基于边远计数的子集数据帧

Question

我有一个如下所示的数据框:

df <- data.frame(Site=rep(paste0('site', 1:5), 50),
           Month=sample(1:12, 50, replace=T),
           Count=(sample(1:1000, 50, replace=T)))

我想删除所有网站上计数总是<每月最大月数的5%的网站.

所有网站的最高月度计数为:

library(plyr)
ddply(df, .(Month), summarise, Max.Count=max(Count))

如果将1的计数分配给site5,则其计数始终<所有站点的最大月计数的5%.因此我希望删除site5.

df$Count[df$Site=='site5'] <- 1

但是,在为site2分配新值后,其中一些计数<最大月度计数的5%,而其他计数> 5%.因此我不希望删除site2.

df$Count[df$Site=='site2'] <- ceiling(seq(1, 1000, length.out=20))

如何将数据框子集化以删除计数总是<每月最大计数的5%的任何网站？如果问题不清楚,请告诉我,我会修改.

Answer 1

一个data.table解决方案:

require(data.table)
set.seed(45)
df <- data.frame(Site=rep(paste0('site', 1:5), 50),
       Month=sample(1:12, 50, replace=T),
       Count=(sample(1:1000, 50, replace=T)))
df$Count[df$Site=='site5'] <- 1

dt <- data.table(df, key=c("Month", "Site"))
# set max.count per site+month
dt[, max.count := max(Count), by = list(Month)]
# get the site that is TRUE for all months it is present
d1 <- dt[, list(check = all(Count < .05 * max.count)), by = list(Month, Site)]
sites <- as.character(d1[, all(check == TRUE), by=Site][V1 == TRUE, Site])

dt.out <- dt[Site != sites][, max.count := NULL]
#       Site Month Count
#   1: site1     1   939
#   2: site1     1   939
#   3: site1     1   939
#   4: site1     1   939
#   5: site1     1   939
#  ---                  
# 196: site2    12   969
# 197: site2    12   684
# 198: site2    12   613
# 199: site2    12   969
# 200: site2    12   684

Answer 2

这是一个plyr解决方案：

## df2$test is true if Count >= max(Count)*0.05 for this month
df2 <- ddply(df, .(Month), transform, test=Count>=(max(Count)*0.05))
## For each site, test$keep is true if at least one count is >= max(Count)*0.05 for this month
test <- ddply(df2, .(Site), summarise, keep=sum(test)>0)
## Subsetting
sites <- test$Site[test$keep]
df[df$Site %in% sites,]