基于因子R的级别进行条件过滤 [英] Conditional filtering based on the level of a factor R

问题描述

我想清理以下代码。具体来说，我想知道是否可以整合三个过滤器语句，以便最终得到包含数据行spring的最终的data.frame（rind（）），如果存在，那么如果弹簧不存在，则最后一行数据不存在弹簧或跌落。下面的代码看起来很笨重，效率低下。我试图释放自己的（），所以希望解决方案不会涉及到一个。这可以使用dplyr吗？

I would like to clean up the following code. Specifically, I'm wondering if I can consolidate the three filter statements so that I end up with the final data.frame (the rind()) that contains the row of data "spring" if it exists, the row of data for "fall" if "spring" doesn't exist, and finally the row of data if neither "spring" nor "fall" exist. The code below seems very clunky and inefficient. I am trying to free myself of for(), so hopefully the solution won't involve one. Could this be done using dplyr?

# define a %not% to be the opposite of %in%
library(dplyr)
`%not%` <- Negate(`%in%`)
f <- c("a","a","a","b","b","c")
s <- c("fall","spring","other", "fall", "other", "other")
v <- c(3,5,1,4,5,2)
(dat0 <- data.frame(f, s, v))
sp.tmp <- filter(dat0, s == "spring")
fl.tmp <- filter(dat0, f %not% sp.tmp$f, s == "fall")
ot.tmp <- filter(dat0, f %not% sp.tmp$f, f %not% fl.tmp$f, s == "other")
rbind(sp.tmp,fl.tmp,ot.tmp)

推荐答案

看起来像每组 f ，您要按照优先级顺序从 spring ， fall 或其他。

It looks like within each group of f, you want to extract the row of, in descending order of preference, spring, fall, or other.

如果您首先按照您的优先顺序排序实际的因素：

If you first make your ordering of preference the actual factor ordering:

dat0$s <- factor(dat0$s, levels=c("spring", "fall", "other"))

然后，您可以使用此dplyr解决方案获取最小行（相对于该因子）：

Then you can use this dplyr solution to get the minimum row (relative to that factor) within each group:

newdat <- dat0 %.% group_by(f) %.% filter(rank(s) == 1)

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