plyr`

offers more flexibility and power for data manipulation, and `reshape`

excels at transforming data between wide and long formats, they don't explicitly replace the entire `apply`

family. However, they can make your data wrangling journey even more enjoyable! So, give them a try and see how they elevate your code! 😎

## Conclusion 💡🎉

Now that you've mastered the art of grouping functions in R, you're ready to take your data manipulation skills to the next level! 🚀 Whether you need to operate on vectors, matrices, or even entire dataframes, there's an `apply`

family function for every occasion. So, go forth and write code that dazzles! 👩💻🌟

Do you have any other burning questions or need further clarifications? Share your thoughts and join the discussion in the comments below! Let's level up our coding skills together! 💬💪