modified gov script

Scripts/gov_plots.R

@@ -2,18 +2,20 @@ library(dplyr)
 library(ggplot2)
 library(gridExtra)
 library(grid)
+library(scales)
 
 
-refn <- 219
-N <- 14165
+refn <- 240
+N <- 9700
+scale <- 1e-3
 
 mydata <- data.frame()
 
-for (i in 1:15){
+for (i in 1:6){
 
-  id <- seq(0, 14)
+  id <- seq(0, 5)
 
-  mydata <- rbind(mydata, read.csv(paste0("/Users/filippo/Downloads/referenda2_vote-219 (",id[i],").csv")))
+  mydata <- rbind(mydata, read.csv(paste0("/Users/filippo/Downloads/referenda2_vote-240 (",id[i],").csv")))
 
 }
 
@@ -35,8 +37,7 @@ mydata$delegation <- ifelse(!mydata$Delegate.To == "-", "Delegated", "Solo")
 
 sum_tab <- as.data.frame(group_by(mydata, delegation, Voted) %>% summarise(n_acc = length(Account), n_votes = sum(Value), n_eff_votes = sum(Effective.Votes), n_deleg = sum(!Delegate.To == "-")))
 
-sum_tab$n_votes <- round(sum_tab$n_votes/10^6)
-sum_tab$n_eff_votes <- round(sum_tab$n_eff_votes/10^6)
+sum_tab$n_votes <- round(sum_tab$n_votes)
 
 #table(mydata$Conviction)
 
@@ -51,25 +52,21 @@ p0 <- ggplot(sum_tab, aes(y=n_acc, x=delegation, fill = Voted)) +
 p1 <- ggplot(sum_tab, aes(y=n_eff_votes, x = delegation, fill = Voted)) +
   geom_bar(stat = "identity") +
   theme(legend.position="none") +
+  scale_y_continuous(labels = label_number(suffix = "K", scale = scale)) +
   labs(y = "Votes (Conviction)", x = "") +
   scale_fill_manual(values=c("#89CFF0","#50C878","red")) +
-  scale_y_continuous(breaks = c(1000000, 10000000, max(sum_tab$n_eff_votes)),
-                     labels = c("1M","10M",paste0(round(max(sum_tab$n_eff_votes)),"M"))) +
   geom_text(aes(label=replace(n_eff_votes, n_eff_votes == 0, "")), size=3.5, position = position_stack(vjust = 0.5))
 
 p2 <- ggplot(mydata, aes(x=Value, fill=Voted)) +
   geom_histogram(position="dodge") +
   theme(legend.position="none") +
-  scale_x_continuous(trans='log10', breaks = c(0.1, 100, 1000, 10000, 100000, 1000000, max(mydata$Value)),
-                     labels = c("0.1","100","1K","10K","100K","1M",paste0(round(max(mydata$Value)/10^6),"M"))) +
+  scale_x_continuous(trans='none', labels = label_number(suffix = "K", scale = scale)) +
   labs(y = "Count", x = "Votes") +
   scale_fill_manual(values=c("#89CFF0","#50C878","red"))
 
 p3 <- ggplot(mydata, aes(x=Effective.Votes, fill=Voted)) +
   geom_histogram(position="dodge") +
-  scale_x_continuous(trans='log10',
-                     breaks = c(0.1, 100, 1000, 10000, 100000, 1000000, max(mydata$Effective.Votes)),
-                     labels = c("0.1","100","1K","10K","100K","1M", paste0(round(max(mydata$Effective.Votes)/10^6),"M"))) +
+  scale_x_continuous(trans='log10', labels = label_number(suffix = "K", scale = scale)) +
   theme(legend.position="none") +
   labs(y = "Count", x = "Votes (Conviction)") +
   scale_fill_manual(values=c("#89CFF0","#50C878","red"))