r - Iterated plotting from list of list of dataframes -

i'm trying explore large dataset, both data frames , charts. i'd analyze distribution of each variable different metrics (e.g., sum(x), sum(x*y)) , different sub-populations. have 4 sub-populations, 2 metrics, , many variables.

in order accomplish that, i've made list structure such this:

$variable1 ...$metric1     <--- that's df. ...$metric2 $variable2 ...$metric1 ...$metric2 

inside 1 of data_frames (e.g., list$variable1$metric1), i've calculated distributions of unique values variable1 , each of 4 population groups (represented in columns). looks this:

$variable1$metric1 unique_values med_all med_some_not_all med_at_least_some med_none 1 (1) 12-17 years old      na               na                na       na 2 (2) 18-25 years old   0.278            0.317             0.278    0.317 3 (3) 26-34 years old   0.225            0.228             0.225    0.228 4     (4) 35 or older   0.497            0.456             0.497    0.456   $variable1$metric2         unique_values med_all med_some_not_all med_at_least_some med_none 1 (1) 12-17 years old      na               na                na       na 2 (2) 18-25 years old   0.544            0.406             0.544    0.406 3 (3) 26-34 years old   0.197            0.310             0.197    0.310 4     (4) 35 or older   0.259            0.284             0.259    0.284 

what i'm trying figure out way loop through list of lists (probably melting dfs in process) , output ton of bar charts. in case, natural plot format be, each dataframe, stacked bar chart 1 stacked bar each sub-population, grouping variable's unique values.

but i'm not familiar iterated plotting , i've hit dead end. how might plot list structure? alternately, there better structure in should storing information?

here's start:

lst <- list(alpha= list(a= data.frame(matrix(1:4, 2)), b= data.frame(matrix(6:11, 2))),                            beta = list(c = data.frame(matrix(11:14, 2))))  lst $alpha $alpha$a   x1 x2 1  1  3 2  2  4  $alpha$b   x1 x2 x3 1  6  8 10 2  7  9 11   $beta $beta$c   x1 x2 1 11 13 2 12 14  #we can subset number or name lst[['alpha']] $a   x1 x2 1  1  3 2  2  4  $b   x1 x2 x3 1  6  8 10 2  7  9 11  lst[[1]] $a   x1 x2 1  1  3 2  2  4  $b   x1 x2 x3 1  6  8 10 2  7  9 11  #the dollar sign naming convention reminds looking @ list. #let's sum columns of both data frames in alpha list lapply(lst[['alpha']], colsums) $a x1 x2   3  7   $b x1 x2 x3  13 17 21  

let's try find sum of each column of each data frame:

lapply(lst, colsums) error in fun(x[[i]], ...) :    'x' must array of @ least 2 dimensions 

what happened? r correctly refusing run array function on list. function colsums needs fed data frames, matrices, , other arrays above one-dimension. have nest lapply function inside of one. logic can complicated:

lapply(lst, function(x) lapply(x, colsums)) $alpha $alpha$a x1 x2   3  7   $alpha$b x1 x2 x3  13 17 21    $beta $beta$c x1 x2  23 27  

we can use rbind put data.frames together:

rbind(lst$alpha$a, lst$beta$c)   x1 x2 1  1  3 2  2  4 3 11 13 4 12 14 

be sure not way might thinking (i've done many times):

do.call(rbind, lst)            b      alpha list,2 list,3 beta  list,2 list,2 

that isn't result you're looking for. , make sure dimensions , column names same:

do.call(rbind, lst[[1]]) error in rbind(deparse.level, ...) :    numbers of columns of arguments not match 

r refusing combine data frames have 2 columns in 1 (alpha$a) , 3 columns in other (alpha$b).

i changed lst make alpha$b have 2 columns others , combined them:

bind1 <- lapply(lst2, function(x) do.call(rbind, x)) bind1 $alpha     x1 x2 a.1  1  3 a.2  2  4 b.1  6  9 b.2  7 10 b.3  8 11  $beta     x1 x2 c.1 11 13 c.2 12 14 

that combines elements of each list. can combine outer list make 1 big data frame.

do.call(rbind, bind1)           x1 x2 alpha.a.1  1  3 alpha.a.2  2  4 alpha.b.1  6  9 alpha.b.2  7 10 alpha.b.3  8 11 beta.c.1  11 13 beta.c.2  12 14