# lapply() on a list

The first function in the apply family that you will learn is `lapply()`

, which is short for "list apply." When you have a list, and you want to apply the same function to each element of the list, `lapply()`

is a potential solution that always returns another list. How might this work?

Let's look at a simple example. Suppose you want to find the length of each vector in the following list.

```
my_list
$a
[1] 2 4 5
$b
[1] 10 14 5 3 4 5 6
# Using lapply
# Note that you don't need parenthesis when calling length
lapply(my_list, FUN = length)
$a
[1] 3
$b
[1] 7
```

As noted in the video, if at first you thought about looping over each element in the list, and using `length()`

at each iteration, you aren't wrong. `lapply()`

is the vectorized version of this kind of loop, and is often preferred (and simpler) in the R world.

A list of daily stock returns *as percentages* called `stock_return`

and the `percent_to_decimal()`

function have been provided.

This is a part of the course

## “Intermediate R for Finance”

### Exercise instructions

- Print
`stock_return`

. - Fill in the
`lapply()`

function to apply`percent_to_decimal()`

to each element in`stock_return`

.

### Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

```
# Print stock_return
___
# lapply to change percents to decimal
lapply(___, FUN = ___)
```

This exercise is part of the course

## Intermediate R for Finance

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

A popular alternative to loops in R are the apply functions. These are often more readable than loops, and are incredibly useful for scaling the data science workflow to perform a complicated calculation on any number of observations. Learn about them here!

Exercise 1: Why use apply?Exercise 2: lapply() on a listExercise 3: lapply() on a data frameExercise 4: FUN argumentsExercise 5: sapply() - simplify it!Exercise 6: sapply() vs. lapply()Exercise 7: Failing to simplifyExercise 8: vapply() - specify your output!Exercise 9: vapply() vs. sapply()Exercise 10: More vapply()Exercise 11: Anonymous functionsExercise 12: Congratulations### What is DataCamp?

Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.