From 735df0cfe943d35e6b4983366209a8e767e20e94 Mon Sep 17 00:00:00 2001
From: Alex <agebben@pm.me>
Date: Wed, 18 Mar 2026 15:11:58 -0600
Subject: [PATCH] Improving figures

---
 Visuals.r | 25 +++++++++++++++++++++----
 1 file changed, 21 insertions(+), 4 deletions(-)

diff --git a/Visuals.r b/Visuals.r
index 0e3cfd4..e83add4 100644
--- a/Visuals.r
+++ b/Visuals.r
@@ -1,5 +1,7 @@
 library(tidyverse)
 #install.packages("paletteer")
+
+install.packages("waffle")
 library(scales)
 library(paletteer)
 DATA_DIR <- 'Results/REMI_Output/'
@@ -50,6 +52,20 @@ OUTPUT_PLOT
 dev.off()
 ###################
 INDUSTRY_JOBS <- read_csv(paste0(DATA_DIR,'Employment- By Industry - Employment by Industry.csv'),skip=5)  %>% pivot_longer(c(-Industry,-Units),names_to="Year")  %>% mutate(Jobs=parse_number(value),Year=parse_number(Year)) %>% select(-value) %>% filter(Industry!='All Industries') %>% select(-Units) %>% filter(Year>=2029)
+INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Data processing, hosting, and related services; Other information services',"Data processing",INDUSTRY_JOBS$Industry)
+INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Professional, scientific, and technical services',"Technical services",INDUSTRY_JOBS$Industry)
+INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Administrative and support services',"Administrative services",INDUSTRY_JOBS$Industry)
+INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='State and Local Government',"Government",INDUSTRY_JOBS$Industry)
+INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Food services and drinking places',"Restaurants",INDUSTRY_JOBS$Industry)
+INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Other transportation equipment manufacturing',"Equipment manufacturing",INDUSTRY_JOBS$Industry)
+INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Repair and maintenance',"maintenance",INDUSTRY_JOBS$Industry)
+
+
+
+
+
+
+
 
 
 INDUSTRY_JOBS <-  INDUSTRY_JOBS  %>% group_by(Year)  %>% mutate(Rank=rank(-Jobs)) %>% mutate(Rank=ifelse(Rank>10,11,Rank),Industry=ifelse(Rank==11,"Other",Industry)) %>% group_by(Year,Industry,Rank) %>% summarize(Jobs=sum(Jobs)) %>% ungroup(Industry,Rank)  %>% arrange(Year,Rank)  
@@ -57,11 +73,12 @@ INDUSTRY_JOBS <-  INDUSTRY_JOBS  %>% group_by(Year)  %>% mutate(Rank=rank(-Jobs)
 ORDER <- c(INDUSTRY_JOBS %>% filter(Industry!='Other')  %>% group_by(Industry) %>% summarize(MEAN=mean(Jobs)) %>% arrange(desc(MEAN)) %>% pull(Industry) %>% unique,"Other")
 INDUSTRY_JOBS$Industry <- factor(INDUSTRY_JOBS$Industry,levels=ORDER)
 
-JOB_TYPE_PLOT <- ggplot(INDUSTRY_JOBS ,aes(x=Year,y=Jobs,fill=Industry))+geom_bar(stat='identity')+ paletteer::scale_fill_paletteer_d("colorBlindness::Blue2DarkRed18Steps")
-png(paste0(OUTPUT_DIR,"Job_Dist_Plot.png"), units = "in", width = 20, height = 8, res = 600)
-JOB_TYPE_PLOT 
+JOB_TYPE_PLOT <- 	ggplot(INDUSTRY_JOBS ,aes(x=Year,y=Jobs,fill=Industry))+geom_bar(stat='identity')+ paletteer::scale_fill_paletteer_d("colorBlindness::Blue2DarkRed18Steps")+theme_bw()+theme(text = element_text(size = 20),legend.position = "top")+guides(fill=guide_legend(nrow=2,byrow=TRUE)) +scale_x_continuous(breaks=seq(2029,2060,by=1))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=250))
+png(paste0(OUTPUT_DIR,"Job_Dist_Plot.png"), units = "in", width = 22, height = 16, res = 600)
+	JOB_TYPE_PLOT 
 dev.off()
 
 
-ggplot(INDUSTRY_JOBS %>% filter(Year %in% c(2032,2045)),aes(x=as.factor(Year),y=Jobs,fill=Industry))+geom_bar(stat='identity')+ paletteer::scale_fill_paletteer_d("colorBlindness::Blue2DarkRed18Steps")
+ggplot(INDUSTRY_JOBS %>% filter(Year %in% c(2032,2045)),aes(x=factor(Year),y=Jobs,fill=factor(Year)))+geom_bar(stat='identity',width=0.99)+facet_wrap(.~Industry)+theme_bw()
+#+ paletteer::scale_fill_paletteer_d("lisa::FridaKahlo")