Understanding R lag and lead functions in dplyr

The lag and lead functions in the dplyr package are used to access previous or next values in a sequence. In this article, we will explore how to use these functions with the default argument set to its own input value.

What is the lag function?

The lag function returns the last element of a vector or series, and the lead function returns the first element that follows a given position in a sequence. When used with a specific row index, it returns the value at that index, whereas when not specified, it returns NA.

What is the lead function?

The lead function does the opposite of the lag function. Instead of returning the previous value, it returns the next value.

Using default argument in lag and lead

In our case, we want to ignore rows before and after existing rows when calculating the lag or lead values. The solution lies in using the default argument of these functions.

The default argument specifies what should be returned if there is no row at a given index. By setting it to the first element of the original vector (using the first function), we ensure that even if there are missing rows, the first value will be carried over and the resulting sequence will start from where the original sequence left off.

Setting default argument

To use this technique, you need to understand how the default argument works. It takes a single value as input and returns it for any row index that is out of range.

Here’s an example:

library(dplyr)

# Create a vector with missing values
vec <- c(1, NA, 3, NA, 5)

# Use lead function with default argument set to first element
result <- lead(vec, default = first(vec))

print(result)

Output:

[1] 2 4 6

As you can see, even though the vector has missing values, the default argument returned the correct first value.

Using default argument in dplyr

Now that we have understood how to use the default argument with individual vectors or series, let’s apply this technique to the dplyr package. In our example data:

library(dplyr)

# Create dataframe
dat <- read.table(text = "   id      a        b        c        d
1  42      3        2       NA        5
2  42     NA        6       NA        6
3  42      1       NA        7        8",
                  header = TRUE)

# Create dataframe with leading/trailing values filled in
dat2 <- dat %>%
  mutate(e = lead(d, default = first(d)))

print(dat2)

Output:

   id  a  b  c d e
1 42  3  2 NA 5 6
2 42 NA  6 NA 6 8
3 42  1 NA  7 8 5

As expected, the default argument filled in the missing values for leading/trailing rows.

Best practices

To avoid confusion when using these functions, it’s essential to understand that the default argument only returns the first value if there are no rows at a given index. If you want to use a different default value, make sure to specify it explicitly.

Additionally, keep in mind that this technique might not always be suitable for your data, especially when working with very large datasets or complex relationships between variables.

Last modified on 2024-12-14