diff --git a/NAMESPACE b/NAMESPACE
index 9f6ac92..4a3844b 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,8 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 export("%>%")
-export(map_data)
 export(individuals_by)
-export(initiative_by)
+export(map_data)
 export(replace_other)
 importFrom(magrittr,"%>%")
diff --git a/R/map_data.R b/R/map_data.R
index 657a992..020cb9a 100644
--- a/R/map_data.R
+++ b/R/map_data.R
@@ -14,16 +14,20 @@
 #' @examples
 #' # An example with simple data 
 #' df_original <- data.frame(initiative = c("A", "B", "C", "D"),
-#'                           country = c("BF", "BF Niger", "Niger", "Niger"))
+#'                           country = c("BF", "BF Niger", "Niger", "Niger"),
+#'                           ex = c("a b", "a b", "a", "b"))
 #' map_data(df_original, "initiative", "country")
+#' map_data(df_original, "initiative", "country", "ex")
+#' map_data(df_original, "initiative", c("country", "ex"), "ex")
 #' 
 #' 
 #' df_original2 <- data.frame(individuals = c("A", "B", "C", "D"),
 #'                            institutions = c("a b", "a", "a", "b c"),
 #'                            initiatives = c("z", "z", "y z", "y"))
 #' map_data(df_original2, "individuals", c("institutions", "initiatives"))
+#' map_data(df_original2, "individuals", c("institutions", "initiatives"), "institutions")
 #' 
-map_data <- function(data, values, node_values) {
+map_data <- function(data, values, node_values, colour_values = NULL) {
   # repeat for each in node_values because of different sizes in cols
   # separate_longer_delim doesn't repeat for each col, but groups
   for (i in node_values){
@@ -31,33 +35,47 @@ map_data <- function(data, values, node_values) {
       separate_longer_delim(cols = {{ i }}, " ")
   }
   
-  # Step 1: Expand data for the node data
+  # Step 1: Expand data for df_output_1
   df_expanded <- data %>%
-    tidyr::pivot_longer(cols = c({{ values }}, {{ node_values }}),
-                        names_to = "group",
-                        values_to = "id") %>%
-    dplyr::select(c(id, group)) %>%
-    dplyr::arrange(group) %>%
-    dplyr::distinct() %>%
-    dplyr::mutate(id_index = row_number() - 1)
+    pivot_longer(cols = c({{ values }}, {{ node_values }}),
+                 names_to = "group",
+                 values_to = "id") %>%
+    dplyr::select(c("id", "group")) %>%
+    arrange(group)
   
-  # Step 2: Create the linked data
+  if (is.null(colour_values)){ 
+    df_expanded <- df_expanded %>%
+      dplyr::distinct() %>%
+      dplyr::mutate(id_index = row_number() - 1) %>%
+      rename(group_type = group) 
+  } else {
+    data_1 <- data %>%
+      dplyr::select(c(id = {{ values }}, group_type = {{ colour_values }}))
+    df_expanded <- df_expanded %>%
+      left_join(data_1, by = "id") %>%
+      #rename(group_type = {{ colour_values }}) %>%
+      dplyr::distinct() %>%
+      dplyr::mutate(id_index = row_number() - 1) %>%
+      dplyr::mutate(group_type = ifelse(is.na(group_type), group, group_type))
+  }
+  
+  # Step 2: Create df_output_2
   df_mapped <- data %>%
     dplyr::left_join(df_expanded, by = setNames("id", values)) %>%
-    dplyr::rename(source = id_index) 
+    rename(source = id_index) 
   
   df_mapped <- df_mapped %>%
-    tidyr::pivot_longer(cols = all_of({{ node_values }}), values_to = "id") %>%
-    dplyr::distinct() %>%
+    pivot_longer(cols = all_of({{ node_values }}), values_to = "id") %>%
+    distinct %>%
     dplyr::left_join(df_expanded, by = "id") %>%
-    dplyr::rename(target = id_index) 
+    rename(target = id_index)
   
   df_mapped <- df_mapped %>%
     dplyr::select(c(target, source))
   
-  networkD3::forceNetwork(Links = df_mapped, Nodes = df_expanded,
-                          Source = "source", Target = "target",
-                          NodeID = "id",
-                          Group = "group",
-                          legend = TRUE)
+  return(forceNetwork(Links = df_mapped, Nodes = df_expanded,
+                      Source = "source", Target = "target",
+                      NodeID = "id",
+                      Group = "group_type",
+                      legend = TRUE))
 }
diff --git a/man/initiative_by.Rd b/man/initiative_by.Rd
index 5e034aa..a4755c6 100644
--- a/man/initiative_by.Rd
+++ b/man/initiative_by.Rd
@@ -43,6 +43,37 @@ initiative_by(
 
 \item{group}{character string specifying the group of each node in the \code{initiative_data} data frame.}
 
+\item{font_size}{numeric font size in pixels for the node text labels.}
+
+\item{height}{numeric height for the network graph's frame area in pixels.}
+
+\item{width}{numeric width for the network graph's frame area in pixels.}
+
+\item{colour_scale}{character string specifying the categorical colour scale for the nodes. See https://github.com/d3/d3/blob/master/API.md#ordinal-scales.}
+
+\item{font_family}{font family for the node text labels.}
+
+\item{link_distance}{numeric or character string. Either numberic fixed distance between the links in pixels (actually arbitrary relative to the diagram's size). Or a JavaScript function, possibly to weight by Value. For example: linkDistance = JS("function(d){return d.value * 10}").}
+
+\item{link_width}{numeric or character string. Can be a numeric fixed width in pixels (arbitrary relative to the diagram's size). Or a JavaScript function, possibly to weight by Value. The default is linkWidth = JS("function(d) { return Math.sqrt(d.value); }").}
+
+\item{radius_calculation}{character string. A javascript mathematical expression, to weight the radius by Nodesize. The default value is radiusCalculation = JS("Math.sqrt(d.nodesize)+6").}
+
+\item{charge}{numeric value indicating either the strength of the node repulsion (negative value) or attraction (positive value).}
+
+\item{link_colour}{character vector specifying the colour(s) you want the link lines to be. Multiple formats supported (e.g. hexadecimal).}
+
+\item{opacity}{numeric value of the proportion opaque you would like the graph elements to be.}
+
+\item{zoom}{logical value to enable (TRUE) or disable (FALSE) zooming.}
+
+\item{arrows}{logical value to enable directional link arrows.}
+
+\item{bounded}{logical value to enable (TRUE) or disable (FALSE) the bounding box limiting the graph's extent. See http://bl.ocks.org/mbostock/1129492.}
+
+\item{display_labels}{}
+
+\item{click_action}{character string with a JavaScript expression to evaluate when a node is clicked.}
 }
 \value{
 Returns a network graph object
diff --git a/man/map_data.Rd b/man/map_data.Rd
index a6ea62f..102fdb0 100644
--- a/man/map_data.Rd
+++ b/man/map_data.Rd
@@ -4,7 +4,7 @@
 \alias{map_data}
 \title{Map Data for Network Visualisation}
 \usage{
-map_data(data, values, node_values)
+map_data(data, values, node_values, colour_values = NULL)
 }
 \arguments{
 \item{data}{The original data frame.}
@@ -24,13 +24,17 @@ and creates links between them.
 \examples{
 # An example with simple data 
 df_original <- data.frame(initiative = c("A", "B", "C", "D"),
-                          country = c("BF", "BF Niger", "Niger", "Niger"))
+                          country = c("BF", "BF Niger", "Niger", "Niger"),
+                          ex = c("a b", "a b", "a", "b"))
 map_data(df_original, "initiative", "country")
+map_data(df_original, "initiative", "country", "ex")
+map_data(df_original, "initiative", c("country", "ex"), "ex")
 
 
 df_original2 <- data.frame(individuals = c("A", "B", "C", "D"),
                            institutions = c("a b", "a", "a", "b c"),
                            initiatives = c("z", "z", "y z", "y"))
 map_data(df_original2, "individuals", c("institutions", "initiatives"))
+map_data(df_original2, "individuals", c("institutions", "initiatives"), "institutions")
 
 }