将连续刻度从十进制更改为百分比 [英] Changing a continuous scale from decimal to percents
问题描述
渗透率的等级以小数点表示(.5及以下)，但将其更改为百分比时遇到问题.
The scale for penetration is listed as a decimal (.5 and down), but I am having a problem changing it to a percent.
我尝试使用此代码将其格式化为百分比格式的数据
I tried to format it in my data as a percentage using this code
penetration_levels$Penetration<-sprintf("%.1f %%", 100*penetration_levels$Penetration)
从格式的角度来看是可行的，但是当我尝试绘制曲线图时，出现了一个错误，说渗透被用作离散的而不是连续的比例.
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.
要解决此问题，请使用此代码将其格式化为数字变量
To fix that, used this code to format it as a numeric variable
penetration_levels$Penetration<-as.numeric(as.character(penetration_levels$Penetration))
哪个返回了一堆NA.有人知道我如何将其更改为百分比的任何其他方法吗?
Which returned a bunch of NAs. Does anyone know any other method of how I can change it to a percent?
这是我用来映射的代码
ggplot代码:
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
mydata和渗透的负责人
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
我还刚刚注意到，有一条白色的条带，类似于华盛顿缺少的一个多边形……您碰巧知道为什么吗?我试图重新合并数据并再次对其进行排序，但结果仍然相同.
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.
任何见识将不胜感激.
Any insight would be greatly appreciated.
我还注意到华盛顿缺少一个白色的多边形吗?有谁知道为什么会这样吗?
Also, I noticed that Washington has a white polygon missing? Does anyone know why this happens?
推荐答案
您可以加载scales软件包并使用scale_fill_continuous(labels = percent).在帮助文本的参数部分中，百分比参数的记录不是很好，但是可以在示例部分
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.
一个小例子:
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)
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