Incorrect plotting of data on Choropleth map with ggplot2 in R

fortify puts the polygons from the shapefile into something ggplot can plot, hence the 1,000+ rows. While you can attach values to the fortified polygons, it's not necessary.

So, you don't really have to go through all that trouble for the choropleth. Take a look at the following. I added in some extra bits to show which values get mapped to which RS:

library(rgdal)
library(ggplot2)
library(gridExtra)

egg <- read.table(text="RS  Tariff
01  -5.25
02  7.16
03  6.65
04  3.10
05  3.69
06  2.49
07  1.89
08  3.93
09  -5.84
10  -2.61
11  -0.21
12  2.35
13  -5.94
14  -7.54
15  -3.27
16  -8.75", header=TRUE, colClasses=c("character", "numeric"))

bundesl <- readOGR("vg2500_geo84/vg2500_bld.shp", "vg2500_bld")
bundesl@data<- bundesl@data[order(bundesl$RS, na.last=NA),]

# good projection for germany but if you intende to draw additional
# lines or points you'll have to project them before plotting so this
# may be more trouble than it's worth and you can just use 
# coord_map("mollweide") or something else that works for you besides mercator

bundesl <- spTransform(bundesl, CRS("+proj=utm +zone=33 +ellps=WGS84 +datum=WGS84 +units=m +no_defs "))

bundesl_map <- fortify(bundesl, region="RS")

# only doing this bit to plot the RS # at the center of each polygon
# totally not necessary for the choropleth

egg <- cbind(egg, data.frame(gCentroid(bundesl, byid=TRUE)))

gg <- ggplot()

# this bit ensures you have the outlines

gg <- gg + geom_map(data=bundesl_map, map=bundesl_map,
                    aes(x=long, y=lat, map_id=id),
                    color="#7f7f7f", size=0.15)

# this bit here does your choropleth

gg <- gg + geom_map(data=egg, map=bundesl_map,
                    aes(fill=Tariff, map_id=RS),
                    color="#7f7f7f", size=0.15)
gg <- gg + geom_text(data=egg, aes(x=x, y=y, label=RS), size=3)
gg <- gg + coord_equal() # we already projected it
gg <- gg + scale_fill_continuous(name=expression(Tariff), 
                                 low="red", high="green", space="Lab", 
                                 na.value="white", guide="colourbar")
gg <- gg + labs(x=NULL, y=NULL)

# decent map theme 

gg <- gg + theme_bw()
gg <- gg + theme(panel.grid=element_blank())
gg <- gg + theme(panel.border=element_blank())
gg <- gg + theme(axis.ticks=element_blank())
gg <- gg + theme(axis.text=element_blank())


gt <- tableGrob(cbind(bundesl@data[,c(2,4)], egg[,2]))

grid.arrange(gg, gt, ncol=2)

08 & 16 have unicode in them, hence the lack of display without conversion. I also realize the plotting of the RS number on the centroid is problematic for Berlin & Brandenburg, but it was to give a general idea, not be perfect.

I'd highly suggest using cut to define 5 or 6 standardized breaks for the values vs use a continuous scale.

This is a bit old, but since it is the best question about germany choropleth maps, I wanted to add a few things i learned while following @hrbrmstr's great answer.

As you can see in the map he plotted, Berlin is just getting the color of Brandenburg. To fix this, the order in the bundesl_map has to be edited, to make sure the Berlin (10) comes after Brandenburg (11). So the full processing of the map should look like this:

library(rgdal)
library(rgeos)
library(maptools)

bundesl <- readOGR("vg2500_geo84/vg2500_bld.shp", "vg2500_bld")
bundesl@data<- bundesl@data[order(bundesl$RS, na.last=NA),]
bundesl_map <- fortify(bundesl, region="RS")
bundesl_map <- rbind(
    bundesl_map[bundesl_map$id != 10, ], 
    bundesl_map[bundesl_map$id == 10, ]
)
saveRDS(bundesl_map, "bundesland")

In the last step we save the map for future use (bundesl_map <- readRDS("budesland")). Here is a copy of the file I created with named ids.

The plotting can also be made a bit more concise as follows:

library(magrittr)
library(ggplot2)
library(viridis)

egg %>% ggplot(aes(fill=Tariff, map_id=RS)) +
    geom_map(map=bundesl_map, color="white", size=0.2) + 
    geom_text(aes(x=x, y=y, label=egg$RS), size=2, color="white") +
    coord_map("mercator") +
    expand_limits(x=bundesl_map$long, y=bundesl_map$lat) +
    scale_fill_viridis(begin=0.4, end=0.9, breaks=-8:7, guide=guide_legend(reverse=T)) + 
    theme_map(base_size=8)

where theme_map is defined as:

theme_map <- function(...) {
    theme_classic(...) %+replace% 
    theme(
        axis.ticks = element_blank(), 
        axis.text = element_blank(),
        axis.title = element_blank(), 
        line=element_blank()
    )
}

This will yield a map like this: