diff --git a/README.md b/README.md
index e1ae627..7d734a7 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,5 @@
 # ironwood plots
+
+Ironwood tree healh data analysis using R.
+
+![ironwood tree health map](health_map_plot.png)
diff --git a/health_map_plot.png b/health_map_plot.png
new file mode 100644
index 0000000..8965026
Binary files /dev/null and b/health_map_plot.png differ
diff --git a/ironwood_plots.R b/ironwood_plots.R
index 4c6210c..c0133c4 100644
--- a/ironwood_plots.R
+++ b/ironwood_plots.R
@@ -6,6 +6,7 @@ library(readODS)
 library(tidyverse)
 library(dplyr)
 library(leaflet)
+library(RColorBrewer)
 
 ##
 # parse the input data, declare global values and auxiliary data
@@ -68,6 +69,7 @@ health_counts <- df %>%
 # Pivot the data frame to wide format for ggplot
 health_counts_wide <- pivot_wider(health_counts, names_from = tree_health_index, values_from = count, values_fill = list(count = 0))
 
+# plot each bar
 ggplot(health_counts_wide, aes(x = site_num)) +
   geom_bar(aes(fill = `0`), position = "stack", width = 0.5) +
   geom_bar(aes(fill = `1`), position = "stack", width = 0.5) +
@@ -78,12 +80,10 @@ ggplot(health_counts_wide, aes(x = site_num)) +
   scale_fill_manual(values = c("#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e")) +  # Custom colors for each health index
   theme_minimal()
 
-
+# rename
 colnames(health_data) <- paste("Site", seq(1,20), sep=" ")
 rownames(health_data) <- condition_names
-
 # create color palette:
-library(RColorBrewer)
 coul <- brewer.pal(3, "Pastel2") 
 # Transform this data in %
 data_percentage <- apply(data, 2, function(x){x*100/sum(x,na.rm=T)})