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! 🚀