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ruas porto 2.R
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ruas porto 2.R
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library(stringr)
library(tidywikidatar)
library(tidyverse)
library(osmdata)
#if(!require("devtools")) install.packages("devtools")
#devtools::install_github("meirelesff/genderBR")
library(sf)
library(genderBR)
library(extrafont)
# install.packages("emojifont")
# library(emojifont)
# load.fontawesome()
remotes::install_github("hrbrmstr/waffle")
library(waffle)
library(magrittr)
library(hrbrthemes)
library(ggplot2)
library(dplyr)
library(tidyverse)
library(waffle)
library(leaflet)
tw_enable_cache()
tw_set_cache_folder(path = fs::path(fs::path_home_r(), "R", "tw_data"))
tw_set_language(language = "en")
tw_create_cache_folder(ask = FALSE)
#https://www.listendata.com/2019/06/create-infographics-with-r.html
#https://stackoverflow.com/questions/51508415/waffle-package-on-r-icon/74589250#74589250
# city_coords <- matrix(data = c(-8.71902,41.10626,-8.54393,41.20758),
# nrow = 2, ncol = 2)
city_coords <- matrix(data = c(-8.698254,41.136520,-8.565388,41.189377),
nrow = 2, ncol = 2)
limits <- c(city_coords[1,1], city_coords[2,1],
city_coords[1,2], city_coords[2,2])
streets <- opq(bbox = limits) %>%
add_osm_feature(key = "highway") %>%
osmdata_sf()
gardens <- opq("Porto Portugal") %>%
add_osm_feature(key = "leisure",value = c("park","garden")) %>%
osmdata_sf()
squares <- opq("Porto Portugal") %>%
add_osm_feature(key = "place",value = c("square")) %>%
osmdata_sf()
#available_features()
# osmdata::available_tags("highway")
unique(squares$osm_polygons$name) %>% sort() %>% as.data.frame() %>%
rename(rua=1) %>%
mutate(rua=iconv(rua,from="UTF-8", to="LATIN1")) %>%
mutate(nome = case_when(str_starts(rua,"Praceta |Jardins |Alameda ")~str_sub(rua,9),
str_starts(rua,"Jardim |Parque |Quinta ")~str_sub(rua,8),
str_starts(rua,"Pra?a |Largo |Fonte ")~str_sub(rua,7)),
clean=case_when(str_starts(nome,"^de\\s|^ da\\s|^da\\s|^do\\s")~str_sub(nome,4),
str_starts(nome,"^das\\s|^dos\\s")~str_sub(nome,5),
TRUE~nome)) -> pracas
unique(gardens$osm_polygons$name) %>% sort() %>% as.data.frame() %>%
rename(rua=1) %>%
mutate(rua=iconv(rua,from="UTF-8", to="LATIN1")) %>%
mutate(nome = case_when(str_starts(rua,"Praceta |Jardins |Alameda ")~str_sub(rua,9),
str_starts(rua,"Jardim |Parque |Quinta ")~str_sub(rua,8),
str_starts(rua,"Pra?a |Largo |Fonte ")~str_sub(rua,7)),
clean=case_when(str_starts(nome,"^de\\s|^ da\\s|^da\\s|^do\\s")~str_sub(nome,4),
str_starts(nome,"^das\\s|^dos\\s")~str_sub(nome,5),
TRUE~nome)) -> parques
unique(streets$osm_lines$name) %>% sort() %>% as.data.frame() %>%
rename(rua=1) %>%
mutate(nome = case_when(str_starts(rua,"Nó ")~str_sub(rua,4),
str_starts(rua,"Rua |Via ")~str_sub(rua,5),
str_starts(rua,"Muro |Cais |Beco |Vila ")~str_sub(rua,6),
str_starts(rua,"Pátio |Campo |Praça |Largo |Viela |Rampa |Túnel |Ponte ")~str_sub(rua,7),
str_starts(rua,"Jardim |Rossio |Escada |Parque |Bairro |Quinta |Vereda ")~str_sub(rua,8),
str_starts(rua,"Ribeira |Recanto |Estrada |Avenida |Viaduto |Praceta |Calçada |Alameda |Rotunda |Escadas |Passeio |Ladeira |Caminho ")~str_sub(rua,9),
str_starts(rua,"Travessa |Ciclovia |Tribunal ")~str_sub(rua,10),
str_starts(rua,"Miradouro |Escadaria ")~str_sub(rua,11))
) %>%
mutate(teste=str_starts(nome,"^de\\s|^da\\s|^ da\\s|^do\\s"),
clean=case_when(str_starts(nome,"^de\\s|^ da\\s|^da\\s|^do\\s")~str_sub(nome,4),
str_starts(nome,"^das\\s|^dos\\s")~str_sub(nome,5),
TRUE~nome)
) %>%
filter(!is.na(clean)) %>%
mutate(genero =get_gender(clean)) -> ruas
parques %>% clipr::write_clip()
pracas %>% clipr::write_clip()
pracas2 = clipr::read_clip_tbl()
parques2 = clipr::read_clip_tbl()
parques$sexoFinal2 = NULL
pracas = pracas %>% bind_cols(pracas2)%>%
mutate(sexoFinal2 = case_when(sexoFinal2=="Nada"~NA_character_,
TRUE~sexoFinal2))
parques = parques %>% bind_cols(parques2) %>%
mutate(sexoFinal2 = case_when(sexoFinal2=="Nada"~NA_character_,
TRUE~sexoFinal2))
# saveRDS(pracas,"pracas.rds")
# saveRDS(parques,"parques.rds")
#saveRDS(ruas,"ruas.rds")
ruas2 = ruas %>%
mutate(sexoWiki = case_when(!is.na(clean)~tw_get_label(tw_get_property(tw_search(search = clean,limit = 1)$id,p="P21")$value),
TRUE~NA_character_))
#saveRDS(ruas2,"ruas2.rds")
ruas2 %>%
mutate(sexoFinal = case_when(tolower(genero)==sexoWiki~genero,
!is.na(genero)& is.na(sexoWiki)~genero,
is.na(genero)&!is.na(sexoWiki)~stringr::str_to_title(sexoWiki))) %>%
clipr::write_clip()
#
# codigos = readRDS("C:\\Users\\rafae\\Downloads\\20221205 codigos ajustados.rds")
# codigos
# codigos2 = readRDS("C:\\Users\\rafae\\Downloads\\20221205 1041 ruas.rds")
# codigos2 %>% clipr::write_clip()
ruas2 %>% filter(!clean %in% codigos2$nome_arteria) %>% clipr::write_clip()
ruas3 = openxlsx::read.xlsx("C:\\Users\\rafae\\OneDrive\\Área de Trabalho\\ruas.xlsx",sheet = "Sheet6")
ruas4 = ruas3 %>% mutate(sexoFinal2 = case_when(ajustar=="Nada"~NA_character_,
ajustar=="Male"~"Male",
ajustar=="Female"~"Female",
is.na(ajustar)~sexoFinal))
streets2 = streets
streets2$osm_lines = streets$osm_lines %>% left_join(ruasfinal %>% select(rua,sexoFinal2),by=c("name"="rua"))
ruasAjustar = ruas %>% anti_join(ruas4 %>% select(rua,sexoFinal2),by=c("nome"="rua")) %>%
filter(!rua %in% ruas4$rua)
ruasAjustar %>% openxlsx::write.xlsx("ruasAjustar.xlsx")
ruasajustadas = openxlsx::read.xlsx("ruasAjustar.xlsx") %>%
mutate(sexoFinal2 = case_when(ajustar=="Nada"~NA_character_,
ajustar=="Male"~"Male",
ajustar=="Female"~"Female",
is.na(ajustar)~genero))
ruasfinal = bind_rows(ruas4 %>% select(-c(sexoWiki,sexoFinal)),
ruasajustadas) %>%
mutate(sexoFinal2 = case_when(clean %in% c("Escritor Costa Barreto","Furriel Guilherme Dantas",
"Moraes Caldas",
"Pintor Júlio Resende",
"Sá da Bandeira",
"Marquês Sá da Bandeira",
"São João do Porto",
"São Paio",
"São Pedro",
"São Salvador",
"Silva Porto",
"Silva Ramos",
"Silva Tapada",
"Sousa Aroso",
"Actor António Silva")~"Male",
clean %in% c("Nova do Fontão","Nova do Picão","Bela Vista","Navegantes")~NA_character_,
TRUE~sexoFinal2))
blankbg <-theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
legend.position = "none",
plot.background=element_blank(),
panel.grid.minor=element_blank(),
panel.background=element_blank(),
panel.grid.major=element_blank(),
plot.margin = unit(c(t=1,r=1,b=1,l=1), "cm"),
plot.caption = element_text(color = "grey20", size = 15,
hjust = .5, face = "plain",
family = "Didot"),
panel.border = element_blank()
)
ggplot() +
blankbg +
geom_sf(data = streets2$osm_lines %>%
filter(sexoFinal2 == "Male"),
size = .8,
color = "limegreen") +
geom_sf(data = streets2$osm_lines %>%
filter(sexoFinal2 == "Female"),
size = .8,
color = "brown1") +
geom_sf(data = streets2$osm_lines %>%
filter(is.na(sexoFinal2)),
size = .35,
color = "black") +
labs(caption = 'Porto') +
coord_sf(xlim = city_coords[1,],
ylim = city_coords[2,],
expand = FALSE)
ruasajustadas %>%
mutate(sexoFinal2 = case_when(clean %in% c("Escritor Costa Barreto","Furriel Guilherme Dantas",
"Moraes Caldas",
"Pintor Júlio Resende",
"Sá da Bandeira",
"São João do Porto",
"São Paio",
"São Pedro",
"São Salvador",
"Silva Porto",
"Silva Ramos",
"Silva Tapada",
"Sousa Aroso",
"Actor António Silva")~"Male")) %>%
filter(str_detect(clean,"Actor António Silva"))
streets2 = readRDS("C:\\Users\\belokurowsr\\Downloads\\streets2.rds")
ruasfinal = readRDS("C:\\Users\\belokurowsr\\Downloads\\ruasfinal.rds")
setwd("C:\\Users\\belokurowsr\\OneDrive - Kantar\\Desktop\\Kantar\\C?digoPostaisDistrito\\PT_adm2")
pt_adm2 = st_read("jt394dz4777.shp")
porto = pt_adm2 %>% filter(name_2 %in% c("Porto")) %>% mutate(name_3 = iconv(name_3,"latin1", "UTF-8"))
intersec = sf::st_intersection(streets2$osm_lines %>% select(osm_id,geometry), st_union(porto))
intersecParque = sf::st_intersection(gardens$osm_polygons %>% select(osm_id,geometry), st_union(porto))
intersec2 = sf::st_intersection(streets2$osm_lines %>% select(osm_id,geometry,name), st_union(porto))
intersecPraca = sf::st_intersection(squares$osm_polygons %>% select(osm_id,geometry), st_union(porto))
streets2$osm_lines = streets2$osm_lines %>%
mutate(porto = case_when(osm_id %in% intersec$osm_id~1,
TRUE~0))
squares2 = squares
squares2$osm_polygons = squares2$osm_polygons %>%
left_join(pracas %>% select(rua,sexoFinal2),by=c("name"="rua")) %>%
mutate(porto = case_when(osm_id %in% intersecPraca$osm_id~1,
TRUE~0)) %>%
mutate(name=iconv(name, "UTF-8","latin1"))
gardens2 = gardens
gardens2$osm_polygons = gardens2$osm_polygons %>%
left_join(parques %>% select(rua,sexoFinal2),by=c("name"="rua")) %>%
mutate(porto = case_when(osm_id %in% intersecParque$osm_id~1,
TRUE~0)) %>%
mutate(name=iconv(name,"latin1", "UTF-8"))
parques %>% distinct(rua,sexoFinal2) %>%
select(rua,sexoFinal2) %>% count(sexoFinal2)
gardens3 = gardens2$osm_polygons %>% bind_rows(squares2$osm_polygons)
pracasParques = gardens3 %>% filter(name %in% c(parques$rua,pracas$rua)) %>% distinct(name) %>%
left_join(parques %>% bind_rows(pracas),by=c("name"="rua")) %>% count(sexoFinal2)
gardens3 %>% filter(porto==1) %>% as.data.frame() %>%
count(sexoFinal2)
#save(porto,gardens3,streets2,file="dadosMapa.rdata")
tag.map.title <- tags$style(HTML("
.leaflet-control.map-title {
transform: translate(-50%,20%);
position: fixed !important;
left: 50%;
text-align: center;
padding-left: 10px;
padding-right: 10px;
background: rgba(255,255,255,0.75);
font-weight: bold;
font-size: 40px;
}
"))
title <- tags$div(
tag.map.title, HTML("Nomes de ruas, praças e parques por gênero no Concelho do Porto")
)
m= leaflet(options = leafletOptions(
attributionControl=FALSE)) %>%
addProviderTiles(provider = "CartoDB.Positron",group="Carto DB - Light",
options = providerTileOptions(attribution = "\u00A9 CartoDB")) %>%
addProviderTiles("CartoDB.DarkMatter", group="Dark",
options = providerTileOptions(noWrap = F,
updateWhenZooming = FALSE,
updateWhenIdle = FALSE,opacity = 0.9,
attribution = ""
)) %>%
addProviderTiles(providers$Stamen.TonerLite, group = "Toner - Light",
options = providerTileOptions(attribution = "")
) %>%
addPolygons(data = porto,stroke = F,color="white",opacity = 0.28,fillOpacity = 0.07,
group = "Perímetro Porto") %>%
addPolygons(data = gardens3 %>%
filter(sexoFinal2 == "Male" & porto == 1 ),
stroke = F,color="#1282A2",opacity = 0.7,fillOpacity = 0.70,
group = "Parques - Homens",
label = gardens3 %>%
filter(sexoFinal2 == "Male" & porto == 1 )%>% pull(name)) %>%
addPolygons(data = gardens3 %>%
filter(sexoFinal2 == "Female" & porto == 1 ),
stroke = F,color="#DC493A",opacity = 0.7,fillOpacity = 0.70,
group = "Parques - Mulheres",
label = gardens3 %>%
filter(sexoFinal2 == "Female" & porto == 1 )%>% pull(name)) %>%
leaflet::addPolylines(
data = streets2$osm_lines %>%
filter(is.na(sexoFinal2) & porto == 1),
color = "#AAAAAA",#648767
smoothFactor = 1,
weight = 1.2,
group="Ruas - Outros",
label=streets2$osm_lines %>%
filter(is.na(sexoFinal2) & porto == 1) %>% pull(name)
) %>%
leaflet::addPolylines(
data = streets2$osm_lines %>%
filter(sexoFinal2 == "Male"& porto == 1),
color = "#1282A2",
smoothFactor = 0.8,
weight = 1.8,
group="Ruas - Homens",
label = streets2$osm_lines %>%
filter(sexoFinal2 == "Male"& porto == 1) %>% pull(name)
) %>%
leaflet::addPolylines(
data = streets2$osm_lines %>%
filter(sexoFinal2 == "Female" & porto == 1) ,
color = "#DC493A",
smoothFactor = 0.8,
weight = 2.5,
group="Ruas - Mulheres",
label = streets2$osm_lines %>%
filter(sexoFinal2 == "Female" & porto == 1) %>% pull(name)
) %>%
addLayersControl( baseGroups = c("Carto DB - Light","Dark","Toner - Light"),
overlayGroups = c("Ruas - Homens","Ruas - Mulheres","Ruas - Outros",
"Perímetro Porto",
"Parques - Homens","Parques - Mulheres"),
options = layersControlOptions(collapsed = T)) %>%
addControl(title, position = "bottomleft") %>%
setView(lat=41.160922,lng = -8.624279, zoom=13)
m
mapshot(x=m,url="map.html",title="Map title")
mapshot(x=m,file ="map.png",vwidth = 1000, vheight = 533)
ruasintersec = intersec2 %>% as.data.frame() %>% count(name)
sexos = ruasfinal %>%
filter(rua %in% ruasintersec$name) %>%
count(rua,sexoFinal2) %>%
count(sexoFinal2)
xdf = pracasParques %>%
mutate(sexoFinal2 = case_when(is.na(sexoFinal2)~"Outros nomes",
sexoFinal2=="Female"~"Nomes Femininos",
sexoFinal2=="Male"~"Nomes Masculinos"
)) %>% mutate(prop = round(n/sum(n),2)*100)
#save.image("dados.rdata")
load("dados.rdata")
plotTotais = sexos %>% mutate(sexoFinal2 = case_when(is.na(sexoFinal2)~"Outros nomes",
sexoFinal2=="Female"~"Nomes Femininos",
sexoFinal2=="Male"~"Nomes Masculinos"
)) %>%
ggplot(aes(x=sexoFinal2, y=n,fill=sexoFinal2)) +
geom_bar(stat="identity", position=position_dodge())+
geom_text(aes(label=n),hjust=1.2,
#vjust=1.6,
color="white",
#position = position_dodge(0.9),
size=6)+
scale_fill_manual(values=c("#DC493A", "#1282A2","#949494"))+#DC493A #648767 ##FF5F15
coord_flip()+
labs(x="",y="",title="Nomes de espaços públicos do Porto por gênero")+
theme_minimal()+theme(legend.position = "None")+
theme(plot.title = element_text(size = 26,face="bold"),
axis.text.y = element_text(size = 18),
axis.text.x = element_text(size = 18))
ggsave(plotTotais,filename = "test3.png", type = "cairo", width =140,
height = 90, dpi = 300,units = "mm")
#Dados parques
#Mudar o azul
#Ver se as cores s?o colorblind-people-friendly
#aumentar fonte dos nomes no eixo y
#remover espa?o nas margens internas
#trocar provider dark Leaflet
plot=sexos %>% mutate(sexoFinal2 = case_when(is.na(sexoFinal2)~"Outros nomes",
sexoFinal2=="Female"~"Nomes Femininos",
sexoFinal2=="Male"~"Nomes Masculinos"
)) %>% mutate(prop = round(n/sum(n),2)*100) %>%
ggplot(aes(fill = sexoFinal2, values = prop)) +
geom_waffle(n_rows = 10, size = 1.3, colour = "white",flip=T) +
scale_fill_manual(name = NULL,
values = c("#DC493A", "#1282A2","#949494"),
labels = c("Nomes Femininos", "Nomes Masculinos",
"Outros")) +
coord_equal() +
theme_void()+
labs(title = "Nomes de espaços públicos por gênero - Porto (Portugal) ") +
theme(plot.title = element_text(size = 28,face="bold"),
legend.text=element_text(size=19)) +
annotate("text", x = 3, y = 1, label =" 913 (5%) ",color="white",
size=5) +
annotate("text", x = 5, y = 3, label = " 913 (44%) ",color="white",
size=5,halign="left")+
annotate("text", x = 5, y = 8, label = " 1073 (51%) ",color="white",
size=5,halign="left") +
theme_enhance_waffle()
ggsave(plot,filename = "test.png", type = "cairo", width = 90,
height = 90, dpi = 300,units = "mm")
#saveRDS(xdf,"xdf.rds")
#xdf=readRDS("C:\\Users\\rafae\\OneDrive\\Área de Trabalho\\xdf.rds")
plot2 = ggplot(xdf, aes(label = sexoFinal2, values = prop)) +
geom_pictogram(n_rows = 10, make_proportional = TRUE,
aes(color=sexoFinal2),flip=T,size=14) +
scale_color_manual(
name = NULL,
values = c("#DC493A", "#1282A2","#949494"),
labels = c("Nomes Femininos", "Nomes Masculinos", "Outros")
) +
scale_label_pictogram(
name = NULL,
values = c(
Masc = "tree",
Fem = "tree",
Outros = "tree"
),
labels=c("Nomes Femininos", "Nomes Masculinos", "Outros")
) +
coord_equal() +
theme_void()+
labs(title = "Nomes de praças e parques públicos por gênero") +
theme(plot.title = element_text(size = 26,face="bold"),
legend.text=element_text(size=19),
legend.position = "none")+
theme_enhance_waffle() +
annotate("text", x = 2, y = 0.4, label ="5 (4%)",color="black",
size=6)+
annotate("text", x = 10.8, y = 3, label ="41 (31%)",color="black",
size=6)+
annotate("text", x = 10.8, y = 8, label ="88 (66%)",color="black",
size=6)
ggsave(plot2,filename = "test2.png", type = "cairo", width = 120,
height = 90, dpi = 300,units = "mm")
sexos %>% mutate(sexoFinal2 = case_when(is.na(sexoFinal2)~"Outros nomes",
sexoFinal2=="Female"~"Nomes Femininos",
sexoFinal2=="Male"~"Nomes Masculinos"
)) %>% filter(!str_detect(sexoFinal2,"Outros")) %>%
mutate(prop = round(n/sum(n),2)*100) %>%
ggplot(aes(fill = sexoFinal2, values = prop)) +
geom_waffle(n_rows = 10, size = 1.3, colour = "white",flip=T) +
scale_fill_manual(name = NULL,
values = c("#DC493A", "#1282A2","#648767"),
labels = c("Femininos", "Masculinos", "Outros")) +
coord_equal() +
theme_void()+
theme_enhance_waffle()
# sexos %>% mutate(sexoFinal2 = case_when(is.na(sexoFinal2)~"Outros nomes",
# sexoFinal2=="Female"~"Nomes Femininos",
# sexoFinal2=="Male"~"Nomes Masculinos"
# )) %>% mutate(prop = round(n/sum(n),2)*100) %>%
sexos = gardens3 %>% filter(name %in% c(parques$rua,pracas$rua)) %>% distinct(name) %>%
left_join(parques %>% bind_rows(pracas),by=c("name"="rua")) %>%
bind_rows(ruasfinal) %>%
filter(rua %in% c(ruasintersec$name,intersecParque$name,intersecPraca$name)) %>%
count(rua,sexoFinal2) %>%
count(sexoFinal2)
sexos %>% mutate(sexoFinal2 = case_when(is.na(sexoFinal2)~"Outros nomes",
sexoFinal2=="Female"~"Nomes Femininos",
sexoFinal2=="Male"~"Nomes Masculinos"
)) %>% filter(!str_detect(sexoFinal2,"Outros")) %>% mutate(prop = round(n/sum(n),2)*100) %>%
ggplot(aes(label = sexoFinal2, values = prop)) +
geom_pictogram(n_rows = 10, make_proportional = TRUE,aes(color=sexoFinal2),
show.legend = F) +
scale_color_manual(
name = NULL,
values = c("#DC493A", "#1282A2","#648767"),
labels = c("Nomes Femininos", "Nomes Masculinos", "Outros")
) +
scale_label_pictogram(
name = NULL,
values = c(
Masc = "user",
Fem = "user",
Outros = "user"
),
labels=c("Nomes Femininos", "Nomes Masculinos", "Outros")
) +
coord_equal() +
hrbrthemes::theme_ipsum_rc(grid="") +
theme_enhance_waffle() +
theme(legend.key.height = unit(2.25, "line")) +
theme(legend.text = element_text(size = 10, hjust = 0, vjust = 0.75))