在dataframe中提取每個(gè)組內(nèi)的最大值我有一個(gè)具有分組變量(“Gene”)和一個(gè)值變量(“value”)的數(shù)據(jù)框架：Gene Value
A 12A 10B 3B 5B 6C 1D 3D 4對(duì)于分組變量的每個(gè)級(jí)別，我希望提取最大值。因此，結(jié)果應(yīng)該是一個(gè)數(shù)據(jù)幀，每級(jí)分組變量有一行：Gene Value
A 12B 6C 1D 4能aggregate玩這個(gè)把戲？
3 回答
飲歌長嘯
TA貢獻(xiàn)1951條經(jīng)驗(yàn) 獲得超3個(gè)贊
在R中有很多這樣做的可能性，以下是其中的一些：
df <- read.table(header = TRUE, text = 'Gene Value
A 12
A 10
B 3
B 5
B 6
C 1
D 3
D 4')
# aggregate
aggregate(df$Value, by = list(df$Gene), max)
aggregate(Value ~ Gene, data = df, max)
# tapply
tapply(df$Value, df$Gene, max)
# split + lapply
lapply(split(df, df$Gene), function(y) max(y$Value))
# plyr
require(plyr)
ddply(df, .(Gene), summarise, Value = max(Value))
# dplyr
require(dplyr)
df %>% group_by(Gene) %>% summarise(Value = max(Value))
# data.table
require(data.table)
dt <- data.table(df)
dt[ , max(Value), by = Gene]
# doBy
require(doBy)
summaryBy(Value~Gene, data = df, FUN = max)
# sqldf
require(sqldf)
sqldf("select Gene, max(Value) as Value from df group by Gene", drv = 'SQLite')
# ave
df[as.logical(ave(df$Value, df$Gene, FUN = function(x) x == max(x))),]
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