nebraska.farmincome {agridat} | R Documentation

## Nebraska farm income in 2007 by county

### Description

Nebraska farm income in 2007 by county

### Format

A data frame with 93 observations on the following 4 variables.

`county`

  county

`crop`

  crop income, thousand dollars

`animal`

  livestock and poultry income, thousand dollars

`area`

  area of each county, square miles

### Details

The variables for each county are:

Value of farm products sold - crops (NAICS) 2007 (adjusted)

Value of farm products sold - livestock, 2007 (adjusted).

Area in square miles.

Note: Cuming county is a very important beef-producing county. Some counties are not reported to protect privacy. Western Nebraska is dryer and has lower income. South-central Nebraska is irrigated and has higher crop income per square mile.

### Source

U.S. Department of Agriculture-National Agriculture Statistics Service. http://censtats.census.gov/usa/usa.shtml

### Examples

    data(nebraska.farmincome)
    dat <- nebraska.farmincome

    if(require("maps") & require("mapproj") & require("latticeExtra")) {
      # latticeExtra for mapplot

      dat$stco <- paste0('nebraska,', dat$county)
      # Scale to million dollars per county
      dat <- transform(dat, crop=crop/1000, animal=animal/1000)

      # Raw, county-wide incomes.  Note the outlier Cuming county
      redblue <- colorRampPalette(c("firebrick", "lightgray", "#375997"))
      mapplot(stco ~ crop + animal, data = dat, colramp=redblue,
              main="nebraska.farmincome",
              xlab="Farm income from animals and crops (million $ per county)",
              scales = list(draw = FALSE),
              map = map('county', 'nebraska', plot = FALSE, fill = TRUE,
                projection = "mercator") )

      # Now scale to income/mile^2
      dat <- within(dat, {
        crop.rate <- crop/area
        animal.rate <- animal/area
      })
      # And use manual breakpoints.
      mapplot(stco ~ crop.rate + animal.rate, data = dat, colramp=redblue,
              main="nebraska.farmincome: income per square mile (percentile breaks)",
              xlab="Farm income (million $ / mi^2) from animals and crops",
              scales = list(draw = FALSE),
              map = map('county', 'nebraska', plot = FALSE, fill = TRUE,
                projection = "mercator"),
              # Percentile break points
              # breaks=quantile(c(dat$crop.rate, dat$animal.rate),
              #                 c(0,.1,.2,.4,.6,.8,.9,1), na.rm=TRUE)
              # Fisher-Jenks breakpoints via classInt package
              # breaks=classIntervals(na.omit(c(dat$crop.rate, dat$animal.rate)),
              #                       n=7, style='fisher')$brks
              breaks=c(0,.049, .108, .178, .230, .519, .958, 1.31))
    }

[Package agridat version 1.16 Index]