R根据if-else语句选择行
基于if-else条件限制数据集时遇到问题 这是我的数据帧的一个示例:R根据if-else语句选择行,r,if-statement,dataframe,subset,plyr,R,If Statement,Dataframe,Subset,Plyr,基于if-else条件限制数据集时遇到问题 这是我的数据帧的一个示例: mydf<-data.frame(chemical=c("Cd","Cd","Cd","Cd","Pb","Pb"),species=c("a","a","a","a","b","d"),scores=c(0,1,2,3,0,0)) 结束表应如下所示: chemical species scores 1 Cd a 1 2 Pb b 0 3
mydf<-data.frame(chemical=c("Cd","Cd","Cd","Cd","Pb","Pb"),species=c("a","a","a","a","b","d"),scores=c(0,1,2,3,0,0))
结束表应如下所示:
chemical species scores
1 Cd a 1
2 Pb b 0
3 Pb d 0
这里使用OP的原始逻辑的可行解决方案,可能不是最优雅的代码 plyr
ddply(mydf,.(chemical,species),
function(x) x[if(any(x$scores != 0)) {which.min(replace(x$scores, x$scores == 0, NA))} else which(x$scores == 0),])
mydf %>%
group_by(chemical, species) %>%
do(.[if(any(.$scores != 0)) {which.min(replace(.$scores, .$scores == 0, NA))} else which(.$scores == 0),])
dplyr
ddply(mydf,.(chemical,species),
function(x) x[if(any(x$scores != 0)) {which.min(replace(x$scores, x$scores == 0, NA))} else which(x$scores == 0),])
mydf %>%
group_by(chemical, species) %>%
do(.[if(any(.$scores != 0)) {which.min(replace(.$scores, .$scores == 0, NA))} else which(.$scores == 0),])
Ifelse逻辑解包
# If none of the values are equal to 0
if(any(.$scores != 0))
# Find the index of the smallest values from a vector where 0 has been replaced by NA
{which.min(replace(.$scores, .$scores == 0, NA))}
# Else find index of value equal to 0
else which(.$scores == 0)
这里使用OP的原始逻辑的可行解决方案,可能不是最优雅的代码 plyr
ddply(mydf,.(chemical,species),
function(x) x[if(any(x$scores != 0)) {which.min(replace(x$scores, x$scores == 0, NA))} else which(x$scores == 0),])
mydf %>%
group_by(chemical, species) %>%
do(.[if(any(.$scores != 0)) {which.min(replace(.$scores, .$scores == 0, NA))} else which(.$scores == 0),])
dplyr
ddply(mydf,.(chemical,species),
function(x) x[if(any(x$scores != 0)) {which.min(replace(x$scores, x$scores == 0, NA))} else which(x$scores == 0),])
mydf %>%
group_by(chemical, species) %>%
do(.[if(any(.$scores != 0)) {which.min(replace(.$scores, .$scores == 0, NA))} else which(.$scores == 0),])
Ifelse逻辑解包
# If none of the values are equal to 0
if(any(.$scores != 0))
# Find the index of the smallest values from a vector where 0 has been replaced by NA
{which.min(replace(.$scores, .$scores == 0, NA))}
# Else find index of value equal to 0
else which(.$scores == 0)
这将实现您想要的:
library(tidyverse)
mydf %>%
group_by(chemical, species) %>%
mutate(zero = if_else(condition = max(scores)==0, true = TRUE, false = FALSE)) %>%
filter(scores==0&zero==TRUE|scores>0&zero==FALSE) %>%
arrange(chemical, species, scores) %>%
distinct(chemical, species, .keep_all = TRUE) %>%
select(-zero)
这将实现您想要的:
library(tidyverse)
mydf %>%
group_by(chemical, species) %>%
mutate(zero = if_else(condition = max(scores)==0, true = TRUE, false = FALSE)) %>%
filter(scores==0&zero==TRUE|scores>0&zero==FALSE) %>%
arrange(chemical, species, scores) %>%
distinct(chemical, species, .keep_all = TRUE) %>%
select(-zero)
我不知道这是否更快,但只是为了好玩,你也可以这样做
mydf %>%
group_by(chemical, species) %>%
summarize(scores = min(max(scores, 0)))
我不知道这是否更快,但只是为了好玩,你也可以这样做
mydf %>%
group_by(chemical, species) %>%
summarize(scores = min(max(scores, 0)))