I am trying to create an interactive map of Germany with plotly and ggplot. At last, I'd like to overlay geom_points with tooltips, but so far I am struggeling with the aspect ratio.
I create the plot like this:
library(tidyverse)
library(ggplot2)
library(plotly)
p <- map_data("world") %>%
filter(region=="Germany") %>%
ggplot(aes(x=long, y = lat, group = group)) +
geom_polygon(fill="grey") +
coord_map()
When simply plotting it with ggplot, the aspect ratio of Germany is how I know it from school.
p
When converting it to a plotly plot with ggplotly the plot is distorted.
ggplotly(p)
Any ideas how to fix it? I don't know whether this is relevant, but I used to run this code in an R Markdown document.
Thanks a lot.
I'll guess you can't get a decent level of detail from the world map you used. With maps there are basically two types: generic, and, GIS (real mapping data).
Below is a non-distorted map of Germany. Here are the steps and data sources.
Download the GIS data - map of Germany. Source, https://gadm.org/download_country_v3.html
Choose the level of detail. 0 - the outline of the country, 1 - the country w/states. These files will have, sp.rds , extensions.
Cut and Paste the downloaded geographical reference data file into your working directory - this is easier than creating a path from the working directory to some other folder location. Since this data is actual geospatial data used in creating this plot of Germany, this data/plot can be used as a base map or overlay map with google maps, Overstreet maps, etc..
Use the following libraries and two lines of code to create the plot of Germany.
library(maptools)
library(raster)
library(rgdal)
gadm <- readRDS("gadm36_DEU_0_sp.rds") # get the gis file from w/d.
plot(gadm)
Is there an easy way to convert a Spatial Lines into a Spatial Polygon object within R?
Reproducible Example
I have put together a reusable dataset here, which is downloaded from OpenStreetMaps through the overpass package. This extracts the locations of a few airports in South England:
devtools::install_github("hrbrmstr/overpass")
library(overpass)
library(raster)
library(sp)
# Write Query
query_airport <- '
(node["aeroway"="aerodrome"](50.8, -1.6,51.1, -1.1);
way["aeroway"="aerodrome"](50.8, -1.6,51.1, -1.1);
relation["aeroway"="aerodrome"](50.8, -1.6,51.1, -1.1);
);
out body;
>;
out skel qt;
'
# Run query
shp_airports <- overpass::overpass_query(query_airport, quiet = TRUE)
crs(shp_airports) <- CRS("+init=epsg:4326") # Add coordinates
shp_airports <- shp_airports[,1]
# Plot Results
plot(shp_airports, axes = T)
However, the data is of the class "SpatialLinesDataFrame". This really messes things up if you want to do any form of spatial joins or intersections, as it only acknowledges the edge of the region.
Potential Leads
I was exploring the use of SpatialLines2PolySet within the maptools package, but in my time exploring I produced nothing but error codes, so I didn't think there would be any worth including these within the question. There is some guidance about these functions here: https://rdrr.io/rforge/maptools/man/SpatialLines2PolySet.html
Notes
I have searched the web and SO to see find similar questions and struggled to find any questions directly referring to this. A lot seem to reference converting SpatialPoints -> SpatialLineDataFrames , but not SpatialLineDataFrames -> SpatialPolygonDataFrames. This question is similar but lacks any answers (or a reproducible dataset): Close a spatial line into a polygon using a shapefile
In addition, it seems strange that this would be difficult as it is something which can be done so easily in ArcGIS using the "Feature to Polygon" tool. This function requires no additional arguments specified and it works perfectly.
A way to solve the problem would be to use the library sf. After your query
library(sp)
library(raster)
library(sf)
sf_airports <- st_as_sf(shp_airports)
sf_airports_polygons <- st_polygonize(sf_airports)
shp_airports <- as(sf_airports_polygons, "Spatial") # If you want sp
class(shp_airports)
I have a shapefile, specifically, a SpatialPolygonsDataFrame, called cdtract. that contains one variable for each district called varcount. varcount is either "NA" or 1. When I do
plot(cdtract)
...I see the map printed out but I don't see the tracts that are '1' in varcount marked any differently from those that are 'NA.' I ideally want to have a spectrum of values in varcount and see those reflected in different colors. I considered using ggplot but according to this post here that is very resource intensive and it might be better to use plot() instead of ggplot() to create the choropleth. But I'm really not sure how to go about it. I am using a different shapefile from states/countries so am not sure that the choroplethr package is the way to go.
Can someone explain how to take a SpatialPolygonsDataFrame and turn it into a choropleth, efficiently? Thanks!
Shamefully taken from Ari's post on gis.stackexchange.com. See the link for pictures. There are more examples here.
library(sp)
Srs1 = Polygons(list(Polygon(cbind(c(2,4,4,1,2),c(2,3,5,4,2)))), "s1")
Srs2 = Polygons(list(Polygon(cbind(c(5,4,2,5),c(2,3,2,2)))), "s2")
SpDF <- SpatialPolygonsDataFrame( SpatialPolygons(list(Srs1,Srs2)),
data.frame(z=1:2, row.names=c("s1","s2") ) )
spplot(SpDF, zcol="z")
How to convert from shape into polygon in R? There was shape2poly(shapefiles) but this function have been removed, are shapefiles, maptools, spdep still packages for handling maps in R?
I tend to use the OGR stuff, as it lets me work with data from a range of sources (geodatabases, kml, etc).
library(rgdal)
mylayer <- readOGR(dsn="/path/to/folder/containing/shapefile",
layer="shapefilename-minus-dot-shp")
There are clearly a number of packages in R for all sorts of spatial analysis. That can by seen in the CRAN Task View: Analysis of Spatial Data. These packages are numerous and diverse, but all I want to do is some simple thematic maps. I have data with county and state FIPS codes and I have ESRI shape files of county and state boundaries and the accompanying FIPS codes which allows joining with the data. The shape files could be easily converted to other formats, if needed.
So what's the most straight forward way to create thematic maps with R?
This map looks like it was created with an ESRI Arc product, but this is the type of thing I would like to do with R:
alt text http://www.infousagov.com/images/choro.jpg Map copied from here.
The following code has served me well. Customize it a little and you are done.
(source: eduardoleoni.com)
library(maptools)
substitute your shapefiles here
state.map <- readShapeSpatial("BRASIL.shp")
counties.map <- readShapeSpatial("55mu2500gsd.shp")
## this is the variable we will be plotting
counties.map#data$noise <- rnorm(nrow(counties.map#data))
heatmap function
plot.heat <- function(counties.map,state.map,z,title=NULL,breaks=NULL,reverse=FALSE,cex.legend=1,bw=.2,col.vec=NULL,plot.legend=TRUE) {
##Break down the value variable
if (is.null(breaks)) {
breaks=
seq(
floor(min(counties.map#data[,z],na.rm=TRUE)*10)/10
,
ceiling(max(counties.map#data[,z],na.rm=TRUE)*10)/10
,.1)
}
counties.map#data$zCat <- cut(counties.map#data[,z],breaks,include.lowest=TRUE)
cutpoints <- levels(counties.map#data$zCat)
if (is.null(col.vec)) col.vec <- heat.colors(length(levels(counties.map#data$zCat)))
if (reverse) {
cutpointsColors <- rev(col.vec)
} else {
cutpointsColors <- col.vec
}
levels(counties.map#data$zCat) <- cutpointsColors
plot(counties.map,border=gray(.8), lwd=bw,axes = FALSE, las = 1,col=as.character(counties.map#data$zCat))
if (!is.null(state.map)) {
plot(state.map,add=TRUE,lwd=1)
}
##with(counties.map.c,text(x,y,name,cex=0.75))
if (plot.legend) legend("bottomleft", cutpoints, fill = cutpointsColors,bty="n",title=title,cex=cex.legend)
##title("Cartogram")
}
plot it
plot.heat(counties.map,state.map,z="noise",breaks=c(-Inf,-2,-1,0,1,2,Inf))
Thought I would add some new information here since there has been some activity around this topic since the posting. Here are two great links to "Choropleth Map R Challenge" on the Revolutions blog:
Choropleth Map R Challenge
Choropleth Challenge Results
Hopefully these are useful for people viewing this question.
All the best,
Jay
Check out the packages
library(sp)
library(rgdal)
which are nice for geodata, and
library(RColorBrewer)
is useful for colouring. This map is made with the above packages and this code:
VegMap <- readOGR(".", "VegMapFile")
Veg9<-brewer.pal(9,'Set2')
spplot(VegMap, "Veg", col.regions=Veg9,
+at=c(0.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5),
+main='Vegetation map')
"VegMapFile" is a shapefile and "Veg" is the variable displayed. Can probably be done better with a little work. I don`t seem to be allowed to upload image, here is an link to the image:
Take a look at the PBSmapping package (see borh the vignette/manual and the demo) and
this O'Reilly Data Mashups in R article (unfortunately it is not free of charge but it worth 4.99$ to download, according Revolutions blog ).
It is just three lines!
library(maps);
colors = floor(runif(63)*657);
map("state", col = colors, fill = T, resolution = 0)
Done!!
Just change the second line to any vector of 63 elements (each element between 0 and 657, which are members of colors())
Now if you want to get fancy you can write:
library(maps);
library(mapproj);
colors = floor(runif(63)*657);
map("state", col = colors, fill = T, projection = "polyconic", resolution = 0);
The 63 elements represent the 63 regions whose names you can get by running:
map("state")$names;
The R Graphics Gallery has a very similar map which should make for a good starting point. The code is here: www.ai.rug.nl/~hedderik/R/US2004 . You'd need to add a legend with the legend() function.
If you stumble upon this question in the 2020ies, use the magnificent tmap package. It's very simple and straightforward and revolutionized making maps in R. Do not bother to investigate this complicated code.
Check the vignette here.