513 lines
19 KiB
R
513 lines
19 KiB
R
getAmountForYearAreaPair(df3, 2022, "Longtermism")
|
|
amounts <- c()
|
|
for(i in c(1:dim(df4)[1])){
|
|
amount <- getAmountForYearAreaPair(df3, df4$year[i], df4$area[i])
|
|
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=cummulative_amount_for_its_area))+
|
|
geom_bar(stat="identity")+
|
|
labs(
|
|
title=title_text,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
legend.text=element_text(size=7)
|
|
) +
|
|
geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
|
|
geom_text(
|
|
aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
|
|
stat = 'summary', fun = sum, size=2.3, vjust = -0.5
|
|
) +
|
|
guides(fill=guide_legend(nrow=3,byrow=TRUE))
|
|
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,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
legend.text.align = 0,
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
legend.text=element_text(size=7)
|
|
) +
|
|
geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
|
|
geom_text(
|
|
aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
|
|
stat = 'summary', fun = sum, size=2.3, vjust = -0.5
|
|
) +
|
|
guides(fill=guide_legend(nrow=3,byrow=TRUE))
|
|
open_philanthropy_plot_lt
|
|
df3 <- list()
|
|
df3$year <- as.vector(sapply(data$Date, getYear))
|
|
df3$amount <- as.vector(sapply(data$Amount, parse_number))
|
|
df3$amount <- ifelse(is.na(df$amount), 0, df$amount)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- as.data.frame(df3)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
## Including Dustin Moskovitz's wealth
|
|
coeff <- 10^7*4
|
|
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, group = cummulative_amount_for_its_area))+
|
|
geom_bar(stat="identity")+
|
|
geom_point(
|
|
aes(x=year, y=wealth), size=2, color="darkblue", shape=4,
|
|
show.legend=show_fortune_legend
|
|
)+
|
|
labs(
|
|
title=title_text,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(
|
|
labels = scales::dollar_format(scale = 0.000001, suffix = "M"),
|
|
name="OpenPhil donations",
|
|
breaks = c(0:5)*10^8,
|
|
sec.axis = sec_axis(
|
|
~.*1,
|
|
name="Dustin Moskovitz's fortune\n(est. Bloomberg)",
|
|
breaks = seq(0,20,by=5)*coeff,
|
|
labels = c("$0B", "$5B","$10B","$15B", "$20B")
|
|
),
|
|
limits=c(0,8*10^8)
|
|
)+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
axis.title.y = element_text(vjust=3, hjust=0.25, size=10),
|
|
axis.title.y.right = element_text(vjust=3, hjust=0.5, size=10),
|
|
legend.text=element_text(size=8)
|
|
) +
|
|
guides(fill=guide_legend(nrow=4,byrow=TRUE))
|
|
# open_philanthropy_plot_with_fortune
|
|
height = 6
|
|
width = 5
|
|
filename = ifelse(
|
|
show_fortune_legend,
|
|
"open_philanthropy_plot_with_fortune.png",
|
|
"open_philanthropy_plot_with_fortune_clean_labels.png"
|
|
)
|
|
ggsave(plot=open_philanthropy_plot_with_fortune, filename, width=width, height=height, bg = "white")
|
|
}
|
|
make_fortune_plot(TRUE)
|
|
make_fortune_plot(FALSE)
|
|
## Look at the different longtermist areas independently.
|
|
longtermism <- c("Biosecurity & Pandemic Preparedness", "Potential Risks from Advanced AI", "Science Supporting Biosecurity and Pandemic Preparedness", "Longtermism")
|
|
df3 <- list()
|
|
df3$year <- as.vector(sapply(data$Date, getYear))
|
|
df3$amount <- as.vector(sapply(data$Amount, parse_number))
|
|
df3$amount <- ifelse(is.na(df$amount), 0, df$amount)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- as.data.frame(df3)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- df3 %>% dplyr::filter(area %in% longtermism)
|
|
df$area <- ifelse(df3$area %in% ea_growth, "EA Community Building", df$area)
|
|
## Group area
|
|
df3
|
|
df3$area <- ifelse(df$area %in% pure_longtermism, "Longtermism", df$area)
|
|
pure_longtermism = c("Longtermism")
|
|
biorisk = c("Biosecurity & Pandemic Preparedness", "Science Supporting Biosecurity and Pandemic Preparedness")
|
|
ai_risk = c( "Potential Risks from Advanced AI")
|
|
df3$area <- ifelse(df$area %in% pure_longtermism, "Longtermism", df$area)
|
|
df3$area <- ifelse(df$area %in% biorisk, "Biosecurity & Pandemic Preparedness", df$area)
|
|
df3$area <- ifelse(df$area %in% ai_risk, "Potential Risks from Advanced AI", df$area)
|
|
df3 <- list()
|
|
df3$year <- as.vector(sapply(data$Date, getYear))
|
|
df3$amount <- as.vector(sapply(data$Amount, parse_number))
|
|
df3$amount <- ifelse(is.na(df$amount), 0, df$amount)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- as.data.frame(df3)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- df3 %>% dplyr::filter(area %in% longtermism)
|
|
pure_longtermism = c("Longtermism")
|
|
biorisk = c("Biosecurity & Pandemic Preparedness", "Science Supporting Biosecurity and Pandemic Preparedness")
|
|
ai_risk = c( "Potential Risks from Advanced AI")
|
|
df3$area <- ifelse(df$area %in% pure_longtermism, "Longtermism", df$area)
|
|
df3$area <- ifelse(df$area %in% biorisk, "Biosecurity & Pandemic Preparedness", df$area)
|
|
df3 <- list()
|
|
df3$year <- as.vector(sapply(data$Date, getYear))
|
|
df3$amount <- as.vector(sapply(data$Amount, parse_number))
|
|
df3$amount <- ifelse(is.na(df$amount), 0, df$amount)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- as.data.frame(df3)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- df3 %>% dplyr::filter(area %in% longtermism)
|
|
pure_longtermism = c("Longtermism")
|
|
biorisk = c("Biosecurity & Pandemic Preparedness", "Science Supporting Biosecurity and Pandemic Preparedness")
|
|
ai_risk = c( "Potential Risks from Advanced AI")
|
|
df3$area <- ifelse(df3$area %in% pure_longtermism, "Longtermism", df3$area)
|
|
df3$area <- ifelse(df3$area %in% biorisk, "Biosecurity & Pandemic Preparedness", df3$area)
|
|
df3$area <- ifelse(df3$area %in% ai_risk, "Potential Risks from Advanced AI", df3$area)
|
|
years <- c(2014: 2022) # as.vector(unique(df$year))
|
|
num_years <- length(years)
|
|
area_names <- longtermism
|
|
num_areas <- length(area_names)
|
|
df4 <- list()
|
|
df4$area <- sort(rep(area_names, num_years))
|
|
df4$year <- rep(years, num_areas)
|
|
df4 <- as.data.frame(df4)
|
|
# View(df4)
|
|
getAmountForYearAreaPair(df3, 2022, "Longtermism")
|
|
amounts <- c()
|
|
for(i in c(1:dim(df4)[1])){
|
|
amount <- getAmountForYearAreaPair(df3, df4$year[i], df4$area[i])
|
|
amounts <- c(amounts, amount)
|
|
}
|
|
df4$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=cummulative_amount_for_its_area))+
|
|
geom_bar(stat="identity")+
|
|
labs(
|
|
title=title_text,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
legend.text.align = 0,
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
legend.text=element_text(size=7)
|
|
) +
|
|
geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
|
|
geom_text(
|
|
aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
|
|
stat = 'summary', fun = sum, size=2.3, vjust = -0.5
|
|
) +
|
|
guides(fill=guide_legend(nrow=3,byrow=TRUE))
|
|
open_philanthropy_plot_lt
|
|
longtermism_labels = c(pure_longtermism, biorisk, ai_risk)
|
|
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,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
legend.text.align = 0,
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
legend.text=element_text(size=7)
|
|
) +
|
|
geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
|
|
geom_text(
|
|
aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
|
|
stat = 'summary', fun = sum, size=2.3, vjust = -0.5
|
|
) +
|
|
guides(fill=guide_legend(nrow=3,byrow=TRUE))
|
|
years <- c(2014: 2022) # as.vector(unique(df$year))
|
|
num_years <- length(years)
|
|
area_names <- longtermism_labels
|
|
num_areas <- length(area_names)
|
|
df4 <- list()
|
|
df4$area <- sort(rep(area_names, num_years))
|
|
df4$year <- rep(years, num_areas)
|
|
df4 <- as.data.frame(df4)
|
|
# View(df4)
|
|
getAmountForYearAreaPair(df3, 2022, "Longtermism")
|
|
amounts <- c()
|
|
for(i in c(1:dim(df4)[1])){
|
|
amount <- getAmountForYearAreaPair(df3, df4$year[i], df4$area[i])
|
|
amounts <- c(amounts, amount)
|
|
}
|
|
df4$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=cummulative_amount_for_its_area))+
|
|
geom_bar(stat="identity")+
|
|
labs(
|
|
title=title_text,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
legend.text.align = 0,
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
legend.text=element_text(size=7)
|
|
) +
|
|
geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
|
|
geom_text(
|
|
aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
|
|
stat = 'summary', fun = sum, size=2.3, vjust = -0.5
|
|
) +
|
|
guides(fill=guide_legend(nrow=3,byrow=TRUE))
|
|
open_philanthropy_plot_lt
|
|
## Look at the different longtermist areas independently.
|
|
longtermism <- c("Biosecurity & Pandemic Preparedness", "Potential Risks from Advanced AI", "Science Supporting Biosecurity and Pandemic Preparedness", "Longtermism")
|
|
df3 <- list()
|
|
df3$year <- as.vector(sapply(data$Date, getYear))
|
|
df3$amount <- as.vector(sapply(data$Amount, parse_number))
|
|
df3$amount <- ifelse(is.na(df$amount), 0, df$amount)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- as.data.frame(df3)
|
|
df3$area <- as.vector(data$Focus.Area)
|
|
df3 <- df3 %>% dplyr::filter(area %in% longtermism)
|
|
pure_longtermism = c("Longtermism")
|
|
biorisk = c("Biosecurity & Pandemic Preparedness", "Science Supporting Biosecurity and Pandemic Preparedness")
|
|
ai_risk = c( "Potential Risks from Advanced AI")
|
|
longtermism_labels = c(pure_longtermism, biorisk, ai_risk)
|
|
df3$area <- ifelse(df3$area %in% pure_longtermism, "Longtermism", df3$area)
|
|
df3$area <- ifelse(df3$area %in% biorisk, "Biosecurity & Pandemic Preparedness", df3$area)
|
|
df3$area <- ifelse(df3$area %in% ai_risk, "Potential Risks from Advanced AI", df3$area)
|
|
years <- c(2014: 2022) # as.vector(unique(df$year))
|
|
num_years <- length(years)
|
|
area_names <- longtermism_labels
|
|
num_areas <- length(area_names)
|
|
df4 <- list()
|
|
df4$area <- sort(rep(area_names, num_years))
|
|
df4$year <- rep(years, num_areas)
|
|
df4 <- as.data.frame(df4)
|
|
# View(df4)
|
|
getAmountForYearAreaPair(df3, 2022, "Longtermism")
|
|
amounts <- c()
|
|
for(i in c(1:dim(df4)[1])){
|
|
amount <- getAmountForYearAreaPair(df3, df4$year[i], df4$area[i])
|
|
amounts <- c(amounts, amount)
|
|
}
|
|
df4$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=cummulative_amount_for_its_area))+
|
|
geom_bar(stat="identity")+
|
|
labs(
|
|
title=title_text,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
legend.text.align = 0,
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
legend.text=element_text(size=7)
|
|
) +
|
|
geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
|
|
geom_text(
|
|
aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
|
|
stat = 'summary', fun = sum, size=2.3, vjust = -0.5
|
|
) +
|
|
guides(fill=guide_legend(nrow=3,byrow=TRUE))
|
|
open_philanthropy_plot_lt
|
|
View(df4)
|
|
df4 <- list()
|
|
df4$area <- sort(rep(area_names, num_years))
|
|
df4 <- list()
|
|
df4$area <- sort(rep(area_names, num_years))
|
|
df4$area
|
|
longtermism_labels
|
|
longtermism_labels = c(pure_longtermism, "Biosecurity & Pandemic Preparedness", ai_risk)
|
|
df3$area <- ifelse(df3$area %in% pure_longtermism, "Longtermism", df3$area)
|
|
df3$area <- ifelse(df3$area %in% biorisk, "Biosecurity & Pandemic Preparedness", df3$area)
|
|
df3$area <- ifelse(df3$area %in% ai_risk, "Potential Risks from Advanced AI", df3$area)
|
|
years <- c(2014: 2022) # as.vector(unique(df$year))
|
|
num_years <- length(years)
|
|
area_names <- longtermism_labels
|
|
num_areas <- length(area_names)
|
|
df4 <- list()
|
|
df4$area <- sort(rep(area_names, num_years))
|
|
df4$year <- rep(years, num_areas)
|
|
df4 <- as.data.frame(df4)
|
|
# View(df4)
|
|
getAmountForYearAreaPair(df3, 2022, "Longtermism")
|
|
amounts <- c()
|
|
for(i in c(1:dim(df4)[1])){
|
|
amount <- getAmountForYearAreaPair(df3, df4$year[i], df4$area[i])
|
|
amounts <- c(amounts, amount)
|
|
}
|
|
df4$amount <- amounts
|
|
df4$cummulative_amount_for_its_area = sapply(df4$area, function(area) {
|
|
return(getAmountForArea(df3, area))
|
|
})
|
|
View(df4)
|
|
## 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=cummulative_amount_for_its_area))+
|
|
geom_bar(stat="identity")+
|
|
labs(
|
|
title=title_text,
|
|
subtitle=subtitle_text,
|
|
x=element_blank(),
|
|
y=element_blank()
|
|
) +
|
|
# scale_fill_wsj() +
|
|
# scale_fill_tableau(dir =1) +
|
|
# scale_fill_tableau(palette, dir=direction) +
|
|
# scale_fill_viridis(discrete = TRUE) +
|
|
# scale_fill_brewer(palette = "Set2") +
|
|
scale_fill_d3( "category20", alpha=0.8) +
|
|
# scale_fill_uchicago("dark") +
|
|
# scale_fill_startrek() +
|
|
scale_y_continuous(labels = scales::dollar_format(scale = 0.000001, suffix = "M"))+
|
|
scale_x_continuous(breaks = years)+
|
|
theme_tufte() +
|
|
theme(
|
|
legend.title = element_blank(),
|
|
legend.text.align = 0,
|
|
plot.title = element_text(hjust = 0.5),
|
|
plot.subtitle = element_text(hjust = 0.5),
|
|
legend.position="bottom",
|
|
legend.box="vertical",
|
|
axis.text.x=element_text(angle=60, hjust=1),
|
|
legend.text=element_text(size=7)
|
|
) +
|
|
geom_text(aes(label=ifelse(amount > 5e6, paste0(round(amount / 1e6, 0), "M"), "")), size = 2, colour="#f9f9f9", position = position_stack(vjust = 0.5)) +
|
|
geom_text(
|
|
aes(label = paste0(round(after_stat(y) / 1e6, 0), "M"), group = year),
|
|
stat = 'summary', fun = sum, size=2.3, vjust = -0.5
|
|
) +
|
|
guides(fill=guide_legend(nrow=3,byrow=TRUE))
|
|
open_philanthropy_plot_lt
|
|
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
|
|
ggsave(plot=open_philanthropy_plot_lt, "open_philanthropy_grants_lt_labeled.png", width=width, height=height, bg = "white")
|