309 lines
11 KiB
R
309 lines
11 KiB
R
## Description:
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## Libraries
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### Install
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# install.packages("ggplot2")
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# install.packages("readr")
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### Load
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library("ggplot2")
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library("readr")
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library("ggthemes")
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library("magrittr")
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library("RColorBrewer")
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library("ggsci")
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## Data import
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setwd("/home/loki/Blog/nunosempere.com/blog/2022/11/20/brief-update-ea-funding/.source")
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data <- read.csv("grants.csv", header=TRUE, stringsAsFactors = FALSE)
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## Data cleaning
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colnames(data)
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getYear <- function(dateRow){
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year = strsplit(dateRow, " ")[[1]][2]
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return(year)
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}
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getYear(data$Date[1])
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as.vector(sapply(data$Date, getYear))
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df <- list()
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df$year <- as.vector(sapply(data$Date, getYear))
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df$amount <- as.vector(sapply(data$Amount, parse_number))
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df$amount <- ifelse(is.na(df$amount), 0, df$amount)
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df$area <- as.vector(data$Focus.Area)
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df <- as.data.frame(df)
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df$area <- as.vector(data$Focus.Area) # not sure why this line is needed, but things break otherwise
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# View(df)
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## Classify according to areas
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areas <- unique(df$area)
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ea_growth <- c("Effective Altruism Community Growth", "Effective Altruism Community Growth (Global Health and Wellbeing)")
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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")
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longtermism <- c("Biosecurity & Pandemic Preparedness", "Potential Risks from Advanced AI", "Science Supporting Biosecurity and Pandemic Preparedness", "Longtermism")
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animal_welfare <- c("Farm Animal Welfare", "Broiler Chicken Welfare", "Cage-Free Reforms", "Alternatives to Animal Products")
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scientific_research <- c("Transformative Basic Science", "Scientific Research", "Other Scientific Research Areas", "Scientific Innovation: Tools and Techniques")
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politicy_advocacy <- c("Land Use Reform","Macroeconomic Stabilization Policy", "Criminal Justice Reform", "Immigration Policy")
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not_other <- c(ea_growth, global_health, longtermism, animal_welfare, scientific_research, politicy_advocacy)
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other <- areas[!(areas %in% not_other)]
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df$area <- ifelse(df$area %in% ea_growth, "EA Community Building", df$area)
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df$area <- ifelse(df$area %in% global_health, "Global Health and Wellbeing", df$area)
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df$area <- ifelse(df$area %in% longtermism, "Longtermism & GCRs", df$area)
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df$area <- ifelse(df$area %in% animal_welfare, "Animal Welfare", df$area)
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df$area <- ifelse(df$area %in% scientific_research, "Scientific Research", df$area)
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df$area <- ifelse(df$area %in% politicy_advocacy, "Policy Advocacy", df$area)
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df$area <- ifelse(df$area %in% other, "Other", df$area)
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df$area
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## Aggregate by year and area
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years <- c(2014: 2022)# as.vector(unique(df$year))
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num_years <- length(years)
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area_names <- as.vector(unique(df$area))
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num_areas <- length(area_names)
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df2 <- list()
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df2$area <- sort(rep(area_names, num_years))
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df2$year <- rep(years, num_areas)
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df2 <- as.data.frame(df2)
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getAmountForYearAreaPair <- function(a_df, target_year, target_area){
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filter = dplyr::filter
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# target_year = 2022
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# target_area = "Longtermism"
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rows = a_df %>% filter(year == target_year) %>% filter(area == target_area)
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return(sum(rows$amount))
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}
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getAmountForYearAreaPair(df, 2022, "Longtermism & GCRs")
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getAmountForArea <- function(a_df, target_area){
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filter = dplyr::filter
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rows = a_df %>% filter(area == target_area)
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return(sum(rows$amount))
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}
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getAmountForArea(df, "Longtermism & GCRs")
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amounts <- c()
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for(i in c(1:dim(df2)[1])){
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amount <- getAmountForYearAreaPair(df, df2$year[i], df2$area[i])
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amounts <- c(amounts, amount)
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}
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df2$amount <- amounts
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## Order by cummulative amount
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df2$cummulative_amount_for_its_area = sapply(df2$area, function(area) {
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return(getAmountForArea(df, area))
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})
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View(df2)
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## Plotting
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title_text="Open Philanthropy allocation by year and cause area"
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subtitle_text="with my own aggregation of categories"
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palette = "Classic Red-Blue"
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direction = -1
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open_philanthropy_plot <- ggplot(data=df2, aes(x=year, y=amount, fill=area, group = cummulative_amount_for_its_area))+
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geom_bar(stat="identity")+
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labs(
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title=title_text,
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subtitle=subtitle_text,
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x=element_blank(),
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y=element_blank()
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) +
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# scale_fill_wsj() +
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# scale_fill_tableau(dir =1) +
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# scale_fill_tableau(palette, dir=direction) +
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# scale_fill_viridis(discrete = TRUE) +
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# scale_fill_brewer(palette = "Set2") +
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scale_fill_d3( "category20", alpha=0.8) +
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# scale_fill_uchicago("dark") +
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# scale_fill_startrek() +
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scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"), breaks = c(0:6)*10^8)+
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scale_x_continuous(breaks = years)+
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theme_tufte() +
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theme(
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legend.title = element_blank(),
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legend.text.align = 0,
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5),
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legend.position="bottom",
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legend.box="vertical",
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axis.text.x=element_text(angle=60, hjust=1),
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legend.text=element_text(size=7, hjust = 0.5)
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) +
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geom_text(aes(label=ifelse(amount > 25e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 1.7, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
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geom_text(
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aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
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stat = 'summary', fun = sum, size=2.2, vjust = -0.5
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) +
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guides(fill=guide_legend(nrow=3,byrow=TRUE))
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open_philanthropy_plot
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getwd() ## Working directory on which the file will be saved. Can be changed with setwd("/your/directory")
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height = 5
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width = 5
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ggsave(plot=open_philanthropy_plot, "open_philanthropy_grants_stacked_with_amounts.png", width=width, height=height, bg = "white")
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## Including Dustin Moskovitz's wealth
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coeff <- 10^7*4
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wealth <- c(6, 8, 12, 15, 18, 12, 14, 19, 14)
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df2$wealth <- rep(wealth * coeff, num_areas)
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make_fortune_plot <- function(show_fortune_legend = FALSE) {
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open_philanthropy_plot_with_fortune <- ggplot(data=df2, aes(x=year, y=amount, fill=area, group = cummulative_amount_for_its_area))+
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geom_bar(stat="identity")+
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geom_point(
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aes(x=year, y=wealth), size=2, color="darkblue", shape=4,
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show.legend=show_fortune_legend
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)+
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labs(
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title=title_text,
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subtitle=subtitle_text,
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x=element_blank(),
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y=element_blank()
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) +
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# scale_fill_wsj() +
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# scale_fill_tableau(dir =1) +
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# scale_fill_tableau(palette, dir=direction) +
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# scale_fill_viridis(discrete = TRUE) +
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# scale_fill_brewer(palette = "Set2") +
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scale_fill_d3( "category20", alpha=0.8) +
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# scale_fill_uchicago("dark") +
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# scale_fill_startrek() +
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scale_y_continuous(
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labels = scales::dollar_format(scale = 0.000001, suffix = "M"),
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name="OpenPhil donations",
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breaks = c(0:5)*10^8,
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sec.axis = sec_axis(
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~.*1,
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name="Dustin Moskovitz's fortune\n(est. Bloomberg)",
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breaks = seq(0,20,by=5)*coeff,
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labels = c("$0B", "$5B","$10B","$15B", "$20B")
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),
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limits=c(0,8*10^8)
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)+
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scale_x_continuous(breaks = years)+
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theme_tufte() +
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theme(
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legend.title = element_blank(),
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5),
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legend.position="bottom",
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legend.box="vertical",
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axis.text.x=element_text(angle=60, hjust=1),
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axis.title.y = element_text(vjust=3, hjust=0.25, size=10),
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axis.title.y.right = element_text(vjust=3, hjust=0.5, size=10),
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legend.text=element_text(size=8)
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) +
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guides(fill=guide_legend(nrow=4,byrow=TRUE))
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# open_philanthropy_plot_with_fortune
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height = 6
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width = 5
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filename = ifelse(
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show_fortune_legend,
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"open_philanthropy_plot_with_fortune.png",
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"open_philanthropy_plot_with_fortune_clean_labels.png"
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)
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ggsave(plot=open_philanthropy_plot_with_fortune, filename, width=width, height=height, bg = "white")
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}
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make_fortune_plot(TRUE)
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make_fortune_plot(FALSE)
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## Look at the different longtermist areas independently.
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longtermism <- c("Biosecurity & Pandemic Preparedness", "Potential Risks from Advanced AI", "Science Supporting Biosecurity and Pandemic Preparedness", "Longtermism")
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df3 <- list()
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df3$year <- as.vector(sapply(data$Date, getYear))
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df3$amount <- as.vector(sapply(data$Amount, parse_number))
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df3$amount <- ifelse(is.na(df$amount), 0, df$amount)
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df3$area <- as.vector(data$Focus.Area)
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df3 <- as.data.frame(df3)
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df3$area <- as.vector(data$Focus.Area)
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df3 <- df3 %>% dplyr::filter(area %in% longtermism)
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# View(df3)
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## Group area
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pure_longtermism = c("Longtermism")
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biorisk = c("Biosecurity & Pandemic Preparedness", "Science Supporting Biosecurity and Pandemic Preparedness")
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ai_risk = c( "Potential Risks from Advanced AI")
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longtermism_labels = c(pure_longtermism, "Biosecurity & Pandemic Preparedness", ai_risk)
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df3$area <- ifelse(df3$area %in% pure_longtermism, "Longtermism", df3$area)
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df3$area <- ifelse(df3$area %in% biorisk, "Biosecurity & Pandemic Preparedness", df3$area)
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df3$area <- ifelse(df3$area %in% ai_risk, "Potential Risks from Advanced AI", df3$area)
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years <- c(2014: 2022) # as.vector(unique(df$year))
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num_years <- length(years)
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area_names <- longtermism_labels
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num_areas <- length(area_names)
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df4 <- list()
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df4$area <- sort(rep(area_names, num_years))
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df4$year <- rep(years, num_areas)
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df4 <- as.data.frame(df4)
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# View(df4)
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getAmountForYearAreaPair(df3, 2022, "Longtermism")
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amounts <- c()
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for(i in c(1:dim(df4)[1])){
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amount <- getAmountForYearAreaPair(df3, df4$year[i], df4$area[i])
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amounts <- c(amounts, amount)
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}
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df4$amount <- amounts
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df4$cummulative_amount_for_its_area = sapply(df4$area, function(area) {
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return(getAmountForArea(df3, area))
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})
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View(df4)
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## Plotting longtermist funding
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title_text="Open Philanthropy allocation by year and cause area"
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subtitle_text="restricted to longtermism & GCRs"
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palette = "Classic Red-Blue"
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direction = -1
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open_philanthropy_plot_lt <- ggplot(data=df4, aes(x=year, y=amount, fill=area, group=cummulative_amount_for_its_area))+
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geom_bar(stat="identity")+
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labs(
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title=title_text,
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subtitle=subtitle_text,
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x=element_blank(),
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y=element_blank()
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) +
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# scale_fill_wsj() +
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# scale_fill_tableau(dir =1) +
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# scale_fill_tableau(palette, dir=direction) +
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# scale_fill_viridis(discrete = TRUE) +
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# scale_fill_brewer(palette = "Set2") +
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scale_fill_d3( "category20", alpha=0.8) +
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# scale_fill_uchicago("dark") +
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# scale_fill_startrek() +
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scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
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scale_x_continuous(breaks = years)+
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theme_tufte() +
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theme(
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legend.title = element_blank(),
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legend.text.align = 0,
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5),
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legend.position="bottom",
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legend.box="vertical",
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axis.text.x=element_text(angle=60, hjust=1),
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legend.text=element_text(size=7)
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) +
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geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
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geom_text(
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aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
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stat = 'summary', fun = sum, size=2.3, vjust = -0.5
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) +
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guides(fill=guide_legend(nrow=3,byrow=TRUE))
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open_philanthropy_plot_lt
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getwd() ## Working directory on which the file will be saved. Can be changed with setwd("/your/directory")
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height = 5
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width = 6
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## open_philanthropy_plot_lt
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ggsave(plot=open_philanthropy_plot_lt, "open_philanthropy_grants_lt_labeled.png", width=width, height=height, bg = "white")
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