I have produced a plot of zipcodes on a grid of longitude and latitude. However, I would like to add the outline for the state of Pennsylvania to this plot. I am not sure how to go about doing this. Here is the code I have so far:
library(tidyverse)
library(zipcode)
data(zipcode)
toplot <- merge(zipcode, nhmzipuse, sort = FALSE, by.x = "zip", by.y = "zip")
ggplot(toplot, aes(longitude, latitude)) + geom_point(aes(color=count))
Here is what my plot looks like currently:
I know that I need to somehow get data for the border of the state of Pennsylvania and merge it with my data, but I'm not sure how to go about doing that.
Any recommendations are much appreciated!
Related
I have a map of Russia with regional subdivision
library(raster)
data <- getData('GADM', country='RUS', level=1)
http://www.gks.ru/bgd/regl/B16_14p/IssWWW.exe/Stg/d01/08-01.doc
The link is to a Word.doc with data (table) on crime rates for Russian regions. I can extract this data and use it in R. I want to take 2015 year and colorize regions on the map depending on the crime rate (also add a legend). How can I do this? The problem is that names of regions are sometimes different in the shape file (NL_NAME_1) and in the data from www.gks.ru.
I also have this code for graph that I need, except that here we have meaningless colors:
library(sp)
library(RColorBrewer)
data$region <- as.factor(iconv(as.character(data$NAME_1)))
spplot(data, "region", xlim=c(15,190), ylim=c(40,83),
col.regions=colorRampPalette(brewer.pal(12, "Set3"))(85), col = "white")
If I understand your question properly, you just need to add your data to the spatial object for making colors meaningful.
Note, please, that the data is a reserved word in R. So, it's better to modify a little your variable name:
geo_data <- getData('GADM', country = 'RUS', level = 1)
Let's emulate some data to demonstrate a visualization strategy:
set.seed(23)
geo_data#data["data_to_plot"] <- sample(1:100, length(geo_data#data$NAME_1))
Using a default GADM projection would cut the most eastern part of the country. A simple transformation helps to fit the whole area to a plot:
# fit Russian area inside the plot
geo_data_trsf <- spTransform(geo_data, CRS("+proj=longlat +lon_wrap=180"))
Draw the map selecting data_to_plot instead of region:
max_data_val <- max(geo_data_trsf#data$data_to_plot)
spplot(geo_data_trsf, zcol = "data_to_plot",
col.regions = colorRampPalette(brewer.pal(12, "Set3"))(max_data_val),
col = "white")
The plot limits are adjusted automatically for the transformed spatial data geo_data_trsf, making possible to omit xlim and ylim.
As for the problem with the names, I can't provide any ready-to-use solution. Obviously, the regions' names of NL_NAME_1 need some additional treatment to use them as labels. I think, it would be better to use NAME_1 as an identifier in your code to ensure that it'll be no troubles with encoding. The NL_NAME_1 column is perfectly suitable to set the correspondence between your Word-data and the data inside the spatial object geo_data.
I'm having difficulty mapping gradient colors to some county-level population data I have using the base R package maps. I know that colors must be interpolated to the dataframe, but I'm not sure how that is then translated to the map. Here is the code I'm using:
library(dplyr)
require(maps)
my_fake_data <- data_frame(
county = sample(c('list','of','all','counties'),115,T),
county_population = sample(1:1000000,115,T))
grey_black <- colorRampPalette(c('grey50','black'))
map_data <- my_fake_data %>%
arrange(county_population) %>%
mutate(county_population_color = grey_black(nrow(.)))
map('county','missouri',interior = T,fill =T,
col = grey_black(map_data$county_population_color))
How do I tell R to map colors in the correct order? My sense tells me to attach my data to map's internal database, but I can't find the documentation to do it correctly - - or, more likely, I'm just wrong. Any help would be greatly appreciated.
To answer your question, you will need to access the county.fips data frame contained in the maps package. This will have the fips number and the state, county name. This list is in the correct order for mapping. The code example below extracts the Missouri counties and randomly colors a couple for verification:
mocounties<-county.fips[grepl('missouri', county.fips$polyname),]
mocounties$col<-"grey"
mocounties$col[5]<-"red"
mocounties$col[15]<-"green"
mocounties$col[115]<-"blue"
map('county','missouri', interior = T,fill =T,
col = mocounties$col)
I am attempting to plot profitability on top of counties in Minnesota, Iowa, and Nebraska. Using leaflet and tigris, I have been able to plot ALL counties, whether or not I have data for it. This leaves me with a few counties with colors and the rest labeled as NA. Is there a way for me to remove all NA's from my geo_join data so that it just isn't used ala unused Wisconsin areas? I have tried using fortify, but I can't figure out how to determine what county boundaries I'm looking at when I merge the TIGER boundary lines with my County FIPS file in order to remove them.
Here is what my leaflet currently looks like:
My code to get the map is this:
library(tigris)
library(leaflet)
pal <- colorNumeric(c("yellow","dark red"),county$Construction.Cost,na.color="white")
IA_counties <- counties(state="IA", cb=TRUE, resolution ="20m")
MN_counties <- counties(state="MN",cb=TRUE,resolution="20m")
NE_counties <- counties(state="NE",cb=TRUE,resolution="20m")
IA_merged <- geo_join(IA_counties,county,"GEOID", "GEOID")
MN_merged <- geo_join(MN_counties,county,"GEOID","GEOID")
NE_merged <- geo_join(NE_counties,county,"GEOID","GEOID")
popupIA <- paste0("County Projects: ", as.character(paste('$',formatC(format(round(IA_merged$Construction.Cost, 0), big.mark=',', format = 'f')))))
popupMN <- paste0("County Projects: ", as.character(paste('$',formatC(format(round(MN_merged$Construction.Cost, 0), big.mark=',', format = 'f')))))
popupNE <- paste0("County Projects: ", as.character(paste('$',formatC(format(round(NE_merged$Construction.Cost, 0), big.mark=',', format = 'f')))))
leaflet() %>%
addProviderTiles("MapQuestOpen.OSM") %>%
addLegend(pal = pal,
values = IA_merged$Construction.Cost,
position = "bottomright",
title = "County Projects",
labFormat=labelFormat(prefix="$")) %>%
addCircles(lng=yup2$lon, lat=yup2$lat,weight=.75,fillOpacity=0.01,color="red",
radius = 96560) %>%
addCircles(lng=yup2$lon, lat=yup2$lat,weight=.75,fillOpacity=0.01,color="blue",
radius = 193121) %>%
addPolygons(data = IA_counties,
fillColor = ~pal(IA_merged$Construction.Cost),
layerId=1,
fillOpacity = .25,
weight = 0.05,
popup = popupIA)%>%
addPolygons(data=MN_counties,
fillColor=~pal(MN_merged$Construction.Cost),
fillOpacity=0.25,
weight=0.05,
popup = popupMN) %>%
addPolygons(data=NE_counties,
fillColor=~pal(NE_merged$Construction.Cost),
fillOpacity=0.25,
weight=0.05,
popup = popupNE)
I apologize for not including reproducible data, but if needed, please ask. I'm hoping that this is more of a simple na.color= formula solution. The map looks "okay" as of now, but I'd like it if it's possible to not have to make the fillOpacity so light so the NA counties don't stand out.
Thanks for any and all help and please, let me know if you have any questions!
I'm the creator of the tigris package. Thanks so much for using it! In the development version of tigris on GitHub (https://github.com/walkerke/tigris), I've added an option to geo_join to accommodate inner joins, which would remove the unmatched data entirely from the resultant spatial data frame (if this is what you are looking for). You can also supply a common merge column name as a named argument to the new by parameter if you want. For example:
IA_merged <- geo_join(IA_counties, county, by = "GEOID", how = "inner")
should work. I'm still testing but I'll probably submit this update to CRAN in January.
So, embarrassingly, the answer to this question was as simple as I had hoped. I tweaked the following na.color code and it worked exactly as I wanted.
pal <- colorNumeric(c("yellow","dark red"),county$Construction.Cost,na.color="transparent")
I'm using the R code shown below, which loads libraries maps and RColorBrewer, to create a map of the world with countries color-coded by population rank. As you can see in the image below, I'm using a green palette in which the darker the green, the larger the population.
I'd like to add a continuous color legend showing the full palette to denote that light green = small population and dark green = large population, but I can't find a way to do it via maps. Could you tell me what is the easiest way to add a continuous color legend (or color key/color scale) to my map?
# Load libraries
library(maps)
library(RColorBrewer)
# Load world data
data(world.cities)
# Calculate world population by country
world.pop = aggregate(x=world.cities$pop, by=list(world.cities$country.etc),
FUN=sum)
world.pop = setNames(world.pop, c('Country', 'Population'))
# Create a color palette
palette = colorRampPalette(brewer.pal(n=9, name='Greens'))(nrow(world.pop))
# Sort the colors in the same order as the countries' populations
palette = palette[rank(-world.pop$Population)]
# Draw a map of the world
map(database='world', fill=T, col=palette, bg='light blue')
The world map in the maps package is about 30 years old (e.g., has USSR & Yugoslavia).
Plus you have a glitch in your code that causes the overpopulated Greenland that #Jealie noticed (and India is less populated than Antarctica).
You can create a continuousish legend with a modern world using rworldmap.
library(rworldmap)
library(RColorBrewer)
#get a coarse resolution map
sPDF <- getMap()
#using your green colours
mapDevice('x11') #create a map shaped device
numCats <- 100 #set number of categories to use
palette = colorRampPalette(brewer.pal(n=9, name='Greens'))(numCats)
mapCountryData(sPDF,
nameColumnToPlot="POP_EST",
catMethod="fixedWidth",
numCats=numCats,
colourPalette=palette)
You can alter the legend adding more labels etc. by doing something like this :
mapParams <- mapCountryData(sPDF, nameColumnToPlot="POP_EST", catMethod="pretty", numCats=100, colourPalette=palette, addLegend=FALSE)
#add a modified legend using the same initial parameters as mapCountryData
do.call( addMapLegend, c( mapParams
, legendLabels="all"
, legendWidth=0.5
))
Just briefly to explore the glitch in your code. It occurs because you create a palette for the number of countries in world.cities (239) and then apply it to the number of polygons in the world database from maps (2026). So it probably gets recycled and the colours of your countries have no relation to population. The code below demonstrates the source of your problem.
#find the countries used in the maps world map
mapCountries <- unique( map('world',namesonly=TRUE) )
length(mapCountries)
#[1] 2026
#exclude those containing ':' e.g. "USA:Alaska:Baranof Island"
mapCountries2 <- mapCountries[-grep(':',mapCountries)]
length(mapCountries2)
#[1] 186
#which don't match between the map and world.cities ?
#cityCountries <- unique( world.cities$country.etc )
cityCountries <- world.pop$Country
length(cityCountries)
#[1] 239
#which countries are in the map but not in world.cities ?
mapCountries2[ is.na(match(mapCountries2,cityCountries)) ]
#includes USSR, Yugoslavia & Czechoslovakia
Within the library SDMTools there is the function legend.gradient
adding this code to the end of your code should give the desired result:
# Draw a map of the world
map(database='world', fill=T, col=palette, bg='light blue')
x = c(-20, -15, -15, -20)
y = c(0, 60, 60, 0)
legend.gradient(cbind(x = x - 150, y = y - 30),
cols = brewer.pal(n=9, name='Greens'), title = "TITLE", limits = "")
You will need to fiddle with the x & y coordinates to get the legend into the desired location however.
EDIT
The x and y coordinates also adjust the shape of the box so I changed the code so that the box shape would not change if you only alter the numbers within the legend.gradient function. Below is what this code should produce
I am a total newbie to R and I would like to draw a line (possibly weighted, e.g., by the number of trips made) between two countries. Currently, I use longitude and latitude for each capital to draw a line, but I would like to do it using the package ggmap. I was looking around, but did not find any solution so far. I would appreciate a quick help.
require(ggmap)
require (rworldmap)
all_content = readLines("ext_lt_intratrd_1_Data.csv")
skip_second = all_content[-2]
dat = read.csv(textConnection(skip_second), header = TRUE, stringsAsFactors =F)
dat[5,2]<- c("Germany") # using a data where the first line is
header, but second line must be skipped as it is EU 27
and not a single country
europe <- read.csv("eulonglat.csv", header = TRUE) # using world capitals to
generate points
myfulldata <- merge(dat, europe)
map <- get_map(location = 'Europe', zoom = 4)
mapPoints <- ggmap(map) + geom_point(aes(x = UNc_longitude, y = UNc_latitude, size
= log(myfulldata$Value)), data = myfulldata, col = "red", alpha= 0.5) # this can
be plotted
# i would continue with drawing line and i searched for references
# i found arrows(42.66,23.34,50.82,4.47) - which did not work
# i tried to look for a reference work more, but could not find
# instead i found it using with the package rworldmap the following
lines(c(4.47, 23.32), c(50.82, 42.66))
# this does not work on ggmap