I'm trying to reproduce a code to display polygons in a map in another computer, however, in one computer the polygons are not shown. Does someone had this kind of problem while sharing code?
You can download the shapefile from here: http://www.conabio.gob.mx/informacion/metadata/gis/muni_2012gw.xml?_xsl=/db/metadata/xsl/fgdc_html.xsl&_indent=no
library(rgdal)
library(rgeos)
library(leaflet)
Mex <- readOGR(dsn="C:/DISCO D", layer="Muni_2012gw")
Mex_sub <- Mex[Mex$CVE_ENT=="01",]
bins <- quantile(Mex_sub#data$OID_1, c(0,.125,.25, .5, .75,.875, 1))
pal <- colorBin("YlOrRd", domain = Mex_sub#data$OID_1, bins = (bins),
na.color = "grey40", reverse = FALSE)
centr <- gCentroid(Mex_sub)#coords
leaflet(Mex_sub, options = leafletOptions(minZoom = 4, maxZoom = 15)) %>%
addTiles() %>%
setView(centr[1], centr[2], zoom = 8) %>%
addPolygons(data=Mex_sub, weight = 1,fill = ~OID_1, fillColor = ~pal(OID_1),
opacity=1, fillOpacity = 0.5, color=grey(0.5))
Related
I'm trying to create a choropleth map in county level using leaflet R package and I actually do it. But when I check my data file and the hover text of any county I find that the values are not correct. For example check the Conejos county. Any explanation? Or a better way to process tha data and create this map without the mismatches?
Code:
library(raster)
library(leaflet)
library(tidyverse)
# Get USA polygon data
USA <- getData("GADM", country = "usa", level = 2)
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE) %>%
dplyr::select(COUNTY_NAME, Avg_yield)
### Check counties that exist in USA, but not in mydata
### Create a dummy data frame and bind it with mydata
mydata <- data.frame(COUNTY_NAME = setdiff(USA$NAME_2, mydata$COUNTY_NAME),
Avg_yield = NA,
stringsAsFactors = FALSE) %>%
bind_rows(mydata)
### Create a color palette
mypal <- colorNumeric(palette = "viridis", domain = mydata$Avg_yield)
leaflet() %>%
addProviderTiles("OpenStreetMap.Mapnik") %>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(data = USA, stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.3,
fillColor = ~mypal(mydata$Avg_yield),
popup = paste("Region: ", USA$NAME_2, "<br>",
"Avg_yield: ", mydata$Avg_yield, "<br>")) %>%
addLegend(position = "bottomleft", pal = mypal, values = mydata$Avg_yield,
title = "Avg_yield",
opacity = 1)
With the code below I get my dataframe with US county data
library(raster)
library(leaflet)
library(tidyverse)
# Get USA polygon data
USA <- getData("GADM", country = "usa", level = 2)
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE)
My object is to crate an interactive leaflet choropleth map of Avg_yield so first I fortify my USA polygon data
library(rgeos)
library(maptools)
library(ggplot2)
states.shp.f <- fortify(USA, region = "NAME_2")
Then I subset my dataset and merge it with the fortified:
mydata2<-mydata[,c("COUNTY_NAME","Avg_yield")]
colnames(mydata2)[1]<-"id"
## merge shape file with data
merge.shp.coef <- merge(states.shp.f, mydata2, by = "id")
but now I have a dataset with every county name many times and also some counties have different values of Avg_yield. Whats the proper way to process those data in order to use the leaflet code like:
leaflet() %>%
addProviderTiles("OpenStreetMap.Mapnik") %>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(data = USA, stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.3,
fillColor = ~mypal(mydata$Avg_yield),
popup = paste("Region: ", USA$NAME_2, "<br>",
"Avg_yield: ", mydata$Avg_yield, "<br>")) %>%
addLegend(position = "bottomleft", pal = mypal, values = mydata$Avg_yield,
title = "Avg_yield",
opacity = 1)
The propoer way to do this is to transform your polygon object into a sf object
with st_as_sf()
Here you have a working example :
(I did used some other data for the polygon, I thought yours too precise and require a lot of resources, plus I made it work with shiny)
library(leaflet)
library(tidyverse)
library(ggplot2)
library(sf)
library(shiny)
USA <- st_read(dsn = '[your path]/cb_2018_us_county_500k.shp')
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE)
states_sf <- st_as_sf(USA)
mydata2<-mydata[,c("COUNTY_NAME","Avg_yield")]
colnames(mydata2)[1]<-"NAME"
## merge shape file with data
states_sf_coef <- left_join(states_sf, mydata2, by = "NAME")
ui <- fluidPage(
leafletOutput("map", height = "100vh")
)
server <- function(input, output, session) {
bins <- c(0, 5, 10, 15, 20, 25, 30, 35, 40)
mypal <- colorBin("YlOrRd", domain = states_sf_coef$Avg_yield, bins = bins)
#Sortie map
output$map <- renderLeaflet({
leaflet()%>%
addProviderTiles("OpenStreetMap.Mapnik")%>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(
data = states_sf_coef,
fillColor = ~mypal(states_sf_coef$Avg_yield),
stroke = FALSE,
smoothFactor = 0.2,
fillOpacity = 0.3,
popup = paste("Region: ", states_sf_coef$NAME_2, "<br>",
"Avg_yield: ", states_sf_coef$Avg_yield, "<br>"))%>%
addLegend(position = "bottomleft",
pal = mypal,
values = states_sf_coef$Avg_yield,
title = "Avg_yield",
opacity = 1)
})
}
# Create Shiny app ----
shinyApp(ui = ui, server = server)
I am working with the leaflet R package. I have a zoning system made of polygons and I'd like to lay their IDs on top of them. Below is an illustration (with another software) of my objective.
Thanks for your suggestions!
Since there is no reproducible data, I decided to use one of my previous posts related to leaflet. There are two things you want to take away from this post: 1) you need to create a data frame containing center points of target regions, 2) you need to use addLabelOnlyMarkers(). You can achieve the first thing using gCentroid(). I added row names of the polygon data set (UK) as character to centers. This is used for labeling. You need to think what labels you use in your own case. Once this data set is ready, you want to use it in addLabelOnlyMarkers().
library(raster)
library(rgeos)
library(leaflet)
# Get UK polygon data
UK <- getData("GADM", country = "GB", level = 2)
# Find a center point for each region
centers <- data.frame(gCentroid(UK, byid = TRUE))
centers$region <- row.names(UK)
### Create dummy data
set.seed(111)
mydf <- data.frame(place = unique(UK$NAME_2),
value = sample.int(n = 1000, size = n_distinct(UK$NAME_2), replace = TRUE))
### Create five colors for fill
mypal <- colorQuantile(palette = "RdYlBu", domain = mydf$value, n = 5, reverse = TRUE)
leaflet() %>%
addProviderTiles("OpenStreetMap.Mapnik") %>%
setView(lat = 55, lng = -3, zoom = 6) %>%
addPolygons(data = UK,
stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.3,
fillColor = ~mypal(mydf$value),
popup = paste("Region: ", UK$NAME_2, "<br>",
"Value: ", mydf$value, "<br>")) %>%
addLabelOnlyMarkers(data = centers,
lng = ~x, lat = ~y, label = ~region,
labelOptions = labelOptions(noHide = TRUE, direction = 'top', textOnly = TRUE)) %>%
addLegend(position = "bottomright", pal = mypal, values = mydf$value,
title = "UK value",
opacity = 0.3)
I'm trying to add multiple polygon to leaflet world map, according to a number of lists of country code. And I was trying to use R loop to add the polygon. Here's the code that I manually add polygons from list 1:
library(sp)
library(raster)
library(leaflet)
library(maps)
library(tidyverse)
countries_1 <- c('PAK','TUR','BGR')
adm1 <- getData('GADM', country='PAK', level=0)
adm2 <- getData('GADM', country= 'TUR', level=0)
adm3 <- getData('GADM', country= 'BGR', level=0)
leaflet() %>%
addTiles() %>%
addPolygons(data=adm1, weight = 3, fillColor = 'purple', color = 'purple') %>%
addPolygons(data=adm2, weight = 3, fillColor = 'purple', color = 'purple') %>%
addPolygons(data=adm3, weight = 3, fillColor = 'purple', color = 'purple')
I am thinking using the loop to add multiple polygon layers so that for list_n:
countries_n <- ('ctry1','ctry2','ctry3',...'ctryn')
for (i in country_n) {
countries <- basemap %>% addPolygons(data=getData('GADM',country = i, level = 0),
weight = 3, fillColor = 'purple', color = 'purple')
}
The question is how can I embed the loop to "leflet() %>%" ?
*Note here:
If try to add multiple data in addPolygons(), it will plot only the first element in the data, in below case, only country 'PAK' will be ploted:
addPolygons(data=c('PAK','TUR'), weight = 3, fillColor = 'purple', color = 'purple')
Here's a solution using packages sf and mapview. Note that this is currently only possible using the develop version of mapview (see commented out devtools::install_github()
# devtools::install_github("r-spatial/mapview#develop")
library(sf)
library(mapview)
library(raster)
countries_1 <- c('PAK','TUR','BGR')
dat_list = lapply(countries_1, function(i) {
st_as_sf(getData("GADM", country = i, level = 0))
})
m = leaflet() %>% addTiles()
for (i in dat_list) {
m = mapview::addFeatures(map = m,
data = i,
weight = 3,
fillColor = 'purple',
color = 'purple')
}
m
Note that addFeatures is type agnostic, so any combination of points, lines and/or polygons will work here.
How do you set the layer order in R's leaflet package so that tiles show up on top of polygons filled with color?
Here's what I've got so far:
require(leaflet)
require(acs)
require(tigris)
require(rgdal)
census.income.end.year = 2015
county = 17
nd.counties=acs.fetch(geography=geo.make(state="ND", county=county),
table.number="B01003", endyear = 2015)
tracts <- tigris::tracts(state = 'ND', county = county, cb=FALSE, year = 2015)
# create a geographic set to grab tabular data (acs)
geo<-geo.make(state=c("ND"),
county = county,
tract="*")
# add in median income
median.income <- acs.fetch(endyear = census.income.end.year,
geography = geo,
variable = c("B19013_001"))
income_df <- data.frame(paste0(as.character(median.income#geography$state),
str_pad(as.character(median.income#geography$county), 3, 'left', '0'),
str_pad(as.character(median.income#geography$tract), 5, 'left', '0')),
median.income#estimate)
rownames(income_df)<-1:nrow(income_df)
names(income_df)<-c("GEOID", "hhincome")
income_merged <- geo_join(tracts, income_df, "GEOID", "GEOID")
income_merged <- spTransform(income_merged, CRS("+init=epsg:4326"))
qpal <- colorQuantile("plasma", income_df$hhincome, n = 4)
leaflet() %>%
setView( -96.7898, 46.8772, zoom=11) %>%
addPolygons(data = income_merged,
fillColor = qpal(income_merged$hhincome),
fillOpacity = 1,
weight = 0.3) %>%
addProviderTiles(providers$Hydda.RoadsAndLabels)
Ultimately, I'ld like to do this with addTiles (instead of addProviderTiles as in the above code) using a custom MapBox, but I can't figure out how to make that reproducible for this example... given that you need a key to access custom MapBox tiles (BTW, I've created a custom MapBox tile that should be transparent except for roads and labels, so the underlying polygons should "show thru.")
Here is one way to do add a tile on top of a circle with the non-R version of leaflet: http://jsfiddle.net/dcu9pz2w/, but I don't see how to make that work in my context. I think adding "panes" may be the way to go, but I don't see that functionality in R leaflet. Also, I explored z-index values, but that seemed to be a dead end.
Any help is much appreciated!
R leaflet now includes addMapPane function. The solution to this problem is to first set up pane order and then add tiles/polygons. Reproducible example:
library(leaflet)
library(geojsonio)
# get polygon data
# https://github.com/simonepri/geo-maps/blob/master/info/countries-land.md
world <- geojson_read(
"https://github.com/simonepri/geo-maps/releases/download/v0.6.0/countries-land-10km.geo.json",
what = "sp"
)
# generate random values
world#data$value <- runif(nrow(world#data))
# get color palette
color_pal <- colorNumeric(palette = "YlOrRd", domain = NULL)
# get leaflet map
leaflet() %>%
setView(lat = 50, lng = 15, zoom = 4) %>%
addMapPane("background_map", zIndex = 410) %>% # Level 1: bottom
addMapPane("polygons", zIndex = 420) %>% # Level 2: middle
addMapPane("labels", zIndex = 430) %>% # Level 3: top
addProviderTiles(
providers$Esri.WorldTerrain,
options = pathOptions(pane = "background_map")
) %>%
addPolygons(
data = world, stroke = FALSE, smoothFactor = 0.2,
fillOpacity = 0.6, fillColor = ~color_pal(value),
options = pathOptions(pane = "polygons")
) %>%
addProviderTiles(
providers$Stamen.TonerLabels,
options = pathOptions(pane = "labels")
)