title: Changing a continuous scale from decimal to percents
body: <p>The scale for penetration is listed as a decimal (.5 and down), but I am having a problem changing it to a percent.  </p>
  
  <p>I tried to format it in my data as a percentage using this code</p>
  
  <pre><code>penetration_levels$Penetration&lt;-sprintf("%.1f %%", 100*penetration_levels$Penetration)
  </code></pre>
  
  <p>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.  </p>
  
  <p>To fix that, used this code to format it as a numeric variable</p>
  
  <pre><code>penetration_levels$Penetration&lt;-as.numeric(as.character(penetration_levels$Penetration))
  </code></pre>
  
  <p>Which returned a bunch of <code>NA</code>s.  Does anyone know any other method of how I can change it to a percent?  </p>
  
  <p>Here is the code I used to map</p>
  
  <p>ggplot code:</p>
  
  <pre><code>map &lt;- 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 &lt;- 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 &lt;- map + theme(plot.title = element_text(size = 12,face="bold"))
  map
  </code></pre>
  
  <p>Head of mydata and penetration    </p>
  
  <pre><code>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
  </code></pre>
  
  
  
  <pre><code>head(penetration_levels)
  State  region      long      lat group order subregion state       To     From    Total    Penetration
  17    AL alabama -87.46201 30.38968     1     1      &lt;NA&gt;    AL 10794947 12537359 23332307    0.462661
  18    AL alabama -87.48493 30.37249     1     2      &lt;NA&gt;    AL 10794947 12537359 23332307    0.462661
  22    AL alabama -87.52503 30.37249     1     3      &lt;NA&gt;    AL 10794947 12537359 23332307    0.462661
  36    AL alabama -87.53076 30.33239     1     4      &lt;NA&gt;    AL 10794947 12537359 23332307    0.462661
  37    AL alabama -87.57087 30.32665     1     5      &lt;NA&gt;    AL 10794947 12537359 23332307    0.462661
  65    AL alabama -87.58806 30.32665     1     6      &lt;NA&gt;    AL 10794947 12537359 23332307    0.462661
  </code></pre>
  
  <p>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.</p>
  
  <p>Any insight would be greatly appreciated.  </p>
  
  <p><img src="https://i.imgur.com/FdFvlzR.png" alt="Map"></p>
  
  <p>Also, I noticed that Washington has a white polygon missing? Does anyone know why this happens? </p>