mapa_perda_valor_ilicito <- function(tidy, map, pop){
p <- tidy %>%
filter(teve_multa == 'sim') %>%
mutate(id = uf) %>%
group_by(id) %>%
summarise(vl_perda_bens = sum(vl_perda_bens)) %>%
inner_join(map) %>% {
ggplot(.) +
geom_map(aes(x = long, y = lat, map_id = id, fill = vl_perda_bens),
color = 'gray30', map = ., data = .) +
scale_fill_continuous(low = 'white', high = 'green') +
coord_equal() +
theme_void()
}
p}
mapa_perda_valor_ilicito_percapita <- function(tidy, map, pop){
p <- tidy %>%
filter(teve_perda_bens == 'sim') %>%
mutate(id = uf) %>%
group_by(id) %>%
summarise(vl_perda_bens = sum(vl_perda_bens)) %>%
inner_join(pop, 'id') %>%
mutate(perda_bens_p_cpt = vl_perda_bens / popt * 100000) %>%
inner_join(map) %>% {
ggplot(.) +
geom_map(aes(x = long, y = lat, map_id = id, fill = perda_bens_p_cpt),
color = 'gray30', map = ., data = .) +
scale_fill_continuous(low = 'white', high = 'green') +
coord_equal() +
theme_void()
}
p}
mapa_multa <- function(tidy, map, pop){
p <- tidy %>%
filter(teve_multa == 'sim') %>%
mutate(id = uf) %>%
group_by(id) %>%
summarise(vl_multa = sum(vl_multa)) %>%
inner_join(map) %>% {
ggplot(.) +
geom_map(aes(x = long, y = lat, map_id = id, fill = vl_multa),
color = 'gray30', map = ., data = .) +
scale_fill_continuous(low = 'white', high = 'green') +
coord_equal() +
theme_void()
}
p}
mapa_multa_percapita <- function(tidy, map, pop){
p <- tidy %>%
filter(teve_multa == 'sim') %>%
mutate(id = uf) %>%
group_by(id) %>%
summarise(vl_multa = sum(vl_multa)) %>%
inner_join(pop, 'id') %>%
mutate(multa_p_cpt = vl_multa / popt * 100000) %>%
inner_join(map) %>% {
ggplot(.) +
geom_map(aes(x = long, y = lat, map_id = id, fill = multa_p_cpt),
color = 'gray30', map = ., data = .) +
coord_equal() +
scale_fill_continuous(low = 'white', high = 'green') +
theme_void()
}
p}
mapa_ress <- function(tidy, map, pop){
p <- tidy %>%
filter(teve_ressarcimento == 'sim') %>%
mutate(id = uf) %>%
group_by(id) %>%
summarise(vl_ress = sum(vl_ressarcimento)) %>%
inner_join(map) %>% {
ggplot(.) +
geom_map(aes(x = long, y = lat, map_id = id, fill = vl_ress),
color = 'gray30', map = ., data = .) +
scale_fill_continuous(low = 'white', high = 'green') +
coord_equal() +
theme_void()
}
p}
mapa_ress_percapita <- function(tidy, map, pop){
p <- tidy %>%
filter(teve_ressarcimento == 'sim') %>%
mutate(id = uf) %>%
group_by(id) %>%
summarise(vl_ress = sum(vl_ressarcimento)) %>%
inner_join(pop, 'id') %>%
mutate(ress_p_cpt = vl_ress / popt * 100000) %>%
inner_join(map) %>% {
ggplot(.) +
geom_map(aes(x = long, y = lat, map_id = id, fill = ress_p_cpt),
color = 'gray30', map = ., data = .) +
scale_fill_continuous(low = 'white', high = 'green') +
coord_equal() +
theme_void()
}
p}
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