I wish to divide the third column of a dataframe by 5. These dataframes are nested and look like this:

```
[[44]]
    Ethnicity      Variant  Sum
 1:       ASW     ACCEPTOR    1
 2:       ASW          CDS   68
 3:       ASW   CGA_CNVWIN 1000
 4:       ASW     CGA_MIRB    0
 5:       ASW       DELETE    0
 6:       ASW      DISRUPT    0
 7:       ASW        DONOR    0
 8:       ASW   FRAMESHIFT    0
 9:       ASW       INSERT    1
10:       ASW       INTRON   54

```

I have used three commands each of which is successful but has off-target effects.

```
lapply(ASWldtSUM,function(x)(x/5))

```

returns 

```
[[44]]
    Ethnicity Variant   Sum
 1:        NA      NA   0.2
 2:        NA      NA  13.6
 3:        NA      NA 200.0
 4:        NA      NA   0.0
 5:        NA      NA   0.0

```

which has the unfortunate effect of dividing ALL rows by 5, leading to issues when the class is not integer as in the $Sum column.

```
lapply(ASWldtSUM,function(x[,3])(x/5))

```

has the effect of returning only a single vector, which would work nicely if this were not a nested array of dataframes, but the statement 

```
ASWdtSUM$NEWCOL<-lapply(ASWldtSUM,function(x[,3])(x/5))

```

Cannot simply be written because it is nested.

Using rapply as in the following statement:

```
rapply(ASWldtSUM,function(x) if (is.integer(x)) {(x/5)})

```

leads to a disordering of the results.

So, is there a simple way to either append a 4th column to each nested DataFrame, or to replace the third column of each DF (Sum) with that value divided by 5?