Add a column in a list of data frames - r

Question

I want to add a column to each of my data frames in my list table after I do this code :
#list of my dataframes
df <- list(df1,df2,df3,df4)
#compute stats
stats <- function(d) do.call(rbind, lapply(split(d, d[,2]), function(x) data.frame(Nb= length(x$Year), Mean=mean(x$A), SD=sd(x$A) )))
#Apply to list of dataframes
table <- lapply(df, stats)
This column which I call Source for example, include the names of my dataframes along with Nb, Mean and SD variables. So the variable Source should contain df1,df1,df1... for my table[1], and so on.
Is there anyway I can add it in my code above?

Answer 1

Here's a different way of doing things:
First, let's start with some reproducible data:
set.seed(1)
n = 10
dat <- list(data.frame(a=rnorm(n), b=sample(1:3,n,TRUE)),
data.frame(a=rnorm(n), b=sample(1:3,n,TRUE)),
data.frame(a=rnorm(n), b=sample(1:3,n,TRUE)),
data.frame(a=rnorm(n), b=sample(1:3,n,TRUE)))
Then, you want a function that adds columns to a data.frame. The obvious candidate is within. The particular things you want to calculate are constant values for each observation within a particular category. To do that, use ave for each of the columns you want to add. Here's your new function:
stat <- function(d){
within(d, {
Nb = ave(a, b, FUN=length)
Mean = ave(a, b, FUN=mean)
SD = ave(a, b, FUN=sd)
})
}
Then just lapply it to your list of data.frames:
lapply(dat, stat)
As you can see, columns are added as appropriate:
> str(lapply(dat, stat))
List of 4
$ :'data.frame': 10 obs. of 5 variables:
..$ a : num [1:10] -0.626 0.184 -0.836 1.595 0.33 ...
..$ b : int [1:10] 3 1 2 1 1 2 1 2 3 2
..$ SD : num [1:10] 0.85 0.643 0.738 0.643 0.643 ...
..$ Mean: num [1:10] -0.0253 0.649 -0.3058 0.649 0.649 ...
..$ Nb : num [1:10] 2 4 4 4 4 4 4 4 2 4
$ :'data.frame': 10 obs. of 5 variables:
..$ a : num [1:10] -0.0449 -0.0162 0.9438 0.8212 0.5939 ...
..$ b : int [1:10] 2 3 2 1 1 1 1 2 2 2
..$ SD : num [1:10] 1.141 NA 1.141 0.136 0.136 ...
..$ Mean: num [1:10] -0.0792 -0.0162 -0.0792 0.7791 0.7791 ...
..$ Nb : num [1:10] 5 1 5 4 4 4 4 5 5 5
$ :'data.frame': 10 obs. of 5 variables:
..$ a : num [1:10] 1.3587 -0.1028 0.3877 -0.0538 -1.3771 ...
..$ b : int [1:10] 2 3 2 1 3 1 3 1 1 1
..$ SD : num [1:10] 0.687 0.668 0.687 0.635 0.668 ...
..$ Mean: num [1:10] 0.873 -0.625 0.873 0.267 -0.625 ...
..$ Nb : num [1:10] 2 3 2 5 3 5 3 5 5 5
$ :'data.frame': 10 obs. of 5 variables:
..$ a : num [1:10] -0.707 0.365 0.769 -0.112 0.881 ...
..$ b : int [1:10] 3 3 2 2 1 1 3 1 2 2
..$ SD : num [1:10] 0.593 0.593 1.111 1.111 0.297 ...
..$ Mean: num [1:10] -0.318 -0.318 0.24 0.24 0.54 ...
..$ Nb : num [1:10] 3 3 4 4 3 3 3 3 4 4