added a palette argument to visdat

I’ve created a draft template for the colours to as described in issue
#26 .

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: visdat
 Title: preliminary visualisation of data
-Version: 0.0.4.9100
+Version: 0.0.4.9500
 Authors@R: person("Nicholas", "Tierney", email = "nicholas.tierney@gmail.com", role = c("aut", "cre"))
 Description: visdat makes it easy to visualise your whole dataset so that you
     can quickly identify problems visually.

NAMESPACE

@@ -1,6 +1,5 @@
 # Generated by roxygen2: do not edit by hand
 
-export(fingerprint)
 export(guess_type)
 export(vis_dat)
 export(vis_dat_ly)

NEWS.md

@@ -1,3 +1,11 @@
+# visdat 0.0.4.9500 (2016/05/31)
+=========================
+
+## NEW FEATURE (under development)
+
+- `vis_dat` gains a "palette" argument in line with [issue 26](https://github.com/njtierney/visdat/issues/26), drawn from http://colorbrewer2.org/, there are currently three arguments, "default", "qual", and "cb_safe". "default" provides the ggplot defaults, "qual" uses some colour blind **unfriendly** colours, and "cb_safe" provides some colours friendly for colour blindness.
+
+
 # visdat 0.0.4.9400 (2016/05/30)
 =========================
 

R/vis_dat.R

@@ -6,10 +6,14 @@
 #'
 #' @param sort_type logical TRUE/FALSE. When TRUE (default), it sorts by the type in the column to make it easier to see what is in the data
 #'
+#' @param palette character "default", "qual" or "cb_safe". "default" (the default) provides the stock ggplot scale for separating the colours. "qual" uses an experimental qualitative colour scheme for providing distinct colours for each Type. "cb_safe" is a set of colours that are appropriate for those with colourblindness. "qual" and "cb_safe" are drawn from http://colorbrewer2.org/.
+#'
 #' @export
 vis_dat <- function(x,
-                    sort_type = TRUE) {
+                    sort_type = TRUE,
+                    palette = "default") {
 
+  # x  = airquality
   if (sort_type == TRUE) {
 
     # arrange by the columns with the highest missingness
@@ -39,6 +43,7 @@ vis_dat <- function(x,
   d$value <- tidyr::gather_(x, "variables", "value", names(x))$value
 
   # do the plotting
+  vis_dat_plot <-
   ggplot(data = d,
          aes_string(x = "variables",
                     y = "rows",
@@ -53,4 +58,68 @@ vis_dat <- function(x,
          y = "Observations") +
     scale_x_discrete(limits = type_order_index) +
     guides(fill = guide_legend(title = "Type"))
+
+   if (palette == "qual"){
+
+     # qualitative, 6 colours
+       vis_dat_palette <- c("#e41a1c", # red
+                            "#ffff33", # yellow
+                            "#ff7f00", # Orange
+                            "#377eb8", # blue
+                            "#4daf4a", # Green
+                            "#984ea3") # Purple
+
+       vis_dat_plot +
+         scale_fill_manual(limits = c("character",
+                                      "date",
+                                      "factor",
+                                      "integer",
+                                      "logical",
+                                      "numeric"),
+                           breaks = c("character", # red
+                                      "date", # orange
+                                      "factor", # yellow
+                                      "integer", # light blue
+                                      "logical", # mid blue
+                                      "numeric"), # dark blue
+                           values = vis_dat_palette,
+                           na.value = "grey")
+       # continue reading here:
+       # http://docs.ggplot2.org/current/discrete_scale.html
+
+   } else if (palette == "cb_safe"){
+
+       # # diverging, 6 colours, colour-blind safe
+       vis_dat_palette <- c('#d73027', # red
+                            '#fc8d59', # orange
+                            '#fee090', # yellow
+                            '#e0f3f8', # light blue
+                            '#91bfdb', # mid blue
+                            '#4575b4') # dark blue
+
+     vis_dat_plot +
+       scale_fill_manual(limits = c("character",
+                                    "date",
+                                    "factor",
+                                    "integer",
+                                    "logical",
+                                    "numeric"),
+                         breaks = c("character", # red
+                                    "date", # orange
+                                    "factor", # yellow
+                                    "integer", # light blue
+                                    "logical", # mid blue
+                                    "numeric"), # dark blue
+                         values = vis_dat_palette,
+                         na.value = "grey")
+     # continue reading here:
+     # http://docs.ggplot2.org/current/discrete_scale.html
+
+   } else if (palette == "default"){
+
+     # regular palette
+     vis_dat_plot
+
+   }
+
 }