Data Manipulation in R: Detele Row and Fill-in Column in Multiple Data Frames at Once

Introduction

When working with multiple data frames in R, it’s not uncommon to need to perform common operations such as deleting the last row of each data frame or filling a specific column with values from another column. In this article, we’ll explore how to achieve these tasks for multiple data frames simultaneously.

We’ll focus on two main challenges:

1. Deleting the last row of each data frame
2. Filling a specific column with values from another column

Deleting the Last Row of Each Data Frame

The first challenge involves deleting the last row of each data frame. In the provided Stack Overflow question, there are attempts to achieve this using the nrow() function. However, there’s an important difference between nrow() and dim()[[2]].

nrow() returns a single value indicating the number of rows in the entire list of data frames.

On the other hand, dim()[[2]] returns a vector containing the column indices for each data frame. It might seem like an intuitive solution to use nrow(temp2[i], ), but it’s actually incorrect.

To delete the last row of each data frame, we can’t rely on nrow() or dim()[[2]]. Instead, we’ll iterate over each data frame in the list and manually remove the last row using slicing (head(dflist[[i]], -1)).

Here is an example code block demonstrating this approach:

dflist <- list(df1 = df1, df2 = df2, df3 = df3)

# Remove the last row of each data frame
for (i in 1:NROW(dflist)) {
    dflist[[i]]$Tissue <- temp2[i]
    dflist[[i]] <- head(dflist[[i]], -1)
}

mydf <- do.call(rbind, dflist)

# Print the result
print(mydf)

In this example, dflist is a list containing our data frames. We iterate over each element in the list and use head() to remove the last row of each data frame. Finally, we bind all the updated data frames together using do.call(rbind).

Filling a Specific Column with Values from Another Column

The second challenge involves filling a specific column (df$Tissue) with values from another column (temp2).

To achieve this, we can iterate over each data frame in the list and assign values to the corresponding column using assignment syntax:

dflist <- list(df1 = df1, df2 = df2, df3 = df3)

# Assign values from temp2 to the Tissue column
for (i in 1:NROW(dflist)) {
    dflist[[i]]$Tissue <- temp2[i]
}

mydf <- do.call(rbind, dflist)

In this example, we iterate over each data frame and assign values from temp2 to the Tissue column. Finally, we bind all the updated data frames together using do.call(rbind).

Merging Multiple Data Frames into One

Now that we’ve updated our data frames by removing the last row of each and filling a specific column with values, we can merge them all together into one big dataframe.

As mentioned earlier, we’ll use do.call(rbind, dflist2). Here is the complete example code block:

dflist <- list(df1 = df1, df2 = df2, df3 = df3)

# Create new columns and strip the last row of each data frame
dflist2 <- lapply(1:NROW(dflist),
    function(i) {
        dflist[[i]]$Tissue <- temp2[i]
        head(dflist[[i]], -1)
    })

mydf <- do.call(rbind, dflist2)

# Print the result
print(mydf)

Conclusion

In this article, we’ve explored how to delete the last row of each data frame and fill a specific column with values from another column when working with multiple data frames in R. We’ll use lists of data frames, lapply(), do.call(rbind), and basic assignment syntax to achieve these tasks.

By following this guide, you should be able to manage your data effectively and streamline your workflow.

Last modified on 2024-02-11