Changing a continuous scale from decimal to percen

The scale for penetration is listed as a decimal (.5 and down), but I am having a problem changing it to a percent.

I tried to format it in my data as a percentage using this code

penetration_levels$Penetration<-sprintf("%.1f %%", 100*penetration_levels$Penetration)

which worked from a format sense, but when I tried to graph the plot I got an error saying penetration was used as a discrete, not continuous scale.

To fix that, used this code to format it as a numeric variable

penetration_levels$Penetration<-as.numeric(as.character(penetration_levels$Penetration))

Which returned a bunch of NAs. Does anyone know any other method of how I can change it to a percent?

Here is the code I used to map

ggplot code:

map <- ggplot(penetration_levels,aes(long,lat,group=region,fill=Penetration),) + geom_polygon() + coord _equal() + scale_fill_gradient2(low="red",mid="white",high="green",midpoint=.25)
map <- map + geom_point(data=mydata, aes(x=long, y=lat,group=1,fill=0, size=Annualized.Opportunity), color="gray6") + scale_size(name="Total Annual Opportunity-Millions",range=c(2,4))  
map <- map + theme(plot.title = element_text(size = 12,face="bold"))
map

Head of mydata and penetration

head(mydata)
Sold.To.Customer            City State Annualized.Opportunity           location          lat      long
21          10000110        NEW YORK    NY              12.142579        NEW YORK,NY     40.71435 -74.00597
262         10016487 FORT LAUDERDALE    FL              12.087310 FORT LAUDERDALE,FL 26.12244 -80.13732
349         11001422      ALLEN PARK    MI              10.910575      ALLEN PARK,MI 42.25754 -83.21104
19          10000096           ALTON    IL              10.040067           ALTON,IL 38.89060 -90.18428
477         11067228        BAY CITY    TX              10.030829        BAY CITY,TX 28.98276 -95.96940
230         10014909        BETHPAGE    NY               9.320271        BETHPAGE,NY 40.74427 -73.48207

head(penetration_levels)
State  region      long      lat group order subregion state       To     From    Total    Penetration
17    AL alabama -87.46201 30.38968     1     1      <NA>    AL 10794947 12537359 23332307    0.462661
18    AL alabama -87.48493 30.37249     1     2      <NA>    AL 10794947 12537359 23332307    0.462661
22    AL alabama -87.52503 30.37249     1     3      <NA>    AL 10794947 12537359 23332307    0.462661
36    AL alabama -87.53076 30.33239     1     4      <NA>    AL 10794947 12537359 23332307    0.462661
37    AL alabama -87.57087 30.32665     1     5      <NA>    AL 10794947 12537359 23332307    0.462661
65    AL alabama -87.58806 30.32665     1     6      <NA>    AL 10794947 12537359 23332307    0.462661

I also just noticed that there was a white strip, similar to a polygon that is missing in Washington… do you happen to know why that is? I tried to re-merge my data and order it again, but still the same result.

Any insight would be greatly appreciated.

Also, I noticed that Washington has a white polygon missing? Does anyone know why this happens?

You may load the scales package and use scale_fill_continuous(labels = percent). The percent argument is not very well documented in the argument section of the help text, but an example of this function, and other convenient formats from the scales package, can be found in the example section here.

A small example:

library(scales)

df <- data.frame(long = 1:10, lat = 1:10,
                 penetration = seq(from = 0.1, to = 1, by = 0.1))

ggplot(data = df, aes(x = long, y = lat, fill = penetration)) +
  geom_point(shape = 21, size = 6) +
  scale_fill_continuous(labels = percent)