# LIBRARIES
{library(ggplot2)
library(ggthemes)
library(dplyr)
library(readr)
library(sf)
library(showtext)
}
# FONTS
font_add_google("Luckiest Guy","ramp")
font_add_google("Bebas Neue","beb")
font_add_google("Fira Sans","fira")
font_add_google("Raleway","ral")
font_add_google("Bitter","bit")
showtext_auto()
# DATA
<- readr::read_rds(
data "https://github.com/viniciusoike/restateinsight/raw/main/static/data/atlas_sp_hdi.rds"
)
<- data |>
HDI st_drop_geometry() |>
mutate(
group_hdi = findInterval(HDI, seq(0.65, 0.95, 0.05), left.open = FALSE),
group_hdi = factor(group_hdi)) |>
group_by(group_hdi) |>
summarise(score = sum(pop, na.rm = TRUE)) |>
ungroup() |>
mutate(share = score / sum(score) * 100) |>
na.omit()
Los datos representan el Índice de Desarrollo Humano en los diferentes distritos del Municipio de São Paulo en el 2010.
ggplot(HDI, aes(group_hdi, share, fill = group_hdi)) +
geom_col()
<- HDI |>
HDI mutate(
y_text = if_else(group_hdi %in% c(0, 7), share + 3, share - 3),
label = paste0(round(share, 1), "%")
)
ggplot(HDI, aes(group_hdi, share, fill = group_hdi)) +
geom_col() +
geom_hline(yintercept = 0) +
geom_text(
aes(y = y_text, label = label, color = group_hdi),
size = 3
+
) coord_flip() +
scale_fill_brewer(palette = "YlGnBu") +
scale_color_manual(values = c(rep("black", 5), rep("white", 2), "black")) +
guides(fill = "none", color = "none")
<- c(
x_labels "Menos desarrollado\n<0.650", "(0.650 - 0.699)", "(0.700 - 0.749)", "(0.750 - 0.799)",
"(0.800 - 0.849)", "(0.850 - 0.899)", "(0.900 - 0.949)", "Más desarrollado\n>0.950"
)
ggplot(HDI, aes(group_hdi, share, fill = group_hdi)) +
geom_col() +
geom_hline(yintercept = 0) +
geom_text(
aes(y = y_text, label = label, color = group_hdi),
size = 4.5
+
) coord_flip() +
scale_x_discrete(labels = x_labels) +
scale_fill_brewer(palette = "YlGnBu") +
scale_color_manual(values = c(rep("black", 5),
rep("white", 2),
"black")) +
guides(fill = "none", color = "none") +
labs(
title = "\nÍndice de Desarrollo Humano\nSão Paulo, Brasil\n",
caption = "Población total: 11.209.673 hab.\nDatos: Atlas Brasil",
x = "\nÍndice de desarrollo humano",
y = "\nPorcentaje por grupo\n\n")
<- ggplot(HDI, aes(group_hdi, share, fill = group_hdi)) +
plot geom_col() +
geom_hline(yintercept = 0) +
geom_text(
aes(y = y_text, label = label, color = group_hdi),
size = 4.5
+
) coord_flip() +
scale_x_discrete(labels = x_labels) +
scale_fill_brewer(palette = "YlGnBu") +
scale_color_manual(values = c(rep("black", 5),
rep("white", 2),
"black")) +
guides(fill = "none", color = "none") +
labs(
title = "\nÍndice de Desarrollo Humano\nSão Paulo, Brasil\n",
caption = "Población total: 11.209.673 hab.\nDatos: Atlas Brasil",
x = "\nÍndice de desarrollo humano",
y = "\nPorcentaje por grupo\n\n") +
theme(
text = element_text(family = "fira"),
panel.grid = element_blank(),
plot.title = element_text(size = 25, colour = "gray20", face="bold"),
axis.text.y = element_text(size = 13, colour = "gray20"),
axis.title.x = element_text(size = 18, colour = "gray20"),
axis.title.y = element_text(size = 18, colour = "gray20"),
axis.text.x = element_blank(),
panel.background = element_rect(fill = 'white', color = 'white')
)
#plot