combine multiple expressions in R into one big expression -

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i new r expression handling. stuck below problem. input appreciated.

i trying generate 2 individual equations , combine them 1 expression , pass algorithm find optimal value. 

   old_price    elast      units      1  59.98        1.3        151       2  59.98        1.3        230

code:

for(i in 1:nrow(df)){     o[i] = df$old_price[i]     el[i] = df$elast[i]     u[i] = df$units[i]     assign(paste0("l",i),(substitute((x)*(1-(x-o)*el/o)*u,     list(o=o[i],el=el[i],u=u[i])))) }

i able generate below 2 equations

l1 = (x) * (1 - (x - 59.98) * 1.3/59.98) * 151 l2 = (x) * (1 - (x - 59.98) * 1.3/59.98) * 230

and objective function this

eval_obj_f <- function(x){eval(l1)+eval(l2)}

i trying figure out how dynamically. if have different dataset of 4 observations, how can generate objective function below dynamically? 

eval(l1)+eval(l2)+eval(l3)+eval(l4)

you need using real r expression's , @ moment not expressions rather call's. (check is.expression or class). don't name "df" dataframes since function name well, used "prdat":

 o <- el <- u <- numeric(2)  # if don't exist, loop errors out  for(i in 1:nrow(prdat)){      o[i] = prdat$old_price[i]      el[i] = prdat$elast[i]      u[i] = prdat$units[i]      assign(paste0("l",i), as.expression(substitute(x*(1-(x-o)*el/o)*u,                                                     list(o=o[i],el=el[i],u=u[i]))))                         }  l1 #expression(x * (1 - (x - 59.98) * 1.3/59.98) * 151) # how expressions appear when printed. l2 #expression(x * (1 - (x - 59.98) * 1.3/59.98) * 230) exprlist <- list(l1,l2)  eval_obj_f <- function(x){sum( sapply( exprlist, eval, envir=list(x=x) ) )} eval_obj_f(2) #[1] 1719.569

this seems pretty clunky. have apply-ed function on dataframe , summed results. suppose might interesting attempt "compute on language"-approach, take alook @ code below think more in keeping "r-way". seems more compact ... , expressive:

func <- function(x) {apply(prdat, 1, function(z) x*(1-                                 (x-z["old_price"])*z["elast"]/z["old_price"])*z["units"] )} > sum( func(x=2)) [1] 1719.569

this might better using code (but still lot more clunky second method imo):

exprvec <- expression() o <- el <- u <- numeric(2)    for(i in 1:nrow(prdat)){      o[i] = prdat$old_price[i]      el[i] = prdat$elast[i]      u[i] = prdat$units[i]      exprvec[[i]] <- substitute(x*(1-(x-o)*el/o)*u,                                  list(o=o[i],el=el[i],u=u[i]))                         }  #substitute-value gets coerced mode-expression # test > eval_obj_f <- function(x){sum( sapply( exprvec, eval, envir=list(x=x) ) )} > eval_obj_f(2) [1] 1719.569

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