Plant traits are critical to plant form and function —including growth, survival and reproduction— and therefore shape fundamental aspects of population and ecosystem dynamics as well as ecosystem services. Here, we present a global species-level compilation of key functional traits for palms (Arecaceae), a plant family with keystone importance in tropical and subtropical ecosystems.
TidyTuesday
Data Visualization
R Programming
2025
Author
Peter Gray
Published
March 19, 2025
Thumbnail
1. R code
Show code
# Load the packages in ----------------------------------------------------if(!require(tidyverse)){install.packages("tidyverse"); library(tidyverse)}if(!require(patchwork)){install.packages("patchwork"); library(patchwork)}if(!require(showtext)){install.packages("showtext"); library(showtext)}if(!require(ggdendro)){install.packages("ggdendro"); library(ggdendro)}if(!require(ggbrick)){install.packages("ggbrick"); library(ggbrick)}if(!require(ggmosaic)){install.packages("ggmosaic"); library(ggmosaic)}if(!require(treemapify)){install.packages("treemapify"); library(treemapify)}# get the wdwd<-getwd()palmtrees<-readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-03-18/palmtrees.csv')font_add_google("Noto Sans Mono", "noto_mono")font<-"noto_mono"showtext_auto()# Color palettecolor<-palette.colors(palette ="Okabe-Ito")color<-append(color, "gold")color[1]<-"#D41159"Custom_Style<-function(){ggplot2::theme( plot.title =ggplot2::element_text(family=font, size=24, face="bold", color="#222222"), plot.subtitle =ggplot2::element_text(family=font, size=18, color="#222222"), plot.caption =ggplot2::element_text(family=font, size=10, color="#222222"), legend.position ="bottom", legend.title =ggplot2::element_text(family=font, size=22, face="bold", color="#222222"),# legend.text.align = 0, legend.key =ggplot2::element_blank(), legend.text =ggplot2::element_text(family=font, size=9, color="#222222"),# Axis format axis.text =ggplot2::element_text(family =font, size=10, color="#222222"), axis.text.x =ggplot2::element_text(margin=ggplot2::margin(5, b =10), size =8), axis.line =ggplot2::element_line(colour =alpha('#222222', 0.5), size =0.5), axis.title =ggplot2::element_text(family=font, size=12, face="bold", color="#222222"),# Grid lines panel.grid.minor =ggplot2::element_blank(), panel.grid.major.y =ggplot2::element_blank(), panel.grid.major.x =ggplot2::element_blank(),# Very pale cream/yellow background panel.background =element_rect(fill ="#FFFBF0", color ="#FFFBF0", linewidth =0.5, linetype ="solid"), plot.background =element_rect(fill ="#FFFBF0", color ="#FFFBF0", linewidth =0.5, linetype ="solid"), legend.background =element_rect(fill ="#FFFBF0", color ="#FFFBF0", linewidth =0.5, linetype ="solid"),)}palm_colours<-palmtrees%>%filter(!is.na(main_fruit_colors))%>%mutate(main_fruit_colors =str_extract(main_fruit_colors, "^[^;]+"), main_fruit_colors =str_to_title(main_fruit_colors))%>%count(palm_tribe, main_fruit_colors)color_mapping<-c("Black"=alpha("black", 0.7), "Blue"="blue", "Brown"="brown", "Green"="green", "Orange"="orange", "Pink"="pink", "Purple"="purple", "Red"="red", "White"="white", "Yellow"="yellow", "Cream"="antiquewhite", "Grey"="grey", "Ivory"="ivory", "Straw-Coloured"="wheat")circular_bar<-palm_colours%>%group_by(palm_tribe)%>%mutate( percent =(n/sum(n))*100,# Capitalize colors here)%>%ggplot(aes(x =palm_tribe, y =percent, fill =main_fruit_colors))+geom_bar(stat ="identity", width =0.8)+coord_polar()+scale_fill_manual(values =color_mapping)+labs(fill ="Primary Fruit Colour")+Custom_Style()+theme( axis.text.x =element_text(size =22), axis.text.y =element_blank(), axis.title.y =element_blank(), axis.title.x =element_blank(), axis.ticks.y =element_blank(), axis.line =element_blank(), legend.text =element_text(size =22))+guides(fill =guide_legend(ncol =3))p1<-circular_bar+theme(legend.position ="bottom")&plot_annotation( title =str_wrap("Percentage of Palm Tree Fruit Colors by Tribe", 60), subtitle ="TidyTuesday: Week 11, 2025", theme =Custom_Style())&theme( caption =element_text(hjust =0.5), plot.subtitle =element_text(size =32), plot.title =element_text(size =48))
