rbind () on a conditional basis - r

Question

Here's the question. I have a bunch of if statements that create different data frames (A-F) based on the user inputs. In some instances, some of the data frames will be empty, so maybe (A-C) are empty, but (D-F) have information.
I'm trying to create a conditional rbind(), where it combines the rows only if the data frame is not empty.
I'm not quite sure how to go about this? I don't know if I should create a bunch of conditions and use another if statement:
cond_a <- nrow(a) != 0
cond_b <- nrow(b) != 0
cond_c <- nrow(c) != 0
cond_d <- nrow(d) != 0
cond_e <- nrow(e) != 0
cond_f <- nrow(f) != 0
but then I don't know how to utilize these conditions...
EDIT: To take a step back and better explain: I have one data frame that I split into 6 different data frames by subsetting by a column, so it splits it into 6 data frames (A-G). The column has the letters A-G. These letters A-G in that column change depending on user inputs.
I then have a series of if statements that asks "if A is not empty then perform this aggregation", thereby skipping the df if it has no data in it. The aggregation takes it from 16 to 19 columns. Because the empty df has not been aggregated it still has 19 columns. After I perform these if statements and aggregations, I am left with dfA, dfB, dfC, etc. that have either been aggregated (16 columns) or still empty (19 columns). I then want a piece of code that says "for the df that have been aggregated (16 columns) rbind, if the df has not been aggregated (is empty), then don't perform the rbind.
thanks!

Answer 1

You can do something like this :
Create an empty list of the data frames you wish to select.
Write a bunch of if statements to see which ones contain non-zero zeros
Keep adding those names of non-zero DFs to the empty list created in step 1
Write an expression which collapses those names to an rbind expression
Evaluate the expression
Here is the script to do it :
1.Create an Empty list to store the names of dataframes
list.df = " "
2&3. If statements check if the Data Frame is Non-Zero, add the name to the list if true
if(nrow(df.a) > 0) {
list.df=c(list.df,deparse(substitute(df.a)))
}
if(nrow(df.b) > 0) {
list.df=c(list.df,deparse(substitute(df.b)))
}
if(nrow(df.c) > 0) {
list.df=c(list.df,deparse(substitute(df.c)))
}
.... So on from A through G
if(nrow(df.g) > 0) {
list.df=c(list.df,deparse(substitute(df.g)))
}
4.Formulate the expression
list.df = list.df[2:length(list.df)] #remove first element
expression = paste0("df.combined = rbind(",paste0( list.df, collapse =
','), paste0(")"))
5.Evaluate the expression
eval(parse(text=expression))
df.combined will be your final dataset that you are looking for