Saving Every Dataframe in a List of Dataframes

Introduction

In this blog post, we’ll explore how to save every dataframe in a list using the write.table function in R. We’ll start by creating a list of dataframes and then discuss various approaches to saving each dataframe individually.

Creating a List of Dataframes

set.seed(1)
S1 = data.frame(replicate(2,sample(0:130,30,rep=TRUE)))
S2 = data.frame(replicate(2,sample(0:130,34,rep=TRUE)))
S3 = data.frame(replicate(2,sample(0:130,21,rep=TRUE)))
S4 = data.frame(replicate(2,sample(0:130,26,rep=TRUE)))
df_list1 = list(S1 = S1, S2 = S2, S3 = S3, S4 = S4)

set.seed(2)
S1 = data.frame(replicate(2,sample(0:130,30,rep=TRUE)))
S2 = data.frame(replicate(2,sample(0:130,34,rep=TRUE)))
S3 = data.frame(replicate(2,sample(0:130,21,rep=TRUE)))
S4 = data.frame(replicate(2,sample(0:130,26,rep=TRUE)))
df_list2 = list(S1 = S1, S2 = S2, S3 = S3, S4 = S4)

set.seed(3)
S1 = data.frame(replicate(2,sample(0:130,30,rep=TRUE)))
S2 = data.frame(replicate(2,sample(0:130,34,rep=TRUE)))
S3 = data.frame(replicate(2,sample(0:130,21,rep=TRUE)))
S4 = data.frame(replicate(2,sample(0:130,26,rep=TRUE)))
df_list3 = list(S1 = S1, S2 = S2, S3 = S3, S4 = S4)

set.seed(4)
S1 = data.frame(replicate(2,sample(0:130,30,rep=TRUE)))
S2 = data.frame(replicate(2,sample(0:130,34,rep=TRUE)))
S3 = data.frame(replicate(2,sample(0:130,21,rep=TRUE)))
S4 = data.frame(replicate(2,sample(0:130,26,rep=TRUE)))
df_list4 = list(S1 = S1, S2 = S2, S3 = S3, S4 = S4)

df_list = list(df_list1, df_list2, df_list3, df_list4)
names(df_list) = c("AB_df", "BC_df", "DE_df", "FG_df")

In this example, we create four dataframes S1, S2, S3, and S4 using the replicate function. We then create a list of these dataframes and assign names to each element in the list.

Flattening the List

flatlist <- unlist(df_list, recursive = FALSE)
for (n in names(flatlist)) write.csv(flatlist[[n]], sprintf("%s.csv", n))

The answer provided uses the unlist function to flatten the list of lists into a single list. This allows us to easily access each dataframe individually using its name.

However, let’s dive deeper into how we can achieve this without using unlist.

Looping Through the List and Saving Each Dataframe

for (i in 1:length(df_list)) {
  df_name <- paste("df_list", names(df_list)[i], sep = "$")
  write.table(df_list[[i]], df_name, row.names = FALSE)
}

This approach uses a for loop to iterate through each element in the list. For each iteration, it creates a character string df_name by concatenating “df_list” with the current name from the list.

However, we have a problem here: names(df_list)[i] returns a character, but df_list[[i]] returns a dataframe. In R, when you use square brackets [], it doesn’t interpret the variable as a string; instead, it interprets it as an index into the vector.

This is where we run into the issue that prevents us from using names(df_list)[i]. To solve this problem, we need to use double quotes in our string concatenation.

for (i in 1:length(df_list)) {
  df_name <- paste0("df_list", names(df_list)[i], ".csv")
  write.table(df_list[[i]], df_name, row.names = FALSE)
}

Note that we also changed sep = "$" to paste0 for better readability.

Another Approach: Using for Loop with Brackets

names_of_df <- names(df_list)
for (n in names_of_df) {
  write.table(df_list[[n]], paste(n, ".csv", sep = ""), row.names = FALSE)
}

In this example, we first extract the names from the list into a vector called names_of_df. We then use these names directly when writing to file.

Conclusion

Saving every dataframe in a list can be achieved using several approaches. By understanding how R handles variables and string concatenation, you can create your own efficient solutions to this common problem.

Last modified on 2024-02-17