假设我想使用按医院和县显示程序价格的医院医疗保险数据，我的数据框被称为 df，列有价格、程序和县。如果我想按县查找每个程序的最低和最高价格，我可以这样
library(plyr)
mostexpensive <- ddply(df,c('county','procedure'),function(x)x[which(x$price==max(x$price)),])
获得一张表格，显示每个县中手术费用最高的医院。然后我可以看到每家医院被列出了多少次
summary(mostexpensive$hospital)
对于最后一步，我想在原始 df 数据框中添加一列，如果该行最昂贵，则为 TRUE，否则为 FALSE，但我无法弄清楚如何从 plyr 函数中获取逻辑向量。谢谢。
Posting reproducible code would be useful. Try this anyway,
For the summary
pricey <- ddply(df, c('county','procedure'), summarise, most = max(price), less=min(price))
and for the logical indexing
testing <- ddply(df, c('county','procedure'), mutate, expensive = price == max(price))
It will be more easier to get an answer with a reproductible example. You should think about it, next time you as for help in SO.
That being said, you can use the transform function to add a new column to your existing data.
The first step is to create a toy data set.
set.seed(123)
df <- data.frame(
county = sample(LETTERS[1:3], size = 20, replace = TRUE),
procedure = sample(c(1, 2), size = 20, replace = TRUE),
price = rpois(20, 10)
)
str(df)
## 'data.frame': 20 obs. of 3 variables:
## $ county : Factor w/ 3 levels "A","B","C": 1 3 2 3 3 1 2 3 2 2 ...
## $ procedure: num 2 2 2 2 2 2 2 2 1 1 ...
## $ price : int 6 8 6 8 4 6 6 8 5 12 ...
Now we can use plyr and the transform function
require(plyr)
expensive <- ddply(df, .(county, procedure),
transform, ismax = price == max(price))
expensive
## county procedure price ismax
## 1 A 1 9 FALSE
## 2 A 1 7 FALSE
## 3 A 1 12 TRUE
## 4 A 2 6 FALSE
## 5 A 2 6 FALSE
## 6 A 2 8 TRUE
## 7 B 1 5 FALSE
## 8 B 1 12 TRUE
## 9 B 2 6 FALSE
## 10 B 2 6 FALSE
## 11 B 2 12 TRUE
## 12 B 2 11 FALSE
## 13 C 1 9 TRUE
## 14 C 1 9 TRUE
## 15 C 2 8 FALSE
## 16 C 2 8 FALSE
## 17 C 2 4 FALSE
## 18 C 2 8 FALSE
## 19 C 2 12 TRUE
## 20 C 2 12 TRUE