agridat (version 1.23)

wallace.iowaland: Iowa farmland values by county in 1925

Description

Iowa farmland values by county in 1925

Usage

data("wallace.iowaland")

Format

A data frame with 99 observations on the following 10 variables.

county

county factor, 99 levels

fips

FIPS code (state+county)

lat

latitude

long

longitude

yield

average corn yield per acre (bu)

corn

percent of land in corn

grain

percent of land in small grains

untillable

percent of land untillable

fedval

land value (excluding buildings) per acre, 1925 federal census

stval

land value (excluding buildings) per acre, 1925 state census

Details

None.

References

Larry Winner. Spatial Data Analysis. https://www.stat.ufl.edu/~winner/data/iowaland.txt

Examples

library(agridat)
data(wallace.iowaland)
dat <- wallace.iowaland

# Interesting trends involving latitude
libs(lattice)
splom(~dat[,-c(1:2)], type=c('p','smooth'), lwd=2, main="wallace.iowaland")

# Means. Similar to Wallace table 1
apply(dat[, c('yield','corn','grain','untillable','fedval')], 2, mean)

# Correlations.  Similar to Wallace table 2
round(cor(dat[, c('yield','corn','grain','untillable','fedval')]),2)

m1 <- lm(fedval ~ yield + corn + grain + untillable, dat)
summary(m1) # estimates similar to Wallace, top of p. 389

# Choropleth map
libs(maps)
data(county.fips)
dat <- transform(dat, polnm = paste0('iowa,',county)) # polnm example: iowa,adair

libs("latticeExtra") # for mapplot
redblue <- colorRampPalette(c("firebrick", "lightgray", "#375997"))
mapplot(polnm~fedval , data=dat, colramp=redblue,
        main="wallace.iowaland - Federal land values",
        xlab="Land value, dollars per acre",
        scales=list(draw=FALSE),
        map=map('county', 'iowa', plot=FALSE,
          fill=TRUE, projection="mercator"))