I have a shapefile with tons of different polygons representing different bodies of water (lakes, rivers etc.)
I would like to create a map of certain polygons. All of the current examples I could find only show how to plot shapefiles with ONLY the polygons wanted in them. So I am not sure how to only plot the specific polygons.
Link to the shapefile: https://hub.arcgis.com/datasets/esri::usa-detailed-water-bodies/explore?location=45.461044%2C-84.374110%2C10.71
I would like to plot OBJECTID295061, 295018, and 295017
Current code:
library(sf)
shp = st_read("USA_Detailed_Water_Bodies.shp")
ggplot(data = shp) +
geom_sf()+
coord_sf()+
theme_bw()
Current map:
Assuming OBJECTID is a numeric column of your data:
library(sf)
shp = st_read("USA_Detailed_Water_Bodies.shp")
Then you can make an "area of interest" subset like this:
aoi = shp[shp$OBJECTID %in% c(295061, 295018, 295017),]
Then make your plot using aoi.
If the OBJECTID numbers are the same as the row numbers you can select by row:
aoi = shp[c(295061, 295018, 295017),]
but I'm not sure because no time for a 250Mb download right now but I think this is correct.
Spatial dataframes from sf behave mostly like regular data frames, with a few weird exceptions. But for selecting rows and columns its not very different.
Related
I have a point shapefile with cities (CitiesPoints), and a dataframe that assigns a number of libraries to some of those cities (df; the data is fictitious). I also have a polygon shapefile for the background.
I joined those files to create a map in which a point is generated for each city that has libraries, and the size of the point is determined by the number of libraries it has.
df$CityCode <- as.factor(df$CityCode)
Joint <- CitiesPoints %>%
left_join(df, by=c("link"="CityCode"))
tmap_mode("view")
tm_shape(Background) +
tm_borders() +
tm_shape(Joint) + tm_symbols(id = "localidad",
size = "BIBLIO",
col = "brown1")
However, when I hover over those points with the mouse, the city name shown is incorrect.
Apparently, the top rows in the shape file (including those with no libraries, NA) are the ones being used to assign the labels.
Example
The correct label for this point should be “Rafaela”.
You can download the files I used here: Files
I would really appreciate the help!
I found a way to fix it. I created a new shapefile only containing the rows corresponding to the citys which have libraries.
Joint$BIBLIO[is.na(Joint$BIBLIO)] <- 0
JOINT2 = filter(Joint,BIBLIO>0)
Using this new shapefile, the automatic labels shown are now correct.
I have a map of Russia with regional subdivision
library(raster)
data <- getData('GADM', country='RUS', level=1)
http://www.gks.ru/bgd/regl/B16_14p/IssWWW.exe/Stg/d01/08-01.doc
The link is to a Word.doc with data (table) on crime rates for Russian regions. I can extract this data and use it in R. I want to take 2015 year and colorize regions on the map depending on the crime rate (also add a legend). How can I do this? The problem is that names of regions are sometimes different in the shape file (NL_NAME_1) and in the data from www.gks.ru.
I also have this code for graph that I need, except that here we have meaningless colors:
library(sp)
library(RColorBrewer)
data$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 working on a shape file and like to highlight some of the boundaries (borders) of the regions (as figure 1):
Figure 1: some but not all of the regions (borders) of the shape file are highlighted
(Source: https://dl.dropboxusercontent.com/u/48721006/highlighted.png)
The highlighting is achieved with ArcMap. I can't figure out how to do the same with R (particularly with the spplot()). Any suggestions on this?
To get the shape file
library(sp)
library(maptools)
con <- url("http://gadm.org/data/rda/ZAF_adm2.RData")
print(load(con))
close(con)
plot(gadm)
Many thanks!
G
What I would do: (1) plot the complete set; (2) take a subset; (3) plot the subset with a different line type. For subsetting shape files, check this question.
plot(gadm)
# check class and structure of the data
class(gadm)
head(gadm#data)
# take a subset based on ID_2
some_polygons = subset(gadm,ID_2>=38840 & ID_2<38850)
plot(some_polygons, add=T, border='cyan', lwd=2)
Hello, I am new to GIS with R and have been trying to create a choropleth map. I successfully created a choropleth map with ggplot2 and the fortify function, but it is not that easy to add more layers on the top of a map with ggplot2. Instead I am using maptools to plot a choropleth map and later add more layers as needed for my analysis.
The choropleth map I am trying to plot is the level of unemployment for Allegheny county by census tract. the files are available here:
shapefile https://www.dropbox.com/s/uci5g2ekeq9niww/census%20tract%20allegheyny%202010.shp
csv file https://www.dropbox.com/s/6nq8nnxftot8iya/allegheyny%20socioeconomic%20info.csv
And here is my code
library(rgdal)
library(RArcInfo)
library(RColorBrewer)
library(maptools)
library(maps)
library(classInt)
we load the csv file, clean it and create a subset with Id2 and unemployment
data<- read.csv('allegheyny socioeconomic info.csv',dec='.',
header=T)
data$Id2<-as.numeric(as.character(data$Id2))
data$Percent.Unemployed<-as.numeric(as.character(data$Percent.Unemployed))
names(data)[names(data)=="Percent.Unemployed"]<-'unemployed'
data1<-subset(data, select= c('Id2', 'unemployed'))
load shapefile of Allegheny County census tracts for 2010
tracts<-readShapePoly("census tract allegheyny 2010.shp")
names(tracts)[names(tracts)=="GEOID10"]<-'Id2'
merge the data by Id2
tr1<-merge(data1,tracts)
sort(tr1$Id2)
colours<-brewer.pal(5, 'Greens')
breaks<- classIntervals(tr1$unemployed, n=5, style='sd')
plot(tr1, col=colours[findInterval(tr1$unemployed, breaks, all.inside=T), axes=F])
And this is the message I get:
Error in x[-1L] >= x[-n] : comparison of these types is not implemented
plot(tracts,col=colours[findInterval(tr1$unemployed, breaks$brks, all.inside=T)])
Produces this:
To answer your question specifically:
The reason for the error is that findInteerval(...) takes as its second argument a vector of numeric. But
breaks<- classIntervals(tr1$unemployed, n=5, style='sd')
produces a list with two elements: 'var' and 'brks'. You need to use breaks$brks in findInterval(...).
Your statement
plot(tr1, col=colours[findInterval(tr1$unemployed, breaks, all.inside=T), axes=F])
attempts to plot tr1, which is not a map, it's a data frame with 402 rows. You need to plot(tracts,...)
Finally, why do you believe it is difficult to add layers in ggplot??