diff --git a/DESCRIPTION b/DESCRIPTION
index 328406d..8da6e0d 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: parttree
 Title: Visualise simple decision tree partitions
-Version: 0.0.1.9005
+Version: 0.0.1.9006
 Authors@R: c(
     person(given = "Grant",
            family = "McDermott",
diff --git a/NAMESPACE b/NAMESPACE
index 18e0a04..1246915 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -11,8 +11,14 @@ export(geom_parttree)
 export(parttree)
 importFrom(data.table,":=")
 importFrom(data.table,.SD)
+importFrom(data.table,as.data.table)
+importFrom(data.table,data.table)
 importFrom(data.table,fifelse)
+importFrom(data.table,rbindlist)
+importFrom(data.table,tstrsplit)
 importFrom(graphics,par)
+importFrom(rpart,path.rpart)
 importFrom(stats,reformulate)
+importFrom(stats,terms)
 importFrom(tinyplot,tinyplot)
 importFrom(utils,packageVersion)
diff --git a/NEWS.md b/NEWS.md
index 47d0414..11f147d 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,10 +1,10 @@
-# parttree 0.0.1.9005
+# parttree 0.0.1.9006
 
 To be released as 0.1.0
 
 #### Breaking changes
 
-* Move ggplot2 to Suggests, following the addition of native (base R)
+* Move ggplot2 to Enhances, following the addition of native (base R)
 `plot.parttree` method. The `geom_parttree()` function now checks whether
 ggplot2 is available on the user's system before executing any code. (#18)
 * The `flipaxes` argument has been renamed to `flip`, e.g.
@@ -23,6 +23,7 @@ by @juliasilge).
 
 * Support for negative values. (#6 by @pjgeens)
 * Better handling of single-level factors and `flip(axes)`. (#5)
+* Handling of complex formula expressions. (#17)
 
 #### Internals
 
diff --git a/R/parttree.R b/R/parttree.R
index ded35f4..3a66551 100644
--- a/R/parttree.R
+++ b/R/parttree.R
@@ -20,7 +20,9 @@
 #' @returns A data frame comprising seven columns: the leaf node, its path, a
 #'   set of rectangle limits (i.e., xmin, xmax, ymin, ymax), and a final column
 #'   corresponding to the predicted value for that leaf.
-#' @importFrom data.table := .SD fifelse
+#' @importFrom data.table := .SD as.data.table data.table fifelse rbindlist tstrsplit
+#' @importFrom rpart path.rpart
+#' @importFrom stats reformulate terms
 #' @export
 #' @examples
 #' library("parttree")
@@ -112,24 +114,25 @@ parttree.rpart =
 
     ## Get details about y variable for later
     ### y variable string (i.e. name)
-    y_var = paste(tree$terms)[2]
-    # y_var = attr(tree$terms, "variables")[[2]]
+    all_terms = terms(tree)
+    y_var = all.vars(all_terms)[attr(all_terms, "response")]
     ### y values
     yvals = tree$frame[tree$frame$var == "<leaf>", ]$yval
-    y_factored = attr(tree$terms, "dataClasses")[paste(y_var)] == "factor"
+    # y_factored = attr(tree$terms, "dataClasses")[paste(y_var)] == "factor"
+    y_factored = attr(tree$terms, "dataClasses")[y_var] == "factor"
     ## factor equivalents (if factor)
     if (y_factored) {
       ylevs = attr(tree, "ylevels")
       yvals = ylevs[yvals]
     }
 
-    part_list = rpart::path.rpart(tree, node=nodes, print.it = FALSE)
-    part_list = lapply(part_list, data.table::as.data.table)
-    part_dt = data.table::rbindlist(part_list, idcol="node")[V1!="root"]
-    part_dt[, c("variable", "split") := data.table::tstrsplit(V1, split = "+<|+<=|>|+>=")][]
+    part_list = path.rpart(tree, nodes = nodes, print.it = FALSE)
+    part_list = lapply(part_list, as.data.table)
+    part_dt = rbindlist(part_list, idcol="node")[V1!="root"]
+    part_dt[, c("variable", "split") := tstrsplit(V1, split = "+<|+<=|>|+>=")][]
     part_dt[, side := gsub("\\s$", "", gsub("\\w|\\.", "", V1))][]
 
-    yvals_dt = data.table::data.table(yvals, node = nodes)
+    yvals_dt = data.table(yvals, node = nodes)
 
     part_dt = part_dt[yvals_dt, on = "node", all = TRUE]
     part_dt[, V1 := NULL][, node := as.integer(node)][, split := as.double(split)][]
@@ -281,7 +284,7 @@ parttree.workflow =
     y_name = names(tree$pre$mold$outcomes)[[1]]
     raw_data = cbind(tree$pre$mold$predictors, tree$pre$mold$outcomes)
     tree = workflows::extract_fit_engine(tree)
-    tree$terms[[2]] = y_name
+    tree$terms[[2]] = reformulate(y_name)[[2]]
     attr(tree$terms, "variables")[[2]] = y_name
     names(attr(tree$terms, "dataClasses"))[[1]] = y_name
 
@@ -456,7 +459,7 @@ parttree.constparty =
     colnames(rval)[4L:7L] = c("xmin", "xmax", "ymin", "ymax")
 
     ## turn into data.table?
-    if(keep_as_dt) rval = data.table::as.data.table(rval)
+    if(keep_as_dt) rval = as.data.table(rval)
 
     class(rval) = c("parttree", class(rval))
     xvar = ifelse(isFALSE(flip), mx[1], mx[2])