# Extracting the Last N’th Row in R Data Frames

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# Introduction

Ever wrangled with a data frame and needed just the final row? Fear not, R warriors! Today’s quest unveils three mighty tools to conquer this task: base R, the dplyr package, and the data.table package.

# Examples

## Method 1: Using Base R

# Create a sample data frame my_df <- data.frame( Name = c("Alice", "Bob", "Charlie"), Age = c(25, 30, 22) ) # Extract the last row using nrow() and indexing last_row_base <- my_df[nrow(my_df), ] print(last_row_base)

Name Age 3 Charlie 22

Explanation: - We use `nrow(my_df)`

to get the total number of rows in the data frame. - Then, we use indexing (`[nrow(my_df), ]`

) to extract the last row.

## Method 2: Using dplyr

library(dplyr) # Extract the last row using tail() last_row_dplyr <- my_df %>% tail(1) print(last_row_dplyr)

Name Age 3 Charlie 22

Explanation: - The `tail()`

function from `dplyr`

returns the last `n`

rows of a data frame (default is 6). - We use `tail(my_df, 1)`

to get only the last row.

## Method 3: Using data.table

library(data.table) # Convert data frame to data.table my_dt <- as.data.table(my_df) # Extract the last row using .N last_row_dt <- my_dt[.N] print(last_row_dt)

Name Age <char> <num> 1: Charlie 22

Explanation: - We convert the data frame to a data.table using `as.data.table(my_df)`

. - The `.N`

special variable in data.table represents the total number of rows. - We use `my_dt[.N]`

to get the last row.

# Bonus Tip: Getting the second to last row!

If you want to get the second to last row, then this is quite easy to do, and in fact is easy to do for any last `n`

rows. Here’s how you can get the second to last row using each method:

Certainly! Let’s explore how to extract the second-to-last row from a data frame using different methods in R. Here’s how you can do it:

## Method 1: Using Base R

# Create a sample data frame my_df <- data.frame( Name = c("Alice", "Bob", "Charlie", "David", "Eva"), Age = c(25, 30, 22, 28, 24) ) # Extract the second-to-last row using nrow() and indexing second_to_last_base <- my_df[nrow(my_df) - 1, ] print(second_to_last_base)

Name Age 4 David 28

Explanation: - We use `nrow(my_df)`

to get the total number of rows in the data frame. - To extract the second-to-last row, we subtract 1 from the total number of rows.

## Method 2: Using dplyr

# Extract the second-to-last row using slice() second_to_last_dplyr <- my_df %>% slice(n() - 1) print(second_to_last_dplyr)

Name Age 1 David 28

Explanation: - The `slice()`

function from `dplyr`

allows us to select specific rows. - We use `slice(my_df, n() - 1)`

to get the second-to-last row.

## Method 3: Using data.table

# Convert data frame to data.table my_dt <- as.data.table(my_df) # Extract the second-to-last row using .N second_to_last_dt <- my_dt[.N - 1] print(second_to_last_dt)

Name Age <char> <num> 1: David 28

Explanation: - Similar to the previous method, we convert the data frame to a data.table. - The `.N`

special variable in data.table represents the total number of rows. - We use `my_dt[.N - 1]`

to get the second-to-last row.

# Conclusion

Now you know three different ways to extract the last row or last `nth`

row from a data frame in R. Feel free to experiment with your own data frames and explore these methods further! 🚀

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