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Copy pathUNFPA YPEI Regional Comparison Graphics.R
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UNFPA YPEI Regional Comparison Graphics.R
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# Creating UNFPA Young People Empowerment Index Graphics
# November 2021
# Code written by Kristin Bietsch, PhD; Avenir Health; kbietsch@avenirhealth.org
# The packages required for this code:
library(ggplot2)
library(tidyr)
library(tidyverse)
library(viridis)
library(sf)
library(rnaturalearth)
library(rnaturalearthdata)
library(dplyr)
library("ggradar")
library(showtext)
## add the Arial font
font.add("Arial", regular = "arial.ttf",
bold = "arialbd.ttf", italic = "ariali.ttf", bolditalic = "arialbi.ttf")
devtools::install_github("ricardo-bion/ggradar")
options(scipen = 999)
# Set the working directory where input files are stored and where you want results to be saved
setwd("C:/Users/KristinBietsch/files/UNFPA/Code for GitHub/Input Data")
regional <- read.csv("YEI Regional Results Weighted 120721.csv")
############################################################################
# Global Graphic
global <- regional %>% filter(Region=="Global") %>%
select(Region, Index, Economics, Education, Gender, Politics, Safety, SRH) %>%
gather(Variable, Value, Index:SRH) %>%
mutate(Variable_full = case_when(Variable== "Economics" ~ "My Life: Economic Empowerment", # renaming
Variable=="Education" ~ "My Life: Educational Empowerment",
Variable=="Gender" ~ "My Life: Gender and Autonomy",
Variable== "Index" ~ "Index",
Variable== "Politics" ~ "My World: Youth Policy and Political Participation",
Variable== "Safety" ~ "My World: Safety and Security",
Variable== "SRH" ~ "My Body: SRH Empowerment" )) %>%
mutate(Variable_full = fct_relevel(Variable_full, # Organizing display level
"Index", "My Body: SRH Empowerment", "My Life: Gender and Autonomy",
"My Life: Educational Empowerment", "My Life: Economic Empowerment",
"My World: Youth Policy and Political Participation", "My World: Safety and Security"))
ggplot(global, aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(
axis.ticks.x = element_blank(),
legend.position = "none")
ggsave("Global YPEI Scores 120721.jpg", dpi=300, width=17, height=6, units = "in")
ggsave("Global YPEI Scores 120721.eps", dpi=300, width=17, height=6, units = "in")
###########################################################################
# Index scores by SDG region
levels(as.factor(regional$Region))
sdg <- regional %>% filter(Region == "Global" |
Region == "SDG: Australia/New Zealand" |
Region == "SDG: Central and Southern Asia" |
Region == "SDG: Eastern and South-Eastern Asia" |
Region == "SDG: Europe and Northern America" |
Region == "SDG: Latin America and the Caribbean" |
Region == "SDG: Northern Africa and Western Asia" |
Region == "SDG: Oceania (excluding Australia and New Zealand)" |
Region == "SDG: Sub-Saharan Africa") %>%
mutate(sdg=case_when(Region == "Global" ~ "Global" ,
Region == "SDG: Australia/New Zealand" ~ "Australia/New Zealand",
Region == "SDG: Central and Southern Asia" ~ "Central and Southern Asia",
Region == "SDG: Eastern and South-Eastern Asia" ~ "Eastern and South-Eastern Asia",
Region == "SDG: Europe and Northern America" ~ "Europe and Northern America",
Region == "SDG: Latin America and the Caribbean" ~ "Latin America and\nthe Caribbean",
Region == "SDG: Northern Africa and Western Asia" ~ "Northern Africa and Western Asia",
Region == "SDG: Oceania (excluding Australia and New Zealand)" ~ "Oceania (excluding\nAustralia and New Zealand)",
Region == "SDG: Sub-Saharan Africa" ~ "Sub-Saharan Africa")) %>%
select(sdg, Index) %>%
mutate(sdg = fct_relevel(sdg, # Organizing display level
"Global" ,
"Australia/New Zealand",
"Central and Southern Asia",
"Eastern and South-Eastern Asia",
"Europe and Northern America",
"Latin America and\nthe Caribbean",
"Northern Africa and Western Asia",
"Oceania (excluding\nAustralia and New Zealand)",
"Sub-Saharan Africa" ))
ggplot(subset(sdg, sdg!= "Oceania (excluding\nAustralia and New Zealand)" & sdg!= "Australia/New Zealand"), aes(x=sdg, y=Index, fill=sdg)) +
geom_bar(stat="identity") +
scale_fill_manual( values=
c( "Global" = "#3BA351", "Sub-Saharan Africa" = "#E4519C", "Central and Southern Asia" = "#FFBF3B",
"Eastern and South-Eastern Asia" = "#E15E27", "Europe and Northern America"= "#EA9200",
"Latin America and\nthe Caribbean" ="#389AD6" , "Northern Africa and Western Asia"= "#80C3DA")) +
labs(fill="", x="", y="", title="Global and SDG Regions Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.ticks.x = element_blank(),
legend.position = "none")
ggsave("Global and SDG YPEI Scores 120921.jpg", dpi=300, width=17, height=6, units = "in")
ggsave("Global and SDG YPEI Scores 120921.eps", dpi=300, width=17, height=6, units = "in")
sdg_full <- regional %>% filter(Region == "Global" |
Region == "SDG: Australia/New Zealand" |
Region == "SDG: Central and Southern Asia" |
Region == "SDG: Eastern and South-Eastern Asia" |
Region == "SDG: Europe and Northern America" |
Region == "SDG: Latin America and the Caribbean" |
Region == "SDG: Northern Africa and Western Asia" |
Region == "SDG: Oceania (excluding Australia and New Zealand)" |
Region == "SDG: Sub-Saharan Africa") %>%
mutate(sdg=case_when(Region == "Global" ~ "Global" ,
Region == "SDG: Australia/New Zealand" ~ "Australia/New Zealand",
Region == "SDG: Central and Southern Asia" ~ "Central and Southern Asia",
Region == "SDG: Eastern and South-Eastern Asia" ~ "Eastern and South-Eastern Asia",
Region == "SDG: Europe and Northern America" ~ "Europe and Northern America",
Region == "SDG: Latin America and the Caribbean" ~ "Latin America and\nthe Caribbean",
Region == "SDG: Northern Africa and Western Asia" ~ "Northern Africa and Western Asia",
Region == "SDG: Oceania (excluding Australia and New Zealand)" ~ "Oceania (excluding\nAustralia and New Zealand)",
Region == "SDG: Sub-Saharan Africa" ~ "Sub-Saharan Africa")) %>%
select(sdg, Index, Economics, Education, Gender, Politics, Safety, SRH) %>%
gather(Variable, Value, Index:SRH) %>%
mutate(sdg = fct_relevel(sdg, # Organizing display level
"Global" ,
"Australia/New Zealand",
"Central and Southern Asia",
"Eastern and South-Eastern Asia",
"Europe and Northern America",
"Latin America and\nthe Caribbean",
"Northern Africa and Western Asia",
"Oceania (excluding\nAustralia and New Zealand)",
"Sub-Saharan Africa" )) %>%
mutate(Variable_full = case_when(Variable== "Economics" ~ "My Life: Economic Empowerment", # renaming
Variable=="Education" ~ "My Life: Educational Empowerment",
Variable=="Gender" ~ "My Life: Gender and Autonomy",
Variable== "Index" ~ "Index",
Variable== "Politics" ~ "My World: Youth Policy and Political Participation",
Variable== "Safety" ~ "My World: Safety and Security",
Variable== "SRH" ~ "My Body: SRH Empowerment" ))
ggplot( subset(sdg_full, sdg!= "Oceania (excluding\nAustralia and New Zealand)" ), aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ sdg, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top")
# If you would like to export these results, uncomment the line below
ggsave("Global SDG Domain YPEI Scores 120921.jpg", dpi=300, width=17, height=6, units = "in")
ggsave("Global SDG Domain YPEI Scores 120921.eps", dpi=300, width=17, height=6, units = "in")
sdg_subdomain <- regional %>% filter(Region == "Global" |
Region == "SDG: Australia/New Zealand" |
Region == "SDG: Central and Southern Asia" |
Region == "SDG: Eastern and South-Eastern Asia" |
Region == "SDG: Europe and Northern America" |
Region == "SDG: Latin America and the Caribbean" |
Region == "SDG: Northern Africa and Western Asia" |
Region == "SDG: Oceania (excluding Australia and New Zealand)" |
Region == "SDG: Sub-Saharan Africa") %>%
mutate(sdg=case_when(Region == "Global" ~ "Global" ,
Region == "SDG: Australia/New Zealand" ~ "Australia/New Zealand",
Region == "SDG: Central and Southern Asia" ~ "Central and Southern Asia",
Region == "SDG: Eastern and South-Eastern Asia" ~ "Eastern and South-Eastern Asia",
Region == "SDG: Europe and Northern America" ~ "Europe and Northern America",
Region == "SDG: Latin America and the Caribbean" ~ "Latin America and\nthe Caribbean",
Region == "SDG: Northern Africa and Western Asia" ~ "Northern Africa and Western Asia",
Region == "SDG: Oceania (excluding Australia and New Zealand)" ~ "Oceania (excluding\nAustralia and New Zealand)",
Region == "SDG: Sub-Saharan Africa" ~ "Sub-Saharan Africa")) %>%
select(Region, Economics_Resource,
Economics_Agency,
Economics_Achievement,
Education_Resource,
Education_Agency,
Education_Achievement,
Gender_Resource,
Gender_Agency,
Gender_Achievement,
Politics_Resource,
Politics_Agency,
Politics_Achievement,
Safety_Resource,
Safety_Agency,
Safety_Achievement,
SRH_Resource,
SRH_Agency,
SRH_Achievement ) %>%
gather(Variable, Value, Economics_Resource:SRH_Achievement) %>%
separate(Variable, c("Domain","Subdomain"), sep = "_") %>%
mutate(Subdomain = fct_relevel(Subdomain, # Organizing display level
"Resource", "Agency", "Achievement"))
###########################################################################
# For these graphics we only want the global and UNFPA groupings, feel free to adjust
unfpa <- regional %>% filter(Region=="Global" |
Region=="UNFPA Total" |
Region=="UNFPA: Arab States" |
Region=="UNFPA: Asia & the Pacific" |
Region=="UNFPA: East & Southern Africa" |
Region=="UNFPA: Eastern Europe & Central Asia" |
Region=="UNFPA: Latin America & the Caribbean" |
Region=="UNFPA: West & Central Africa" ) %>%
mutate(Region=case_when(Region=="Global" ~ "Global", # renaming
Region=="UNFPA Total" ~ "UNFPA Total",
Region=="UNFPA: Arab States" ~ "Arab States",
Region=="UNFPA: Asia & the Pacific" ~ "Asia & the Pacific",
Region=="UNFPA: East & Southern Africa" ~ "East & Southern Africa",
Region=="UNFPA: Eastern Europe & Central Asia" ~ "Eastern Europe & Central Asia",
Region=="UNFPA: Latin America & the Caribbean" ~ "Latin America & the Caribbean",
Region=="UNFPA: West & Central Africa" ~ "West & Central Africa" )) %>%
select(Region, Index, Economics, Education, Gender, Politics, Safety, SRH) %>%
gather(Variable, Value, Index:SRH) %>%
mutate(Region = fct_relevel(Region, # Organizing display level
"Global", "UNFPA Total", "Arab States",
"Asia & the Pacific", "East & Southern Africa", "Eastern Europe & Central Asia",
"Latin America & the Caribbean", "West & Central Africa")) %>%
mutate(Variable_full = case_when(Variable== "Economics" ~ "My Life: Economic Empowerment", # renaming
Variable=="Education" ~ "My Life: Educational Empowerment",
Variable=="Gender" ~ "My Life: Gender and Autonomy",
Variable== "Index" ~ "Index",
Variable== "Politics" ~ "My World: Youth Policy and Political Participation",
Variable== "Safety" ~ "My World: Safety and Security",
Variable== "SRH" ~ "My Body: SRH Empowerment" )) %>%
mutate(Variable_full = fct_relevel(Variable_full, # Organizing display level
"Index", "My Body: SRH Empowerment", "My Life: Gender and Autonomy",
"My Life: Educational Empowerment", "My Life: Economic Empowerment",
"My World: Youth Policy and Political Participation", "My World: Safety and Security"))
ggplot(unfpa, aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top")
# If you would like to export these results, uncomment the line below
ggsave("Global Averages YPEI Scores 120721.jpg", dpi=300, width=17, height=6, units = "in")
ggsave("Global Averages YPEI Scores 120721.eps", dpi=300, width=17, height=6, units = "in")
# Graphics comparing an individual region to the global results
ggplot(subset(unfpa, Region== "Global" | Region=="Arab States"), aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("Arab States Averages YPEI Scores 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("Arab States Averages YPEI Scores 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa, Region== "Global" | Region=="Asia & the Pacific"), aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("Asia Averages YPEI Scores 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("Asia Averages YPEI Scores 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa, Region== "Global" | Region=="East & Southern Africa"), aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("East South Africa Averages Scores 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("East South Africa Averages Scores 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa, Region== "Global" | Region=="Eastern Europe & Central Asia"), aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("EEurope CAsia Averages YPEI Scores 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("EEurope CAsia Averages YPEI Scores 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa, Region== "Global" | Region=="Latin America & the Caribbean"), aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("LAC Averages YPEI Scores 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("LAC Averages YPEI Scores 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa, Region== "Global" | Region=="West & Central Africa"), aes(x=Variable_full, y=Value, fill=Variable_full)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Index" = "#3BA351", "My Body: SRH Empowerment" = "#E4519C", "My Life: Gender and Autonomy" = "#FFBF3B",
"My Life: Educational Empowerment" = "#E15E27", "My Life: Economic Empowerment"= "#EA9200",
"My World: Youth Policy and Political Participation" ="#389AD6" , "My World: Safety and Security" = "#80C3DA")) +
labs(fill="", x="", y="", title="Global Average Young People Empowerment Index Scores") +
theme_bw() +
guides(fill = guide_legend(nrow = 2)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("W C Africa Averages YPEI Scores 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("W C Africa Averages YPEI Scores 120721.eps", dpi=300, width=10, height=6, units = "in")
############################################################################
# Subdomains by UNFPA regions
names(regional)
unfpa_subdomain <- regional %>% filter(Region=="Global" |
Region=="UNFPA Total" |
Region=="UNFPA: Arab States" |
Region=="UNFPA: Asia & the Pacific" |
Region=="UNFPA: East & Southern Africa" |
Region=="UNFPA: Eastern Europe & Central Asia" |
Region=="UNFPA: Latin America & the Caribbean" |
Region=="UNFPA: West & Central Africa" ) %>%
mutate(Region=case_when(Region=="Global" ~ "Global", # renaming
Region=="UNFPA Total" ~ "UNFPA Total",
Region=="UNFPA: Arab States" ~ "Arab States",
Region=="UNFPA: Asia & the Pacific" ~ "Asia &\nthe Pacific",
Region=="UNFPA: East & Southern Africa" ~ "East &\nSouthern\nAfrica",
Region=="UNFPA: Eastern Europe & Central Asia" ~ "Eastern\nEurope &\nCentral Asia",
Region=="UNFPA: Latin America & the Caribbean" ~ "Latin\nAmerica &\nthe\nCaribbean",
Region=="UNFPA: West & Central Africa" ~ "West &\nCentral Africa" )) %>%
select(Region, Economics_Resource,
Economics_Agency,
Economics_Achievement,
Education_Resource,
Education_Agency,
Education_Achievement,
Gender_Resource,
Gender_Agency,
Gender_Achievement,
Politics_Resource,
Politics_Agency,
Politics_Achievement,
Safety_Resource,
Safety_Agency,
Safety_Achievement,
SRH_Resource,
SRH_Agency,
SRH_Achievement ) %>%
gather(Variable, Value, Economics_Resource:SRH_Achievement) %>%
separate(Variable, c("Domain","Subdomain"), sep = "_") %>%
mutate(Subdomain = fct_relevel(Subdomain, # Organizing display level
"Resource", "Agency", "Achievement")) %>%
mutate(Region = fct_relevel(Region, # Organizing display level
"Global", "UNFPA Total", "Arab States",
"Asia &\nthe Pacific", "East &\nSouthern\nAfrica", "Eastern\nEurope &\nCentral Asia",
"Latin\nAmerica &\nthe\nCaribbean", "West &\nCentral Africa"))
ggplot(subset(unfpa_subdomain, Domain== "Economics" ), aes(x=Subdomain, y=Value, fill=Subdomain)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Resource" = "#3BA351", "Agency" = "#E4519C", "Achievement" = "#FFBF3B")) +
labs(fill="", x="", y="", title="My Life: Economic Empowerment Subdomains") +
theme_bw() +
guides(fill = guide_legend(nrow = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
legend.text = element_text(size=13),
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("UNFPA Economics Subdomain 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("UNFPA Economics Subdomain 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa_subdomain, Domain== "Education" ), aes(x=Subdomain, y=Value, fill=Subdomain)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Resource" = "#3BA351", "Agency" = "#E4519C", "Achievement" = "#FFBF3B")) +
labs(fill="", x="", y="", title="My Life: Educational Empowerment") +
theme_bw() +
guides(fill = guide_legend(nrow = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
legend.text = element_text(size=13),
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("UNFPA Education Subdomain 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("UNFPA Education Subdomain 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa_subdomain, Domain== "Gender" ), aes(x=Subdomain, y=Value, fill=Subdomain)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Resource" = "#3BA351", "Agency" = "#E4519C", "Achievement" = "#FFBF3B")) +
labs(fill="", x="", y="", title="My Life: Gender and Autonomy") +
theme_bw() +
guides(fill = guide_legend(nrow = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
legend.text = element_text(size=13),
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("UNFPA Gender Subdomain 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("UNFPA Gender Subdomain 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa_subdomain, Domain== "Politics" ), aes(x=Subdomain, y=Value, fill=Subdomain)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Resource" = "#3BA351", "Agency" = "#E4519C", "Achievement" = "#FFBF3B")) +
labs(fill="", x="", y="", title="My World: Youth Policy and Political Participation") +
theme_bw() +
guides(fill = guide_legend(nrow = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
legend.text = element_text(size=13),
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("UNFPA Politics Subdomain 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("UNFPA Politics Subdomain 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa_subdomain, Domain== "Safety" ), aes(x=Subdomain, y=Value, fill=Subdomain)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Resource" = "#3BA351", "Agency" = "#E4519C", "Achievement" = "#FFBF3B")) +
labs(fill="", x="", y="", title="My World: Safety and Security") +
theme_bw() +
guides(fill = guide_legend(nrow = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
legend.text = element_text(size=13),
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("UNFPA Safety Subdomain 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("UNFPA Safety Subdomain 120721.eps", dpi=300, width=10, height=6, units = "in")
ggplot(subset(unfpa_subdomain, Domain== "SRH" ), aes(x=Subdomain, y=Value, fill=Subdomain)) +
geom_bar(stat="identity") +
facet_wrap( ~ Region, nrow=1, strip.position="bottom") +
scale_fill_manual( values=
c( "Resource" = "#3BA351", "Agency" = "#E4519C", "Achievement" = "#FFBF3B")) +
labs(fill="", x="", y="", title="My Body: SRH Empowerment") +
theme_bw() +
guides(fill = guide_legend(nrow = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank(),
legend.position = "top",
legend.text = element_text(size=13),
axis.text = element_text(size=13),
strip.text = element_text(size=13))
# If you would like to export these results, uncomment the line below
ggsave("UNFPA SRH Subdomain 120721.jpg", dpi=300, width=10, height=6, units = "in")
ggsave("UNFPA SRH Subdomain 120721.eps", dpi=300, width=10, height=6, units = "in")
############################################################################
# Creating Spider Charts which compare a region with global results
spider <- regional %>% filter(Region=="Global" |
Region=="UNFPA Total" |
Region=="UNFPA: Arab States" |
Region=="UNFPA: Asia & the Pacific" |
Region=="UNFPA: East & Southern Africa" |
Region=="UNFPA: Eastern Europe & Central Asia" |
Region=="UNFPA: Latin America & the Caribbean" |
Region=="UNFPA: West & Central Africa" |
Region=="UNFPA: Non-UNFPA Country" ) %>%
mutate(Region=case_when(Region=="Global" ~ "Global",
Region=="UNFPA Total" ~ "UNFPA Total",
Region=="UNFPA: Arab States" ~ "Arab States",
Region=="UNFPA: Asia & the Pacific" ~ "Asia & the Pacific",
Region=="UNFPA: East & Southern Africa" ~ "East & Southern Africa",
Region=="UNFPA: Eastern Europe & Central Asia" ~ "Eastern Europe & Central Asia",
Region=="UNFPA: Latin America & the Caribbean" ~ "Latin America & the Caribbean",
Region=="UNFPA: West & Central Africa" ~ "West & Central Africa",
Region=="UNFPA: Non-UNFPA Country" ~ "Non-UNFPA Country" )) %>%
select(Region, Economics, Education, Gender, Politics, Safety, SRH) %>%
rename("My Life:\nEconomic Empowerment"= Economics,
"My Life:\nEducational\nEmpowerment"= Education,
"My Life:\nGender and\nAutonomy"= Gender,
"My World:\nYouth Policy and\nPolitical Participation"= Politics,
"My World:\nSafety and\nSecurity" = Safety,
"My Body:\nSRH Empowerment" = SRH)
# https://www.datanovia.com/en/blog/beautiful-radar-chart-in-r-using-fmsb-and-ggplot-packages/
ggradar(
spider[c(1, 3), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
# If you would like to export these results, uncomment the line below
ggsave("Arab Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="Arab Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
spider[c(1, 3), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
dev.off()
ggradar(
spider[c(1, 4), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
# If you would like to export these results, uncomment the line below
ggsave("Asia Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="Asia Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
spider[c(1, 4), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
dev.off()
ggradar(
spider[c(1, 5), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
# If you would like to export these results, uncomment the line below
ggsave("E S Africa Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="E S Africa Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
spider[c(1, 5), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
dev.off()
ggradar(
spider[c(1, 6), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
# If you would like to export these results, uncomment the line below
ggsave("E Europe C Asia Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="E Europe C Asia Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
spider[c(1, 6), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#3BA351", "#FFBF3B"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
dev.off()
ggradar(
spider[c(1, 7), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#FFBF3B", "#3BA351" ),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
# If you would like to export these results, uncomment the line below
ggsave("LAC Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="LAC Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
spider[c(1, 7), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#FFBF3B", "#3BA351" ),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
dev.off()
ggradar(
spider[c(1, 9), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#FFBF3B", "#3BA351" ),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
# If you would like to export these results, uncomment the line below
ggsave("W C Africa Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="W C Africa Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
spider[c(1, 9), ],
values.radar = c("0", ".5", "1"),
group.colours = c( "#FFBF3B", "#3BA351" ),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey"
)
dev.off()
###############################################
# Spider Charts to compare subdomains and domains within a region
spider2 <- regional %>% filter(Region=="Global" |
Region=="UNFPA Total" |
Region=="UNFPA: Arab States" |
Region=="UNFPA: Asia & the Pacific" |
Region=="UNFPA: East & Southern Africa" |
Region=="UNFPA: Eastern Europe & Central Asia" |
Region=="UNFPA: Latin America & the Caribbean" |
Region=="UNFPA: West & Central Africa" |
Region=="UNFPA: Non-UNFPA Country" ) %>%
mutate(Region=case_when(Region=="Global" ~ "Global",
Region=="UNFPA Total" ~ "UNFPA Total",
Region=="UNFPA: Arab States" ~ "Arab States",
Region=="UNFPA: Asia & the Pacific" ~ "Asia & the Pacific",
Region=="UNFPA: East & Southern Africa" ~ "East & Southern Africa",
Region=="UNFPA: Eastern Europe & Central Asia" ~ "Eastern Europe & Central Asia",
Region=="UNFPA: Latin America & the Caribbean" ~ "Latin America & the Caribbean",
Region=="UNFPA: West & Central Africa" ~ "West & Central Africa",
Region=="UNFPA: Non-UNFPA Country" ~ "Non-UNFPA Country" )) %>%
select(Region, Economics_Achievement, Economics_Agency, Economics_Resource,
Education_Achievement, Education_Agency, Education_Resource,
Gender_Achievement, Gender_Agency, Gender_Resource,
Politics_Achievement, Politics_Agency, Politics_Resource,
Safety_Achievement, Safety_Agency, Safety_Resource,
SRH_Achievement, SRH_Agency, SRH_Resource ) %>%
gather(Subdomain, Score, Economics_Achievement:SRH_Resource) %>%
separate(Subdomain, c("Domain", "Subdomain"), sep="_") %>%
spread(Domain, Score) %>%
rename("My Life:\nEconomic Empowerment"= Economics,
"My Life:\nEducational\nEmpowerment"= Education,
"My Life:\nGender and\nAutonomy"= Gender,
"My World:\nYouth Policy and\nPolitical Participation"= Politics,
"My World:\nSafety and\nSecurity" = Safety,
"My Body:\nSRH Empowerment" = SRH) %>%
mutate(Subdomain = fct_relevel(Subdomain, "Resource" , "Agency",
"Achievement"))
# Creating smaller datasets for each chart
global_spider <- spider2 %>% filter(Region=="Global") %>% select(-Region)
arab_spider <- spider2 %>% filter(Region=="Arab States" ) %>% select(-Region)
asia_spider <- spider2 %>% filter(Region== "Asia & the Pacific" ) %>% select(-Region)
esafrica_spider <- spider2 %>% filter(Region=="East & Southern Africa" ) %>% select(-Region)
eeuropecasia_spider <- spider2 %>% filter(Region== "Eastern Europe & Central Asia") %>% select(-Region)
lac_spider <- spider2 %>% filter(Region=="Latin America & the Caribbean") %>% select(-Region)
unfpa_spider <- spider2 %>% filter(Region=="UNFPA Total") %>% select(-Region)
wcafrica_spider <- spider2 %>% filter(Region== "West & Central Africa" ) %>% select(-Region)
ggradar(
global_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Global"
)
# If you would like to export these results, uncomment the line below
ggsave("Global Domain Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="Global Domain Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
global_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Global"
)
dev.off()
ggradar(
arab_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Arab States"
)
# If you would like to export these results, uncomment the line below
ggsave("Arab States Domain Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="Arab States Domain Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
arab_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Arab States"
)
dev.off()
ggradar(
asia_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Asia & the Pacific"
)
# If you would like to export these results, uncomment the line below
ggsave("Asia Domain Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="Asia Domain Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
asia_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Asia & the Pacific"
)
dev.off()
ggradar(
esafrica_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="East & Southern Africa"
)
# If you would like to export these results, uncomment the line below
ggsave("East South Africa Domain Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="East South Africa Domain Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
esafrica_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="East & Southern Africa"
)
dev.off()
ggradar(
eeuropecasia_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Eastern Europe & Central Asia"
)
# If you would like to export these results, uncomment the line below
ggsave("East Europe Cent Asia Domain Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="East Europe Cent Asia Domain Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device
ggradar(
eeuropecasia_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Eastern Europe & Central Asia"
)
dev.off()
ggradar(
lac_spider,
values.radar = c("0", ".5", "1"),
group.colours = c( "#E4519C", "#389AD6" , "#80C3DA"),
grid.min = 0, grid.mid = .5, grid.max = 1, background.circle.colour = "white",
gridline.mid.colour = "grey",
plot.title="Latin America & the Caribbean"
)
# If you would like to export these results, uncomment the line below
ggsave("LAC Domain Spider Plot 120721.jpg", dpi=300, width=14, height=8, units = "in")
setEPS()
postscript(file="LAC Domain Spider Plot 120721.eps", onefile=FALSE, width=14, height=8)
showtext_begin() ## call this function after opening a device