How can I create lattice chart using spplot() when data are arranged in rows, e.g. there are more values for every region (I have unemployment rate unemp
for many years (year
) for regions CSO_NAME)
?
This is my code to load map and merge data:
library(rgdal)
library(sqldf)
# Import map and assign data.shape@data to spdata
data.shape<-readOGR(dsn="folder",layer="mylayer")
spdata <- data.shape@data
# Load statistics data
unemp <- read.csv("cso_unemployment_rwise.csv")
# Merge data with spdata
spdata <- sqldf("select sp.*, cu.year, cu.unemp from spdata sp join unemp cu on (sp.nazok_a = cu.CSO_NAME) ")
# Build new spdata
spdata_merged <- SpatialPolygonsDataFrame(data.shape, spdata)
# This fails: length(Sr@polygons) == nrow(data) is not TRUE
I thought I can use something similar as formula
, e.g. like this example for barchart:
barchart(spdata$year~spdata$unemp|spdata$CSO_NAME)
But because I can't merge data with polygons I do not know what should be the next step. I can transpose data easily in this case and then use something like:
spplot(spdata,c("y2009","y2010","y2011","y2012",...))
Reproducible Example
Here are sample data, stats_data
with only one grouping variable year
and stats_data2
with two grouping variables year
and sex
# Get map
con <- url("http://gadm.org/data/rda/CZE_adm2.RData")
print(load(con))
close(con)
gadm_data <- gadm@data
# Create sample Data
stats_data <-
data.frame(
as.character(rep(gadm_data$NAME_2,3)),
as.numeric(round(runif(3*length(gadm_data$NAME_2), 0, 1),digits=3)*100),
as.factor(rep(c(2010,2011,2012),length(gadm_data$NAME_2)))
)
names(stats_data) <- c("NAME_2","UNEMPR","YEAR") # str(stats_data)
# Add each year to map data
library("sqldf")
gadm_data <- sqldf("select gd.*, sd.UNEMPR as u2010 from gadm_data gd join stats_data sd using (NAME_2) where year = 2010")
gadm_data <- sqldf("select gd.*, sd.UNEMPR as u2011 from gadm_data gd join stats_data sd using (NAME_2) where year = 2011")
gadm_data <- sqldf("select gd.*, sd.UNEMPR as u2012 from gadm_data gd join stats_data sd using (NAME_2) where year = 2012")
gadm@data <- gadm_data
# Plot
spplot(gadm,c("u2010","u2011","u2012"),at=c(0,10,20,30,40,50,70,100))
# Create sample Data, two factor variables
stats_data2 <-
data.frame(
as.character(rep(gadm_data$NAME_2,6)),
as.numeric(round(runif(6*length(gadm_data$NAME_2), 0, 1),digits=3)*100),
as.factor(rep(c(2010,2011,2012),2*length(gadm_data$NAME_2))),
as.factor(c("f","m"))
)
names(stats_data2) <- c("NAME_2","UNEMPR","YEAR","SEX") # str(stats_data2)
I can do the ugly data manipulation using sqldf
, but this gets more and more complicated with more factors added. Suppose I have 2 factors with 2 and 10 values then I have to add 20 columns.
R version 2.15.1, Windows XP, SP3