tweak: Order by cummulative area amount.

blog/2022/11/20/brief-update-ea-funding/.source/analysis.R

@@ -4,7 +4,7 @@
 
 ### Install
 # install.packages("ggplot2")
-#install.packages("readr")
+# install.packages("readr")
 
 ### Load
 library("ggplot2")
@@ -14,7 +14,6 @@ library("magrittr")
 library("RColorBrewer")
 library("ggsci")
 
-
 ## Data import
 setwd("/home/loki/Documents/core/ea/fresh/misc/openphil-funding")
 data <- read.csv("grants.csv", header=TRUE, stringsAsFactors = FALSE)
@@ -32,13 +31,12 @@ df$year <- as.vector(sapply(data$Date, getYear))
 df$amount <- as.vector(sapply(data$Amount, parse_number))
 df$amount <- ifelse(is.na(df$amount), 0, df$amount)
 df$area <- as.vector(data$Focus.Area)
-
 df <- as.data.frame(df)
-## View(df)
+df$area <- as.vector(data$Focus.Area) # not sure why this line is needed, but things break otherwise
-df$area <- as.vector(data$Focus.Area)
+# View(df)
 
+## Classify according to areas
 areas <- unique(df$area)
-
 ea_growth <-  c("Effective Altruism Community Growth", "Effective Altruism Community Growth (Global Health and Wellbeing)")
 global_health <- c("South Asian Air Quality", "Human Health and Wellbeing", "GiveWell-Recommended Charities", "Global Aid Policy", "Global Health & Wellbeing", "Global Health & Development","Science for Global Health")
 longtermism <- c("Biosecurity & Pandemic Preparedness", "Potential Risks from Advanced AI", "Science Supporting Biosecurity and Pandemic Preparedness", "Longtermism")
@@ -56,7 +54,6 @@ df$area <- ifelse(df$area %in% scientific_research, "Scientific Research", df$ar
 df$area <- ifelse(df$area %in% politicy_advocacy, "Policy Advocacy", df$area)
 df$area <- ifelse(df$area %in% other, "Other", df$area)
 df$area
-# df <- df[order(df$area),]
 
 ## Aggregate by year and area
 years <- c(2014: 2022)# as.vector(unique(df$year))
@@ -69,31 +66,40 @@ df2$area <- sort(rep(area_names, num_years))
 df2$year <- rep(years, num_areas)
 df2 <- as.data.frame(df2)
 
-# View(df2)
+getAmountForYearAreaPair <- function(a_df, target_year, target_area){
-
-getAmountForYearAreaPair <- function(target_year, target_area){
   filter = dplyr::filter
   # target_year = 2022
   # target_area = "Longtermism"
-  rows = df %>% filter(year == target_year) %>% filter(area == target_area)
+  rows = a_df %>% filter(year == target_year) %>% filter(area == target_area)
   return(sum(rows$amount))
 }
-getAmountForYearAreaPair(2022, "Longtermism")
+getAmountForYearAreaPair(df, 2022, "Longtermism & GCRs")
+
+getAmountForArea <- function(a_df, target_area){
+  filter = dplyr::filter
+  rows = a_df %>% filter(area == target_area)
+  return(sum(rows$amount))
+}
+getAmountForArea(df, "Longtermism & GCRs")
 
 amounts <- c()
 for(i in c(1:dim(df2)[1])){
-  amount <- getAmountForYearAreaPair(df2$year[i], df2$area[i])
+  amount <- getAmountForYearAreaPair(df2, df2$year[i], df2$area[i])
   amounts <- c(amounts, amount)
 }
 df2$amount <- amounts
-# View(df2)
+
+## Order by cummulative amount
+df2$cummulative_amount_for_its_area = sapply(df2$area, function(area) {
+  return(getAmountForArea(df, area)) 
+})
 
 ## Plotting
 title_text="Open Philanthropy allocation by year and cause area"
 subtitle_text="with my own aggregation of categories"
 palette = "Classic Red-Blue"
 direction = -1
-open_philanthropy_plot <- ggplot(data=df2, aes(x=year, y=amount, fill=area))+
+open_philanthropy_plot <- ggplot(data=df2, aes(x=year, y=amount, fill=area, group = cummulative_amount_for_its_area))+
   geom_bar(stat="identity")+
   labs(
     title=title_text,
@@ -123,6 +129,7 @@ open_philanthropy_plot <- ggplot(data=df2, aes(x=year, y=amount, fill=area))+
     legend.text=element_text(size=7, hjust = 0.5)
   ) + 
   guides(fill=guide_legend(nrow=3,byrow=TRUE))
+open_philanthropy_plot
 getwd() ## Working directory on which the file will be saved. Can be changed with setwd("/your/directory")
 height = 5
 width = 5
@@ -134,7 +141,7 @@ wealth <- c(6, 8, 12, 15, 18, 12, 14, 19, 14)
 df2$wealth <- rep(wealth * coeff, num_areas)
 
 make_fortune_plot <- function(show_fortune_legend = FALSE) {
-  open_philanthropy_plot_with_fortune <- ggplot(data=df2, aes(x=year, y=amount, fill=area))+
+  open_philanthropy_plot_with_fortune <- ggplot(data=df2, aes(x=year, y=amount, fill=area, group = cummulative_amount_for_its_area))+
     geom_bar(stat="identity")+
     geom_point(
       aes(x=year, y=wealth), size=2, color="darkblue", shape=4,
@@ -209,7 +216,6 @@ df3 <- as.data.frame(df3)
 df3$area <- as.vector(data$Focus.Area)
 df3 <- df3 %>% dplyr::filter(area %in% longtermism)
 # View(df3)
-df3
 
 years <- c(2014: 2022) # as.vector(unique(df$year))
 num_years <- length(years)
@@ -229,13 +235,15 @@ for(i in c(1:dim(df4)[1])){
   amounts <- c(amounts, amount)
 }
 df4$amount <- amounts
-
+df4$cummulative_amount_for_its_area = sapply(df4$area, function(area) {
+  return(getAmountForArea(df3, area)) 
+})
 ## Plotting longtermist funding
 title_text="Open Philanthropy allocation by year and cause area"
 subtitle_text="restricted to longtermism & GCRs"
 palette = "Classic Red-Blue"
 direction = -1
-open_philanthropy_plot_lt <- ggplot(data=df4, aes(x=year, y=amount, fill=area, group=amount))+
+open_philanthropy_plot_lt <- ggplot(data=df4, aes(x=year, y=amount, fill=area, group=cummulative_amount_for_its_area))+
   geom_bar(stat="identity")+
   labs(
     title=title_text,
@@ -268,5 +276,5 @@ open_philanthropy_plot_lt <- ggplot(data=df4, aes(x=year, y=amount, fill=area, g
 getwd() ## Working directory on which the file will be saved. Can be changed with setwd("/your/directory")
 height = 5
 width = 6
-open_philanthropy_plot_lt
+## open_philanthropy_plot_lt
 ggsave(plot=open_philanthropy_plot_lt, "open_philanthropy_grants_lt.png", width=width, height=height, bg = "white")